| 1. |
- Chatterjee, Bapi, 1982
(författare)
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Lock-free Concurrent Search
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The contemporary computers typically consist of multiple computing cores with high compute power. Such computers make excellent concurrent asynchronous shared memory system. On the other hand, though many celebrated books on data structure and algorithm provide a comprehensive study of sequential search data structures, unfortunately, we do not have such a luxury if concurrency comes in the setting. The present dissertation aims to address this paucity. We describe novel lock-free algorithms for concurrent data structures that target a variety of search problems. (i) Point search (membership query, predecessor query, nearest neighbour query) for 1-dimensional data: Lock-free linked-list; lock-free internal and external binary search trees (BST). (ii) Range search for 1-dimensional data: A range search method for lock-free ordered set data structures - linked-list, skip-list and BST. (iii) Point search for multi-dimensional data: Lock-free kD-tree, specially, a generic method for nearest neighbour search. We prove that the presented algorithms are linearizable i.e. the concurrent data structure operations intuitively display their sequential behaviour to an observer of the concurrent system. The lock-freedom in the introduced algorithms guarantee overall progress in an asynchronous shared memory system. We present the amortized analysis of lock-free data structures to show their efficiency. Moreover, we provide sample implementations of the algorithms and test them over extensive micro-benchmarks. Our experiments demonstrate that the implementations are scalable and perform well when compared to related existing alternative implementations on common multi-core computers. Our focus is on propounding the generic methodologies for efficient lock-free concurrent search. In this direction, we present the notion of help-optimality, which captures the optimization of amortized step complexity of the operations. In addition to that, we explore the language-portable design of lock-free data structures that aims to simplify an implementation from programmer’s point of view. Finally, our techniques to implement lock-free linearizable range search and nearest neighbour search are independent of the underlying data structures and thus are adaptive to similar data structures.
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| 2. |
- Ali, Muhaddisa Barat, 1986
(författare)
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Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The most common type of brain cancer in adults are gliomas. Under the updated 2016 World Health Organization (WHO) tumor classification in central nervous system (CNS), identification of molecular subtypes of gliomas is important. For low grade gliomas (LGGs), prediction of molecular subtypes by observing magnetic resonance imaging (MRI) scans might be difficult without taking biopsy. With the development of machine learning (ML) methods such as deep learning (DL), molecular based classification methods have shown promising results from MRI scans that may assist clinicians for prognosis and deciding on a treatment strategy. However, DL requires large amount of training datasets with tumor class labels and tumor boundary annotations. Manual annotation of tumor boundary is a time consuming and expensive process. The thesis is based on the work developed in five papers on gliomas and their molecular subtypes. We propose novel methods that provide improved performance. The proposed methods consist of a multi-stream convolutional autoencoder (CAE)-based classifier, a deep convolutional generative adversarial network (DCGAN) to enlarge the training dataset, a CycleGAN to handle domain shift, a novel federated learning (FL) scheme to allow local client-based training with dataset protection, and employing bounding boxes to MRIs when tumor boundary annotations are not available. Experimental results showed that DCGAN generated MRIs have enlarged the original training dataset size and have improved the classification performance on test sets. CycleGAN showed good domain adaptation on multiple source datasets and improved the classification performance. The proposed FL scheme showed a slightly degraded performance as compare to that of central learning (CL) approach while protecting dataset privacy. Using tumor bounding boxes showed to be an alternative approach to tumor boundary annotation for tumor classification and segmentation, with a trade-off between a slight decrease in performance and saving time in manual marking by clinicians. The proposed methods may benefit the future research in bringing DL tools into clinical practice for assisting tumor diagnosis and help the decision making process.
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| 3. |
- Homem, Irvin, 1985-
(författare)
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Advancing Automation in Digital Forensic Investigations
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Digital Forensics is used to aid traditional preventive security mechanisms when they fail to curtail sophisticated and stealthy cybercrime events. The Digital Forensic Investigation process is largely manual in nature, or at best quasi-automated, requiring a highly skilled labour force and involving a sizeable time investment. Industry standard tools are evidence-centric, automate only a few precursory tasks (E.g. Parsing and Indexing) and have limited capabilities of integration from multiple evidence sources. Furthermore, these tools are always human-driven.These challenges are exacerbated in the increasingly computerized and highly networked environment of today. Volumes of digital evidence to be collected and analyzed have increased, and so has the diversity of digital evidence sources involved in a typical case. This further handicaps digital forensics practitioners, labs and law enforcement agencies, causing delays in investigations and legal systems due to backlogs of cases. Improved efficiency of the digital investigation process is needed, in terms of increasing the speed and reducing the human effort expended. This study aims at achieving this time and effort reduction, by advancing automation within the digital forensic investigation process.Using a Design Science research approach, artifacts are designed and developed to address these practical problems. Summarily, the requirements, and architecture of a system for automating digital investigations in highly networked environments are designed. The architecture initially focuses on automation of the identification and acquisition of digital evidence, while later versions focus on full automation and self-organization of devices for all phases of the digital investigation process. Part of the remote evidence acquisition capability of this system architecture is implemented as a proof of concept. The speed and reliability of capturing digital evidence from remote mobile devices over a client-server paradigm is evaluated. A method for the uniform representation and integration of multiple diverse evidence sources for enabling automated correlation, simple reasoning and querying is developed and tested. This method is aimed at automating the analysis phase of digital investigations. Machine Learning (ML)-based triage methods are developed and tested to evaluate the feasibility and performance of using such techniques to automate the identification of priority digital evidence fragments. Models from these ML methods are evaluated in identifying network protocols within DNS tunneled network traffic. A large dataset is also created for future research in ML-based triage for identifying suspicious processes for memory forensics.From an ex ante evaluation, the designed system architecture enables individual devices to participate in the entire digital investigation process, contributing their processing power towards alleviating the burden on the human analyst. Experiments show that remote evidence acquisition of mobile devices over networks is feasible, however a single-TCP-connection paradigm scales poorly. A proof of concept experiment demonstrates the viability of the automated integration, correlation and reasoning over multiple diverse evidence sources using semantic web technologies. Experimentation also shows that ML-based triage methods can enable prioritization of certain digital evidence sources, for acquisition or analysis, with up to 95% accuracy.The artifacts developed in this study provide concrete ways to enhance automation in the digital forensic investigation process to increase the investigation speed and reduce the amount of costly human intervention needed.
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| 4. |
- Mohseni, Zeynab (Artemis)
(författare)
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Development of Visual Learning Analytic Tools to Explore Performance and Engagement of Students in Primary, Secondary, and Higher Education
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Schools and educational institutions collect large amounts of data about students and their learning, including text, grades, quizzes, timestamps, and other activities. However, in primary and secondary education, this data is often dispersed across different digital platforms, lacking standardized methods for collection, processing, analysis, and presentation. These issues hinder teachers and students from making informed decisions or strategic and effective use of data. This presents a significant obstacle to progress in education and the effective development of Educational Technology (EdTech) products. Visual Learning Analytics (VLA) tools, also known as Learning Analytics Dashboards (LADs), are designed to visualize student data to support pedagogical decision-making. Despite their potential, the effectiveness of these tools remains limited. Addressing these challenges requires both technical solutions and thoughtful design considerations, as explored in Papers 1 through 5 of this thesis. Paper 1 examines the design aspects of VLA tools by evaluating higher education data and various visualization and Machine Learning (ML) techniques. Paper 2 provides broader insights into the VLA landscape through a systematic review, mapping key concepts and research gaps in VLA and emphasizing the potential of VLA tools to enhance pedagogical decisions and learning outcomes. Meanwhile, Paper 3 delves into a technical solution (data pipeline and data standard) considering a secure Swedish warehouse, SUNET. This includes a data standard for integrating educational data into SUNET, along with customized scripts to reformat, merge, and hash multiple student datasets. Papers 4 and 5 focus on design aspects, with Paper 4 discussing the proposed Human-Centered Design (HCD) approach involving teachers in co-designing a simple VLA tool. Paper 5 introduces a scenario-based framework for Multiple Learning Analytics Dashboards (MLADs) development, stressing user engagement for tailored LADs that facilitate informed decision-making in education. The dissertation offers a comprehensive approach to advancing VLA tools, integrating technical solutions with user-centric design principles. By addressing data integration challenges and involving users in tool development, these efforts aim to empower teachers in leveraging educational data for improved teaching and learning experiences.
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| 5. |
- Vogel, Bahtijar, 1980-
(författare)
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An Open Architecture Approach for the Design and Development of Web and Mobile Software
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The rapid evolution of web and mobile technologies as well as open standards are important ingredients for developing open software applications. HTML5, affordable electronics, and connectivity costs are some of the trends that drive the web towards an open platform and lead to an increased use of distributed applications. Proprietary software technologies have been extensively deployed throughout multiple platforms, including desktop, web, and mobile systems. Such systems are closed in many cases. Thus, it is rather difficult to expand existing and create additional features for them. Web and mobile software development is fragmented with the existence of multiple browsers and mobile operating systems, that comply differently with web standards. The evolution of web and mobile technologies, coupled with the changes in the deployment environments in which they operate, has resulted in complex requirements that are challenging to satisfy. Additionally, the largest part of the development lifecycle is related to the need to constantly change/modify these software systems within a short-time period. The fact that these systems evolve over time makes it difficult to meet the changing requirements.In this thesis, we offer a novel open architecture approach in the area of web and mobile software design and development when dealing with heterogeneous device environments, together with constantly evolving and dynamic requirements. This approach is grounded on our experiences gained during the last four years of project work regarding the development of a web and mobile software system to support mobile inquiry learning. This case served as a testbed for experimentation with heterogeneous device environments. After five development iterations, our software solution is considered robust, flexible, and expandable as a platform. Among others, this was validated with being tested with more than 500 users. The open architecture approach is also grounded on a literature survey of state of the art projects and definitions related to this concept. The outcomes of this thesis show that an open architecture approach is characterized by flexibility, customizability, and extensibility, which are instantiated into a set of properties. The importance of stressing these three characteristics and their properties in the open architecture approach is based on the identified needs of using open source components, using open data standards, and reducing development time. The research efforts in this thesis resulted in a refined definition of an open architecture approach as well as the initial and refined models that are contextualized within the field of web and mobile software. For validation of the research, the Goal Question Metric (GQM) approach is adapted and extended with a layer of Tasks/Activities. The data is collected from the project work mentioned above and three follow-up cases. The results show that the benefits of an open architecture approach can be reflected in terms of: achievement of the software system’s long-term goals; reduced development time; and increased satisfaction of the users. These benefits refer to the possibility to easily adapt emerging technologies and address dynamic changes and requirements. The contributions of this thesis are threefold: (1) for researchers, our open architecture approach could be used to analyze a system from a top down perspective; (2) for developers, it could be used as an approach to identify and address the needs for building an open evolvable system from a bottom up perspective; (3) for domain experts in the technology enhanced learning field, it could be used as a sustainability approach through which to integrate new tools and address complex requirements when designing new educational activities.
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| 6. |
- Svärd, Malin, 1985
(författare)
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Computational driver behavior models for vehicle safety applications
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The aim of this thesis is to investigate how human driving behaviors can be formally described in mathematical models intended for online personalization of advanced driver assistance systems (ADAS) or offline virtual safety evaluations. Both longitudinal (braking) and lateral (steering) behaviors in routine driving and emergencies are addressed. Special attention is paid to driver glance behavior in critical situations and the role of peripheral vision. First, a hybrid framework based on autoregressive models with exogenous input (ARX-models) is employed to predict and classify driver control in real time. Two models are suggested, one targeting steering behavior and the other longitudinal control behavior. Although the predictive performance is unsatisfactory, both models can distinguish between different driving styles. Moreover, a basic model for drivers' brake initiation and modulation in critical longitudinal situations (specifically for rear-end conflicts) is constructed. The model is based on a conceptual framework of noisy evidence accumulation and predictive processing. Several model extensions related to gaze behavior are also proposed and successfully fitted to real-world crashes and near-crashes. The influence of gaze direction is further explored in a driving simulator study, showing glance response times to be independent of the glance's visual eccentricity, while brake response times increase for larger gaze angles, as does the rate of missed target detections. Finally, the potential of a set of metrics to quantify subjectively perceived risk in lane departure situations to explain drivers' recovery steering maneuvers was investigated. The most influential factors were the relative yaw angle and splay angle error at steering initiation. Surprisingly, it was observed that drivers often initiated the recovery steering maneuver while looking off-road. To sum up, the proposed models in this thesis facilitate the development of personalized ADASs and contribute to trustworthy virtual evaluations of current, future, and conceptual safety systems. The insights and ideas contribute to an enhanced, human-centric system development, verification, and validation process. In the long term, this will likely lead to improved vehicle safety and a reduced number of severe injuries and fatalities in traffic.
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| 7. |
- Brunetta, Carlo, 1992
(författare)
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Cryptographic Tools for Privacy Preservation
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Data permeates every aspect of our daily life and it is the backbone of our digitalized society. Smartphones, smartwatches and many more smart devices measure, collect, modify and share data in what is known as the Internet of Things. Often, these devices don’t have enough computation power/storage space thus out-sourcing some aspects of the data management to the Cloud. Outsourcing computation/storage to a third party poses natural questions regarding the security and privacy of the shared sensitive data. Intuitively, Cryptography is a toolset of primitives/protocols of which security prop- erties are formally proven while Privacy typically captures additional social/legislative requirements that relate more to the concept of “trust” between people, “how” data is used and/or “who” has access to data. This thesis separates the concepts by introducing an abstract model that classifies data leaks into different types of breaches. Each class represents a specific requirement/goal related to cryptography, e.g. confidentiality or integrity, or related to privacy, e.g. liability, sensitive data management and more. The thesis contains cryptographic tools designed to provide privacy guarantees for different application scenarios. In more details, the thesis: (a) defines new encryption schemes that provide formal privacy guarantees such as theoretical privacy definitions like Differential Privacy (DP), or concrete privacy-oriented applications covered by existing regulations such as the European General Data Protection Regulation (GDPR); (b) proposes new tools and procedures for providing verifiable computation’s guarantees in concrete scenarios for post-quantum cryptography or generalisation of signature schemes; (c) proposes a methodology for utilising Machine Learning (ML) for analysing the effective security and privacy of a crypto-tool and, dually, proposes a secure primitive that allows computing specific ML algorithm in a privacy-preserving way; (d) provides an alternative protocol for secure communication between two parties, based on the idea of communicating in a periodically timed fashion.
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| 8. |
- Tsaloli, Georgia, 1993
(författare)
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Secure and Privacy-Preserving Cloud-Assisted Computing
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Smart devices such as smartphones, wearables, and smart appliances collect significant amounts of data and transmit them over the network forming the Internet of Things (IoT). Many applications in our daily lives (e.g., health, smart grid, traffic monitoring) involve IoT devices that often have low computational capabilities. Subsequently, powerful cloud servers are employed to process the data collected from these devices. Nevertheless, security and privacy concerns arise in cloud-assisted computing settings. Collected data can be sensitive, and it is essential to protect their confidentiality. Additionally, outsourcing computations to untrusted cloud servers creates the need to ensure that servers perform the computations as requested and that any misbehavior can be detected, safeguarding security. Cryptographic primitives and protocols are the foundation to design secure and privacy-preserving solutions that address these challenges. This thesis focuses on providing privacy and security guarantees when outsourcing heavy computations on sensitive data to untrusted cloud servers. More concretely, this work: (a) provides solutions for outsourcing the secure computation of the sum and the product functions in the multi-server, multi-client setting, protecting the sensitive data of the data owners, even against potentially untrusted cloud servers; (b) provides integrity guarantees for the proposed protocols, by enabling anyone to verify the correctness of the computed function values. More precisely, the employed servers or the clients (depending on the proposed solution) provide specific values which are the proofs that the computed results are correct; (c) designs decentralized settings, where multiple cloud servers are employed to perform the requested computations as opposed to relying on a single server that might fail or lose connection; (d) suggests ways to protect individual privacy and provide integrity. More pre- cisely, we propose a verifiable differentially private solution that provides verifiability and avoids any leakage of information regardless of the participa- tion of some individual’s sensitive data in the computation or not.
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| 9. |
- Jalali, Amin, 1980-
(författare)
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Aspect-Oriented Business Process Management
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Separation of concerns has long been considered an effective and efficient strategy to deal with complexity in information systems.One sort of concern, like security and privacy, crosses over other concerns in a system. Such concerns are called cross-cutting concerns.As a result, the realization of these concerns is scattered through the whole system, which makes their management difficult.Aspect Orientation is a paradigm in information systems which aims to modularize cross-cutting concerns.This paradigm is well researched in the programming area, where many aspect-oriented programming languages have been developed, e.g., AspectJ.It has also been investigated in other areas, such as requirement engineering and service composition.In the Business Process Management (BPM) area, Aspect Oriented Business Process Modeling aims to specify how this modularization technique can support encapsulating cross-cutting concerns in process models.However, it is not clear how these models should be supported in the whole BPM lifecycle.In addition, the support for designing these models has only been limited to imperative process models that support rigid business processes.Neither has it been investigated how this modularization technique can be supported through declarative or hybrid models to support the separation of cross-cutting concerns for flexible business processes.Therefore, this thesis investigates how aspect orientation can be supported over the whole BPM lifecycle using imperative aspect-oriented business process models. It also investigates how declarative and hybrid aspect-oriented business process models can support the separation of cross-cutting concerns in the BPM area.This thesis has been carried out following the design science framework, and the result is presented as a set of artifacts (in the form of constructs, models, methods, and instantiations) and empirical findings.The artifacts support modeling, analysis, implementation/configuration, enactment, monitoring, adjustment, and mining cross-cutting concerns while supporting business processes using Business Process Management Systems. Thus, it covers the support for the management of these concerns over the whole BPM lifecycle. The use of these artifacts and their application shows that they can reduce the complexity of process models by separating different concerns.
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| 10. |
- ur Réhman, Shafiq, 1978-
(författare)
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Expressing emotions through vibration for perception and control
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis addresses a challenging problem: “how to let the visually impaired ‘see’ others emotions”. We, human beings, are heavily dependent on facial expressions to express ourselves. A smile shows that the person you are talking to is pleased, amused, relieved etc. People use emotional information from facial expressions to switch between conversation topics and to determine attitudes of individuals. Missing emotional information from facial expressions and head gestures makes the visually impaired extremely difficult to interact with others in social events. To enhance the visually impaired’s social interactive ability, in this thesis we have been working on the scientific topic of ‘expressing human emotions through vibrotactile patterns’. It is quite challenging to deliver human emotions through touch since our touch channel is very limited. We first investigated how to render emotions through a vibrator. We developed a real time “lipless” tracking system to extract dynamic emotions from the mouth and employed mobile phones as a platform for the visually impaired to perceive primary emotion types. Later on, we extended the system to render more general dynamic media signals: for example, render live football games through vibration in the mobile for improving mobile user communication and entertainment experience. To display more natural emotions (i.e. emotion type plus emotion intensity), we developed the technology to enable the visually impaired to directly interpret human emotions. This was achieved by use of machine vision techniques and vibrotactile display. The display is comprised of a ‘vibration actuators matrix’ mounted on the back of a chair and the actuators are sequentially activated to provide dynamic emotional information. The research focus has been on finding a global, analytical, and semantic representation for facial expressions to replace state of the art facial action coding systems (FACS) approach. We proposed to use the manifold of facial expressions to characterize dynamic emotions. The basic emotional expressions with increasing intensity become curves on the manifold extended from the center. The blends of emotions lie between those curves, which could be defined analytically by the positions of the main curves. The manifold is the “Braille Code” of emotions. The developed methodology and technology has been extended for building assistive wheelchair systems to aid a specific group of disabled people, cerebral palsy or stroke patients (i.e. lacking fine motor control skills), who don’t have ability to access and control the wheelchair with conventional means, such as joystick or chin stick. The solution is to extract the manifold of the head or the tongue gestures for controlling the wheelchair. The manifold is rendered by a 2D vibration array to provide user of the wheelchair with action information from gestures and system status information, which is very important in enhancing usability of such an assistive system. Current research work not only provides a foundation stone for vibrotactile rendering system based on object localization but also a concrete step to a new dimension of human-machine interaction.
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