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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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Defect Detection of Agricultural Commodities using Image Processing and Artificial Neural Networks

Defect Detection of Agricultural Commodities using Image Pro...

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2022 International Seminar on Application for technology of information and Communication, iSemantic 2022

作者： Suprijono, Herwin Kartikadarma, Etika Yusianto, Rindra Marimin, Marimin Dian Nuswantoro University Faculty of Engineering Department of Electrical Engineering Semarang53192 Indonesia Dian Nuswantoro University Study Program of Information Technology Faculty of Computer Science Semarang53192 Indonesia Dian Nuswantoro University Faculty of Engineering Department of Industrial Engineering Semarang53192 Indonesia Faculty of Agricultural Engineering and Technology Department of Agro-Industrial Technology West Java Bogor16002 Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

Production losses of agricultural commodities on agricultural land due to product defects depend on the level of pest and disease attacks. Defects cause the product not to be harvested or rejected by the market. Data from the Ministry of Agriculture of the Republic of Indonesia in 2021 shows the percentage of defective products for this commodity is 5%. This study aims to detect defects in agricultural products using image processing and artificial neural networks. We used the screening threshold method with potato research samples from Dieng, Indonesia. The study results for spot defects showed that from 100 training data, there were five incorrect identification data, so the accuracy of the training process was 95%. At the same time, the hole defect accuracy is better, which is 97%. It shows that defects in agricultural commodities can be detected using this method. For further research, the development of agricultural product sorting can combine sorting techniques with this method. © 2022 IEEE.

关键词： Defects

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Pillow for Detecting Snoring with Embedded Techniques for Elderly People with Snoring Problems

Pillow for Detecting Snoring with Embedded Techniques for El...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Worawut Yimyam Mahasak Ketcham Thittaporn Ganokratanaa Patiyuth Pramkeaw Narumol Chumuang Department. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Department of Information Technology Management King Mongkut's University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Department of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand

This research aimed to design, produce, and assess a snoring detection neck pillow for elderly individuals with snoring symptoms. The research process began with finding information on snoring. The data obtained were used to design a snore detection neck pillow in the form of a U-shaped neck pillow. The functional principle was that when the microphone module detects the snoring sound, it activates a vibrating motor to alert the snorer to awake or change sleeping positions and stop snoring. There was a program to control the operation. The results of the snoring detection neck pillow test with a sample size of 20 people showed an average efficiency of 80%.

关键词： Performance evaluation Technological innovation Sleep apnea Neck Delays Older adults Cybernetics

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Smart Agricultural Greenhouses for Earthworm Farming

Smart Agricultural Greenhouses for Earthworm Farming

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Cybernetics and Innovations (ICCI), International Conference on

In this research, the design of the earthworm rearing house was presented. Internet of Things, in which the research has designed houses and various equipment to be designed. The results showed that the traditional way of raising earthworms by walking to check the humidity in the cultured basin by touching and regularly watering compared to using the IOT system to measure the moisture. And there is a notification when the humidity drops below or above the specified threshold. and has an automatic watering system when the humidity is below a specified threshold It was found that the IOT-based method was more productive than the traditional method.

关键词： Legged locomotion Technological innovation Insects Humidity measurement Moisture Humidity Soil

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Exploring Collaborative Distributed Diffusion-Based AI-Generated Content (AIGC) in Wireless Networks

arXiv

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In Shen, Xuemin Poor, H. Vincent The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

Driven by advances in generative artificial intelligence (AI) techniques and algorithms, the widespread adoption of AI-generated content (AIGC) has emerged, allowing for the generation of diverse and high-quality content. Especially, the diffusion model-based AIGC technique has been widely used to generate content in a variety of modalities. However, the real-world implementation of AIGC models, particularly on resource-constrained devices such as mobile phones, introduces significant challenges related to energy consumption and privacy concerns. To further promote the realization of ubiquitous AIGC services, we propose a novel collaborative distributed diffusion-based AIGC framework. By capitalizing on collaboration among devices in wireless networks, the proposed framework facilitates the efficient execution of AIGC tasks, optimizing edge computation resource utilization. Furthermore, we examine the practical implementation of the denoising steps on mobile phones, the impact of the proposed approach on the wireless network-aided AIGC landscape, and the future opportunities associated with its real-world integration. The contributions of this paper not only offer a promising solution to the existing limitations of AIGC services but also pave the way for future research in device collaboration, resource optimization, and the seamless delivery of AIGC services across various devices. Our code is available at https://***/HongyangDu/DistributedDiffusion. © 2023, CC BY.

关键词： Wireless networks

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Identification of Beef Freshness Using Linear Discriminant Analysis (LDA) Algorithm and Extraction of HSV Values

Identification of Beef Freshness Using Linear Discriminant A...

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Electronic and Electrical Engineering and Intelligent System (ICE3IS), International Conference on

作者： Riduwan Napianto Agung Tri Prastowo Agung Deni Wahyudi Wajiran Yohanes Egi Pratama Yudoutomo Arico Ayani Suparto Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Information Technology Education Study Program STKIP PGRI Situbondo Situbondo Indonesia

ISBN: (纸本)9781665465427

To determine the quality of beef, it is usually seen using a flashlight and matching it with a predetermined color standard. However, this method is time consuming and the results are inconsistent due to human visual limitations. This study aims to identify the freshness of beef based on its color characteristics using feature extraction method with HSV and LDA method for identification. The identification process begins with the transformation process from RGB images to L*a*b, then image segmentation serves to separate one object from another and image identification uses the LDA method with feature extraction using HSV. The use of color feature extraction with the HSV algorithm to assist in obtaining information from the colors contained in the image for easy identification. Furthermore, the LDA algorithm has a function to obtain the maximum projection to obtain a smaller dimensional space so that the desired patterns can be separated through the boundary line of a linear equation so as to form a certain class or group. Based on the test results using the confusion matrix, it produces a precision value of 80%, recall of 84%, and accuracy of 82%.

关键词： Visualization Image segmentation Image color analysis Shape Feature extraction Mathematical models Linear discriminant analysis

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Globally Harmonized System Label detection using Color Segmentation

Globally Harmonized System Label detection using Color Segme...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Thidarat Pinthong Mahasak Ketcham Thittaporn Ganokratanaa Patiyuth Pramkeaw Narumol Chumuang Department. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Department of Information Technology Management King Mongkut's University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Department of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand

This paper presents an approach for color detection and segmentation based on Image Processing Process to retrieve candidate regions of GHS Sign. For color classification, where the dimension of each vector can be extended by a group of neighboring pixels. The experimental results are highly accurate and robust for our testing database, where samples are recorded on various states of environment. But in the meantime, it was found that the error processing. It is an image that looks asymmetrical image. It is impossible to detect the symbol GHS.

关键词： Image segmentation Technological innovation Image resolution Image color analysis Shape Symbols Transportation

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Coffee Roast Intelligence

arXiv

引用

arXiv 2022年

作者： Ontoum, Sakdipat Khemanantakul, Thitaree Sroison, Pornphat Triyason, Tuul Watanapa, Bunthit Computer Science Program School of Information Technology Bangmod Thung-Khru Bangkok Thailand King Mongkut's University of Technology Thonburi Bangmod Thung-Khru Bangkok Thailand

As the coffee industry has grown, there would be more demand for roasted coffee beans, as well as increased rivalry for selling coffee and attracting customers. As the flavor of each variety of coffee is dependent on the degree of roasting of the coffee beans, it is vital to maintain a consistent quality related to the degree of roasting. Each barista has their own method for determining the degree of roasting. However, extrinsic circumstances such as light, fatigue, and other factors may alter their judgment. As a result, the quality of the coffee cannot be controlled. The "Coffee Roast Intelligence" application is a machine learning-based study of roasted coffee bean degrees classification produced as an Android application platform that identifies the color of coffee beans by photographing or uploading them while roasting. This application displays the text showing at what level the coffee beans have been roasted, as well as informs the percent chance of class prediction to the consumers. Users may also keep track of the result of the predictions related to the roasting level of coffee beans. © 2022, CC BY-SA.

关键词： Machine learning

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Automatic computer Shutdown with Image Processing via Webcam to Save Energy

Automatic Computer Shutdown with Image Processing via Webcam...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Narumol Chumuang Mahasak Ketcham Thittaporn Ganokratanaa Patiyuth Pramkeaw Worawut Yimyam Chuamoo Dep. of Digital Media Technology Muban Chombueng Rajabhat University (MCRU) Thailand Dep. of Information Technology Management King Mongkut's University of Technology North Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Thailand

The purpose of this research is to help save electricity within organizations and workplaces that use computers. Due to the behavior of general users today, they do not give importance to saving electricity. The researcher has developed an automatic computer shutdown system. with image processing via a webcam By using image processing techniques (Image Processing) applied to a webcam. By using a webcam to capture the user on the computer screen. Then the images are analyzed and examined with the principles of image processing with the Face Detection technique using the algorithm of Haar-like Features to detect human faces and ROI. Define a specific area of interest The system will then check the amount of inactivity on the screen. or does not show the face image within 10 minutes, the system will automatically turn off the computer. with image processing This research can make it easier to turn off computers when not in use. and helps to save electricity for the organization or agencies as well.

关键词： computers Performance evaluation Technological innovation Webcams Organizations Inspection Feature extraction

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Sorting Red and Green Chilies by Digital Image Processing

Sorting Red and Green Chilies by Digital Image Processing

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Cybernetics and Innovations (ICCI), International Conference on

作者： Narumol Chumuang Mahasak Ketcham Thittaporn Ganokratanaa Patiyuth Pramkeaw Jiratha Chongsri Worawut Yimyam Dep. of Digital Media Technology Muban Chombueng Rajabhat University (MCRU) Thailand Dep. of Information Technology Management King Mongkut's University of Technology North Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Thailand

The purpose of this research is to help save electricity within organizations and workplaces that use computers. Due to the behavior of general users today, they do not give importance to saving electricity. This work has developed an automatic computer shutdown system. with image processing via a webcam by using image processing techniques (image processing) applied to a webcam by using a webcam to capture the user on the computer screen. Then the images are analyzed and examined with the principles of image processing with the face detection technique using the algorithm of Haar -like features to detect human faces and ROI. define a specific area of interest. The system will then check the amount of inactivity on the screen. or does not show the face image within 10 minutes, the system will automatically turn off the computer. with image processing. This work can make it easier to turn off computers when not in use. and helps to save electricity for the organization or agencies as well.

关键词： computers Technological innovation Webcams Digital images Employment Organizations Feature extraction

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