• 제목/요약/키워드: things classification

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A Study on the Service Improvement Strategies by Enterprise through the Analysis of Customer Response Reviews in Smart Home Applications : Based on the Classification of Functional Elements and Design Elements of smart Home Usability Values (스마트 홈 어플리케이션의 고객반응리뷰분석을 통한 기업별 서비스개선전략에 대한 연구 : 스마트 홈 사용성 가치의 기능적요소와 디자인적 요소 분류를 바탕으로)

  • Heo, Ji Yeon;Kim, Min Ji;Cha, Kyung Jin
    • Journal of Information Technology Services
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    • v.19 no.4
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    • pp.85-107
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    • 2020
  • The Internet of Things market, a technology that connects the Internet to various things, is growing day by day. Besides, various smart home services using IoT and AI (Artificial Intelligence) are being launched in homes. Related to this, existing smart home-related studies focus primarily on ICT technology, not on what service improvements should be made in customer positions. In this study, we will use smart home application customer review data to classify functional and design elements of smart home usability value and examine the ways customers think of service improvement. For this, LG Electronics and Samsung Electronics" Smart Home application, the main provider of Smart Home in Korea, customer reviews were crawled to conduct a comparative analysis between them. In this study, the review of IoT home-applications was analyzed to find service improvement insights from customer perspective, and related analysis of text mining, social network analysis and Doc2vec was used to efficiently analyze data equivalent to about 16,000 user reviews. Through this research, we hope that related companies effectively seek ways to improve smart home services that reflect customer needs and are expected to help them establish competitive strategies by identifying weaknesses and strengths among competitors.

Analysis of IoT Usage in Korean Key Manufacturing Industries (주요 제조업의 사물인터넷 활용성 분석)

  • Hwang, Gyusun;Park, Juhyung;Lee, Jeongcheol;Park, Jinwoo;Chang, Tai-Woo;Won, Joongyeon
    • The Journal of Society for e-Business Studies
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    • v.21 no.4
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    • pp.81-93
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    • 2016
  • Internet of Things (IoT) has been established in various industries and IoT technology is highlighted as a new value creation technology. Especially, Korean government has launched Manufacturing Innovation 3.0 Strategy for developing Smart Factory concept to improve national and corporate's competitiveness. This study tries to present new industry classification scheme considering 10 national key manufacturing industries. Based on the new scheme, 10 national main forces industries are categorized into 6 segments. We have conducted SWOT analysis to comprehend Korean IoT environment. Based on the analysis, we have positioned 6 segments at the strategic decision-making grid to analyze industries' IoT practical usage.

A study of bioindicator selection for long-term ecological monitoring

  • Han, Yong-Gu;Kwon, Ohseok;Cho, Youngho
    • Journal of Ecology and Environment
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    • v.38 no.1
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    • pp.119-122
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    • 2015
  • It is very useful and important to see the status and change of necessary parts in a short period through selecting and observing the bioindicator continually to forecast and prepare the future. Especially, living things are so closely related to the environment that the indicator between the environment and living things shows close interrelationship. Also, the indicator related to environment provides information about representative or decisive environmental phenomenon and is used to simplify complicated facts. Considering wide range of background and application including various indicators such as the change-, destruction-, pollution-, and restoration of habitats, climate change, and species diversity, the closest category includes "environmental indicator," "ecological indicator," and "biodiversity indicator." The selection and use of bioindicator is complicated and difficult. The necessary conditions for the indicator selection are flexible and greatly depend on the goals of investigation such as the indicator for biological diversity investigation of specific area, the indicator for habitat destruction, the indicator for climate change, and the indicator for polluted area. It should meet many various conditions to select a good indicator. In this study, eleven selection standards are established based on domestic and overseas studies on bioindicator selection: species with clear classification and ecology, species distributed in geographically widespread area, species that show clear habitat characteristics, species that can provide early warning for a change, species that are easy and economically benefited for the investigation, species that have many independent individual groups and that is not greatly affected by the size of individual groups, species that is thought to represent the response of other species, species that represent the ecology change caused by the pressure of human influence, species for which researches on climate change have been done, species that is easy to observe, appears for a long time and forms a group with many individuals, and species that are important socially, economically, and culturally.

A Scheme on Object Tracking Techniques in Multiple CCTV IoT Environments (다중 CCTV 사물인터넷 환경에서의 객체 추적 기법)

  • Hong, Ji-Hoon;Lee, Keun-Ho
    • Journal of Internet of Things and Convergence
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    • v.5 no.1
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    • pp.7-11
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    • 2019
  • This study suggests a methodology to track crime suspects or anomalies through CCTV in order to expand the scope of CCTV use as the number of CCTV installations continues to increase nationwide in recent years. For the abnormal behavior classification, we use the existing studies to find out suspected criminals or abnormal actors, use CNN to track objects, and connect the surrounding CCTVs to each other to predict the movement path of objectified objects CCTVs in the vicinity of the path were used to share objects' sample data to track objects and to track objects. Through this research, we will keep track of criminals who can not be traced, contribute to the national security, and continue to study them so that more diverse technologies can be applied to CCTV.

Relationship between Global Citizenship Education and Geography Education (글로벌 시민성교육과 지리교육의 관계)

  • Cho, Chul Ki
    • Journal of the Korean association of regional geographers
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    • v.19 no.1
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    • pp.162-180
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    • 2013
  • This paper is to explore the relationship between global citizenship education needed to be taught recently and geography. First, the paper examines the concept, as well as the reason why it became important concept in dimension of education in terms of progress of globalization. Second, the paper examines justification of global citizenship education through geography subject through discussion of place, space, scale and interdependence as geographical key concepts. Then, it establishes the category of sub-area of global citizenship education to grasp structurally. This is to reestablish in terms of knowledge and understanding, skill, value and attitude through the inductive examination of existing system of classification. Third, for geography instruction as practical dimension for fostering global citizenship, the paper discusses things to consider previously to design it in terms of aims, contents and methods, and examined instruction strategies in terms of issues-based approach and geographies of resistance. The last, the paper should things to pay attention to be cautious in global citizenship education through geography.

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Analysis of User Head Motion for Motion Classifier of Motion Headset (모션헤드셋의 동작분류기를 위한 사용자 머리동작 분석)

  • Shin, Choonsung;Lee, Youngho
    • Journal of Internet of Things and Convergence
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    • v.2 no.2
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    • pp.1-6
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    • 2016
  • Recently, various types of wearable computers have been studied. In this paper, we analyze the characteristics of head motion information for the operation of the motion classifier produced motion headset that the user can use while listening to music. The prototype receives music from smart phone over bluetooth communications, and transmits the motion information measured by the acceleration sensor to the smart phone. And the smartphone classifies the motion of the head through a motion classifier. we implemented a prototype for our experiment. The user's head motion "up", "down", "left" and "right" were classified using a Bayesian classifier. As a result, in case of the movement of the head "up" and "down", there are a large changes in the x, z-axis values. In future we have a plan to perform a user study to find suitable variables for creating motion classifier.

Kriging Regressive Deep Belief WSN-Assisted IoT for Stable Routing and Energy Conserved Data Transmission

  • Muthulakshmi, L.;Banumathi, A.
    • International Journal of Computer Science & Network Security
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    • v.22 no.7
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    • pp.91-102
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    • 2022
  • With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

Improved Hot data verification considering the continuity and frequency of data update requests (데이터 갱신요청의 연속성과 빈도를 고려한 개선된 핫 데이터 검증기법)

  • Lee, Seungwoo
    • Journal of Internet of Things and Convergence
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    • v.8 no.5
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    • pp.33-39
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    • 2022
  • A storage device used in the mobile computing field should have low power, light weight, durability, etc., and should be able to effectively store and manage large-capacity data generated by users. NAND flash memory is mainly used as a storage device in the field of mobile computing. Due to the structural characteristics of NAND flash memory, it is impossible to overwrite in place when a data update request is made, so it can be solved by accurately separating requests that frequently request data update and requests that do not, and storing and managing them in each block. The classification method for such a data update request is called a hot data identification method, and various studies have been conducted at present. This paper continuously records the occurrence of data update requests using a counting filter for more accurate hot data validation, and also verifies hot data by considering how often the requested update requests occur during a specific time.

Editorial for Vol. 30, Issue 3 (편집자 주 - 30권 3호)

  • Kim, Young Hyo
    • Korean journal of aerospace and environmental medicine
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    • v.30 no.3
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    • pp.83-85
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    • 2020
  • In commemoration of Vol. 30, Issue 3, our journal prepared five review articles and one original paper. The global outbreak of COVID-19 in 2020 has impacted our society, and especially the aviation and travel industries have been severely damaged. Kwon presented the aviation medical examination regulations related to COVID-19 announced by the Ministry of Land, Infrastructure, and Transport of the Republic of Korea. Lim summarized various efforts of airlines to overcome the crisis in the aviation industry. He also discussed the management of these aircraft as the number of airplanes landing for long periods increased. Finally, he suggested various quarantine guidelines at airports and onboard aircraft. COVID-19 has had a profound impact on mental health as well as physical effects. Kim investigated the impact of COVID-19 on mental health and suggested ways to manage the stress caused by it. The Internet of Things (IoT) refers to a technology in which devices communicate with each other through wired or wireless communication. Hyun explained the current state of the technology of the IoT and how it could be used, especially in the aviation field. In the area of airline service, various situations arise between passengers and crew. Therefore, role-playing is useful in performing education to prepare and respond to passengers' different needs appropriately. Ra introduced the conceptual background and general concepts of role-playing and presented the actual role-play's preparation process, implementation, evaluation, and feedback process. For a fighter to fly for a long time and perform a rapid air attack, air refueling is essential, which serves refueling from the air rather than from the aircraft base. Koo developed a questionnaire based on the HFACS (Human Factors Analysis and Classification System) model and used it to conduct a fighter pilot survey and analyze the results.

Design of Customized Research Information Service Based on Prescriptive Analytics (처방적 분석 기반의 연구자 맞춤형 연구정보 서비스 설계)

  • Lee, Jeong-Won;Oh, Yong-Sun
    • Journal of Internet of Things and Convergence
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    • v.8 no.3
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    • pp.69-74
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    • 2022
  • Big data related analysis techniques, the prescriptive analytics methodology improves the performance of passive learning models by ensuring that active learning secures high-quality learning data. Prescriptive analytics is a performance maximizing process by enhancing the machine learning models and optimizing systems through active learning to secure high-quality learning data. It is the best subscription value analysis that constructs the expensive category data efficiently. To expand the value of data by collecting research field, research propensity, and research activity information, customized researcher through prescriptive analysis such as predicting the situation at the time of execution after data pre-processing, deriving viable alternatives, and examining the validity of alternatives according to changes in the situation Provides research information service.