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Development of Smart Light Detection and Monitoring System with Machine Learning 7

Development of Smart Light Detection and Monitoring System w...

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7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Chansareewittaya, Suppakarn Intan, Korawit Pramoonjakko, Nattapon Sripenbenja, theerametha Kemavuthanon, Kemachart Laohapensaeng, Teeravisit Sebakor, Mahamah Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center Thailand Mae Fah Luang University School of Information Technology Thailand

ISBN: (纸本)9781665495103

In this paper, the smart light detection and monitoring system is presented. the light sensors are used to detect the light temperature value in the room. the Arduino UNO and ESP32 are used as the main embedded systems. the ZigBee transmitters are used as the main transmitter. MySQL is set as the database. Moreover, Machine Learning is used to classify the light temperature value to natural light or fluorescent light. Test result shows that the cross-validation accuracy of KNN is 0.996. this accuracy of KNN is greater than other algorithms. Moreover, this system can be used to examine the status of the light in the room that can solve the problem of forgetting to turn off the light and can analyze data of using light as well. © 2022 IEEE.

关键词： Zigbee

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DDoS attack model with detection accuracy feedback mechanism 7

DDoS attack model with detection accuracy feedback mechanism

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2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Li, Fengjiao Ren, Jianguo School of Computer Science and Technology Jiangsu Normal University Xuzhou China

ISBN: (纸本)9783800760565

Due to the lack of pertinence to specific types of attacks in the existing models, a kind of model specially suitable for DDoS attacks is constructed based on the malicious behavior knowledge base with feedback mechanism. Based on the classical SIR model, the model introduces the actual attack stage of DDoS attack, and the detection accuracy feedback mechanism can continuously improve the detection accuracy of the model and effectively control the scale of DDoS attack. the equilibrium point of the new model is calculated, and the propagation threshold of the model is obtained by the next generation matrix theory. then the local stability and global stability of the equilibrium point of the model are proved by Routh-Hurwitz criterion and Lyapunov function. the experimental results show that constructing a DDoS attack model with feedback mechanism can more effectively resist DDoS attacks by improving its own detection ability. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Lyapunov functions

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7th international conference on computer, Communication and Signal processing, ICCCSP 2023

7th International Conference on Computer, Communication and ...

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7th international conference on computer, Communication and Signal processing, ICCCSP 2023

ISBN: (纸本)9783031398100

the proceedings contain 26 papers. the special focus in this conference is on computer, Communication, and Signal processing. the topics include: Forecast of Movie Sentiment Based on Multi Label Text Classification on Rotten Tomatoes Using Multiple Machine and Deep Learning Technique;an Ensemble Approach to Hostility Detection in Hindi Tweets;an Optimized Framework for Diabetes Mellitus Diagnosis Using Grid Search Based Support Vector Machine;inquisition of Vision Transformer for Content Based Satellite Image Retrieval;impact of Spectral Domain Features for Small Object Detection in Remote Sensing;application of Phonocardiogram and Electrocardiogram Signal Features in Cardiovascular Abnormality Recognition;analyzing Cricket Biomechanical Parameters through Keypoint Detection and Tracking;multi-feature Based Sea–land Segmentation for Multi-spectral and Panchromatic Remote-Sensing Imagery;deoxyribonucleic Acid Cryptography Based Least Significant Byte Steganography;detection and Estimation of Diameter of Retinal Vessels;a Simple Hybrid Local Search Algorithm for Solving Optimization Problems;Performance Study of RIS Assisted NOMA Based Wireless Network with Passive IoT Communication;multi-channel Man-in-the-Middle Attacks Against Protected Wi-Fi Networks and their Attack Signatures;a Study in Analysing the Critical Determinants of Internet of things (IoT) Based Smart processing for Sustainable Supply Chain Management;IOT Enabled Rover for Remote Survey of Archeological Areas;an Embedded System for Smart Farming Using Machine Learning Approaches;an Intrusion Detection System for Securing IoT Based Sensor Networks from Routing Attacks;automated Summarization of Gastrointestinal Endoscopy Video;interpretation of Feature Contribution Towards Diagnosis of Diabetic Retinopathy from Exudates in Retinal Images;false Positive Reduction in Mammographic Mass Detection;Collaborative CNN with Multiple Tuning for Automated Coral Reef Classification.

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Development of 7th generation 3D VNAND Flash Product with COP structure for Growing Demand in Storage Market

Development of 7th generation 3D VNAND Flash Product with CO...

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international conference on Electronics, information, and Communication (ICEIC)

作者： Lim, Joonsung Chung, Soochan Ko, Dong-Hyeon Sung, Suk-Kang Noh, Kyungyoon Ahn, Su Jin Song, Jai Hyuk Samsung Elect Co Dept Flash Prod & Technol Pyeongtaek 17786 Gyeonggi South Korea

ISBN: (纸本)9781665409346

Next generation 3D VNAND Flash memory device with 176 Word-line (WL) layer has been successfully built. the Cell-Over-Peripheral (COP) architecture was used, which reduced tR (Read Latency) by 11% and tPROG (Program Latency) by 20%, respectively. the bit density has been enhanced by 70% over our previous device (6th generation) thanks to cell volume scaling and COP architecture. To create this new device, double stack process was successfully merged for higher bit density. In addition, the channel hole profile was greatly improved using the double stack method. As a result, compared to our earlier product, we were able to attain superior cell operation characteristics. the technology used in the 7th generation 3D VNAND device, as well as our ongoing efforts to expand it to QLC devices and their results will be discussed in this paper.

关键词： three-dimensional displays Microprocessors computer architecture Flash memories Optimization Next generation networking Consumer electronics

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Research on control flow conversion technique based on Domestic Sunway compiler 7

Research on control flow conversion technique based on Domes...

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7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Kong, JinYing Han, Lin Xu, JinLong Nie, Kai School of Information Engineering Zhengzhou University Henan Zhengzhou China Henan Supercomputing Center Zhengzhou University Henan China Information Engineering University Henan Zhengzhou China

ISBN: (纸本)9781665478571

Control flow conversion replaces a series of control-dependent instructions with only data-dependent instructions. Sunway compiler uses this technology to eliminate pipeline pauses caused by conditional branch statements, thereby improving the instruction-level parallelism of the overall program. Based on the instruction set characteristics and structural characteristics of the Sunway processor, the improvement is made for the inaccurate calculation of the control flow conversion cost in the RTL stage in the Sunway compiler. In the control flow conversion benefit judgment algorithm, by adding control flow basic blocks the execution frequency of the branch statement is weighted to calculate the expected value of the execution cost of the basic block of the branch statement to improve the accuracy of the cost calculation during the conversion process. Using SPEC2006 Benchmarks to test the performance of the improved compiler on the new generation of Sunway 1621 server, the overall performance is increased by 2%, and the maximum performance of a single subject is increased by 6%. this work improves the control flow conversion in the Sunway compiler. Efficiency is of great significance in order to give full play to the performance advantages of the domestic Sunway processor architecture. © 2022 IEEE.

关键词： Program compilers

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Building Extraction from Remote Sensing Images with Conditional Generative Adversarial Networks 7

Building Extraction from Remote Sensing Images with Conditio...

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7th international conference on Signal and Image processing, ICSIP 2022

作者： Chen, Hongshun Sun, Wenjing Beijing Normal University Zhuhai School of Information Technology Zhuhai China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

Automated building extraction from remote sensing images is one of the most challenging problems. In order to automatically extract buildings from remote sensing images by Conditional Generative Adversarial Networks(CGAN), the pix2pix model was adopted and tested on the aerial imagery dataset of WHU Building Dataset. Results show that the pix2pix model performances well and achieves a high precision. © 2022 IEEE.

关键词： Generative adversarial networks

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An Innovative Method for Detection of Insect Based on Mask-R-CNN Approach 7

An Innovative Method for Detection of Insect Based on Mask-R...

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7th international conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Geetha, B.T. Jiwatode, Vilas Ramkrushna Raut, Ranjit Raosaheb Hussan, M.I. thariq Tiwari, Mohit Dobhal, Dinesh Chandra Saveetha School of Engineering Department of ECE SIMATS Tamil Nadu Chennai India Shri Sadguru Gangagir Maharaj Science Department of Zoology Gautam Arts and Sanjeevani Commerce College Maharashtra Kopargaon India Yogeshwari Mahavidyalaya Department of Zoology Maharashtra Beed India Guru Nanak Institutions Technical Campus Telangana Hyderabad India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350340600

Seventy percent of India's labor force works in agriculture, according to a recent survey. Pests and illnesses cause both qualitative and quantitative losses in crop production. While automatic in-field pest detection using a computer vision approach is an important part of modern intelligent agriculture, there are still significant challenges to be overcome. these include the complexity of the natural environment, the detection of tiny size pests, and the classification into several classes of pests. the proposed method consists of four stages: image preprocessing, segmentation, GLCM, and analysis. Model training and feature extraction. Image preprocessing techniques allow for the processing of a still image and the creation of an image improvement approach. the segmentation procedure makes use of grayscale insert images. A feature extraction tool that makes good use of the Gray level co-occurrence matrix. the models are then trained via Mask R-CNN, after information gain has been used to choose relevant features. CNN and RPN, two of the most common substitutes, are both outperformed by the proposed strategy. © 2023 IEEE.

关键词： Feature extraction

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Image Recognition of Concrete Electromagnetic Flaw Detection Based on Improved YOLOv7 24

Image Recognition of Concrete Electromagnetic Flaw Detection...

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7th international conference on Image and Graphics processing, ICIGP 2024

作者： Yuan, Shuai Yuan, Ze He, Kai School of Computer Science and Engineering Shenyang Jianzhu University China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction China Shenyang Branch of National Special Computer Engineering Technology Research Center China School of Electrical and Control Engineering Shenyang Jianzhu University China

ISBN: (纸本)9798400716720

Owing to the invisibility characteristics of the interiors of concrete structures, nondestructive testing technologies are commonly employed to detect internal damage. Electromagnetic flaw detection technology, as a prominent nondestructive testing method, offers capabilities of strong penetration and precise imaging. However, the output images produced by this detection technology are usually reliant on subjective human judgment, and existing automatic detection algorithms have limitations in terms of accuracy. To enhance the accuracy of electromagnetic flaw detection images, this paper proposes improved YOLOv7 based detection method. First of all, the ACBlock convolution module is introduced to replace the original 3×3 convolution kernel for alleviating the loss of edge feature information caused by the sampling operation of the backbone network MP module. Next, in order to have more focus on the semantic features of small targets, a global attention mechanism (GAMAttention) is incorporated into the algorithm. then, the FReLU activation function is adopted to enhance the algorithm sensitivity to image space. Finally, experiments are conducted on a self-created concrete flaw detection image dataset to illustrate the efficiency of the proposed algorithm. the results show that the mean Average Precision (mAP) value achieved by the improved algorithm is 95.85%. which has a significant improvement of 13.89% in comparison with the pre-improved YOLOv7 algorithm and surpasses other algorithms in the same domain. these findings represent that the proposed algorithm effectively enhances the accuracy of concrete electromagnetic flaw detection image detection. © 2024 ACM.

关键词： Nondestructive examination

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Voting Based Ensemble Framework For Crop Recommendation 7

Voting Based Ensemble Framework For Crop Recommendation

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7th international conference on Image information processing, ICIIP 2023

作者： Aryaman, Mayank Paliwal, Yashica Sharma, Aman Mohana, Rajni Jaypee University of Information Technology Computer Science And Engineering Department Waknaghat India Cse Jaypee University of Information Technology Waknaghat India Cse Amity School of Engineering Chandigarh India

ISBN: (纸本)9798350371406

Agriculture holds paramount importance for a significant portion of India's population, contributing significantly to the national economy. However, many Indian farmers rely on traditional senses rather than data-driven insights for crop selection, risking negative impacts on their mental and financial well-being. this article emphasizes the potential of Machine Learning models, utilizing a comprehensive dataset combining factors like rainfall, climate, humidity, and soil nutrients, to guide farmers in making informed decisions for optimal crop selection. To address the challenges faced by Indian farmers, the proposed methodology involves the application of Machine Learning models to a dataset encompassing crucial parameters such as sowing season, soil properties, climate, and location. By leveraging advanced algorithms, the models aim to recommend crops tailored to the farm's specific conditions, ensuring precision and accuracy in decision-making. this data-driven approach seeks to revolutionize traditional farming practices and enhance overall agricultural outcomes. the application of Machine Learning models on a comprehensive dataset demonstrated a robust recommendation system for crop selection, considering factors like soil health and weather conditions. this technology-driven approach empowers Indian farmers with informed decision-making, mitigating risks and fostering sustainable agricultural practices. © 2023 IEEE.

关键词： Crops

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Design and Implementation of System of the Web Vulnerability Detection Based on Crawler and Natural Language processing 7

Design and Implementation of System of the Web Vulnerability...

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7th international conference on information and Network Technologies, ICINT 2022

作者： Ge, Xin Yue, Minnan Information Office University of Shanghai for Science and Technology Shanghai China School of Energy and Power Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (数字)9781665482844

ISBN: (纸本)9781665482844

Application code analysis and static rules are the most common methods for Web vulnerability detection, but this process will generate a large amount of contaminated data and network pressure, the false positive rate is high. this study implements a detection system on the basis of the crawler and NLP. the crawler visits page in imitation of a human, we collect the HTTP request and response as dataset, classify the dataset according to parameter characteristic and whether the samples get to interact with a database, then we convert text word vector, reduce the dimension and serialized them, through train dataset by NLP algorithm, finally we obtain a model that can accurately predict Web vulnerabilities. Experimental results show that this method can detect Web vulnerabilities efficiently, greatly reduce invalid attack test parameters, and reduce network pressure. © 2022 IEEE. All rights reserved.

关键词： Natural language processing systems

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