Estimating the Parameters of Software Reliability Growth Models Using the Grey Wolf Optimization Algorithm - Sheta, Alaa F.; Abdel-Raouf, Amal (International Journal of Advanced Computer Science and Applications (IJACSA), 2016)
In this age of technology, building quality software is essential to competing in the business market. One of the major principles required for any quality and business software product for value fulfillment is reliability. Estimating software reliability early during the software development life cycle saves time and money as it prevents spending larger sums fixing a defective software product after deployment. The Software Reliability Growth Model (SRGM) can be used to predict the number of failures that may be encountered during the software testing process. In this paper we explore the advantages of the Grey Wolf Optimization (GWO) algorithm in estimating the SRGM’s parameters with the objective of minimizing the difference between the estimated and the actual number of failures of the software system. We evaluated three different software reliability growth models: the Exponential Model (EXPM), the Power Model (POWM) and the Delayed S-Shaped Model (DSSM). In addition, we used three different datasets to conduct an experimental study in order to show the effectiveness of our approach.
Number: 4
Keywords: dept.csc; peer-reviewed

Statistical Models for Predicting a Patient’s Respiratory Disturbance Index - Park, Jangwoon; Sheta, Alaa; Surani, Salim (CHEST, 2019)
SESSION TITLE: Clinical Prediction and Diagnosis of OSA
Keywords: dept.csc

Evolving neural networks using bird swarm algorithm for data classification and regression applications - Aljarah, Ibrahim; Faris, Hossam; Mirjalili, Seyedali; Al-Madi, Nailah; Sheta, Alaa; Mafarja, Majdi (Cluster Computing, 2019)
This work proposes a new evolutionary multilayer perceptron neural networks using the recently proposed Bird Swarm Algorithm. The problem of finding the optimal connection weights and neuron biases is first formulated as a minimization problem with mean square error as the objective function. The BSA is then used to estimate the global optimum for this problem. A comprehensive comparative study is conducted using 13 classification datasets, three function approximation datasets, and one real-world case study (Tennessee Eastman chemical reactor problem) to benchmark the performance of the proposed evolutionary neural network. The results are compared with well-regarded conventional and evolutionary trainers and show that the proposed method provides very competitive results. The paper also considers a deep analysis of the results, revealing the flexibility, robustness, and reliability of the proposed trainer when applied to different datasets.
Keywords: Bird Swarm Algorithm; Classification; Multilayer perceptron; Neural networks; Optimization; Regression; dept.csc; peer-reviewed

Diagnosis of Sleep Apnea Using Artificial Neural Network and Binary Particle Swarm Optimization for Feature Selection - Surani, Salim; Sheta, Alaa; Turabieh, Hamza; Park, Jangwoon; Mathur, Sunil; Katangur, Ajay (CHEST, 2019)
SESSION TITLE: Clinical Prediction and Diagnosis of OSA
Keywords: dept.csc

Collision-Free Autonomous Robot Navigation in Unknown Environments Utilizing PSO for Path Planning - Krell, Evan; Sheta, Alaa; Balasubramanian, Arun Prassanth Ramaswamy; King, Scott A. (Journal of Artificial Intelligence and Soft Computing Research, 2019)
AbstractThe autonomous navigation of robots in unknown environments is a challenge since it needs the integration of a several subsystems to implement different functionality. It needs drawing a map of the environment, robot map localization, motion planning or path following, implementing the path in real-world, and many others; all have to be implemented simultaneously. Thus, the development of autonomous robot navigation (ARN) problem is essential for the growth of the robotics field of research. In this paper, we present a simulation of a swarm intelligence method is known as Particle Swarm Optimization (PSO) to develop an ARN system that can navigate in an unknown environment, reaching a pre-defined goal and become collision-free. The proposed system is built such that each subsystem manipulates a specific task which integrated to achieve the robot mission. PSO is used to optimize the robot path by providing several waypoints that minimize the robot traveling distance. The Gazebo simulator was used to test the response of the system under various envirvector representing a solution to the optimization problem.onmental conditions. The proposed ARN system maintained robust navigation and avoided the obstacles in different unknown environments. vector representing a solution to the optimization problem.
Keywords: dept.csc; peer-reviewed

Adaboosting Model for Detecting Osa - Surani, Salim; Sheta, Alaa; Turabieh, Hamza; Subramanian, Shyamsunder (CHEST, 2019)
SESSION TITLE: Clinical Prediction and Diagnosis of OSA
Keywords: dept.csc

The Use of Census-Based Geographic Automata Systems in Understanding the Spread of Infectious Disease. - Vitale, Joseph (2010)
Keywords: dept.csc; faculty_collection; sabbatical_report

Big Data Framework - Abdel-Raouf, Amal (2016)
The objective of my sabbatical leave project was to propose a new scheduling algorithm that extends the current MapReduce model to improve system performance. MapReduce, which has been popularized by Google, is a scalable tool that enables the processing of massive volumes of data.
Keywords: dept.csc; faculty_collection; sabbatical_report

Sabbatical leave report: Spring 2014 - Antonios, Imad (2014)
the page describes the 3 projects Antonios completed: Data Network Traffic Analysis, Gossiping Algorithm Development and Analysis, and ZigBee Networks
Keywords: dept.csc; faculty_collection; sabbatical_report

A Platform for Development and Test of Spatio-Temporal Algorithms. - Seyed, Taraneh Baradaran (2011)
In-depth research of theoretical foundations of spatio-temporal databases and their indexing, leading to the development of software.
Keywords: dept.csc; faculty_collection; sabbatical_report

Zigbee Wireless Sensor and Control Network - Elahi, Ata; Gschwender, Adam (Prentice Hall, 2010)
Topics include: Fundamental wireless concepts: OSI Model, error detection, the ISM Band, modulation, WLAN, FHSS, DSSS, Wireless MANs, Bluetooth ; ZigBee essentials: applications, characteristics, device types, topologies, protocol architecture, and expanded ZigBee PRO features ; Physical layer: includes frequency bands, data rate, channels, data/management services, transmitter power, and receiver sensitivity ; MAC layer: data/management services, MAC layer information base, access methods, and frames ; Network layer: data entities, NIB, device configuration, starting network, addressing, discovery, channel scanning ; Application support sublayer and application layer: includes profiles, cluster format, attributes, device discovery, and binding ; ZigBee network security: includes encryption, trust center, security modes, and security management primitives ; Address assignment and routing techniques ; Alternative technologies: 6lowpan, WirelessHART, and Z-wave.:–pub. desc.
Keywords: Industrial applications; Industrial applications; Radio frequency; Personal communication service systems; Standards; Sensor networks; Low voltage systems; dept.csc; faculty_collection

Bidirectional reservoir networks trained using SVM$$+$$privileged information for manufacturing process modeling - Rodan, Ali; Sheta, Alaa F.; Faris, Hossam (Soft Computing, 2017)
In the last decade, a wide range of machine learning approaches were proposed and experimented to model highly nonlinear manufacturing processes. However, improving the performance of such models is challenging due to the complexity and high dimensionality of the manufacturing processes in general. In this paper, we propose bidirectional echo state reservoir networks (Bi-ESNs) trained using support vector machine privileged information method (SVM$$+$$) to model a winding machine process. The proposed model will be applied, tested and compared to reported models in the literature such as classical ESN with linear regression, ESN with a linear SVM readout, genetic programming, feedfoward neural network with backpropagation, radial basis function network, adaptive neural fuzzy inference system and local linear wavelet neural network. The developed results show that Bi-ESNs trained with SVM$$+$$are promising. It was able to provide better generalization performance compared to other models.
19 citations (Crossref) [2023-10-31]
Keywords: Engineering process; Privileged information; Recurrent neural network; Reservoir computing; Support vector machines; Winding machines; dept.csc; peer-reviewed

An information system for multi-instrument atmospheric laser radar studies - Sharma, N.; Parikh, J.A. (WMSCI - World Multi-Conf. Syst., Cybern. Informatics, Proc., 2010)
In this paper we describe an information system that we have designed for students and researchers to conduct atmospheric studies using data that they have collected from multiple atmospheric instruments including two laser radar (lidar) systems. The lidar systems available for research include a monostatic Micro Pulse Lidar System and a bistatic imaging CLidar system. Complementary instruments for data analysis and ground truth specification include a nephelometer, sunphotometers and a weather station. Information structures within the system allow users to 1) label, describe and archive raw and derived datasets from multiple atmospheric instruments with associated metadata using NetCDF format, 2) link together coincident and co-located datasets from different instruments and 3) identify owner and verify user access rights of raw and derived datasets. Data analysis software tools have been developed in MATLAB to characterize and remove instrument artifacts based on experimental lidar studies, to analyze clear sky data to determine variability in atmospheric aerosol content over time and altitude, and to investigate cloud and aerosol patterns.
Journal Abbreviation: WMSCI - World Multi-Conf. Syst., Cybern. Informatics, Proc.
Keywords: Aerosol patterns; Atmospheric aerosols; Atmospheric instruments; Atmospheric laser; Atmospheric studies; Bistatic; Clear sky; Co-located; Cybernetics; Data analysis softwares; Data sets; Ground truth; Information science; Information structures; Information systems; Instruments; Laser radar; Lasers; Lidar; Lidar systems; Metadata; Micro pulse lidar; Monostatic; Optical radar; Sun-photometers; User access; Weather stations; dept.csc

Meeting deadlines within object-oriented systems - El-Raouf, A.A. (International Conference on High Performance Computing and Simulation, 2011)
In real-time software systems, meeting deadlines is crucial. Software engineers face many challenges to model the object-oriented software system to handle complex real-time constraints. The accurate estimating of the performance time is a key criterion for a precise scheduling decision. This paper presents an object-oriented performance model that analyzes the behavior of the real-time objects' tasks whose executions are controlled by a scheduler. Each task is subject to a time/utility function (TUF) that determines the accrued utility of the task according to its completion time. The scheduling scheme uses both the estimated time generated by the object-oriented performance model and the time utility function (TUF) of each task in the object-oriented system in order to maximize the total accrued utility. In addition, we implemented a software tool to conduct experimental study in order to show the effectiveness of our approach. © 2011 IEEE.
0 citations (Crossref) [2023-10-31] Journal Abbreviation: Proc. Int. Conf. High Perform. Comput. Simul., HPCS
Keywords: Completion time; Computer software selection and evaluation; Experimental studies; Object oriented; Object oriented software; Object-oriented software systems; Object-oriented system; Performance Model; Performance analysis; Real time constraints; Real time systems; Real-time software; Scheduling; Scheduling decisions; Scheduling schemes; Software engineers; Software tool; Time-utility functions; deadline; dept.csc; object-oriented software; performance analysis; scheduling; time utility function

ARM Assembly Language with Hardware Experiments - Elahi, Ata; Arjeski, Trevor (Springer, 2015)
This book provides a hands-on approach to learning ARM assembly language with the use of a TI microcontroller. The book starts with an introduction to computer architecture and then discusses number systems and digital logic. The text covers ARM Assembly Language, ARM Cortex Architecture and its components, and Hardware Experiments using TILM3S1968. Written for those interested in learning embedded programming using an ARM Microcontroller. © Springer International Publishing Switzerland 2015.
Keywords: ARM microcontrollers; ARM processors; Arm cortices; Assembly language; Assembly languages (Electronic computers); Microprocessors; Computer architecture; Computer hardware; Digital logic; Education; Embedded programming; Hardware; Hardware experiment; Microcontrollers; Number system; Numbering systems; Programming; dept.csc; faculty_collection

Analyzing HTTP-Based Information Exfiltration of Malicious Android Applications - Kelkar, S.; Kraus, T.; Morgan, D.; Zhang, J.; Dai, R. (Proc. - IEEE Int. Conf. Trust, Secur. Priv. Comput. Commun. IEEE Int. Conf. Big Data Sci. Eng., Trustcom/BigDataSE, 2018)
Exfiltrating sensitive information from smartphones has become one of the most significant security threats. We have built a system to identify HTTP-based information exfiltration of malicious Android applications. In this paper, we discuss the method to track the propagation of sensitive information in Android applications using static taint analysis. We have studied the leaked information, destinations to which information is exfiltrated, and their correlations with types of sensitive information. The analysis results based on 578 malicious Android applications have revealed that a significant portion of these applications are interested in identity-related sensitive information. The vast majority of malicious applications leak multiple types of sensitive information. We have also identified servers associated with three country codes including CN, US, and SG are most active in collecting sensitive information. The analysis results have also demonstrated that a wide range of non-default ports are used by suspicious URLs. © 2018 IEEE.
4 citations (Crossref) [2023-10-31] Journal Abbreviation: Proc. - IEEE Int. Conf. Trust, Secur. Priv. Comput. Commun. IEEE Int. Conf. Big Data Sci. Eng., Trustcom/BigDataSE
Keywords: Android (operating system); Android Applications; Android applications; Big data; Data privacy; Exfiltration; HTTP; HTTP Based; Information Exfiltration; Malicious android applications; Security threats; Sensitive informations; dept.csc

Nonperturbative strange-quark sea from lattice QCD, light-front holography, and meson-baryon fluctuation models - Sufian, R.S.; Liu, T.; De Téramond, G.F.; Dosch, H.G.; Brodsky, S.J.; Deur, A.; Islam, M.T.; Ma, B.-Q.; HLFHS Collaboration (Physical Review D, 2018)
We demonstrate that a nonzero strangeness contribution to the spacelike electromagnetic form factor of the nucleon is evidence for a strange-antistrange asymmetry in the nucleon's light-front wave function, thus implying different nonperturbative contributions to the strange and antistrange quark distribution functions. A recent lattice QCD calculation of the nucleon strange quark form factor predicts that the strange quark distribution is more centralized in coordinate space than the antistrange quark distribution, and thus the strange quark distribution is more spread out in light-front momentum space. We show that the lattice prediction implies that the difference between the strange and antistrange parton distribution functions, s(x)-s(x), is negative at small-x and positive at large-x. We also evaluate the strange quark form factor and s(x)-s(x) using a baryon-meson fluctuation model and a novel nonperturbative model based on light-front holographic QCD. This procedure leads to a Veneziano-like expression of the form factor, which depends exclusively on the twist of the hadron and the properties of the Regge trajectory of the vector meson which couples to the quark current in the hadron. The holographic structure of the model allows us to introduce unambiguously quark masses in the form factors and quark distributions preserving the hard scattering counting rule at large-Q2 and the inclusive counting rule at large-x. Quark masses modify the Regge intercept which governs the small-x behavior of quark distributions, therefore modifying their small-x singular behavior. Both nonperturbative approaches provide descriptions of the strange-antistrange asymmetry and intrinsic strangeness in the nucleon consistent with the lattice QCD result. © 2018 authors. Published by the American Physical Society.
18 citations (Crossref) [2023-10-31]
Keywords: dept.csc; peer-reviewed

DeePEL: Deep learning architecture to recognize p-lncRNA and e-lncRNA promoters - Alam, T.; Islam, M.T.; Schmeier, S.; Househ, M.; Al-Thani, D.A. (Proc. - IEEE Int. Conf. Bioinform. Biomed., BIBM, 2019)
Promoter regions of long non-coding RNA (lncRNA) genes are crucial to understand their transcriptional regulatory pattern. LncRNA genes, being more cryptic than protein-coding genes in terms of their functionality and biogenesis divergence, are lacking in number of existing studies to elucidate the roles of their promoters compared to their counterparts. Based on the overlap between epigenetic marks and transcription start sites, human lncRNAs were categorized into two broad categories: enhancer-originated lncRNAs (e-lncRNAs) and promoter-originated lncRNAs (p-lncRNAs) and hence these two groups are subject to distinct transcriptional regulatory programs. To understand the difference in the transcriptional regulatory mechanisms that governs p- and e-lncRNAs, we studied the promoter sequences of these two groups of lncRNAs including distinct transcription factor (TF) proteins that favor p-over e-lncRNA (and vice versa). In addition, we developed a convolution neural network (CNN) based deep learning (DL) framework DeePEL (deep p-, e-lncRNA promoter recognizer), to classify the promoter of p- and e-lncRNAs. To the best of our knowledge, this is the first attempt to classify these two groups of lncRNA promoters, using sequence and TF information, based on DL framework. We report several sequence specific signatures in the promoter regions as well as several distinct TFs specific to groups of lncRNAs that will help in understanding the promoter-proximal transcriptional regulation of p-lncRNAs and e-lncRNAs. © 2019 IEEE.
0 citations (Crossref) [2023-10-31] Journal Abbreviation: Proc. - IEEE Int. Conf. Bioinform. Biomed., BIBM
Keywords: Bioinformatics; Classification (of information); Convolution neural network; Deep learning; FANTOM; Learning architectures; Promoter sequences; Protein-coding genes; Proteins; Regulatory mechanism; Regulatory patterns; Transcription; Transcription start site; Transcriptional regulation; convolution neural network; deep learning; dept.csc; long non-coding RNA; promoter

Deep learning based plant disease detection for smart agriculture - Ale, L.; Sheta, A.; Li, L.; Wang, Y.; Zhang, N. (IEEE Globecom Workshops, GC Wkshps - Proc., 2019)
Deep learning is a promising approach for fine- grained disease severity classification for smart agriculture, as it avoids the labor-intensive feature engineering and segmentation-based threshold. In this work, we first propose a Densely Connected Convolutional Networks (DenseNet) based transfer learning method to detect the plant diseases, which expects to run on edge servers with augmented computing resources. Then, we propose a lightweight Deep Neural Networks (DNN) approach that can run on Internet of Things (IoT) devices with constrained resources. To reduce the size and computation cost of the model, we further simplify the DNN model and reduce the size of input sizes. The proposed models are trained with different image sizes to find the appropriate size of the input images. Experiment results are provided to evaluate the performance of the proposed models based on real- world dataset, which demonstrate the proposed models can accurately detect plant disease using low computational resources. © 2019 IEEE.
30 citations (Crossref) [2023-10-31] Journal Abbreviation: IEEE Globecom Workshops, GC Wkshps - Proc.
Keywords: Agriculture; Classification; Classification (of information); Computational resources; Computing resource; Constrained resources; Convolution; Convolutional Neural Network; Convolutional networks; Convolutional neural networks; Corp Disease; Deep learning; Deep neural networks; Detection; Digital Epidemiology; Error detection; Feature engineerings; Internet of Things (IOT); Internet of things; Learning systems; Plants Disease; Smart agricultures; Transfer learning; Transfer learning methods; dept.csc

Application of electrical capacitance tomography for imaging conductive materials in industrial processes - Deabes, W.; Sheta, A.; Bouazza, K.E.; Abdelrahman, M. (Journal of Sensors, 2019)
This paper presents highly robust, novel approaches to solving the forward and inverse problems of an Electrical Capacitance Tomography (ECT) system for imaging conductive materials. ECT is one of the standard tomography techniques for industrial imaging. An ECT technique is nonintrusive and rapid and requires a low burden cost. However, the ECT system still suffers from a soft-field problem which adversely affects the quality of the reconstructed images. Although many image reconstruction algorithms have been developed, still the generated images are inaccurate and poor. In this work, the Capacitance Artificial Neural Network (CANN) system is presented as a solver for the forward problem to calculate the estimated capacitance measurements. Moreover, the Metal Filled Fuzzy System (MFFS) is proposed as a solver for the inverse problem to construct the metal images. To assess the proposed approaches, we conducted extensive experiments on image metal distributions in the lost foam casting (LFC) process to light the reliability of the system and its efficiency. The experimental results showed that the system is sensible and superior. © 2019 Wael Deabes et al.
15 citations (Crossref) [2023-10-31]
Keywords: Capacitance; Capacitance measurement; Conductive materials; Electric impedance tomography; Electrical Capacitance Tomography; Electrical capacitance tomography systems; Image reconstruction; Image reconstruction algorithm; Industrial processs; Inverse problems; Its efficiencies; Lost foam castings; Metal distributions; Neural networks; Reconstructed image; dept.csc; peer-reviewed

Multiple Waypoint Mobile Robot Path Planning Using Neighborhood Search Genetic Algorithms - Maddi, D.R.; Sheta, A.; Mahdy, A.; Turabieh, H. (ACM Int. Conf. Proc. Ser., 2019)
In this paper, we present a Neighborhood Search Genetic Algorithms (NSGAs) for mobile robot path planning. GAs have been used successfully in a variety of path planning problem because they can search the space of all possible paths and provide the optimal one. The convergence process of GAs might be lengthy compared to traditional search techniques that depend on local search methods. We propose a hybrid approach that allows GAs to combine both the advantages of GAs and local search algorithms. GAs will create a multiple waypoint path allowing a mobile robot to navigate through static obstacles and finding the optimal path in order to approach the target location without collision. The proposed NSGAs has been examined over four different path planning case studies with varying complexity. The performance of the enhanced GA has been compared with A-star algorithm (A∗) standard GA, particle swarm optimization (PSO) algorithm. The obtained results show that the proposed approach is able to get good results compared to other algorithms. © 2019 ACM.
1 citations (Crossref) [2023-10-31] Journal Abbreviation: ACM Int. Conf. Proc. Ser.
Keywords: Air navigation; Convergence process; Gases; Genetic Algorithm; Genetic algorithms; Local search (optimization); Local search algorithm; Local search method; Mobile robots; Neighborhood Search; Neighborhood search; Particle swarm optimization (PSO); Particle swarm optimization algorithm; Path Planning; Path planning problems; Robot path-planning; Robot programming; Robotics; Search technique; dept.csc

Medical Data Classification Using Binary Brain Storm Optimization Algorithm - Ogwo, O.; Turabieh, H.; Sheta, A.; King, S. (ACM Int. Conf. Proc. Ser., 2019)
With the growing access to technology in the medical domain, an increased volume of medical data is recorded. The size and complexity of these data make the process of analysis of meaningful discoveries of beneficial patterns more challenging. This problem has attracted numerous researchers around the world. Statistical methods have been employed to handle medical data for diagnosis purposes. Unfortunately, these methods were less capable of dealing with these massive and complex datasets. To solve this problem, we suggest a process to classify medical data which includes feature selection and classification using a number of supervised learning techniques. Binary Brain Storm Optimization (BBSO) is used for feature selection, which is a population search approach that simulates the process of electing the best idea (solution), among others. We simulated six different classifiers: Naive-Bayes, K-Nearest Neighbor, Support Vector Machine, Linear Discriminant Analysis, Decision Tree and Random Forest. Five datasets adopted from the UCI Machine Learning Repository, (Breast Cancer, Diabetes, Heart Disease, Chronic Kidney, and SPECT), are employed as a benchmark test data. The performance of BBSO is evaluated using accuracy on the datasets using the various classifiers. Experimental results show that the proposed approach improves the classification performance for better medical diagnosis. © 2019 ACM.
1 citations (Crossref) [2023-10-31] Journal Abbreviation: ACM Int. Conf. Proc. Ser.
Keywords: Benchmarking; Classification performance; Complex datasets; Computer aided diagnosis; Decision trees; Discriminant analysis; Diseases; Feature extraction; Feature selection and classification; K-nearest neighbors; Learning systems; Linear discriminant analysis; Medical domains; Nearest neighbor search; Optimization algorithms; Robotics; Storms; Support vector machines; UCI machine learning repository; classification; dept.csc; feature selection; medical diagnosis

Web user authentication using chosen word keystroke dynamics - Rahman, K.A.; Neupane, D.; Zaiter, A.; Hossain, M.S. (Proc. - IEEE Int. Conf. Mach. Learn. Appl., ICMLA, 2019)
Keystroke dynamics has been used as a form of one-time user authentication and continuous verification especially when it comes to securing the cyberspace. In this paper, we present the idea of using keystroke dynamics as a form of second layer authentication in web applications. We showed that this method can authenticate a user with high accuracy and can be used as an alternate to CAPTCHA tests, security questions and image selections that are being used today. We have developed a working web-based platform in a browser environment that enforces the proposed second-layer security. We performed penetration test experiments by launching a total of 598,500 impostor and genuine authentication attempts and found the Equal Error Rate (EER) as 10.5%. © 2019 IEEE.
5 citations (Crossref) [2023-10-31] Journal Abbreviation: Proc. - IEEE Int. Conf. Mach. Learn. Appl., ICMLA
Keywords: Authentication; CAPTCHA; CAPTCHAs; Cyber security; Cybersecurity; Dynamics; Electronic mail filters; Equal error rate; Keystroke dynamics; Machine learning; Network security; Penetration test; User authentication; WEB application; Web based platform; Websites; dept.csc

Cascaded layered recurrent neural network for indoor localization in wireless sensor networks - Turabieh, H.; Sheta, A. (Int. Conf. New Trends Comput. Sci., ICTCS - Proc., 2019)
The growth in using various smart wireless devices in the last few decades has given rise to indoor localization service (ILS). Indoor localization is defined as the process of locating a user location in an indoor environment. Indoor device localization has been widely studied due to its popular applications in public settlement planning, health care zones, disaster management, the implementation of location-based services (LBS) and the Internet of Things (IoT). The ILS problem can be formulated as a learning problem utilizing Wi-Fi technology. The measured Wi-Fi signal strength can be used as an indication of the distribution of users in a various indoor location. Developing a classification model with high accuracy can be achieved using a machine learning approach. Artificial Neural Network is one of the most successful trends in machine learning. In this article, we provide our initial idea of using Cascaded Layered Recurrent Neural Network (L-RNN) for the classification of user localization in an indoor environment. Several neural network models were trained, with the best performance attainment is reported. The experimental results marked that the presented L-RNN model is highly accurate for indoor localization and can be utilized for many applications. © 2019 IEEE.
5 citations (Crossref) [2023-10-31] Journal Abbreviation: Int. Conf. New Trends Comput. Sci., ICTCS - Proc.
Keywords: Classification models; Disaster management; Disaster prevention; Disasters; Forecasting; Indoor Environment; Indoor environment; Indoor localization; Indoor positioning systems; Internet of thing (IOT); Internet of things; Layered Recurrent Neural Network; Location; Location based services; Machine learning; Machine learning approaches; Multilayer neural networks; Network layers; Neural network model; Prediction; Recurrent neural networks; Telecommunication services; User Localization; User localization; Wireless local area networks (WLAN); Wireless sensor networks; dept.csc

Authorship categorization of public domain literature - Boran, Tudor; Voss, John; Hossain, Shafaeat (Ubiquitous Computing, 2016)
We defined a set of quantifiable features for authorship categorization. We performed our experiments on public domain literature - all books analyzed were obtained in plain text format through Project Gutenberg's online repository of classic books. We tested three machine learning algorithms: Artificial Neural Network, Naïve Bayes Classifier, and Support Vector Machine with our features. We found that certain features, such as punctuation and various suffixes result in a higher accuracy. In addition, the Support Vector Machine classifier produces repeatedly higher accuracies than other classifiers and seems to be a far superior method of classification in terms of authorship categorization. © 2016 IEEE.
1 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Authorship categorization; Bayes Classifier; Classification (of information); Learning algorithms; Learning systems; Mobile telecommunication systems; Neural networks; Online repositories; Plain text; Public domains; Support vector machine classifiers; Support vector machines; Ubiquitous computing; classification; dept.csc; public domain literature; support vector machine

On finding appropriate reject region in serial fusion based biometric verification - Hossain, Shafaeat (IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, 2016)
We give the theoretical foundation for finding a reject region which gives the minimum equal error rate in serial fusion based biometric verification. Given a user-specified tolerance of x percent genuine score reject rate, we prove that there exists a unique reject region inside which the false alarm rate and impostor pass rate curves overlap, and this reject region gives the minimum equal error rate. Our theory leads to new algorithms for finding reject regions, which have two key advantages over the state-of-the-art: (1) the algorithms allow the system administrator to control the proportion of genuine scores that a reject region can erroneously reject and (2) the algorithms determine reject regions directly from the scores, without the need to estimate score distributions. Our proofs do not rely on data belonging to any particular distribution, which makes them applicable to a wide range of biometric modalities including face, finger, iris, speech, gait, and keystrokes. © 2016 IEEE.
3 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Biometric verification; Biometrics; Decision support systems; Equal error rate; False alarm rate; Genuine scores; Particular distribution; State of the art; System administrators; Theoretical foundations; dept.csc

User authentication and identification on smartphones by incorporating capacitive touchscreen - Rilvan, Mohamed Azard; Lacy, Kolby Isiah; Hossain, Shafaeat; Wang, Bing (International Performance, Computing, and Communications Conference, 2016)
Smartphones, while providing users ease of access to sensitive information on the go, also present severe security risks if an attacker is able to gain access to them. To strengthen the user authentication and identification in a smartphone, we develop a biometric authentication and identification system which uses the capacitive touchscreen that is featured in all current smartphones. Our methodology focuses on using the touchscreen as a sensor to capture the image of a user's ear, thumb or four fingers. We extract the capacitive raw data from the touched body part to obtain a capacitive image, and then use it to capture geometric features (e.g., length and width of a finger) and principal components. After that, we experiment with Support Vector Machine (SVM) and Random Forest (RF) classifiers to verify and also identify each user. We achieved the maximum authentication accuracy of 98.84% by four fingers with SVM, and maxinum identification accuracy of 97.61% by four fingers with RF. © 2016 IEEE.
4 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Authentication; Biometric; Biometric authentication; Biometrics; Decision trees; Geometric feature; Identification (control systems); Identification accuracy; Principal Components; Random forests; Security risks; Sensitive informations; Smartphones; Support vector machines; User authentication; authentication; capacitive touchscreen; dept.csc; identification; smart-phones

Exploring search task difficulty reasons in different task types and user knowledge groups - Liu, Jingjing; Kim, Chang Suk; Creel, Caitlin (Information Processing and Management, 2015)
Search task difficulty has been attracting much research attention in recent years, mostly regarding its relationship with searchers' behaviors and the prediction of task difficulty from search behaviors. However, it remains unknown what makes searchers feel the difficulty. A study consisting of 48 undergraduate students was conducted to explore this question. Each participant was given 4 search tasks that were carefully designed following a task classification scheme. Questionnaires were used to elicit participants' ratings on task difficulty and why they gave those ratings. Based on the collected difficulty reasons, a coding scheme was developed, which covered various aspects of task, user, and user-task interaction. Difficulty reasons were then categorized following this scheme. Results showed that searchers reported some common reasons leading to task difficulty in different tasks, but most of the difficulty reasons varied across tasks. In addition, task difficulty had some common reasons between searchers with low and high levels of topic knowledge, although there were also differences in top task difficulty reasons between high and low knowledge users. These findings further our understanding of search task difficulty, the relationship between task difficulty and task type, and that between task difficulty and knowledge level. The findings can also be helpful with designing tasks for information search experiments, and have implications on search system design both in general and for personalization based on task type and searchers' knowledge. (C) 2014 Elsevier Ltd. All rights reserved.
21 citations (Crossref) [2023-10-31] Citation Key Alias: lens.org/112-166-586-835-305 tex.type: [object Object]
Keywords: Information search; Knowledge level; Personalizations; Search engines; Students; Surveys; Task classification; Task difficulty; Task difficulty reason; Task type; Topic knowledge; Undergraduate students; dept.csc

Asynchronous gossip-based data propagation protocol - Andrew, Priyanka; Antonios, Imad (Digital Information and Communication Technology and Its Applications, 2015)
Data dissemination protocols govern interaction and exchange of data among nodes in a distributed system. An understanding of data transfer protocols provides insight into efficient middleware management. Due to their simplicity, scalability and fault-tolerance, gossip-based protocols are researched widely as an effective communication strategy. The Shuffle protocol presented in [1], is an example of a decentralized, gossip-based data transfer protocol used to spread information in a wireless network via probabilistic exchange of data. This paper presents, an asynchronous variant of the Shuffle protocol and a system model that captures variability in data transmission times. This transmission time variability is inherent in dynamic networks, where such algorithms are typically deployed. A simulation-based analysis of the protocol's performance behavior is presented. Results show the effects of transmission variability, on data replication and its coverage. Also examined is the relationship between available storage and the performance of the protocol, expressed using measures such as propagation time and work. © 2015 IEEE.
1 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Data communication systems; Data dissemination; Data dissemination protocols; Data propagation protocols; Data transfer; Data transfer protocols; Digital storage; Distributed database systems; Effective communication; Fault tolerance; Fault tolerant computer systems; Gossip-based algorithms; Gossip-based protocol; Internet protocols; Middleware; Shuffle protocol; Simulation-based analysis; Wireless networks; asynchronous gossip-based algorithm; data dissemination; data transfer protocol; dept.csc; wireless network

ARM Assembly language programming Using Keil Development Tools Introduction - Elahi, Ata; Arjeski, Trevor (ARM Assembly Language with Hardware Experiments, 2015)
Manufacturers of CPUs publish a document that contains information about the processor that includes: list of registers, function of each register, size of data bus, size of address bus and list of instructions that can be executed by the CPU. Each CPU has a known instruction set that a programmer can use to write assembly language programs. Instruction sets are specific to each type of processor. That being said, Pentium processors use a different instruction set than ARM processors. Using the Instructions a of processor to write a program is called assembly language and function of an assembler is to convert assembly language to machine code (binary) that the CPU can understand.
Citation Key Alias: lens.org/088-348-966-769-812
Keywords: dept.csc

ARM Cortex-M3 Processor and MBED NXP LPC1768 - Elahi, Ata; Arjeski, Trevor (ARM Assembly Language with Hardware Experiments, 2015)
ARM offers variety of the core processor base on their applications and they are: Cortex A series: Cortex A series is a High performance processor for open operating system, the Cortex-A50 is a 64 bit process, application of Cortex-A series are Smart phones, Netbook, Digital TV, and eBook readers
Citation Key Alias: lens.org/031-467-574-875-492
Keywords: dept.csc

ARM Instructions and Part II - Elahi, Ata; Arjeski, Trevor (ARM Assembly Language with Hardware Experiments, 2015)
The data transfer instructions are used to transfer data from memory to registers and from registers to memory and they are Load (LDR) and Store (STR) instructions.
Citation Key Alias: lens.org/013-090-628-194-319
Keywords: dept.csc

ARM Instructions Part I - Elahi, Ata; Arjeski, Trevor (ARM Assembly Language with Hardware Experiments, 2015)
Advanced RISC Machine (ARM) was developed by the Acorn Company. ARM is a leader supplier of microprocessors in the world, ARM develop the core CPU and thousand of suppliers add more functional units to the core. ARM uses two types instruction called Thumb and Thumb-2. Thumb instructions are 16 bits and thumb-2 instructions are 32 bits, currently most ARM processors uses 32 bit instructions.
Citation Key Alias: lens.org/004-692-447-907-924
Keywords: dept.csc

Logic Gates and Introduction to Computer Architecture - Elahi, Ata; Arjeski, Trevor (ARM Assembly Language with Hardware Experiments, 2015)
The basic components of an Integrated Circuit (IC) is logic gates which made of transistors, in digital system there are three basic logic operations and they are called AND, OR and NOT.
Citation Key Alias: lens.org/102-318-987-004-411
Keywords: dept.csc

Number Systems and Data Communication - Elahi, Ata; Arjeski, Trevor (ARM Assembly Language with Hardware Experiments, 2015)
In order to understand network technology it is important to know how information is represented for transmission from one computer to another. Information can be transferred between computers in one of two ways: an analog signal or a digital signal.
Citation Key Alias: lens.org/038-175-763-396-415
Keywords: Analog Signal; Binary Number; Digital Signal; Number System; Transmission Method; dept.csc

Enhancing EDP of multicore processors through DVFS - Hajiamini, Shervin; Shirazi, Behrooz; Rilvan, Mohamed Azard (International Green and Sustainable Computing Conference, 2015)
Dynamic voltage and frequency scaling (DVFS) is a well-known technique to optimize the power dissipation of electronic systems without significantly compromising overall system performance. DVFS exploits the periods of inter-core data exchange (memory-bound operations) to reduce the voltage and frequency (V/F) of the cores in order to reduce the power dissipation during the execution flow of an application running on the CMP. As the lengths of the idle and busy periods of the cores vary depending on the benchmarks, it is crucial for any DVFS technique to maximize the power saving without losing a significant performance. In this work we present two power optimization methodologies that are integrated into a full-system simulator to make online predictions about the voltage and frequency of the cores during the execution time of the benchmarks. We evaluate these methodologies in terms of the V/F predictions vs. the actual utilization of each core periodically. We also compare the overall execution time, energy dissipation, and energy-delay product (EDP) of the power optimization methodologies for various benchmarks. © 2015 IEEE.
1 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Benchmarking; DVFS; Dynamic frequency scaling; Dynamic voltage and frequency scaling; Electric losses; Electronic data interchange; Electronic systems; Energy delay product; Energy dissipation; Energy efficiency; Forecasting; Full system simulators; Multi core; Multi-core processor; Multicore; Power Optimization; V/F tracking; Voltage scaling; dept.csc; energy efficiency

Free indulgences: Enhanced zero-price effect for hedonic options - Hossain, Mehdi T; Saini, Ritesh (International Journal of Research in Marketing, 2015)
We find that the relative preference of hedonic products is disproportionately enhanced when they are offered at a free price. This “free price bounce” is more subdued for utilitarian products. This is surprising because rational choice theory posits that relative preference amidst two options - say a hedonic and a utilitarian product - remains intact as long as the price difference between them is constant. We propose and demonstrate that this axiom is violated when a hedonic product is offered for free. (C) 2015 Elsevier B.V. All rights reserved.
14 citations (Crossref) [2023-10-31] Citation Key Alias: lens.org/107-412-613-199-640 tex.type: [object Object]
Keywords: Affective appraisal; Behavioral pricing; Hedonic-utilitarian differences; Sales promotion; Zero price; dept.csc

Analyzing PHP frameworks for use in a project-based software engineering course - Lancor, Lisa; Katha, Samyukta (Technical Symposium on Computer Science Education, 2013)
Given the popularity of PHP frameworks used in developing webbased applications, a comparative study is conducted to determine which framework is best suited for incorporation into the curriculum of an undergraduate software engineering course that uses project-based learning. The top six PHP frameworks (Zend, Yii, CakePHP, CodeIgniter, PRADO, and Symphony) were initially considered and then narrowed down to two (CakePHP and CodeIgniter) based on their alignment with common functionality in previous class projects, framework complexity for those new to frameworks (learning curve), and developer friendliness (availability of documentation and online resources). An in-depth comparative study is conducted by developing a functionally-equivalent web application using each of the two frameworks as well as plain PHP (no framework). This work was motivated by the difficulties that were encountered in an evolving, content-rich software engineering course and discusses the educational changes that were made to align student learning with sound software engineering principles and current software development practices used in the computing industry. Copyright © 2013 ACM.
4 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Application programs; Curricula; Education computing; Engineering education; PHP frameworks; Project based learning; Project-based learning; Software design; Software design and development; Software development practices; Software engineering; Software engineering course; Software engineering principles; Technical presentations; Undergraduate software engineering; Web-based applications; dept.csc

Why do users perceive search tasks as difficult? Exploring difficulty in different task types - Liu, Jingjing; Kim, Chang Suk (Symposium on Human-Computer Interaction and Information Retrieval, 2013)
In this paper, we examined why information searchers perceive search tasks as difficult, and what factors/reasons make them perceive tasks as difficult. We also examined if task difficulty reasons vary across different tasks (task types). Data was collected through a controlled laboratory experiment in which tasks were designed following a classification scheme. A total of 32 undergraduate students participated, each was given 4 search tasks, and they were asked in questionnaires both before and after the tasks for task difficulty ratings and why they gave those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. Difficulty reasons were categorized following this scheme. Results showed that searchers had some common reasons for task difficulty in different tasks, but most of the difficulty reasons varied across tasks. For each task, there were also common reasons for task difficulty, although there was some variation here as well. Task difficulty was also found to be negatively correlated with users topic knowledge, previous experience, and topic interest. Our findings help understand search task difficulty, as well as the relationships between task difficulty and task type, knowledge background, etc. These can also be helpful with experiment task design. © 2013 ACM.
5 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Classification scheme; Coding scheme; Controlled laboratories; Experiments; Human computer interaction; Information retrieval; Search tasks; Students; Surveys; Task difficulty; Task difficulty reason categories; Undergraduate students; dept.csc; task features; topic knowledge

Why do users feel search task difficult - Liu, Jingjing; Kim, Chang Suk; Creel, Caitlin (ASIST '13 Proceedings of the 76th ASIS&T Annual Meeting: Beyond the Cloud: Rethinking Information Boundaries, 2013)
This paper reports on an examination of why information searchers find search tasks difficult and the specific reasons they feel difficult. Data was collected through a controlled laboratory experiment with 32 participants, each working with 4 search tasks. They were asked in questionnaires, both before and after the tasks, for task difficulty ratings and their reasoning for giving those ratings. We developed a coding scheme based on the difficulty reasons users gave, which covered various aspects of task, user, and user-task interaction. This helps us understand search task difficulty, as well as provides a scheme for task difficulty control in experiment task design.
6 citations (Crossref) [2023-10-31]
Keywords: Task difficulty reason categories; Task features; Topic knowledge; dept.csc

Software environments for atmospheric lidar remote sensing - Sharma, Nimmi C P; Parikh, Jo Ann (International Geoscience and Remote Sensing Symposium, 2013)
Research and training in atmospheric lidar remote sensing requires highly versatile software environments for both experimentation and analysis. Experimentation and analysis may be conducted either directly on site at the location of the lidar equipment and/or institutional computer center or remotely from a distant location. The requirements for lidar software environments depend not only on type of user access (remote or onsite) but also on the nature of the teaching or research missions they support and the characteristics of the lidar systems for which they are used. The software environments discussed in this paper have been used to support lidar aerosol studies in settings ranging from urban locations to a remote atmospheric baseline station. Experiments and data analysis studies have been conducted for two different ground-based lidar systems, a monostatic Micro Pulse Lidar system and a bistatic imaging lidar system. © 2013 IEEE.
0 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: aerosols; dept.csc; laser radar; remote sensing software

A performance model of gossip-based update propagation - Antonios, Imad; Dhar, Reetu; Zhang, Feng; Lipsky, Lester (Network Computing and Applications, 2010)
We consider the problem of propagating an update to nodes in a distributed system using two gossiping protocols. The first is an idealized algorithm with static and dynamic knowledge of the system, and the second is a simple randomized algorithm. We construct a theoretical model that allows us to derive work and completion time statistics under varying transmission delay distributions. Numerical results are obtained for both exponential and nonexponential transmission times using linear-algebraic queueing theory techniques. Additionally, we present the results of simulation experiments showing that under node churn assumptions, the randomized algorithm's performance is qualitatively different than in a fault-free system. © 2010 IEEE.
0 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Algorithms; Completion time; Distributed systems; Gossiping protocols; Linear-algebraic; Numerical results; Performance Model; Queueing theory; Randomized Algorithms; Simulation experiments; Static and dynamic; Theoretical models; Transmission delays; dept.csc

Timing Prediction for Dynamic Application Migration on Multi-core Embedded Systems - Li, Zheng; Wu, Hao; He, Shuibing (2018 IEEE 4th International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing, (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS), 2018)
To accommodate execution mode change and hardware malfunction, dynamic system reconfiguration, which invokes application migration across different processing cores, needs to be supported on multi-core embedded systems. Different application migration strategies will impact system's timing behaviors in different manners, it is important to select an appropriate one such that the system's timing performance after the migration process is still acceptable. The focus of our research is to predict the system's timing change of possible migration strategies and upon which to choose the optimal one. Extensive experiments have been set up by running multiple benchmarks and experimental results validate the effectiveness of our proposed approach.
0 citations (Crossref) [2023-10-31]
Keywords: Application Migration; Application migrations; Big data; Dynamic applications; Dynamic system reconfigurations; Embedded systems; Forecasting; Kernel; Migration process; Migration strategy; Multi Core; Multi core; Multi-core embedded systems; Multicore processing; Network security; Predictive models; Timing; Timing Prediction; Timing circuits; Timing performance; Training; Training data; dept.csc; dynamic application migration; dynamic system reconfiguration; embedded systems; execution mode; hardware malfunction; multicore embedded systems; multiprocessing systems; systems timing behaviors; timing prediction

Approximation of the time alignment error for measurements in electricity grids - Antonios, I.; Schwefel, H.-P.; Lipsky, L. (Proc. - Eur. Dependable Comput. Conf., EDCC, 2019)
Measurements of parameters in electricity grids are frequently captured as average values over some time interval. In scenarios of distributed measurements such as in distribution grids, offsets of local clocks can result in misaligned averaging intervals. This paper investigates the properties of the so-called time alignment error of such measurands that is caused by shifts of the averaging interval. We extend a previously derived Markov-modulated model and provide an approximation of the variance of the time alignment error. The model accounts for slow-decaying correlation structure found in actual traces of electrical measures. We compare results of three electrical measures for 20 traces with numerical results and simulations from the the fitted Markov model. © 2019 IEEE.
2 citations (Crossref) [2023-10-31] Journal Abbreviation: Proc. - Eur. Dependable Comput. Conf., EDCC
Keywords: Alignment; Clock Synchronization; Clock synchronization; Clocks; Decaying correlations; Distributed measurements; Distribution grid; Electric power transmission networks; Electric variables measurement; Electrical distribution; Electrical distribution grids; Electricity grids; Errors; Markov processes; Measurement errors; Modulated model; Numerical results; dept.csc

On enhancing serial fusion based multi-biometric verification system - Hossain, Md; Chen, Jundong; Rahman, Khandaker (Applied Intelligence, 2018)
Design of a serial fusion based multi-biometric verification system requires fixing several parameters, such as reject thresholds at each stage of the architecture and the order in which each individual verifier is placed within the multi-stage system. Selecting the order of verifier is a crucial parameter to fix because of its high impact on verification errors. A wrong choice of verifier order might lead to tremendous user inconvenience by denying a large number of genuine users and might cause severe security breach by accepting impostors frequently. Unfortunately, this design issue has been poorly investigated in multi-biometric literature. In this paper, we address this design issue by performing experiments using three different serial fusion based multi-biometric verification schemes. We did our experiments on publicly available NIST multi-modal dataset. We tested 24 orders—all possible orders originated from four individual verifiers—on a four-stage biometric verification system. Our experimental results show that the verifier order “best-to-worst”, where the best performing individual verifier is placed in the first stage, the next best performing individual verifier is placed in the second stage, and so on, is the top performing order. In addition, we have proposed a modification to the traditional architecture of serial fusion based multi-biometric verification systems. With rigorous experiments on the NIST multi-modal dataset and using three serial fusion based multi-biometric verification schemes, we demonstrated that our proposed architecture significantly improves the performance of serial fusion based multi-biometric verification systems.
9 citations (Crossref) [2023-10-31] Citation Key Alias: hossainEnhancingSerialFusion2018a, lens.org/017-508-366-099-573, pop00310 tex.type: [object Object]
Keywords: Architecture; Biometric verification; Biometrics; Multi biometrics; Multi-biometric verification; Multi-modal dataset; Proposed architectures; Reject option; Serial fusion; Traditional architecture; Verifier order; dept.csc; peer-reviewed

Impact of time interval alignment on data quality in electricity grids - Schwefel, Hans-Peter; Antonios, Imad; Lipsky, Lester (2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2018)
Measurements of parameters in electricity grids are frequently average values over some time interval. In scenarios of distributed measurements such as in distribution grids, offsets of local clocks can result in the averaging interval being misaligned. This paper investigates the properties of the so-called time alignment error of such measurands that is caused by shifts of the averaging interval. A Markov model is derived that allows for numerically calculating the expected value and other distribution properties of this error. Actual consumption measurements of an office building are used to study the behavior of this time alignment error, and to compare the results from the trace with numerical results and simulations from a fitted Markov model. For increasing averaging interval offset, the time alignment error approaches a normal distribution, whose parameters can be calculated or approximated from the Markov model.
6 citations (Crossref) [2023-10-31] Citation Key Alias: pop00152, schwefelImpactTimeInterval2018a tex.type: [object Object]
Keywords: Alignment; Clocks; Consumption measurement; Data Quality; Data quality; Distributed measurements; Distribution Grid Measurements; Distribution grid; Distribution property; Electric power transmission networks; Errors; Markov Models; Markov model; Markov processes; Mathematical model; Measurement uncertainty; Normal distribution; Numerical models; Numerical results; Office buildings; Power measurement; Smart power grids; Time Alignment Error; Time alignment; actual consumption measurements; averaging interval offset; data quality; dept.csc; distributed measurements; distribution grids; distribution properties; electricity grids; fitted Markov model; normal distribution; parameter measurement; power grids; power supply quality; power system measurement; time alignment error; time interval alignment

An enhanced architecture for serial fusion based multi-biometric verification system - Hossain, Shafaeat; Chen, Jundong; Rahman, Khandaker Abir (International Symposium on Networks, Computers and Communications, 2018)
The traditional architecture of serial fusion based multi-biometric verification systems places an average performing or the worst performing individual verifier in the final stage. Because the final stage gives the verification decision using a single threshold and takes on the most confusing samples which are rejected by all previous stages, an average or the worst performing individual verifier may incur high verification errors in the final stage, which may negatively impact the performance of the whole system. Unfortunately, it is not possible to place a strong individual verifier in the final stage of a traditional architecture because if we place a strong individual verifier in the final stage, we will have to place a weak individual verifier in an earlier stage. Studies show that placing a weak individual verifier in an earlier stage worsens the performance of the whole system by giving more wrong decision earlier. Hence, the challenge is-how can we place the best performing individual verifier in the first stage and at the same time not place an average or the worst performing individual verifier in the final stage? In this paper, we address this challenge. We have come up with a very simple but effective solution. We have proposed a modification to the traditional architecture of serial fusion based multi-biometric verification systems. With rigorous experiments on the NIST multi-modal dataset and using three serial fusion based multi-biometric verification schemes, we demonstrated that our proposed architecture significantly improves the performance of serial fusion based multi-biometric verification systems. © 2018 IEEE.
1 citations (Crossref) [2023-10-31] tex.type: Proceedings paper
Keywords: Architecture; Biometrics; Effective solution; Multi biometrics; Multi-modal dataset; Network architecture; Proposed architectures; Serial fusion; Traditional architecture; dept.csc

A game theoretic analysis of the twitter follow-unfollow mechanism - Chen, Jundong; Hossain, Md Shafaeat; Brust, Matthias R.; Johnson, Naomi (Decision and Game Theory for Security, 2018)
Twitter users often crave more followers to increase their social popularity. While a variety of factors have been shown to attract the followers, very little work has been done to analyze the mechanism how Twitter users follow or unfollow each other. In this paper, we apply game theory to modeling the follow-unfollow mechanism on Twitter. We first present a two-player game which is based on the Prisoner’s Dilemma, and subsequently evaluate the payoffs when the two players adopt different strategies. To allow two players to play multiple rounds of the game, we propose a multi-stage game model. We design a Twitter bot analyzer which follows or unfollows other Twitter users by adopting the strategies from the multi-stage game. We develop an algorithm which enables the Twitter bot analyzer to automatically collect and analyze the data. The results from analyzing the data collected in our experiment show that the follow-back ratios for both of the Twitter bots are very low, which are 0.76%0.76%0.76\% and 0.86%0.86%0.86\%. This means that most of the Twitter users do not cooperate and only want to be followed instead of following others. Our results also exhibit the effect of different strategies on the follow-back followers and on the non-following followers as well.
2 citations (Crossref) [2023-10-31] Citation Key Alias: chenGameTheoreticAnalysis2018, pop00231 tex.type: [object Object]
Keywords: Decision theory; Game theoretic analysis; Game theory; Learning systems; Machine learning; Multi stage games; Social network; Social networking (online); Twitter bot; Twitter classification; Two-player games; dept.csc

Computer systems: Digital design, fundamentals of computer architecture and assembly language - Elahi, Ata (Springer International Publishing, 2018)
This textbook covers digital design, fundamentals of computer architecture, and assembly language. The book starts by introducing basic number systems, character coding, basic knowledge in digital design, and components of a computer. The book goes on to discuss information representation in computing; Boolean algebra and logic gates; sequential logic; input/output; and CPU performance. The author also covers ARM architecture, ARM instructions and ARM assembly language which is used in a variety of devices such as cell phones, digital TV, automobiles, routers, and switches. The book contains a set of laboratory experiments related to digital design using Logisim software; in addition, each chapter features objectives, summaries, key terms, review questions and problems. The book is targeted to students majoring Computer Science, Information System and IT and follows the ACM/IEEE 2013 guidelines. • Comprehensive textbook covering digital design, computer architecture, and ARM architecture and assembly • Covers basic number system and coding, basic knowledge in digital design, and components of a computer • Features laboratory exercises in addition to objectives, summaries, key terms, review questions, and problems in each chapter
Citation Key Alias: elahiComputerSystemsDigital2017
Keywords: ARM architecture; ARM processors; Assembly language; Boolean algebra; Computation theory; Computer architecture; Digital designs; Digital devices; Digital television; Information representation; Laboratory exercise; Laboratory experiments; Number system; Numbering systems; Reviews; Sequential logic; Textbooks; dept.csc

Understanding the relationship between network traffic correlation and queueing behavior: A review based on the N-Burst ON/OFF model - Schwefel, Hans-Peter; Antonios, Imad; Lipsky, Lester (Performance Evaluation, 2017)
Understanding the impact of network traffic properties on performance behavior in bottleneck links or larger networks is of primary interest to traffic analysts and network designers. Among the contributing factors, variance and correlation properties have been thoroughly studied and a large set of individual results have been obtained. However, these individual contributing factors are not sufficient to predict performance behavior. In this paper we review a unifying and versatile class of ON/OFF models through which the relationship among these parameters can be characterized and their influence on network performance be understood. The analytic performance results from the model show that there is a radically different queueing behavior when the ON period duration follows truncated power-tail distributions (even if truncated), as opposed to model variants where these distribution types are used for the OFF periods. All these models create correlation functions that only decay slowly. This motivates the development of a simple data analysis scheme to distinguish performance relevant correlation. The scheme is described both for interarrival and count processes of traffic data and its effectiveness is shown using real data traces.
9 citations (Crossref) [2023-10-31] Citation Key Alias: lens.org/016-979-057-202-359, pop00159 tex.type: [object Object]
Keywords: Contributing factor; Correlation function; Correlation properties; Long range dependence; Long-range dependence; Network designer; Network traffic; ON/OFF models; Power-tail distributions; Queueing model; Queueing models; Queueing networks; Queueing theory; Tail distribution; dept.csc

Sentiment analysis of the correlation between regular tweets and retweets - Chen, Jundong; Li, He; Wu, Zeju; Hossain, Md Shafaeat (2017 IEEE 16th International Symposium on Network Computing and Applications (NCA), 2017)
In this paper, we study the influence from the sentiment of regular tweets on retweeting. We propose a method to calculate the sentiment score for each tweet and each Twitter user. This method enables us to place the tweets and retweets into the same time period to explore the sentiment factor. We adopt the correlation coefficient between the sentiment scores of regular tweets and those of retweets to measure the influence. We categorize the Twitter users in three different ways to investigate three factors, which are the number of followers, betweenness centrality and the types of accounts. Community detection and machine learning are integrated into our approach. We find that the difference for correlation coefficients exists between different levels of the number of followers, and different types of users. Our method sheds a light on better predicting the dynamics of tweets diffusion by including the sentiment factor into the prediction model. © 2017 IEEE.
6 citations (Crossref) [2023-10-31] Citation Key Alias: pop00210 tex.type: [object Object]
Keywords: Artificial intelligence; Betweenness centrality; Community detection; Correlation coefficient; Data mining; Learning systems; Prediction model; Sentiment analysis; Sentiment scores; Social networking (online); Time-periods; Twitter classification; dept.csc; machine learning; sentiment analysis; social network

An empirical study on verifier order selection in serial fusion based multi-biometric verification system - Hossain, Md Shafaeat; Rahman, Khandaker Abir (Advances in Artificial Intelligence: From Theory to Practice, 2017)
Selecting the order of verifier in a serial fusion based multi-biometric system is a crucial parameter to fix because of its high impact on verification errors. A wrong choice of verifier order might lead to tremendous user inconvenience by denying a large number of genuine users and might cause severe security breach by accepting impostors frequently. Unfortunately, this design issue has been poorly investigated in multi-biometric literature. In this paper, we address this design issue by performing experiments using three different serial fusion based multi-biometric verification schemes, in particular (1) symmetric scheme, (2) SPRT-based scheme, and (3) Marcialis et al.’s scheme. We experimented on publicly available NIST-BSSR1 multi-modal database. We tested 24 orders—all possible orders originated from four individual verifiers—on a four-stage biometric verification system. Our experimental results show that the verifier order “best-to-worst”, where the best performing individual verifier is placed in the first stage, the next best performing individual verifier is placed in the second stage, and so on, is the top performing order for all three serial fusion schemes mentioned above.
2 citations (Crossref) [2023-10-31] Citation Key Alias: hossainEmpiricalStudyVerifier2017, pop00277 tex.type: [object Object]
Keywords: Biometric verification; Biometrics; Crucial parameters; Intelligent systems; Multi biometrics; Multi-biometric verification; Multibiometric systems; Multimodal database; Order selection; Security breaches; Serial fusion; Verifier order selection; dept.csc