• Title/Summary/Keyword: Build Tools

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Compact Robotic Arm to Assist with Eating using a Closed Link Mechanism (크로스 링크 기구를 적용한 소형 식사지원 로봇)

  • 강철웅;임종환
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.3
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    • pp.202-209
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    • 2003
  • We succeeded to build a cost effective assistance robotic arm with a compact and lightweight body. The robotic arm has three joints, and the tip of robotic arm to install tools consists of a closed link mechanism, which consisted of two actuators and several links. The robotic arm has been made possible by the use of actuators typically used in radio control devices. The controller of the robotic arm consists of a single chip PIC only. The robotic arm has a friendly user interface, as the operators are aged and disabled in most cases. The operator can manipulate the robotic arm by voice commands or by pressing a push button. The robotic arm has been successfully prototyped and tested on an elderly patient to assist with eating. The results of field test were satisfactory.

Detection of Political Manipulation through Unsupervised Learning

  • Lee, Sihyung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.1825-1844
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    • 2019
  • Political campaigns circulate manipulative opinions in online communities to implant false beliefs and eventually win elections. Not only is this type of manipulation unfair, it also has long-lasting negative impacts on people's lives. Existing tools detect political manipulation based on a supervised classifier, which is accurate when trained with large labeled data. However, preparing this data becomes an excessive burden and must be repeated often to reflect changing manipulation tactics. We propose a practical detection system that requires moderate groundwork to achieve a sufficient level of accuracy. The proposed system groups opinions with similar properties into clusters, and then labels a few opinions from each cluster to build a classifier. It also models each opinion with features deduced from raw data with no additional processing. To validate the system, we collected over a million opinions during three nation-wide campaigns in South Korea. The system reduced groundwork from 200K to nearly 200 labeling tasks, and correctly identified over 90% of manipulative opinions. The system also effectively identified transitions in manipulative tactics over time. We suggest that online communities perform periodic audits using the proposed system to highlight manipulative opinions and emerging tactics.

Android Application for Connecting Cycling Routes on Strava Segments

  • Mulasastra, Intiraporn;Kao-ian, Wichpong
    • Journal of information and communication convergence engineering
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    • v.17 no.2
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    • pp.142-148
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    • 2019
  • Relatively few countries provide separate bicycle lanes for cyclists. Hence, tools for suggesting cycling routes are essential for a safe and pleasant cycling experience. This study aims to develop a mobile application to build cycling routes based on user preferences, specifically location, search radius, ride distance, and number of optimal routes. Our application calls the Strava API to retrieve Strava cycling segments crowdsourced from the cycling community. Then, it creates a graph consisting of the start and end points of these segments. Beginning from a user-specified location, the depth-first search algorithm (DFS) is applied to find routes that conform to the user's preferences. Next, a set of optimal routes is obtained by computing a trade-off ratio for every discovered route. This ratio is calculated from the lengths of all segments and the lengths of all connecting paths. The connected routes can be displayed on a map on an Android device or exported as a GPX file to a bike computer. Future work must be performed to improve the design of the user interface and user experience.

Big Data Astronomy: Large-scale Graph Analyses of Five Different Multiverses

  • Hong, Sungryong
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.2
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    • pp.36.3-37
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    • 2018
  • By utilizing large-scale graph analytic tools in the modern Big Data platform, Apache Spark, we investigate the topological structures of five different multiverses produced by cosmological n-body simulations with various cosmological initial conditions: (1) one standard universe, (2) two different dark energy states, and (3) two different dark matter densities. For the Big Data calculations, we use a custom build of stand-alone Spark cluster at KIAS and Dataproc Compute Engine in Google Cloud Platform with the sample sizes ranging from 7 millions to 200 millions. Among many graph statistics, we find that three simple graph measurements, denoted by (1) $n_\k$, (2) $\tau_\Delta$, and (3) $n_{S\ge5}$, can efficiently discern different topology in discrete point distributions. We denote this set of three graph diagnostics by kT5+. These kT5+ statistics provide a quick look of various orders of n-points correlation functions in a computationally cheap way: (1) $n = 2$ by $n_k$, (2) $n = 3$ by $\tau_\Delta$, and (3) $n \ge 5$ by $n_{S\ge5}$.

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A Study on the Implementation of Smart Farm Environment Control System Using Unity and Photon (Unity와 Photon을 활용한 스마트 팜 환경 제어 시스템 구현에 관한 연구)

  • Jung, Hyeon Ji;Lee, Wan Bum
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.1
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    • pp.104-107
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    • 2021
  • Unity programs are largely recognized as game development tools. However, it has many functions built in, so it can be applied to various fields as well as game development. Therefore, in this paper, we propose a smart farm environmental control program using Unity and Photon. The proposed program has vast compatibility that is not limited to specific devices, and it is very easy to build network systems for remote control. In addition, the proposed programs were installed on various devices such as pc and smartphones, making it easy to control the smart farm environment system. Through experiments, it was confirmed that data transmission and reception between Windows and Android, other operating system environments, and that smart farm systems were operating normally.

Managing the Heterogeneous File System for Anti-Virus

  • Kim, Kyung-Su;Han, Seung-Jo;Kim, Pan-Koo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.7 no.3
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    • pp.3-10
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    • 1997
  • Computer viruses are increasing in number and are continually intellectualized as well. To cope with this problem, anti-virus tools such as a scanner and the monitoring program have been developed. But it is not guaranteed that these softwares will work in safety under MS-DOS' control. If the virus is run first, it can avoid the monitoring of anti-virus software or even can attack the anti-virus software. Therefore, anti-virus programs should be run before the system is infected. This paper presents a new PC starting mechanism which allows the PC system to start from a clean state after booting. For this mechanism, we build a new disk file system different from DOS' file system, and manage the two file systems heterogeneously. Our system is strong against boot viruses and recovers from infections automatically.

A Semi-supervised Learning of HMM to Build a POS Tagger for a Low Resourced Language

  • Pattnaik, Sagarika;Nayak, Ajit Kumar;Patnaik, Srikanta
    • Journal of information and communication convergence engineering
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    • v.18 no.4
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    • pp.207-215
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    • 2020
  • Part of speech (POS) tagging is an indispensable part of major NLP models. Its progress can be perceived on number of languages around the globe especially with respect to European languages. But considering Indian Languages, it has not got a major breakthrough due lack of supporting tools and resources. Particularly for Odia language it has not marked its dominancy yet. With a motive to make the language Odia fit into different NLP operations, this paper makes an attempt to develop a POS tagger for the said language on a HMM (Hidden Markov Model) platform. The tagger judiciously considers bigram HMM with dynamic Viterbi algorithm to give an output annotated text with maximum accuracy. The model is experimented on a corpus belonging to tourism domain accounting to a size of approximately 0.2 million tokens. With the proportion of training and testing as 3:1, the proposed model exhibits satisfactory result irrespective of limited training size.

Naive Bayes classifiers boosted by sufficient dimension reduction: applications to top-k classification

  • Yang, Su Hyeong;Shin, Seung Jun;Sung, Wooseok;Lee, Choon Won
    • Communications for Statistical Applications and Methods
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    • v.29 no.5
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    • pp.603-614
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    • 2022
  • The naive Bayes classifier is one of the most straightforward classification tools and directly estimates the class probability. However, because it relies on the independent assumption of the predictor, which is rarely satisfied in real-world problems, its application is limited in practice. In this article, we propose employing sufficient dimension reduction (SDR) to substantially improve the performance of the naive Bayes classifier, which is often deteriorated when the number of predictors is not restrictively small. This is not surprising as SDR reduces the predictor dimension without sacrificing classification information, and predictors in the reduced space are constructed to be uncorrelated. Therefore, SDR leads the naive Bayes to no longer be naive. We applied the proposed naive Bayes classifier after SDR to build a recommendation system for the eyewear-frames based on customers' face shape, demonstrating its utility in the top-k classification problem.

The Effectiveness of a Program in Activities for Early Students to Develop Some of the Basic Skills Needed for the Age of Artificial Intelligence

  • Adelah Abdulhamid Abdulwahab, Rajab
    • International Journal of Computer Science & Network Security
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    • v.22 no.12
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    • pp.239-244
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    • 2022
  • The study aimed to build a program in activities for early childhood students to develop some of the basic skills necessary for the age of artificial intelligence, to achieve the objectives of the study , the researcher used the experimental design, and the research sample consisted of 37 early childhood students. The study used the following tools: Experimental treatment subject: the proposed program in the activities, Measurement and evaluation tool: testing the basic skills needed for the age of artificial intelligence. The study concluded several results: There is a statistically significant difference (α≤0.05) between the average grades of the early childhood students in the research group in the tribal and remote measurements to test the basic skills necessary for the age of artificial intelligence in favor of the students grades in the dimensional measurements. Practical application of the study through benefiting from the proposed program of activities prepared in the current study in planning and implementing activities to develop the basic skills necessary for the age of artificial intelligence among early childhood students.

Metaverse Interaction Technology Trends and Development Prospects (메타버스 상호작용 기술 동향 및 발전 전망)

  • S.M. Baek;Y.H. Lee;J.Y. Kim;S.H. Park;Y.-H. Gil
    • Electronics and Telecommunications Trends
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    • v.39 no.2
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    • pp.12-23
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    • 2024
  • The Metaverse industry is developing rapidly, and related technologies are being actively improved. Tools such as controllers, keyboards, and mouses are used to interact in the Metaverse, but they are not natural and intuitive interfaces to resemble real-world interactions. Immersive interaction in a Metaverse space requires the engagement of various senses such as vision, touch, and proprioception. Moreover, in terms of body senses, it requires a sense of body ownership and agency. In addition, eliciting cognitive and emotional empathy based on non-verbal expression, which cannot be suitably conveyed to the digital world, requires higher-level technologies than existing emotion measurement solutions. This diversity of technologies can converge to build an immersive realistic Metaverse environment. We review the latest research trends in technologies related to immersive interactions and analyze future development prospects.