Computer Engineering Commons^™

Treated Hfo2 Based Rram Devices With Ru, Tan, Tin As Top Electrode For In-Memory Computing Hardware, Yuvraj Dineshkumar Patel

Theses

The scalability and power efficiency of the conventional CMOS technology is steadily coming to a halt due to increasing problems and challenges in fabrication technology. Many non-volatile memory devices have emerged recently to meet the scaling challenges. Memory devices such as RRAMs or ReRAM (Resistive Random-Access Memory) have proved to be a promising candidate for analog in memory computing applications related to inference and learning in artificial intelligence. A RRAM cell has a MIM (Metal insulator metal) structure that exhibits reversible resistive switching on application of positive or negative voltage. But detailed studies on the power consumption, repeatability and retention …

The Assessments Of Internet-Based Technology Use By University Academic Members, Mohammed Alghamdi

BAU Journal - Science and Technology

Social networking applications (SNAs), as technologies that rely on internet infrastructure, are widely used as platforms for user interaction, content creation and social communication. However, in recent years, SNAs have been used in the context of teaching and learning, and this aspect, as well as others, has attracted research attention. Limited research has investigated the motivations and barriers to teaching with SNAs in higher education, and so this study sought to examine the purposes, motivations and barriers associated with SNA use in education among academic members at Albaha University, Saudi Arabia. A quantitative research design involving a sample of academic …

Recent Advances And Machine Learning Techniques On Sickle Cell Disease, Noorh H. Alharbi, Rana O. Bameer, Shahad S. Geddan, Hajar M. Alharbi

Future Computing and Informatics Journal

Sickle cell disease is a severe hereditary disease caused by an abnormality of the red blood cells. The current therapeutic decision-making process applied to sickle cell disease includes monitoring a patient’s symptoms and complications and then adjusting the treatment accordingly. This process is time-consuming, which might result in serious consequences for patients’ lives and could lead to irreversible disease complications. Artificial intelligence, specifically machine learning, is a powerful technique that has been used to support medical decisions. This paper aims to review the recently developed machine learning models designed to interpret medical data regarding sickle cell disease. To propose an …

Twitter Analysis Based On Damage Detection And Geoparsing For Event Mapping Management, Yasmeen Ali, Khaled Bahnasy, Adel El-Mahdy

Future Computing and Informatics Journal

Background: Early event detection, monitor, and response can significantly decrease the impact of disasters. Lately, the usage of social media for detecting events has displayed hopeful results. Objectives: for event detection and mapping; the tweets will locate and monitor them on a map. This new approach uses grouped geoparsing then scoring for each tweet based on three spatial indicators. Method/Approach: Our approach uses a geoparsing technique to match a location in tweets to geographic locations of multiple-events tweets in Egypt country, administrative subdivision. Thus, additional geographic information acquired from the tweet itself to detect the actual locations that …

Metric Learning Via Linear Embeddings For Human Motion Recognition, Byoungdoo Kong

Masters Theses

We consider the application of Few-Shot Learning (FSL) and dimensionality reduction to the problem of human motion recognition (HMR). The structure of human motion has unique characteristics such as its dynamic and high-dimensional nature. Recent research on human motion recognition uses deep neural networks with multiple layers. Most importantly, large datasets will need to be collected to use such networks to analyze human motion. This process is both time-consuming and expensive since a large motion capture database must be collected and labeled. Despite significant progress having been made in human motion recognition, state-of-the-art algorithms still misclassify actions because of characteristics …

Mechanical Alloying-Assisted Coating Of Fe–Al Powders On Steel Substrate, Alfian Noviyanto, Sri Harjanto, Wahyu Bambang Widayatno, Agus Sukarto Wismogroho, Muhamad Ikhlasul Amal, Nurul Taufiqu Rochman

Makara Journal of Technology

The coating layer of Fe–Al powders on the steel substrate was prepared by mechanical alloying at room temperature. Fe, Al, and the steel substrates were milled with high-energy ball milling for 32 h with a ball-to-powder ratio of 8 in an argon atmosphere to prevent oxidation during milling. Although mechanical alloying was performed for 32 h, no new phases were observed after mechanical alloying, as analyzed by X-ray diffraction. However, the crystallite size of the milled powders for 32 h decreased by factor two compared with the initial powders. Scanning electron micrographs showed that the coating layers formed >8 h …

Performance Of Free-Space Optical Communication Systems Using Optical Amplifiers Under Amplify-Forward And Amplify-Received Configurations, Ucuk Darusalam, Arockia Bazil Raj, Fitri Yuli Zulkifli, Purnomo Sidi Priambodo, Eko Tjipto Rahardjo

Makara Journal of Technology

With the growth of digital technology in the stage of industrial revolution 4.0, the demand for broadcasting large amounts of information to last mile users has increased. Free-space optical (FSO) communication is one of the telecommunication platforms that has shown immense potential in meeting the demand for information broadcasting. In this work, the performance of FSO communication based on wavelength division multiplexing with a data rate of 80 Gbps is investigated through simulations. The configuration of optical amplifiers in the FSO system is set up on the basis of the amplify-forward and amplify-received configurations to expand the network. The investigation …

Use Of Viscoplastic Damper For Improving The Resistance Of Steel Frames To Blast Loading, Gholamreza Abdollahzadeh, Hadi Faghihmaleki, Hamed Hamidi Jamnani, Atefeh Ebrahimi Bardar

Makara Journal of Technology

In this paper, we evaluated the effect of viscoplastic dampers on the response of steel frames under blast loading. We used SAP2000 software and link elements to investigate the responses of nine-story steel frames with and without dampers. The proposed viscoplastic damper is a new type of viscous damper. The application of this damper is based on the availability of its constituent materials. The damper acts as a viscoelastic damper at low levels of vibration, but it acts as a combination of viscoelastic operator and metal-yielding device at extreme levels of vibration. With respect to the height of the structure, …

A Density Functional Theory Study On Using Montmorillonite To Reduce Air Pollution, Triati Dewi Kencana Wungu, Meqorry Yusfi, Suprijadi Suprijadi

Makara Journal of Technology

In this study, density functional theory (DFT) method is used to investigate the possibility of using a smectite clay mineral called montmorillonite (MMT) in reducing heavy metals, such as Cd, through Cd adsorption. The mechanism of Cd adsorption in MMT is observed theoretically, and the tetrahedrally isomorphic substitution on the upper layer of MMT is considered to observe the role of Al and Fe in strengthening Cd adsorption. Two types of MMT are modeled in this study: Al-MMT and Fe-MMT. The Al-MMT means that Al substitutes one atom in the upper tetrahedral layer of MMT, while Fe-MMT means that Fe …

Influence Of The Shaping Process On The Tensile Properties Of Steel Reinforcement Bars Carbon Steel Grades Bjtp24 And Bjts40, Nuraziz Handika, Ridha Amalia Idhar, Jessica Sjah, Essy Arijoeni, Elly Tjahjono

Makara Journal of Technology

According to the current applicable national standard in Indonesia, i.e. SNI 07 2529 1991, in addition to the limitation on the loading rate, the steel bar must be reduced, formed, or lathed, as part of the shaping process of samples. This study determined and compared the effect of the shaping process on the yield strength, ultimate strength, and percent elongation by conducting tensile tests of steel bar grade BJTS40, i.e. deformed bar type of steel, and grade BJTP24, i.e., plain bar type of steel. Three diameters of the deformed bar (BJTS40) and one diameter of the plain bar (BJTP24) were …

Iso 9001:2015 Risk-Based Thinking: A Framework Using Fuzzy-Support Vector Machine, Ralph Sherwin A. Corpuz

Makara Journal of Technology

Risk-based thinking (RBT) is one of the distinct new features of the International Organization for Standardization 9001:2015. Interestingly, the standard does not prescribe any tools. Hence, organizations are puzzled as to the extent of conformance. Some organizations have adopted formal tools. However, these tools seem insufficient in linking the standard into an evidence-based decision support system. To resolve gaps in RBT implementation, this paper proposes a framework based on fuzzy inference system (FIS) and support vector machine (SVM) to automate risk analysis and evaluation, proposal and verification of action plans, and prediction of the feasibility of risks and opportunities according …

Ionic Conductiviy Of Alginate-Nh4cl Polymer Electrolyte, Nurhasniza Mamajan Khan, Noor Saadiah Mohd Ali, Ahmad Faizrin Ahmad Fuzlin, Ahmad Salihin Samsudin

Makara Journal of Technology

This study aims to produce a solid biopolymer electrolyte (SBE) by doping ammonium chloride (NH4Cl) into alginate. Solution casting was used to prepare the alginate–NH4Cl SBE system. Electrical impedance spectroscopy was performed to analyze the electrical properties of the SBE under the applied frequency range of 50 Hz–1 MHz. The incorporation of 8 wt.% NH4Cl enhances the ionic conductivity of the SBE up to 3.18 × 10-7 S/cm at ambient room temperature. Fourier transform infrared spectroscopy shows that complexation occurs between the hydroxyl (-OH), carboxylate (COO-) and ether linkage (C-O-C) functional groups due to the formation of inter- and intra-molecular …

Influence Of Lithium Bromide On Electrical Properties In Bio-Based Polymer Electrolytes, Ahmad Faizrin Fuzlin, Bouchta Sahraoui, Ahmad Salihin Samsudin

Makara Journal of Technology

This research presents the influence of lithium bromide (LiBr) on the electrical properties of alginate in bio-based polymer electrolytes (BBPEs) system. Bio-based alginate was prepared using the solution casting technique with various LiBr compositions. The ionic conductivity and electrical properties of the prepared BBPEs samples were studied using electrical impedance spectroscopy over a frequency range of 50 Hz–1 MHz. A maximum ionic conductivity of 7.46 × 10−5 S cm-1 was obtained for a sample containing 15 wt. % lithium bromide-doped alginate BBPEs at ambient temperature (303 K). The electrical analysis revealed that the most conductive sample based on alginate-LiBr BBPEs …

Deep Reinforcement Learning For Collaborative Edge Computing In Vehicular Networks, Mushu Li, Jie Gao, Lian Zhao, Xuemin Shen

Electrical and Computer Engineering Faculty Research and Publications

Mobile edge computing (MEC) is a promising technology to support mission-critical vehicular applications, such as intelligent path planning and safety applications. In this paper, a collaborative edge computing framework is developed to reduce the computing service latency and improve service reliability for vehicular networks. First, a task partition and scheduling algorithm (TPSA) is proposed to decide the workload allocation and schedule the execution order of the tasks offloaded to the edge servers given a computation offloading strategy. Second, an artificial intelligence (AI) based collaborative computing approach is developed to determine the task offloading, computing, and result delivery policy for vehicles. …

Deep Neural Network For Load Forecasting Centred On Architecture Evolution, Santiago Gomez-Rosero, Miriam A M Capretz, London Hydro

Electrical and Computer Engineering Publications

Nowadays, electricity demand forecasting is critical for electric utility companies. Accurate residential load forecasting plays an essential role as an individual component for integrated areas such as neighborhood load consumption. Short-term load forecasting can help electric utility companies reduce waste because electric power is expensive to store. This paper proposes a novel method to evolve deep neural networks for time series forecasting applied to residential load forecasting. The approach centres its efforts on the neural network architecture during the evolution. Then, the model weights are adjusted using an evolutionary optimization technique to tune the model performance automatically. Experimental results on …

A Circle Hough Transform Implementation Using High-Level Synthesis, Carlos Lemus

UNLV Theses, Dissertations, Professional Papers, and Capstones

Circle Hough Transform (CHT) has found applications in biometrics, robotics, and imageanalysis. In this work, the focus is the development of a Field Programmable Gate Array (FPGA) based accelerator that performs a series of procedures and results in circle detection. The design is performed using Vivado High-Level Synthesis (HLS) tools and targeted for a Zynq UltraScale+ ZCU106. The implementation includes the following procedures: Gaussian filter, Sobel edge operator, thresholding, and finally the CHT algorithm. The performance is evaluated based on the execution time as compared to the software (Python code) execution and the analysis tools provided by Vivado HLS tool. …

Predicting Residential Energy Consumption Using Wavelet Decomposition With Deep Neural Network, Dagimawi Eneyew, Miriam A M Capretz, Girma Bitsuamlak, London Hydro

Electrical and Computer Engineering Publications

Electricity consumption is accelerating due to economic and population growth. Hence, energy consumption prediction is becoming vital for overall consumption management and infrastructure planning. Recent advances in smart electric meter technology are making high-resolution energy consumption data available. However, many parameters influencing energy consumption are not typically monitored for residential buildings. Therefore, this study’s main objective is to develop a data-driven energy consumption forecasting model (next-hour consumption) for residential houses solely based on analyzing electricity consumption data. This research proposes a deep neural network architecture that combines stationary wavelet transform features and convolutional neural networks. The proposed approach utilizes automatically …

Identifying Depressive Symptoms From Tweets: Figurative Language Enabled Multitask Learning Framework, Shweta Yadav, Jainish Chauhan, Joy Prakash Sain, Krishnaprasad Thirunarayan, Amit P. Sheth, Jeremiah Schumm

Publications

Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and scalable depressive disorder screening and triage system. This study aims to design and evaluate a decision support system (DSS) to reliably determine the depressive triage level by capturing fine-grained depressive symptoms expressed in user tweets through the emulation of Patient Health Questionnaire-9 (PHQ-9) that is routinely used in clinical practice. The reliable detection of depressive symptoms from tweets is challenging because the 280-character limit on tweets incentivizes the …

Medical Knowledge-Enriched Textual Entailment Framework, Shweta Yadav, Vishal Pallagani, Amit P. Sheth

Publications

One of the cardinal tasks in achieving robust medical question answering systems is textual entailment. The existing approaches make use of an ensemble of pre-trained language models or data augmentation, often to clock higher numbers on the validation metrics. However, two major shortcomings impede higher success in identifying entailment: (1) understanding the focus/intent of the question and (2) ability to utilize the real-world background knowledge to capture the context beyond the sentence. In this paper, we present a novel Medical Knowledge-Enriched Textual Entailment framework that allows the model to acquire a semantic and global representation of the input medical text …

A Multi-Channel Mcp-Pmt Based Readout Integrated Circuit For Lidar Applications, Sachin Purushothaman Namboodiri

UNLV Theses, Dissertations, Professional Papers, and Capstones

Photon counting techniques are becoming more critical in fields such as LiDAR, high energy physics (HEP), and positron emission tomography (PET). For space-based aerosol-cloud-ocean (ACO) LiDAR, the total aggregate photon flux signal has a very high dynamic range, from a single-photon up to giga-photons per second for a single channel. This dissertation focuses on the design of a multichannel, photon counting readout circuit that can interface with MCP-PMTs for high dynamic range, space-based LiDAR applications. Chapter 2 presents the conventional current mode approach that has been employed to realize a photon counting circuit. A transimpedance amplifier, a 6-bit delay line …

Cyber Defense Remediation In Energy Delivery Systems, Kamrul Hasan

Computational Modeling & Simulation Engineering Theses & Dissertations

The integration of Information Technology (IT) and Operational Technology (OT) in Cyber-Physical Systems (CPS) has resulted in increased efficiency and facilitated real-time information acquisition, processing, and decision making. However, the increase in automation technology and the use of the internet for connecting, remote controlling, and supervising systems and facilities has also increased the likelihood of cybersecurity threats that can impact safety of humans and property. There is a need to assess cybersecurity risks in the power grid, nuclear plants, chemical factories, etc. to gain insight into the likelihood of safety hazards. Quantitative cybersecurity risk assessment will lead to informed cyber …

Digital And Mixed Domain Hardware Reduction Algorithms And Implementations For Massive Mimo, Najath A. Mohomed

FIU Electronic Theses and Dissertations

Emerging 5G and 6G based wireless communications systems largely rely on multiple-input-multiple-output (MIMO) systems to reduce inherently extensive path losses, facilitate high data rates, and high spatial diversity. Massive MIMO systems used in mmWave and sub-THz applications consists of hundreds perhaps thousands of antenna elements at base stations. Digital beamforming techniques provide the highest flexibility and better degrees of freedom for phased antenna arrays as compared to its analog and hybrid alternatives but has the highest hardware complexity.

Conventional digital beamformers at the receiver require a dedicated analog to digital converter (ADC) for every antenna element, leading to ADCs for …

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, Alexis Papamichail, Vanya Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga₂O₃, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, A. Papamichail, V. Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga₂O₃, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …

Incentivization In Mobile Edge Computing Using A Full Bayesian Approach, Sean Lebien

Electrical and Computer Engineering ETDs

The advances of multi-access edge computing (MEC) have paved the way for the integration of the MEC servers, as intelligent entities into the Internet of Things (IoT) environment as well as into the 5G radio access networks. In this thesis, a novel artificial intelligence-based MEC servers’ activation mechanism is proposed, by adopting the principles of Reinforcement Learning (RL) and Bayesian Reasoning. The considered problem enables the MEC servers’ activation decision-making, aiming at enhancing the reputation of the overall MEC system, as well as considering the total computing costs to serve efficiently the users’ computing demands, guaranteeing at the same time …

Effect Of Landfill Leachates On Some Water Quality Indicators Of Selected Surface Water And Groundwater At Ilokun, Ado-Ekiti, Nigeria, Olorunwa Omofunmi, Adesola Satimehin, Abraham Oloye, Okwunna Umego

Makara Journal of Technology

This study was conducted to examine the impact of dumpsites on the quality of groundwater and surface water. The water samples and leachates were collected from dumpsites in respective zones. The physicochemical properties of the samples were examined and determined in accordance with the standards of the American Public Health Association. Results indicated that the groundwater and surface water that are close to the dumpsites have an electrical conductivity of 385 and 245 Sd/cm, total dissolved solids of 168 and 128 mg/L, a turbidity of 4.6 and 22 NTU, a total alkalinity of 103 and 50 mg/L, a total hardness …

Effect Of Catholyte Concentration On Current Production During Chocolate Industry Wastewater Treatment By A Microbial Fuel Cell, Diana Rahayuning Wulan, Suprihanto Notodarmojo

Makara Journal of Technology

Microbial fuel cells (MFCs) use bacteria as a catalyst to oxidize organic and/or inorganic substrates and produce electric currents. Wastewater could function as an electron donor in the anode chamber and, thus, represents a very promising energy source. Catholytes, as electron acceptors, influence power production in MFCs by increasing the availability of electrons. The present research aims to determine the influence of catholyte concentration on current production in an aerobic two-chamber MFC. Aerobic treatment was carried out in the two-chamber MFC operated in an incubator at 37  1 °C with and without aeration in the cathode chamber. Wastewater from …

Evaluation Of Il-17a And Il-17f Gene Expression In Peripheral Blood Mononuclear Cells In Different Clinical Stages Of Chronic Hepatitis B Infection In An Iranian Population, Tannaz Akbari Kolagar, Seyed Reza Mohebbi, Fatemeh Ashrafi, Shahrzad Shoraka, Hamid Asadzadeh Aghdaei, Mohammad Reza Zali

Makara Journal of Technology

Hepatitis B virus (HBV) infection is one of the main causes of liver damage, which can also lead to chronic hepatitis B (CHB) infection. More than 240 million individuals worldwide are chronic carriers of HBV. Among individuals with CHB who are untreated, approximately 15% – 40% will progress to liver cirrhosis or cancer. The interactions between HBV and host immune response play significant roles in the progression of CHB. CHB can be generally divided into four different clinical phases: immune tolerance (IT), immune clearance, inactive carrier, and Hepatitis B surface antigen (HBsAg)-negative reactivation phase (ENEG). Many studies showed that interleukins …

Effect Of Pvdf-Ca Ratio On Electrospun Membrane For Water–Oil Filtration Application, Mohamad Haziq Alias, Izan Izwan Misnon, Rajan Jose

Makara Journal of Technology

Oil spillage and generation of industrial water–oil wastewater mixture ignite a focus on filtration technology. Electrospinning technique provides a versatile route in producing tunable diameter and pores in nanofiber filtration membrane development. In this work, polyvinylidene difluoride (PVDF) and cellulose acetate (CA) electrospun membrane at different concentration ratios were synthesized for water–oil filtration application. The polymeric solutions were characterized using viscometer and conductivity testing, whereas the membranes were analyzed using contact angle, tensile test, scanning electron microscopy (SEM), and filtration testing of oil (dichloromethane). Conductivity test showed a decreased conductivity along with decrement of CA ratio in the polymeric solution. …

Redesign Of Product Packaging With Kansei Engineering: Empirical Study On Small-Medium Enterprises In Indonesia, Amalia Suzianti, A. Aldianto

Makara Journal of Technology

Small-medium enterprises (SMEs) in Indonesia have been proven to be one of the important pillars of the national economy. Unfortunately, some problems hinder their development, and one of the critical problems is the quality of product packaging. The packages of SME products are considered poor, dirty, and unattractive. Packaging problem is one of the factors why consumers are less interested in buying and why SME products always lose in the competition with other products. This study discusses how to employ Kansei engineering to design better SME product packaging with a focus on psychological (affective) aspects. This research concludes that there …