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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

共 4197 条记录，以下是431-440 订阅

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Promotion Classification Using DecisionTree and Principal Component Analysis 7

Promotion Classification Using DecisionTree and Principal Co...

引用

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： Kaewwiset, theeramet Temdee, Punnarumol Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665495103

the goal of human resource management is to support the employee to higher position promotion and improve their work performance. the key process for performance evaluation is promotion classification. this paper proposes the machine learning based promotion classification using decision tree and principle Component Analysis (PCA). this paper uses Human Resource Analysis Case Study dataset from Kaggle for comparing the promotion classification. the comparison of classification performance for all features, personal features, and performance features are conducted. the classification results show that the classification with PCA provides the highest accuracy at 91.25%. © 2022 IEEE.

关键词： Classification (of information)

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Data transformation in the Infectious Disease Surveillance System for the Public Health information Management 7

Data transformation in the Infectious Disease Surveillance S...

引用

作者： Homla, Pipitton Puritat, Kitti Chiang Mai University Department of Library and Information Science Chiang Mai Thailand

ISBN: (纸本)9781665495103

this paper aims to solve the problem of large number of COVID-19 patients with paper form for COVID-19 investigation and to communicate between medical staffs and public health office center. We applied the agile model to design and develop data transformation in the infectious disease surveillance system to help a project to adapt to change requests quickly. this data transformations provide the public health emergency surveillance such as routine surveillance, COVID-19 surveillance, event-based surveillance and outbreak investigation. this approach can be useful to the Infectious disease situation. In additional, it can be provided greater contributions to manage public health data in term communicable diseases in the future. © 2022 IEEE.

关键词： Public health

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Research on Signal Attenuation by Humidity and Rain in 60GHz Frequency Band 7

Research on Signal Attenuation by Humidity and Rain in 60GHz...

引用

7th IEEE international conference on computer and Communication Engineering technology, CCET 2024

作者： Adong, Zhang Bo, Li Yang, Li Pengfei, Xue Jiao, Ma School of Communication and Information Engineering Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9798350355673

With the rapid development of wireless communication technology, millimeter-wave band (30GHz to 300GHz) has begun to serve global communication. Among them, 38GHz, 77GHz and 120GHz are relatively mature in research and application. 60GHz has become one of the most promising frequency bands in future wireless communication technology due to its large bandwidth and license-free characteristics. Firstly, based on millimeter wave wireless communication, this paper expounds the attenuation factors affecting 60GHz signal transmission, and establishes millimeter wave models considering water vapor content indoors and rain attenuation outdoors respectively. Finally, by capturing and processing received signal strength indication (RSSI) and receiving rate changes of signals, the attenuation effect of water molecules on 60GHz millimeter wave signals in communication environment is analyzed. the results show that both gaseous water vapor and liquid raindrops have a significant attenuation effect on the 60GHz signal. this research is expected to play an important reference and promotion role in the field of processing 5G millimeter wave and even future 6G signal coverage and optimization. © 2024 IEEE.

关键词： Image coding

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Eye Positioning System for PC Based on Autostereoscopy with Android 7

Eye Positioning System for PC Based on Autostereoscopy with ...

引用

7th international conference on Multimedia Communication Technologies, ICMCT 2022

作者： Wang, Ke Chen, Yu Ting Pan, Zong Hai Li, Fei Lan, Chun Mei College of Computer Science and Technology. Chengdu Jincheng College Chengdu Jincheng College Sichuan China

ISBN: (纸本)9781665473620

When combining with the Autostereoscopy technology of Android mobile devices, it is necessary to use the eye tracking technology to locate the position of the eye to switch the pictures on the Android side. When the face detection mode of camera2 of Android system is used for real-time eye tracking, the arithmetic power of cell phone will be relatively low, and it will cause lag when calculating the position of eye, so this paper combines computer vision processing to put the calculation of eye tracking and positioning on the computer terminal, and uses gpu to calculate, so it can have unlimited arithmetic power and higher efficiency. © 2022 IEEE.

关键词： computer vision

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Research on Evaluation and Grading of information Security Classification Protection Based on Robot Navigation and 3D Reconstruction 7

Research on Evaluation and Grading of Information Security C...

引用

7th IEEE information technology and Mechatronics Engineering conference, ITOEC 2023

作者： An, Rui Shaanxi Institute of International Trade and Commerce School of Information Engineering Shaanxi Xi'an China

ISBN: (纸本)9798350334197

In this paper, we propose a grading method for the evaluation of information security level protection based on robot navigation and 3D reconstruction, study and propose a grading evaluation scheme for robot positioning and understanding of the surrounding environment, quickly reconstruct the 3D system of the site environment through the auxiliary evaluation of industrial robots based on ID code positioning, and finally transplant the algorithm to the robot operating system to achieve mobile cruise function in combination with ROS function package and path planning, Multiple threshold adjustments are made to control the evaluation error within a reasonable range. By analyzing the grading of level protection evaluation, the obtained data is calculated to obtain the grading level of relevant institutions' level protection evaluation, which greatly increases the accuracy and execution efficiency of the evaluation. © 2023 IEEE.

关键词： Grading

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the IoT-based weighing system for growth monitoring and evaluation of fattening process in beef cattle farm 7

The IoT-based weighing system for growth monitoring and eval...

引用

作者： Noinan, Khunkanok Wicha, Santichai Chaisricharoen, Roungsan Mae Fah Luang University School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665495103

this study investigated a tracking model to evaluate growth efficiency of beef cattle, an amount of 60 male cows, with 18-20 month age, an average body weight of 350-400 kg was feeding program for 120 days experiment in measuring growth performance. the cattle were divided into four groups: Charolais, Charbray (Cross Charolais and Brahman), Brahman, and Native thai group. this study focuses on analyzing and processing the data collection which design weighing scale process by identification from using RFID ear tag (radio-frequency identification) in cow individuals. that processing connects with the Internet of things system (IoT) to collect weighing aggregate data of individual cows, with precision in real-time. therefore, the design system provides a support process for decision-making in the beef cattle data traceability system. the objective of this study designed to evaluate growth in a cow's weight by comparing the cost-effectiveness of generating profits in total operating cost especially, the fattening process. this design system was implemented in Northern thailand with a local beef cattle farm by the execution of appropriated technology context. the result shows that this study shows the positive result of farming support system development in terms of cows weighing track and cost-efficiency analysis of fettering process. © 2022 IEEE.

关键词： Internet of things

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Traffic Target Detection System Based on Improved YOLOv7 5

Traffic Target Detection System Based on Improved YOLOv7

引用

5th international conference on computer Vision, Image and Deep Learning, CVIDL 2024

作者： Yang, Xiaoling Chen, Bin Wu, Yushi Zeng, Wenjing Hong, Yongqin Zhuhai University of Science and Technology Zhuhai China Zhuhai University of Science and Technology Shantou China Zhuhai University of Science and Technology Nanping China

ISBN: (纸本)9798350373820

With the intelligent development of the times, traffic scenes are becoming increasingly complex. In order to solve this problem, this paper proposes a traffic target detection system based on an improved YOLOv7 network. Based on the existing YOLOv7 network, it has been improved and applied for target detection in complex traffic scenarios. Firstly, the Wise_IoU loss function has been improved to enhanced Box frame edge information reading capability;without completely replacing the original GIoU loss function. Secondly, the SE attention mechanism is added to enable the image data to focus on important information as it passes through the neural network. this reduces the amount of irrelevant computation and enhances the overall convergence speed. Finally, for fixed region detection, set the region of interest (ROI) to detect vehicles, pedestrians, and other targets moving within that area. the improved YOLOv7 model presented in this paper has made a significant advancement in the performance metrics of target detection in traffic scenes, including PR precision, mAP@0.5 precision, F1 value, Box loss accuracy, and more. Comparison with the original YOLOv7 model shows an improvement in the F1 recognition rate from 89% to 95%, and the overall mAP@0.5 has also increased to 80%. © 2024 IEEE.

关键词： Object detection

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K-Fold Cross-Validation Analysis for Student Status Prediction Using Classification Models 7

K-Fold Cross-Validation Analysis for Student Status Predicti...

引用

7th international conference on information technology, information Systems and Electrical Engineering, ICITISEE 2023

作者： Ridwan, Mohammad Wahyono, Teguh Iriani, Ade Darmastuti, Rini Sukisno Nugroho, Asep Hardiyanto Wacana Christian University Shekh Yusuf Islamic University Computer Science Satya Salatiga Indonesia Satya Wacana Christian University Computer Science Salatiga Indonesia Shekh Yusuf Islamic University Tangerang Indonesia

ISBN: (纸本)9798350382266

Predicting the academic status of students in full-scale study processes is crucial for universities in designing institutional planning and accurate resource allocation. It can also help identify students who may require early intervention, thereby avoiding serious strategic impacts of student status on institutional sustainability. Machine learning (ML), a branch of artificial intelligence, can be used to predict the academic status of students by considering the factors that continuously influence their academic performance. this research aims to develop a model that offers optimal student status predictions for universities. To achieve this goal, researcher developed an approach for predicting student status using four models: Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (Tree), and Naive Bayes (NB). In order to optimize the processing of the dataset, researcher used K-fold Cross Validation (KCV) for handling imbalanced datasets. this approach yielded the best results when the original imbalanced dataset was transformed using K-fold Cross Validation (KCV) technique. the RF method demonstrated a dominant advantage over other methods, achieving the highest accuracy score of 92% on the 4th fold. However, the other methods also showed significant performance improvements, with accuracy scores ranging from high to low, including 91.9% (Decision Tree), 89.6% (Naive Bayes), and 84.8% (Artificial Neural Network). © 2023 IEEE.

关键词： Forecasting

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Radar Signal Pre-sorting Based on Mean-Shift Algorithm 7

Radar Signal Pre-sorting Based on Mean-Shift Algorithm

引用

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

作者： Zhu, Rongqing Wang, Chaoyu Jin, Songpo Zhang, Jingrong Lu, Ming Li, Hongtao Nanjing University of Science and Technology School of Electronic and Optical Engineering Nanjing China China Shipbuilding Industry Corporation Nanjing Marine Radar Institute Nanjing China Electronics Technology Group Corp 54th Research Institute Shijiazhuang China

ISBN: (纸本)9781665478571

Radar signal pre-sorting, generally adopts a clustering algorithm, which can reduce the workload for the next main sorting. However, the traditional clustering algorithm is employed with inherent defects - strong stochasticity, poor robustness and burdensome computation. To reduce these limitations, the principle of K-Mean algorithm is studied to analyze its merits, and a pre-sorting model based on Mean-Shift (PSMS) algorithm is proposed. the sorting accuracy and performance of K-Means and Mean-Shift algorithms are analyzed by using the same batch of radar signals. through computer simulation analysis, the conclusion is drawn that Mean-Shift algorithm has certain superiority and application value in radar signal pre-sorting. © 2022 IEEE.

关键词： K-means clustering

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three-Step Intelligent Pruning for Data Classification in Just-in-Time Software Defect Prediction 7

Three-Step Intelligent Pruning for Data Classification in Ju...

引用

7th international conference on computer and information processing technology, iscipt 2022

作者： Luo, Nan Ma, Ying Department of Computer and Information Engineering Xiamen University of Technology Xiamen China

Just-in-time software defect prediction technology is a defect prediction method that enables defect prediction of software change levels. the difficulties of learning classifiers from imbalanced data is demonstrated in a variety of real-world applications,especially in this era of big data, which has generated more classification tasks. Researchers have taken many existing JIT-SDP efforts to assume that the features of software releases remain costant over time. However, the researchers did not consider that JIT-SDP may be affected by the gradual evolution of class imbalance. Specifically, class imbalance (that is, the number of changes caused by defects is not adequately represented) has been changing over time, and the number of clean class changes and defect class changes may both increase or decrease, so here In this case, the existing JIT-SDP method becomes inapplicable. Taking these factors into consideration, we propose a new imbalanced classification framework, which aims to achieve data class balance by applying a new three-step smart pruning strategy, i.e., first undersampling the majority class, then undersampling the minority class. Oversampling is performed, since the minority class becomes the majority class after oversampling, as a result, the final stage is to intelligently undersample the minority group that eventually becomes the dominant group. through these three steps, data balance is achieved before classification. Experiments show that this new framework is very computationally efficient, leading to better performance even under highly imbalanced distributions of clean and defective data. At the same time, our proposed framework can also be easily adapted to most existing learning methods to improve their performance on imbalanced data. © 2022 Copyright for this paper by its authors.

关键词： Defects

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