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Hue Spectrum visualizer using python with OpenCV 2

Hue Spectrum visualizer using python with OpenCV

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2nd IEEE international conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Raajyavardhini, A. Gowthaman, T. Krishnamoorthy, R. Dhanush, S. Harish, S. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

Color analysis is a significant source in many image processing processes consisting of automotive vehicle navigation, protest detection, traffic sign recognition, skin color analysis, and object tracking. The approach adopted in this study mainly relies on the ability to locate the color name right at the center of the camera frame and determine the objects of red, green, and blue colors using the bounding box property. By rating the amount of red, green and blue of each pixel's outfits, the colors of these pixel are revealed. Next, all objects of interest that fall within the video segment of interest are detected and located using rectangular boundary boxes based on the HSV color model. The process used in this process entails the use of a dataset that has a tabular form with data on color names and its values to arrive at the best match. The values of Red, Blue, and Green (RGB) as well as color names of each pixel are extracted, providing the means to track the three separate colors in the video stream. When a color is not detected in the reference data but observed in the real-time stream, a box surrounds the mentioned color: the color name is written above the box. It enhances the approaches to recognition of color and also provides significant improvements in the field of robotics. The application of these techniques generally involves the use of the OPENCV software library together with the PYTHON programming language. © 2024 IEEE.

关键词： Python

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Genetic programming Approach in Better Understanding of the Relationship Between the Number of Viable Cells and Concentration of O2^-, NO2^- and GSH Produced in Cancer Cells Treated with Pd(II) Complexes 2nd

Genetic Programming Approach in Better Understanding of the ...

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2nd Serbian international conference on Applied artificial Intelligence (SICAAI)

作者： Mladenovic, Tamara M. Zivanovic, Marko N. Benolic, Leo Pavic, Jelena N. Filipovic, Nenad Univ Kragujevac Dept Nat Sci Inst Informat Technol Kragujevac Kragujevac Serbia Bioengn Res & Dev Ctr BioIRC Kragujevac Serbia Univ Kragujevac Fac Engn Kragujevac Serbia

ISBN: (纸本)9783031608391;9783031608407

Genetic programming (GP) is a powerful tool for creating mathematical models and has been used in various fields to discover complex relationships in data. GP is a method that uses artificial intelligence to automatically create programs, based on the Darwinian principle of natural selection to create a population of better programs over many generations. Therefore, this study investigated the possibility of obtaining a function describing the data obtained from the research work conducted by Petrovic et al., by applying genetic programming. Experimental results showed that Pd(II) complexes, labeled as Pd-1, Pd-3, Pd-5 and Pd-6, showed significant cytotoxic effects and extreme oxidative stress in cancer cell lines HCT-116 and MDA-MB-231. Specifically, the aim was to determine whether there is a concentration-dependent relationship between the number of viable cells for all experiments. To create the function, symbolic regression was used. R2 is a useful metric for evaluating the performance of the created function. Overall, the results demonstrate that GP is a powerful tool for creating mathematical models that accurately describe the relationship between concentration and the number of viable cells. In conclusion, it has been shown that GP can be used with high precision on such examples, with R2 ranging from 0.9747 to 0.99948. Such a method of calculating values could facilitate the selection of the required concentration for use in experiments.

关键词： genetic programming Pd(II) complexes optimization cytotoxic oxidative stress

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A Study of Crew Allocation Based on a Novel Heuristic Algorithm and Simulated Annealing Algorithm 2

A Study of Crew Allocation Based on a Novel Heuristic Algori...

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2nd IEEE international conference on Image Processing and Computer Applications, ICIPCA 2024

作者： Wang, Hong Xia, Jun Song, Yuqin School of Management Science and Engineering Anhui University of Technology Ma'anshan China Anhui Jianghuai Automobile Group Co. Ltd. Hefei China

ISBN: (纸本)9798350360240

This paper addresses the optimization of flight crew assignments by introducing a mathematical optimization model aimed at maximizing the allocation of flight crew to flights while minimizing overall occurrences and the use of substitute qualifications. The proposed approach involves route-based clustering, where flight routes are aggregated around hub airports to serve as the fundamental unit for matching flight crew. This transforms the problem of flight crew assignment into a route-based matching scenario. A mathematical programming model is established to minimize the number of unfulfilled crew assignments, flight occurrences, and substitute qualification usage, while also prioritizing these objectives. To enhance computational efficiency, a simulated annealing algorithm and a novel heuristic strategy are employed for solving. Results demonstrate the superiority of the new heuristic strategy over simulated annealing. Specifically, for dataset A, 202 flights were successfully scheduled with no crew occurrences or substitute qualification usage. For dataset B, 13235 flights were successfully arranged with zero crew occurrences or substitute qualification usage, and the program execution time was 0.32s. © 2024 IEEE.

关键词： Simulated annealing

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Dynamic Program Slicing of Agent-oriented Software 2

Dynamic Program Slicing of Agent-oriented Software

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2nd international conference for Innovation in Technology, INOCON 2023

作者： Mishra, Alina Kabat, M.R. Mohapatra, D.P. Veer Surendra Sai University of Technology Department of Computer Science and Engineering India National Institute of Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350320923

Slicing programs is an essential aspect of program development and maintenance. Because numerous statements might be discarded in the procedure of locating a bug, dynamic program slicing approaches are commonly utilized for debugging. Only the statements that have a consequence on the variable are included in a dynamic program slice with regard to that variable. Agent-oriented programming is a novel paradigm which uses agents as their basic entity. Agents are defined as an object which achieves an explicit action in an atmosphere known to it and responds to the variations. In this paper, a different approach for computation of relevant slices in agent-oriented programs is presented. We have taken a single-agent program as our working example. First, we have developed an intermediate representation for the agent-oriented program. Then, we have developed an algorithm based on dependencies among the nodes in the graph to compute slices. © 2023 IEEE.

关键词： Multi agent systems

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A Double Layer Encryption for Communication using Cryptographic Algorithms 2

A Double Layer Encryption for Communication using Cryptograp...

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2nd international conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Ragavan, K. Mohankumar, B. Vivekrabinson, K. Arun, R. Arumuga School of Computer Science and Engineering Vellore Institute of Technology Vellore India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Krishnankoil India

ISBN: (纸本)9798350328202

Cryptography is a fundamental field in computer science that focuses on securing communication and protecting sensitive information from unauthorized access. It involves the use of mathematical algorithms and techniques to transform plaintext into ciphertext, rendering it unintelligible to anyone without the proper decryption key. Cryptographic systems play a crucial role in ensuring confidentiality, integrity, and authenticity of data in various domains, including finance, healthcare, e-commerce, and communication networks. In this paper, a double-layer encryption method is proposed that uses the Vigenere and Polybius ciphers to secure communication. The Vigenere cipher is a classical method that uses a keyword to encrypt plaintext, while the Polybius cipher is another classical cipher that uses a grid to map letters to two-digit numbers to encrypt data. By combining these two ciphers, the proposed algorithm aims to enhance the security of the data by introducing a more complex and secure encryption method. The proposed method is implemented using Python programming language with web implementation. The web implementation of the algorithm uses Flask, a Python web framework. This allows users to encrypt and decrypt their data through a user-friendly interface, making it more accessible and practical for real-world use. Based on the obtained results demonstrate that the proposed method provides a higher level of security compared to using each cipher individually, without significantly impacting the encryption and decryption speed. Overall, the proposed double-layer encryption method can be a useful tool for secure communication in various applications. It contributes to the field of cryptography by introducing a novel approach that enhances data security without compromising usability. © 2024 IEEE.

关键词： Cryptography

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Implementing and Analyzing Behaviour of ML based Tamil Songs Recommendation System 2

Implementing and Analyzing Behaviour of ML based Tamil Songs...

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2nd international conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Garg, Shalini Pooja Chaoudhary, Shailee Lohmor Dixit, Rinku Govil, Nikhil Design and Technology University Mit Art MH Pune India Galgotias University School of Cse Delhi - NCR Gr. Noida India New Delhi Institute of Management Department of Aiml - Data Science New Delhi India Gla University Department of Computer Engineering & Applications U.P. Mathura India

ISBN: (纸本)9781665491990

Music gives listeners a chance to relax, relieve fatigue and connect one culture with another. In such a situation, if the favorite song-music is heard one after another and according to the emotion, it gives a unique and wonderful experience to the listener. It is determined based on the emotion and interest, ratings provided by listeners and search patterns. In this research article, the proposed method presents Tamil songs compilation and recommendation system with the help of these factors. The behavior of this recommendation system is also analyzed in this system. The proposed system is developed in Java programming language by adopting the techniques of Machine Learning. Through this system, listeners have the choice to play category wise songs. As per the listening history and patterns, upcoming songs are predicted to the listeners. This system also provides ratings to each song. This developed application can also be used commercially as it has been validated that the ratings provided by the listeners are in line with IMDb ratings. © 2023 IEEE.

关键词： Recommender systems

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Exploring Taiwan Monkeypox Virus (MPOX/MPXV) Clade IIb by Establishing Dataset and Clustering by using Sequence and Image Similarity Comparisons 24

Exploring Taiwan Monkeypox Virus (MPOX/MPXV) Clade IIb by Es...

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7th international conference on Computational Intelligence and Intelligent Systems, CIIS 2024

作者： Wang, Tzung-Wei Li, Ming-Kuang Lou, Der-Chyuan Lin, Chun-Yuan Dept. of Electronics Engineering Chang Gung University Taoyuan Taiwan Dept. of Computer Science and Information Engineering Asia University Taiwan Taichung Taiwan Dept. of Computer Science and Information Engineering Chang Gung University Taoyuan Taiwan

ISBN: (纸本)9798400717437

Based on the MPXV Clade IIb cases in Taiwan, 175 segments were identified from OPG001 to OPG210. The first focus of this paper is on sequence analysis of the MPXV cases in Taiwan, detailing the procedures, including semi-automated segmentation and dataset creation from a large number of MPXV Clade IIb nucleotide sequences found in the NCBI and GISAID databases. The second feature highlights the pioneering establishment of an MPXV Clade IIb RNA 2nd structure image dataset in Taiwan, as such a dataset does not yet exist globally. The third characteristic involves the use of unsupervised learning methods for the rapid clustering of MPXV Clade IIb RNA 2nd structure images. This approach allows not only for the quick detection and clustering of unknown MPXV Clade IIb cases but also for the rapid identification of new MPXV mutations and structural changes. Compared to traditional sequence analysis, this new hybrid systematic method significantly enhances overall efficiency, improving processing speed by at least 24 hours when handling the alignment of 10 MPXV sequences from Taiwan. Future plans include using this prototype analytical model and method to accelerate the analysis of critical lethal factors in MPXV Clade IIb, such as D14L, ultimately helping biologists reduce the time required for analysis and antiviral drug development. © 2024 Copyright held by the owner/author(s).

关键词： Nucleotides

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Enhancing Blurred Image Processing with IoT Integration for Improved Clarity 2

Enhancing Blurred Image Processing with IoT Integration for ...

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2nd IEEE international conference on Emerging Research in Computational science, ICERCS 2024

作者： Tummalapalli, Geetamma Summia Parveen, H. Ramesh, S.M. Monica, P. Santhiya, B. Rajasekaran, Arun Sekar GMR Institute of Technology Department of Electronics and Communication Engineering Rajam India Sri Eshwar College of Engineering Department of Computer Science Engineering Coimbatore India KPR Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India GITAM Deemed to be University Department of Electronics and Communication Engineering GST Visakhapatnam India Bannari Amman Institute of Technology Department of Information Technology Sathyamangalam India SR University Department of Electronics and Communication Engineering Warangal India

ISBN: (纸本)9798331534950

A blurred image is an image that has undergone a blurring or smoothing effect, resulting in a loss of sharpness and clarity. Blurring is a technique used in image processing to reduce noise, remove unwanted details, or create a visual effect. It involves averaging or blending neighboring pixels to create a smoother appearance. The specific processing techniques and algorithms used will depend on the nature and extent of the blur, the intended outcome, and the available software or programming tools. It's important to experiment with different methods and parameters to achieve the desired result. IoT (Internet of Things) can be used in image processing in several ways to enhance functionality, efficiency, and data processing capabilities enhances image processing by enabling real-time analysis, edge computing capabilities, integration with other IoT devices, and remote monitoring and control. These advancements facilitate applications such as object detection, image recognition, and real-time decision-making, contributing to more efficient and intelligent systems in various domains. Here is a proposed model for blurred image processing with IoT. This proposed model demonstrates the integration of IoT devices, image processing techniques, and cloud-based analytics to address the challenges of blurred image processing. It combines edge processing for real-time analysis and cloud-based processing for more complex algorithms, enabling efficient and intelligent image processing applications in various domains. © 2024 IEEE.

关键词： Edge computing

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Hardware-based Dual Booting Switch with Customizable Setup Script and Cross Platform Support 2

Hardware-based Dual Booting Switch with Customizable Setup S...

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2nd international conference on Applied artificial Intelligence and Computing, ICAAIC 2023

作者： Chaturvedi, Venkatesh Arora, Deepak Amity School of Engineering & Technolgy Lucknow Amity University Aset Department of Computer Science & Engineering Uttar Pradesh India

ISBN: (纸本)9781665456302

Many people use numerous operating systems to do a variety of tasks in today's hectic world. While using Linux for programming and coding, someone may utilize Windows for some document editing. There are no major problems faced while dual booting two operating systems aside from the fact that in order to dual boot, one has to open the boot menu every time in order to select which operating system is to be booted. This process of opening the boot menu and selecting the operating system each time is a very redundant task. Hence, the idea of a hardware-based switch that would help in switching the operating system without opening the boot menu every time was born. Initial thoughts for the switch included using a control board such as the Raspberry Pi for programming the switch. Even modification of the bootloader source code in order to create some hardware-based controller was attempted. However, after several days of research and testing, it was concluded that even though previous attempts had been made to create a dual booting switch using control boards, and were successful to an extent, those solutions were too complex for the value they provided. Hence, work was started on creating a dual booting switch without using a control board and with minimum modifications to the bootloader. © 2023 IEEE.

关键词： Linux

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Sentiment Analysis of GitHub Commit Comments using Machine Learning Techniques 2

Sentiment Analysis of GitHub Commit Comments using Machine L...

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2nd DMIHER international conference on artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Patel, Safaa Zagade, Gayatri Sharma, Rahul D Y Patil International University School of Computer Science Engineering and Applications Akurdi Pune India

ISBN: (纸本)9798331528713

The proliferation of collaborative platforms like GitHub necessitates robust sentiment analysis tools to interpret developer emotions in commit comments, offering insights into project health and team dynamics. This study advances existing research by evaluating three machine learning algorithms for this task: Passive Aggressive Classifier, C-Support Vector Classifier (C-SVC) with a linear kernel, and Random Forest *** analyzed 10,000 GitHub commit comments from diverse projects spanning multiple programming languages and development periods. Performance was assessed using accuracy, precision, recall, and F1-score. C-SVC outperformed other algorithms with 98 percent accuracy, 97 percent precision, 98 percent recall, and an F1-score of 0.975. The Random Forest Classifier achieved 96 percent accuracy, while the Passive Aggressive Classifier reached 94 *** findings demonstrate C-SVC's effectiveness for sentiment analysis in this context, surpassing previous benchmarks. Integration of this tool into development workflows could enhance team communication, enable early issue detection, and provide quantitative metrics for project emotional health. Future research should examine the generalizability of these results across various project types and explore real-time sentiment analysis in collaborative coding environments. © 2024 IEEE.

关键词： Adversarial machine learning

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