Digital Commons Network^™

Finding Street Gang Member Profiles On Twitter, Lakshika Balasuriya

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The crime and violence street gangs introduce into neighborhoods is a growing epidemic in cities around the world. Today, over 1.4 million people, belonging to more than 33,000 gangs, are active in the United States, of which 88% identify themselves as being members of a street gang. With the recent popularity of social media, street gang members have established online presences coinciding with their physical occupation of neighborhoods. Recent studies report that approximately 45% of gang members participate in online offending activities such as threatening, harassing individuals, posting violent videos or attacking someone on the street for something they said …

Impact Of Reviewer Social Interaction On Online Consumer Review Fraud Detection, Kunal Goswami, Younghee Park, Chungsik Song

Faculty Publications

Background Online consumer reviews have become a baseline for new consumers to try out a business or a new product. The reviews provide a quick look into the application and experience of the business/product and market it to new customers. However, some businesses or reviewers use these reviews to spread fake information about the business/product. The fake information can be used to promote a relatively average product/business or can be used to malign their competition. This activity is known as reviewer fraud or opinion spam. The paper proposes a feature set, capturing the user social interaction behavior to identify fraud. …

Gait Analysis From Wearable Devices Using Image And Signal Processing, Bradley A. Schneider

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We present the results of analyzing gait motion in-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera and are validated using the ground truth dataset. We perform an additional data collection with both the camera and a body-worn accelerometer …

Annual Report 2016-2017, Depaul University College Of Computing And Digital Media

CDM Annual Reports

The College of Computing and Digital Media has always prided itself on curriculum, creative work, and research that stays current with changes in our various fields of instruction. As we looked back on our 2016-17 academic year, the need to chronicle the breadth and excellence of this work became clear. We are pleased to share with you this annual report, our first, highlighting our accomplishments.

Last year, we began offering three new graduate programs and two new certificate programs. We also planned six degree programs and three new certificate programs for implementation in the current academic year. CDM faculty were …

Semi-Supervised Approach To Monitoring Clinical Depressive Symptoms In Social Media, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Monireh Ebrahimi, Goonmeet Bajaj, Tanvi Banerjee, Krishnaprasad Thirunarayan, Jyotishman Pathak, Amit Sheth

Computer Science and Engineering Faculty Publications

With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of clinical depression from tweets obtained unobtrusively. Based on the analysis of tweets crawled from users with self-reported depressive symptoms in their Twitter profiles, we demonstrate the potential for detecting clinical depression symptoms which emulate the PHQ-9 questionnaire clinicians use today. Our study uses a semi-supervised statistical model to evaluate how the duration of these symptoms …

Identification And Characterization Of Irregular Consumptions Of Load Data, Desh Deepak Sharma, S. N. Singh, Jeremy Lin, Elham Foruzan

Department of Electrical and Computer Engineering: Faculty Publications

The historical information of loadings on substation helps in evaluation of size of photovoltaic (PV) generation and energy storages for peak shaving and distribution system upgrade deferral. A method, based on consumption data, is proposed to separate the unusual consumption and to form the clusters of similar regular consumption. The method does optimal partition of the load pattern data into core points and border points, high and less dense regions, respectively. The local outlier factor, which does not require fixed probability distribution of data and statistical measures, ranks the unusual consumptions on only the border points, which are a few …

Using Mediawiki, The Semantic Mediawiki Extension And Relfinder For Heritage Data Management: A Rock Art Case Study, Robert A. Haubt

Staff Scholarship - Australia & Dubai

This paper looks at the usefulness of the MediaWiki and relevant wiki extensions for rock art data management and research. The paper follows a framework provided by the Global Rock Art Database www.rockartdatabase.com and examines a new database model for a semantic data management approach. Through practical examples it explores the usefulness of wikis in the data management life cycle from data planning to collection, storage and dissemination and examines interconnections within each phase of the cycle. The paper proposes a combined use of the Semantic MediaWiki extension and the RelFinder for visualization of semantic relationships, which could assist researchers …

Cockpit In The Systems Engineering Lenses, Aysen K. Taylor, Charles B. Keating, T. Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

The commercial transport aircraft of today vary greatly from early aircraft in regards to how they are controlled and the feedback provided from the machine to the human operator. Automation has improved operational precision and efficiency but at the cost of providing less feedback. Pilots are the last line of defense and current technology cannot provide the human ability to solve novel problems for which no computer logic can be written. The automated cockpits of today have may sub-components that interact in a manner often opaque and unpredictable when a sensor or sub-component fails or even in situations where no …

Optimizing Rpl Objective Function For Mobile Low-Power Wireless Networks, Mohammad Abdellatif, Ifeoma Urama, Hossein Fotouhei

Electrical Engineering

Supporting mobility in wireless sensor networks is one of the major requirements for future Internet of Things (IoT) applications. This work focuses on optimizing the objective function of Routing Protocol for Low-power and Lossy Networks (RPL) in mobile applications. RPL routing is the most common standard routing protocol designed for IoT applications. We optimized RPL objective function by combining several RPL parameters, such as (i) Expected Transmission Count (ETX), (ii) number of hops, and (iii) average Received Signal Strength Indicator (RSSI) as inputs in a fuzzy logic model. These parameters are more influenced in mobile applications. We applied the fuzzy …

When Machines Decide: Creating Justice.Exe, Randy Dryer, Suresh Venkatasubramanian, Austin Anderson, Abigail Busath, Logan Cox, Morgan Cox, Logan Erickson, Zachary Grena, Joseph Hutchins, Skyler Jayson, Andrew Yang

Law School Historical Documents

Our Praxis Lab centered on the increasingly important need for algorithmic literacy, transparency and oversight, particularly in the context of the use of algorithms in the criminal justice system. Accordingly, we (1) designed an educational simulation to illustrate the function of algorithms in the context of criminal sentencing; (2) created several pre-packaged course modules that faculty in a variety of disciplines could integrate into their existing curriculum to educate students about algorithms and their increasing role in modern society; and (3) curated a set of best practices designed to promote the transparency and oversight of algorithmic systems.

Evaluation Of Career Readiness At An Industrial Technology Program Using A Fuzzy Approach, Ahmed Deif, Cameron Stark, Kathryn Butler, Eric Olsen

Industrial Technology and Packaging

In this research, a quantitative model to measure the “career readiness” performance level of the current curriculum of the Industrial Technology and Packaging program at California Polytechnic State University is proposed. Career readiness is first defined through performance attributes and these attributes are further classified into specific categories and metrics. Using a fuzzy logic computational approach, “career readiness” measures are developed and a “career readiness” score referred to as (CRS) is calculated. The model is designed to be flexible, dynamic and easy to use. It should enable a systematic measurement of career readiness by producing a final integrated unit-less score. …

A Neuro-Fuzzy Controller For Grid-Connected Heavy-Duty Gas Turbine Power Plants, Mohamed Iqbal Mohamed Mustafa, Joseph Xavier Rayappan, Kanakaraj Jagannathan

Turkish Journal of Electrical Engineering and Computer Sciences

Frequent load fluctuation and set-point variation may affect the stability of grid-connected heavy-duty gas turbine power plants. To overcome such problems, a novel neuro-fuzzy controller is proposed in this paper for single-shaft heavy-duty gas turbines ranging from 18.2 MW to 106.7 MW. A neuro-fuzzy controller was developed using a hybrid learning algorithm and the effectiveness of the controller for all heavy-duty gas turbine plants (5, 6, 7, and 9 series) is demonstrated against load disturbance and set-point variation in a grid-connected environment. Various time domain specifications and performance index criteria of the neuro-fuzzy controller are compared with that of a …

Nonlinear Model Predictive Control Based On Fuzzy Wavelet Neural Network And Chaos Optimization, Mehrnoush Davanipour, Hanieh Asadipooya

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a combined controller is proposed for nonlinear dynamical systems. The controller is constructed by a fuzzy wavelet network and nonlinear model predictive control. Chaotic optimization, which is fast and robust, is applied to generate optimized controlled input in nonlinear model predictive control. The ability of the fuzzy wavelet neural network and the proposed controller is shown by simulation. It is illustrated that the proposed method is able to increase the speed of tracking in addition to having very little steady state error. Using chaotic optimization makes the controller robust in the presence of noise.

A New Word-Based Compression Model Allowing Compressed Pattern Matching, Hali̇l Nusret Buluş, Aydin Carus, Altan Mesut

Turkish Journal of Electrical Engineering and Computer Sciences

In this study a new semistatic data compression model that has a fast coding process and that allows compressed pattern matching is introduced. The name of the proposed model is chosen as tagged word-based compression algorithm (TWBCA) since it has a word-based coding and word-based compressed matching algorithm. The model has two phases. In the first phase a dictionary is constructed by adding a phrase, paying attention to word boundaries, and in the second phase compression is done by using codewords of phrases in this dictionary. The first byte of the codeword determines whether the word is compressed or not. …

Multiverse Optimized Fuzzy-Pid Controller With A Derivative Filter For Load Frequency Control Of Multisource Hydrothermal Power System, Amit Kumar, Sathans Suhag

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a multiverse optimized (MVO) fuzzy PID controller with a derivative filter (fuzzy-PIDF) is proposed for the load frequency control (LFC) of a two-area multisource hydrothermal power system. The superiority of the MVO algorithm is demonstrated by comparing the system LFC performance with integral and fuzzy-PIDF controllers, both optimized using MVO, as well as some of the recent heuristic optimization techniques such as the ant lion optimizer, gray wolf optimizer, differential evolution, bacterial foraging optimization algorithm, and particle swarm optimization. To the best of the knowledge of the authors, the use of the MVO technique has not yet …

Indirect Adaptive Neurofuzzy Hermite Wavelet Based Control Of Pv In A Grid-Connected Hybrid Power System, Sidra Mumtaz, Laiq Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Owing to the evolution of the smart grid, the emergence of hybrid power systems (HPSs), and the proliferation of plug-in-hybrid electric vehicles, the development of efficient and robust maximum power point tracking (MPPT) algorithms for renewable energy sources due to their inherent intermittent nature has overwhelmed the power industry. In this paper, an incremental conductance (IC) based Hermite wavelet incorporated neurofuzzy indirect adaptive MPPT control paradigm for a photovoltaic (PV) system in a grid-connected HPS is proposed. The performance of the proposed adaptive Hermite wavelet incorporated neurofuzzy MPPT control paradigm is validated through a comprehensive grid-connected HPS test-bed developed in …

Turkish Synonym Identification From Multiple Resources: Monolingual Corpus, Mono/Bilingual Online Dictionaries, And Wordnet, Tuğba Yildiz, Banu Di̇ri̇, Savaş Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a model is proposed to determine synonymy by incorporating several resources. The model extracts the features from monolingual online dictionaries, a bilingual online dictionary, WordNet, and a monolingual Turkish corpus. Once it has built a candidate list, it determines the synonymy for a given word by means of those features. All these resources and the approaches are evaluated. Taking all features into account and applying machine learning algorithms, the model shows good performance of F-measure with 81.4%. The study contributes to the literature by integrating several resources and attempting the first corpus-driven synonym detection system for Turkish.

A Self-Tuning Neurofuzzy Feedback Linearization-Based Damping Control Strategy For Multiple Hvdc Links, Saghir Ahmad, Laiq Khan

Turkish Journal of Electrical Engineering and Computer Sciences

This research work proposes a multi-input multi-output (MIMO) online adaptive feedback linearization NeuroFuzzy control (AFLNFC) scheme to improve the damping of low frequency oscillations (LFOs) in an AC/DC power system. Optimized NeuroFuzzy identification architecture online captures the oscillatory dynamics of the power system through wide area measurement system (WAMS)-based measured speed signals of machines. Based on the identified power system model, the appropriate control law is derived through feedback linearization control with a self-tuned coefficient vector. The generated control signal modulates the real power flow through a high voltage direct current (HVDC) link during perturbed operating conditions and enhances system …

A Data-Aware Cognitive Engine For Scheduling Data Intensive Applications In A Grid, Vijaya Nagarajan, Maluk Mohamed Mulk Abdul

Turkish Journal of Electrical Engineering and Computer Sciences

Data-intensive applications produce huge amounts of data that need to be stored, analyzed, and interpreted. A data grid serves as a cost-effective infrastructure for solving these data-intensive applications. Existing scheduling strategies are best suited for handling compute-intensive applications, although they lack in performance while handling data-intensive applications. In this work, a novel mechanism of incorporating cognitive science in a data grid is proposed for scheduling data-intensive workflows. A unique model is derived in which a cognitive engine (CE) is built into the middleware of the data grid. The intelligent agents present in the CE handle the request for data sets …

Adslanf: A Negotiation Framework For Cloud Management Systems Using A Bulk Negotiation Behavioral Learning Approach, Rajkumar Rajavel, Mala Thangarathinam

Turkish Journal of Electrical Engineering and Computer Sciences

One of the major challenges in cloud computing is the development of a service-level agreement (SLA) negotiation framework using an intelligent third-party broker negotiation strategy. Current frameworks exploit various negotiation strategies using game theoretic, heuristic, and argumentation-based approaches for obtaining optimal negotiation with a better success rate (negotiation commitment). However, these approaches fail to optimize the negotiation round (NR), total negotiation time (TNT), and communication overhead (CO) involved in the negotiation strategy. To overcome these problems, certain researchers have exploited trade-off, concession, and behavioral learning strategies with varying degrees of sacrifices (reductions) in their concerned proposal generation. Such sacrifices can …

A Hybrid Of Sliding Mode Control And Fuzzy Logic Control Using A Fuzzy Supervisory Switched System For Dc Motor Speed Control, Husain Ahmed, Abha Rajoriya

Turkish Journal of Electrical Engineering and Computer Sciences

In many applications of DC motor speed control systems, PID controllers are mostly used. Such control schemes do not show good performance when input and load torque disturbances are applied. This paper shows that sliding mode (SM) can give better control due to its robust property but it has an unwanted chattering problem associated with it, which is harmful to the plant. To limit this problem a hybrid controller is presented in which a fuzzy controller is combined with the SM controller by a fuzzy supervisory system in such a way that the SM controller works in transient state and …

Android Malware Classification Based On Anfis With Fuzzy C-Means Clustering Using Significant Application Permissions, Altyeb Altaher, Omar Barukab

Turkish Journal of Electrical Engineering and Computer Sciences

Mobile phones have become an essential part of our lives because we depend on them to perform many tasks, and they contain personal and important information. The continuous growth in the number of Android mobile applications resulted in an increase in the number of malware applications, which are real threats and can cause great losses. There is an urgent need for efficient and effective Android malware detection techniques. In this paper, we present an adaptive neuro-fuzzy inference system with fuzzy c-means clustering (FCM-ANFIS) for Android malware classification. The proposed approach utilizes the FCM clustering method to determine the optimum number …

Turkish Entity Discovery With Word Embeddings, Murat Kalender, Emi̇n Erkan Korkmaz

Turkish Journal of Electrical Engineering and Computer Sciences

Entity-linking systems link noun phrase mentions in a text to their corresponding knowledge base entities in order to enrich a text with metadata. Wikipedia is a popular and comprehensive knowledge base that is widely used in entity-linking systems. However, long-tail entities are not popular enough to have their own Wikipedia articles. Therefore, a knowledge base created by using Wikipedia entities would be limited to only popular entities. In order to overcome the knowledge base coverage limitation of Wikipedia-based entity-linking systems, this paper presents an entity-discovery system that can detect semantic types of entities that are not defined in Wikipedia. The …

Evaluation Of Distance Education Websites: A Hybrid Multicriteria Approach, Mehmet Kabak, Eren Özceylan, Meti̇n Dağdevi̇ren, Tolga Genç

Turkish Journal of Electrical Engineering and Computer Sciences

This study provides an evaluation model that prioritizes the relative weights of various distance education websites. The proposed approach consists of four sequential steps. In the first step, 25 different subcriteria under 4 major criteria are gathered from the existing literature. Identified criteria are weighted by stakeholders of distance education websites using the analytic network process outlined in the second step. In the third step, the technique for order preference by similarity to ideal solution method is applied in order to rank the 15 different Turkish distance education website alternatives. Finally, in the fourth step, different scenario analyses are applied …

Hesitant Fuzzy Pairwise Comparison For Software Cost Estimation: A Case Study In Turkey, Ayfer Başar

Turkish Journal of Electrical Engineering and Computer Sciences

Estimating the cost of software is a complex process for almost all engineering companies. Uncertainties about development method, design, estimation process, data, and processing affect the accuracy of estimation. Underestimation results in fewer resources being committed than the project really needs, an unrealistic schedule, and low quality outputs. On the other hand, overestimation wastes resources and causes loss of customer credit. Thus, choosing the appropriate cost estimation method is crucial. Studies in the literature emphasize the importance of empirical, analytical methods and expert judgement. Certain cost estimation techniques have been widely studied in the literature. However, there are limited studies …

Analysis Of Mechanical Properties Of Alternative Timber Beams For A Native American Earth Lodge, Freddy E. Moran

Electronic Theses and Dissertations

To fill a gap in the literature, this thesis explored the mechanical properties for alternative roof beams of a historic Native American Hidatsa earth lodge. The research demonstrates that in those alternative beams, when Moisture Content (MC) increases, Modulus of Elasticity (E) decreases and deflection increases. The procedure included obtaining dimensions for alternative beams from scaled sketches created by ethnographers and informants who recorded an actual Hidatsa earth lodge in the early 1800s (confirmed by other sources) although no material properties studies have resulted. After calculating loads, the variations in the E were determined using an equation. Using linear analysis, …

Efficacy Of Real-Time Functional Magnetic Resonance Imaging Neurofeedback Training (Fmri-Nft) In The Treatment Of Tinnitus, Matthew S. Sherwood

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There is a growing interest in the application of real-time (fMRI) with neurofeedback training (NFT) to the treatment of disorders associated with abnormal brain function. Chronic tinnitus is one such disorder that is often characterized by hyperactivity of the primary auditory cortex (A1) and decreased activity of the ventromedial prefrontal cortex (vmPFC). In this work, we investigated the use of fMRI-NFT to teach self-regulation of A1 using directed attention strategies. The overall objective of the proposed study is to determine the efficacy of fMRI-NFT for potential treatment of tinnitus. Healthy participants were separated into two groups: the experimental group received …

A Lattice Theoretic Look: A Negated Approach To Adjectival (Intersective, Neutrosophic And Private) Phrases, Florentin Smarandache, Selcuk Topal

Branch Mathematics and Statistics Faculty and Staff Publications

No abstract provided.

Computation Of Shortest Path Problem In A Network With Sv-Triangular Neutrosophic Numbers, Florentin Smarandache, Said Broumi, Assia Bakali, Mohamed Talea

Branch Mathematics and Statistics Faculty and Staff Publications

In this article, we present an algorithm method for finding the shortest path length between a paired nodes on a network where the edge weights are characterized by single valued triangular neutrosophic numbers. The proposed algorithm gives the shortest shortest path length from source node to destination node based on a ranking method. Finally, a numerical example is also presented to illustrate the efficiency of the proposed approach.

An Operational View In Computational Construction Of Information, Florentin Smarandache, Stefan Vladutescu, Constantin Dima, Valeriu Voinea

Branch Mathematics and Statistics Faculty and Staff Publications

The paper aims to explain the technology of emergence of information. Our research proves that information as communicational product is the result of processing within some operations, actions, mechanisms and strategies of informational material meanings. Are determined eight computational-communicative operations of building information. Information occurs in two communication phases, syncretic and the segregation-synthetic. The syncretic phase consists of four operations: referral of significant field, primary delimitation of information, detection-looking information and an anticipative-draft constitution (feedforward). The segregation-synthetic phase also includes four operations: discrimination, identification, interpretation and confrontation (feedback). In the future we will investigate informational actions, mechanisms and strategies.