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1st IEEE International Conference on Emerging research in Computational science, ICERCS 2023

作者： Jabez, J. Franklin, Ramya G Ronald Doni, A. Kamalesh, Murari Devakannan Sathyabama Institute of Science & Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350359756

A key a part of early analysis and treatment of neurological illnesses is the detection of anomalies inside the mind through ultrasound scans. Using a Signal Processing Network (SPN), this studies seems into the cost of characteristic extraction techniques for identifying and categorizing brain problems in ultrasound mind pics. Timely scientific action is appreciably aided through the early and accurate analysis of mind abnormalities in ultrasound pics. In mild of these findings, it's far obvious that accurate categorization techniques are vital for improving patient consequences through facilitating in advance diagnoses. It is hard to stumble on abnormalities in the brain using ultrasound pics because of historical past noise, artifacts, and the need for correct localization. This paper attracts attention to these problems and proposes a strategy for overcoming them through a Signal Processing Network. For better class of brain problems, this studies proposes a unique method that combines function extraction techniques and a Signal Processing Network: Deep learning-based improved function Ultrasound Brain Images (DL-EFUBI). The technique employs state-of-the-art sign processing algorithms to extract distinguishing traits from ultrasound photos, taking into consideration more particular class of abnormalities. The proposed technique shows promise in some of therapeutic programs, such as the analysis of brain tumors, cysts, and other irregularities at an early degree. It can assist scientific practitioners make higher choices, which in flip blessings affected person care and results. Extensive simulation studies, wherein the cautioned method is compared to mounted methods, is used to assess the approach's efficacy. The effects display that the method has the ability to outperform general approaches close to type accuracy, sensitivity, and specificity. © 2023 IEEE.

关键词： Feature extraction

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ElectRA-Decentralized Voting Application 9

ElectRA-Decentralized Voting Application

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9th International Conference on Smart Computing and Communications, ICSCC 2023

作者： Mohan, Anila Rakhee, M. Muthoot Institute of Technology and Science Computer Science and Engineering Kerala Kochi India

ISBN: (纸本)9798350314090

Blockchain technology is one of the most promising modem technologies. The decentralization principle is used to distribute data among the active nodes of the network. There are many different use cases in the contemporary digital era because of the technology's ability to assure confidentiality, privacy, and immutability. The existing electoral process is centralized and unreliable in operation. Elections must therefore be conducted using secure online methods. The most effective method for guaranteeing election anonymity, security, privacy, and dependability is blockchain technology. The goal of this work is to implement an online voting system based on blockchain technology. It looks for examples of how blockchain technology might be used in the Indian electoral system, how to do it, and what other considerations need to be made. Scalability, application methodology, implementation criteria, blockchain characteristics, and technological components must all be taken into account while managing an online voting application using smart contract writing. © 2023 IEEE.

关键词： Blockchain

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Unstructured Text Classification Using NLP and LSTM Algorithms 7th

Unstructured Text Classification Using NLP and LSTM Algorith...

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7th International Conference on Artificial Intelligence and Virtual Reality, AIVR 2023

作者： Prusty, Sashikanta Patnaik, Srikanta Sahoo, Ghanashyam Rautaray, Jyotirmayee Prusty, Sushree Gayatri Priyadarsini Department of Computer Science and Engineering Siksha ‘O’ Anusandhan [Deemed to be University Bhubaneswar751030 India Interscience Institute of Management and Technology Kantabada Bhubaneswar752024 India Department of Computer Science and Engineering GITA Autonomous College Bhubaneswar751017 India Department of Computer Science and Engineering Odisha University of Technology and Research Bhubaneswar751003 India

ISBN: (纸本)9789819990177

In the last two decades, cancer has found as the most severe disease that causes a large number of deaths worldwide. However, it seems that the medical data are in the unstructured form, which makes it challenging for the pathologist to classify the disease in the beginning stages. This article provides a novel technique using natural language processing (NLP) for the classification of three common cancers thyroid, lung, and colon from the unstructured medical data, removing at-stop words, and articles such as ‘a,’ ‘an,’ and ‘the’ to form tokens. Tokenization is performed on larger text to divide it into smaller parts with the help of the TensorFlow technique. Besides that, long short-term memory networks (LSTM) model has been proposed to handle long sentences, especially in sequence prediction problems. This article also discusses the basic workflow of model design and prediction of three cancers. Finally, a confusion_matrix has been drawn to evaluate our model performance and found 99.41% at classifying three individual cancers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Long short-term memory

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Saddlepoint Approximation Method in Reliability Analysis:A Review

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computer Modeling in engineering & sciences 2024年第6期139卷 2329-2359页

作者： Debiao Meng Yipeng Guo Yihe Xu Shiyuan Yang Yongqiang Guo Lidong Pan Xinkai Guo School ofMechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu611731China Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan523808China Glasgow College University of Electronic Science and Technology of ChinaChengdu611731China Beijing Research Institute of Mechanical&Electrical Technology Ltd.Beijing100083China

The escalating need for reliability analysis(RA)and reliability-based design optimization(RBDO)within engineering challenges has prompted the advancement of saddlepoint approximationmethods(SAM)tailored for such *** article offers a detailed overview of the general SAM and summarizes the method characteristics ***,recent enhancements in the SAM theoretical framework are ***,the mean value first-order saddlepoint approximation(MVFOSA)bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation(MVSOSA);the latter serves as an auxiliary approach to the *** distinction is rooted in the varying expansion orders of the performance function as implemented through the Taylor *** the saddlepoint approximation and third-moment(SATM)and saddlepoint approximation and fourth-moment(SAFM)strategies model the cumulant generating function(CGF)by leveraging the initial random moments of the *** their optimal application domains diverge,each method consistently ensures superior relative precision,enhanced efficiency,and sustained *** method elucidated is exemplified through pertinent RA or RBDO *** juxtaposing them against alternative strategies,the efficacy of these methods becomes *** outcomes proffered are subsequently employed as a foundation for contemplating prospective theoretical and practical research endeavors concerning *** main purpose and value of this article is to review the SAM and reliability-related issues,which can provide some reference and inspiration for future research scholars in this field.

关键词： Reliability analysis reliability-based design optimization saddlepoint approximation

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Tracking of Artillery Shell using Optical Flow 23

Tracking of Artillery Shell using Optical Flow

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5th International Conference on Image Processing and Machine Vision, IPMV 2023

作者： Masum, Abdullah Al Reza, Shad Sharmin, Nusrat Rahman, Md. Mahbubur Department of Computer Science and Engineering Military Institute of Science & Technology Dhaka Bangladesh

ISBN: (纸本)9781450397926

The effectiveness of the Artillery shell is measured by its precision of hitting the target. During hitting the target, the intended firing path can be affected by the inherited source as well as external factors like wind, temperature changes, etc. Thus tracking such a path becomes crucial. In this paper, we address the problem of artillery shell tracking with optical flow and adopted the solution for it with sparse and dense optical flow. The outcome of this work can be used in test firing to determine the accuracy of the artillery target. Experimental findings show that the proposed methodology is more effective than the current military artillery unguided shell's impact point locating, even if the shell ended up being an unexplored or blind shell. © 2023 ACM.

关键词： Optical flows

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Wireless Gesture-Driven Navigation for Autonomous Robots: An Innovative Human-Machine Interface Approach

Wireless Gesture-Driven Navigation for Autonomous Robots: An...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Zarina Begum, M. Gowthami, V. Ramya, M. Vijaya Shanthi, V. Manakula Vinayagar Institute of Technology Department of Electronics and Communication Engineering Puducherry India Christ Institute of Technology Department of Computer Science Engineering Puducherry India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510022

As more and more features are added to the car's Human- Machine Interface (HMI), device management becomes increasingly difficult. Making the most of the many human senses is consequently a tactic to facilitate using in-car technologies. With the use of an Arduino Uno and this concept, a car robot with wireless navigation can be built. The robot chassis's direction is altered in accordance with the statement specified in the Arduino code, which is run when the position of the hand is monitored and the designed coordinates are taken into consideration as the parameter. in order for it to carry out the necessary actions, such as going ahead, backward, turning left, turning right, and stopping. © 2024 IEEE.

关键词： DC motors

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Automated Interview through Online Video Interface

Automated Interview through Online Video Interface

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2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Joshila Grace, L.K. Asha, P. Shabu, Jany Refonaa, J. Selvan, Mercy Paul Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350333244

Automated Video Interview Interface is a streamlined approach to job interviews that uses AI and video conferencing. This system can evaluate candidates and make hiring decisions by utilizing natural language processing, facial recognition, and machine learning algorithms, dispensing with the need for physical interviews while enhancing the recruitment process efficiency and decision quality. This technology allows organizations to conduct video interviews with candidates remotely, using pre-recorded or live questions, and also provides the added ability to evaluate and score the candidate's responses. Additionally, it offers the added benefit of personalized feedback for candidates and detailed performance reports for employers. In today's fast-paced recruitment environment, managing effective human interaction, recognizing candidates' facial expressions and body language, and resolving technical issues such as network connectivity, camera and microphone access can be challenging. However, this innovative application offers a solution by providing an efficient interface for accurate candidate assessment and valuable insights. The system not only facilitates the creation, analysing, and evaluating a large number of candidates, but also generates performance reports and personalized feedback based on their performance. This research paper provides an overview of the concept, benefits, and limitations of AVII, and discusses the potential impact of this technology on the recruitment process. It delves into the numerous advantages of implementing an Automated Video Interview Interface, as well as addressing potential challenges and the future impact of this technology on the job market. By utilizing this application, candidates can perform in a secure and private environment with efficient responses of candidate's performance. © 2023 IEEE.

关键词： Video conferencing

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Classification of Indicators Based on Morbidity and Mortality

Classification of Indicators Based on Morbidity and Mortalit...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Deepak Kumar, A. Jayakumar, Shruti Balamurali, A. Mithun, P. Janagiraman, S. Rajesh Kanna, R. St. Joseph's Institute of Technology Department of Computer Science and Engineering Chennai India SRM Institute of Science and Technology Department of Computer Science and Engineering Chennai Ramapuram India

ISBN: (纸本)9798350319200

In our evolving world, human vulnerability to diseases remains a critical concern, with an overwhelming volume of health data generated by applications. Managing this massive and complex big data requires advanced processing methods. This is particularly evident in medicine, where predicting outcomes is vital for patient care [15]. The intricate and variable nature of healthcare data presents challenges, necessitating the development of sophisticated algorithms and tools. These advancements have the potential to revolutionize disease prevention, personalized treatment, and healthcare [17] system optimization. Enhancing analytical capabilities is urgent, enabling healthcare professionals to uncover valuable patterns that improve patient care [8]. Efforts are underway to efficiently analyze medical big data [11], promising a brighter future for healthcare. Ultimately, of all the algorithms used, Decision Tree analysis proves to be the most effective approach after enhancing using bagging classifier. © 2023 IEEE.

关键词： Bagging Classifier Big data Decision Tree Machine Learning

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Synergizing Futures: Precision Career Mapping with Llama 2 and AI Fine-Tuning for Personalized Path Prediction and Guided Navigation

Synergizing Futures: Precision Career Mapping with Llama 2 a...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Singh, Anuradha Sharma, Himanshu Jindal, Kanika Chaudhary, Ankur Noida Institute Of Engineering And Technology Department Of Computer Science And Engineering Greater Noida India Noida Institute Of Engineering And Technology Department Of Electronics And Communication Engineering Greater Noida India

ISBN: (纸本)9798350366846

These days, a lot of students struggle in how to choose the career. As they progress through their studies, students must recognize their abilities and assess their areas of interest to determine the most appropriate job for them. With the aid of this approach, today's youngsters will be able to determine which career route will yield the best outcomes in the long run if they choose the suggested vocation. This will assist in raising the student's performance and spark their interest to keep them concentrated on their desired job. This system is based on an exam that students must complete;based on their responses, it will produce a summary of the test results. The primary goal of this system is to give a summary of the artificial intelligence methods that we employed to forecast the student's performance. This structure likewise be emphasizing how we are identifying characteristics in student data by employing prediction systems. For educators, educational institutions, and students alike, using this system has proven to be advantageous. In this paper we have used various technologies like Flutter, Llama-2 generative A.I. model, Firebase and UI/UX design tools. Our experimental results of proposed system reduce the career searching effort by 80% when tested for Lyman people. © 2024 IEEE.

关键词： Students

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Enhancing Human Action Recognition through advanced Motion Descriptors and Machine Learning 1

Enhancing Human Action Recognition through advanced Motion D...

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1st International Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Ramalingam, Vijay Saravanan, D. Vignesh, S. Rahin Batcha, R. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350328042

Understanding human activities from videos presents a formidable challenge in computer Vision. Intelligent video systems primarily specialize in automatically recognizing human actions within video sequences and annotating them accordingly;human action identification involves recognizing actions associated with one or more objects based on analysis of their activities and context. As technology has proliferated rapidly, huge amounts of human-centric video data have accumulated;it has become an obstacle in contemporary video processing systems due to identifying all these actions efficiently. Complex backgrounds compound these challenges, creating error margins that severely hamper many object detection algorithms and creating error margins that compromise performance - particularly with regard to occlusion and distortion issues. This work addresses these obstacles using Apache Spark with in-memory computing and distributed environment for improved recognition of human actions;specifically, a Local Motion Descriptor is employed for feature extraction that calculates intensities between frames that include both motion and appearance elements. Spark MLlib employs random forest to effectively recognize human behavior. Experimental studies are performed to evaluate its activity recognition capabilities and results are benchmarked against popular supervised classification techniques like Decision Trees;results demonstrate that our proposed model outshone other classification techniques, confirming its efficacy in activity recognition. © 2023 IEEE.

关键词： Decision trees

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