• Title/Summary/Keyword: Big data Processing

Search Result 1,063, Processing Time 0.029 seconds

A Study on Smart Device for Open Platform Ontology Construction of Autonomous Vihicles (자율주행자동차 오픈플랫폼 온톨로지 구축을 위한 스마트디바이스 연구)

  • Choi, Byung Kwan
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.15 no.3
    • /
    • pp.1-14
    • /
    • 2019
  • The 4th Industrial Revolution, intelligent automobile application technology is evolving beyond the limit of the mobile device to a variety of application software and multi-media collective technology with big data-based AI(artificial intelligence) technology. with the recent commercialization of 5G mobile communication service, artificial intelligent automobile technology, which is a fusion of automobile and IT technology, is evolving into more intelligent automobile service technology, and each multimedia platform service and application developed in such distributed environment is being developed Accordingly, application software technology developed with a single system SoC of a portable terminal device through various service technologies is absolutely required. In this paper, smart device design for ontology design of intelligent automobile open platform enables to design intelligent automobile middleware software design technology such as Android based SVC Codec and real time video and graphics processing that is not expressed in single ASIC application software technology as SoC based application designWe have experimented in smart device environment through researches, and newly designed service functions of various terminal devices provided as open platforms and application solutions in SoC environment and applied standardized interface analysis technique and proved this experiment.

Strategy to coordinate actions through a plant parameter prediction model during startup operation of a nuclear power plant

  • Jae Min Kim;Junyong Bae;Seung Jun Lee
    • Nuclear Engineering and Technology
    • /
    • v.55 no.3
    • /
    • pp.839-849
    • /
    • 2023
  • The development of automation technology to reduce human error by minimizing human intervention is accelerating with artificial intelligence and big data processing technology, even in the nuclear field. Among nuclear power plant operation modes, the startup and shutdown operations are still performed manually and thus have the potential for human error. As part of the development of an autonomous operation system for startup operation, this paper proposes an action coordinating strategy to obtain the optimal actions. The lower level of the system consists of operating blocks that are created by analyzing the operation tasks to achieve local goals through soft actor-critic algorithms. However, when multiple agents try to perform conflicting actions, a method is needed to coordinate them, and for this, an action coordination strategy was developed in this work as the upper level of the system. Three quantification methods were compared and evaluated based on the future plant state predicted by plant parameter prediction models using long short-term memory networks. Results confirmed that the optimal action to satisfy the limiting conditions for operation can be selected by coordinating the action sets. It is expected that this methodology can be generalized through future research.

Mini-review on VO2-based Sensors Utilizing Metal-insulator Transition

  • Hyeongyu Gim;Minho Lee;Woojin Hong;Kootak Hong
    • Journal of Sensor Science and Technology
    • /
    • v.33 no.5
    • /
    • pp.265-273
    • /
    • 2024
  • With the advent of artificial intelligence and Internet of Things, demands for high-performance sensors with high sensitivity and ultrafast response for big data acquisition and processing have increased. VO2, a strongly correlated material, has been shown to exhibit a reversible and abrupt resistance change in the sub-nanosecond scale through a phase transition from an insulating to a metallic state at 68℃. The metal-insulator transition (MIT) of VO2 provides the potential for the development of highly sensitive and ultrafast high-performance sensors. This is because it can be triggered by various external stimuli, such as heat, light, gas adsorption/desorption, and strain. Therefore, attempts have been made to develop high-performance sensors by controlling the MIT of VO2 in response to external stimuli. This study reviewed recent progress in various VO2-based sensors that utilize MIT, including photodetectors, gas sensors, and strain sensors. This review is expected to serve as an overview of the approaches for controlling the MIT behavior of VO2 and provide insights into the design of high-performance sensors that exploit MIT.

Analysis of Korean Language Parsing System and Speed Improvement of Machine Learning using Feature Module (한국어 의존 관계 분석과 자질 집합 분할을 이용한 기계학습의 성능 개선)

  • Kim, Seong-Jin;Ock, Cheol-Young
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.51 no.8
    • /
    • pp.66-74
    • /
    • 2014
  • Recently a variety of study of Korean parsing system is carried out by many software engineers and linguists. The parsing system mainly uses the method of machine learning or symbol processing paradigm. But the parsing system using machine learning has long training time because the data of Korean sentence is very big. And the system shows the limited recognition rate because the data has self error. In this thesis we design system using feature module which can reduce training time and analyze the recognized rate each the number of training sentences and repetition times. The designed system uses the separated modules and sorted table for binary search. We use the refined 36,090 sentences which is extracted by Sejong Corpus. The training time is decreased about three hours and the comparison of recognized rate is the highest as 84.54% when 10,000 sentences is trained 50 times. When all training sentence(32,481) is trained 10 times, the recognition rate is 82.99%. As a result it is more efficient that the system is used the refined data and is repeated the training until it became the steady state.

Design and Implementation of a Smart Home Cloud Control System Using Bridge based on IoT (IoT 기반의 브리지를 이용한 스마트 홈 클라우드 제어 시스템 설계 및 구현)

  • Hao, Xu;Kim, Chul-Won
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.12 no.5
    • /
    • pp.865-872
    • /
    • 2017
  • Recently, in response to the Internet age, the demand for hardware devices has been increasing, centering on the rapidly growing smart home field, due to the growth and management of sensor and control technology, mobile application, network traffic, big data management and cloud computing. In order to maintain the sustainable development of the hardware system, it is necessary to update the system, and the hardware device is absolutely necessary in real time processing of complex data (voice, image, etc.) as well as data collection. In this paper, we propose a method to simplify the control and communication method by integrating the hardware devices in two operating systems in a unified structure to solve the simultaneous control and communication method of hardware under different operating systems. The performance evaluation results of the proposed integrated hardware and the cloud control system connected to the cloud server are described and the main directions to be studied in the field of internet smart home are described.

A Design of Permission Management System Based on Group Key in Hadoop Distributed File System (하둡 분산 파일 시스템에서 그룹키 기반 Permission Management 시스템 설계)

  • Kim, Hyungjoo;Kang, Jungho;You, Hanna;Jun, Moonseog
    • KIPS Transactions on Computer and Communication Systems
    • /
    • v.4 no.4
    • /
    • pp.141-146
    • /
    • 2015
  • Data have been increased enormously due to the development of IT technology such as recent smart equipments, social network services and streaming services. To meet these environments the technologies that can treat mass data have received attention, and the typical one is Hadoop. Hadoop is on the basis of open source, and it has been designed to be used at general purpose computers on the basis of Linux. To initial Hadoop nearly no security was introduced, but as the number of users increased data that need security increased and there appeared new version that introduced Kerberos and Token system in 2009. But in this method there was a problem that only one secret key can be used and access permission to blocks cannot be authenticated to each user, and there were weak points that replay attack and spoofing attack were possible. Hence, to supplement these weak points and to maintain efficiency a protocol on the basis of group key, in which users are authenticated in logical group and then this is reflected to token, is proposed in this paper. The result shows that it has solved the weak points and there is no big overhead in terms of efficiency.

A Study on the Theme Selection and Prototype Production for the LX Information Map Service (LX의 정보지도 서비스를 위한 주제선정 및 시범제작)

  • Jeong, Dong-Hoon;Bae, Sang-Keun;Lee, Seong-Gyu
    • Journal of Cadastre & Land InformatiX
    • /
    • v.45 no.1
    • /
    • pp.123-135
    • /
    • 2015
  • In order to satisfy the high expectations of consumers for a variety of consumer's desired subject area, information could be provided in the form of a map according to the analysis information. With the name change in 2015, LX would intend to play a role in building the information infrastructure that can be supported government policy as an intermediary between the government and private sector. Therefore, in this study, we would like to propose a plan that provide personalized information to the consumer. Through compositing a variety of time-series data(inner or outer of LX) based on public information, and analyzing spatially and temporally the rapidly changing land status. For these purpose, prior research and domestic or abroad thematic map service about thematic map making were reviewed. And the reason why the LX makes information map was presented. Also, themes of 3 field were selected, and depending on the data processing or analysis level and theme were subdivided, and then production and expression method were proposed.

Logistic Regression Ensemble Method for Extracting Significant Information from Social Texts (소셜 텍스트의 주요 정보 추출을 위한 로지스틱 회귀 앙상블 기법)

  • Kim, So Hyeon;Kim, Han Joon
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.6 no.5
    • /
    • pp.279-284
    • /
    • 2017
  • Currenty, in the era of big data, text mining and opinion mining have been used in many domains, and one of their most important research issues is to extract significant information from social media. Thus in this paper, we propose a logistic regression ensemble method of finding the main body text from blog HTML. First, we extract structural features and text features from blog HTML tags. Then we construct a classification model with logistic regression and ensemble that can decide whether any given tags involve main body text or not. One of our important findings is that the main body text can be found through 'depth' features extracted from HTML tags. In our experiment using diverse topics of blog data collected from the web, our tag classification model achieved 99% in terms of accuracy, and it recalled 80.5% of documents that have tags involving the main body text.

Discovery of Frequent Sequence Pattern in Moving Object Databases (이동 객체 데이터베이스에서 빈발 시퀀스 패턴 탐색)

  • Vu, Thi Hong Nhan;Lee, Bum-Ju;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
    • /
    • v.15D no.2
    • /
    • pp.179-186
    • /
    • 2008
  • The converge of location-aware devices, GIS functionalities and the increasing accuracy and availability of positioning technologies pave the way to a range of new types of location-based services. The field of spatiotemporal data mining where relationships are defined by spatial and temporal aspect of data is encountering big challenges since the increased search space of knowledge. Therefore, we aim to propose algorithms for mining spatiotemporal patterns in mobile environment in this paper. Moving patterns are generated utilizing two algorithms called All_MOP and Max_MOP. The first one mines all frequent patterns and the other discovers only maximal frequent patterns. Our proposed approach is able to reduce consuming time through comparison with DFS_MINE algorithm. In addition, our approach is applicable to location-based services such as tourist service, traffic service, and so on.

Digital Competencies Required for Information Science Specialists at Saudi Universities

  • Yamani, Hanaa;AlHarthi, Ahmed;Elsigini, Waleed
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.2
    • /
    • pp.212-220
    • /
    • 2021
  • The objectives of this research were to identify the digital competencies required for information science specialists at Saudi universities and to examine whether there existed conspicuous differences in the standpoint of these specialists due to years of work experience with regard to the importance of these competencies. A descriptive analytical method was used to accomplish these objectives while extracting the required digital competency list and ascertaining its importance. The research sample comprised 24 experts in the field of information science from several universities in the Kingdom of Saudi Arabia. The participants in the sample were asked to complete a questionnaire prepared to acquire the pertinent data in the period between January 5, 2021 and January 20, 2021. The results reveal that the digital competencies required for information science specialists at Saudi universities encompass general features such as the ability to use computer, Internet, Web2, Web3, and smartphone applications, digital learning resource development, data processing (big data) and its sharing via the Internet, system analysis, dealing with multiple electronic indexing applications and learning management systems and its features, using electronic bibliographic control tools, artificial intelligence tools, cybersecurity system maintenance, ability to comprehend and use different programming languages, simulation, and augmented reality applications, and knowledge and skills for 3D printing. Furthermore, no statistically significant differences were observed between the mean ranks of scores of specialists with less than 10 years of practical experience and those with practical experience of 10 years or more with regard to conferring importance to digital competencies.