Computer Engineering Commons^™

A Proof-Theoretic Semantic Analysis Of Dynamic Epistemic Logic, Sabine Frittella, Giuseppe Greco, Alexander Kurz, Alessandra Palmigiano, Vlasta Sikimić

Engineering Faculty Articles and Research

The present paper provides an analysis of the existing proof systems for dynamic epistemic logic from the viewpoint of proof-theoretic semantics. Dynamic epistemic logic is one of the best known members of a family of logical systems which have been successfully applied to diverse scientific disciplines, but the proof theoretic treatment of which presents many difficulties. After an illustration of the proof-theoretic semantic principles most relevant to the treatment of logical connectives, we turn to illustrating the main features of display calculi, a proof-theoretic paradigm which has been successfully employed to give a proof-theoretic semantic account of modal and substructural …

Inferring Memory Map Instructions, Paul T. Scheid, Ari J. Spilo, Ron K. Cytron

All Computer Science and Engineering Research

We describe the problem of inferring a set of memory map instructions from a reference trace, with the goal of minimizing the number of such instructions as well as the number of unreferenced but mapped storage locations. We prove the related decision problem NP-complete. We then present and compare the results of two heuristic approaches on some actual traces.

Translation Of 'Seasons Of Life: A Panoramic Selection Of Songs By Rabindranath Tagore', Monish Ranjan Chatterjee

Electrical and Computer Engineering Faculty Publications

No abstract provided.

Scalable Approximation Of Kernel Fuzzy C-Means, Zijian Zhang

Dissertations, Master's Theses and Master's Reports - Open

Virtually every sector of business and industry that uses computing, including financial analysis, search engines, and electronic commerce, incorporate Big Data analysis into their business model. Sophisticated clustering algorithms are popular for deducing the nature of data by assigning labels to unlabeled data. We address two main challenges in Big Data. First, by definition, the volume of Big Data is too large to be loaded into a computer’s memory (this volume changes based on the computer used or available, but there is always a data set that is too large for any computer). Second, in real-time applications, the velocity of …

Cgt 256: User-Centered (Re)Design, Mihaela Vorvoreanu

IMPACT Symposium

The poster presented at the IMPACT Symposium 2014 outlines the redesign of of CGT 256: User Centered Design.

Communication Protocol Design Considerations For Highway Vehicle Platoons And Enhanced Networked Robustness By Stochastic Dithers, Lijian Xu

Wayne State University Dissertations

Highway platooning of vehicles has been identified as a promising framework in

developing intelligent transportation systems. By autonomous or semi-autonomous

vehicle control and inter-vehicle coordination, an appropriately managed platoon can

potentially offer enhanced safety, improved highway utility, increased fuel economy,

and reduced emission. This thesis is focused on quantitative characterization of impact

of communication information structures and contents on platoon safety. By

comparing different information structures which combine front sensors, rear sensors,

and wireless communication channels, and different information contents such

as distances, speeds, and drivers' actions, we reveal a number of intrinsic relationships

between vehicle coordination and communications in …

Building A Scalable And High-Performance Key-Value Store System, Yuehai Xu

Wayne State University Dissertations

Contemporary web sites can store and process very large amounts of data. To provide timely service to their users, they have adopted key-value (KV) stores, which is a simple but effective caching infrastructure atop the conventional databases that store these data, to boost performance. Examples are Facebook, Twitter and Amazon. As yet little is known about the realistic workloads outside of the companies that operate them, this dissertation work provides a detailed workload study on Facebook's Memcached, which is one of the world's largest KV deployment. We analyze the Memcached workload from the perspective of server-side performance, request composition, caching …

Development And Human Performance Evaluation Of Control Modes Of An Exo-Skeletal Assistive Robotic Arm (Esara), Umer Khalid

Wayne State University Dissertations

This research was conducted to assist with functional tasks for a targeted group of individuals with spinal cord injury (SCI); with C5 to C7 level of injury relating to upper extremity movement. The specific population was selected as the existing technology was either too expensive, too bulky or was unable to address their needs in regards to upper extremity mobility. In addition, no platforms allowed multimodal control options for customization or provided a methodology for this crucial evaluation. The motivation of this research was to provide a methodology for selecting the appropriate control of an assistive device based on the …

Evaluation And Analysis Of Distributed Graph-Parallel Processing Frameworks, Yue Zhao, Kenji Yoshigoe, Mengjun Xie, Suijian Zhou, Remzi Seker, Jiang Bian

Publications

A number of graph-parallel processing frameworks have been proposed to address the needs of processing complex and large-scale graph structured datasets in recent years. Although significant performance improvement made by those frameworks were reported, comparative advantages of each of these frameworks over the others have not been fully studied, which impedes the best utilization of those frameworks for a specific graph computing task and setting. In this work, we conducted a comparison study on parallel processing systems for large-scale graph computations in a systematic manner, aiming to reveal the characteristics of those systems in performing common graph algorithms with real-world …

Solving A New Bi-Objective Joint Replenishment Inventory Model With Modified Rand And Genetic Algorithms, Ommolbanin Yousefi, Seyed Jafar Sadjadi

Turkish Journal of Electrical Engineering and Computer Sciences

There are many cases in real inventory systems where more than one objective must be optimized. The main purpose of this research is to develop a multiobjective joint replenishment problem (JRP), where one objective is the minimization of the total inventory investment and another is the minimization of the total inventory ordering and holding costs. To solve the suggested model, 3 algorithms are proposed. In the first algorithm, the existing RAND method, called the best heuristic for solving the JRP, is modified and a new heuristic algorithm is developed to be applicable to the JRP with 2 objectives. The second …

Contrast Enhancement Using Linear Image Combinations Algorithm (Ceulica) For Enhancing Brain Magnetic Resonance Images, Burak Yilmaz, Yüksel Özbay

Turkish Journal of Electrical Engineering and Computer Sciences

Brain magnetic resonance imaging (MRI) images support important information about brain diseases for physicians. Morphological alterations in brain tissues indicate the probable existence of a disease in many cases. Proper estimation of these tissues, measuring their sizes, and analyzing their image patterns are parts of the diagnosis process. Therefore, the interpretability and perceptibility level of the MRI image is valuable for physicians. In this paper, a new image contrast enhancement algorithm based on linear combinations is presented. The proposed algorithm is focused on improving the interpretability and perceptibility of the image information. An MRI image is presented to the algorithm, …

Online Feature Selection And Classification With Incomplete Data, Habi̇l Kalkan

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a classification system in which learning, feature selection, and classification for incomplete data are simultaneously carried out in an online manner. Learning is conducted on a predefined model including the class-dependent mean vectors and correlation coefficients, which are obtained by incrementally processing the incoming observations with missing features. A nearest neighbor with a Gaussian mixture model, whose parameters are also estimated from the trained model, is used for classification. When a testing observation is received, the algorithm discards the missing attributes on the observation and ranks the available features by performing feature selection on the model that …

Model-Free Controller With An Observer Applied In Real-Time To A 3-Dof Helicopter, Ahsene Boubakir, Salim Labiod, Fares Boudjema, Franck Plestan

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a model-free controller with an observer is presented for a class of uncertain continuous-time multiinput-multioutput nonlinear dynamic systems. The proposed model-free control law consists of 2 parts: the first part is a linear control term used to specify the dynamics of the closed loop system, and the second part is a compensator of the effects of uncertainties and external disturbances. The compensator is synthesized from an estimator of the effects of uncertainties and disturbances based on the Lyapunov approach. In order to estimate the unavailable states of the controlled system, a linear state observer is designed. All …

A User-Oriented Network Forensic Analyser: The Design Of A High-Level Protocol Analyser, D Joy, F Li, N L. Clarke, S M. Furnell

Australian Digital Forensics Conference

Network forensics is becoming an increasingly important tool in the investigation of cyber and computer-assisted crimes. Unfortunately, whilst much effort has been undertaken in developing computer forensic file system analysers (e.g. Encase and FTK), such focus has not been given to Network Forensic Analysis Tools (NFATs). The single biggest barrier to effective NFATs is the handling of large volumes of low-level traffic and being able to exact and interpret forensic artefacts and their context – for example, being able extract and render application-level objects (such as emails, web pages and documents) from the low-level TCP/IP traffic but also understand how …

Fragment Association Matching Enhancement (Fame) On A Video Tracker, Andrew Johnson

Browse all Theses and Dissertations

In the field of surveillance, algorithms are developed to extract meaningful information out of a video feed captured via a camera. One type of algorithm used in the field of surveillance is a tracking algorithm. A tracking algorithm allows a user to watch the movement of an object in the camera's field of view. The tracker used in this thesis research is a feature aided tracker (FAT). The FAT uses both features and kinematics to generate tracks. However, camera movement will affect the tracker's ability to accurately track an object which poses a problem to the tracker. Specifically, the camera …

Combating Integrity Attacks In Industrial Control Systems, Chad Arnold

Browse all Theses and Dissertations

Industrial Control Systems are vulnerable to integrity attacks because of connectivity to the external Internet and trusted internal networking components that can become compromised. Integrity attacks can be modeled, analyzed, and sometimes remedied by exploiting properties of physical devices and reasoning about the trust worthiness of ICS communication components.

Industrial control systems (ICS) monitor and control the processes of public utility that society depends on - the electric power grid, oil and gas pipelines, transportation, and water facilities. Attacks that impact the operations of these critical assets could have devastating consequences. The complexity and desire to interconnect ICS components have …

A Novel Synergistic Model Fusing Electroencephalography And Functional Magnetic Resonance Imaging For Modeling Brain Activities, Konstantinos Michalopoulos

Browse all Theses and Dissertations

Study of the human brain is an important and very active area of research. Unraveling the way the human brain works would allow us to better understand, predict and prevent brain related diseases that affect a significant part of the population. Studying the brain response to certain input stimuli can help us determine the involved brain areas and understand the mechanisms that characterize behavioral and psychological traits.

In this research work two methods used for the monitoring of brain activities, Electroencephalography (EEG) and functional Magnetic Resonance (fMRI) have been studied for their fusion, in an attempt to bridge together the …

Automated Complexity-Sensitive Image Fusion, Brian Patrick Jackson

Browse all Theses and Dissertations

To construct a complete representation of a scene with environmental obstacles such as fog, smoke, darkness, or textural homogeneity, multisensor video streams captured in diferent modalities are considered. A computational method for automatically fusing multimodal image streams into a highly informative and unified stream is proposed. The method consists of the following steps: 1. Image registration is performed to align video frames in the visible band over time, adapting to the nonplanarity of the scene by automatically subdividing the image domain into regions approximating planar patches

2. Wavelet coefficients are computed for each of the input frames in each modality …

Adapting Linguistic Deception Cues For Malware Detection, Stacie Noel Severyn

Browse all Theses and Dissertations

People verbally express themselves in a variety of ways, yet the same patterns consistently appear within the words of a person who is being deceptive. This research provides insight and demonstrates that similar patterns exist within malicious software that do not commonly exist within benign software, and can be used to help determine that the software is malicious or untrustworthy.

The patterns that have been shown to exist within deceptive language were investigated to determine whether similar patterns exist within malware. Tests were performed to determine whether malware is more likely to consistently contain a higher or lower frequency of …

The Properties Of Property Alignment On The Semantic Web, Michelle Andreen Cheatham

Browse all Theses and Dissertations

Ontology alignment is an important step in enabling computers to query and reason across the many linked datasets on the semantic web. This is a difficult challenge because the ontologies underlying different linked datasets can vary in terms of subject area coverage, level of abstraction, ontology modeling philosophy, and even language. The alignment approach presented here centers on string similarity metrics. Nearly all ontology alignment systems use a string similarity metric in one form or another, but it seems that the choice of a particular metric is often arbitrary. We begin this dissertation with the most comprehensive survey to date …