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Articles 3091 - 3120 of 37154
Full-Text Articles in Electrical and Computer Engineering
Joint Time-Frequency Analysis: Taking Charge Penetration Depth And Current Spatial Distribution In The Single Pore As An Example, Nan Wang, Qiu-An Huang, Wei-Heng Li, Yu-Xuan Bai, Jiu-Jun Zhang
Joint Time-Frequency Analysis: Taking Charge Penetration Depth And Current Spatial Distribution In The Single Pore As An Example, Nan Wang, Qiu-An Huang, Wei-Heng Li, Yu-Xuan Bai, Jiu-Jun Zhang
Journal of Electrochemistry
In recent years, joint time-frequency analysis has once again become a research hotspot. Supercapacitors have high power density and long service life, however, in order to balance between power density and energy density, two key factors need to be considered: (i) the specific surface area of the porous matrix; (ii) the electrolyte accessibility to the intra-pore space of porous carbon matrix. Electrochemical impedance spectra are extensively used to investigate charge penetration ratio and charge storage mechanism in the porous electrode for capacitance energy storage. Furthermore, similar results could be obtained by different methods such as stable-state analysis in the frequency …
Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng
Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng
Journal of Electrochemistry
Redox potentials and acidity constants are key properties for evaluating the performance of energy materials. To achieve computational design of new generation of energy materials with higher performances, computing redox potentials and acidity constants with computational chemistry have attracted lots of attention. However, many works are done by using implicit solvation models, which is difficult to be applied to complex solvation environments due to hard parameterization. Recently, ab initio molecular dynamics (AIMD) has been applied to investigate real electrolytes with complex solvation. Furthermore, AIMD based free energy calculation methods have been established to calculate these physical chemical properties accurately. However, …
Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles
Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles
Journal of Electrochemistry
This study identifies, for the first time, critical calculation errors made by Nathan Lewis and his co-authors, in their study presented on May 1, 1989, at the American Physical Society meeting in Baltimore, Maryland. Lewis et al. analysed calorimetrically measured heat results in nine experiments reported by Martin Fleischmann and his co-authors. According to the Lewis et al. analysis, each of the experiments, where calculated for no recombination, showed anomalous power losses. When we used the same raw data, our corrected calculations indicate that each experiment showed anomalous power gains. As such, these data suggest the possibility of a new, …
Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool
Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool
Henry M. Rowan College of Engineering Departmental Research
Artificial intelligence and neuroscience have a long and intertwined history. Advancements in neuroscience research have significantly influenced the development of artificial intelligence systems that have the potential to retain knowledge akin to humans. Building upon foundational insights from neuroscience and existing research in adversarial and continual learning fields, we introduce a novel framework that comprises two key concepts: feature distillation and re-consolidation. The framework distills continual learning (CL) robust features and rehearses them while learning the next task, aiming to replicate the mammalian brain's process of consolidating memories through rehearsing the distilled version of the waking experiences. Furthermore, the proposed …
Reliability Improvement In The Traction System Of Tanzania Standard Gauge Railway, Yusufu Katuga
Reliability Improvement In The Traction System Of Tanzania Standard Gauge Railway, Yusufu Katuga
Tanzania Journal of Engineering and Technology (TJET)
In recent years, many African governments have been developing Standard Gauge Railway (SGR) to replace the old after becoming absolute, inefficient Meter Gauge System (MGR) to carry more loads at high mileage and speed while combating the oil and environmental crises. With the increase of SGR, the amount of traction systems has grown sharply, the service life of the traction system has increased gradually, and the components of the vehicle traction system have become worn and aged as a result. While Tanzania is transitioning to SGR with its gradually increasing traction systems, reliability improvement becomes a key for the sustainability …
Augmented Finite Control Set Mpc Design Technique For Wide Speed Range Control Of Permanent Magnet Synchronous Motor Drives, Francis Mwasilu
Augmented Finite Control Set Mpc Design Technique For Wide Speed Range Control Of Permanent Magnet Synchronous Motor Drives, Francis Mwasilu
Tanzania Journal of Engineering and Technology (TJET)
The effective motion control task is highly influencing the final drive performance in wide-range motor drives applications such as electric vehicles (EVs), washing machines, compressors, elevators and lathe machines. Recently, permanent magnet synchronous motor (PMSM) drive has been widely employed in these applications to achieve desired performances such as high efficiency, high torque requirements with minimum size “occupancy”. The PMSM drive features combining with these modern drive applications are highly nonlinear and the desired operation requirements demand high-performance control schemes with fast system response and robustness features. Linear control schemes are usually implemented to drive the PMSM that entail trade …
Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson
Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson
Dissertations
Our co-authored research ‘Steminism: Analyzing Factors That Improve Retention for Women as STEM Majors’ analyzed factors that contributed to the retention of women in science, technology, engineering, and mathematics (STEM) programs at Missouri University of Science & Technology (Missouri S&T). Women make up half of the US population, and while careers in (STEM) are an integral part of the US economy, women are underrepresented in these career fields. The purpose of our dissertation is to address the underrepresentation of women in STEM majors. Our methodology included homogeneous sampling to collect qualitative data. More specifically, we consulted with academic advisors and …
Pre‑Sizing Online Tool For Photovoltaic Water Pumping System: Development, Testing, Validation, And Evaluation, Sameh O. Abdellatif, Hani Ghali, Ibrahem Mohamed Mahmoud, Ahmed Hatem, Abdullah Hatem
Pre‑Sizing Online Tool For Photovoltaic Water Pumping System: Development, Testing, Validation, And Evaluation, Sameh O. Abdellatif, Hani Ghali, Ibrahem Mohamed Mahmoud, Ahmed Hatem, Abdullah Hatem
Electrical Engineering
No abstract provided.
Path And Strategy Of Pollution And Carbon Reduction By Digitization In Electric Power Enterprises, Xiaohong Chen, Runcheng Tang, Dongbin Hu, Xuesong Xu, Xiangbo Tang, Guodong Yi, Weiwei Zhang
Path And Strategy Of Pollution And Carbon Reduction By Digitization In Electric Power Enterprises, Xiaohong Chen, Runcheng Tang, Dongbin Hu, Xuesong Xu, Xiangbo Tang, Guodong Yi, Weiwei Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
With the extensive application and innovation of digital technology in the energy sector, digital technology has become increasingly crucial for the power industry to achieve the goal of reducing pollution and carbon emissions. How digital technology enables electric power enterprises to achieve this goal has attracted much attention. Firstly, the study analyzes the progress of digital technology applications in pollution reduction and carbon reduction in electric power enterprises. Then, it identifies the existing problems in the current application of digital technology in the power industry for reducing pollution and carbon emissions. Finally, it explores the potential ways and approaches of …
Analysis And Recommendations For Energy Conservation And Carbon Emission Reduction In Industry Boosted By Digital Energy Management Systems, Duanyang Geng, Tong Xu, Qinghua Zhu, Steve Evans
Analysis And Recommendations For Energy Conservation And Carbon Emission Reduction In Industry Boosted By Digital Energy Management Systems, Duanyang Geng, Tong Xu, Qinghua Zhu, Steve Evans
Bulletin of Chinese Academy of Sciences (Chinese Version)
Energy consumption during production processes in the industry is a main source of carbon dioxide emissions. Therefore, for China’s dual-carbon goals, industrial enterprises need to focus on reducing energy waste to achieve energy-efficient production, thereby effectively reducing carbon emissions in industrial production. In recent years, with the continuous development and popularization of digital technology, digital energy management systems have played a crucial role in energy saving by visualizing invisible energy in the industry. In this context, this study first analyses the current status of digital energy management system applications in the UK, the US, Germany, and Sweden, summarizes their characteristics …
Impact Of Chips And Science Act Of 2022 On China's Related Industries And Policy Suggestions, Jiuling Shi, Yongmiao Hong, Ying Liu
Impact Of Chips And Science Act Of 2022 On China's Related Industries And Policy Suggestions, Jiuling Shi, Yongmiao Hong, Ying Liu
Bulletin of Chinese Academy of Sciences (Chinese Version)
As the cornerstone of modern information technology, chips are the strategic commanding heights of competition game and industrial development of countries all over the world. In recent years, the United States has taken advantage of its technological advances to successively introduce chip laws against China, which seriously violates the laws of market economy and has a significant impact on the global semiconductor industry chain. This study first sorts out the development pattern of the global semiconductor industry, and then introduces the background, content and purpose of CHIPS and Science Act of 2022. Then, it analyzes the impact of the …
A Systematic Survey On 5g And 6g Security Considerations, Challenges, Trends, And Research Areas, Paul Scalise, Matthew Boeding, Hamid Sharif, Joseph Delloiacovo, John Reed
A Systematic Survey On 5g And 6g Security Considerations, Challenges, Trends, And Research Areas, Paul Scalise, Matthew Boeding, Hamid Sharif, Joseph Delloiacovo, John Reed
Department of Electrical and Computer Engineering: Faculty Publications
With the rapid rollout and growing adoption of 3GPP 5thGeneration (5G) cellular services, including in critical infrastructure sectors, it is important to review security mechanisms, risks, and potential vulnerabilities within this vital technology. Numerous security capabilities need to work together to ensure and maintain a sufficiently secure 5G environment that places user privacy and security at the forefront. Confidentiality, integrity, and availability are all pillars of a privacy and security framework that define major aspects of 5G operations. They are incorporated and considered in the design of the 5G standard by the 3rd Generation Partnership Project (3GPP) with the goal …
Wireless Power Transfer Using Electronic Textiles: A Comparative Review, Showrov Rahman, Marjan Al Haque, Mohammad Solaiman, Rashed Hasan Ratul, Istiak Ahmed, Shawana Tabassum, Izabela Ciesielska-Wrobel
Wireless Power Transfer Using Electronic Textiles: A Comparative Review, Showrov Rahman, Marjan Al Haque, Mohammad Solaiman, Rashed Hasan Ratul, Istiak Ahmed, Shawana Tabassum, Izabela Ciesielska-Wrobel
Electrical Engineering Faculty Publications and Presentations
Wireless power transfer (WPT) has already been established as a popular technology in multiple areas such as electric vehicle charging, smartphone charging, or powering bio-medical implants. In recent years, wireless power transfer in electronic textiles (e-textiles) or smart textiles has seen rapid growth with the advancement of textile materials and flexible electronic components. Although many reviews and surveys on WPT can be found in the literature for other popular fields, this is not the case for the application of WPT in e-textiles. To address this issue, a comparative review of previous literature on WPT in e-textiles is presented in this …
Power Allocation For Next Generation Iot Systems Using Cnoma, Srikamu C
Power Allocation For Next Generation Iot Systems Using Cnoma, Srikamu C
Theses and Dissertations
The global Pandemic/COVID-19 keeps people connected through wireless commu- nication. The tremendous growth of mobile data traffic and an increase in massive IoT connectivity among different devices leads to a scarcity of wireless resources. One of the advancing technologies for the 5G Beyond communication network, Non-Orthogonal Multiple Access (NOMA), is used for M2M, V2V, and connecting low-power IoT devices. NOMA outperforms OMA schemes such as FDMA, TDMA, CDMA, and OFDMA of 1G, 2G, 3G, and 4G in terms of data rate, latency, and spectral efficiency. NOMA exploits the multiplexing of signals in the power domain with the same frequency/time, and …
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Dissertations and Theses
This thesis outlines the design of an IQ Test Bench that allows for experimentation of quadrature modulation techniques. Quadrature modulation utilizes two signals I and Q, 90° out of phase from each other, to greatly increase communication data rates. Using Desmos, a thorough mathematical analysis of waveform mixing is presented, and constellation diagrams are plotted from the results. From this an ancient fire signaling technique known as the Polybius Square is encoded into the system. The IQ Test Bench is built from fundamental components that would be contained within an RFFE: a local oscillator and two frequency mixers. The LO …
Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk
Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …
Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu
Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …
Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan
Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Turkish Journal of Electrical Engineering and Computer Sciences
It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Turkish Journal of Electrical Engineering and Computer Sciences
Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …
Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim
Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …
A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran
A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …
Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu
Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …
Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi
Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi
Turkish Journal of Electrical Engineering and Computer Sciences
In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …
Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu
Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …
Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy
Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy
Turkish Journal of Electrical Engineering and Computer Sciences
Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …
Multimode Point Spectroscopy For Food Authentication, Sayed Asaduzzaman, Nicholas Mackinnon, Hossein Kashani Zadeh
Multimode Point Spectroscopy For Food Authentication, Sayed Asaduzzaman, Nicholas Mackinnon, Hossein Kashani Zadeh
SDSU Data Science Symposium
Enhancing food quality measurement is a necessity to guarantee food safety and adherence to health regulations. Current methods involve lab testing which are time-consuming, costly, destructive and require skilled workers. Spectroscopy has the potential to overcome these challenges. This study employs a multi-mode point spectroscopy method to distinguish food products according to their spectral characteristics,. The system records fluorescence, excited at 365 and 405 nm, visible-near infrared (Vis-NIR) and short-wave infrared (SWIR) spectra. The three main subjects of the study are olive oil, milk, and honey. Samples were kept in a transparent cell culture pot, and Gray and White Spectralon …
Buckling Behavior Of Thin Wall Stiffened Cylindrical Shells Through Ml Techniques, Fnu Tabish, Muhammad Hamza Karim, Rajesh Godasu, Iraj H.P Mamaghani
Buckling Behavior Of Thin Wall Stiffened Cylindrical Shells Through Ml Techniques, Fnu Tabish, Muhammad Hamza Karim, Rajesh Godasu, Iraj H.P Mamaghani
SDSU Data Science Symposium
Stiffened cylindrical shell buckling strength mainly depends on the geometric and stiffness properties. A detailed parametric study was conducted to investigate the influence of these properties on the stiffened aluminium cylindrical shell buckling strength. The proposed framework involves an integration of finite element method and various machine learning techniques. The dataset obtained from the eigenvalue buckling analysis of 350 numerical simulations using ANSYS workbench 2022; however, the FE simulation of ten ring-stiffened cylindrical specimens was initially substantiated by experimental work conducted in the literature. 350 sample specimens were categorized into seven groups based on the no. of stiffeners varying from …