Computer Sciences Commons^™

A Compact Pattern Reconfigurable Antenna Employing Shorted Quarterwave Patch Antennas, Feza Turgay Çeli̇k, Lale Alatan, Hati̇ce Özlem Aydin Çi̇vi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a compact pattern reconfigurable antenna structure is proposed. The proposed antenna is a half-wave square microstrip patch antenna divided into two quarter-wave antenna portions by a conducting wall. This wall forces potential zero at the connection point; therefore, it separates the antenna into two independent quarter-wave portions. Pattern reconfiguration is achieved by separate feeding of the quarter-wave portions. Phase difference between excitations of antenna ports result in variation at the maximum beam direction. Hence, pattern reconfiguration is achieved. Within such a compact antenna, beam steering up to 400 is achieved

A New Network-Based Community Detection Algorithm For Disjoint Communities, Peli̇n Çeti̇n, Şahi̇n Emrah Amrahov

Turkish Journal of Electrical Engineering and Computer Sciences

A community is a group of people that shares something in common. The definition of the community can be generalized as things that have common properties. By using this definition, community detection can be used to solve different problems in various areas. In this study, we propose a new network-based community detection algorithm that can work on different types of datasets. The proposed algorithm works on unweighted graphs and determines the weight by using cosine similarity. We apply a bottom-up approach and find the disjoint communities. First, we accept each node as an independent community. Then, the merging process is …

On Approximate Nash Equilibria Of The Two-Source Connection Game, Buğra Çaşkurlu, Utku Umur Açikalin, Fati̇h Erdem Kizilkaya, Özgün Eki̇ci̇

Turkish Journal of Electrical Engineering and Computer Sciences

The arbitrary-sharing connection game is prominent in the network formation game literature [1]. An undirected graph with positive edge weights is given, where the weight of an edge is the cost of building it. An edge is built if agents contribute a sufficient amount for its construction. For agent i, the goal is to contribute the least possible amount while assuring that the source node si is connected to the terminal node ti . In this paper, we study the special case of this game in which there are only two source nodes. In this setting, we prove that there …

Chemical Disease Relation Extraction Through The Combination Of Multiple Mention Levels: Relscan+, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş

Turkish Journal of Electrical Engineering and Computer Sciences

Chemical-induced disease (CID) relation extraction has been pivotal in the understanding of biological processes. A CID relation between a chemical and disease entity may be extracted either from a single sentence or from two or more adjacent sentences. We use `intrasentence level' to refer to the mention of the desired entities in the same sentence and `intersentence level? to refer to the mention of these entities in two or more adjacent sentences. This study proposes a three-phase architecture for extracting CID relations from biomedical literature by considering both sentence levels and additionally the combination of these two sentence levels which …

Inserting Of Heuristic Techniques Into The Stability Regions For Multiarea Load Frequency Control Systems With Time Delays, Mustafa Saka, Şahi̇n Sönmez, İbrahi̇m Eke, Haluk Gözde, Müslüm Cengi̇z Taplamacioğlu, Saffet Ayasun

Turkish Journal of Electrical Engineering and Computer Sciences

The design and optimization of robust controller parameters are required to improve the controller performances and to keep the stability of load frequency control (LFC) system. In addition, reducing the number of iterations and computational time is very important for swiftly tuning of the controller parameters and the system to reach stability rapidly. For this purpose, this study presents the inserting of heuristic optimization techniques into stability regions method identified in proportional-integral (PI) controllers space for multiarea LFC systems with communication time delays (CTDs). This method consists of two steps: determination of stability region for the system and application of …

A Novel Broadband Double-Ring Holed Element Metasurface Absorber To Suppress Emi From Pcb Heatsinks, Bülent Urul, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t, Abdullah Genç

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a new Broadband Double Ring Hole Element (BDHE) meta-surface absorber is studied to suppress EMI from PCB heatsink for 1-12 GHz covering L, S, C, and X bands. The proposed metamaterial-structure consists of resistances and 8 ring resonators, four of which are inner and four are outer that are configured to provide an absorbing effect. For broadband, numerical simulations show that an average of 65% absorption value is obtained between 4-12 GHz. It is determined that this value reached 69.84% by increasing the used resistance values (R = 150?). This value may be significant to reduce the …

Learning To Play An Imperfect Information Card Game Using Reinforcement Learning, Buğra Kaan Demi̇rdöver, Ömer Baykal, Ferdanur Alpaslan

Turkish Journal of Electrical Engineering and Computer Sciences

Artificial intelligence and machine learning are widely popular in many areas. One of the most popular ones is gaming. Games are perfect testbeds for machine learning and artificial intelligence with various scenarios and types. This study aims to develop a self-learning intelligent agent to play the Hearts game. Hearts is one of the most popular trick-taking card games around the world. It is an imperfect information card game. In addition to having a huge state space, Hearts offers many extra challenges due to its nature. In order to ease the development process, the agent developed in the scope of this …

Comparison Of Deep Learning And Regression-Based Mppt Algorithms In Pv Systems, Murat Sali̇m Karabi̇naoğlu, Beki̇r Çakir, Mustafa Engi̇n Başoğlu, Abdülvehhab Kazdaloğlu, Azi̇z Güneroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Solar energy systems (SES) and photovoltaic (PV) modules should be operated at the maximum power point (MPP) to achieve the highest efficiency in the energy generation processes. Maximum power point tracking (MPPT) applications using conventional methods may not be able to follow the global MPP (GMPP) of the PV system under changing atmospheric conditions and they could oscillate around the local MPP. In this study, a machine learning and deep learning (DL) based long short-term memory (LSTM) model is proposed as an innovative solution for MPPT. Contrary to the traditional MPPT applications using current and voltage sensors, the output resistance …

Presenting A Method To Detect Intrusion In Iot Through Private Blockchain, Rezvan Mahmoudie, Saeed Parsa, Amir Masoud Rahmani

Turkish Journal of Electrical Engineering and Computer Sciences

Blockchain (BC) has been used as a new solution to overcome security and privacy challenges in the Internet of Things (IoT). However, recent studies have indicated that the BC has a limited scalability and is computationally costly. Also, it has significant overhead and delay in the network, which is not suitable to the nature of IoT. This article aims at implementing BC in the IoT context for smart home management, as the integration of these two technologies ensures the IoT's security and privacy. Therefore, we proposed an overlay network in private BC to optimize its compatibility with IoT by increasing …

Improving The Performance Of Industrial Mixers That Are Used In Agricultural Technologies Via Chaotic Systems And Artificial Intelligence Techniques, Onur Kalayci, İhsan Pehli̇van, Selçuk Coşkun

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, it is aimed to show how important to apply chaotic systems and Fuzzy Logic artificial intelligence technique to increase the production performance of industrial mixers used in agriculture in terms of important criteria such as product quality, homogeneity, time, and energy saving by using. A PLC (Programmable Logic Controller) controlled mixer whose all functions can be controlled by the HMI (Human Machine Interface) operator panel is designed and manufactured for experimental studies. Water, leonardite and potassium hydroxide (KOH) mixture components are mixed in a newly designed mixer in three different ways by using traditional, chaos, and artificial …

Rtpltool: A Software Tool For Path Loss Modeling In 5g Outdoor Systems, Ci̇han Bariş Findik, Özlem Özgün

Turkish Journal of Electrical Engineering and Computer Sciences

The increase in the required bandwidth along with the global growth of existing wireless communication systems is one of the major reasons why research and industry communities are exploring 5G and millimeter-wave frequencies. The advantages of millimeter wave frequencies for 5G applications are a wide range of accessible and unlicensed spectrum, the use of small antennas in RF applications with increasing frequency, and low losses due to the interference effects compared to the currently used frequency bands. However, due to some computational challenges especially at millimeter waves (i.e. in FR2 frequency band), it is necessary to develop efficient software tools …

Design And Implementation Of A Low Cost And Portable Tactile Stimulator, Coşkun Kazma, Vecdi̇ Emre Levent, Merve Çardak, Ni̇zametti̇n Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

When central nervous system has a problem, somatic area I and II respond to stimulation differently. Therefore, it is possible to identify some of the central nervous diseases when somatosensory on the fingertip is stimulated and responses are recorded and analyzed. We designed a system to stimulate the mechanoreceptors on fingertips. It is composed of a mechanical system for fingertip stimulation, an embedded controller, a control computer, and a software to control overall operation. During test, mechanoreceptors are stimulated according to the test protocols. Individuals' answers are recorded to be evaluated by the developed software. In this study, several design …

How Facial Features Convey Attention In Stationary Environments, Janelle Domantay, Brendan Morris

Spectra Undergraduate Research Journal

Awareness detection technologies have been gaining traction in a variety of enterprises; most often used for driver fatigue detection, recent research has shifted towards using computer vision technologies to analyze user attention in environments such as online classrooms. This paper aims to extend previous research on distraction detection by analyzing which visual features contribute most to predicting awareness and fatigue. We utilized the open-source facial analysis toolkit OpenFace in order to analyze visual data of subjects at varying levels of attentiveness. Then, using a Support-Vector Machine (SVM) we created several prediction models for user attention and identified the Histogram of …

Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li

Dissertations

Many application areas employ various risk measures, such as a quantile, to assess risks. For example, in finance, risk managers employ a quantile to help determine appropriate levels of capital needed to be able to absorb (with high probability) large unexpected losses in credit portfolios comprising loans, bonds, and other financial instruments subject to default. This dissertation discusses the computation of risk measures in finance and parallel real-time scheduling.

Firstly, two estimation approaches are compared for one risk measure, a quantile, via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large, but …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Towards Ensuring Integrity And Authenticity Of Software Repositories, Sangat Vaidya

Dissertations

The software development process comprises a series of steps known as a software supply chain. These steps include managing the source code, testing, building and packaging it into a final product, and distributing the product to end users. Along this chain, software repositories are used for different purposes such as source code management (Git, SVN, mercurial), software distribution (PyPI, RubyGems, NPM) or for deploying software based on container images (Harbor, DockerHub, Artifact Hub). In the recent past, different types of repositories have increasingly been the target of attacks. As such, there is a need for mechanisms to ensure integrity and …

Parameter Selection In Fully Homomorphic Encryption Schemes And Fhe Applications, Cavidan Yakupoglu

Dissertations

Quantum computing has been gaining momentum as a result of recent technological advances. Existing cryptographic systems rely on the difficult problems that can be solved by sufficiently powerful quantum computers. As the quantum age approaches, the desire to discover new difficult problems that cannot be solved by quantum systems has increased. Lattice-based cryptography is a prominent tool for the post-quantum era that facilitates the implementation of encryption systems for practical applications.

The Learning with Error (LWE) and Ring-LWE problems introduce new lattice hardness assumptions that have been incorporated into public-key cryptosystems to facilitate the implementation of numerous privacy-enhancing applications. Fully …

Truncated Matrix Power Iteration For Differentiable Dag Learning, Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan M. Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi

Machine Learning Faculty Publications

Recovering underlying Directed Acyclic Graph structures (DAG) from observational data is highly challenging due to the combinatorial nature of the DAG-constrained optimization problem. Recently, DAG learning has been cast as a continuous optimization problem by characterizing the DAG constraint as a smooth equality one, generally based on polynomials over adjacency matrices. Existing methods place very small coefficients on high-order polynomial terms for stabilization, since they argue that large coefficients on the higher-order terms are harmful due to numeric exploding. On the contrary, we discover that large coefficients on higher-order terms are beneficial for DAG learning, when the spectral radiuses of …

Efficient And Scalable Triangle Centrality Algorithms In The Arkouda Framework, Joseph Thomas Patchett

Theses

Graph data structures provide a unique challenge for both analysis and algorithm development. These data structures are irregular in that memory accesses are not known a priori and accesses to these structures tend to lack locality.

Despite these challenges, graph data structures are a natural way to represent relationships between entities and to exhibit unique features about these relationships. The network created from these relationships can create unique local structures that can describe the behavior between members of these structures. Graphs can be analyzed in a number of different ways including at a high level in community detection and at …

Edge Assignment And Data Valuation In Federated Learning, Thuy T. Do

Graduate Doctoral Dissertations

Federated Learning (FL) is a recent Machine Learning method for training with private data separately stored in local machines without gathering them into one place for central learning. It was born to address the following challenges when applying Machine Learning in practice: (1) Communication cost: Most real-world data that can be useful for training are locally collected; to bring them all to one place for central learning can be expensive, especially in real-time learning applications when time is of the essence, for example, predicting the next word when texting on a smartphone; and (2) Privacy protection: Many applications must protect …

From The Editors, Ahmad Gamal

Smart City

No abstract provided.

Stochastic Models Of Jaya And Semi-Steady-State Jaya Algorithms, Uday K. Chakraborty

Educator Preparation & Leadership Faculty Works

The Jaya algorithm and its variants have enjoyed great success in diverse application areas, but no theoretical analysis of the algorithm, to our knowledge, is available in the literature. In this paper we build stochastic models for analyzing Jaya and semi-steady-state Jaya algorithms. For these algorithms, the computational cost depends on how, at each iteration, the new individual fares against the existing individual. Costs must be incurred for any replacement of individuals and the subsequent update of the population-worst individual’s (and/or the population-best individual’s) index. We use the following two quantities as the main metrics for analysis: the expected number …

Research On Uncertainties And Challenges Of Cyber Security In Maritime Industry, Qianrong Chen

World Maritime University Dissertations

No abstract provided.

Exploiting Higher-Order Derivatives In Convex Optimization Methods, Dmitry Kamzolov, Alexander Gasnikov, Pavel Dvurechensky, Artem Agafonov, Martin Takac

Machine Learning Faculty Publications

Exploiting higher-order derivatives in convex optimization is known at least since 1970’s. In each iteration higher-order (also called tensor) methods minimize a regularized Taylor expansion of the objective function, which leads to faster convergence rates if the corresponding higher-order derivative is Lipschitz-continuous. Recently a series of lower iteration complexity bounds for such methods were proved, and a gap between upper an lower complexity bounds was revealed. Moreover, it was shown that such methods can be implementable since the appropriately regularized Taylor expansion of a convex function is also convex and, thus, can be minimized in polynomial time. Only very recently …

Sr-Dcsk Cooperative Communication System With Code Index Modulation: A New Design For 6g New Radios, Yi Fang, Wang Chen, Pingping Chen, Yiwei Tao, Mohsen Guizani

Machine Learning Faculty Publications

This paper proposes a high-throughput short reference differential chaos shift keying cooperative communication system with the aid of code index modulation, referred to as CIM-SR-DCSK-CC system. In the proposed CIM-SR-DCSK-CC system, the source transmits information bits to both the relay and destination in the first time slot, while the relay not only forwards the source information bits but also sends new information bits to the destination in the second time slot. To be specific, the relay employs an N-order Walsh code to carry additional log2N information bits, which are superimposed onto the SR-DCSK signal carrying the decoded source information bits. …

Augmented Reality-Based English Language Learning: Importance And State Of The Art, Mohammad Wedyan, Jannat Falah, Omar Elshaweesh, Salsabeel F. M. Alfalah, Moutaz Alazab

All Works

Augmented reality is increasingly used in the educational domain. However, little is known concerning the actual importance of AR for learning English skills. The weakness of the English language among English as a foreign Language (EFL) students is widespread in different educational institutions. Accordingly, this paper aims at exploring the importance of AR for learning English skills from the perspectives of English language teachers and educators. Mixed qualitative methods were used. To achieve the objective of this study, 12 interviews were conducted with English teachers concerning the topic under investigation. Second, a systematic literature review (SLR) that demonstrates the advantages, …

Towards A Model On Digital Transformation Within The Higher Education Sector – A South African Perspective, Olusegun A. Ajigini

African Conference on Information Systems and Technology

Digital transformation is the application of technology to build new business models, processes, software and systems that result in more profitable revenue, greater competitive advantage and higher efficiency. The factors influencing digital transformation in the higher educational sector were examined in this study. Specifically, data was drawn from 400 respondents and the following variables: organizational IT application portfolio, organizational culture, organizational structure, leadership and ethics predict digital transformation in higher educational sector by using regression analysis. The researcher found that the organizational culture contribution was the highest by predicting 78.9% of digital transformation in the higher education sector.

Adapting An Online Learning Quality Assurance Framework In A Developing Country Setting: The Case Of A Hei In Malawi, Bennett Kankuzi, Menard Phiri, Robert Chanunkha, Jonathan Makuwira, Paul Makocho

African Conference on Information Systems and Technology

Covid-19 prompted many higher education institutions (HEIs), even in developing countries like Malawi, to abruptly shift from their traditional face-to-face mode of delivery to online learning. However, quality issues with online learning remain one of the greatest challenges to acceptance of online learning by many students and stakeholders. This paper presents an action research based study at the Malawi University of Science and Technology, in which an online learning quality assurance framework is adapted to a developed country setting. The adapted framework builds on the Online Learning Consortium (OLC) Quality Scorecard for the Administration of Online Programs. The contextualization and …

Towards A Conceptual Model For Developing A Career Prediction System For Students’ Subject Selection At Secondary School Level, Moses Kamondo Tuhame, Gilbert Maiga, Annabella Habinka, Barbara Kayondo

African Conference on Information Systems and Technology

Career choice prediction has been a complex phenomenon both in developed and developing countries. Though various theories that describe career prediction have emerged, their practical implementation in the form of a system has been hampered by the shortfalls that come along with each of them. However, there is no existing theoretically based holistic model that merges various theories that can inform the development of such a system in the developing world context. This paper, therefore, aims at proposing a holistic conceptual model that integrates a number of variables to inform the development of a career prediction system in the developing …

Factors That Influence The Implementation Of Information And Communication Technology Inclusive Design Practices In Organisations, Faizel Ebrahim, Salah Kabanda, Guidance Mthwazi

African Conference on Information Systems and Technology

Inclusive design in information and communication technology (ICT) is the development of information and communication technology artifacts that are accessible and easy to use for as many people as possible. Human diversities must be considered when producing these inclusive design artifacts. It is not only important for abled people but also extends to people with disabilities, the elderly and anybody challenged with using these artifacts. Yet, few designers and developers adopt inclusive design methodologies in their practice. This study seeks to identify and understand the factors that influence the implementation of inclusive design practices in organisations. The methodology was based …