SwePub
Sök i SwePub databas

  Extended search

Träfflista för sökning "L773:2169 3536 OR L773:2169 3536 "

Search: L773:2169 3536 OR L773:2169 3536

  • Result 1-50 of 700
Sort/group result
   
EnumerationReferenceCoverFind
1.
  • Abbas, Muhammad Tahir, et al. (author)
  • Energy-Saving Solutions for Cellular Internet of Things - A Survey
  • 2022
  • In: IEEE Access. - IEEE : IEEE. - 2169-3536. ; 10, s. 62096-62096
  • Journal article (peer-reviewed)abstract
    • The Cellular Internet of Things (CIoT), a new paradigm, paves the way for a large-scale deployment of IoT devices. CIoT promises enhanced coverage and massive deployment of low-cost IoT devices with an expected battery life of up to 10 years. However, such a long battery life can only be achieved provided the CIoT device is configured with energy efficiency in mind. This paper conducts a comprehensive survey on energy-saving solutions in 3GPP-based CIoT networks. In comparison to current studies, the contribution of this paper is the classification and an extensive analysis of existing energy-saving solutions for CIoT, e.g., the configuration of particular parameter values and software modifications of transport- or radio-layer protocols, while also stressing key parameters impacting the energy consumption such as the frequency of data reporting, discontinuous reception cycles (DRX), and Radio Resource Control (RRC) timers. In addition, we discuss shortcomings, limitations, and possible opportunities which can be investigated in the future to reduce the energy consumption of CIoT devices.
  •  
2.
  • Abourraja, Mohamed Nezar, et al. (author)
  • A multi-agent based simulation model for rail–rail transshipment : An engineering approach for gantry crane scheduling
  • 2017
  • In: IEEE Access. - : IEEE Press. - 2169-3536. ; 5, s. 13142-13156
  • Journal article (peer-reviewed)abstract
    • Le Havre Port Authority is putting into service a multimodal hub terminal with massified hinterland links (trains and barges) in order to restrict the intensive use of roads, to achieve a more attractive massification share of hinterland transportation and to provide a river connection to its maritime terminals that do not currently have one. This paper focuses on the rail-rail transshipment yard of this new terminal. In the current organizational policy, this yard is divided into two equal operating areas, and, in each one, a crane is placed, and it is equipped with reach stackers to enable container moves across both operating areas. However, this policy causes poor scheduling of crane moves, because it gives rise to many crane interference situations. For the sake of minimizing the occurrence of these undesirable situations, this paper proposes a multi-agent simulation model including an improved strategy for crane scheduling. This strategy is inspired by the ant colony approach and it is governed by a new configuration for the rail yard's working area that eliminates the use of reach stackers. The proposed simulation model is based on two planner agents, to each of which a time-horizon planning is assigned. The simulation results show that the model developed here is very successful in significantly reducing unproductive times and moves (undesirable situations), and it outperforms other existing simulation models based on the current organizational policy.
  •  
3.
  • Abuella, Mohamed, Postdoktor, 1980-, et al. (author)
  • Spatial Clustering Approach for Vessel Path Identification
  • 2024
  • In: IEEE Access. - Piscataway, NJ : IEEE. - 2169-3536. ; 12, s. 66248-66258
  • Journal article (peer-reviewed)abstract
    • This paper addresses the challenge of identifying the paths for vessels with operating routes of repetitive paths, partially repetitive paths, and new paths. We propose a spatial clustering approach for labeling the vessel paths by using only position information. We develop a path clustering framework employing two methods: a distance-based path modeling and a likelihood estimation method. The former enhances the accuracy of path clustering through the integration of unsupervised machine learning techniques, while the latter focuses on likelihood-based path modeling and introduces segmentation for a more detailed analysis. The result findings highlight the superior performance and efficiency of the developed approach, as both methods for clustering vessel paths into five clusters achieve a perfect F1-score. The approach aims to offer valuable insights for route planning, ultimately contributing to improving safety and efficiency in maritime transportation. © 2013 IEEE.
  •  
4.
  • Afzal, Wasif, et al. (author)
  • On using grey literature and google scholar in systematic literature reviews in software engineering
  • 2020
  • In: IEEE Access. - United States. - 2169-3536. ; 8, s. 36226-36243
  • Journal article (peer-reviewed)abstract
    • © 2013 IEEE. Context: The inclusion of grey literature (GL) is important to remove publication bias while gathering available evidence regarding a certain topic. The number of systematic literature reviews (SLRs) in Software Engineering (SE) is increasing but we do not know about the extent of GL usage in these SLRs. Moreover, Google Scholar is rapidly becoming a search engine of choice for many researchers but the extent to which it can find the primary studies is not known. Objective: This tertiary study is an attempt to i) measure the usage of GL in SLRs in SE. Furthermore this study proposes strategies for categorizing GL and a quality checklist to use for GL in future SLRs; ii) explore if it is feasible to use only Google Scholar for finding scholarly articles for academic research. Method: We have conducted a systematic mapping study to measure the extent of GL usage in SE SLRs as well as to measure the feasibility of finding primary studies using Google Scholar. Results and conclusions: a) Grey Literature: 76.09% SLRs (105 out of 138) in SE have included one or more GL studies as primary studies. Among total primary studies across all SLRs (6307), 582 are classified as GL, making the frequency of GL citing as 9.23%. The intensity of GL use indicate that each SLR contains 5 primary studies on average (total intensity of GL use being 5.54). The ranking of GL tells us that conference papers are the most used form 43.3% followed by technical reports 28.52%. Universities, research institutes, labs and scientific societies together make up 67.7% of GL used, indicating that these are useful sources for searching GL. We additionally propose strategies for categorizing GL and criteria for evaluating GL quality, which can become a basis for more detailed guidelines for including GL in future SLRs. b) Google Scholar Results: The results show that Google Scholar was able to retrieve 96% of primary studies of these SLRs. Most of the primary studies that were not found using Google Scholar were from grey sources.
  •  
5.
  • Ahmad, Ijaz, et al. (author)
  • Machine Learning Meets Communication Networks: Current Trends and Future Challenges
  • 2020
  • In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 8, s. 223418-223460
  • Journal article (peer-reviewed)abstract
    • The growing network density and unprecedented increase in network traffic, caused by the massively expanding number of connected devices and online services, require intelligent network operations. Machine Learning (ML) has been applied in this regard in different types of networks and networking technologies to meet the requirements of future communicating devices and services. In this article, we provide a detailed account of current research on the application of ML in communication networks and shed light on future research challenges. Research on the application of ML in communication networks is described in: i) the three layers, i.e., physical, access, and network layers; and ii) novel computing and networking concepts such as Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Functions Virtualization (NFV), and a brief overview of ML-based network security. Important future research challenges are identified and presented to help stir further research in key areas in this direction.
  •  
6.
  • Ahmad, Ijaz, et al. (author)
  • Security of Satellite-Terrestrial Communications : Challenges and Potential Solutions
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 96038-96052
  • Journal article (peer-reviewed)abstract
    • The integration of satellite and terrestrial networks has become inevitable in the next generations of communications networks due to emerging needs of ubiquitous connectivity of remote locations. New and existing services and critical infrastructures in remote locations in sea, on land and in space will be seamlessly connected through a diverse set of terrestrial and non-terrestrial communication technologies. However, the integration of terrestrial and non-terrestrial systems will open up both systems to unique security challenges that can arise due to the migration of security challenges from one to another. Similarly, security challenges can also arise due to the incompatibility of distinct systems or incoherence of security policies. The resulting security implications, thus, can be highly consequential due to the criticality of the infrastructures such as space stations, autonomous ships, and airplanes, for instance. Therefore, in this article we study existing security challenges in satellite-terrestrial communication systems and discuss potential solutions for those challenges. Furthermore, we provide important research directions to encourage future research on existing security gaps.
  •  
7.
  • Ahmad, Muhammad Ovais, Senior Lecturer (author)
  • On the Efficiency of Supernodal Factorization in Interior-Point Method Using CPU-GPU Collaboration
  • 2020
  • In: IEEE Access. - : IEEE Computer Society Digital Library. - 2169-3536. ; 8, s. 120892-120904
  • Journal article (peer-reviewed)abstract
    • Primal-dual interior-point method (PDIPM) is the most efficient technique for solving sparse linear programming (LP) problems. Despite its efficiency, PDIPM remains a compute-intensive algorithm. Fortunately, graphics processing units (GPUs) have the potential to meet this requirement. However, their peculiar architecture entails a positive relationship between problem density and speedup, conversely implying a limited affinity of GPUs for problem sparsity. To overcome this difficulty, the state-of-the-art hybrid (CPU-GPU) implementation of PDIPM exploits presence of supernodes in sparse matrices during factorization. Supernodes are groups of similar columns that can be treated as dense submatrices. Factorization method used in the state-of-the-art solver performs only selected operations related to large supernodes on GPU. This method is known to underutilize GPU’s computational power while increasing CPU-GPU communication overhead. These shortcomings encouraged us to adapt another factorization method, which processes sets of related supernodes on GPU, and introduce it to the PDIPM implementation of a popular open-source solver. Our adaptation enabled the factorization method to better mitigate the effects of round-off errors accumulated over multiple iterations of PDIPM. To augment performance gains, we also used an efficient CPU-based matrix multiplication method. When tested for a set of well-known sparse problems, the adapted solver showed average speed-ups of approximately 55X, 1.14X and 1.05X over the open-source solver’s original version, the state-of-the-art solver, and a highly optimized proprietary solver known as CPLEX, respectively. These results strongly indicate that our proposed hybrid approach can lead to significant performance gains for solving large sparse problems.
  •  
8.
  • Ahmad, Sarosh, et al. (author)
  • A Compact CPW-Fed Ultra-Wideband Multi-Input-Multi-Output (MIMO) Antenna for Wireless Communication Networks
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 25278-25289
  • Journal article (peer-reviewed)abstract
    • In this article, a compact coplanar waveguide (CPW) technique based ultra-wideband multiple-input-multiple-output (MIMO) antenna is proposed. The design is characterized by a broad impedance bandwidth starting from 3 GHz to 11 GHz. The overall size of the MIMO design is 60 x 60 mm(2) (1.24 x 1.24 lambda(2)(g) @ 3 GHz) with a thickness of 1.6 mm. To make the design ultra-wideband, the proposed MIMO antenna design has four jug-shaped radiating elements. The design is printed on a FR-4 substrate (relative permittivity of epsilon(r) = 4.4 and loss tangent of tan delta = 0.025). The polarization diversity phenomenon is realized by placing four antenna elements orthogonally. This arrangement increases the isolation among the MIMO antenna elements. The simulated results of the ultra-wideband MIMO antenna are verified by measured results. The proposed MIMO antenna has a measured diversity gain greater than 9.98, envelope correlation coefficient (ECC) less than 0.02, and good MIMO performance where the isolation is more than -20dB between the elements. The group delay, channel capacity loss (CCL), and the total active reflection coefficient (TARC) multiplexing efficiency and mean effective gain results are also analyzed. The group delay is found to be less than 1.2ns, CCL values calculated to be less than 0.4 bits/sec/Hz, while the TARC is below -10dB for the whole operating spectrum. The proposed design is a perfect candidate for ultra-wideband wireless communication systems and portable devices.
  •  
9.
  • Ahmad, Waqas, et al. (author)
  • Computationally Efficient Light Field Image Compression Using a Multiview HEVC Framework
  • 2019
  • In: IEEE Access. - 2169-3536. ; 7, s. 143002-143014
  • Journal article (peer-reviewed)abstract
    • The acquisition of the spatial and angular information of a scene using light eld (LF) technologies supplement a wide range of post-processing applications, such as scene reconstruction, refocusing, virtual view synthesis, and so forth. The additional angular information possessed by LF data increases the size of the overall data captured while offering the same spatial resolution. The main contributor to the size of captured data (i.e., angular information) contains a high correlation that is exploited by state-of-the-art video encoders by treating the LF as a pseudo video sequence (PVS). The interpretation of LF as a single PVS restricts the encoding scheme to only utilize a single-dimensional angular correlation present in the LF data. In this paper, we present an LF compression framework that efciently exploits the spatial and angular correlation using a multiview extension of high-efciency video coding (MV-HEVC). The input LF views are converted into multiple PVSs and are organized hierarchically. The rate-allocation scheme takes into account the assigned organization of frames and distributes quality/bits among them accordingly. Subsequently, the reference picture selection scheme prioritizes the reference frames based on the assigned quality. The proposed compression scheme is evaluated by following the common test conditions set by JPEG Pleno. The proposed scheme performs 0.75 dB better compared to state-of-the-art compression schemes and 2.5 dB better compared to the x265-based JPEG Pleno anchor scheme. Moreover, an optimized motionsearch scheme is proposed in the framework that reduces the computational complexity (in terms of the sum of absolute difference [SAD] computations) of motion estimation by up to 87% with a negligible loss in visual quality (approximately 0.05 dB).
  •  
10.
  • Ahmed, Bestoun S., 1982-, et al. (author)
  • Aspects of Quality in Internet of Things (IoT) Solutions : A Systematic Mapping Study
  • 2019
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 7, s. 13758-13780
  • Journal article (peer-reviewed)abstract
    • Internet of Things (IoT) is an emerging technology that has the promising power to change our future. Due to the market pressure, IoT systems may be released without sufficient testing. However, it is no longer acceptable to release IoT systems to the market without assuring the quality. As in the case of new technologies, the quality assurance process is a challenging task. This paper shows the results of the first comprehensive and systematic mapping study to structure and categories the research evidence in the literature starting in 2009 when the early publication of IoT papers for IoT quality assurance appeared. The conducted research is based on the most recent guidelines on how to perform systematic mapping studies. A set of research questions is defined carefully regarding the quality aspects of the IoT. Based on these questions, a large number of evidence and research papers is considered in the study (478 papers). We have extracted and analyzed different levels of information from those considered papers. Also, we have classified the topics addressed in those papers into categories based on the quality aspects. The study results carry out different areas that require more work and investigation in the context of IoT quality assurance. The results of the study can help in a further understanding of the research gaps. Moreover, the results show a roadmap for future research directions.
  •  
11.
  • Ahmed, Bestoun S., 1982-, et al. (author)
  • Constrained interaction testing : A systematic literature study
  • 2017
  • In: IEEE Access. - Sweden : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 5, s. 25706-25730
  • Journal article (peer-reviewed)abstract
    • Interaction testing can be used to effectively detect faults that are otherwise difficult to find by other testing techniques. However, in practice, the input configurations of software systems are subjected to constraints, especially in the case of highly configurable systems. Handling constraints effectively and efficiently in combinatorial interaction testing is a challenging problem. Nevertheless, researchers have attacked this challenge through different techniques, and much progress has been achieved in the past decade. Thus, it is useful to reflect on the current achievements and shortcomings and to identify potential areas of improvements. This paper presents the first comprehensive and systematic literature study to structure and categorize the research contributions for constrained interaction testing. Following the guidelines of conducting a literature study, the relevant data are extracted from a set of 103 research papers belonging to constrained interaction testing. The topics addressed in constrained interaction testing research are classified into four categories of constraint test generation, application, generation and application, and model validation studies. The papers within each of these categories are extensively reviewed. Apart from answering several other research questions, this paper also discusses the applications of constrained interaction testing in several domains, such as software product lines, fault detection and characterization, test selection, security, and graphical user interface testing. This paper ends with a discussion of limitations, challenges, and future work in the area.
  •  
12.
  • Ahmed, Kazi Main Uddin, 1989-, et al. (author)
  • A Novel Reliability Index to Assess the Computational Resource Adequacy in Data Centers
  • 2021
  • In: IEEE Access. - NY : IEEE. - 2169-3536. ; 9, s. 54530-54541
  • Journal article (peer-reviewed)abstract
    • The energy demand of data centers is increasing globally with the increasing demand for computational resources to ensure the quality of services. It is important to quantify the required resources to comply with the computational workloads at the rack-level. In this paper, a novel reliability index called loss of workload probability is presented to quantify the rack-level computational resource adequacy. The index defines the right-sizing of the rack-level computational resources that comply with the computational workloads, and the desired reliability level of the data center investor. The outage probability of the power supply units and the workload duration curve of servers are analyzed to define the loss of workload probability. The workload duration curve of the rack, hence, the power consumption of the servers is modeled as a function of server workloads. The server workloads are taken from a publicly available data set published by Google. The power consumption models of the major components of the internal power supply system are also presented which shows the power loss of the power distribution unit is the highest compared to the other components in the internal power supply system. The proposed reliability index and the power loss analysis could be used for rack-level computational resources expansion planning and ensures energy-efficient operation of the data center.
  •  
13.
  • Ahmed, Kazi Main Uddin, 1989-, et al. (author)
  • A Review of Data Centers Energy Consumption And Reliability Modeling
  • 2021
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 9
  • Research review (peer-reviewed)abstract
    • Enhancing the efficiency and the reliability of the data center are the technical challenges for maintaining the quality of services for the end-users in the data center operation. The energy consumption models of the data center components are pivotal for ensuring the optimal design of the internal facilities and limiting the energy consumption of the data center. The reliability modeling of the data center is also important since the end-user’s satisfaction depends on the availability of the data center services. In this review, the state-of-the-art and the research gaps of data center energy consumption and reliability modeling are identified, which could be beneficial for future research on data center design, planning, and operation. The energy consumption models of the data center components in major load sections i.e., information technology (IT), internal power conditioning system (IPCS), and cooling load section are systematically reviewed and classified, which reveals the advantages and disadvantages of the models for different applications. Based on this analysis and related findings it is concluded that the availability of the model parameters and variables are more important than the accuracy, and the energy consumption models are often necessary for data center reliability studies. Additionally, the lack of research on the IPCS consumption modeling is identified, while the IPCS power losses could cause reliability issues and should be considered with importance for designing the data center. The absence of a review on data center reliability analysis is identified that leads this paper to review the data center reliability assessment aspects, which is needed for ensuring the adaptation of new technologies and equipment in the data center. The state-of-the-art of the reliability indices, reliability models, and methodologies are systematically reviewed in this paper for the first time, where the methodologies are divided into two groups i.e., analytical and simulation-based approaches. There is a lack of research on the data center cooling section reliability analysis and the data center components’ failure data, which are identified as research gaps. In addition, the dependency of different load sections for reliability analysis of the data center is also included that shows the service reliability of the data center is impacted by the IPCS and the cooling section.
  •  
14.
  • Ait-Mlouk, Addi, et al. (author)
  • KBot : a Knowledge graph based chatBot for natural language understanding over linked data
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 149220-149230
  • Journal article (peer-reviewed)abstract
    • With the rapid progress of the semantic web, a huge amount of structured data has become available on the web in the form of knowledge bases (KBs). Making these data accessible and useful for end-users is one of the main objectives of chatbots over linked data. Building a chatbot over linked data raises different challenges, including user queries understanding, multiple knowledge base support, and multilingual aspect. To address these challenges, we first design and develop an architecture to provide an interactive user interface. Secondly, we propose a machine learning approach based on intent classification and natural language understanding to understand user intents and generate SPARQL queries. We especially process a new social network dataset (i.e., myPersonality) and add it to the existing knowledge bases to extend the chatbot capabilities by understanding analytical queries. The system can be extended with a new domain on-demand, flexible, multiple knowledge base, multilingual, and allows intuitive creation and execution of different tasks for an extensive range of topics. Furthermore, evaluation and application cases in the chatbot are provided to show how it facilitates interactive semantic data towards different real application scenarios and showcase the proposed approach for a knowledge graph and data-driven chatbot.
  •  
15.
  • Akbarian, Fatemeh, et al. (author)
  • Attack Resilient Cloud-Based Control Systems for Industry 4.0
  • 2023
  • In: IEEE Access. - 2169-3536. ; 11, s. 27865-27882
  • Journal article (peer-reviewed)abstract
    • In recent years, since the cloud can provide tremendous advantages regarding storage and computing resources, the industry has been motivated to move industrial control systems to the cloud. However, the cloud also introduces significant security challenges since moving control systems to the cloud can enable attackers to infiltrate the system and establish an attack that can lead to damages and disruptions with potentially catastrophic consequences. Therefore, some security measures are necessary to detect these attacks in a timely manner and mitigate their impact. In this paper, we propose a security framework for cloud control systems that makes them resilient against attacks. This framework includes three steps: attack detection, attack isolation, and attack mitigation. We validate our proposed framework on a real testbed and evaluate its capability by subjecting it to a set of attacks. We show that our proposed solution can detect an attack in a timely manner and keep the plant stable, with high performance during the attack.
  •  
16.
  • Akil, Mahdi, et al. (author)
  • Privacy-Preserving Identifiers for IoT : A Systematic Literature Review
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 168470-168485
  • Research review (peer-reviewed)abstract
    • The Internet of Things (IoT) paves the way for smart applications such as in E-health, E-homes, transportation, or energy production. However, IoT technologies also pose privacy challenges for their users, as they allow the tracking and monitoring of the users' behavior and context. The EU General Data Protection Regulation (GDPR) mandates data controller to follow a data protection by design and default approach by implementing for instance pseudonymity for achieving data minimisation. This paper provides a systematic literature review for answering the question of what types of privacy-preserving identifiers are proposed by the literature in IoT environments for implementing pseudonymity. It contributes with classifications and analyses of IoT environments for which privacy-preserving identifiers have been proposed and of the pseudonym types and underlying identity management architectures used. Moreover, it discusses trends and gaps in regard to addressing privacy trade-offs.
  •  
17.
  • Akram, Shazad, et al. (author)
  • Design and Development of a Battery Powered Electrofusion Welding System for Optical Fiber Microducts
  • 2020
  • In: IEEE Access. - 2169-3536. ; 8, s. 173024-173043
  • Journal article (peer-reviewed)abstract
    • At present, optical fiber microducts are coupled together by mechanical types of joints. Mechanical joints are thick, require a large space, and reduce the installation distance in multi-microduct installation. They may leak or explode in the blown fiber installation process. Mechanical joints are subjected to time dependent deterioration under long service times beneath the earth's surface. It may start with a small leakage, followed by damage due to water freezing inside the optical fiber microduct. Optical fiber microducts are made up of high-density polyethylene, which is considered most suitable for thermoelectric welding. For thermoelectric welding of two optical fiber microducts, the welding time should be one second, and should not cause any damage to the inner structure of the microducts that are being coupled. To fulfill these requirements, an LTspice simulation model for the welding system was developed and validated. The developed LTspice model has two parts. The first part models the power input to joule heating wire and the second part models the heat propagation inside the different layers of the optical fiber microduct and surrounding joint by using electro-thermal analogy. In order to validate the simulation results, a battery powered prototype welding system was developed and tested. The prototype welding system consists of a custom-built electrofusion joint and a controller board. A 40 volt 4 ampere-hour Li-Ion battery was used to power the complete system. The power drawn from the battery was controlled by charging and discharging of a capacitor bank, which makes sure that the battery is not overloaded. After successful welding, a pull strength test and an air pressure leakage test were performed to ensure that the welded joints met the requirements set by the mechanical joints. The results show that this new kind of joint and welding system can effectively replace mechanical joints in future optical fiber duct installations.
  •  
18.
  • Al Banna, Md. Hasan, et al. (author)
  • Attention-based Bi-directional Long-Short Term Memory Network for Earthquake Prediction
  • 2021
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 9, s. 56589-56603
  • Journal article (peer-reviewed)abstract
    • An earthquake is a tremor felt on the surface of the earth created by the movement of the major pieces of its outer shell. Till now, many attempts have been made to forecast earthquakes, which saw some success, but these attempted models are specific to a region. In this paper, an earthquake occurrence and location prediction model is proposed. After reviewing the literature, long short-term memory (LSTM) is found to be a good option for building the model because of its memory-keeping ability. Using the Keras tuner, the best model was selected from candidate models, which are composed of combinations of various LSTM architectures and dense layers. This selected model used seismic indicators from the earthquake catalog of Bangladesh as features to predict earthquakes of the following month. Attention mechanism was added to the LSTM architecture to improve the model’s earthquake occurrence prediction accuracy, which was 74.67%. Additionally, a regression model was built using LSTM and dense layers to predict the earthquake epicenter as a distance from a predefined location, which provided a root mean square error of 1.25.
  •  
19.
  • Al-Dhaqm, Arafat, et al. (author)
  • A Review of Mobile Forensic Investigation Process Models
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 173359-173375
  • Research review (peer-reviewed)abstract
    • Mobile Forensics (MF) field uses prescribed scientific approaches with a focus on recovering Potential Digital Evidence (PDE) from mobile devices leveraging forensic techniques. Consequently, increased proliferation, mobile-based services, and the need for new requirements have led to the development of the MF field, which has in the recent past become an area of importance. In this article, the authors take a step to conduct a review on Mobile Forensics Investigation Process Models (MFIPMs) as a step towards uncovering the MF transitions as well as identifying open and future challenges. Based on the study conducted in this article, a review of the literature revealed that there are a few MFIPMs that are designed for solving certain mobile scenarios, with a variety of concepts, investigation processes, activities, and tasks. A total of 100 MFIPMs were reviewed, to present an inclusive and up-to-date background of MFIPMs. Also, this study proposes a Harmonized Mobile Forensic Investigation Process Model (HMFIPM) for the MF field to unify and structure whole redundant investigation processes of the MF field. The paper also goes the extra mile to discuss the state of the art of mobile forensic tools, open and future challenges from a generic standpoint. The results of this study find direct relevance to forensic practitioners and researchers who could leverage the comprehensiveness of the developed processes for investigation.
  •  
20.
  • Al-Dhaqm, Arafat, et al. (author)
  • Categorization and Organization of Database Forensic Investigation Processes
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 112846-112858
  • Journal article (peer-reviewed)abstract
    • Database forensic investigation (DBFI) is an important area of research within digital forensics. It & x2019;s importance is growing as digital data becomes more extensive and commonplace. The challenges associated with DBFI are numerous, and one of the challenges is the lack of a harmonized DBFI process for investigators to follow. In this paper, therefore, we conduct a survey of existing literature with the hope of understanding the body of work already accomplished. Furthermore, we build on the existing literature to present a harmonized DBFI process using design science research methodology. This harmonized DBFI process has been developed based on three key categories (i.e. planning, preparation and pre-response, acquisition and preservation, and analysis and reconstruction). Furthermore, the DBFI has been designed to avoid confusion or ambiguity, as well as providing practitioners with a systematic method of performing DBFI with a higher degree of certainty.
  •  
21.
  • Al-Dhaqm, Arafat, et al. (author)
  • Digital Forensics Subdomains : The State of the Art and Future Directions
  • 2021
  • In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 9, s. 152476-152502
  • Journal article (peer-reviewed)abstract
    • For reliable digital evidence to be admitted in a court of law, it is important to apply scientifically proven digital forensic investigation techniques to corroborate a suspected security incident. Mainly, traditional digital forensics techniques focus on computer desktops and servers. However, recent advances in digital media and platforms have seen an increased need for the application of digital forensic investigation techniques to other subdomains. This includes mobile devices, databases, networks, cloud-based platforms, and the Internet of Things (IoT) at large. To assist forensic investigators to conduct investigations within these subdomains, academic researchers have attempted to develop several investigative processes. However, many of these processes are domain-specific or describe domain-specific investigative tools. Hence, in this paper, we hypothesize that the literature is saturated with ambiguities. To further synthesize this hypothesis, a digital forensic model-orientated Systematic Literature Review (SLR) within the digital forensic subdomains has been undertaken. The purpose of this SLR is to identify the different and heterogeneous practices that have emerged within the specific digital forensics subdomains. A key finding from this review is that there are process redundancies and a high degree of ambiguity among investigative processes in the various subdomains. As a way forward, this study proposes a high-level abstract metamodel, which combines the common investigation processes, activities, techniques, and tasks for digital forensics subdomains. Using the proposed solution, an investigator can effectively organize the knowledge process for digital investigation.
  •  
22.
  • Al-Dhaqm, Arafat, et al. (author)
  • Towards the Development of an Integrated Incident Response Model for Database Forensic Investigation Field
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 145018-145032
  • Journal article (peer-reviewed)abstract
    • For every contact that is made in a database, a digital trace will potentially be left and most of the database breaches are mostly aimed at defeating the major security goals (Confidentiality, Integrity, and Authenticity) of data that reside in the database. In order to prove/refute a fact during litigation, it is important to identify suitable investigation techniques that can be used to link a potential incident/suspect to the digital crime. As a result, this paper has proposed suitable steps of constructing and Integrated Incident Response Model (IIRM) that can be relied upon in the database forensic investigation field. While developing the IIRM, design science methodology has been adapted and the outcome of this study has shown significant and promising approaches that could be leveraged by digital forensic experts, legal practitioners and law enforcement agencies. This is owing to the fact, that IIRM construction has followed incident investigation principles that are stipulated in ISO guidelines.
  •  
23.
  • Alam, Sana, et al. (author)
  • Trust Management in Social Internet of Things (SIoT) : A Survey
  • 2022
  • In: IEEE Access. - 2169-3536. ; 10, s. 108924-108954
  • Journal article (peer-reviewed)abstract
    • A survey on trust management in the Social Internet of Things (SIoT) is provided, beginning with a discussion of SIoT architectures and relationships. Using a variety of publication databases, we describe efforts that focus on various trust management aspects of SIoT. Trust management models comprise three themes: trust computation, aggregation, and updates. Our study presents a detailed discussion of all three steps. Trust computation and trust aggregation depend upon Trust Attributes (TAs) for the calculation of local and global trust values. Our paper discusses many strategies for aggregating trust, but “Weighted Sum” is the most frequently used in the relevant studies. Our paper addresses trust computation and aggregation scenarios. Our work classifies research by TAs (Social Trust, Quality of Service). We’ve categorized the research (reputation-based, recommendation-based, knowledge-based) depending on the types of feedback/opinions used to calculate trust values (global feedback/opinion, feedback from a friend, trustor’s own opinion considering the trustee’s information). Our work classifies studies (policy-based, prediction-based, weighted sum-based/weighted linear combination-based) by trust computation/aggregation approach. Two trust-update schemes are discussed: time-driven and event-driven schemes, while most trust management models utilize an event-driven scheme. Both trust computation and aggregation need propagating trust values in a centralized, decentralized, or semi-centralized way. Our study covers classifying research by trust updates and propagation techniques. Trust models should provide resiliency to SIoT attacks. This analysis classifies SIoT attacks as collaborative or individual. We also discuss scenarios depicted in the relevant studies to incorporate resistance against trust-related attacks in SIoT. Studies suggest context-based or context-free trust management strategies. Our study categorizes studies based on context-based or context-free approaches. To gain the benefits of an immutable, privacy-preserving approach, a future trust management system should utilize Blockchain technology to support non-repudiation and tracking of trust relationships.
  •  
24.
  • Alam, Umair, et al. (author)
  • Entropy and Memory Aware Active Transfer Learning in Smart Sensing Systems
  • 2024
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 12, s. 88841-88861
  • Journal article (peer-reviewed)abstract
    • Automated Human Activity Recognition (HAR) stems from the requirement to seamlessly integrate technology into daily life, to enhance user experience, improve healthcare, provide improved operations, ensure safety, deliver data-driven insights, and address various real-world challenges. However, unscripted Human activity faces challenges that must be understood, and require advances in sensor technology and machine learning models. This paper presents an Active Transfer Learning (ATL) approach for real-time HAR using mobile sensor data. Unlike traditional methods, our approach accounts for both the physical and habitual constraints of individuals. Existing works make an unrealistic assumption of an omniscient oracle while using the same datasets for both training and testing of the models, which makes them impractical for industry requirements. Our proposed approach addresses challenges in existing HAR algorithms, proposing a methodology to adapt models to the real-world datasets while training and testing on cross datasets. We have tailored an existing Entropy and Memory Maximization algorithm to work in a real-time environment while considering user constraints. Primarily trained in a well-labeled controlled environment dataset, we introduce noise injection to prevent the model from overfitting and enhance its generalization for scarcely labeled real-world datasets. Evaluations on publicly available datasets demonstrate our approach achieves 80% - 90% accuracy, outperforming the base algorithm accuracy of 12% - 14%. Importantly, our proposed technique outperforms with limited labeled data, making it valuable for real-time scenarios where labeling is sparse. This research advances HAR in real-world settings, offering improved accuracy and adaptability.
  •  
25.
  • Alani, Mohammed M., et al. (author)
  • PAIRED: An Explainable Lightweight Android Malware Detection System
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 73214-73228
  • Journal article (peer-reviewed)abstract
    • With approximately 2 billion active devices, the Android operating system tops all other operating systems in terms of the number of devices using it. Android has gained wide popularity not only as a smartphone operating system, but also as an operating system for vehicles, tablets, smart appliances, and Internet of Things devices. Consequently, security challenges have arisen with the rapid adoption of the Android operating system. Thousands of malicious applications have been created and are being downloaded by unsuspecting users. This paper presents a lightweight Android malware detection system based on explainable machine learning. The proposed system uses the features extracted from applications to identify malicious and benign malware. The proposed system is tested, showing an accuracy exceeding 98% while maintaining its small footprint on the device. In addition, the classifier model is explained using Shapley Additive Explanation (SHAP) values.
  •  
26.
  • Alawadi, Sadi, 1983-, et al. (author)
  • FedCSD : A Federated Learning Based Approach for Code-Smell Detection
  • 2024
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 12, s. 44888-44904
  • Journal article (peer-reviewed)abstract
    • Software quality is critical, as low quality, or 'Code smell,' increases technical debt and maintenance costs. There is a timely need for a collaborative model that detects and manages code smells by learning from diverse and distributed data sources while respecting privacy and providing a scalable solution for continuously integrating new patterns and practices in code quality management. However, the current literature is still missing such capabilities. This paper addresses the previous challenges by proposing a Federated Learning Code Smell Detection (FedCSD) approach, specifically targeting 'God Class,' to enable organizations to train distributed ML models while safeguarding data privacy collaboratively. We conduct experiments using manually validated datasets to detect and analyze code smell scenarios to validate our approach. Experiment 1, a centralized training experiment, revealed varying accuracies across datasets, with dataset two achieving the lowest accuracy (92.30%) and datasets one and three achieving the highest (98.90% and 99.5%, respectively). Experiment 2, focusing on cross-evaluation, showed a significant drop in accuracy (lowest: 63.80%) when fewer smells were present in the training dataset, reflecting technical debt. Experiment 3 involved splitting the dataset across 10 companies, resulting in a global model accuracy of 98.34%, comparable to the centralized model's highest accuracy. The application of federated ML techniques demonstrates promising performance improvements in code-smell detection, benefiting both software developers and researchers. © 2013 IEEE.
  •  
27.
  • Ali, Hazrat, et al. (author)
  • A Deep Learning Pipeline for Identification of Motor Units in Musculoskeletal Ultrasound
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 170595-170608
  • Journal article (peer-reviewed)abstract
    • Skeletal muscles are functionally regulated by populations of so-called motor units (MUs). An MU comprises a bundle of muscle fibers controlled by a neuron from the spinal cord. Current methods to diagnose neuromuscular diseases and monitor rehabilitation, and study sports sciences rely on recording and analyzing the bio-electric activity of the MUs. However, these methods provide information from a limited part of a muscle. Ultrasound imaging provides information from a large part of the muscle. It has recently been shown that ultrafast ultrasound imaging can be used to record and analyze the mechanical response of individual MUs using blind source separation. In this work, we present an alternative method - a deep learning pipeline - to identify active MUs in ultrasound image sequences, including segmentation of their territories and signal estimation of their mechanical responses (twitch train). We train and evaluate the model using simulated data mimicking the complex activation pattern of tens of activated MUs with overlapping territories and partially synchronized activation patterns. Using a slow fusion approach (based on 3D CNNs), we transform the spatiotemporal image sequence data to 2D representations and apply a deep neural network architecture for segmentation. Next, we employ a second deep neural network architecture for signal estimation. The results show that the proposed pipeline can effectively identify individual MUs, estimate their territories, and estimate their twitch train signal at low contraction forces. The framework can retain spatio-temporal consistencies and information of the mechanical response of MU activity even when the ultrasound image sequences are transformed into a 2D representation for compatibility with more traditional computer vision and image processing techniques. The proposed pipeline is potentially useful to identify simultaneously active MUs in whole muscles in ultrasound image sequences of voluntary skeletal muscle contractions at low force levels.
  •  
28.
  • Ali Shah, Usman, et al. (author)
  • Accelerating Revised Simplex Method using GPU-based Basis Update
  • 2020
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 8, s. 52121-52138
  • Journal article (peer-reviewed)abstract
    • Optimization problems lie at the core of scientific and engineering endeavors. Solutions to these problems are often compute-intensive. To fulfill their compute-resource requirements, graphics processing unit (GPU) technology is considered a great opportunity. To this end, we focus on linear programming (LP) problem solving on GPUs using revised simplex method (RSM). This method has potentially GPU-friendly tasks, when applied to large dense problems. Basis update (BU) is one such task, which is performed in every iteration to update a matrix called basis-inverse matrix. The contribution of this paper is two-fold. Firstly, we experimentally analyzed the performance of existing GPU-based BU techniques. We discovered that the performance of a relatively old technique, in which each GPU thread computed one element of the basis-inverse matrix, could be significantly improved by introducing a vectorcopy operation to its implementation with a sophisticated programming framework. Second, we extended the adapted element-wise technique to develop a new BU technique by using three inexpensive vector operations. This allowed us to reduce the number of floating-point operations and conditional processing performed by GPU threads. A comparison of BU techniques implemented in double precision showed that our proposed technique achieved 17.4% and 13.3% average speed-up over its closest competitor for randomly generated and well-known sets of problems, respectively. Furthermore, the new technique successfully updated basisinverse matrix in relatively large problems, which the competitor was unable to update. These results strongly indicate that our proposed BU technique is not only efficient for dense RSM implementations but is also scalable.
  •  
29.
  • Alibakhshikenari, Mohammad, et al. (author)
  • A Comprehensive Survey on Antennas On-Chip Based on Metamaterial, Metasurface, and Substrate Integrated Waveguide Principles for Millimeter-Waves and Terahertz Integrated Circuits and Systems
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 3668-3692
  • Journal article (peer-reviewed)abstract
    • Antennas on-chip are a particular type of radiating elements valued for their small footprint. They are most commonly integrated in circuit boards to electromagnetically interface free space, which is necessary for wireless communications. Antennas on-chip radiate and receive electromagnetic (EM) energy as any conventional antennas, but what distinguishes them is their miniaturized size. This means they can be integrated inside electronic devices. Although on-chip antennas have a limited range, they are suitable for cell phones, tablet computers, headsets, global positioning system (GPS) devices, and WiFi and WLAN routers. Typically, on-chip antennas are handicapped by narrow bandwidth (less than 10%) and low radiation efficiency. This survey provides an overview of recent techniques and technologies investigated in the literature, to implement high performance on-chip antennas for millimeter-waves (mmWave) and terahertz (THz) integrated-circuit (IC) applications. The technologies discussed here include metamaterial (MTM), metasurface (MTS), and substrate integrated waveguides (SIW). The antenna designs described here are implemented on various substrate layers such as Silicon, Graphene, Polyimide, and GaAs to facilitate integration on ICs. Some of the antennas described here employ innovative excitation mechanisms, for example comprising open-circuited microstrip-line that is electromagnetically coupled to radiating elements through narrow dielectric slots. This excitation mechanism is shown to suppress surface wave propagation and reduce substrate loss. Other techniques described like SIW are shown to significantly attenuate surface waves and minimise loss. Radiation elements based on the MTM and MTS inspired technologies are shown to extend the effective aperture of the antenna without compromising the antenna's form factor. Moreover, the on-chip antennas designed using the above technologies exhibit significantly improved impedance match, bandwidth, gain and radiation efficiency compared to previously used technologies. These features make such antennas a prime candidate for mmWave and THz on-chip integration. This review provides a thorough reference source for specialist antenna designers.
  •  
30.
  • Alizadeh, Morteza, 1987-, et al. (author)
  • Comparative Analysis of Decentralized Identity Approaches
  • 2022
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 10, s. 92273-92283
  • Journal article (peer-reviewed)abstract
    • Decentralization is essential when trust and performance must not depend on a single organization. Distributed Ledger Technologies (DLTs) and Decentralized Hash Tables (DHTs) are examples where the DLT is useful for transactional events, and the DHT is useful for large-scale data storage. The combination of these two technologies can meet many challenges. The blockchain is a DLT with immutable history protected by cryptographic signatures in data blocks. Identification is an essential issue traditionally provided by centralized trust anchors. Self-sovereign identities (SSIs) are proposed decentralized models where users can control and manage their identities with the help of DHT. However, slowness is a challenge among decentralized identification systems because of many connections and requests among participants. In this article, we focus on decentralized identification by DLT and DHT, where users can control their information and store biometrics. We survey some existing alternatives and address the performance challenge by comparing different decentralized identification technologies based on execution time and throughput. We show that the DHT and machine learning model (BioIPFS) performs better than other solutions such as uPort, ShoCard, and BBID.
  •  
31.
  • Alizadehsani, Roohallah, et al. (author)
  • Explainable Artificial Intelligence for Drug Discovery and Development: A Comprehensive Survey
  • 2024
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers Inc.. - 2169-3536. ; 12, s. 35796-35812
  • Research review (peer-reviewed)abstract
    • The field of drug discovery has experienced a remarkable transformation with the advent of artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI and ML models are becoming more complex, there is a growing need for transparency and interpretability of the models. Explainable Artificial Intelligence (XAI) is a novel approach that addresses this issue and provides a more interpretable understanding of the predictions made by machine learning models. In recent years, there has been an increasing interest in the application of XAI techniques to drug discovery. This review article provides a comprehensive overview of the current state-of-the-art in XAI for drug discovery, including various XAI methods, their application in drug discovery, and the challenges and limitations of XAI techniques in drug discovery. The article also covers the application of XAI in drug discovery, including target identification, compound design, and toxicity prediction. Furthermore, the article suggests potential future research directions for the application of XAI in drug discovery. This review article aims to provide a comprehensive understanding of the current state of XAI in drug discovery and its potential to transform the field.
  •  
32.
  • Alkharabsheh, Khalid, et al. (author)
  • Analysing Agreement Among Different Evaluators in God Class and Feature Envy Detection
  • 2021
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 9, s. 145191-145211
  • Journal article (peer-reviewed)abstract
    • The automatic detection of Design Smells has evolved in parallel to the evolution of automatic refactoring tools. There was a huge rise in research activity regarding Design Smell detection from 2010 to the present. However, it should be noted that the adoption of Design Smell detection in real software development practice is not comparable to the adoption of automatic refactoring tools. On the basis of the assumption that it is the objectiveness of a refactoring operation as opposed to the subjectivity in definition and identification of Design Smells that makes the difference, in this paper, the lack of agreement between different evaluators when detecting Design Smells is empirically studied. To do so, a series of experiments and studies were designed and conducted to analyse the concordance in Design Smell detection of different persons and tools, including a comparison between them. This work focuses on two well known Design Smells: God Class and Feature Envy. Concordance analysis is based on the Kappa statistic for inter-rater agreement (particularly Kappa-Fleiss). The results obtained show that there is no agreement in detection in general, and, in those cases where a certain agreement appears, it is considered to be a fair or poor degree of agreement, according to a Kappa-Fleiss interpretation scale. This seems to confirm that there is a subjective component which makes the raters evaluate the presence of Design Smells differently. The study also raises the question of a lack of training and experience regarding Design Smells.
  •  
33.
  • Almas, Muhammad Shoaib, et al. (author)
  • A Hybrid Synchrophasor and GOOSE-Based Power System Synchronization Scheme
  • 2016
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 4, s. 4659-4668
  • Journal article (peer-reviewed)abstract
    • The design and real-time hardware-in-the-loop implementation of a hybrid synchrophasors and GOOSE-based automatic synchronization algorithm are presented in this paper. Automatic synchronization is performed by utilizing the synchrophasor measurements from two commercial phasor measurement units (PMUs), while the coordinated control commands to automatic voltage regulator and/or turbine governor control and trip command to the circuit breaker are issued using IEC 61850-8-1 GOOSE messages. The algorithm is deployed inside the PMU using the protection logic equations, and direct communication between the PMUs is established to minimize the communication latencies. In addition, the algorithm is tested using a standard protection relay test-set, and automatic test sequences are executed to validate its performance. It is concluded that the hybrid synchrophasor and GOOSE-based automatic synchronization scheme ensures minimum communication latencies, reduces equipment cost, facilitates interoperability, and performs automatic reconnection adequately.
  •  
34.
  • Alonso-Fernandez, Fernando, 1978-, et al. (author)
  • A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learning
  • 2019
  • In: IEEE Access. - Piscataway, NJ : IEEE. - 2169-3536. ; 7, s. 6519-6544
  • Journal article (peer-reviewed)abstract
    • The lack of resolution has a negative impact on the performance of image-based biometrics. While many generic super-resolution methods have been proposed to restore low-resolution images, they usually aim to enhance their visual appearance. However, an overall visual enhancement of biometric images does not necessarily correlate with a better recognition performance. Reconstruction approaches need thus to incorporate specific information from the target biometric modality to effectively improve recognition performance. This paper presents a comprehensive survey of iris super-resolution approaches proposed in the literature. We have also adapted an Eigen-patches reconstruction method based on PCA Eigentransformation of local image patches. The structure of the iris is exploited by building a patch-position dependent dictionary. In addition, image patches are restored separately, having their own reconstruction weights. This allows the solution to be locally optimized, helping to preserve local information. To evaluate the algorithm, we degraded high-resolution images from the CASIA Interval V3 database. Different restorations were considered, with 15 × 15 pixels being the smallest resolution evaluated. To the best of our knowledge, this is among the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators, which were used to carry out biometric verification and identification experiments. Experimental results show that the proposed method significantly outperforms both bilinear and bicubic interpolation at very low-resolution. The performance of a number of comparators attain an impressive Equal Error Rate as low as 5%, and a Top-1 accuracy of 77-84% when considering iris images of only 15 × 15 pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching. © 2018, Emerald Publishing Limited.
  •  
35.
  • Alsayfi, Majed S., et al. (author)
  • Securing Real-Time Video Surveillance Data in Vehicular Cloud Computing : A Survey
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 51525-51547
  • Journal article (peer-reviewed)abstract
    • Vehicular ad hoc networks (VANETs) have received a great amount of interest, especially in wireless communications technology. In VANETs, vehicles are equipped with various intelligent sensors that can collect real-time data from inside and from surrounding vehicles. These real-time data require powerful computation, processing, and storage. However, VANETs cannot manage these real-time data because of the limited storage capacity in on board unit (OBU). To address this limitation, a new concept is proposed in which a VANET is integrated with cloud computing to form vehicular cloud computing (VCC) technology. VCC can manage real-time services, such as real-time video surveillance data that are used for monitoring critical events on the road. These real-time video surveillance data include highly sensitive data that should be protected against intruders in the networks because any manipulation, alteration, or sniffing of data will affect a driver's life by causing improper decision-making. The security and privacy of real-time video surveillance data are major challenges in VCC. Therefore, this study reviewed the importance of the security and privacy of real-time video data in VCC. First, we provide an overview of VANETs and their limitations. Second, we provide a state-of-the-art taxonomy for real-time video data in VCC. Then, the importance of real-time video surveillance data in both fifth generation (5G), and sixth generation (6G) networks is presented. Finally, the challenges and open issues of real-time video data in VCC are discussed.
  •  
36.
  • Alsolai, Hadeel, et al. (author)
  • A Systematic Review of Literature on Automated Sleep Scoring
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 79419-79443
  • Research review (peer-reviewed)abstract
    • Sleep is a period of rest that is essential for functional learning ability, mental health, and even the performance of normal activities. Insomnia, sleep apnea, and restless legs are all examples of sleep-related issues that are growing more widespread. When appropriately analyzed, the recording of bio-electric signals, such as the Electroencephalogram, can tell how well we sleep. Improved analyses are possible due to recent improvements in machine learning and feature extraction, and they are commonly referred to as automatic sleep analysis to distinguish them from sleep data analysis by a human sleep expert. This study outlines a Systematic Literature Review and the results it provided to assess the present state-of-the-art in automatic analysis of sleep data. A search string was organized according to the PICO (Population, Intervention, Comparison, and Outcome) strategy in order to determine what machine learning and feature extraction approaches are used to generate an Automatic Sleep Scoring System. The American Academy of Sleep Medicine and Rechtschaffen & Kales are the two main scoring standards used in contemporary research, according to the report. Other types of sensors, such as Electrooculography, are employed in addition to Electroencephalography to automatically score sleep. Furthermore, the existing research on parameter tuning for machine learning models that was examined proved to be incomplete. Based on our findings, different sleep scoring standards, as well as numerous feature extraction and machine learning algorithms with parameter tuning, have a high potential for developing a reliable and robust automatic sleep scoring system for supporting physicians. In the context of the sleep scoring problem, there are evident gaps that need to be investigated in terms of automatic feature engineering techniques and parameter tuning in machine learning algorithms.
  •  
37.
  • Alvarez, Ines, et al. (author)
  • Comparing Admission Control Architectures for Real-Time Ethernet
  • 2020
  • In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 8, s. 136260-136260
  • Journal article (peer-reviewed)abstract
    • Industry 4.0 and Autonomous Driving are emerging resource-intensive distributed application domains that deal with open and evolving environments. These systems are subject to stringent resource, timing, and other non-functional constraints, as well as frequent reconfiguration. Thus, real-time behavior must not preclude operational flexibility. This combination is motivating ongoing efforts within the Time Sensitive Networking (TSN) standardization committee to define admission control mechanisms for Ethernet. Existing mechanisms in TSN, like those of AVB, its predecessor, follow a distributed architecture that favors scalability. Conversely, the new mechanisms envisaged for TSN (IEEE 802.1Qcc) follow a (partially) centralized architecture, favoring short reconfiguration latency. This paper shows the first quantitative comparison between distributed and centralized admission control architectures concerning reconfiguration latency. Here, we compare AVB against a dynamic real-time reconfigurable Ethernet technology with centralized management, namely HaRTES. Our experiments show a significantly lower latency using the centralized architecture. We also observe the dependence of the distributed architecture in the end nodes & x2019; performance and the benefit of having a protected channel for the admission control transactions.
  •  
38.
  •  
39.
  • Alves, Dimas irion, et al. (author)
  • Change Detection Method for Wavelength-Resolution SAR Images Based on Bayes’ Theorem : An Iterative Approach
  • 2023
  • In: IEEE Access. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 11, s. 84734-84743
  • Journal article (peer-reviewed)abstract
    • This paper presents an iterative change detection (CD) method based on Bayes’ theorem for very high-frequency (VHF) ultra-wideband (UWB) SAR images considering commonly used clutter-plus-noise statistical models. The proposed detection technique uses the information of the detected changes to iteratively update the data and distribution information, obtaining more accurate clutter-plus-noise statistics resulting in false alarm reduction. The Bivariate Rayleigh and Bivariate Gaussian distributions are investigated as candidates to model the clutter-plus-noise, and the Anderson-Darling goodness-of-fit test is used to investigate three scenarios of interest. Different aspects related to the distributions are discussed, the observed mismatches are analyzed, and the impact of the distribution chosen for the proposed iterative change detection method is analyzed. Finally, the proposed iterative method performance is assessed in terms of the probability of detection and false alarm rate and compared with other competitive solutions. The experimental evaluation uses data from real measurements obtained using the CARABAS II SAR system. Results show that the proposed iterative CD algorithm performs better than the other methods. Author
  •  
40.
  • Amador Molina, Oscar, 1986-, et al. (author)
  • A Survey on Remote Operation of Road Vehicles
  • 2022
  • In: IEEE Access. - Piscataway, NJ : IEEE. - 2169-3536. ; 10, s. 130135-130154
  • Research review (peer-reviewed)abstract
    • In recent years, the use of remote operation has been proposed as a bridge towards driverless mobility by providing human assistance remotely when an automated driving system finds a situation that is ambiguous and requires input from a remote operator. The remote operation of road vehicles has also been proposed as a way to enable drivers to operate vehicles from safer and more comfortable locations. While commercial solutions for remote operation exist, remaining challenges are being tackled by the research community, who is continuously testing and validating the feasibility of deploying remote operation of road vehicles on public roads. These tests range from the technological scope to social aspects such as acceptability and usability that affect human performance. This survey presents a compilation of works that approach the remote operation of road vehicles. We start by describing the basic architecture of remote operation systems and classify their modes of operation depending on the level of human intervention. We use this classification to organize and present recent and relevant work on the field from industry and academia. Finally, we identify the challenges in the deployment of remote operation systems in the technological, regulatory, and commercial scopes.
  •  
41.
  • Amador, Oscar, et al. (author)
  • A Survey on Remote Operation of Road Vehicles
  • 2022
  • In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 10, s. 130135-130154
  • Journal article (peer-reviewed)abstract
    • In recent years, the use of remote operation has been proposed as a bridge towards driverless mobility by providing human assistance remotely when an automated driving system finds a situation that is ambiguous and requires input from a remote operator. The remote operation of road vehicles has also been proposed as a way to enable drivers to operate vehicles from safer and more comfortable locations. While commercial solutions for remote operation exist, remaining challenges are being tackled by the research community, who is continuously testing and validating the feasibility of deploying remote operation of road vehicles on public roads. These tests range from the technological scope to social aspects such as acceptability and usability that affect human performance. This survey presents a compilation of works that approach the remote operation of road vehicles. We start by describing the basic architecture of remote operation systems and classify their modes of operation depending on the level of human intervention. We use this classification to organize and present recent and relevant work on the field from industry and academia. Finally, we identify the challenges in the deployment of remote operation systems in the technological, regulatory, and commercial scopes.
  •  
42.
  • Amani, Navid, 1985, et al. (author)
  • Sparse Automotive MIMO Radar for Super-Resolution Single Snapshot DOA Estimation With Mutual Coupling
  • 2021
  • In: IEEE Access. - 2169-3536 .- 2169-3536. ; 9, s. 146822-146829
  • Journal article (peer-reviewed)abstract
    • A novel sparse automotive multiple-input multiple-output (MIMO) radar configuration is proposed for low-complexity super-resolution single snapshot direction-of-arrival (DOA) estimation. The physical antenna effects are incorporated in the signal model via open-circuited embedded-element patterns (EEPs) and coupling matrices. The transmit (TX) and receive (RX) array are each divided into two uniform sparse sub-arrays with different inter-element spacings to generate two MIMO sets. Since the corresponding virtual arrays (VAs) of both MIMO sets are uniform, the well-known spatial smoothing (SS) algorithm is applied to suppress the temporal correlation among sources. Afterwards, the co-prime array principle between two spatially smoothed VAs is deployed to avoid DOA ambiguities. A performance comparison between the sparse and conventional MIMO radars with the same number of TX and RX channels confirms a spatial resolution enhancement. Meanwhile, the DOA estimation error due to the mutual coupling (MC) is less pronounced in the proposed sparse architecture since antennas in both TX and RX arrays are spaced larger than half wavelength apart.
  •  
43.
  • Amizhtan, S. K., et al. (author)
  • Impact of Surfactants on the Electrical and Rheological Aspects of Silica Based Synthetic Ester Nanofluids
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 18192-18200
  • Journal article (peer-reviewed)abstract
    • This study reports experimental investigations of the effects of different surfactants (CTAB, Oleic acid and Span 80) on silica based synthetic ester nanofluids. The positive and negative potential observed for the ionic (CTAB) and non-ionic surfactant (Span 80) from zeta potential analysis indicates an improved stability. The optimization of nanofillers and surfactants is performed considering the corona inception voltage measured using ultra high frequency (UHF) technique and fluorescent fiber. Rheological analysis shows no significant variation of properties with shear rate, implying Newtonian behavior even with the addition of surfactant. In addition, the permittivity of the nanofluid is not much affected by adding surfactant but a marginal variation is noticed in the loss tangent with the effect of temperature. The fluorescence spectroscopy shows no change in the emission wavelength with the addition of silica nanofiller and surfactants. Flow electrification studies indicate an increase in the streaming current with the rotation speed and temperature, with a higher current magnitude observed in the case of nanofluids.
  •  
44.
  • Ananno, Anan Ashrabi, et al. (author)
  • A Multi-Heuristic Algorithm for Multi-Container 3-D Bin Packing Problem Optimization Using Real World Constraints
  • 2024
  • In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 12, s. 42105-42130
  • Journal article (peer-reviewed)abstract
    • With the growing demand for sustainable and optimal packaging solutions, this study proposes a novel two-stage algorithm for the multi-container three-dimensional bin packing problem. The research addresses this problem within the context of a real-world industrial scenario and implements several practical constraints including: full shipment, customer positioning requirements, and product geometric interlocking, for increased stability and with the purpose of minimizing the use of plastic wrapping and/or additional supporting surfaces. The main optimization target is to minimize the total number of containers used in the palletization process of custom orders with varying degrees of complexity. The proposed algorithm includes two stages/phases of processing. In the first phase, the algorithm uses constructive heuristics to generate homogeneous product layers. The layers are then stacked to produce blocks, which are then placed on individual containers or pallets. The second phase packs the leftover items using a genetic algorithm. The performance of the proposed solution is benchmarked using real-world industrial data, as well as a more classic academic benchmark. It is demonstrated, across a very large set of orders, that the algorithm always achieves solutions for full palletization of the orders. The analysis shows that the approach is generic and the quality of the solutions generated is relatively even for both small and large, homogeneous and heterogeneous problem instances.
  •  
45.
  • ANDERSSON, MICHAEL, 1988, et al. (author)
  • Feasibility of Ambient RF Energy Harvesting for Self-Sustainable M2M Communications Using Transparent and Flexible Graphene Antennas
  • 2016
  • In: IEEE Access. - 2169-3536 .- 2169-3536. ; 4, s. 5850-5857
  • Journal article (peer-reviewed)abstract
    • Lifetime is a critical parameter in ubiquitous, battery-operated sensors for machine-to-machine (M2M) communication systems, an emerging part of the future Internet of Things. In this practical article, the performance of radio frequency (RF) to DC energy converters using transparent and flexible rectennas based on graphene in an ambient RF energyharvesting scenario is evaluated. Full-wave EM simulations of a dipole antenna assuming the reported state-of-the-art sheet resistance for few-layer, transparent graphene yields an estimated ohmic efficiency of 5 %. In the power budget calculation, the low efficiency of transparent graphene antennas is an issue because of the relatively low amount of available ambient RF energy in the frequency bands of interest, which together sets an upper limit on the harvested energy available for the RF-powered device. Using a commercial diode rectifier and an off-the-shelf wireless system for sensor communication, the graphene-based solution provides only a limited battery lifetime extension. However, for ultra-low-power technologies currently at the research stage, more advantageous ambient energy levels, or other use cases with infrequent data transmission, graphene-based solutions may be more feasible.
  •  
46.
  • Ansari, Rafay Iqbal, et al. (author)
  • Control-Data Separation Architecture for Dual-Band mmWave Networks : A New Dimension to Spectrum Management
  • 2019
  • In: IEEE Access. - 2169-3536. ; 7, s. 34925-34937
  • Journal article (peer-reviewed)abstract
    • The exponential growth in global mobile data traffic, especially with regards to the massive deployment of devices envisioned for the fifth generation (5G) mobile networks, has given impetus to exploring new spectrum opportunities to support the new traffic demands. The millimeter wave (mmWave) frequency band is considered as a potential candidate for alleviating the spectrum scarcity. Moreover, the concept of multi-tier networks has gained popularity, especially for dense network environments. In this article, we deviate from the conventional multi-tier networks and employ the concept of control-data separation architecture (CDSA), which comprises of a control base station (CBS) overlaying the data base station (DBS). We assume that the CBS operates on the sub-6 GHz single band, while the DBS possesses a dual-band mmWave capability, i.e., 26 GHz unlicensed band and 60 GHz licensed band. We formulate a multi-objective optimization (MOO) problem, which jointly optimizes conflicting objectives: the spectral efficiency (SE) and the energy efficiency (EE). The unique aspect of this work includes the analysis of a joint radio resource allocation algorithm based on Lagrangian Dual Decomposition (LDD) and we compare the proposed algorithm with the maximal-rate (maxRx), dynamic sub-carrier allocation (DSA) and joint power and rate adaptation (JPRA) algorithms to show the performance gains achieved by the proposed algorithm.
  •  
47.
  • Apiola, Mikko, et al. (author)
  • From a National Meeting to an International Conference : A Scientometric Case Study of a Finnish Computing Education Conference
  • 2022
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 10, s. 66576-66588
  • Journal article (peer-reviewed)abstract
    • Computerisation and digitalisation are shaping the world in fundamental and unpredictable ways, which highlights the importance of computing education research (CER). As part of understanding the roots of CER, it is crucial to investigate the evolution of CER as a research discipline. In this paper we present a case study of a Finnish CER conference called Koli Calling, which was launched in 2001, and which has become a central publication venue of CER. We use data from 2001 to 2020, and investigate the evolution of Koli Calling's scholarly communities and zoom in on it's publication habits and internalisation process. We explore the narrative of the development and scholarly agenda behind changes in the conference submission categories from the perspective of some of the conference chairs over the years. We then take a qualitative perspective, analysing the conference publications based on a comprehensive bibliometric analysis. The outcomes include classification of important research clusters of authors in the community of conference contributors. Interestingly, we find traces of important events in the historical development of CER. In particular, we find clusters emerging from specific research capacity building initiatives and we can trace how these connect research spanning the world CER community from Finland to Sweden and then further to the USA, Australia and New Zealand. This paper makes a strategic contribution to the evolution of CER as a research discipline, from the perspective of one central event and publication venue, providing a broad perspective on the role of the conference in connecting research clusters and establishing an international research community. This work contributes insights to researchers in one specific CER community and how they shape the future of computing education
  •  
48.
  • Araujo, Gustavo F., et al. (author)
  • Synthetic SAR Data Generator Using Pix2pix cGAN Architecture for Automatic Target Recognition
  • 2023
  • In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 11, s. 143369-143386
  • Journal article (peer-reviewed)abstract
    • Synthetic Aperture Radar (SAR) technology has unique advantages but faces challenges in obtaining enough data for noncooperative target classes. We propose a method to generate synthetic SAR data using a modified pix2pix Conditional Generative Adversarial Networks (cGAN) architecture. The cGAN is trained to create synthetic SAR images with specific azimuth and elevation angles, demonstrating its capability to closely mimic authentic SAR imagery through convergence and collapsing analyses. The study uses a model-based algorithm to assess the practicality of the generated synthetic data for Automatic Target Recognition (ATR). The results reveal that the classification accuracy achieved with synthetic data is comparable to that attained with original data, highlighting the effectiveness of the proposed method in mitigating the limitations imposed by noncooperative SAR data scarcity for ATR. This innovative approach offers a promising solution to craft customized synthetic SAR data, ultimately enhancing ATR performance in remote sensing.
  •  
49.
  • Arfaoui, Ghada, et al. (author)
  • A Security Architecture for 5G Networks
  • 2018
  • In: IEEE Access. - : IEEE. - 2169-3536. ; 6:17, s. 22466-22479
  • Journal article (peer-reviewed)abstract
    • 5G networks will provide opportunities for the creation of new services, for new business models, and for new players to enter the mobile market. The networks will support efficient and cost-effective launch of a multitude of services, tailored for different vertical markets having varying service and security requirements, and involving a large number of actors. Key technology concepts are network slicing and network softwarisation, including network function virtualisation and software-defined networking. The presented security architecture builds upon concepts from the 3G and 4G security architectures but extends and enhances them to cover the new 5G environment. It comprises a toolbox for security relevant modelling of the systems, a set of security design principles, and a set of security functions and mechanisms to implement the security controls needed to achieve stated security objectives. In a smart city use case setting, we illustrate its utility; we examine the high-level security aspects stemming from the deployment of large numbers of IoT devices and network softwarisation.
  •  
50.
  • Asan, Noor Badariah, 1984-, et al. (author)
  • Assessment of Blood Vessel Effect on Fat-Intrabody Communication Using Numerical and Ex-Vivo Models at 2.45 GHZ
  • 2019
  • In: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 7, s. 89886-89900
  • Journal article (peer-reviewed)abstract
    • The potential offered by the intra-body communication (IBC) over the past few years has resulted in a spike of interest for the topic, specifically for medical applications. Fat-IBC is subsequently a novel alternative technique that utilizes fat tissue as a communication channel. This work aimed to identify such transmission medium and its performance in varying blood-vessel systems at 2.45 GHz, particularly in the context of the IBC and medical applications. It incorporated three-dimensional (3D) electromagnetic simulations and laboratory investigations that implemented models of blood vessels of varying orientations, sizes, and positions. Such investigations were undertaken by using ex-vivo porcine tissues and three blood-vessel system configurations. These configurations represent extreme cases of real-life scenarios that sufficiently elucidated their principal influence on the transmission. The blood-vessel models consisted of ex-vivo muscle tissues and copper rods. The results showed that the blood vessels crossing the channel vertically contributed to 5.1 dB and 17.1 dB signal losses for muscle and copper rods, respectively, which is the worst-case scenario in the context of fat-channel with perturbance. In contrast, blood vessels aligned-longitudinally in the channel have less effect and yielded 4.5 dB and 4.2 dB signal losses for muscle and copper rods, respectively. Meanwhile, the blood vessels crossing the channel horizontally displayed 3.4 dB and 1.9 dB signal losses for muscle and copper rods, respectively, which were the smallest losses among the configurations. The laboratory investigations were in agreement with the simulations. Thus, this work substantiated the fat-IBC signal transmission variability in the context of varying blood vessel configurations.
  •  
Skapa referenser, mejla, bekava och länka
  • Result 1-50 of 700
Type of publication
journal article (668)
research review (32)
Type of content
peer-reviewed (688)
other academic/artistic (12)
Author/Editor
Vyatkin, Valeriy (16)
Ottersten, Björn, 19 ... (16)
Al-Ansari, Nadhir, 1 ... (11)
Chatzinotas, S. (11)
Vinel, Alexey, 1983- (10)
Yaseen, Zaher Mundhe ... (10)
show more...
Schelén, Olov (10)
Svensson, Tommy, 197 ... (9)
Gidlund, Mikael, 197 ... (9)
Tenhunen, Hannu (9)
Vasilakos, Athanasio ... (8)
Wymeersch, Henk, 197 ... (8)
Andersson, Karl, 197 ... (8)
Wang, Lihui (8)
Mubeen, Saad (7)
Kebande, Victor R. (7)
Uz Zaman, Ashraf, 19 ... (7)
O'Nils, Mattias, 196 ... (7)
Loo, Jonathan (6)
Brunström, Anna, 196 ... (6)
Nikolakopoulos, Geor ... (6)
Vanfretti, Luigi (6)
Afzal, Wasif (6)
Dalarsson, Mariana (6)
Imran, Ali Shariq (6)
Kastrati, Zenun, 198 ... (6)
Al-Dhaqm, Arafat (6)
Glazunov, Andres Ala ... (6)
Flammini, Francesco, ... (5)
Tufvesson, Fredrik (5)
Rönnberg, Sarah (5)
Chamorro Vera, Harol ... (5)
Amin, Yasar (5)
Galar, Diego (5)
Daudpota, Sher Muham ... (5)
Mahmood, Aamir, 1980 ... (5)
Pettersson, Mats, 19 ... (5)
Hassan, Syed Ali (4)
Chatzinotas, Symeon (4)
Fischione, Carlo (4)
Liwicki, Marcus (4)
Yang, Jian, 1960 (4)
Ivashina, Marianna, ... (4)
Ikuesan, Richard Ade ... (4)
Liu, Hui (4)
Alibakhshikenari, Mo ... (4)
Bertilsson, Kent, 19 ... (4)
Alam, Farhan Muhamma ... (4)
Rusek, Fredrik (4)
Edfors, Ove (4)
show less...
University
Royal Institute of Technology (192)
Luleå University of Technology (105)
Chalmers University of Technology (81)
Mälardalen University (49)
Linköping University (42)
Uppsala University (35)
show more...
Mid Sweden University (32)
RISE (32)
Lund University (30)
Umeå University (29)
Halmstad University (23)
Blekinge Institute of Technology (22)
Karlstad University (21)
Linnaeus University (17)
University of Skövde (13)
Stockholm University (12)
Malmö University (11)
Karolinska Institutet (10)
University of Gothenburg (9)
Örebro University (6)
University West (3)
University of Borås (3)
Jönköping University (2)
Swedish National Defence College (2)
VTI - The Swedish National Road and Transport Research Institute (2)
University of Gävle (1)
Stockholm School of Economics (1)
Högskolan Dalarna (1)
show less...
Language
English (699)
Swedish (1)
Research subject (UKÄ/SCB)
Engineering and Technology (474)
Natural sciences (262)
Social Sciences (23)
Medical and Health Sciences (21)
Agricultural Sciences (1)

Year

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view