Digital Commons Network^™

A Survey On Energy Efficient Medium Access Control For Acoustic Wireless Communication Networks In Underwater Environments, Walid K. Hasan, Iftekhar Ahmad, Daryoush Habibi, Quoc Viet Phung, Mohammad Al-Fawa'reh, Kazi Yasin Islam, Ruba Zaheer, Haitham Khaled

Research outputs 2022 to 2026

Underwater communication plays a crucial role in monitoring the aquatic environment on Earth. Due to their unique characteristics, underwater acoustic channels present unique challenges including lengthy signal transmission delays, limited data transfer bandwidth, variable signal quality, and fluctuating channel conditions. Furthermore, the reliance on battery power for most Underwater Wireless Acoustic Networks (UWAN) devices, coupled with the challenges associated with battery replacement or recharging, intensifies the challenges. Underwater acoustic communications are heavily constrained by available resources (e.g., very limited bandwidth, and limited energy storage). Consequently, the role of medium access control (MAC) protocol which distributes available resources among nodes is …

Joint Estimation Of The State And Parameters Of Dynamic Control Objects Based On The Maine Estimator, Yulduz Abdurakhmanova

Chemical Technology, Control and Management

The issues of constructing an adaptive joint estimation of the state and parameters of dynamic control objects using the Maine estimator are considered. There are various variants of the extended filter, and a variant based on iterations between parameter and state estimates was used in the work. In this version of the extended Kalman filter, the problem of joint parameter and state estimation is solved in such a way that parameter estimation is performed before state estimation. Then, the parameter values are used to assess the state. In this case, further iterations between the state vector estimation and the parameter …

Modeling Of Analog-To-Digital Converter In Signal Processing, Ravshan Aliev, A.U. Djalilov

Chemical Technology, Control and Management

This article is devoted to the study of the modeling process of analog-to-digital converters (ADCs) that process signals, one of the main parts of control system elements and devices. As we know, ADCs are an important part of modern control systems. During the research, the main stages of analog signal conversion were analyzed, i.e. discretization, quantization, coding. A classification of analog-to-digital conversion methods was made and the advantages and disadvantages of each were identified. Also, the characteristics and parameters of ADC were studied, their impact on ADCs performance was evaluated, and it was determined that certain characteristics should be taken …

Prototyping Various Mppt Techniques Used In Wind Energy Conversion Systems For Response Time Monitoring, Amro Kawashty, Sameh O. Abdellatif, Gamal Ebrahim, Hani Ghali

Electrical Engineering

This paper focuses on prototyping various maximum power point tracking (MPPT) techniques used in wind energy conversion systems (WECS) for response time monitoring. MPPT plays a crucial role in optimizing the power extraction from wind turbines by dynamically adjusting their operating conditions to track the maximum power point. The response time of an MPPT algorithm determines how quickly it can adapt to changes in wind conditions and maximize power output. In this study, we implement and compare multiple MPPT techniques on an emulated WECS. Several commonly used MPPT techniques, such as perturb and observe (P&O), incremental conductance (IncCond), and tip …

Greening The Workplace: Can Sustainable Practices Reduce Anxiety And Enhance Meaningful Work Engagement?, Cyril Tom T. Sunny, Peter Muttungal, Benny G. Davidson

Northeast Journal of Complex Systems (NEJCS)

This academic research examines the relationship between job engagement, green work climate, job-related anxiety, meaningfulness at work within the organization. It draws attention to identify the significant relations among all these factors and highlights the role of a green work climate in promoting meaningful work and alleviating job-related anxiety. The research emphasizes a diverse sample of employees from various organisations using structural modelling to find the mediating roles of job engagement and work meaningfulness in the correlation between organizational practices, environmental sustainability, and employee satisfaction. The study finds that a green work climate significantly enhances meaningful work experiences and reduces …

Increasing Guard Band Size To Decrease Interference In V2x Communication, Nakira Oglesby, Mackenzie Prescott, Billy Kihei, Ph.D.

Symposium of Student Scholars

As technologies evolve and new devices are introduced, the demand for fast and reliable vehicle-to-everything (V2X) communication increases. As this demand increases, the interference level in the 5.9GHz Dedicated Short Range Communications (DSRC) band will inevitably increase. And thus, the task of somehow minimizing this interference becomes increasingly important as time passes. This report investigates the effects of increasing the guard band size of the lower 5.9 GHz DSRC band on the adjacent channel interference from Unlicensed National Information Infrastructure 4 band (U-NII-4) devices and to try and see if there is a significant decrease in the interference level. The …

Impact Of Node Failures On Productivity In Multilayer Supply Chain Networks: An Influence Network Analysis In The Indian Electronics Sector, Surendra Orupalli, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Supply chain networks are essential for the delivery of goods and information, but disruptions such as natural disasters or trade embargoes can severely impact them. Resilience of entire networks under different types of disruptions when nodes or edges fail has been extensively studied. However, the extent to which the failure of a particular company affects another company of interest within a network has not been widely explored. To address this, we created a multilayer physical supply chain network of companies in an electronics supply chain concentrated in India. Through systematic node removal simulations, we examined how the productivity of one …

A Novel Preprocessing Model For Multi Modal Brain Mri Image Classification For Stroke Prognosis, Alwin Joseph, Chandra J

Northeast Journal of Complex Systems (NEJCS)

Magnetic Resonance Imaging (MRI) is an imaging technique used for the diagnosis and observing the progression in various neurological disorders. Stroke is one of the prominent neurological disorders that creates significant impacts in the patients. It occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissues from getting oxygen and nutrients. Multimodal data from various modalities help clinicians in proper prognosis of stroke. Ischemic Stroke Lesion Segmentation Challenge (ISLES22) provides data of stroke data for various stroke patients, the dataset consists of three modalities of data – Fluid Attenuated Inversion Recovery (FLAIR), Apparent …

Classification Of Microcontroller Integrated Circuit On The Pocket Of Jedec Tray Using Convolutional Neural Network In Embedded Machine Learning System, Mark Pallones, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

One serious issue in the microcontroller manufacturing environment is the mixing of microcontroller unit (MCU) parts, leading to the wastage of materials, dissatisfied customers, and the implementation of non-value-adding activities to address it. More adverse effects include negative feedback from customers, loss of confidence, and impact on business growth. One root cause traces back to the final testing of the manufacturing back-end process when reusing unemptied standard JEDEC matrix trays for good and bad units in the test handler. Currently, emptying the JEDEC matrix tray and inspecting it is a manual process prone to human error due to high-volume test …

Zno Nanowires For Biosensing Applications, G.M. Mehedi Hossain, Daniel Garza, Emilio Chavez, Ahmed Hasnain Jalal, Fahmida Alam

Electrical and Computer Engineering Faculty Publications

Zinc oxide Nanowires (ZnO-NWs) are promising biosensor materials and hold the key to overcoming challenges in the field. This chapter provides an introductory overview of biosensing technology, focusing on the fundamental principles and comparing ZnO-NWs with other nanostructures regarding the surface area, reactivity, electrical properties, charge transport behavior, optical, magnetic, and piezoelectric properties, and mechanical flexibility. Providing the synthesis and characterization methods, ZnO-NWs’ biosensing processes are also elaborated on surface modification for selectivity, integration with microfluidic systems, enhancing signal transduction, and connecting with biological elements like enzymes, antibodies, and DNA. The chapter also discusses the applications of ZnO-NWs-based biosensors in …

Leveraging Network Science For Customer Segmentation And Product Recommendation, Ali Nasirzonouzi

Northeast Journal of Complex Systems (NEJCS)

The rapid growth in e-commerce has forced the development and implementation of enhanced customer segmentation and recommendation systems, improving business results and improving customer experience. Traditional approaches, such as RFM analysis and clustering algorithms like K-means, are very helpful in many situations but usually fail to catch complex interdependencies among customers and products. This paper proposes a new approach using network science methodologies, a bipartite graph model, toward the advancement of customer segmentation and product recommendation. It implements a bipartite graph of customers and products using the "Online Retail II" dataset and proceeds with community detection, segmenting customers into unique …

Integrating Neural Networks For Predictive Torque Control And Obstacle Avoidance In Autonomous Robot, Viswanath Kodali, Harsha Vardhan Borra, Kiran P

Northeast Journal of Complex Systems (NEJCS)

In the field of robotics, precise motion control and accurate computation of joint forces are critical for ensuring optimal performance. Traditional methods, such as using the Jacobian matrix for joint angle determination and Euler-Lagrange equations for torque computation, are reliable but computationally intensive, making them less suitable for real-time applications. This paper presents an advanced approach to improving the productivity and efficiency of a 3-Degree of Freedom (DOF) robotic arm by utilizing Artificial Neural Network (ANN). The proposed system dynamically predicts joint angles and torque, enabling faster and more efficient motion control.

To address the challenge of obstacle avoidance in …

Multimodal Search On A Line, Jared Coleman, Dmitry Ivanov, Evangelos Kranakis, Danny Krizanc, Oscar Morales Ponce

Computer Science Faculty Works

Inspired by the diverse set of technologies used in underground object detection and imaging, we introduce a novel multimodal linear search problem whereby a single searcher starts at the origin and must find a target that can only be detected when the searcher moves through its location using the correct of p possible search modes. The target’s location, its distance d from the origin, and the correct search mode are all initially unknown to the searcher. We prove tight upper and lower bounds on the competitive ratio for this problem. Specifically, we show that when p is odd, the optimal …

Nonlinear Self-Synchronizing Current Control For Single-Phase Ac Inverters, Shruti Pandey, Michael Mclntyre

Electrical and Computer Engineering Faculty Research & Creative Works

Grid-connected single-phase inverters require accurate phase detection for synchronization and power control. Traditionally, phase-locked loops (PLLs) are used to estimate grid parameters. This paper proposes a novel approach that determines the grid phase angle using only current feedback, eliminating the need for grid voltage measurements or cascaded control schemes. The proposed method integrates a phase angle observer with a current controller to regulate real and reactive power. Lyapunov stability analysis and hardware experiments validate the effectiveness of the approach.

Design And Implementation Of Uvm-Based Verification Framework For Deep Learning Accelerators, Randa Ahmed Hussein Aboudeif

Theses and Dissertations

Recent advancements in deep learning (DL) have made hardware accelerators, known as deep learning accelerators (DLAs), a preferred solution for numerous high-performance computing (HPC) applications, including speech recognition, computer vision, and image classification. DLAs are composed of hundreds of parallel processing engines to speed up computations and can gain access to pre-trained networks from the cloud or through on-chip memory to implement the DNN inference process. DLA verification is becoming an important and challenging phase. The verification process is required to handle the complex DLA design. Moreover, the reliability of DLAs is critical for assessment as they are involved in …

A Precoding, Companding, And Nonlinearity Reduction Approach To Optimize High-Speed Ado-Ofdm For Visible Light Communication, Swaminathan S

Theses and Dissertations

Using light-emitting diodes (LEDs) for data transfer, visible light communication (VLC) presents a strong substitute for radio frequency communication. Yet, because of the non-linearity of LEDs, conventional Orthogonal Frequency-Division Multiplexing (OFDM) approaches in VLC are limited regarding spectrum efficiency, peak-to-average power ratio (PAPR), and system linearity. Multi-carrier asymmetrically Clipped Optical OFDM (MADO-OFDM) is introduced in this study. For VLC operations based on Optical Orthogonal Frequency Division Multiplexing (O-OFDM), a model-driven Deep Learning (DL) approach has been presented. Utilizing an Auto Encoder (AE) network technology reduced the non-linearity of the LEDs. A proposed improved ADO-OFDM protocol, called MADO-OFDM, adaptively modifies the …

Sensing Rotational Direction Using Paramagnetic Nanoparticles For Gyroscopic Applications, Jacob C. Pung

Masters Theses

Gyroscopes have long been used for measuring an object’s angular orientation. Methods range from mechanical spinning disks to oscillating spring-mass systems. However, previous gyroscopes can suffer from high maintenance or fragility. A recently invented novel gyroscope aims to curb these restrictions through the use of ferrofluid.

This thesis proposes a new method of modeling and measuring the signals from the novel gyroscopic device. Rather than simply measuring the device’s average current consumption via slow RMS measurements, an attempt was made to model the voltage amplitude at any time. This allows a faster examination of both the changing magnitude and phase …

Feasibility And Acceptability Of The Mazi Umntanakho Digital Tool In South African Settings: A Qualitative Evaluation, Catherine E. Draper, Caylee J. Cook, Elizabeth A. Ankrah, Jesus A. Beltran, Franceli L. Cibrian, Kimberley D. Lakes, Hanna Mofid, Lucretia Williams, Gillian R. Hayes

Engineering Faculty Articles and Research

To address the need for interventions targeting social emotional development and mental health of young children in South Africa, the Mazi Umntanakho (‘know your child’) digital tool was co-designed, and piloted with caregivers and 3–5-year-old children involved in home visiting programmes promoting early childhood development. The aim of this study was to qualitatively evaluate the feasibility and acceptability of this tool in four urban and four rural low-income communities, from the perspective of home visitors and caregivers. Focus groups were conducted with home visitors (n = 117) and caregivers (n = 72). Issues relating to the feasibility of …

Dunbar’S Number In Motion: Agent-Based Simulations Of Friendship Formation, Christopher R. Cooke, Cameron D. Lutz

Northeast Journal of Complex Systems (NEJCS)

By contrasting Lévy flight and random walk strategies in simulated agents, we discern the effect of movement behavior on the total duration of social interactions. Our agent-based simulation results approximate empirically observed Dunbar social circle formation using simple behavioral rules of interaction and compatibility to mimic exogenous attribute-based friendship formation. We simulate the complexities of social interactions among agents with unique attributes and a time budget for social engagement over a one-year period. Two distinct simulations were conducted to evaluate the behavioral contributions of Lévy flight and random walk movement patterns on cumulative interaction duration and the formation of Dunbar …

A Novel Mu-Metal Based Weak Magnetic Energy Harvester For Self-Powered Monitoring Of Power Grid Assets, Arsalan Habib Khawaja, Hassan Pervaiz, Dongsheng Cai, Jian Li, Qi Huang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a novel magnetic field driven contactless energy harvester with improved flux concentration capabilities for potential utilization in Power system monitoring where stray magnetic field is abundant and readily available. The designed harvester employs multilayered Mu-Metal based cone shaped core to maximize magnetic flux density. To achieve the final design, this work investigates magnetic flux concentration ability of various geometries and material properties in magnetic flux conditions typical to overhead 11 kV power distribution circuits. Impact of layers in core-coil region of harvesting coil on magnetic flux concentration is evaluated by means of Finite Element analysis. Resultantly, the …

Advanced Prediction Of Events And Temporal Expressions In Medical Text Using The Jena Api: Integrating Ontologies And Deep Learning, Hafida Tiaiba, Lyazid Sabri, Okba Kazar

Turkish Journal of Electrical Engineering and Computer Sciences

The automatic recognition of medical concepts and temporal expressions in narrative clinical text enhances the utility of electronic health records (EHRs) and supports clinical decision-making and research. However, challenges arise due to the complexity of medical language, ambiguity of terms, and variability in expression. To address these issues, the use of medical ontologies significantly improves data management in healthcare. A novel approach integrates various medical ontologies covering drugs, symptoms, diseases, anatomy, disease drivers, and food, and with convolutional neural networks (CNNs) -including Standard, Transposed, and Separable convolution models (CONSEPTR)- to extract both medical events (e.g., clinical departments, treatments, problems) and …

Machine Learning Models Approach For The Quantitative Classification Of Ferricyanide Compound Using Electrochemical Detection With Cpe-Fe3o4nps, Süleyman Aşir, Nemah Abu Shama, Najya Maroof Saleem, Devri̇m Kayali, Kami̇l Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

Most common electrochemical analysis techniques used to evaluate enzymes, proteins, and heavy metals over a wide potential range include electrochemical impedance EIS, differential pulse voltammetry DPV, and square wave voltammetry SQWV. Machine leaning algorithms MLA are employed to classify the Potassium ferricyaniyde K3Fe(CN)6 concentrations using a modified carbon paste electrode CPE embedded with iron (II, III) oxide (Fe3O4) NPs. The CV, DPV, and SQWV voltametric data collected from all K3Fe(CN)6 concentrations were used as input data to the machine learning algorithms. Signaling current of K3Fe(CN)6 concentrations improved at Fe3O4 modified with nanoparticles NPs CPE in a comparison with the unmodified …

Balancing Anarchy And Efficiency: Partial Team Formations And Learning In Potential Games, Muhammed Sayin

Turkish Journal of Electrical Engineering and Computer Sciences

Non-cooperative multi-agent learning, focusing on individual rationality (anarchy), often falls short in achieving system-wide efficiency in potential games, a class of games with applications in decentralized control and optimization. On the other hand, cooperative approaches prioritize system efficiency but often via global coordination, which could be impractical, e.g., for large-scale and less controlled environments. To address this dilemma, we propose a novel framework that introduces partial team formations, allowing team members with shared objectives to coordinate their actions while maintaining team-wise rationality for improved system-wide efficiency without the burden of global coordination. We model such interactions as a multi-team game …

Long-Range Inertia Prediction Considering Contemporary Evolution Of Power Grid Networks, Peter M. Makolo

Tanzania Journal of Engineering and Technology (TJET)

Reduced network inertia due to high penetration levels of non-synchronous generators in modern power systems is becoming a pressing issue. As a result, very quick inertial responses are observed after contingency events in networks. Due to quick inertial responses, there is a practically very limited time interval for control actions in real-time. Thus, system operators need to understand the prior inertia values to plan, control, and operate the network securely. Long-range forecasting of the network's inertia values, in contrast to short-range forecasting techniques, can pinpoint when the network is most likely to be vulnerable in a reasonable time ahead. Thus, …

A Content-Based Recommender System For The Uav Caching In The Field Of Entertainment In Fog Computing, Elham Darbanian, Mohsen Nickray

Turkish Journal of Electrical Engineering and Computer Sciences

The Unmanned Aerial Vehicle (UAV) can be used as good flying base stations to cache popular content and follow a user mobility pattern, to help them in a suitable services. Conventional edge caching algorithms often prioritize cache contents with higher popularity. Nevertheless, the cache capacity of mobile devices is restricted, and diverse clients may have expansive varieties in content inclination designs. In this manner, the performance and effectiveness of the cache will be so constrained without great strategies. The composition of recommender system and edge caching is considered as a new research topic, which is used to reduce cost and …

Compact Dual-Band Semicircular Slot Mimo Antenna Design For 5g Sub-6 Ghz Applications, Reham Wageh Abd El Salam Reham W., Amr H. Hussein Prof.Dr., Mustafa M. Abd Elnaby Prof. Dr., Hussein E. Seleem

Journal of Engineering Research

This paper presents a novel compact semi-circular slot (SCS) 4 × 4 MIMO antenna specifically designed for 5G sub-6 GHz applications, achieving significant isolation without requiring extra decoupling components. The antenna features four symmetric, orthogonally arranged elements, each sized at 42×42 .It includes a U-shaped radiating patch, which is fed by a 50-ohm microstrip line on the top surface of the substrate. A semicircle-defected ground structure (DGS) is etched on the underside to improve bandwidth and reduce overall size. To enable dual-band functionality, a T-shaped stub is incorporated into the U-shaped patch, allowing for adjustable resonant frequencies. The higher frequency …

Indoor Localization With Ensemble Machine Learning Via Visible Light Communication Channels, Alzahraa M. Ghonim, Wessam M. Salama

Journal of Engineering Research

An indoor localization system based on received signal strength, visible light communication (VLC) and several machine learning approaches is proposed in this paper. Our proposed framework is divided into two strategies. The first one is consisting of gathering our dataset based on MATLAB software to create indoor VLC channel model. While the second phase is depending on training the gained dataset using ensemble machine learning models. Specifically, random forest, decision tree and gradient boosting models. In order to evaluate the robustness of the proposed framework, several evaluation metrics are applied, specifically, training time, testing time, classification accuracy (CA), area under …

Performance Evaluation Of Free Space Optical Communication In Dar Es Salaam: Impact Of Scintillation And Modulation Schemes, Mustafa H. Mohsini

Tanzania Journal of Engineering and Technology (TJET)

Free space optical communication (FSO) holds significant relevance in the modern communication system as it offers high and unlimited data rates, enhanced security, rapid deployment, and low cost for installation. However, the performance of FSO transmission is greatly affected by harsh atmospheric conditions such as wind, temperature, and humidity, which induce scintillation. With the rapid growth of internet users and Dar es Salaam being a business city in Tanzania, higher and unlimited bandwidth for communication is highly demanded. This study primarily aims to evaluate the performance of FSO transmission in Dar es Salaam, Tanzania, by investigating the impact of atmospheric …

Improved Minimum Variance Channel Estimation Techniques For Ofdm Systems, Kwame S. Ibwe

Tanzania Journal of Engineering and Technology (TJET)

Orthogonal frequency division multiplexing (OFDM) systems face challenges in channel estimation due to noise, variability, and the doubly dispersive nature of wireless channels, which degrade performance. To address these challenges, a multichannel minimum variance double dispersive channel estimator is proposed. The method employs a hybrid approach that combines subspace and minimum variance techniques, optimizing the filter bank output power under a signal-to-noise ratio (SNR) constraint. This design preserves the desired signal while effectively suppressing disturbances, achieving robust performance with reduced computational complexity compared to existing methods. Simulation results demonstrate that the proposed estimator outperforms subspace and asymptotic methods in terms …

Design And Implementation Of Secured Hybrid Gateway Node For Securing Iot - Enabled Distribution Automation, Ally Bitebo

Tanzania Journal of Engineering and Technology (TJET)

The integration of smart grid and Internet of Things (IoT) technologies plays a crucial role in enhancing the quality of services provided by traditional electrical grids. This combination has enabled the introduction of new services, such as demand response, automatic meter reading, and IoT-enabled Distribution Automation (IoT-DA), which incorporates sensors, actuators, intelligent electrical devices (IEDs), and information and communication technologies to monitor and control the grid. However, this integration also introduces network security risks, including Denial of Service (DoS) attacks, false data injection, and masquerading attacks, such as system node impersonation that can transmit incorrect readings, trigger false alarms, and …