Engineering Commons^™

Enhancing Service Restoration In Tanzanian Power Grid Using Internet Of Things Sensors And Renewable Energy Sources, Rukia J. Mwifunyi, Daudi C. Mnyanghwalo, Shamte J. Kawambwa

Tanzania Journal of Science

The increased dependence on the electric power grid, coupled with the increasing number of new customers, motivates the need to improve the reliability and resilience of the electric distribution systems. Modern distribution systems are becoming more resilient against power outages due to the increasing integration of Distributed Energy Resources (DERs) and the availability of efficient mechanisms for load shedding. Several studies considered fault detection and Service Restoration (SR) as separate problems without considering the implementation feasibility of integrating both solutions. To ensure the resiliency in the power system, it is important to have proper mechanisms which integrate sensing, detection, and …

The Santa Clara, 2023-09-29, Santa Clara University

The Santa Clara

No abstract provided.

Using T-Distributed Stochastic Neighbor Embedding For Visualization And Segmentation Of 3d Point Clouds Of Plants, Heli̇n Dutağaci

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, the use of t-SNE is proposed to embed 3D point clouds of plants into 2D space for plant characterization. It is demonstrated that t-SNE operates as a practical tool to flatten and visualize a complete 3D plant model in 2D space. The perplexity parameter of t-SNE allows 2D rendering of plant structures at various organizational levels. Aside from the promise of serving as a visualization tool for plant scientists, t-SNE also provides a gateway for processing 3D point clouds of plants using their embedded counterparts in 2D. In this paper, simple methods were proposed to perform semantic …

Dynamic Deep Neural Network Inference Via Adaptive Channel Skipping, Meixia Zou, Xiuwen Li, Jinzheng Fang, Hong Wen, Weiwei Fang

Turkish Journal of Electrical Engineering and Computer Sciences

Deep neural networks have recently made remarkable achievements in computer vision applications. However, the high computational requirements needed to achieve accurate inference results can be a significant barrier to deploying DNNs on resource-constrained computing devices, such as those found in the Internet-of-things. In this work, we propose a fresh approach called adaptive channel skipping (ACS) that prioritizes the identification of the most suitable channels for skipping and implements an efficient skipping mechanism during inference. We begin with the development of a new gating network model, ACS-GN, which employs fine-grained channel-wise skipping to enable input-dependent inference and achieve a desirable balance …

Joint Intent Detection And Slot Filling For Turkish Natural Language Understanding, Osman Büyük

Turkish Journal of Electrical Engineering and Computer Sciences

Intent detection and slot filling are two crucial subtasks of a text-based goal-oriented dialogue system. In a goal-oriented dialogue system, users interact with the system to complete a goal (or to fulfill their intent) and provide the necessary information (slot values) to achieve that goal. Therefore, a user?s text input includes information about the user?s intent and contains required slot values. Recently, joint models that simultaneously detect the intent and extract the slots are proposed to benefit from the interaction between the two tasks. The proposed methods are usually tested using benchmark data sets in English such as ATIS and …

Transforming Temporal-Dynamic Graphs Into Time-Series Data For Solving Event Detection Problems, Kutay Taşci, Fuat Akal

Turkish Journal of Electrical Engineering and Computer Sciences

Event detection on temporal-dynamic graphs aims at detecting significant events based on deviations from the normal behavior of the graphs. With the widespread use of social media, many real-world events manifest as social media interactions, making them suitable for modeling as temporal-dynamic graphs. This paper presents a workflow for event detection on temporal-dynamic graphs using graph representation learning. Our workflow leverages generated embeddings of a temporal-dynamic graph to reframe the problem as an unsupervised time-series anomaly detection task. We evaluated our workflow on four distinct real-world social media datasets and compared our results with the related work. The results show …

Recognizing Handwritten Digits Using Spiking Neural Networks With Learning Algorithms Based On Sliding Mode Control Theory, Yeşi̇m Öni̇z, Mehmet Ayyildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a spiking neural network (SNN) has been proposed for recognizing the digits written on the LCD screen of an experimental setup. The convergence of the learning algorithm has been ensured by using sliding mode control (SMC) theory and the Lyapunov stability method for the adaptation of the network parameters. The spike response model (SRM) has been utilized in the design of the SNN. The performance of the proposed learning scheme has been evaluated both on the experimental data and on the MNIST dataset. The simulated and experimental results of the SNN structure have been compared with the …

A Machine Learning Approach For Dyslexia Detection Using Turkish Audio Records, Tuğberk Taş, Muhammed Abdullah Bülbül, Abas Haşi̇moğlu, Yavuz Meral, Yasi̇n Çalişkan, Gunay Budagova, Mücahi̇d Kutlu

Turkish Journal of Electrical Engineering and Computer Sciences

Dyslexia is a learning disorder, characterized by impairment in the ability to read, spell, and decode letters. It is vital to detect dyslexia in earlier stages to reduce its effects. However, diagnosing dyslexia is a time-consuming and costly process. In this paper, we propose a machine-learning model that predicts whether a Turkish-speaking child has dyslexia using his/her audio records. Therefore, our model can be easily used by smart phones and work as a warning system such that children who are likely to be dyslexic according to our model can seek an examination by experts. In order to train and evaluate, …

Direct Pore-Based Identification For Fingerprint Matching Process, Vedat Delican, Behçet Uğur Töreyi̇n, Ege Çeti̇n, Ayli̇n Yalçin Saribey

Turkish Journal of Electrical Engineering and Computer Sciences

Fingerprints are one of the most important scientific proof instruments in solving forensic cases. Identification in fingerprints consists of three levels based on the flow direction of the papillary lines at the first level, the minutiae points at the second level, and the pores at the third level. The inadequacy of existing imaging systems in detecting fingerprints and the lack of pore details at the desired level limit the widespread use of third-level identification. The fact that fingerprints with images based on pores in the unsolved database are not subjected to any evaluation criteria and remain in the database reveals …

The Role Of Nanofluids In Renewable Energy Engineering, M. M. Bhatti, K. Vafai, Sara I. Abdelsalam

Basic Science Engineering

No abstract provided.

Stepwise Dynamic Nearest Neighbor (Sdnn): A New Algorithm For Classification, Deni̇z Karabaş, Derya Bi̇rant, Peli̇n Yildirim Taşer

Turkish Journal of Electrical Engineering and Computer Sciences

Although the standard k-nearest neighbor (KNN) algorithm has been used widely for classification in many different fields, it suffers from various limitations that abate its classification ability, such as being influenced by the distribution of instances, ignoring distances between the test instance and its neighbors during classification, and building a single/weak learner. This paper proposes a novel algorithm, called stepwise dynamic nearest neighbor (SDNN), which can effectively handle these problems. Instead of using a fixed parameter k like KNN, it uses a dynamic neighborhood strategy according to the data distribution and implements a new voting mechanism, called stepwise voting. Experimental …

Cognitive Load Detection Using Ci-Ssa For Eeg Signal Decomposition And Nature-Inspired Feature Selection, Jammisetty Yedukondalu, Lakhan Dev Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

Cognitive load detection is eminent during the mental assignment of neural activity because it indicates how the brain reacts to stimuli. The level of cognitive load experienced during mental arithmetic tasks can be determined using an electroencephalogram (EEG). The EEG data were collected from publicly available datasets, namely, mental arithmetic task (MAT) and simultaneous task workload (STEW). The first phase comprises decomposing the electroencephalogram (EEG) signal into intrinsic mode functions (IMFs) using circulant singular spectrum analysis (Ci-SSA). In the second phase, entropy-based features were evaluated using IMFs. After that, the extracted features were fed to nature-inspired feature selection algorithms: genetic …

Modeling Leaf-Level Transpiration: Exploring The Consequences Of Assumed Saturated Vapor Pressure In Leaves, Danlyn L. Brennan

Dissertations and Theses

Understanding the dynamics of water transport through leaf intercellular airspaces (IAS) and its impact on transpiration is crucial for accurate predictions of plant water use and ecosystem response to changing climates. This study investigates the implications of assuming undersaturation of water vapor in the IAS for transpiration predictions and explores potential modifications to standard modeling approaches.

A dynamic 1D soil-plant-atmosphere continuum using a stomatal optimization model (SPAC-SOT) framework was used to simulate the response of tree species, P. edulis, to prolonged drought and varying environmental conditions. Comparisons between two model assumptions (saturated vs. undersaturated IAS) reveal notable differences in …

Asymmetric Electrode-Electrolyte Interfaces For High-Performance Rechargeable Lithium-Sulfur Batteries, Jia Chou, Ya-Hui Wang, Wen-Peng Wang, Sen Xin, Yu-Guo Guo

Journal of Electrochemistry

With a high cell-level specific energy and a low cost, lithium-sulfur (Li-S) battery has been intensively studied as one of the most promising candidates for competing the next-generation energy storage campaign. Currently, the practical use of Li-S battery is hindered by the rapidly declined storage performance during battery operation, as caused by irreversible loss of electroactive sulfide species at the cathode, dendrite formation at the anode and parasitic reactions at the electrode-electrolyte interface due to unfavorable cathode-anode crosstalk. In this perspective, we propose to stabilize the Li-S electrochemistry, and improve the storage performance of battery by designing asymmetric electrode-electrolyte interfaces …

Hydrophobicity Optimization Of Cathode Catalyst Layer For Proton Exchange Membrane Fuel Cell, Hao-Jie Chen, Mei-Hua Tang, Sheng-Li Chen

Journal of Electrochemistry

Hydrophobicity of the cathode catalyst layers (CCLs) crucially determines the performance of proton exchange membrane fuel cells (PEMFCs) by affecting the transports of oxygen and liquid water. In this regard, polytetrafluoroethylene (PTFE) is usually used as a hydrophobic additive to facilitate the oxygen and water transports in CCLs. So far, there remains lacking systematic effort to optimize the addition methods of PTFE in CCLs and the mechanisms behind. In this work, the effects of the approaches for PTFE addition and the distribution of PTFE on the mass transport of oxygen and the proton conduction in CCLs were studied by using …

Dependence Of Heat Transfer Model On The Structure Of Electrically Coil-Heated Microelectrodes, Ju Li, Sen Yang, Jian-Jun Sun

Journal of Electrochemistry

Electrically heated microelectrodes have gained much attention in electroanalytical chemistry in recent years. It has been shown that the promotion of mass transport and reaction kinetics at high-temperatures often results in increased current signals. However, there is no study about the heat transfer inner the microelectrodes which is necessary for the design and operation for microsensors. This report introduces a finite element software (COMSOL) to analyze the factors that influence the surface temperature (T_s), which is crucial for the heating ability of micro-disk electrodes with coils. Distances between the electrode surface and the bottom of the heated copper …

Privacy-Preserving Federated Learning, Dumindu Samaraweera

Math Department Colloquium Series

AI's applicability across diverse fields is hindered by data sensitivity, privacy concerns, and limited training data availability. Federated Learning (FL) addresses this challenge by enabling collaborative machine learning while preserving data privacy. FL allows clients to engage in model training with their local data, avoiding centralized storage. However, even with FL, security threats persist, jeopardizing model integrity and client data privacy. In this presentation, we will explore our latest findings in this area of research, safeguarding sensitive data from attacks through techniques like secure multiparty computation, homomorphic encryption, and differential privacy within the FL framework, enhancing data protection, and expanding …

Multi-Criteria Analysis Of The Possibility Of Retrofitting The System Of Rainwater Drainage From Subsidence Basins In A Liquidated Mine, Andrzej Chmiela, Małgorzata Wysocka, Adam Smoliński

Journal of Sustainable Mining

Mine closure is the natural final stage of mining activity. The process of financing mine liquidation is complex and expensive. The many years of conducted hard coal extraction affect the surface height differences. Analyses of the shifts in hydrogeological conditions and water hazard states in mining plants led to legal regulation adaptations, primarily in terms of hydrogeological documentation preparation, and made it necessary to conduct work concerning new options for water hazard assessment and prevention. Current subjects of particular interest include shifts in terrain morphology and the water regime, resulting in periodic flooding and permanent flooding of the most depressed …

Research On Three-Stage Automatic Hole Packer For Gas Extraction Drilling In Underground Coal Mine, Wang Qingfeng, Shi Shuhan, Xin Dezhong, Chen Hang, Zhang Shitao

Coal Geology & Exploration

In view of the requirements of hole sealing during gas extraction drilling in underground coal mine for manual packer installation and sealing material injection, as well as the low automation level of hole sealing technology, a three-stage automatic hole packer for gas extraction drilling in underground coal mine was developed, with the appearance similar to the drill pipe. The hole packer could be mechanized into the drilling hole by an automatic drilling machine, and realize the automatic injection of sealing material. Herein, the Mooney-Rivlin hyperelastic constitutive model was used to represent the strain energy function by the finite element analysis …

Intelligent Optimization And Control Technology For Drilling Process Of Coal Mine Tunnels, Yao Ningping, Wu Min, Chen Luefeng, Lu Chengda, Fan Haipeng, Zhang Youzhen, Li Wangnian, Yao Ke

Coal Geology & Exploration

The harsh environment for drilling construction of coal mine tunnel, complex coal seam structure and complicated operation procedures can cause low drilling efficiency and high drilling cost. For this reason, it is imperative to carry out studies on the optimization and control technology for the drilling process of coal mine tunnel. Herein, study was conducted from intelligent identification of lithology of coal-bearing formation, intelligent optimization of drilling parameters and their intelligent control, focusing on the key technology for control of drilling process of coal mine tunnel. First, in order to accurately determine the type of coal-bearing formation, an intelligent identification …

Synergistic Effect Of Nanoclay And Barium Sulfate Fillers On The Corrosion Resistance Of Polyester Powder Coatings, Jinbao Huang, Marshall Shuai Yang, Chengqian Xian, James Joseph Noel, Yolanda S. Hedberg, Jian Chen, Ubong Eduok, Ivan Barker, Jeffrey Daniel Henderson, Haiping Zhang, Liqin Wang, Hui Zhang, Jesse Zhu

Chemistry Publications

No abstract provided.

Research Status And Development Trend Of Near-Bit Mwd In Underground Coal Mine, Hao Shijun, Chu Zhiwei, Li Quanxin, Fang Jun, Chen Long, Liu Jianlin

Coal Geology & Exploration

Near-bit meusurement while drilling (MWD) integrates several key technologies such as near-bit multi-parameter measurement, power supply and communication across positive displacement motor drills, turbine continuous power generation and high-speed mud pulse wireless transmission, capable of obtaining various types of parameters near the bit. It is one of the key components of intelligent drilling technology in underground coal mine. Herein, the limitation of the existing technology applied in coal mine was analyzed with full reference to the development experience and development path of near-bit MWD in the field of surface oil and gas drilling. Meanwhile, the research idea of near-bit MWD …

Continuous And Discontinuous Numerical Simulation Of The Rock Breaking Process Of Pdc Drill Bit Under Composite Impact, Qin Chengshuai, Sun Hongbin, Li Liping, Liu Xuegang, Liu Zhihui, Feng Chun, Sun Zizheng

Coal Geology & Exploration

Composite impact drilling is a novel rock-breaking technique that combines both axial and torsional impacts. To address the issues of complex failure mechanisms and unclear rock-breaking mechanisms under the axial-torsional impacts on rock by Polycrystalline Diamond Compact (PDC) drill bits, a FEM-DEM rock model based on shared nodes was established using the Continuous Discontinuous Element Method (CDEM), and the rationality of this computational model was verified through laboratory uniaxial compression experiments. Besides, a composite impact motion model for single drill bit was built through the secondary development of JavaScript, and the composite impact rock-breaking process of single PDC drill bit …

Application Of Intelligent Direct Push Measurement While Drilling Device For Environmental Geological Surveys, Sun Pinghe, Zhou Shengwei, Cao Han, Gao Qiang, Cheng Gongbi, Zhang Hui

Coal Geology & Exploration

In order to solve the technical challenges of inaccuracy and poor credibility of contaminant survey results due to the low accuracy of drilling trajectories in environmental geological surveys, the structural and functional characteristics of the existing direct-push drilling tools were analyzed. On this basis, the method of near-bit measurement while drilling using single-action combination was proposed. An intelligent measurement-while-drilling (MWD) device was developed, a laboratory platform monitoring module was established, a set of monitoring software was developed, and the stability and reliability of the intelligent MWD device was analysed. Then, verification tests have been carried out on the laboratory platforms …

Wear Law And Design Of Assembling Diamond Bit Based On Finite Element Analysis, Yang Zhan, Tan Songcheng, Yang Kaihua, Fang Xiaohong

Coal Geology & Exploration

In addition to coring drilling, full (non-coring) drilling also occupies a large proportion in the energy exploration and development. Non-coring drilling can reduce the high time cost of lifting and lowering work required for coring, thereby increasing the net drilling time, improving the drilling efficiency and reducing the drilling costs. The traditional non-coring drill bits are prone to uneven wear on the bit surface during the drilling process. To identify and improve this law of uneven wear, it was herein proposed to use the assembling non-coring bit to improve the eccentric wear of bit. For this reason, numerical simulation analysis …

3d Garment Collision Simulation Based On Human Skeletal Features, Yuanyuan Chen, Yongjian Huai, Xiaoying Nie, Ke Lang

Journal of System Simulation

Abstract: In order to enhance the realism of garment and human body collision in real-time fabric simulation, an automated human body fitting collision method based on the bounding box and mesh method is proposed. According to the human skeletal structure and garment type, the skeletal information involved in collision simulation is effectively optimized, so as to better obtain the feature points of the human body and semantically segment them. According to the characteristics of skinning animation, simple capsule colliders and mesh colliders are generated to fit the geometric shape of the human body, and the dynamic following of colliders is …

Table Of Contents, The Editors

Coal Geology & Exploration

No abstract provided.

Attenuation Model And Law Of High-Frequency Drilling Fluid Pressure Wave, Zhou Botao, Su Yinao, Wang Jiajin

Coal Geology & Exploration

The technology of transmitting high-frequency drilling fluid pressure wave information with high transmission rate. It is also one of the key technologies to achieve the automated and intelligent drilling. However, the field application of this technology is hindered by the substantial attenuation experienced by high-frequency drilling fluid pressure waves during the transmission process. Thus, exploring the attenuation characteristics of these waves is crucial for the development of high-speed transmission technology. Herein, it is assumed that the drilling fluid pressure is equivalent on the same section of drill string, and the flow rate of drilling fluid is radially distributed. On this …

Magnetic Beacon-Based Horizontal Directional Drilling Guidance Technology, Zu Yutong, Wang Lu, Gong Da, Hu Yuanbiao

Coal Geology & Exploration

In order to solve the problems of existing horizontal directional drilling (HDD) guidance methods, including low measurement accuracy, shallow positioning distance, discontinuous measurement data and great interference by magnetic field, a magnetic beacon-based horizontal directional drilling guidance and positioning method was proposed to achieve the position and attitude measurement of HDD. Meanwhile, a measurement array based on the third-order magnetic gradient tensor was designed, which verifies through simulation that the method could eliminate the influence of the geomagnetic fields and achieve the position measurement. In order to improve the attitude measurement accuracy, the multisource data fusion was performed with MEMS …

Analysis On Motor Output Characteristics And Influencing Factors Of Oscillating Valve Mud Pulser, Qu Hanwu, Shang Jie, Lu Huatao, Wang Zhiming, Chen Kun

Coal Geology & Exploration

The oscillating valve pulser is a better choice for high-speed mud pulse transmission due to its capability of generating a higher frequency carrier. Great difficulties are brought to the research on the motor output characteristics due to the complex load moment and its numerous influencing factors during the operation. Using the dynamic balance equation for the motor operating in underground coal mine, the position angle and output current data of the oscillating valve motor under the Max Torque per Ampere (MTPA) control mode were obtained by measurement in the water cycle experiment. Then, the output torque and output power of …