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Numrering	Referens	Omslagsbild	Hitta
1.	Ahmadilivani, M. H., et al. (författare) A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks 2024 Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 56:6 Tidskriftsartikel (refereegranskat)abstract Artificial Intelligence (AI) and, in particular, Machine Learning (ML), have emerged to be utilized in various applications due to their capability to learn how to solve complex problems. Over the past decade, rapid advances in ML have presented Deep Neural Networks (DNNs) consisting of a large number of neurons and layers. DNN Hardware Accelerators (DHAs) are leveraged to deploy DNNs in the target applications. Safety-critical applications, where hardware faults/errors would result in catastrophic consequences, also benefit from DHAs. Therefore, the reliability of DNNs is an essential subject of research. In recent years, several studies have been published accordingly to assess the reliability of DNNs. In this regard, various reliability assessment methods have been proposed on a variety of platforms and applications. Hence, there is a need to summarize the state-of-the-art to identify the gaps in the study of the reliability of DNNs. In this work, we conduct a Systematic Literature Review (SLR) on the reliability assessment methods of DNNs to collect relevant research works as much as possible, present a categorization of them, and address the open challenges. Through this SLR, three kinds of methods for reliability assessment of DNNs are identified, including Fault Injection (FI), Analytical, and Hybrid methods. Since the majority of works assess the DNN reliability by FI, we characterize different approaches and platforms of the FI method comprehensively. Moreover, Analytical and Hybrid methods are propounded. Thus, different reliability assessment methods for DNNs have been elaborated on their conducted DNN platforms and reliability evaluation metrics. Finally, we highlight the advantages and disadvantages of the identified methods and address the open challenges in the research area. We have concluded that Analytical and Hybrid methods are light-weight yet sufficiently accurate and have the potential to be extended in future research and to be utilized in establishing novel DNN reliability assessment frameworks.
2.	Bae, Juhee, et al. (författare) Interactive clustering : A comprehensive review 2020 Ingår i: ACM Computing Surveys. - New York, NY : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 53:1 Tidskriftsartikel (refereegranskat)abstract In this survey, 105 papers related to interactive clustering were reviewed according to seven perspectives: (1) on what level is the interaction happening, (2) which interactive operations are involved, (3) how user feedback is incorporated, (4) how interactive clustering is evaluated, (5) which data and (6) which clustering methods have been used, and (7) what outlined challenges there are. This article serves as a comprehensive overview of the field and outlines the state of the art within the area as well as identifies challenges and future research needs.
3.	Batalla, Jordi Mongay, et al. (författare) Secure Smart Homes : Opportunities and Challenges 2017 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 50:5, s. p75:1-75:32 Tidskriftsartikel (refereegranskat)abstract The Smart Home concept integrates smart applications in the daily human life. In recent years, Smart Homes have increased security and management challenges due to the low capacity of small sensors, multiple connectivity to the Internet for efficient applications (use of big data and cloud computing) and heterogeneity of home systems, which require inexpert users to configure devices and micro-systems. This article presents current security and management approaches in Smart Homes and shows the good practices imposed on the market for developing secure systems in houses. At last, we propose future solutions for efficiently and securely managing the Smart Homes
4.	Budzisz, Łukasz, et al. (författare) A taxonomy and survey of SCTP research 2012 Ingår i: ACM Computing Surveys. - New York : ACM Press. - 0360-0300 .- 1557-7341. ; 44:4, s. -36 Tidskriftsartikel (refereegranskat)abstract The Stream Control Transmission Protocol (SCTP) is a relatively recent general-purpose transport layer protocol for IP networks that has been introduced as a complement to the well-established TCP and UDP transport protocols. Although initially conceived for the transport of PSTN signaling messages over IP networks, the introduction of key features in SCTP, such as multihoming and multistreaming, has spurred considerable research interest surrounding SCTP and its applicability to different networking scenarios. This article aims to provide a detailed survey of one of these new features—multihoming—which, as it is shown, is the subject of evaluation in more than half of all published SCTP-related articles. To this end, the article first summarizes and organizes SCTP-related research conducted so far by developing a four-dimensional taxonomy reflecting the (1) protocol feature examined, (2) application area, (3) network environment, and (4) study approach. Over 430 SCTP-related publications have been analyzed and classified according to the proposed taxonomy. As a result, a clear perspective on this research area in the decade since the first protocol standardization in 2000 is given, covering both current and future research trends. On continuation, a detailed survey of the SCTP multihoming feature is provided, examining possible applications of multihoming, such as robustness, handover support, and loadsharing.
5.	Castañeda Lozano, Roberto, 1986-, et al. (författare) Survey on Combinatorial Register Allocation and Instruction Scheduling 2018 Ingår i: ACM Computing Surveys. - : ACM Press. - 0360-0300 .- 1557-7341. Tidskriftsartikel (refereegranskat)abstract Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time.This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization.
6.	Castañedalozano, Roberto, et al. (författare) Survey on combinatorial register allocation and instruction scheduling 2019 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery. - 0360-0300 .- 1557-7341. ; 52:3 Tidskriftsartikel (refereegranskat)abstract Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the past three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This article provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization. .
7.	Ciccozzi, Federico, 1983-, et al. (författare) A Comprehensive Exploration of Languages for Parallel Computing 2023 Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 55:2 Tidskriftsartikel (refereegranskat)abstract Software-intensive systems in most domains, from autonomous vehicles to health, are becoming predominantly parallel to efficiently manage large amount of data in short (even real-) time. There is an incredibly rich literature on languages for parallel computing, thus it is difficult for researchers and practitioners, even experienced in this very field, to get a grasp on them. With this work we provide a comprehensive, structured, and detailed snapshot of documented research on those languages to identify trends, technical characteristics, open challenges, and research directions. In this article, we report on planning, execution, and results of our systematic peer-reviewed as well as grey literature review, which aimed at providing such a snapshot by analysing 225 studies.
8.	Dai, Hong-Ning, et al. (författare) Big Data Analytics for Large-scale Wireless Networks : Challenges and Opportunities 2019 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 52:5 Tidskriftsartikel (refereegranskat)abstract The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large-scale wireless networks. Big data of large-scale wireless networks has the key features of wide variety, high volume, real-time velocity, and huge value leading to the unique research challenges that are different from existing computing systems. In this article, we present a survey of the state-of-art big data analytics (BDA) approaches for large-scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage, and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large-scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area.
9.	De Boer, Frank, et al. (författare) A Survey of Active Object Languages 2017 Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 50:5 Tidskriftsartikel (refereegranskat)abstract To program parallel systems efficiently and easily, a wide range of programming models have been proposed, eachwith different choices concerning synchronization and communication between parallel entities. Among them, the actor model is based on loosely coupled parallel entities that communicate by means of asynchronous messages and mailboxes. Some actor languages provide a strong integration with object-oriented concepts; these are often called active object languages. This article reviews four major actor and active object languages and compares them according to carefully chosen dimensions that cover central aspects of the programming paradigms and their implementation.
10.	Dou, Mingliang, et al. (författare) Drug-drug interaction relation extraction based on deep learning : A review 2024 Ingår i: ACM Computing Surveys. - New York, NY : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:6, s. 1-33 Tidskriftsartikel (refereegranskat)abstract Drug-drug interaction (DDI) is an important part of drug development and pharmacovigilance. At the same time, DDI is an important factor in treatment planning, monitoring effects of medicine and patient safety, and has a significant impact on public health. Therefore, using deep learning technology to extract DDI from scientific literature has become a valuable research direction to researchers. In existing DDI datasets, the number of positive instances is relatively small. This makes it difficult for existing deep learning models to obtain sufficient feature information directly from text data. Therefore, existing deep learning models mainly rely on multiple feature supplementation methods to collect sufficient feature information from different types of data. In this study, the general process of DDI relation extraction based on deep learning is introduced first for comprehensive analysis. Next, we summarize the various feature supplement methods and analyze their merits and demerits. We then review the state-of-the-art literature related to DDI extraction from the deep neural network perspective. Finally, all the feature supplement methods are compared, and some suggestions are given to approach the current problems and future research directions. The purpose of this article is to give researchers a more complete understanding of the feature complementation methods used in DDI extraction to be able to rapidly design and implement custom DDI relation extraction methods. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
11.	Eslami Kiasari, Abbas, et al. (författare) Mathematical formalisms for performance evaluation of networks-on-chip 2013 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 45:3, s. 38- Tidskriftsartikel (refereegranskat)abstract This article reviews four popular mathematical formalisms-queueing theory, network calculus, schedulability analysis, anddataflow analysis-and how they have been applied to the analysis of on-chip communication performance in Systems-on-Chip. The article discusses the basic concepts and results of each formalism and provides examples of how they have been used in Networks-on-Chip (NoCs) performance analysis. Also, the respective strengths and weaknesses of each technique and its suitability for a specific purpose are investigated. An open research issue is a unified analytical model for a comprehensive performance evaluation of NoCs. To this end, this article reviews the attempts that have been made to bridge these formalisms.
12.	Fagerholm, F., et al. (författare) Cognition in Software Engineering: A Taxonomy and Survey of a Half-Century of Research 2022 Ingår i: Acm Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 54:11 Tidskriftsartikel (refereegranskat)abstract Cognition plays a fundamental role in most software engineering activities. This article provides a taxonomy of cognitive concepts and a survey of the literature since the beginning of the Software Engineering discipline. The taxonomy comprises the top-level concepts of perception, attention, memory, cognitive load, reasoning, cognitive biases, knowledge, social cognition, cognitive control, and errors, and procedures to assess them both qualitatively and quantitatively. The taxonomy provides a useful tool to filter existing studies, classify new studies, and support researchers in getting familiar with a (sub) area. In the literature survey, we systematically collected and analysed 311 scientific papers spanning five decades and classified them using the cognitive concepts from the taxonomy. Our analysis shows that the most developed areas of research correspond to the four life-cycle stages, software requirements, design, construction, and maintenance. Most research is quantitative and focuses on knowledge, cognitive load, memory, and reasoning. Overall, the state of the art appears fragmented when viewed from the perspective of cognition. There is a lack of use of cognitive concepts that would represent a coherent picture of the cognitive processes active in specific tasks. Accordingly, we discuss the research gap in each cognitive concept and provide recommendations for future research.
13.	Giraldo, Jairo, et al. (författare) A Survey of Physics-Based Attack Detection in Cyber-Physical Systems 2018 Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 51:4 Tidskriftsartikel (refereegranskat)abstract Monitoring the "physics" of cyber-physical systems to detect attacks is a growing area of research. In its basic form, a security monitor creates time-series models of sensor readings for an industrial control system and identifies anomalies in these measurements to identify potentially false control commands or false sensor readings. In this article, we review previous work on physics-based anomaly detection based on a unified taxonomy that allows us to identify limitations and unexplored challenges and to propose new solutions.
14.	Gomes, Claudio, et al. (författare) Co-Simulation : A Survey 2018 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 51:3 Tidskriftsartikel (refereegranskat)abstract Modeling and simulation techniques are today extensively used both in industry and science. Parts of larger systems are, however, typically modeled and simulated by different techniques, tools, and algorithms. In addition, experts from different disciplines use various modeling and simulation techniques. Both these facts make it difficult to study coupled heterogeneous systems. Co-simulation is an emerging enabling technique, where global simulation of a coupled system can be achieved by composing the simulations of its parts. Due to its potential and interdisciplinary nature, cosimulation is being studied in different disciplines but with limited sharing of findings. In this survey, we study and survey the state-of-the-art techniques for co-simulation, with the goal of enhancing future research and highlighting the main challenges. To study this broad topic, we start by focusing on discrete-event-based co-simulation, followed by continuous-time-based co-simulation. Finally, we explore the interactions between these two paradigms, in hybrid co-simulation. To survey the current techniques, tools, and research challenges, we systematically classify recently published research literature on co-simulation, and summarize it into a taxonomy. As a result, we identify the need for finding generic approaches for modular, stable, and accurate coupling of simulation units, as well as expressing the adaptations required to ensure that the coupling is correct.
15.	He, Tongyue, et al. (författare) Toward Wearable Sensors : Advances, Trends, and Challenges 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 55:14S Forskningsöversikt (refereegranskat)abstract Sensors suitable for wearable devices have many special characteristics compared to other sensors, such as stability, sensitivity, sensor volume, biocompatibility, and so on. With the development of wearable technology, amazing wearable sensors have attracted a lot of attention, and some researchers have done a large number of technology explorations and reviews. However, previous surveys generally were concerned with a specified application and comprehensively reviewed the computing techniques for the signals required by this application, as well as how computing can promote data processing. There is a gap in the opposite direction, i.e., the fundamental data source actively stimulates application rather than from the application to the data, and computing promotes the acquisition of data rather than data processing. To fill this gap, starting with different parts of the body as the source of signal, the fundamental data sources that can be obtained and detected are explored by combining the three sensing principles, as well as discussing and analyzing the existing and potential applications of machine learning in simplifying sensor designs and the fabrication of sensors.
16.	Hedin, Görel, et al. (författare) On the role of language constructs for framework design 2000 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 32:1es Tidskriftsartikel (refereegranskat)abstract The relationship between framework design and language constructs are discussed for two reasons: firstly, designing frameworks requires the ability to give the framework designer precise control over aspects of the framework extensions; secondly, the framework constraints should be specified such that they are statically checkable. Four existing language constructs are discussed: generalized block structure, generalized inheritance, generalized virtuality, and singular objects. It is discussed how these language constructs give precise means for controlling the framework extensions in statically checkable ways.
17.	Hogan, Aidan, et al. (författare) Knowledge Graphs 2021 Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 54:4 Tidskriftsartikel (refereegranskat)abstract In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.
18.	Houy, Sabine, et al. (författare) Security aspects of cryptocurrency wallets : a systematic literature review 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:1 Forskningsöversikt (refereegranskat)abstract Cryptocurrencies are gaining prominence among individuals and companies alike, resulting in the growing adoption of so-called cryptocurrency wallet applications, as these simplify transactions. These wallets are available in a myriad of different forms and specifications. All of them are susceptible to various ways the attacker can exploit the vulnerabilities and steal money from victims. Cryptocurrency wallets create a unique field as they combine features of password managers, banking applications, and the need to keep their users and their transactions anonymous. We collect the findings from previous literature to provide an overview of the different attack surfaces, possible countermeasures, and further research. Existing literature focused on one of the features mentioned before, while we considered all of them. Our systematic study shows that there is a considerable variety of attack vectors, which we have divided into six subcategories, (i) Memory and Storage, (ii) Operating Systems, (iii) Software Layer, (iv) Network Layer, (v) Blockchain Protocol, and (vi) Others. We have found a large gap between the possible countermeasures and their actual adoption. Therefore, we provide a list of possible directions for future research to tackle this gap.
19.	Ibidunmoye, Olumuyiwa, et al. (författare) Performance Anomaly Detection and Bottleneck Identification 2015 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 48:1 Tidskriftsartikel (refereegranskat)abstract In order to meet stringent performance requirements, system administrators must effectively detect undesirable performance behaviours, identify potential root causes and take adequate corrective measures. The problem of uncovering and understanding performance anomalies and their causes (bottlenecks) in different system and application domains is well studied. In order to assess progress, research trends and identify open challenges, we have reviewed major contributions in the area and present our findings in this survey. Our approach provides an overview of anomaly detection and bottleneck identification research as it relates to the performance of computing systems. By identifying fundamental elements of the problem, we are able to categorize existing solutions based on multiple factors such as the detection goals, nature of applications and systems, system observability, and detection methods.
20.	Idowu, Samuel, 1985, et al. (författare) Asset Management in Machine Learning: State-of-research and State-of-practice 2023 Ingår i: Acm Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 55:7 Tidskriftsartikel (refereegranskat)abstract Machine learning components are essential for today's software systems, causing a need to adapt traditional software engineering practices when developing machine-learning-based systems. This need is pronounced due to many development-related challenges of machine learning components such as asset, experiment, and dependency management. Recently, many asset management tools addressing these challenges have become available. It is essential to understand the support such tools offer to facilitate research and practice on building new management tools with native supports for machine learning and software engineering assets. This article positions machine learning asset management as a discipline that provides improved methods and tools for performing operations on machine learning assets. We present a feature-based survey of 18 state-of-practice and 12 state-of-research tools supporting machine-learning assetmanagement. We overview their features for managing the types of assets used in machine learning experiments. Most state-of-research tools focus on tracking, exploring, and retrieving assets to address development concerns such as reproducibility, while the state-of-practice tools also offer collaboration and workflow-execution-related operations. In addition, assets are primarily tracked intrusively from the source code through APIs and managed via web dashboards or command-line interfaces (CLIs). We identify asynchronous collaboration and asset reusability as directions for new tools and techniques.
21.	Kebande, Victor R., et al. (författare) Industrial Internet of Things Ecosystems Security and Digital Forensics : Achievements, Open Challenges, and Future Directions 2024 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:5 Tidskriftsartikel (refereegranskat)abstract The Industrial Internet of Things (IIoT) has been positioned as a key pillar of the Industry 4.0 revolution, which is projected to continue accelerating and realizing digital transformations. The IIoT is becoming indispensable, providing the means through which modern communication is conducted across industries and offering improved efficiency, scalability, and robustness. However, the structural and dynamic complexity introduced by the continuous integration of the IIoT has widened the scope for cyber-threats, as the processes and data generated by this integration are susceptible and vulnerable to attacks. This article presents an in-depth analysis of the state-of-the-art in the IIoT ecosystem from security and digital forensics perspectives. The dimensions of this study are twofold: first, we present an overview of the cutting-edge security of IIoT ecosystems, and second, we survey the literature on digital forensics. The key achievements, open challenges, and future directions are identified in each case. The challenges and directions for future studies that we identify will provide important guidance for cybersecurity researchers and practitioners. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
22.	Khan, Salman, et al. (författare) Transformers in Vision: A Survey 2022 Ingår i: ACM Computing Surveys. - : ASSOC COMPUTING MACHINERY. - 0360-0300 .- 1557-7341. ; 54:10 Tidskriftsartikel (refereegranskat)abstract Astounding results from Transformer models on natural language tasks have intrigued the vision community to study their application to computer vision problems. Among their salient benefits, Transformers enable modeling long dependencies between input sequence elements and support parallel processing of sequence as compared to recurrent networks, e.g., Long short-term memory. Different from convolutional networks, Transformers require minimal inductive biases for their design and are naturally suited as set-functions. Furthermore, the straightforward design of Transformers allows processing multiple modalities (e.g., images, videos, text, and speech) using similar processing blocks and demonstrates excellent scalability to very large capacity networks and huge datasets. These strengths have led to exciting progress on a number of vision tasks using Transformer networks. This survey aims to provide a comprehensive overview of the Transformer models in the computer vision discipline. We start with an introduction to fundamental concepts behind the success of Transformers, i.e., self-attention, large-scale pre-training, and bidirectional feature encoding. We then cover extensive applications of transformers in vision including popular recognition tasks (e.g., image classification, object detection, action recognition, and segmentation), generative modeling, multi-modal tasks (e.g., visual-question answering, visual reasoning, and visual grounding), video processing (e.g., activity recognition, video forecasting), low-level vision (e.g., image super-resolution, image enhancement, and colorization), and three-dimensional analysis (e.g., point cloud classification and segmentation). We compare the respective advantages and limitations of popular techniques both in terms of architectural design and their experimental value. Finally, we provide an analysis on open research directions and possible future works. We hope this effort will ignite further interest in the community to solve current challenges toward the application of transformer models in computer vision.
23.	Kleyko, Denis, et al. (författare) A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part I: Models and Data Transformations 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 55:6 Tidskriftsartikel (refereegranskat)abstract This two-part comprehensive survey is devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and distributed vector representations. Notable models in the HDC/VSA family are Tensor Product Representations, Holographic Reduced Representations, Multiply-Add-Permute, Binary Spatter Codes, and Sparse Binary Distributed Representations but there are other models too. HDC/VSA is a highly interdisciplinary field with connections to computer science, electrical engineering, artificial intelligence, mathematics, and cognitive science. This fact makes it challenging to create a thorough overview of the field. However, due to a surge of new researchers joining the field in recent years, the necessity for a comprehensive survey of the field has become extremely important. Therefore, amongst other aspects of the field, this Part I surveys important aspects such as: known computational models of HDC/VSA and transformations of various input data types to high-dimensional distributed representations. Part II of this survey [84] is devoted to applications, cognitive computing and architectures, as well as directions for future work. The survey is written to be useful for both newcomers and practitioners.
24.	Kleyko, Denis, et al. (författare) A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II : Applications, Cognitive Models, and Challenges 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery. - 0360-0300 .- 1557-7341. ; 55:9 Tidskriftsartikel (refereegranskat)abstract This is Part II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations. Holographic Reduced Representations [321, 326] is an influential HDC/VSA model that is well known in the machine learning domain and often used to refer to the whole family. However, for the sake of consistency, we use HDC/VSA to refer to the field.Part I of this survey [222] covered foundational aspects of the field, such as the historical context leading to the development of HDC/VSA, key elements of any HDC/VSA model, known HDC/VSA models, and the transformation of input data of various types into high-dimensional vectors suitable for HDC/VSA. This second part surveys existing applications, the role of HDC/VSA in cognitive computing and architectures, as well as directions for future work. Most of the applications lie within the Machine Learning/Artificial Intelligence domain; however, we also cover other applications to provide a complete picture. The survey is written to be useful for both newcomers and practitioners.
25.	Kosch, Thomas, et al. (författare) A Survey on Measuring Cognitive Workload in Human-Computer Interaction 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 55:13s Tidskriftsartikel (refereegranskat)abstract The ever-increasing number of computing devices around us results in more and more systems competing for our attention, making cognitive workload a crucial factor for the user experience of human-computer interfaces. Research in Human-Computer Interaction (HCI) has used various metrics to determine users' mental demands. However, there needs to be a systematic way to choose an appropriate and effective measure for cognitive workload in experimental setups, posing a challenge to their reproducibility. We present a literature survey of past and current metrics for cognitive workload used throughout HCI literature to address this challenge. By initially exploring what cognitive workload resembles in the HCI context, we derive a categorization supporting researchers and practitioners in selecting cognitive workload metrics for system design and evaluation. We conclude with three following research gaps: (1) defining and interpreting cognitive workload in HCI, (2) the hidden cost of the NASA-TLX, and (3) HCI research as a catalyst for workload-aware systems, highlighting that HCI research has to deepen and conceptualize the understanding of cognitive workload in the context of interactive computing systems.
26.	Lanciano, Tommaso, et al. (författare) A Survey on the Densest Subgraph Problem and its Variants 2024 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:8 Tidskriftsartikel (refereegranskat)abstract The Densest Subgraph Problem requires us to find, in a given graph, a subset of vertices whose induced subgraph maximizes a measure of density. The problem has received a great deal of attention in the algorithmic literature since the early 1970s, with many variants proposed and many applications built on top of this basic definition. Recent years have witnessed a revival of research interest in this problem with several important contributions, including some groundbreaking results, published in 2022 and 2023. This survey provides a deep overview of the fundamental results and an exhaustive coverage of the many variants proposed in the literature, with a special attention to the most recent results. The survey also presents a comprehensive overview of applications and discusses some interesting open problems for this evergreen research topic.
27.	Le Duc, Thang, 1980-, et al. (författare) Machine Learning Methods for Reliable Resource Provisioning in Edge-Cloud Computing : A Survey 2019 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 52:5 Tidskriftsartikel (refereegranskat)abstract Large-scale software systems are currently designed as distributed entities and deployed in cloud data centers. To overcome the limitations inherent to this type of deployment, applications are increasingly being supplemented with components instantiated closer to the edges of networks—a paradigm known as edge computing. The problem of how to efficiently orchestrate combined edge-cloud applications is, however, incompletely understood, and a wide range of techniques for resource and application management are currently in use.This article investigates the problem of reliable resource provisioning in joint edge-cloud environments, and surveys technologies, mechanisms, and methods that can be used to improve the reliability of distributed applications in diverse and heterogeneous network environments. Due to the complexity of the problem, special emphasis is placed on solutions to the characterization, management, and control of complex distributed applications using machine learning approaches. The survey is structured around a decomposition of the reliable resource provisioning problem into three categories of techniques: workload characterization and prediction, component placement and system consolidation, and application elasticity and remediation. Survey results are presented along with a problem-oriented discussion of the state-of-the-art. A summary of identified challenges and an outline of future research directions are presented to conclude the article.
28.	Magnani, Matteo, et al. (författare) Community Detection in Multiplex Networks 2021 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 54:3 Tidskriftsartikel (refereegranskat)abstract A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures, and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic.
29.	Malik, Jamshaid Sarwar, et al. (författare) Gaussian Random Number Generation : A Survey on Hardware Architectures 2016 Ingår i: ACM Computing Surveys. - : ACM Digital Library. - 0360-0300 .- 1557-7341. ; 49:3 Tidskriftsartikel (refereegranskat)abstract Some excellent surveys of the Gaussian random number generators (GRNGs) from the algorithmic perspective exist in the published literature to date (e.g., Thomas et al. [2007]). In the last decade, however, advancements in digital hardware have resulted in an ever-decreasing hardware cost and increased design flexibility. Additionally, recent advances in applications like gaming, weather forecasting, and simulations in physics and astronomy require faster, cheaper, and statistically accurate GRNGs. These two trends have contributed toward the development of a number of novel GRNG architectures optimized for hardware design. A detailed comparative study of these hardware architectures has been somewhat missing in the published literature. This work provides the potential user a capsulization of the published hardware GRNG architectures. We have provided the method and theory, pros and cons, and a comparative summary of the speed, statistical accuracy, and hardware resource utilization of these architectures. Finally, we have complemented this work by describing two novel hardware GRNG architectures, namely, the CLT-inversion and the multihat algorithm, respectively. These new architectures provide high tail accuracy (6 sigma and 8 sigma, respectively) at a low hardware cost.
30.	Methnani, Leila, et al. (författare) Who's in charge here? a survey on trustworthy AI in variable autonomy robotic systems 2024 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:7 Tidskriftsartikel (refereegranskat)abstract This article surveys the Variable Autonomy (VA) robotics literature that considers two contributory elements to Trustworthy AI: transparency and explainability. These elements should play a crucial role when designing and adopting robotic systems, especially in VA where poor or untimely adjustments of the system's level of autonomy can lead to errors, control conflicts, user frustration, and ultimate disuse of the system. Despite this need, transparency and explainability is, to the best of our knowledge, mostly overlooked in VA robotics literature or is not considered explicitly. In this article, we aim to present and examine the most recent contributions to the VA literature concerning transparency and explainability. In addition, we propose a way of thinking about VA by breaking these two concepts down based on: the mission of the human-robot team; who the stakeholder is; what needs to be made transparent or explained; why they need it; and how it can be achieved. Last, we provide insights and propose ways to move VA research forward. Our goal with this article is to raise awareness and inter-community discussions among the Trustworthy AI and the VA robotics communities.
31.	Nguyen, Kien, et al. (författare) Deep Learning for Iris Recognition : A Survey 2024 Ingår i: ACM Computing Surveys. - New York, NY : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:9 Tidskriftsartikel (refereegranskat)abstract In this survey, we provide a comprehensive review of more than 200 articles, technical reports, and GitHub repositories published over the last 10 years on the recent developments of deep learning techniques for iris recognition, covering broad topics on algorithm designs, open-source tools, open challenges, and emerging research. First, we conduct a comprehensive analysis of deep learning techniques developed for two main sub-tasks in iris biometrics: segmentation and recognition. Second, we focus on deep learning techniques for the robustness of iris recognition systems against presentation attacks and via human-machine pairing. Third, we delve deep into deep learning techniques for forensic application, especially in post-mortem iris recognition. Fourth, we review open-source resources and tools in deep learning techniques for iris recognition. Finally, we highlight the technical challenges, emerging research trends, and outlook for the future of deep learning in iris recognition. © 2024 Copyright held by the owner/author(s).
32.	Olugbade, Temitayo, et al. (författare) Human Movement Datasets : An Interdisciplinary Scoping Review 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 55:6 Forskningsöversikt (refereegranskat)abstract Movement dataset reviews exist but are limited in coverage, both in terms of size and research discipline. While topic-specific reviews clearly have their merit, it is critical to have a comprehensive overview based on a systematic survey across disciplines. This enables higher visibility of datasets available to the research communities and can foster interdisciplinary collaborations. We present a catalogue of 704 open datasets described by 10 variables that can be valuable to researchers searching for secondary data: name and reference, creation purpose, data type, annotations, source, population groups, ordinal size of people captured simultaneously, URL, motion capture sensor, and funders. The catalogue is available in the supplementary materials. We provide an analysis of the datasets and further review them under the themes of human diversity, ecological validity, and data recorded. The resulting 12-dimension framework can guide researchers in planning the creation of open movement datasets. This work has been the interdisciplinary effort of researchers across affective computing, clinical psychology, disability innovation, ethnomusicology, human-computer interaction, machine learning, music cognition, music computing, and movement neuroscience.
33.	Patrignani, Marco, et al. (författare) Formal Approaches to Secure Compilation : A Survey of Fully Abstract Compilation and Related Work 2019 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 51:6 Tidskriftsartikel (refereegranskat)abstract Secure compilation is a discipline aimed at developing compilers that preserve the security properties of the source programs they take as input in the target programs they produce as output. This discipline is broad in scope. targeting languages with a variety of features (including objects, higher-order functions, dynamic memory allocation, call/cc, concurrency) and employing a range of different techniques to ensure that source-level security is preserved at the target level. This article provides a survey of the existing literature on formal approaches to secure compilation with a focus on those that prove fully abstract compilation, which has been the criterion adopted by much of the literature thus far. This article then describes the formal techniques employed to prove secure compilation in existing work, introducing relevant terminology, and discussing the merits and limitations of each work. Finally, this article discusses open challenges and possible directions for future work in secure compilation.
34.	Perera, Charith, et al. (författare) Fog Computing for Sustainable Smart Cities : A Survey 2017 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 50:3 Tidskriftsartikel (refereegranskat)abstract The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, especially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g., network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build a sustainable IoT infrastructure for smart cities. In this article, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges toward implementing them, to shed light on future research directions on realizing Fog computing for building sustainable smart cities.
35.	Perez-Cerrolaza, Jon, et al. (författare) Artificial Intelligence for Safety-Critical Systems in Industrial and Transportation Domains: A Survey 2024 Ingår i: ACM Computing Surveys. - New York : Association for Computing Machinery. - 0360-0300 .- 1557-7341. ; 56:7 Tidskriftsartikel (refereegranskat)abstract Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-critical systems in which Machine Learning (ML) algorithms learn optimized and safe solutions. AI can also support and assist human safety engineers in developing safety-critical systems. However, reconciling both cutting-edge and state-of-the-art AI technology with safety engineering processes and safety standards is an open challenge that must be addressed before AI can be fully embraced in safety-critical systems. Many works already address this challenge, resulting in a vast and fragmented literature. Focusing on the industrial and transportation domains, this survey structures and analyzes challenges, techniques, and methods for developing AI-based safety-critical systems, from traditional functional safety systems to autonomous systems. AI trustworthiness spans several dimensions, such as engineering, ethics and legal, and this survey focuses on the safety engineering dimension.
36.	Radetzki, Martin, et al. (författare) Methods for Fault Tolerance in Networks-on-Chip 2013 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 46:1, s. 8- Tidskriftsartikel (refereegranskat)abstract Networks-on-Chip constitute the interconnection architecture of future, massively parallel multiprocessors that assemble hundreds to thousands of processing cores on a single chip. Their integration is enabled by ongoing miniaturization of chip manufacturing technologies following Moore's Law. It comes with the downside of the circuit elements' increased susceptibility to failure. Research on fault-tolerant Networks-on-Chip tries to mitigate partial failure and its effect on network performance and reliability by exploiting various forms of redundancy at the suitable network layers. The article at hand reviews the failure mechanisms, fault models, diagnosis techniques, and fault-tolerance methods in on-chip networks, and surveys and summarizes the research of the last ten years. It is structured along three communication layers: the data link, the network, and the transport layers. The most important results are summarized and open research problems and challenges are highlighted to guide future research on this topic.
37.	Tavara, Shirin (författare) Parallel Computing of Support Vector Machines : A Survey 2019 Ingår i: ACM Computing Surveys. - United States : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 51:6, s. 123:1-123:38 Forskningsöversikt (refereegranskat)abstract The immense amount of data created by digitalization requires parallel computing for machine-learning methods. While there are many parallel implementations for support vector machines (SVMs), there is no clear suggestion for every application scenario. Many factor—including optimization algorithm, problem size and dimension, kernel function, parallel programming stack, and hardware architecture—impact the efficiency of implementations. It is up to the user to balance trade-offs, particularly between computation time and classification accuracy. In this survey, we review the state-of-the-art implementations of SVMs, their pros and cons, and suggest possible avenues for future research.
38.	Uneson, Marcus (författare) When Errors Become the Rule : Twenty Years with Transformation-Based Learning 2014 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 46:4, s. 50-51 Tidskriftsartikel (refereegranskat)abstract Transformation-based learning (TBL) is a machine learning method for, in particular, sequential classification, invented by Eric Brill [Brill 1993b, 1995a]. It is widely used within computational linguistics and natural language processing, but surprisingly little in other areas. TBL is a simple yet flexible paradigm, which achieves competitive or even state-of-the-art performance in several areas and does not overtrain easily. It is especially successful at catching local, fixed-distance dependencies and seamlessly exploits information from heterogeneous discrete feature types. The learned representation—an ordered list of transformation rules—is compact and efficient, with clear semantics. Individual rules are interpretable and often meaningful to humans. The present article offers a survey of the most important theoretical work on TBL, addressing a perceived gap in the literature. Because the method should be useful also outside the world of computational linguistics and natural language processing, a chief aim is to provide an informal but relatively comprehensive introduction, readable also by people coming from other specialities.
39.	Veiga, Tiago, et al. (författare) From Reactive to Active Sensing : A Survey on Information Gathering in Decision-theoretic Planning 2023 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 55:13S Tidskriftsartikel (refereegranskat)abstract In traditional decision-theoretic planning, information gathering is a means to a goal. The agent receives information about its environment (state or observation) and uses it as a way to optimize a state-based reward function. Recent works, however, have focused on application domains in which information gathering is not only the mean but the goal itself. The agent must optimize its knowledge of the environment. However, traditional Markov-based decision-theoretic models cannot account for rewarding the agent based on its knowledge, which leads to the development of many approaches to overcome this limitation. We survey recent approaches for using decision-theoretic models in information-gathering scenarios, highlighting common practices and existing generic models, and show that existing methods can be categorized into three classes: reactive sensing, single-agent active sensing, and multi-agent active sensing. Finally, we highlight potential research gaps and suggest directions for future research.
40.	Voronkov, Artem, 1990-, et al. (författare) Systematic Literature Review on Usability of Firewall Configuration 2018 Ingår i: ACM Computing Surveys. - New York, NY, USA : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 50:6 Tidskriftsartikel (refereegranskat)abstract Firewalls are network security components that handle incoming and outgoing network traffic based on a set of rules. The process of correctly configuring a firewall is complicated and prone to error, and it worsens as the network complexity grows. A poorly configured firewall may result in major security threats; in the case of a network firewall, an organization’s security could be endangered, and in the case of a personal firewall, an individual computer’s security is threatened. A major reason for poorly configured firewalls, as pointed out in the literature, is usability issues. Our aim is to identify existing solutions that help professional and non-professional users to create and manage firewall configuration files, and to analyze the proposals in respect of usability. A systematic literature review with a focus on the usability of firewall configuration is presented in the article. Its main goal is to explore what has already been done in this field. In the primary selection procedure, 1,202 articles were retrieved and then screened. The secondary selection led us to 35 articles carefully chosen for further investigation, of which 14 articles were selected and summarized. As main contributions, we propose a taxonomy of existing solutions as well as a synthesis and in-depth discussion about the state of the art in firewall usability. Among the main findings, we perceived that there is a lack (or even an absence) of usability evaluation or user studies to validate the proposed models. Although all articles are related to the topic of usability, none of them clearly defines it, and only a few actually employ usability design principles and/or guidelines.
41.	Wang, Benyou, et al. (författare) Pre-trained Language Models in Biomedical Domain : A Systematic Survey 2024 Ingår i: ACM Computing Surveys. - New York, NY : Association for Computing Machinery (ACM). - 0360-0300 .- 1557-7341. ; 56:3 Forskningsöversikt (refereegranskat)abstract Pre-trained language models (PLMs) have been the de facto paradigm for most natural language processing tasks. This also benefits the biomedical domain: researchers from informatics, medicine, and computer science communities propose various PLMs trained on biomedical datasets, e.g., biomedical text, electronic health records, protein, and DNA sequences for various biomedical tasks. However, the cross-discipline characteristics of biomedical PLMs hinder their spreading among communities; some existing works are isolated from each other without comprehensive comparison and discussions. It is nontrivial to make a survey that not only systematically reviews recent advances in biomedical PLMs and their applications but also standardizes terminology and benchmarks. This article summarizes the recent progress of pre-trained language models in the biomedical domain and their applications in downstream biomedical tasks. Particularly, we discuss the motivations of PLMs in the biomedical domain and introduce the key concepts of pre-trained language models. We then propose a taxonomy of existing biomedical PLMs that categorizes them from various perspectives systematically. Plus, their applications in biomedical downstream tasks are exhaustively discussed, respectively. Last, we illustrate various limitations and future trends, which aims to provide inspiration for the future research. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
42.	Winter, Stephan, et al. (författare) Infrastructure-Independent Indoor Localization and Navigation 2019 Ingår i: ACM Computing Surveys. - : ACM Digital Library. - 0360-0300 .- 1557-7341. ; 52:3 Tidskriftsartikel (refereegranskat)abstract In the absence of any global positioning infrastructure for indoor environments, research on supporting human indoor localization and navigation trails decades behind research on outdoor localization and navigation. The major barrier to broader progress has been the dependency of indoor positioning on environment-specific infrastructure and resulting tailored technical solutions. Combined with the fragmentation and compartmentalization of indoor environments, this poses significant challenges to widespread adoption of indoor location-based services. This article puts aside all approaches of infrastructure-based support for human indoor localization and navigation and instead reviews technical concepts that are independent of sensors embedded in the environment. The reviewed concepts rely on a mobile computing platform with sensing capability and a human interaction interface (“smartphone”). This platform may or may not carry a stored map of the environment, but does not require in situ internet access. In this regard, the presented approaches are more challenging than any localization and navigation solutions specific to a particular, infrastructure-equipped indoor space, since they are not adapted to local context, and they may lack some of the accuracy achievable with those tailored solutions. However, only these approaches have the potential to be universally applicable.
43.	Zahid, Maryam, et al. (författare) Model-based Trustworthiness Evaluation of Autonomous Cyber-Physical Production Systems : A Systematic Mapping Study 2024 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery. - 0360-0300 .- 1557-7341. ; 56:6 Tidskriftsartikel (refereegranskat)abstract The fourth industrial revolution, i.e., Industry 4.0, is associated with Cyber-Physical Systems (CPS), which are entities integrating hardware (e.g., smart sensors and actuators connected through the Industrial Internet of Things) together with control and analytics software used to drive and support decisions at several levels. The latest developments in Artificial Intelligence (AI) and Machine Learning (ML) have enabled increased autonomy and closer human-robot cooperation in the production and manufacturing industry, thus leading to Autonomous Cyber-Physical Production Systems (ACPPS) and paving the way to the fifth industrial revolution (i.e., Industry 5.0). ACPPS are increasingly critical due to the possible consequences of their malfunctions on human co-workers, and therefore, evaluating their trustworthiness is essential. This article reviews research trends, relevant attributes, modeling languages, and tools related to the model-based trustworthiness evaluation of ACPPS. As in many other engineering disciplines and domains, model-based approaches, including stochastic and formal analysis tools, are essential to master the increasing complexity and criticality of ACPPS and to prove relevant attributes such as system safety in the presence of intelligent behaviors and uncertainties.
44.	Zimmerling, Marco, et al. (författare) Synchronous Transmissions in Low-Power Wireless : A Survey of Communication Protocols and Network Services 2021 Ingår i: ACM Computing Surveys. - : Association for Computing Machinery. - 0360-0300 .- 1557-7341. ; 53:6 Tidskriftsartikel (refereegranskat)abstract Low-power wireless communication is a central building block of cyber-physical systems and the Internet of Things. Conventional low-power wireless protocols make avoiding packet collisions a cornerstone design choice. The concept of synchronous transmissions challenges this view. As collisions are not necessarily destructive, under specific circumstances, commodity low-power wireless radios are often able to receive useful information even in the presence of superimposed signals from different transmitters. We survey the growing number of protocols that exploit synchronous transmissions for higher robustness and efficiency as well as unprecedented functionality and versatility compared to conventional designs. The illustration of protocols based on synchronous transmissions is cast in a conceptional framework we establish, with the goal of highlighting differences and similarities among the proposed solutions. We conclude this article with a discussion on open questions and challenges in this research field
45.	Zolfaghari, Samaneh, et al. (författare) Sensor-based Locomotion Data Mining for Supporting the Diagnosis of Neurodegenerative Disorders : a Survey 2023 Ingår i: ACM Computing Surveys. - 0360-0300 .- 1557-7341. Tidskriftsartikel (refereegranskat)abstract Locomotion characteristics and movement patterns are reliable indicators of neurodegenerative diseases (NDDs). This survey provides a systematic literature review of locomotion data mining systems for supporting NDDs diagnosis. We discuss techniques for discovering low-level locomotion indicators, sensor data acquisition and processing methods, and NDDs detection algorithms. The survey presents a comprehensive discussion on the main challenges for this active area, including the addressed diseases, locomotion data types, duration of monitoring, employed algorithms, and experimental validation strategies. We also identify prominent open challenges and research directions regarding ethics and privacy issues, technological and usability aspects, and availability of public benchmarks.
46.	Bosch, Jan, et al. (författare) Object-oriented framework-based software development : problems and experiences 2000 Ingår i: ACM Computing Surveys. - 0360-0300. ; 32:1, s. 3-8 Tidskriftsartikel (refereegranskat)
47.	Togerö, Åse (författare) Leaching of hazardous substances from additives and admixtures in concrete 2006 Ingår i: Environmental Engineering Science. - : Mary Ann Liebert Inc. - 1092-8758 .- 1557-9018. ; 23:1, s. 102-117 Tidskriftsartikel (refereegranskat)abstract The aim of this work was to study the leaching of hazardous substances in additives and admixtures that are commonly contained in concrete. Time-dependent leaching has been analyzed for three types of metal containing concretes: with ordinary Portland cement (OPC), fly ash, and slag. The concretes had uniform leaching patterns, clearly above detection limits. The prolonged diffusion test of 1,700 days showed a substantial decline in metal release. There was no significant difference between the concretes with byproducts and the concrete with Portland cement. This study proposes an alternative availability test to NEN 7341, for generation of data for use in models of leaching during the service life of concrete as a monolithic material. The results of the two different availability tests are compared for naturally carbonated and noncarbonated materials and for different particle sizes. The leaching of concrete with admixtures containing thiocyanate, resin acids, or nonylphenol ethoxylate was also studied, because of their toxic character. The thiocyanate was leached with an initial fast dissolution process followed by a slower continuous diffusion process. The leached amount thiocyanate in the availability test was very high, 71%, due to its high solubility. Resin acids from tall oil-based air-entraining agents in concrete had a continuous diffusional leaching that is proportional to the square root of time. The fraction available for leaching was 17% of the added amount of oil and similar to 20-30% of the added amount of nonylphenol ethoxylates. In addition to nonylphenol ethoxylate, nonylphenol was determined-a more toxic, genotoxic and low-degradable substance.

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