Computer Engineering Commons^™

Investigation Of An Object Follower System, Eli̇f Erzan Topçu, Ahmet Demi̇rkesen, İbrahi̇m Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Implementation Analyses Of Proteins And Genes Obtained From Cancer Patients, Murat Demi̇r, Ali̇ Karci

Turkish Journal of Electrical Engineering and Computer Sciences

bioinformatics and computational molecular biology, since these studies may result in important results in the case of diseases. Due to this, in this study, bioinformatics data were analyzed based on nucleotides and motifs. Bioinformatics data for proteins were obtained from two different databases. The obtained data belonged to cancer patients, and the genes in these DNA and protein sequences, the proteins synthesized by these sequences, and motifs in these data were analyzed. In the analysis, the ABCB1, ALOX5AP, AKT1, BRCA1, BRCA2, TNF, TNFSF13B, TP53, TP63, TP73, and WT1 genes were used. The proteins synthesized by genes belonging to similar classes …

Short-Term Economic Emission Power Scheduling Of Hydrothermal Systems Using Improved Chaotic Hybrid Differential Evolution, Tahir Nadeem Malik, Salman Zafar, Saaqib Haroon

Turkish Journal of Electrical Engineering and Computer Sciences

utilities to retain their generations within maximum allowable emission levels. Therefore, in present-day power system operations, the minimization of emission pollutants along with the total fuel cost has become an important aspect in short-term generation scheduling of hydrothermal power systems. This paper presents an improved hybrid approach based on the application of chaos theory in a differential evolution (DE) algorithm for the solution of this biobjective constrained optimization problem. In this proposed methodology, self-adjusted parameter setting in DE is obtained by using chaotic sequences. Secondly, a chaotic hybridized local search mechanism is embedded in DE to avoid it from trapping …

Effects Of Mica2-Based Discrete Energy Levels On The Lifetime Of Cooperation Neighbor Sensor Networks, Zeydi̇n Pala

Turkish Journal of Electrical Engineering and Computer Sciences

using Mica2 mote discrete power levels on neighbor sensor network lifetime. We built a linear programming framework to qualify the cooperation of sensor networks using a discrete energy model in comparison to noncooperating networks. Our results showed that a wireless sensor neighbor network that uses a discrete radio model can be more energy efficient than a network that uses a nondiscrete energy model.

Cascaded Half-Full-Bridge Pwm Multilevel Inverter Configuration, Charles Ikechukwu Odeh

Turkish Journal of Electrical Engineering and Computer Sciences

inverter topology. It is made up of a main inverting H-bridge legs and level-clamping half-bridge circuits, each having its own dc source. The single-carrier, multilevel PWM scheme is employed to generate gating signals for the power switches. The modulation scheme is hybridized to enable the output voltage of the proposed inverter configuration to inherit the features of switching-loss reduction from fundamental PWM and good harmonic performance from multiple sinusoidal PWM. Moreover, a simple base PWM circulation scheme is also introduced in this work to obtain a resultant sequential switching hybrid PWM (SSHPWM) circulation that balances power dissipation among the four …

A Current Feedback Control Strategy For Parallel-Connected Single-Phase Inverters Using A Third-Order General-Integrator Crossover Cancellation Method, Yuan Huang, An Luo

Turkish Journal of Electrical Engineering and Computer Sciences

Virtual impedance is usually introduced to the control system of parallel inverters in order to change the inverter equivalent output impedance and to enhance control accuracy and power sharing. In this paper, a current feedback control strategy using a third-order general-integrator crossover-cancellation method that can be implemented in a virtual impedance loop is proposed. This method consists of 2 parts: a crossover-cancellation feedback network, which achieves the band-pass effect, and a multilevel TOGI-OSG link, which acts as a filter. Compared with the conventional virtual impedance method, the proposed method can avoid derivation of output current, reduce system calculating burden, and …

The Use Of Cross-Company Fault Data For The Software Fault Prediction Problem, Çağatay Çatal

Turkish Journal of Electrical Engineering and Computer Sciences

We investigated how to use cross-company (CC) data in software fault prediction and in predicting the fault labels of software modules when there are not enough fault data. This paper involves case studies of NASA projects that can be accessed from the PROMISE repository. Case studies show that CC data help build high-performance fault predictors in the absence of fault labels and remarkable results are achieved. We suggest that companies use CC data if they do not have any historical fault data when they decide to build their fault prediction models.

It Centralization And The Innovation Value Chain In Higher Education: A Study For Promoting Key Innovations Through Innovation Management And Organizational Design, Edmund Udaya Clark

All Graduate Theses, Dissertations, and Other Capstone Projects

The purpose of the present study was to investigate the impact of organizational centralization in higher education technology support units on institutional innovativeness. The centralization tools used for the present study included measures developed by Hage & Aiken (1971), Kaluzny, et al. (1974), and Ferrell & Skinner (1988). The innovativeness measures were established by Hansen & Birkinshaw's (2007) tool for evaluating innovation value chain activities in organizations. Data were gathered from a nation-wide sample (n = 303) of IT workers at 38 research one institutions in the United States. The results indicated that innovation value chain activities (idea generation, conversion, …

An Evaluation Of Robotics In Nursing Homes To Reduce Adverse Drug Events, Ozell Ueal Jr.

Walden Dissertations and Doctoral Studies

Adverse drug events (ADE) cause many deaths annually in addition to affecting the quality of life of many others. The descriptive mixed methods approach, specifically exploratory case study and experimental design that guided this research utilized the survey and focus group methods to evaluate perceptions about robotic technology (RT) to reduce the rate of ADEs in U.S. nursing homes (NH). There is a lack of scholarly research into whether a conceptual approach rooted in RT can be implemented to assist with drug administrations in NHs. The purpose of this study was twofold. The first purpose was to evaluate the causes …

Multi-Type Display Calculus For Propositional Dynamic Logic, Sabine Frittella, Giuseppe Greco, Alexander Kurz, Alessandra Palmigiano

Engineering Faculty Articles and Research

We introduce a multi-type display calculus for Propositional Dynamic Logic (PDL). This calculus is complete w.r.t. PDL, and enjoys Belnap-style cut-elimination and subformula property.

Tool Support For Reasoning In Display Calculi, Samuel Balco, Sabine Frittella, Giuseppe Greco, Alexander Kurz, Alessandra Palmigiano

Engineering Faculty Articles and Research

We present a tool for reasoning in and about propositional sequent calculi. One aim is to support reasoning in calculi that contain a hundred rules or more, so that even relatively small pen and paper derivations become tedious and error prone. As an example, we implement the display calculus D.EAK of dynamic epistemic logic. Second, we provide embeddings of the calculus in the theorem prover Isabelle for formalising proofs about D.EAK. As a case study we show that the solution of the muddy children puzzle is derivable for any number of muddy children. Third, there is a set of meta-tools, …

Table Of Contents

Journal of International Technology and Information Management

Table of Contents for Volume 25 Number 4

Conceptual Models On The Effectiveness Of E-Marketing Strategies In Engaging Consumers, Cheristena Bolos, Efosa C. Idemudia, Phoebe Mai, Mahesh Rasinghani, Shelley Smith

Journal of International Technology and Information Management

Effective marketing has always been an important factor in business success. Without the ability to identify customers and convince them to purchase the product or service being offered, businesses would not survive. Recent advancements in technology have given rise to new opportunities to engage customers through the use of electronic marketing (e-marketing). E- marketing draws from traditional marketing principles, while also expanding the types of strategies available to companies. Websites, social media, and online marketplaces are just some examples of how businesses are leveraging e-marketing approaches to connect with potential customers. In formulating sound e-marketing strategies, it is important for …

Healthcare System-Use Behavior: A Systematic Review Of Its Determinants, Jiming Wu

Journal of International Technology and Information Management

To understand patient and physician behavior, researchers have investigated the determinants of using healthcare information systems. Although this stream of research has produced important findings, it has yet to appreciably advance our understanding of system-use behavior in healthcare. To fill this gap, the current paper employs a systematic review to synthesize past research, reveal the key determinants of healthcare system usage, and illuminate a deeper understanding of the topic. This study thus helps healthcare researchers expand their baseline knowledge of these core determinants and conduct more fruitful future research on system-use behavior in healthcare.

Clustering: Methodology, Hybrid Systems, Visualization, Validation And Implementation, Dao Minh Lam

Doctoral Dissertations

"Unsupervised learning is one of the most important steps of machine learning applications. Besides its ability to obtain the insight of the data distribution, unsupervised learning is used as a preprocessing step for other machine learning algorithm. This dissertation investigates the application of unsupervised learning into various types of data for many machine learning tasks such as clustering, regression and classification. The dissertation is organized into three papers. In the first paper, unsupervised learning is applied to mixed categorical and numerical feature data type to transform the data objects from the mixed type feature domain into a new sparser numerical …

Robots As Legal Metaphors, Ryan Calo

Articles

This Article looks at the specific role robots play in the judicial imagination. The law and technology literature is replete with examples of how the metaphors and analogies that courts select for emerging technology can be outcome determinative. Privacy law scholar Professor Daniel Solove argues convincingly, for instance, that George Orwell's Big Brother metaphor has come to dominate, and in ways limit, privacy law and policy in the United States. Even at a more specific, practical level, whether a judge sees email as more like a letter or a postcard will dictate the level of Fourth Amendment protection she is …

A Cloud-Based Framework For Smart Permit System For Buildings, Magdalini Eirinaki, Subhankar Dhar, Shishir Mathur

Faculty Publications

In this paper we propose a novel cloud-based platform for building permit system that is efficient, user-friendly, transparent, and has quick turn-around time for homeowners. Compared to the existing permit systems, the proposed smart city permit framework provides a pre-permitting decision workflow, and incorporates a data analytics and mining module that enables the continuous improvement of a) the end user experience, by analyzing explicit and implicit user feedback, and b) the permitting and urban planning process, allowing a gleaning of key insights for real estate development and city planning purposes, by analyzing how users interact with the system depending on …

Pro-Fit: Exercise With Friends, Saumil Dharia, Vijesh Jain, Jvalant Patel, Jainikkumar Vora, Rizen Yamauchi, Magdalini Eirinaki, Iraklis Varlamis

Faculty Publications

The advancements in wearable technology, where embedded accelerometers, gyroscopes and other sensors enable the users to actively monitor their activity have made it easier for individuals to pursue a healthy lifestyle. However, most of the existing applications expect continuous commitment from the end users, who need to proactively interact with the application in order to connect with friends and attain their goals. These applications fail to engage and motivate users who have busy schedules, or are not as committed and self-motivated. In this work, we present PRO-Fit, a personalized fitness assistant application that employs machine learning and recommendation algorithms in …

Threshold-Bounded Influence Dominating Sets For Recommendations In Social Networks, Magdalini Eirinaki, Nuno Moniz, Katerina Potika

Faculty Publications

The process of decision making in humans involves a combination of the genuine information held by the individual, and the external influence from their social network connections. This helps individuals to make decisions or adopt behaviors, opinions or products. In this work, we seek to investigate under which conditions and with what cost we can form neighborhoods of influence within a social network, in order to assist individuals with little or no prior genuine information through a two-phase recommendation process. Most of the existing approaches regard the problem of identifying influentials as a long-term, network diffusion process, where information cascading …

Time-Based Ensembles For Prediction Of Rare Events In News Streams, Nuno Moniz, Luís Torgo, Magdalini Eirinaki

Faculty Publications

Thousands of news are published everyday reporting worldwide events. Most of these news obtain a low level of popularity and only a small set of events become highly popular in social media platforms. Predicting rare cases of highly popular news is not a trivial task due to shortcomings of standard learning approaches and evaluation metrics. So far, the standard task of predicting the popularity of news items has been tackled by either of two distinct strategies related to the publication time of news. The first strategy, a priori, is focused on predicting the popularity of news upon their publication when …

Positioning Commuters And Shoppers Through Sensing And Correlation, Rufeng Meng

Theses and Dissertations

Positioning is a basic and important need in many scenarios of human daily activities. With position information, multifarious services could be vitalized to benefit all kinds of users, from individuals to organizations. Through positioning, people are able to obtain not only geo-location but also time related information. By aggregating position information from individuals, organizations could derive statistical knowledge about group behaviors, such as traffic, business, event, etc.

Although enormous effort has been invested in positioning related academic and industrial work, there are still many holes to be filled. This dissertation proposes solutions to address the need of positioning in people’s …

Digital Forensics In Law Enforcement: A Needs Based Analysis Of Indiana Agencies, Teri A. Cummins Flory

Journal of Digital Forensics, Security and Law

Cyber crime is a growing problem, with the impact to society increasing exponentially, but the ability of local law enforcement agencies to investigate and successfully prosecute criminals for these crimes is unclear. Many national needs assessments have previously been conducted, and all indicated that state and local law enforcement did not have the training, tools, or staff to effectively conduct digital investigations, but very few have been completed recently. This study provided a current and localized assessment of the ability of Indiana law enforcement agencies to effectively investigate crimes involving digital evidence, the availability of training for both law enforcement …

Verification Of Recovered Digital Evidence On The Amazon Kindle, Marcus Thompson, Raymond Hansen

Journal of Digital Forensics, Security and Law

The Amazon Kindle is a popular e-book reader. This popularity will lead criminals to use the Kindle as an accessory to their crime. Very few Kindle publications in the digital forensics domain exist at the time of this writing. Various blogs on the Internet currently provide some of the foundation for Kindle forensics. For this research each fifth generation Kindle was populated with various types of files a typical user may introduce using one method, the USB interface. The Kindle was forensically imaged with AccessData’s Forensic Toolkit Imager before and after each Kindle was populated. Each file was deleted through …

Making Sense Of Email Addresses On Drives, Neil C. Rowe, Riqui Schwamm, Michael R. Mccarrin, Ralucca Gera

Journal of Digital Forensics, Security and Law

Drives found during investigations often have useful information in the form of email addresses which can be acquired by search in the raw drive data independent of the file system. Using this data we can build a picture of the social networks that a drive owner participated in, even perhaps better than investigating their online profiles maintained by social-networking services because drives contain much data that users have not approved for public display. However, many addresses found on drives are not forensically interesting, such as sales and support links. We developed a program to filter these out using a Naïve …

Countering Noise-Based Splicing Detection Using Noise Density Transfer, Thibault Julliand, Vincent Nozick, Hugues Talbot

Journal of Digital Forensics, Security and Law

Image splicing is a common and widespread type of manipulation, which is defined as pasting a portion of an image onto a second image. Several forensic methods have been developed to detect splicing, using various image properties. Some of these methods exploit the noise statistics of the image to try and find discrepancies. In this paper, we propose a new counter-forensic approach to eliminate the noise differences that can appear in a spliced image. This approach can also be used when creating computer graphics images, in order to endow them with a realistic noise. This is performed by changing the …

Evidential Reasoning For Forensic Readiness, Yi-Ching Liao, Hanno Langweg

Journal of Digital Forensics, Security and Law

To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Electronic Voting Service Using Block-Chain, Kibin Lee, Joshua I. James, Tekachew G. Ejeta, Hyoung J. Kim

Journal of Digital Forensics, Security and Law

Cryptocurrency, and its underlying technologies, has been gaining popularity for transaction management beyond financial transactions. Transaction information is maintained in the block-chain, which can be used to audit the integrity of the transaction. The focus on this paper is the potential availability of block-chain technology of other transactional uses. Block-chain is one of the most stable open ledgers that preserves transaction information, and is difficult to forge. Since the information stored in block-chain is not related to personally identify information, it has the characteristics of anonymity. Also, the block-chain allows for transparent transaction verification since all information in the block-chain …

Internet Of Things To Smart Iot Through Semantic, Cognitive, And Perceptual Computing, Amit P. Sheth

Publications

Rapid growth in the Internet of Things (IoT) has resulted in a massive growth of data generated by these devices and sensors put on the Internet. Physical-cyber-social (PCS) big data consist of this IoT data, complemented by relevant Web-based and social data of various modalities. Smart data is about exploiting this PCS big data to get deep insights and make it actionable, and making it possible to facilitate building intelligent systems and applications. This article discusses key AI research in semantic computing, cognitive computing, and perceptual computing. Their synergistic use is expected to power future progress in building intelligent systems …