• Title/Summary/Keyword: New Address Information

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Design of IPv6 based UFID(Unique feature Identification) Communication Systems (IPv6기반의 UFID(지형지물유일식별자)통신시스템 설계)

  • Kang, Min-Goo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.3
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    • pp.437-443
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    • 2007
  • In this paper, the design of URL structures and managements for UFID(Unique feature Identification) based wireless communications is presented with the combination of GIS and URL address informations. As a result of IPv6 based UFID wireless communications, new methods for URI(Uniform Resource Identifier) informations and UFID communication systems are proposed with a 6byte coded 128-bit IPv6 DNS system for the presentation of 1,500,000 korean buildings.

Comparative Study of Health Care System in Three Central Asian Countries: Kazakhstan, Kyrgyzstan, Uzbekistan

  • Dronina, Yuliya;Nam, Eun Woo
    • Health Policy and Management
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    • v.29 no.3
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    • pp.342-356
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    • 2019
  • Background: The objectives of the study are to find out the effect of the implementing reform in three Central Asian countries, identify its impact on health status and health care delivery systems. This study address to identify strong and weak points of the health systems and provide a recommendation for further health care organization. Methods: A comparative analysis was conducted to evaluate the effects of implemented policy on health care system efficiency and equity. Secondary data were collected on selected health indicators using information from the World Health Organization Global Health Expenditure Database, European Health Information Platform, and World Bank Open Data. Results: In terms of population status, countries achieved relatively good results. Infant mortality and under-5 mortality rate decreased in all countries; also, life expectancy increased, and it was more than 70 years. Regulations of the health systems are still highly centralized, and the Ministry of Health is the main organ responsible for national health policy developing and implementation. Among the three countries, only Kyrgyzstan was successful in introducing a national health system. Distribution of health expenditure between public expenditure and out-of-pocket payments was decreased, and out-of-pocket payments were less the 50% of total health expenditure in all countries, in 2014. Conclusion: After independent, all three countries implemented a certain number of the policy reform, mostly it was directed to move away from the old the Soviet system. Subsequent reform should be focused on evidence-based decision making and strengthening of primary health care in terms of new public health concepts.

Connection Management Scheme using Mobile Agent System

  • Lim, Hee-Kyoung;Bae, Sang-Hyun;Lee, Kwang-Ok
    • Journal of Integrative Natural Science
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    • v.11 no.4
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    • pp.192-196
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    • 2018
  • The mobile agent paradigm can be exploited in a variety of ways, ranging from low-level system administration tasks to middle ware to user-level applications. Mobile agents can be useful in building middle-ware services such as active mail systems, distributed collaboration systems, etc. An active mail message is a program that interacts with its recipient using a multimedia interface, and adapts the interaction session based on the recipient's responses. The mobile agent paradigm is well suitable to this type of application, since it can carry a sender-defined session protocol along with the multimedia message. Mobile agent communication is possible via method invocation on virtual references. Agents can make synchronous, one-way, or future-reply type invocations. Multicasting is possible, since agents can be aggregated hierarchically into groups. A simple check-pointing facility has also been implemented. Another proposed solution is to use multi agent computer systems to access, filter, evaluate, and integrate this information. We will present the overall architectural framework, our agent design commitments, and agent architecture to enable the above characteristics. Besides, the each information needed a mobile agent system such as text, graphic, image, audio and video etc, constructed a great capacity multimedia database system. However, they have problems in establishing connections over multiple subnetworks, such as no end-to-end connections, transmission delay due to ATM address resolution, no QoS protocols. We propose a new connection management scheme in the thesis to improve the connection management involved of mobile agent systems.

Block Unit Mapping Technique of NAND Flash Memory Using Variable Offset

  • Lee, Seung-Woo;Ryu, Kwan-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.8
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    • pp.9-17
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    • 2019
  • In this paper, we propose a block mapping technique applicable to NAND flash memory. In order to use the NAND flash memory with the operating system and the file system developed on the basis of the hard disk which is mainly used in the general PC field, it is necessary to use the system software known as the FTL (Flash Translation Layer). FTL overcomes the disadvantage of not being able to overwrite data by using the address mapping table and solves the additional features caused by the physical structure of NAND flash memory. In this paper, we propose a new mapping method based on the block mapping method for efficient use of the NAND flash memory. In the case of the proposed technique, the data modification operation is processed by using a blank page in the existing block without using an additional block for the data modification operation, thereby minimizing the block unit deletion operation in the merging operation. Also, the frequency of occurrence of the sequential write request and random write request Accordingly, by optimally adjusting the ratio of pages for recording data in a block and pages for recording data requested for modification, it is possible to optimize sequential writing and random writing by maximizing the utilization of pages in a block.

Privacy-Preservation Using Group Signature for Incentive Mechanisms in Mobile Crowd Sensing

  • Kim, Mihui;Park, Younghee;Dighe, Pankaj Balasaheb
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1036-1054
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    • 2019
  • Recently, concomitant with a surge in numbers of Internet of Things (IoT) devices with various sensors, mobile crowdsensing (MCS) has provided a new business model for IoT. For example, a person can share road traffic pictures taken with their smartphone via a cloud computing system and the MCS data can provide benefits to other consumers. In this service model, to encourage people to actively engage in sensing activities and to voluntarily share their sensing data, providing appropriate incentives is very important. However, the sensing data from personal devices can be sensitive to privacy, and thus the privacy issue can suppress data sharing. Therefore, the development of an appropriate privacy protection system is essential for successful MCS. In this study, we address this problem due to the conflicting objectives of privacy preservation and incentive payment. We propose a privacy-preserving mechanism that protects identity and location privacy of sensing users through an on-demand incentive payment and group signatures methods. Subsequently, we apply the proposed mechanism to one example of MCS-an intelligent parking system-and demonstrate the feasibility and efficiency of our mechanism through emulation.

A Novel Dynamic Optimization Technique for Finding Optimal Trust Weights in Cloud

  • Prasad, Aluri V.H. Sai;Rajkumar, Ganapavarapu V.S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.6
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    • pp.2060-2073
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    • 2022
  • Cloud Computing permits users to access vast amounts of services of computing power in a virtualized environment. Providing secure services is essential. There are several problems to real-world optimization that are dynamic which means they tend to change over time. For these types of issues, the goal is not always to identify one optimum but to keep continuously adapting to the solution according to the change in the environment. The problem of scheduling in Cloud where new tasks keep coming over time is unique in terms of dynamic optimization problems. Until now, there has been a large majority of research made on the application of various Evolutionary Algorithms (EAs) to address the issues of dynamic optimization, with the focus on the maintenance of population diversity to ensure the flexibility for adapting to the changes in the environment. Generally, trust refers to the confidence or assurance in a set of entities that assure the security of data. In this work, a dynamic optimization technique is proposed to find an optimal trust weights in cloud during scheduling.

WACFI: Code Instrumentation Technique for Protection of Indirect Call in WebAssembly (WACFI: 웹 어셈블리에서의 간접호출 명령어 보호를 위한 코드 계측 기술)

  • Chang, Yoonsoo;Kim, Youngju;Kwon, Donghyun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.31 no.4
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    • pp.753-762
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    • 2021
  • WebAssembly(WASM) is a low-level instruction format that can be run in a web environment. Since WASM has a excellent performance, various web applications use webassembly. However, according to our security analysis WASM has a security pitfall related to control flow integrity (CFI) for indirect calls. To address the problem in this paper we propose a new code instrumentation scheme to protect indirect calls, named WACFI. Specifically WACFI enhances a CFI technique for indirect call in WASM based on source code anlysis and binary instrumentation. To test the feasibility of WACFI, we applied WACFI to a sound-encoding application. According to our experimental results WACFI only adds 2.75% overhead on the execution time while protecting indirect calls safely.

Beam Tracking Method Using Unscented Kalman Filter for UAV-Enabled NR MIMO-OFDM System with Hybrid Beamforming

  • Yuna, Sim;Seungseok, Sin;Jihun, Cho;Sangmi, Moon;Young-Hwan, You;Cheol Hong, Kim;Intae, Hwang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.280-294
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    • 2023
  • Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems.

Crop Leaf Disease Identification Using Deep Transfer Learning

  • Changjian Zhou;Yutong Zhang;Wenzhong Zhao
    • Journal of Information Processing Systems
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    • v.20 no.2
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    • pp.149-158
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    • 2024
  • Traditional manual identification of crop leaf diseases is challenging. Owing to the limitations in manpower and resources, it is challenging to explore crop diseases on a large scale. The emergence of artificial intelligence technologies, particularly the extensive application of deep learning technologies, is expected to overcome these challenges and greatly improve the accuracy and efficiency of crop disease identification. Crop leaf disease identification models have been designed and trained using large-scale training data, enabling them to predict different categories of diseases from unlabeled crop leaves. However, these models, which possess strong feature representation capabilities, require substantial training data, and there is often a shortage of such datasets in practical farming scenarios. To address this issue and improve the feature learning abilities of models, this study proposes a deep transfer learning adaptation strategy. The novel proposed method aims to transfer the weights and parameters from pre-trained models in similar large-scale training datasets, such as ImageNet. ImageNet pre-trained weights are adopted and fine-tuned with the features of crop leaf diseases to improve prediction ability. In this study, we collected 16,060 crop leaf disease images, spanning 12 categories, for training. The experimental results demonstrate that an impressive accuracy of 98% is achieved using the proposed method on the transferred ResNet-50 model, thereby confirming the effectiveness of our transfer learning approach.

Trends in the AI-based Banking Conversational Agents Literature: A Bibliometric Review

  • Eden Samuel Parthiban;Mohd. Adil
    • Asia pacific journal of information systems
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    • v.33 no.3
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    • pp.702-736
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    • 2023
  • Artificial Intelligence (AI) and the technologies powered by AI fuel the fourth industrial revolution. Being the primary adopter of such innovations, banking has recently started using the most common AI-based technology, i.e., conversational agents. Although research extensively focuses on this niche area and provides bibliometric understanding for such agents in other industries, a similar review with scientometric insights of the banking literature concerning AI conversational agents is absent till date. Furthermore, in the era following the pandemic, banks are faced with the imperative to provide solutions that align with the changing landscape of remote consumer behavior. As a result, banks are proactively integrating technology-driven solutions, such as automated agents, to effectively address the growing demand for remote customer support. Hence more research is needed to perfect such agents. In order to bridge these existing gaps, the present study undertook a comprehensive examination of two decades' worth of banking literature. A meticulous review was conducted, analyzing approximately 116 papers published from 2003 to 2023. The aim was to provide a scientometric overview of the topic, catering to the research needs of both academic and industrial professionals. Holistically, the study seeks to present a macro-view about the existing trends in AI based banking conversational agents' literature while focusing on quantity, qualitative and structural indicators that are effectively necessary to offer new directions for the AI-based banking solutions. Our study, therefore, presents insights surrounding the literature, using selected techniques related to performance analysis and science mapping.