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检索条件"任意字段=2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2022"

共 962 条记录，以下是361-370 订阅

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Code management platform of PLC in tobacco primary processing

Code management platform of PLC in tobacco primary processin...

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2022 ieee asia-pacific conference on Image Processing, Electronics and computers, IPEC 2022

作者： Jianhua, Cui Jin, Meng Huaizhong, Shi Shuangqiang, Luo Chuhao, Shi Xiangyun, Zhang Tao, Ou Yang, Yang China Tobacco Henan Industrial Co. Ltd. Anyang Cigarette Factory Anyang China Hunan University College of Computer Science and Electronic Engineering Changsha China

ISBN: (纸本)9781665409025

As one of the fundamental ideas of software configuration management, reversion control has been widely valued and applied in IT industry. But in the traditional industrial field, this idea has not been widely recognized, and software developers in this field have troubles in code storing, tracking, managing, security disclosure and so on. In order to solve these problems, a two-way encryption reversion control system for tobacco primary processing electronic control is presented. In addition to the implementation of reversion traceability, paralleled code development, modification and update in real time, and unified storage management, in order to eliminate the omission of the code and code leaks in the process of development, additional bilateral control and code encryption were realized. © 2022 ieee.

关键词： Servomechanisms

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IoT-Powered Pest Management System for Chili Plants: Analyzing the Effects of Various Light Spectrum Towards Pest and Plant Health

IoT-Powered Pest Management System for Chili Plants: Analyzi...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Muhamad Ahmad Hasyer Ahmad Muzakker Khalid Navod Neranjan Joshua Belayan Faizah Metali Hayati Yassin Muhammad Saifullah Abu Baka Faculty of Integrated Technologies Universiti Brunei Darussalam Brunei Darussalam Faculty of Science Universiti Brunei Darussalam Environmental and Life Sciences Programme Brunei Darussalam

Using different light spectra in pest management has gained significant attention due to its potential impact on pest control strategies. This study investigates the effectiveness of the light spectrum in controlling pests and their implications on the health of chili plants. In this regard, we have used an IoT-powered pest management system to monitor and analyze the impacts of the light spectrum on both pests and plant growth. From the experiments, it is evident that, on average, the green-light spectrum showed the most effective protection against pest infestations, while the red-light spectrum showed the least efficacy. Furthermore, in terms of plant health, at day 0 and 7, the chlorophyll contents of chilli plants from Station 3 (violet) and Station 2 (green) were the lowest and greatest, respectively, while at day 14, Station 2 (green) and Station 3 (violet) recorded the lowest and greatest chlorophyll content, respectively. These results suggest that in the early stage of plant growth, green light promoted better plant growth, whereas violet light enhanced growth after 14 days. Overall, this study provides insights into the importance of considering a balanced light spectrum in pest management control strategies and the enhancement of plant growth and health for chilli plants.

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Loss Function Computation using Machine Learning Algorithms based on the effects of Natural Disasters and Plant Diseases on Plant Growth

Loss Function Computation using Machine Learning Algorithms ...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Mohammad faizul Kabir Farzana Chowdhury Raisa Shakib Mahmud Dipto Arif Shakil Md Ashraful Alam Department of Computer Science and Engineering BRAC University Dhaka Bangladesh

Many Machine Learning(ML) architectures have been in use for detecting soil structure, plant diseases and other plant related tasks for many years. So here using Machine Learning we are trying to compute a “Loss Function” which will provide a Loss factor value between (0–1) for determining how different Natural Disasters(particular weather factors) and Plant Diseases affect plant structure (growth) and get an output of how much of the crop is affected. Moreover, the Loss function mainly will help us get a value which will quickly determine plant growth in a particular condition. In addition, for the Disease detection we are going to use images with real life backgrounds which will ensure that there are plants in a particular background and we can still detect the disease. Therefore, our main target will be making the “Loss Function” depending on two factors namely Natural Disasters (particular weather factors) and Plant Diseases. By using our “Loss Function” a Loss factor value will be given as output which considers effects of these two parameters on plant growth.

关键词： Plant diseases Machine learning algorithms Insects Crops Machine learning Soil data engineering

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Multi-dimensional Attention UNet with Variable Size Convolution Group for Road Segmentation in Remote Sensing Imagery 2

Multi-dimensional Attention UNet with Variable Size Convolut...

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2nd asia-pacific conference on Communications Technology and computer science, ACCTCS 2022

作者： Zou, Wenjie Feng, Dacang University of Science and Technology of China Anhui Hefei230052 China

ISBN: (纸本)9781665400343

The information extraction of high-resolution remote sensing images is an increasingly important part in essential urban planning, geological survey, and disaster monitoring. High-resolution feature information helps us quickly understand the arrangement of ground targets in an area. This article proposes a model called MDAUNet with multi-dimensional attention module, based on different dimensional information of road feature maps for attention. Besides, we use a variable size convolution group (VCG) module in resnet embedded to obtain better road representation. At the same time, to obtain road feature information at different levels in the decoding part, we adopt the dense connection of the decoding part to optimize the feature map of the decoding part. Our proposed road multi-dimensional information attention network has achieved superior performance on the Ottawa road dataset and CHN-CUG road dataset, its performance far exceeds the national art level. © 2022 ieee.

关键词： Convolution

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Research on the Modular System of Tourism Practice Course Based on computer Big data Technology

Research on the Modular System of Tourism Practice Course Ba...

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2022 ieee asia-pacific conference on Image Processing, Electronics and computers, IPEC 2022

作者： Bai, Yang Henan Vocational College of Agriculture Zhengzhou China

ISBN: (纸本)9781665409025

'Research on the application of professional interactive teaching platform for tour guides based on virtual reality technology (VR)' is based on 3D real scene technology, combined with today's advanced image simulation display technology, splicing image edge fusion technology, automatic tracking recording and broadcasting technology, computer A special solution for simulated tour guide teaching and training developed by network and multimedia technology. The article describes the interactive module, audio-visual system and interactive interface (UI) design method of the tour guide training platform in the human-computer interaction design process, as well as the three-dimensional modeling, UV coordinate and texture drawing, and three-dimensional scene used in the interactive realization process. Key technologies such as roaming, multimedia embedding and camera animation. © 2022 ieee.

关键词： Big data

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A Review of Heuristic Approaches to Vehicle Routing Problems

A Review of Heuristic Approaches to Vehicle Routing Problems

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8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Buyukozdemir, Kerem Yildiz, Kazim Bas, Anil Uslu, Banu Calis Marmara Univ Inst Pure & Appl Sci Comp Engn Istanbul Turkey Marmara Univ Fac Technol Comp Engn Istanbul Turkey Marmara Univ Fac Engn Comp Engn Istanbul Turkey

ISBN: (纸本)9781665495523

This study reviews the approaches that are based on heuristic methods and include processed GPS data in their solutions for vehicle routing problems. Vehicle routing problems are challenging given their constraints and complexity. Due to the nature of vehicle routing, the appropriate solution must be found within a reasonable timeframe. However, it is not possible to scan the entire solution space and find the optimum solution within the ideal timeframe when the problem's complexity increases because of the number of points and the constraints. In order to solve these kinds of situations, the aim is finding the optimum solution, or the optimum solution as close as possible. This situation reveals some scenarios where heuristic and meta-heuristic algorithms are used as solution algorithms to routing problems. GPS data is included in the solution algorithms to increase the performance of heuristic algorithms and routing solutions. As a result of the processed data, environmental factors such as congestion points, average speed on the route and traffic density according to hours are also taken into account. In this way, more consistent solutions are developed for real-life applications.

关键词： Vehicle routing problem heuristic optimization GPS data data processing

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Performance Improvement for Speaker Detection from Mixed Speech of Multiple Speakers Using Probabilistic Prediction and Combining LPCSE, MFCC and pLPCPD

Performance Improvement for Speaker Detection from Mixed Spe...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Kodai Komatsu Shuichi Kurogi Dept. of Mechanical and Control Eng. Kyushu Institute of Technology Kitakyushu Japan

This paper presents a method for performance improvement using the combination of feature vectors for speaker detection from the mixed speech of multiple speakers. Recently, we have shown that the combination of the linear predictive coding spectral envelope (LPCSE), the Mel-frequency cepstral coefficients (MFCC) and the piecewise linear predictive coding pole distribution (pLPCPD) improves the performance of the speaker verification, where pLPCPD is the feature vector that we have introduced and developed for speaker verification. On the other hand, we have examined a method of speaker verification from the mixed speech of multiple speakers using pLPCPD feature vectors, where we have shown that the recall, or the performance measure for the verification, decreases suddenly with the change of the speech from unmixed to mixed, while the precision does not decrease so much. This paper applies the above method of combining features and the findings on speaker verification to the speaker detection from the mixed speech of multiple speakers using the probabilistic prediction which we are also developing. Through the experiments, we show the performance improvement by the combination of three features and the effectiveness of the pesent prediction method.

关键词： computer science Feature extraction Probabilistic logic data engineering Linear predictive coding Mel frequency cepstral coefficient

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Integrated Big data Analytics Conceptual Framework for Information Sharing across the fast-moving consumer goods industry

Integrated Big Data Analytics Conceptual Framework for Infor...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Bhekifa Radebe Michael Ayomoh Sarma Yadavalli Department of Industrial and Systems Engineering University of Pretorial Pretoria South Africa

Industrial revolution 4.0. (I.R.4.0) has augmented the number of cyber-physical systems (CSP) that generate., store and process data at an unprecedented rate hence., requiring big data (BD) and big data analytics (BDA) technologies. The FMCG consist of complex and dynamic entities., wherein., physical goods and information exchange occur and generate massive amounts of data., classified as big data (BD)., which is siloed., fragmented., etc. and requires BD technologies to be processed. The absence of information integration and data defusion deprives the FMCG SC of opportunities to achieve and maintain balanced demand and supply., reduce inventory holding costs and improve logistic efficiency. The utilization of technologies such as Hadoop., etc. to process and integrate the massive amounts of BD provides streamlined information processes., reduced operational costs., information integration and fusion throughout the diverse SC to achieve accurate., timely and reliable data/information was presented in this paper using a BDA conceptual framework.

关键词： Industries data analysis Costs data integration Big data Predictive models Software

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Web-based Signing of English Text

Web-based Signing of English Text

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Zexi Dai Sathiamoorthy Manoharan Ross Millar Xinfeng Ye School of Computer Science The University of Auckland Auckland New Zealand

Deaf people use sign language to communicate. There is a misconception that deaf people can read the text written in their surrounding spoken language easily. In fact, sign languages have linguistic structures quite different from their surrounding spoken languages. Therefore, a surrounding spoken language is foreign to most deaf people. Hence, the best way to help deaf people understand written text is to convert the text to signs in sign language. This paper presents a system that translates English text to American Sign Language (ASL) gloss and uses an avatar to show the signs. The system has a database that stores the sign pose data for various descriptions in sign gloss. First, the system uses a transformer-based model to translate English to ASL. Then, it looks up the sign pose data database to find the sign pose data for the descriptions in the sign gloss. The sign pose data is used to generate the animations of the signs by an avatar. The system provides a web-based interface, making it widely accessible across multiple platforms. Experiments show that the translation from text to sign language gloss achieves a good accuracy.

关键词： databases Avatars Gesture recognition Assistive technologies Linguistics Animation Transformers

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Research on Optimizing the Intelligent Recommendation System of College Courses by Machine Learning Algorithm

Research on Optimizing the Intelligent Recommendation System...

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2025 asia-Europe conference on Cybersecurity, Internet of Things and Soft Computing, CITSC 2025

作者： Zhang, Lei Qian, Feng School of Mathematics and Computer Science Tongling University Tongling China

ISBN: (纸本)9798331504205

This paper proposes a course intelligent recommendation system based on machine learning algorithm to achieve more accurate personalized recommendation. The system uses deep learning model to design an optimized recommendation algorithm by collecting and analyzing multi-dimensional data such as student behavior, course evaluation and personal interests. Collaborative filtering, content-based filtering and deep-learning algorithm based on graph convolutional network (GCN) are introduced to convert the course recommendation problem into a multi-objective optimization problem, and the recommendation precision and the level of personalization are continuously enhanced by training the model. To validate the efficacy of the system, this article conducts extensive model simulation and data analysis. The simulation results show that on a specific data set, the accuracy and recall rate of the recommendation system reach 93% and 88% respectively, which is better than the traditional recommendation algorithm. By comparing with other mainstream algorithms, the recommendation system proposed in this paper performs better in dealing with data sparsity and improving recommendation accuracy, and greatly improves user satisfaction. © 2025 ieee.

关键词： Adversarial machine learning

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