• Title/Summary/Keyword: 모바일 AI

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A mobile P2P a farming support system implementation which uses JXTA (JXTA를 이용한 모바일 P2P 영농 지원 시스템 구현)

  • Bae, Il-Ho;Cho, Ai-Ri;Min, Hae-Ran;Lee, Gwang;Lee, Joon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.579-582
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    • 2004
  • File share system in client/server method requires server of High performance and capacity and this server is very expensive and management is complex and is been influenced much to flatform. Also, extension of correct memory or hard drive etc. causes a lot of expenses to server. While, may minimise human who happen by buying high-capacity server by dispersing file public ownership way unuse expensive server in client/serve. way who put up files in PC(client) to a sewer and manage files and make use of only client computers because public ownership of data and government official in P2P(peer to peer) environment, waste of material resources. Many people are interested to P2P by such reason, researches that use P2P to connection field to be Moba that have Gakgwangbatgo current are gone vigorously.

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Mileage-based Asymmetric Multi-core Scheduling for Mobile Devices (모바일 디바이스를 위한 마일리지 기반 비대칭 멀티코어 스케줄링)

  • Lee, Se Won;Lee, Byoung-Hoon;Lim, Sung-Hwa
    • Journal of Korea Society of Industrial Information Systems
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    • v.26 no.5
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    • pp.11-19
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    • 2021
  • In this paper, we proposed an asymmetric multi-core processor scheduling scheme which is based on the mileage of each core. We considered a big-LITTLE multi-core processor structure, which consists of low power consuming LITTLE cores with general performance and high power consuming big cores with high performance. If a task needs to be processed, the processor decides a core type (big or LITTLE) to handle the task, and then investigate the core with the shortest mileage among unoccupied cores. Then assigns the task to the core. We developed a mileage-based balancing algorithm for asymmetric multi-core assignment and showed that the proposed scheduling scheme is more cost-effective compared to the traditional scheme from a management perspective. Simulation is also conducted for the purpose of performance evaluation of our proposed algorithm.

Community Health Center Digital Transition (마을 건강센터 디지털 전환)

  • Han, Jeong-won;Han, June-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.514-516
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    • 2022
  • Busan Metropolitan City runs Community Health Center which aims to health care service based on the community, besides the established health medical service towards people with low-income. 71 centers are run in 2021, therefore, this papear explores the way of digital transition of these centers. Digital Technologies possibly adopted inside the centers are: First, smart devices to advance the management system of chronical diseases based on health index; Second, IoT with mobile tech to manage health index; Third, AI Robot to care lone elderly people and to warn the emergency.

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Design of Location Recognition and ID Identification for NFT Reports in Metaverse-based Field_study Trip (메타버스기반 체험학습 NFT보고서의 위치인식과 ID식별 설계)

  • Mingoo Kang
    • Smart Media Journal
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    • v.12 no.9
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    • pp.38-44
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    • 2023
  • In this paper, a blockchain-based platform of NFT(Non-Fungible Token) reports was proposed to ensure the reliable performance contents of field study trip. It is possible to identify and manage the personal multi biomeric authentication user ID of activity records for students in a mobile IP-based metaverse with the linkage of extended reality(XR). At this time, many quests and incentives of platform are provided to induce students to experience smart and fun field studying facilities by linking real trip experiences and virtual extended_reality studies in the metaverse interworking.

A Comparative Study on Discrimination Issues in Large Language Models (거대언어모델의 차별문제 비교 연구)

  • Wei Li;Kyunghwa Hwang;Jiae Choi;Ohbyung Kwon
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.125-144
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    • 2023
  • Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

Development of a Simulator for Optimizing Semiconductor Manufacturing Incorporating Internet of Things (사물인터넷을 접목한 반도체 소자 공정 최적화 시뮬레이터 개발)

  • Dang, Hyun Shik;Jo, Dong Hee;Kim, Jong Seo;Jung, Taeho
    • Journal of the Korea Society for Simulation
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    • v.26 no.4
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    • pp.35-41
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    • 2017
  • With the advances in Internet over Things, the demand in diverse electronic devices such as mobile phones and sensors has been rapidly increasing and boosting up the researches on those products. Semiconductor materials, devices, and fabrication processes are becoming more diverse and complicated, which accompanies finding parameters for an optimal fabrication process. In order to find the parameters, a process simulation before fabrication or a real-time process control system during fabrication can be used, but they lack incorporating the feedback from post-fabrication data and compatibility with older equipment. In this research, we have developed an artificial intelligence based simulator, which finds parameters for an optimal process and controls process equipment. In order to apply the control concept to all the equipment in a fabrication sequence, we have developed a prototype for a manipulator which can be installed over an existing buttons and knobs in the equipment and controls the equipment communicating with the AI over the Internet. The AI is based on the deep learning to find process parameters that will produce a device having target electrical characteristics. The proposed simulator can control existing equipment via the Internet to fabricate devices with desired performance and, therefore, it will help engineers to develop new devices efficiently and effectively.

A Study on the Measures for Detection Error from the Displacement Distortion of the RADAR Waveform (레이더 전파의 왜곡현상에서 오는 탐지 오류 저감 방안 연구)

  • Kim, Jin Hieu;Kim, ChangEun;Lee, Yong-Soo
    • Journal of the Korea Institute of Construction Safety
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    • v.2 no.1
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    • pp.36-44
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    • 2019
  • $21^{st}$ century is digitally civilized era. Technologies such as AI, Iot, Big Data, Mobile and etc makes this era digitally advanced. These advancement of the technology greatly impacted detection range of the radar. Human's eye sight can see about 20Km and hear 20 ~ 20000 Hz. These limitations can be overcome using radar. This radar technology is used in military, aircraft, ship, vehicle and etc. to replace human eye. However, radar technology is capable of making False Alarm Rate. This document will propose the fix of these problems. Radar's distortion includes beam refraction, diffraction and reflection. These inaccurate data result in deterioration of human judgements and my cause various casualties and damages. Radar goes through annual testing to test how many false alarm is being produced. Normal radar usually makes 10 to 20 False alarms. In emergency situation, if operator were to follow this false alarm, this might result in following false object or take 12 more seconds to follow the right object. This problem can be overcome by using different radar data from different places and angles. This helps reduces False Alarm rate and track the object twice as fast.

Digital Transformation Based on Chatbot in Legacy Environment (챗봇을 이용한 Legacy 환경의 Digital Transformation)

  • Jang, Jeong-ho;Kim, Jin-soo;Lee, Kang-Yoon
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.79-85
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    • 2018
  • As the utilization of chatbots grows and the AI market grows, many companies are interested. And everybody is spurring growth by offering chatbot build services so that they can create chatbots. This makes chatbots easier to service on the messenger platform, which is changing the existing application market. In this paper, we present a methodology for designing and implementing existing DB-based applications as instant messenger platform-based applications, and summarize what to consider in actual implementation to provide an optimal system structure. According to this methodology, we design and implement a chatbot that serves as an teaching advisor who provides information to the students in the curriculum. The implemented application objectively visualizes the user's desired information from the user's point of view and delivers it through the interactive interface quickly and intuitively. By implementing these services and real service, it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. Enterprise legacy application will take chatbot technology as one of important digital transformation initiative.

Design of an Intellectual Smart Mirror Appication helping Face Makeup (얼굴 메이크업을 도와주는 지능형 스마트 거울 앱의설계)

  • Oh, Sun Jin;Lee, Yoon Suk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.497-502
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    • 2022
  • Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

Suggestion of Selecting features and learning models for Android-based App Malware Detection (안드로이드 기반 앱 악성코드 탐지를 위한 Feature 선정 및 학습모델 제안)

  • Bae, Se-jin;Rhee, Jung-soo;Baik, Nam-kyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.377-380
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    • 2022
  • An application called an app can be downloaded and used on mobile devices. Among them, Android-based apps have the disadvantage of being implemented on an open source basis and can be exploited by anyone, but unlike iOS, which discloses only a small part of the source code, Android is implemented as an open source, so it can analyze the code. However, since anyone can participate in changing the source code of open source-based Android apps, the number of malicious codes increases and types are bound to vary. Malicious codes that increase exponentially in a short period of time are difficult for humans to detect one by one, so it is efficient to use a technique to detect malicious codes using AI. Most of the existing malicious app detection methods are to extract Features and detect malicious apps. Therefore, three ways to select the optimal feature to be used for learning after feature extraction are proposed. Finally, in the step of modeling with optimal features, ensemble techniques are used in addition to a single model. Ensemble techniques have already shown results beyond the performance of a single model, as has been shown in several studies. Therefore, this paper presents a plan to select the optimal feature and implement a learning model for Android app-based malicious code detection.

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