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Determinants of Electric Vehicle Adoption and Integration with Public Transportation through Park-and-Ride

Determinants of Electric Vehicle Adoption and Integration wi...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Mulham Fawakherji Driss Benhaddou Bruce Race Bryan. Carrollia Wilfredo. Santamaria Dep. Computer Engineering Technology University of Houston Houston USA Dep. of Electrical Engineering College of Engineering Alfaisal University Riyadh SA College of Architecture and Design University of Houston Houston USA Metropolitan Transit Authority of Harris County Houston USA

The rise of Electric Vehicles (EVs) has presented a promising solution to the environmental and resource challenges posed by conventional combustion engine vehicles. With their potential to significantly reduce greenhouse gas emissions and enhance air quality, the adoption of EVs is essential for a more sustainable future. However, despite their benefits, widespread adoption remains limited. Thus, understanding the key factors that impact consumer adoption is crucial for promoting their use. This study aims to identify and analyze the various determinants that influence EV adoption, including social and demographic, political, economic, technological, and environmental factors. The findings offer valuable insights into the most significant barriers to EV adoption and provide potential strategies to encourage their use. Furthermore, this study examines the feasibility and sustainability of integrating EVs with public transportation via park-and-ride stations, emphasizing the importance of promoting sustainable transportation given the continued reliance on personal vehicles for park-and-ride travel.

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Logistic Regression Classification for Assessing the Risk of Kidney Tumor

Logistic Regression Classification for Assessing the Risk of...

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Electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Dalia Alzu'bi Rabia Emhamed Al Mamlook Ahmad Nasayreh Mohammad Aljaidi Rami AlAzab Hasan Gharaibeh Qais Al-Na'amneh Dep. Information and Systems Engineering Concordia University Montreal Canada Dep. of Business Administration Trine University Indiana USA Department of Industrial Engineering University Zawia Tripoli Libia Dep. Computer Science Yarmouk University Irbid Jordan Dep. of Computer Science Zarqa University Zarqa Jordan Dep. Surgery and Urology Jordan University of Science and Technology Irbid Jordan Dep. of Cyber Security Applied Science Private University Amman Jordan

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

The kidneys have the important function of filtering waste products and toxins from the blood in the human body. Any problems affecting the kidneys can potentially impact their efficiency and overall function. Kidney Tumor (KT) is a disease that specifically affects kidney cells and causes the abnormal growth of tissue in one or both kidneys. Assessing the risk of developing a kidney tumor and identifying the key factors that contribute to this risk are crucial for ensuring patient well-being. Additionally, this information assists doctors and specialists in making faster and more accurate diagnoses, determining appropriate treatment methods, and potentially influencing the course of the disease to minimize its severity and impact. Machine learning algorithms have recently been introduced to evaluate disease risks, and in this study, we specifically focus on examining the risk of kidney tumor development and investigating the influencing factors. We employed a logistic regression model to predict if a patient is at risk of developing a kidney tumor or not, and further categorized the samples into high-risk and low-risk groups. Our model was trained and tested using a unique dataset obtained from the (KAUH) hospital in Jordan, consisting of well-balanced metadata from 120 patients with kidney issues. Our work demonstrated accuracy results ranging from 90% to 98%. Ultimately, specialists can utilize our model as an additional tool to enhance the speed and accuracy of patient diagnoses

关键词： Logistic regression Analytical models Accuracy Predictive models Genetics History Reliability

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The Correlation Between Architecture Smells, Package Stability and Reusability: A Case Study

The Correlation Between Architecture Smells, Package Stabili...

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Sciences and Techniques of Automatic Control and computer engineering MI-STA, IEEE International Maghreb Meeting of the Conference on

作者： Mrwan BenIdris Ehab A. Omar Elfallah Marwa Aslam Cheema Mohammed Salah Addin Alsma Tareq Ziad Kadiki Abdelfattah Elbarsha Dep. of Computer Science Faculty of Information Technology University of Benghazi Dept. of Software Engineering Faculty of Information Technology Libyan International Medical University Health Informatics Department Faculty of Public Health University of Benghazi

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. Architecture smells (ASs) can be used to identify any quality issues within the system. To further explore the relationships between ASs, stability, and reusability, Spearman correlation coefficients will be calculated. This paper seeks to examine the connection between architecture smells, software stability, and reusability. To do this, we utilized a dataset created by other researchers and conducted an empirical study of the associations between five types of architecture smells and software stability and reusability. This research is necessary as there is a lack of in-depth research on architecture smells and their relationship to software stability and reusability. We found a relationship between the presence of Feature Concentration in package and the stability and reusability of the package. Also, package's stability is affected by both Cyclic dependency and Unstable dependency. A slight positive correlation has been found between God Class and stability, as well as a very weak negative correlation between Unstable dependency and reusability. Finally, we found a slight negative correlation between package stability and reusability.

关键词： Correlation coefficient Correlation Codes Conferences computer architecture Software systems Software development management

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Predictive Maintenance of Power Transformers in Distribution Network with Energy Management Using Deep Learning

Predictive Maintenance of Power Transformers in Distribution...

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Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： Pooja Pande K Hussain B Pravallika Mohammed Saleh Al Ansari R.M. Tharsanee Srinivasa Acharya Department of Information Technology Yeshwantrao Chavan College of Engineering Nagpur Maharashtra India Department of EE Sharad Institute of Technology College of Engineering Ichalkaranji Kolhapur Maharashtra Institute of Aeronautical Engineering Hyderabad College of Engineering Dep artment of Chemical Engineering University of Bahrain Bahrain Department of Computer science and engineering Bannari Amman Institute of Technology Sathyamangalam Erode Electrical and Electronics Engineering Department Aditya Institute of Technology and Managemnt Tekkali Andhra Pradesh India

The reliability and efficiency of the electrical grid network are obtained through proper maintenance of the power transformers. The advanced maintenance of the electrical grid is obtained through modern strategies to enhance the performance of the system. Power transformers are an important part of the electrical distribution systems. Failure of transformers leads to various constraints regarding service interferences with costly outrages. Traditional forms of maintenance rely on manual inspections on fixed timelines which is not able to detect the transformer degradation at early stages. Advanced predictive maintenance with energy management is obtained through deep learning techniques with hybrid optimization techniques. This includes Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). This is done through various sensors and monitoring equipment placed in the distribution network. The extraction of spatial and temporal data from images is obtained through the CNN component. The hidden defects and abnormal functioning of various parts in the transformer are detected through CNN. Oil leakages, overheating and insulation failure are the early signs of transformer failures. The RNN component concentrates on the data generated by sensors and meters in real-time environment. This helps to predict the future demand for power transformers. The sequential patterns are obtained through the LS TM component. They provide accurate details regarding the performance and life of transformers. The integration of energy management with predictive maintenance helps optimise power utility while maintaining the reliable operation of transformers.

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computer Vision and Image Processing the Challenges and Opportunities for new technologies approach: A paper review 3

Computer Vision and Image Processing the Challenges and Oppo...

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3rd International Scientific Conference of engineering Sciences and Advances Technologies, IICESAT 2021

作者： Hussien, Reem M. Al-Jubouri, Karrar Q. Gburi, Mohaimen Al Hussein Qahtan, Al Gburi Duaa Jaafar, Al Hamami Department of Civil Engineering Al-Farabi University College Baghdad Iraq Department of Production Engineering and Metallurgy University of Technology Iraq Dep of Electrical and Computer Engineering Altinbaş University Istanbul Turkey Administrative Affairs ID Dep Ministry of Education Baghdad Iraq

Digital image processing has numerous applications in many sectors of the world. It expands from initial information registration into methods and thoughts combining pattern recognition, computer vision, and machine learning. The wide utilization has pulled in many researchers to integrate with a range of related specializations. This work gives a study of the latest development and theoretical ideas clarifying an improvement of computer vision particularly with pattern recognition and image processing, utilizing various regions of their field implementation. Digital image processing causes researchers to analyze images to get important data and comprehend information. It utilized a technique of multi-range implementation and huge information analysis. This work aims to focus on the latest studies related to image processing, pattern recognition, and computer vision. In this paper, computer vision standard has been categorized into groups. For example, pattern recognition, image processing, and AI. Additionally, we give a short clarification of the forward-thinking data about the methods and their realization. This survey is restricted to computer vision, and more research can include detecting the conduct and properties of the object including people actions. © Published under licence by IOP Publishing Ltd.

关键词： computer vision

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A Multivariate Functional Analysis of Inter-Hands Spatiotemporal Coordination in Human Bimanual Tasks and its Implications for Robotics

A Multivariate Functional Analysis of Inter-Hands Spatiotemp...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Marco Baracca Andre Meixner Giuseppe Averta Paolo Salaris Tamim Asfour Matteo Bianchi Dept. of Information Engineering Research Center “E. Piaggio” University of Pisa Pisa Italy Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Dep. of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Dual-arm manipulation is a key enabler for significantly enhancing the interaction between humans and robots, and their capabilities to purposefully shape the surrounding environment. However, the spatiotemporal coordination between the motion of the hands required for this type of actions makes their planning not trivial. A proper definition of these coordination patterns moving from the human example could simplify their translation on the robot side, fostering the generation of effective bimanual tasks. In this work, we propose Multivariate functional Principal Component Analysis (MfPCA) as a mathematical tool to encode inter-hands temporal kinematic covariations in terms of principal spatiotemporal coordination patterns in the Cartesian domain. We compared these patterns extracted from a dataset of human bimanual tasks with those resulting from the usage of classical fPCA, applied independently to each hand (univariate fPCA). We found that MfPCA allows for a better classification of the tasks, with respect to a state of the art taxonomy. For what concerns motion planning, MfPCA and fPCA yield similar accuracy in the reconstruction of the motion, but with a smaller number of principal components needed in the MfPCA case. These results, although preliminary, can open interesting perspectives for the usage of MfPCA for human-like bimanual motion planning and control of robotic manipulators, as well as for action recognition, to enable a more effective human-robot interaction.

关键词： Hands Translation Shape Robot kinematics Taxonomy Human-robot interaction Functional analysis Planning Spatiotemporal phenomena Principal component analysis

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Image Encryption using Chaotic Techniques: A Survey Study

Image Encryption using Chaotic Techniques: A Survey Study

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2021 International Conference in Advances in Power, Signal, and Information technology, APSIT 2021

作者： Ayad, Jenan Hasan, Fadhil Sahib Ali, Alaa H. Hussein, Zaid Khudhur Abdulkareem, Hanan J. Jalil, Mustafa A. Ahmed, Ghaidaa Sadiq, Ahmed University of Technology Electrical Engineering Dep. Baghdad Iraq Electrical Engineering Dep. Mustansiriyah University Baghdad Iraq Technical Engineering Al-Esraa University College Medical Instrumentation Baghdad Iraq Al-Esraa University College Computer Technical Engineering Baghdad Iraq

ISBN: (纸本)9781665425063

The sharing of information through unsecured networks like the internet has increased fast recently. This information could be text, audio, image, or video. The security of data transmission is an essential issue. Encryption is one of the most effective techniques to assure safe data transmission. Videos and Images size are very large and have a high correlation between neighboring pixels, so the classical encryption techniques such as RSA, DES, AES, etc., cannot be utilized for image encryption while chaotic image encryption schemes, which use a high level of unpredictability in key generation, can solve this problem. The chaos encryption main properties are pseudorandom number, sensitivity to initial conditions, and large key size. The goal of this study was to find the best chaotic map for picture encryption, this research looks into the use of chaos maps for image encryption, such as the Tent map, Logistic map, Sine map, and others. Arnold's Cat map, and also presents a comparison for their performance. © 2021 IEEE.

关键词： Data transfer

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Secure Images Transmission Through OFDM System

Secure Images Transmission Through OFDM System

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Computing and Machine Intelligence (ICMI), International Conference on

作者： Jenan Ayad Ahmed Sadiq Basma Makki Zainab Ali Abbood Hanan j. Abdulkareem Zaid Khudhur Hussein Computer Technology Engineering dep Al-Esraa University College Baghdad Iraq Medical Instrumentation Technical Engineering dep. Al-Esraa University College Baghdad Iraq

ISBN: (数字)9781665474832

ISBN: (纸本)9781665474849

OFDM (Orthogonal Frequency Division Multiplexing) Next-generation wireless communication networks rely heavily on the OFDM system to transmit digital information in a more effective method as well as other traditional methods. Using mobile devices, digital document data such as videos, images, and texts can be easily shared and copied without the owner's permission. In this case, information security is a primary consideration. There are several advantages to using chaotic systems, such as their randomness, which makes them far more secure than traditional encryption methods, such as RSA (AES, DES). An efficient method for transmitting secure images across an AWGN channel has been developed because of this research. The dual-sided encryption and scrambling method for an OFDM system proposed in this paper is described in detail. Here, MATLAB is used to design an OFDM system that employs high-efficiency scrambling and a chaotic map for encryption to achieve high-security image transfer. Signal to noise ratio as well as bit error rate measurements are utilized to gauge the clear of image transmission. Using entropy, histogram analysis, NPCR, and UACI for testing encryption quality.

关键词： Wireless communication Chaotic communication OFDM Image communication System performance Encryption Noise measurement

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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Electronic engineering (ICEEM), International Conference on

作者： Mahmoud Elshabrawy Marwa M. Eid Abdelaziz A. Abdelhamid El-Sayed M. El-Kenawy Abdelhameed Ibrahim Dept. of Communications & Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt Faculty of Artificial Intelligence Delta University for Science and Technology Mansoura Egypt Dep. of Computer Science Faculty of Computer and Information Sciences Ain Shams University Cairo Egypt Computer Engineering and Control Systems Dept. Faculty of Engineering University Mansoura Egypt

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models.

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Optimization of Dualband Microstrip mm-Wave Antenna with Improved Directivity for Mobile Application Using Genetic Algorithm 9th

Optimization of Dualband Microstrip mm-Wave Antenna with Imp...

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9th EAI International Conference on Advancement of Science and technology, ICAST 2021

作者： Dejen, Arebu Jayasinghe, Jeevani Ridwan, Murad Anguera, Jaume School of Electrical and Computer Engineering Addis Ababa University Addis Ababa Ethiopia Department of Electronics Wayamba University of Sri Lanka Kuliyapitiya Sri Lanka Technology and Intellectual Property Rights Dep’t Fractus Antennas Barcelona Spain Telecommunication Engineering Unversitat Ramon LLull Barcelona Spain

ISBN: (纸本)9783030937089

The demand of high data rate requirement and spectrum scarcity in the current wireless communication drives the next generation communication technology to mm-wave frequencies. Researches in directivity improvement and multi-functionality of antenna are the determinant factor to provide high data rate and quality of services. This research discourses directivity optimization of a single microstrip rectangular patch antenna with dualband service for mm-wave mobile communication using binary-coded genetic algorithm. Optimization has been done by dividing the patch geometry into 100 small circular cells and assigning them as conducting and none conducting. The proposed antenna was iteratively simulated using a combination of HFSS and MATLAB, and obtained S11 © 2022, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Microstrip antennas

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