Engineering Commons^™

A Charging Strategy For Large Commercial Electric Vehicle Fleets, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A. S. Masoum

Research outputs 2022 to 2026

The popularity of Commercial Electric Vehicles (CEVs) has experienced a surge in recent years, particularly in urban vocational contexts, as a means of advancing towards the goal of attaining net-zero emissions by 2050. The return-to-base charging strategy, which involves charging CEVs at depots, has become a prevalent practice for smaller CEV fleets. Nevertheless, for larger CEV fleets, the limited charging capacity at depots presents a significant challenge, leading to a reliance on both limited depot charging infrastructure and public charging infrastructure. This reliance can have a substantial impact on both the operational costs and the sustainability of logistics services. To …

Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia

Research outputs 2022 to 2026

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …

Optimal Pilot Length For Key Generation In Correlated Wireless Channels, Danqi Li, Shihao Yan, Jia Zhang, Jiande Sun, Feng Shu

Research outputs 2022 to 2026

This work examines the optimal pilot length for key generation in correlated wireless channels. We first deduce the secret key capacity as a function of the pilot length N and other system parameters. Then, derive two fixed-point equations to identify the optimal N with and without an eavesdropper. Our analysis and numerical results confirm the existence of the optimal N that maximizes the secret key capacity, and both results for optimal N are consistent. Furthermore, the optimal N generally decreases with average signal-to-noise ratio and maximum Doppler shift. Our examination can provide useful guidelines in designing practical key generation systems.

Radiation Damage Simulation Using Molecular Dynamics In Ni-Based Alloy, Yanxin Shen, Yue Yang, Xuelian Ou, Peng Wang, Zhenjiang You, Xiaofeng Tian

Research outputs 2022 to 2026

In the present study, we investigated the irradiation-induced induction in Ni80Cr20, Ni80Fe20, Ni50Fe50, Ni40Fe40Cr20 by molecular dynamics (MD) simulation. A previously published modified potential is used to provide a detailed account of the process involved in the production and evolution of defects. Ni50Fe50 and Ni40Fe40Cr20 alloys exhibit comparable damage level and better radiation response compared to Ni80Cr20 and Ni80Fe20. The inhibition effect of interstitial clusters increases with the complexity of alloying elements. The alloying of Cr has resulted in Ni80Fe20 and Ni50Fe50 tend to form 1/3<111> dislocation loops while at the same time making Ni40Fe40Cr20 and Ni80Cr20 more susceptible to …

Application Of The Mixed Integer Nonlinear Programming Technique For The Economic Planning Of Transmission Networks In New Manner, Nader Shawky Abdelhakeem, Maged Gamal Lotfy, Mohamed Shibl Albags, Ahmed Saied Elzawawy

Mansoura Engineering Journal

In the recent years, the mathematical planning model of transmission networks based on full AC load flow has been developed. But, due to the model non-convexity and the existing of large number of local solutions, this model can only be used for small size networks as it consumes large unreasonable computation time in addition to its incapability to yield global solution in most cases. To overcome these problems, two new iterative solution procedures have been presented in this paper. In the first one, the objective function is changed to the minimization of the number of new lines required to satisfy …

A Survey On Few-Shot Class-Incremental Learning, Songsong Tian, Lusi Li, Weijun Li, Hang Ran, Xin Ning, Prayag Tiwari

Computer Science Faculty Publications

Large deep learning models are impressive, but they struggle when real-time data is not available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for deep neural networks to learn new tasks from just a few labeled samples without forgetting the previously learned ones. This setup can easily leads to catastrophic forgetting and overfitting problems, severely affecting model performance. Studying FSCIL helps overcome deep learning model limitations on data volume and acquisition time, while improving practicality and adaptability of machine learning models. This paper provides a comprehensive survey on FSCIL. Unlike previous surveys, we aim to synthesize few-shot learning and incremental …

Mosaic: A Prune-And-Assemble Approach For Efficient Model Pruning In Privacy-Preserving Deep Learning, Yifei Cai, Qiao Zhang, Rui Ning, Chunsheng Xin, Hongyi Wu

Computer Science Faculty Publications

To enable common users to capitalize on the power of deep learning, Machine Learning as a Service (MLaaS) has been proposed in the literature, which opens powerful deep learning models of service providers to the public. To protect the data privacy of end users, as well as the model privacy of the server, several state-of-the-art privacy-preserving MLaaS frameworks have also been proposed. Nevertheless, despite the exquisite design of these frameworks to enhance computation efficiency, the computational cost remains expensive for practical applications. To improve the computation efficiency of deep learning (DL) models, model pruning has been adopted as a strategic …

K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur

Publications

Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to tend to a user’s persona appropriately. This is particularly crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response with supplementing information from a background knowledge source. We develop K-PERM (Knowledge-guided PErsonalization with Reward Modulation), a dynamic conversational agent that combines these elements. …

Personalized Bayesian Inference For Explainable Healthcare Management And Intervention, Utkarshani Jaimini, Krishnaprasad Thirunaravan, Maninder Kalra, Robin Dawson, Amit Sheth

Publications

Chronic healthcare conditions such as Asthma re- quires constant monitoring and managing of symptoms and their triggers for better quality of life. Each asthma patient reacts very differently to potential triggers. Hence, there is a need to develop a explainable personalized framework for each patient to capture susceptibility to asthma triggers. We developed a personalized knowledge-based probabilistic model to predict asthma exacerbation for different environmental factors utilizing patient generated health data from pediatric asthma patients. Further, the personalized model provides a metric, called Health Coefficient, to quantify the health of a patient for varying environmental factors. We demonstrate the predictive …

Towards Pragmatic Temporal Alignment In Stateful Generative Ai Systems: A Configurable Approach, Kaushik Roy, Yuxn Zi, Amit Sheth

Publications

Temporal alignment in stateful generative artificial intelligence (AI) systems remains an underexplored area, particularly beyond goal-driven approaches in planning. Stateful refers to maintaining a persistent memory or “state” across runs or sessions. This helps with referencing past information to make system outputs more contextual and relevant. This position paper proposes a framework for temporal alignment with several configurable toggles. We present four alignment mechanisms: knowledge graph path-based, neural score-based, vector similarity-based, and sequential process-guided alignment. By offering these interchangeable approaches, we aim to provide a flexible solution adaptable to complex and real-world applications. This paper discusses the potential benefits and …

Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance In The Age Of Large Language Models, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Allen, Amit P. Sheth

Publications

Current Virtual Mental Health Assistants (VMHAs) primarily offer counseling and suggestive care but do not assist with patient diagnosis due to their lack of training in safety-constrained and specialized clinical process knowledge, referred to as ProKnow. In this work, we define ProKnow as an ordered set of information aligned with evidence-based guidelines or categories of conceptual understanding used by domain experts. We also introduce a new dataset of diagnostic conversations guided by safety constraints and Pro- Know, known as ProKnow-data. We develop a method for natural language question generation (NLG) designed to interactively gather diagnostic information from patients, termed ProKnow-algo. …

A Comprehensive Survey On Rare Event Prediction, Chathurangi Shyalika Jayakody Kankanamalage, Ruwan Wickramarachchi, Amit Sheth

Publications

Rare event prediction involves identifying and forecasting events with a low probability using machine learning (ML) and data analysis. Due to the imbalanced data distributions, where the frequency of common events vastly outweighs that of rare events, it requires using specialized methods within each step of the ML pipeline, i.e., from data processing to algorithms to evaluation protocols. Predicting the occurrences of rare events is important for real-world applications, such as Industry 4.0, and is an active research area in statistics and ML. This paper comprehensively reviews the current approaches for rare event prediction along four dimensions: rare event data, …

5g New Radio Access And Core Network Slicing For Next-Generation Network Services And Management, Abdullah Ridwan Hossain

Dissertations

In recent years, fifth-generation New Radio (5G NR) has attracted much attention owing to its potential in enhancing mobile access networks and enabling better support for heterogeneous services and applications. Network slicing has garnered substantial focus as it promises to offer a higher degree of isolation between subscribers with diverse quality-of-service requirements. Integrating 5G NR technologies, specifically the mmWave waveform and numerology schemes, with network slicing can unlock unparalleled performance so crucial to meeting the demands of high throughput and sub-millisecond latency constraints.

While conceding that optimizing next-generation access network performance is extremely important, it needs to be acknowledged that …

Distributed Intelligence: Exploring Federated Paradigms Across Computing And Networking On The Edge, Yang Deng

Dissertations

Computer Graphics (CG) revolves around virtual content creation using computational methods, spanning applications from games to visual effects. Typically, the creation of CG content is led by expert practitioners who guide computational algorithms towards satisfactory results. Thus, creating CG content often requires manual iterations encompassing algorithm design, parameter tuning, and aesthetic feedback. This work investigates how to leverage crowd-sourcing to streamline such creation processes, focusing on animation and simulation. In animation, a novel crowd-sourcing framework is proposed for combat animation, enabling users to analyze motion similarities, and retrieve matching motions using novel crowd-sourced motion features. Such features enable quantifying previously …

Comparison Of Dc Motor Speed Calculation Efficiency Between Inductive Proximity Sensor And Rotary Encoder, Dino Dwi Aryanto, S. Sukir

Elinvo (Electronics, Informatics, and Vocational Education)

This study examines the level of effectiveness and efficiency of a sensor on the calculation of the rotational speed (RPM) of a DC motor, considering that the calculation of the rotational speed of an electric motor, both AC motors and DC motors, greatly influences the output of the system. the speed of motor rotation is very influential in several fields, such as power generation, which will affect the output voltage that will be generated. There are many methods for measuring the rotational speed of a motor, including using an inductive proximity sensor and a rotary encoder combined with a PLC …

Gen-Acceleration: Pioneering Work For Hardware Accelerator Generation Using Large Language Models, Durga Lakshmi Venkata Deepak Vungarala

Theses

Optimizing computational power is critical in the age of data-intensive applications and Artificial Intelligence (AI)/Machine Learning (ML). While facing challenging bottlenecks, conventional Von-Neumann architecture with implementing such huge tasks looks seemingly impossible. Hardware Accelerators are critical in efficiently deploying these technologies and have been vastly explored in edge devices. This study explores a state-of-the-art hardware accelerator; Gemmini is studied; we leveraged the open-sourced tool. Furthermore, we developed a Hardware Accelerator in the study we compared with the Non-Von-Neumann architecture. Gemmini is renowned for efficient matrix multiplication, but configuring it for specific tasks requires manual effort and expertise. We propose implementing …

Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, May Itani, Layal Abu Daher, Ahmad Hammoud

BAU Journal - Science and Technology

With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics …

The Interaction Of The Cotton Piece With The Piles Of The Scrabble Cotton Drum, Fazliddin Egamberdiev, Ilkhom Abbazov, Oybek Kholmuratov, Rashid Kaldybaev

Technical science and innovation

This article presents the results of an analytical study of the process of loosening and cleaning raw cotton from small debris by pileging working bodies of purifiers, on the basis of which directions for further research were chosen to optimize the parameters of the developed pile drum with spherical piles and rubber strips. Cotton entering production contains impurities. The processes of loosening and cleaning the fiber shreds are key in the initial stages of ginning, as they prepare the raw cotton for ginning and directly affect the reliability, productivity of these processes and the quality of the resulting fiber. Weed …

Creating A 3d Model Of The Planned Construction Area Of The Npp In Autocad Civil, Аbduvali A. Abduazizov, Olimjon Raxmonovich Allanazarov, Anvarjon Pardaboy Ugli Pardaboyev, Xusnidin Abdushukurovich Qoraboyev, Kamolliddin Аbdishukurovich Qoraboyev

Technical science and innovation

This article presents the AutoCAD Civil of the area where a nuclear power plant is planned to be built. in a programme A 3D model has been created . AutoCAD Civil in article The program is considered a universal program for performing work in the field of geodesy, topography, general plans, as well as the design and reconstruction of linear objects (roads, railways, utility networks). The main feature of the program in this work is a dynamic design model, which allows you to quickly and without errors make changes to the project at any design stage and in any model …

Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, Francesco Gregoretti

Technical science and innovation

Modern methods for solving problems of planning the execution of batches of tasks in multi-stage systems are characterized by the presence of restrictions on their dimensionality, the impossibility of guaranteed obtaining better results in comparison with fixed packages for different values of the input parameters of the problem. In the article, the author solved the problem of optimizing the composition of job packages running in multi-stage systems using the branch and bound method. Research has been carried out on various ways to form package execution orders tasks in multi-stage systems (heuristic rules for ordering packages tasks in the sequence of …

Use Of Hydroelectric Power Plants In Regulation Of Daily Load Of The Electric Power System Of The Republic Of Uzbekistan, Boborakhim Urishev, Burkhon Donayevich Donayev,

Technical science and innovation

The necessity of optimal regulation of power generation and consumption in the energy system of the Republic of Uzbekistan by highly manoeuvrable hydro- and hydro-storage power plants has been substantiated, their participation in the regulation of energy production process has been analysed on the example of the daily load schedule of the energy system. The method of determining the energy characteristics of power plants by solving the problem of optimal distribution of loads between hydro- and thermoelectric power plants during the day, taking into account the maximum use of limited water resources. The results of calculations of load distribution between …

Potential Applications Of Encoders, Erkin Uljaev, Utkirjon Murodillayevich Ubaydullaev

Technical science and innovation

This article explores the applicability of diverse sensor types—such as optical, magnetic incremental encoder and potentiometric sensors—for controlling the turning angle of tractor steering wheels, specifically addressing the control challenges faced by semi-mounted cotton pickers. The discussion encompasses fundamental principles, operational aspects, advantages, and limitations of turning angle sensors prevalent in the industry. Emphasizing advancements in sensor technology, the article recommends sensor options for controlling the steering wheel's turning angle, crucial for enhanced maneuverability and operational efficiency of semi-mounted cotton pickers. Various sensor types, including optical and magnetic encoders and potentiometers, are evaluated for their suitability in this context. Optical …

An Experimental Investigation Of The New Vibration Viscometer, Jamshidbek Ulugbek Ugli Shamuratov

Technical science and innovation

The characteristics of the new oscillating-plate viscometer have been investigated experimentally. The results obtained are as follows: the resonant frequency of plate oscillation decreases with increasing viscosity; the apparatus constant 𝐾 determined experimentally includes the end and slip effects; the dimensions of the plate should be determined by referring to empirical relations between 𝜌𝜇 and Λ(≡{(𝐸𝑎𝐸)−1}𝑛) for various dimensions of the plate; where 𝜌 is the density, 𝜇 is the viscosity; 𝐸𝑎 the resonant amplitude of plate in the air; E the amplitude of plate in a liquid, and 𝑛 a constant. If the distance between the plate and the …

Indicators Affecting Passenger Service Processes And Their Scientific Interpretation, Maxliyoxon Madaminova Maxamatjon Qizi, Saidazim Amanullayevich Ganihodjayev

Technical science and innovation

Many traffic flow parameters affect the performance of the road network at high voltage. These are low vehicle speeds, high vehicle distances relative to road capacity, and density per unit time (lane occupancy). In turn, a number of factors affect the decrease in traffic speed: the presence of slow-moving vehicles in the stream; pedestrians crossing the road irregularly; increase in traffic flow, etc. The issues of public transportation depend on many factors, each of which requires a separate approach and a complex solution. In large cities around the world, the quality indicators of public transport services, including the issues of …

Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot Qizi Phd

Technical science and innovation

Currently, much attention is paid to the issue of energy efficiency of gas processing enterprises. The continuous growth of world prices for energy resources requires constant improvement of the management system, providing the most optimal conditions for the flow of technological processes. A conceptual model of the heat-mass transfer process occurring in the absorber as an object of research has been developed, which characterizes the relationship of the variables involved in the drying process of natural gas, control, measurable and immeasurable, as well as controlled parameters have been selected, which are used to develop and study a mathematical model of …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Algorithms For Synthesis Of Adaptive Control Systems With A Customized Model Using The Speed Gradient Method, Jasur Sevinov, Oxunjon Boborayimov

Chemical Technology, Control and Management

Algorithms are considered for the synthesis of adaptive control systems with a customized model based on the speed gradient method. For the synthesis of adaptive control systems, the identification approach is based on obtaining estimates of the unknown parameters in the object. By calculating the speed gradient, identification algorithms with an explicit and implicit customized model were obtained as well as that in sliding modes. A joint solution is given to the interrelated problems of identifying parameters with insufficient current information. The position of an object is about assessing the state with insufficient a priori information about its parameters. This …

Improvement Of Calorimetric Quality Analyzers For Substances, Makhfuza Azimovna Radjabova

Chemical Technology, Control and Management

It is noted that the development of intelligent means of measuring qualitative indices is of topical importance. Since the quality of many substances is determined by optical methods, an algorithm for spectrophotometric data processing has been developed, which consists of primary data processing (stage I) and determination of qualitative indices of liquid products (stage II). Since the task of numerical determination of colour characteristics of transmittance coefficients of liquid samples is incorrectly set, it is recommended to use regularization methods of A.N.Tikhonov to improve metrological characteristics of the device. On the basis of regularization methods for solving incorrect problems, algorithms …

Life Cycle Management Of A Technological Complex For Separating Multicomponent Mixtures Under Conditions Of Uncertainty Of Parameters, Yusuf Shodievich Avazov

Chemical Technology, Control and Management

The issue of control the lifecycle of technological complexes of multicomponent mixtures is considered, taking into account the uncertainty of parameters. Among uncertainties such as parameter uncertainty, model uncertainty, choice uncertainty under variability, spatial variability uncertainty, temporal variability uncertainty, inter-site variability uncertainty, more attention is paid to input parameter uncertainty and action uncertainty. The rectification technology is schematically presented, the influence of parameter uncertainty on the technological functions of the rectification complex. The scheme analyzes the control and assessment of “uncertainty” to repeat the lifecycle of the rectification complex and make changes to the components of the rectification complex technology. …

Improvements Of The Control System For The Technological Process Of Drying Bulk Materials, Azizbek Nodirbekovich, Dilmurod Ikromovich

Chemical Technology, Control and Management

The issues of convective drying of bulk materials as objects of monitoring, control and advanced management are presented based on the results of simulation modeling of a complex heat and mass transfer process, taking into account the drying kinetics. As a result of the work of a number of them, in the last few decades neat hypotheses were formed about moisture migration in and around dried materials, which led to the creation of accurate mathematical models of drying behavior, with successfully applied in a wide range of fields. The reasons for this are the dynamics of processes in the drying …