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Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.) Jan 2023

Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.)

Electrical & Computer Engineering Faculty Publications

This work is a review and extension of our ongoing research in human recognition analysis using multimodality motion sensor data. We review our work on hand crafted feature engineering for motion capture skeleton (MoCap) data, from the Air Force Research Lab for human gender followed by depth scan based skeleton extraction using LIDAR data from the Army Night Vision Lab for person identification. We then build on these works to demonstrate a transfer learning sensor fusion approach for using the larger MoCap and smaller LIDAR data for gender classification.

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Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner Jan 2023

Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner

Electrical & Computer Engineering Faculty Publications

This paper presents a novel deep-learning (DL)-based approach for classifying digitally modulated signals, which involves the use of capsule networks (CAPs) together with the cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals, but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in the paper …

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Continuity Of Formal Power Series Products In Nonlinear Control Theory, W. Steven Gray, Mathias Palmstrøm, Alexander Schmeding Jan 2023

Continuity Of Formal Power Series Products In Nonlinear Control Theory, W. Steven Gray, Mathias Palmstrøm, Alexander Schmeding

Electrical & Computer Engineering Faculty Publications

Formal power series products appear in nonlinear control theory when systems modeled by Chen–Fliess series are interconnected to form new systems. In fields like adaptive control and learning systems, the coefficients of these formal power series are estimated sequentially with real-time data. The main goal is to prove the continuity and analyticity of such products with respect to several natural (locally convex) topologies on spaces of locally convergent formal power series in order to establish foundational properties behind these technologies. In addition, it is shown that a transformation group central to describing the output feedback connection is in fact an …

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Ict Security Tools And Techniques Among Higher Education Institutions: A Critical Review, Miko Nuñez, Xavier-Lewis Palmer, Lucas Potter, Chris Jordan Aliac, Lemuel Clark Velasco Jan 2023

Ict Security Tools And Techniques Among Higher Education Institutions: A Critical Review, Miko Nuñez, Xavier-Lewis Palmer, Lucas Potter, Chris Jordan Aliac, Lemuel Clark Velasco

Electrical & Computer Engineering Faculty Publications

Higher education institutions (HEIs) are increasingly relying on digital technologies for classroom and organizational management, but this puts them at higher risk for information and communication (ICT security attacks. Recent studies show that HEIs have experienced more security breaches in ICT security composed of both cybersecurity an information security. A literature review was conducted to identify common ICT security practices in HEIs over the last decade. 11 journal articles were profiled and analyzed, revealing threats to HEIs’ security and protective measures in terms of organizational security, technological security, physical security, and standards and frameworks. Security tools and techniques were grouped …

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A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, Danda Rawat Jan 2023

A Review Of Iot Security And Privacy Using Decentralized Blockchain Techniques, Vinay Gugueoth, Sunitha Safavat, Sachin Shetty, Danda Rawat

Electrical & Computer Engineering Faculty Publications

IoT security is one of the prominent issues that has gained significant attention among the researchers in recent times. The recent advancements in IoT introduces various critical security issues and increases the risk of privacy leakage of IoT data. Implementation of Blockchain can be a potential solution for the security issues in IoT. This review deeply investigates the security threats and issues in IoT which deteriorates the effectiveness of IoT systems. This paper presents a perceptible description of the security threats, Blockchain based solutions, security characteristics and challenges introduced during the integration of Blockchain with IoT. An analysis of different …

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Quantum Efficiency And Lifetime Study For Negative Electron Affinity Gaas Nanopillar Array Photocathode, Md Aziz Ar Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali Jan 2023

Quantum Efficiency And Lifetime Study For Negative Electron Affinity Gaas Nanopillar Array Photocathode, Md Aziz Ar Rahman, Md Abdullah Mamun, Shukui Zhang, Hani E. Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

Recent studies showed significant improvement in quantum efficiency (QE) by negative electron affinity (NEA) GaAs nanopillar array (NPA) photocathodes over their flat surface peers, particularly at 500 ─ 800 nm waveband. However, the underlying physics is yet to be well understood for further improvement in its performance. In this report, NEA GaAs NPA photocathodes with different dimensions were studied. The diameter of the nanopillars varied from 200 ─ 360 nm, the height varied from 230 ─ 1000 nm and the periodicity varied from 470 ─ 630 nm. The QE and photocathode lifetime were measured. Mie-resonance enhancement was observed at tunable …

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Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides Jan 2023

Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides

Electrical & Computer Engineering Faculty Publications

This editorial introduces the JMI Special Section on Artificial Intelligence for Medical Imaging in Clinical Practice.

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Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter Jan 2023

Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter

Electrical & Computer Engineering Faculty Publications

Biocybersecurity is an evolving discipline that aims to identify the gaps and risks associated with the convergence of Biology (the science of life and living organisms) and cybersecurity (the science, study, and theory of cyberspace and cybernetics) to protect the bioeconomy. The biological industries’ increased reliance on digitization, automation, and computing power has resulted in benefits for the scientific community, it has simultaneously multiplied the risk factors associated with industrial espionage and the protection of data both commercial and proprietary. The sensitive and potentially destructive power of this data and its access inherently poses a risk to the national and …

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A Reflection Of Typology And Verification Flaws In Consideration Of Biocybersecurity/Cyberbiosecurity: Just Another Gap In The Wall, Luke Potter, Kim Mossberg, Xavier Palmer Jan 2023

A Reflection Of Typology And Verification Flaws In Consideration Of Biocybersecurity/Cyberbiosecurity: Just Another Gap In The Wall, Luke Potter, Kim Mossberg, Xavier Palmer

Electrical & Computer Engineering Faculty Publications

Verification is central to any process in a functional and enduring cyber-secure organization. This verification is how the validity or accuracy of a state of being is assessed (Schlick, 1936; Balci, 1998). Conversely, breakdown in verification procedures is core to the interruption of normal operations for an organization. A key problem for organizations that utilize biology as an interlock within their systems is that personnel lack sufficient ability to verify all practically relevant biological information for procedures such as a nurse logging a blood draw, or a molecular biology technician preparing agar to culture microbes for study. This has several …

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Optimizing Technical And Economic Aspects Of Off-Grid Hybrid Renewable Systems: A Case Study Of Manoka Island, Cameroon, Reagan J. J. Molu, Serge R. D. Naoussi, Patrice Wira, Wulfran F. Mbasso, Saatong T. Kenfack, Barun K. Das, Enas Ali, Muhannad J. Alshareef, Sherif S. M. Ghoneim Jan 2023

Optimizing Technical And Economic Aspects Of Off-Grid Hybrid Renewable Systems: A Case Study Of Manoka Island, Cameroon, Reagan J. J. Molu, Serge R. D. Naoussi, Patrice Wira, Wulfran F. Mbasso, Saatong T. Kenfack, Barun K. Das, Enas Ali, Muhannad J. Alshareef, Sherif S. M. Ghoneim

Research outputs 2022 to 2026

The lack of accessible and reliable electrical energy in Cameroon has become a pervasive obstacle to the nation's progress, with energy availability, quality, and cost identified as key hindrances to development over the past 15 years. Conventional solutions that rely on combustion engines and electrochemical storage systems have proven to be cost-prohibitive, limited in power output, and constrained in capacity. The dependence on traditional diesel generators has perpetuated maintenance challenges and a continuous demand for fuel supply, while the accompanying noise and pollution have restricted their use in residential areas. Recognizing the imperative of reducing dependence on fossil fuels and …

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A Provable Secure And Efficient Authentication Framework For Smart Manufacturing Industry, Muhammad Hammad, Akhtar Badshah, Ghulam Abbas, Hisham Alasmary, Muhammad Waqas, Wasim A. Khan Jan 2023

A Provable Secure And Efficient Authentication Framework For Smart Manufacturing Industry, Muhammad Hammad, Akhtar Badshah, Ghulam Abbas, Hisham Alasmary, Muhammad Waqas, Wasim A. Khan

Research outputs 2022 to 2026

Smart manufacturing is transforming the manufacturing industry by enhancing productivity and quality, driving growth in the global economy. The Internet of Things (IoT) has played a crucial role in realizing Industry 4.0, where machines can communicate and interact in real-time. Despite these advancements, security remains a major challenge in developing and deploying smart manufacturing. As cyber-attacks become more prevalent, researchers are making security a top priority. Although IoT and Industrial IoT (IIoT) are used to establish smart industries, these systems remain vulnerable to various types of attacks. To address these security issues, numerous authentication methods have been proposed. However, many …

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Automatic Optical Inspection-Based Pcb Fault Detection Using Image Processing, Shruti Rajiv Vaidya Jan 2023

Automatic Optical Inspection-Based Pcb Fault Detection Using Image Processing, Shruti Rajiv Vaidya

Dissertations, Master's Theses and Master's Reports

Increased Printed Circuit Board (PCB) route complexity and density combined with the growing demand for low-scale rapid prototyping has increased the desire for Automated Optical Inspection (AOI) that reduces prototyping time and production costs by detecting defects early in the production process. Traditional defect detection method of human visual inspection is not only error prone but is also time-consuming given the growing complex and dense circuitry of modern-day electronics. Electric contact-based testing, either in the form of a bed of nails testing fixture or a flying probe system, is costly for low-rate rapid prototyping. An AOI is a non-contact test …

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Neuromorphic Computing Applications In Robotics, Noah Zins Jan 2023

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

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Novel Bayesian Neural Networks And Uncertainty Quantification Of Computational Mechanics Models, Ponkrshnan Thiagarajan Jan 2023

Novel Bayesian Neural Networks And Uncertainty Quantification Of Computational Mechanics Models, Ponkrshnan Thiagarajan

Dissertations, Master's Theses and Master's Reports

Computational and data-driven models suffer from a wide range of uncertainties that impact the reliability of such models. Given the exponential proliferation of machine learning models in real-world systems, establishing a degree of confidence in their predictions becomes paramount. Reliability in predictions takes on utmost significance in domains such as autonomous driving, medical image analysis, etc., where human lives are involved, and inaccuracies in predictions could lead to disastrous outcomes. For these reasons, comprehending and quantifying uncertainties in computational and data-driven models is of utmost importance. A number of techniques have been developed to quantify uncertainties in machine learning models. …

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Carrier Transport Engineering In Wide Bandgap Semiconductors For Photonic And Memory Device Applications, Ravi Teja Velpula Dec 2022

Carrier Transport Engineering In Wide Bandgap Semiconductors For Photonic And Memory Device Applications, Ravi Teja Velpula

Dissertations

Wide bandgap (WBG) semiconductors play a crucial role in the current solid-state lighting technology. The AlGaN compound semiconductor is widely used for ultraviolet (UV) light-emitting diodes (LEDs), however, the efficiency of these LEDs is largely in a single-digit percentage range due to several factors. Until recently, AlInN alloy has been relatively unexplored, though it holds potential for light-emitters operating in the visible and UV regions. In this dissertation, the first axial AlInN core-shell nanowire UV LEDs operating in the UV-A and UV-B regions with an internal quantum efficiency (IQE) of 52% are demonstrated. Moreover, the light extraction efficiency of this …

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Filtering Effect On Rssi-Based Indoor Localization Methods, Kwame S. Ibwe Dec 2022

Filtering Effect On Rssi-Based Indoor Localization Methods, Kwame S. Ibwe

Tanzania Journal of Engineering and Technology (TJET)

Indoor positioning systems are used to locate and track objects in an indoor environment. Distance estimation is done using received signal strength indicator (RSSI) of radio frequency signals. However, RSSI is prone to noise and interference which can greatly affect the accuracy performance of the system. In this paper Internet of Things (IoT) technologies like low energy Bluetooth (BLE), WiFi, LoRaWAN and ZigBee are used to obtain indoor positioning. Adopting the existing trilateration and positioning algorithms, the Kalman, Fast Fourier Transform (FFT) and Particle filtering methods are employed to denoise the received RSSI signals to improve positioning accuracy. Experimental results …

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A Genetic Algorithm Approach To Optimal Sizing And Placement Of Distributed Generation On Nigerian Radial Feeders, Adelowo Balogun Dec 2022

A Genetic Algorithm Approach To Optimal Sizing And Placement Of Distributed Generation On Nigerian Radial Feeders, Adelowo Balogun

Tanzania Journal of Engineering and Technology (TJET)

Mitigating power loss and voltage profile problems on radial distribution networks has been a major challenge to distribution system operators. While deployment of distributed generation, as compensators, has made a suitable solution option, optimum placement and sizing of the compensators has been a concern and it has thus been receiving great attention. Meta-heuristic algorithms have been found efficacious in this respect, yet the use of the algorithms in addressing problems of radial feeders is still comparatively low in Nigeria where analytical and numerical programming methods are common. Hence; the use of genetic algorithm to site and size distributed generator for …

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Evaluation Of Energy Efficiency Of Photoelectric Heat Batteries With Mechanism Of Solar Observation, M N. Tursunov, X Sabirov, I A. Yuldoshev, U R. Xolov Dec 2022

Evaluation Of Energy Efficiency Of Photoelectric Heat Batteries With Mechanism Of Solar Observation, M N. Tursunov, X Sabirov, I A. Yuldoshev, U R. Xolov

Technical science and innovation

Cooling of the rear surface of photoelectric batteries (PEB) was investigated by attaching a newly designed heat collector made of parallel channel cellular polycarbonate to the rear surface in order to improve the electrical and thermal efficiency in this research work. The experiment was conducted on June 7, 2022 at the Heliopolygon of the Physical-Technical Institute of Tashkent city (latitude: +41,34 (41°20'23"N), longitude: +69,3 (69°17'36"E). 2 340 W monocrystalline silicon PEBs(photoelectric batteries) were used as experimental devices. The rear surface of the first is equipped with a cooling …

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Efficiency Of Using Solar Collectors In Energy Saving And Saving Energy Resources, R R. Tillahodjaev, A A. Mirzayev Dec 2022

Efficiency Of Using Solar Collectors In Energy Saving And Saving Energy Resources, R R. Tillahodjaev, A A. Mirzayev

Technical science and innovation

Most manufacturers, suppliers and installers make only a rough calculation of solar collectors. The article goes step-by-step calculation, solar systems for heating, in order to fully provide the house with warmth in winter. Calculation of the real power of the solar collector. Calculation of the efficiency of the solar collector in the direction. Calculation of solar collector performance by installation angle. Features of flat panels. The performance of the vacuum manifold. How many solar collectors do you need to heat your home? Hot water connection.

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Solar Irradiance Forecasting Using A Novel Hybrid Deep Ensemble Reinforcement Learning Algorithm, Seyed Mohammad Jafar Jalali, Sajad Ahmadian, Bahareh Nakisa, Mahdi Khodayar, Abbas Khosravi, Saeid Nahavandi, Syed Mohammed Shamsul Islam, Miadreza Shafie-Khah, João P. S. Catalão Dec 2022

Solar Irradiance Forecasting Using A Novel Hybrid Deep Ensemble Reinforcement Learning Algorithm, Seyed Mohammad Jafar Jalali, Sajad Ahmadian, Bahareh Nakisa, Mahdi Khodayar, Abbas Khosravi, Saeid Nahavandi, Syed Mohammed Shamsul Islam, Miadreza Shafie-Khah, João P. S. Catalão

Research outputs 2022 to 2026

Solar irradiance forecasting is a major priority for the power transmission systems in order to generate and incorporate the performance of massive photovoltaic plants efficiently. As such, prior forecasting techniques that use classical modelling and single deep learning models that undertake feature extraction procedures manually were unable to meet the output demands in specific situations with dynamic variability. Therefore, in this study, we propose an efficient novel hybrid solar irradiance forecasting model based on three steps. In the first step, we employ a powerful variable input selection strategy named as partial mutual information (PMI) to calculate the linear and non-linear …

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An Accurate Real-Time Method For Face Mask Detectionusing Cnn And Svm, Shili Hechmi Dec 2022

An Accurate Real-Time Method For Face Mask Detectionusing Cnn And Svm, Shili Hechmi

Knowledge Engineering and Data Science

Infectious respiratory diseases, including COVID-19, pose a significant challenge to humanity and a potential threat to life due to their severity and rapid spread. Using a surgical mask is among the most significant safety precautions that can help keep this sort of pandemic from spreading, and manual monitoring of large crowds in public places for face masks is problematic. In this research, we suggest a real-time approach for face mask detection. First, we use a multi-scale deep neural network to extract features. As a result, the attributes are better suited for training the detection system. We employ SVM post-processing in …

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Hybrid Artificial Bee Colony And Improved Simulatedannealing For The Capacitated Vehicle Routing Problem, Farhanna Mar'i, Hafidz Ubaidillah, Wayan Firdaus Mahmudy, Ahmad Afif Supianto Dec 2022

Hybrid Artificial Bee Colony And Improved Simulatedannealing For The Capacitated Vehicle Routing Problem, Farhanna Mar'i, Hafidz Ubaidillah, Wayan Firdaus Mahmudy, Ahmad Afif Supianto

Knowledge Engineering and Data Science

Capacitated Vehicle Routing Problem (CVRP) is a type of NP-Hard combinatorial problem that requires a high computational process. In the case of CVRP, there is an additional constraint in the form of a capacity limit owned by the vehicle, so the complexity of the problem from CVRP is to find the optimum route pattern for minimizing travel costs which are also adjusted to customer demand and vehicle capacity for distribution. One method of solving CVRP can be done by implementing a meta-heuristic algorithm. In this research, two meta-heuristic algorithms have been hybridized: Artificial Bee Colony (ABC) with Improved Simulated Annealing …

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Adaptive Neuro-Fuzzy Inference System For Waste Prediction, Haviluddin Haviluddin, Herman Santoso Pakpahan, Novianti Puspitasari, Gubtha Mahendra Putra, Rima Yustika Hasnida, Rayner Alfred Dec 2022

Adaptive Neuro-Fuzzy Inference System For Waste Prediction, Haviluddin Haviluddin, Herman Santoso Pakpahan, Novianti Puspitasari, Gubtha Mahendra Putra, Rima Yustika Hasnida, Rayner Alfred

Knowledge Engineering and Data Science

The volume of landfills that are increasingly piled up and not handled properly will have a negative impact, such as a decrease in public health. Therefore, predicting the volume of landfills with a high degree of accuracy is needed as a reference for government agencies and the community in making future policies. This study aims to analyze the accuracy of the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The prediction results' accuracy level is measured by the value of the Mean Absolute Percentage Error (MAPE). The final results of this study were obtained from the best MAPE test results. The best …

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Indonesian Language Term Extraction Using Multi-Task Neural Network, Joan Santoso, Esther Irawati Setiawan, Fransiskus Xaverius Ferdinandus, Gunawan Gunawan, Leonel Hernandez Collantes Dec 2022

Indonesian Language Term Extraction Using Multi-Task Neural Network, Joan Santoso, Esther Irawati Setiawan, Fransiskus Xaverius Ferdinandus, Gunawan Gunawan, Leonel Hernandez Collantes

Knowledge Engineering and Data Science

The rapidly expanding size of data makes it difficult to extricate information and store it as computerized knowledge. Relation extraction and term extraction play a crucial role in resolving this issue. Automatically finding a concealed relationship between terms that appear in the text can help people build computer-based knowledge more quickly. Term extraction is required as one of the components because identifying terms that play a significant role in the text is the essential step before determining their relationship. We propose an end-to-end system capable of extracting terms from text to address this Indonesian language issue. Our method combines two …

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Associated Patterns In Open-Ended Concept Maps Within E-Learning, Didik Dwi Prasetya, Tsukasa Hirasama Dec 2022

Associated Patterns In Open-Ended Concept Maps Within E-Learning, Didik Dwi Prasetya, Tsukasa Hirasama

Knowledge Engineering and Data Science

A concept map is a diagram that visualizes the structure of individual cognitive knowledge. An approach to creating a concept map structure that allows users to contribute concepts and linkages that express their understanding freely is known as an "open-ended concept map." It has been demonstrated that an open-ended concept map accurately depicts student knowledge structures and reveals student differences. However, manually analyzing an open-ended map is difficult, time-consuming, and includes many propositions, especially in a big classroom. Educational data mining could be used to further process and analyze a collection of concept maps. However, many works attempted to employ …

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Autonomous Decision-Making In Interdependent Computing Systems Based On Artificial Intelligence, Georgios Fragkos Dec 2022

Autonomous Decision-Making In Interdependent Computing Systems Based On Artificial Intelligence, Georgios Fragkos

Electrical and Computer Engineering ETDs

With the advent of Artificial Intelligence (AI), the notion of autonomy, in terms of acting and thinking based on personal experience and judgment, has paved the way towards an autonomous decision-making future. This future can address the complex domain of the interdependent computing systems, whose main challenge is that they interact with each other with unpredictable and often unstable outcomes. It is crucial to envision and design this AI-driven autonomy for the reciprocal computing systems which cover a variety of use-cases ranging from the Internet of Things (IoT) to cybersecurity. This can be achieved by cloning the human decision-making process, …

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Advances On Composite Cathodes For Lithium-Sulfur Batteries, Xi-Yao Li, Chang-Xin Zhao, Bo-Quan Li, Jia-Qi Huang, Qiang Zhang Dec 2022

Advances On Composite Cathodes For Lithium-Sulfur Batteries, Xi-Yao Li, Chang-Xin Zhao, Bo-Quan Li, Jia-Qi Huang, Qiang Zhang

Journal of Electrochemistry

Lithium-sulfur (Li-S) batteries are deemed as high-promising next-generation energy storage technique due to their ultrahigh theoretical energy density, where the sulfur cathodes with high specific capacity guarantee the energy density advantage and directly determine the battery performances. After decades of exploration, the most promising sulfur cathodes are sulfur/carbon composite (S/C) cathodes and sulfurized polyacrylonitrile (SPAN) cathodes. In this manuscript, recent advances on S/C and SPAN cathodes in Li-S batteries are comprehensively reviewed. The electrochemical reaction circumstances on S/C and SPAN cathodes are firstly introduced and compared to reveal the working mechanisms of the two types of Li-S batteries. The S/C …

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Preparation Of Highly-Cyclized Sulfurized Polyacrylonitrile For Lithium-Sulfur Batteries, Xuan Ji, Jia-Yu Wang, An-Bang Wang, Wei-Kun Wang, Ming Yao, Ya-Qin Huang Dec 2022

Preparation Of Highly-Cyclized Sulfurized Polyacrylonitrile For Lithium-Sulfur Batteries, Xuan Ji, Jia-Yu Wang, An-Bang Wang, Wei-Kun Wang, Ming Yao, Ya-Qin Huang

Journal of Electrochemistry

Sulfurized polyacrylonitrile (SPAN) is regarded as an attractive cathode candidate of lithium-sulfur (Li-S) batteries for its non-dissolution mechanism and effective alleviation of polysulfides shuttling issue in Li-S batteries, displaying high utilization of cathode active material, outstanding cycle stability and structural stability. However, the relation between cyclization degree and cycle stability of SPAN is still unveiled. In this work, SPAN-C-V composites were synthesized by co-introduction of CuSO4 and zinc n-ethyl-n-phenyldithiocarbamate (ZDB) in the co-heating of sulfur and polyacrylonitrile. The co-introduction of CuSO4 and ZDB reduced the cyclization reaction onset temperature of PAN while increased the C—C/C=C within SPAN-C-V, thus …

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Carbon-Al Interface Effect On The Performance Of Ionic Liquid-Based Supercapacitor At 3 V And 65 OC, Zhen-Zhen Ye, Shu-Ting Zhang, Xin-Qi Chen, Jin Wang, Ying Jin, Chao-Jie Cui, Lei Zhang, Lu-Ming Qian, Gang Zhang, Wei-Zhong Qian Dec 2022

Carbon-Al Interface Effect On The Performance Of Ionic Liquid-Based Supercapacitor At 3 V And 65 OC, Zhen-Zhen Ye, Shu-Ting Zhang, Xin-Qi Chen, Jin Wang, Ying Jin, Chao-Jie Cui, Lei Zhang, Lu-Ming Qian, Gang Zhang, Wei-Zhong Qian

Journal of Electrochemistry

Ionic liquid (IL) electrolyte-based supercapacitors (SCs) have advantages of high operating voltage window, high energy density and nonflammability, as compared to conventional acetonitrile-based organic electrolyte SCs, and are typically suitable for the large-scale energy storage in the era of carbon neutrality full of renewable, but unstable electricity. However, current efforts were concentrated on the study with coin-cell type of IL-SCs, and less has been reported on the pouch type of IL-SCs for a long cycling time yet. To fabricate a reliable SC for the life time test or for the accelerated aging test under high temperature, one should concern the …

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Application Of Artificial Intelligence To Lithium-Ion Battery Research And Development, Zhen-Wei Zhu, Jing-Yi Qiu, Li Wang, Gao-Ping Cao, Xiang-Ming He, Jing Wang, Hao Zhang Dec 2022

Application Of Artificial Intelligence To Lithium-Ion Battery Research And Development, Zhen-Wei Zhu, Jing-Yi Qiu, Li Wang, Gao-Ping Cao, Xiang-Ming He, Jing Wang, Hao Zhang

Journal of Electrochemistry

Lithium-ion batteries (LIBs) have become one of the best solutions to the energy storage issue in modern society. However, the battery materials and device development are both complex, and involve multivariable problems. Traditional trial-and-error approach, which relies on researchers to conduct experiments, has encountered bottlenecks in the improvement of the battery performance. Artificial intelligence (AI) is the most potential technology to deal with this issue due to its powerful high-speed and capabilities of processing massive data. In particular, the capability of machine learning (ML) algorithms in assessing multidimensional data variables and discovering patterns in the sets are expected to assist …

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