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Energy, Materials and Communication engineering (ICEMCE), International Conference on

作者： Sarathkumar D Srinivasan Murugesan P Sukumar Raymon Antony Raj Sampath Kumar Venkatachary Leo John Baptist Andrews Dishore Shunmugham Vanaja Department of Electrical and Electronics Engineering Kongu Engineering College Tamilnadu India Department of Computer Science and Engineering Nandha Engineering College (Autonomous) Erode Tamilnadu Grant Thornton Gaborone Botswana Department of Information Technology Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Electrical and Electronics Engineering MarBaselios College of Engineering and Technology Thiruvananthapuram Kerala India

Today, the Internet of Things (IoT) technique is applied in a variety of study fields to observe, collect, and analyze data from remote locations. The quality of water has significantly declined as a result of the massive increase in global industrial output, the move from rural to urban areas, and the over exploitation of land and marine resources. Impurities can be found in the dying chamber's output water. Repeatedly, the same water is controlled in the ETP chamber and fed to the death chamber. The impact of the various physical water contaminations created during the hydrologic cycle and/or bacterial colonization relies on the unique circumstances of the water consumer. The different contaminants must be identified and calculated in order to examine the demand for treatment and the suitable technology. The most common application of qualitative differentiating is to describe the aesthetic or visual quality of water. Water that is turbid contains suspended particles that give it a murky look. These particles scatter and submerge light, giving the impression of clouds. Organic or inorganic particles may be suspended. The pH of a fluid is used to determine its relative acidic or basic level. Calculating the hydrogen ion concentration in water results in pH. For the additional treatment step, the waste water's temperature is measured. The degree of pollution present in the waste water can be identified and appropriately handled by measuring the pH, turbidity, temperature, and humidity.

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A New Hybrid Approach Cluster-Heads Election to reduce the number of clusters in VANETs 5

A New Hybrid Approach Cluster-Heads Election to reduce the n...

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5th International Conference on engineering Technology and its Applications, IICETA 2022

作者： Abbas, Ali Hashim Abdulsattar, Nejood Faisal Mansour, Hassnen Shakir Mutar, Mohammed Hasan Habelalmateen, Mohammed I. Audah, L. Alduais, N.A.M. Mohammed, Admen College of Information Technology Imam ja'Afar Al-Sadiq University Department of Computer Technical Engineering Al-Muthanna 66002 Iraq Engineering College of Technical Engineering Islamic University Department of Computer Technical Najaf54001 Iraq Faculty of Electrical and Electronic Engineering Batu Pahat Malaysia Parit Raja Malaysia Al-Farahidi University Medical Technical College Baghdad Iraq

ISBN: (纸本)9781665472159

Vehicular Ad-hoc Networks (VANETs) is a subpart from mobile Ad-hoc networks (MANETs). The main idea from VANETs is to establish communication between vehicles for the safety of the people. However, mobility of vehicles appears to be the main challenge in VANETs. High speed of vehicles causes topology changed that results in an unstable network. Therefore, clustering is used to reduce the effect of vehicle mobility by combining vehicles in a group called cluster. Network stability is based on clusters stability. Therefore, most of the authors focused on increasing cluster stability to enhance the network. Nevertheless, increasing the number of the cluster in the network affects the network performance negatively. This paper proposes a new method called Hybrid Cluster-Head Election (HCHE) to reduce the number of the cluster in the network to increase network performance. Performance of the proposed method was evaluated through simulation by utilising real-time datasets. Arduino, GPS and external antennas were used to collect real GPS locations from Batu Pahat City - Johor - Malaysia. Overall, the proposed method resulted high performance in the reduction ratio of the number of cluster head compared to other recent methods. The proposed method successfully reduced the number of cluster heads by 30%. © 2022 IEEE.

关键词： Stability

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Design and Implementation of Needle Steering System 11

Design and Implementation of Needle Steering System

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11th IEEE International Conference on control System, Computing and engineering, ICCSCE 2021

作者： Shaaban, Abdel-Salam Ali, Ahmed S. Mostafa, R. El-Samie, Fathi E. Abd Beni-Suef University Faculty of Technology and Education Department of Process Control Technology Egypt Assuit University Faculty of Engineering Department of Mechanical Engineering Egypt Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Engineering Menouf32952 Egypt

ISBN: (纸本)9781665412810

The insertion of a needle for many scientific researches is an important aspect to consider and is the simplest and most diagnostic of the medical and interventional procedures. In needle based medical procedures, a flexible needle is directed at the soft tissue to achieve a predefined target position. The efficiency of the needle insertion depends on the precise control of the tip of the needle. This article provides a complete mechanical model for inserting needles into soft tissues. The proposed needle insertion model depends on the insertion speed as the input, which can then be used as a needle direction control. The model considers the length of needle and bevel angle. Various experiments were performed that inserts a needle into biological tissue. The results show the accuracy of the proposed system at different application speeds with an error of up to 2 mm. © 2021 IEEE.

关键词： Needles

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Applied ARMA process as current filter for VFD application 4

Applied ARMA process as current filter for VFD application

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4th IEEE International Conference and Workshop in Obuda on electrical and Power engineering, CANDO-EPE 2021

作者： Bensic, Tin Varga, Toni Barukcic, Marinko Stil, Vedrana Jerkovic Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Department of Electromechanical Engineering Osijek Croatia

ISBN: (纸本)9781665420235

The paper proposes the application of ARMA time series model to VFD (variable frquency drive) current filtering. The problem is examined on measured currents of an induction motor driven by comercial frequency converter. The currents are filtered by adaptive ARMA time series model structured as a band-pass filter. The adaptation is realized through recursive least squares regression. © 2021 IEEE.

关键词： Induction motors

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Streamlining Attendance with Voice Recognition via Gaussian Mixture Model

Streamlining Attendance with Voice Recognition via Gaussian ...

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IT and Industrial Technologies (ICIT), International Conference on

作者： Noor Ali Khadija Ali Fatimah Ali Aaminah Ali Nisar Ali Raja Hashim Ali A-Levels Lahore Pakistan Department of Software Engineering NUST College of Electrical and Mechanical Engineering Islamabad Pakistan Faculty of Engineering and Applied Science University of Regina Regina Canada Department of Artificial Intelligence Faculty of Computer Science & Engineering GIK Institute of Engineering Sciences & Technology Topi Pakistan Department of Business University of Europe for Applied Sciences Potsdam Germany

ISBN: (数字)9798331504465

ISBN: (纸本)9798331504472

Voice recognition systems are crucial because they allow seamless human-computer interaction and improve accessibility for users of all abilities. The use of these technologies in hands-free control, language translation, virtual assistants, transcription services, and hands-free control is revolutionising how we engage with technology and enhancing convenience and productivity in general. Several attendance systems based on voice recognition exist, but we wanted to deploy an attendance system with a good graphical user interface specifically for students of GIK Institute. For this purpose, we wanted to make a user-friendly and accurate voice recognition system based and trained on self-provided data of ten students. This study introduces an AI-driven attendance system, which demonstrates high efficiency and accuracy in identifying students’ daily class attendance. To achieve this, the Gaussian Mixture Model approach was employed. The paper also delves into the utilization of libraries and methods, encompassing the training and validation of well-known machine learning models. Additionally, the system’s performance, its strengths, weaknesses and potential areas for improvement are also discussed in the study.

关键词： Biometrics Training Accuracy Translation Virtual assistants Speech recognition Transforms Security Gaussian mixture model Graphical user interfaces

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Probabilistic analysis of arithmetic coding showing its robustness

arXiv

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arXiv 2025年

作者： Mahmoud, Hosam M. Rivertz, Hans J. Department of Statistics The George Washington University WashingtonDC20052 United States Department of Computer Science Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Norway

We probabilistically analyze the performance of the arithmetic coding algorithm under a probability model for binary data in which a message is received by a coder from a source emitting independent equally distributed bits, with 1 occurring with probability p ∈ (0, 1) and 0 occurring with probability 1 − p. We establish a functional equation for the bivariate moment generating function for the two ends of the final interval delivered by the algorithm. Via the method of moments, we show that the transmitted message converges in distribution to the standard continuous uniform random variable on the interval [0,1]. It is remarkable that the limiting distribution is the same for all p, indicating robustness in the performance of arithmetic coding across an entire family of bit distributions. The nuance with p appears only in the rate of convergence. Copyright © 2025, The Authors. All rights reserved.

关键词： Probability distributions

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Improving DeepFake Video Detection Performance with a Noval Deep Learning Approach

Improving DeepFake Video Detection Performance with a Noval ...

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Electronic engineering (ICEEM), International Conference on

作者： Mona A. Fouda Walid El-Shafai El-Sayed M. El-Rabaie Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Computer Science Department Security Engineering Lab Prince Sultan University Riyadh Saudi Arabia

With the rise in both the quantity and sophistication of deepfake videos, the need for robust detection systems to identify potentially misleading content on social media and the internet has become paramount. However, current automated face forgery detection systems still face limitations, often demonstrating bias towards the training dataset. This research paper addresses this issue by proposing a novel approach for detecting deepfake media. We introduce a custom Visual Geometry Group (VGG16) deepfake detection method that leverages convolutional neural network architectures. To evaluate the effectiveness of our approach, we utilize the deepfake detection challenge (DFDC) dataset on Kaggle to build network models and compare the performance of our custom VGG16 method against the standard VGG16. Additionally, we investigate the impact of data augmentation techniques on the performance of Convolutional Neural Network (CNN)-based deepfake detectors, examining their effect on both VGG16 and our custom VGG16 approach using the DFDC dataset. Our results demonstrate a high level of accuracy, with precision, recall, and f1-score values of 0.983, 0.975, and 0.979, respectively, and an overall accuracy of 0.986 for deepfake detection. This study presents a promising approach to enhance the accuracy of deepfake video detection, representing a crucial step towards mitigating the potential negative impacts of deepfake technology.

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Multivariate Dependence Modeling of Electric Vehicle Charging Stochastic Parameters

Multivariate Dependence Modeling of Electric Vehicle Chargin...

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Smart Grid Conference (SGC)

作者： Payam Farhadi Seyyed Masoud Moghaddas Tafreshi Amir Shahirinia Department of Electrical Engineering Faculty of Engineering University of Guilan Rasht Iran Department of Electrical and Computer Engineering University of the District of Columbia Washington D.C. USA

ISBN: (数字)9798350333961

ISBN: (纸本)9798350333978

Electric vehicles are considered a sustainable mode of terrestrial transport worldwide because of low- or zero-carbon emissions. Public charging stations, particularly fast and extra fast, play a crucial role in adopting and developing electric vehicles. To enable optimum planning of the fast charging stations, multivariate dependence of electric vehicle charging variables regarding stochastic nature should be taken into account. This paper uses multiple Elliptical and Archimedean copula functions to model the correlation/dependency between the electric vehicle charging characteristic parameters. Typically, by employing the multivariate copulas, synthetic electric vehicle charging data or observations are effectively generated for accurate simulation of multiple theoretical and practical applications, such as planning electric vehicle charging infrastructures while handling inherent variability and complex dependencies of electric vehicle charging characteristic parameters. Simulations are carried out in R.

关键词： Stochastic processes Charging stations Electric vehicle charging Data models Planning Smart grids

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An Enhanced DFFNN for Location-Based Services of Indoor Device-Free Submissive Localization 5

An Enhanced DFFNN for Location-Based Services of Indoor Devi...

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5th International Conference on Information Technology for Education and Development, ITED 2022

作者： Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Bhoi, Akash Kumar Jimoh, Rasheed Gbenga Ojo, Stephen Panigrahi, Ranjit Faruk, Nasir University of Ilorin Faculty of Communication and Information Sciences Department of Computer Science Ilorin Nigeria University of Lagos Department of Electrical and Electronics Engineering Nigeria Institute of Digital Communication Ruhr University Department of Electrical Engineering and Information Technology Bochum44801 Germany Sikkim Manipal University Directorate of Research Sikkim Gangtok737102 India Sambalpur Burla768018 India Anderson University Department of Electrical and Computer Engineering AndersonSC29621 United States Sikkim Manipal Institute of Technology Department of Computer Applications Sikkim Manipal University Sikkim Majitar737136 India Sule Lamido University Department of Physics Nigeria SLU Directorate of ICT Nigeria

ISBN: (纸本)9781509064229

With no associated devices, device-free localization (DFL) uses wireless sensor networks to find a target. DFL has created comprehensive applications, smart cities and the Internet of Things (IoT), among other things. This technique has attracted significant attention from various fields, increasing the demand for tracking indoor location-based services. The critical challenge in DFL is a way to retrieve essential characteristics to illustrate raw signals with various locations linked with diverse patterns. The complexity of an indoor environment with limited space has created low indoor positioning reliability and effectiveness problems. Therefore, this study proposes and formulated an image classification problem for the DFL problem by initially transforming the receiving signal strength (RSS) inputs into picture frames. The feature extraction from raw signals was performed using Deep Feed-Forward Neural Network (DFFNN) and deep auto-encoder (DAE) to fine-turning for classification. The DAE combined DFFNN were used for signal reconstruction and feature learning to present the DFL better. The findings revealed an accuracy of 100% using real-world data collected, and a signal-to-noise ratio over -5dB, 0dB, and 5dB was used to measure the react to noisy data. Moreover, in IoT applications, its time cost is very fast in single activity by 5ms for classification. The proposed method is better in noiseless and noisy situations, localization accuracy, and other related techniques. © 2022 IEEE.

关键词： Wireless sensor networks

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Acoustotaxis‑Based Pump-Less Separation of Highly Motile Human Sperm by a Saw-in-Capillary Acoustofluidic Platform

SSRN

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SSRN 2024年

作者： Abbasi, Sara Barahimi, Behdad Darbari, Sara Halvaei, Iman Targhi, Mohammad Zabetian Nosrati, Reza Neild, Adrian Moravvej-Farshi, Mohammad Kazem Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Anatomical Sciences Faculty of Medical Sciences Tarbiat Modares University Tehran Iran Faculty of Mechanical Engineering Tarbiat Modares University Tehran Iran Department of Mechanical and Aerospace Engineering Monash University ClaytonVIC Australia

In artificial reproductive technologies mirroring in vivo fertilization, there is a correlation between sperm motility and fertilization outcomes. Here, we present a technology for separating sperm based on motility, which uses a biocompatible, pump-less, and simple acoustofluidic approach. Our developed and fabricated sperm separation configuration is an acoustofluidic platform consisting of a circular glass capillary tube mounted on top of a ZnO-based surface acoustic wave (SAW) device. It can separate highly motile sperm from small volumes of normal raw human semen samples. This configuration allows the generated traveling SAW to couple into the capillary, causing highly motile sperm cells to swim against the propagation direction of the traveling SAW along the capillary tube. We term this fascinating acoustic-induced sperm swimming behavior acoustotaxis in analogy with the well-known rheotaxis, in which sperm orientate to swim against a continuous fluid flow frequently generated by using an external pump in the microfluidic systems. Here, we benefit from the acoustotaxis for a pump-less separation of an effective highly motile sperm concentration from raw human semen samples at low volumes of up to 20-30 µL within a short period of about 4 minutes free from any centrifugation step. This sperm separation device exhibits a successful selection capability that leads to sperm progressive motility increase by 45%, sperm curvilinear velocity by 23%, sperm average path velocity by 69%, and sperm linearity by 78% in the selected cells in comparison with the raw sample. This acoustotaxic sperm selection separation approach provides an easy-to-use and effective method for the selection of highly motile sperm cells without adversely affecting sperm viability, paving the way for efficient and rapid sperm separation platforms, applicable for patients with low semen volumes, and up-scalable for a large volume of raw semen processing in a short time. © 2024, The Authors. All r

关键词： Pumps

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