• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.6-21
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• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.17-21
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• 2010

As the compact and easily accessible handheld devices, such as cellular phones and MP3 players equipped with image acquisition functionality, are becoming widely available among common users, various applications of images are rapidly increasing. Image related services and software such as web-based image presentation and image manipulation for personal or commercial purpose enable users to view contents of remote image archive and to manipulate enormous amount of images in local or network based storage as well. It is necessary for users to identify the images efficiently so that the same images are perceived as one physical entity instead of recognizing them as different images as the trends are getting stronger. In order to support this environment, we propose a method that generates image identifiers or indexing for images within a solid and efficient manner. The proposed image identifier utilizes multiple index values. The integration of component index values creates a unique composite value that can be used as a file name, file system identifier, or database index. Our experimental results on generation of constituent index values have shown favorable results.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.212-220
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• 2024

A recently the advancement of society, AI technology has made significant strides, especially in the fields of computer vision and voice recognition. This study introduces a system that leverages these technologies to recognize users through a camera and relay commands within a vehicle based on voice commands. The system uses the YOLO (You Only Look Once) machine learning algorithm, widely used for object and entity recognition, to identify specific users. For voice command recognition, a machine learning model based on spectrogram voice analysis is employed to identify specific commands. This design aims to enhance security and convenience by preventing unauthorized access to vehicles and IoT devices by anyone other than registered users. We converts camera input data into YOLO system inputs to determine if it is a person, Additionally, it collects voice data through a microphone embedded in the device or computer, converting it into time-domain spectrogram data to be used as input for the voice recognition machine learning system. The input camera image data and voice data undergo inference tasks through pre-trained models, enabling the recognition of simple commands within a limited space based on the inference results. This study demonstrates the feasibility of constructing a device management system within a confined space that enhances security and user convenience through a simple real-time system model. Finally our work aims to provide practical solutions in various application fields, such as smart homes and autonomous vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2417-2430
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• 2024

The need for secure user authentication in blockchain-based applications has been growing with the increased adoption of Decentralized Identity (DID) credentials in blockchain. Zokrates, a tool designed to protect user privacy within smart contracts, had a limitation in that it could not accept authenticated user information such as credentials, only allowing the use of manually inputted data. In this paper, we propose a smart contract system that securely validates DID credentials to overcome the limitations of traditional centralized authentication systems. This system ensures the safe identification of users within blockchain-based applications by authenticating their identities in a trusted manner within the blockchain. As the demand for user authentication in blockchain rises, this paper emphasizes the significance of a blockchain-based identity verification system that guarantees both privacy and security. Leveraging the Zero-Knowledge Proof method and utilizing the Zokrates tool, this innovative approach aims to provide solutions for the digital identity verification process, thereby expanding the scope of blockchain technology applications. Moreover, we also provide a CLI for each entity. We help anyone who wants to authenticate their identity using the tool to safely verify it on-chain.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.64-74
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• 2015

Because of the burgeoning demand of the energy, the countries are finding sustainable solutions for these emerging challenges. Demand Side Management is playing a significant role in managing the demand with an aim to support the electrical grid during the peak hours. However, advancement in controls and communication technologies, the aggregators are appearing as a third party entity in implementing demand response program. In this paper, a detailed mathematical framework is discussed in which the aggregator acts as an energy service provider between the utility and the consumers, and facilitate the consumers to actively participate in demand side management by introducing the new concept of demand reduction bidding (DRB) under constrained direct load control. Paper also presented an algorithm for the proposed framework and demonstrated the efficacy of the algorithm by considering few case studies and concluded with simulation results and discussions.

• Annals of Clinical Neurophysiology
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• v.12 no.1
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• pp.7-10
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• 2010

Chronic low back pain (CLBP) is a distinct disease entity in that its clinical course and response to the treatment are quite different from acute low back pain (ALBP). CLBP is also closely related with systemic or preexisting psychosocial factors rather than focal or localized factors. Since there has been little consensus in practice regarding the proper management of CLBP, clinicians tend to approach and manage patients with CLBP in an empirical manner rather than an evidence-based one. In this article, I will review the difficulties of therapeutic choice in CLBP and provide superior aspects of medical treatment over invasive interventional treatments.

• Journal of Chest Surgery
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• v.51 no.2
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• pp.142-145
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• 2018

Malignant gastrointestinal neuroectodermal tumor (GNET) is a very rare disease entity, especially in the esophagus. The diagnosis of GNET is based on histologic, immunohistochemical, and genetic findings. The choice of treatment is complete resection, and further treatment options can be considered. H erein, we describe a case of successful surgical treatment of a 23-year-old man with recurrent malignant esophageal GNET.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.101-116
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• 1996

Increased attention has been paid in recent years to the need of traffic management for alleviating urban traffic congestion. This paper presents a discrete event modeling and simulation framework for analyzing the traffic flow. Traffic simulation models can be classified as being either microscopic and macroscopic models. The discrete event modeling and simulation technique can be basically employed to describe the macroscopic traffic simulation model. To do this, we have employed the System Entity Structure/Model Base (SES/MB) framework which integrates the dynamic-based formalism of simulation with the symbolic formalism of AI. The SES/MB framework supports to hierarchical, modular discrete event modeling and simulation environment. We also adopt the Symbolic DEVS (Discrete Event System Specification) to developed the automated analysis methodology for generating optimal signal light policy. Several simulation tests will demonstrates the techniques.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1491-1494
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• 2003

Video adaptation in response to dynamic resource conditions and user preferences is required as a key technology to enable universal multimedia access (UMA) through heterogeneous networks by a multitude of devices in a seamless way. Although many adaptation techniques exist, selections of appropriate adaptations among multiple choices are often ad hoc. To provide a systematic solution, we present a general conceptual framework to model video entity, adaptation, resource, utility, and relations among them. It allows for formulation of various adaptation problems as resource-constrained utility maximization. We apply the framework to a practical case of dynamic bit rate adaptation. Furthermore, we present a description tool, which has been accepted as a part of the MPEG-21 Digital Item Adaptation (DIA), along with a brief overview of the .elated descriptors to support terminal and network quality of service (QoS).

• Journal of Chest Surgery
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• v.26 no.4
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• pp.325-328
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• 1993

The pedicled omental flap has been used for treatment of various kind of complications in thoraxcic surgery. Its property of promoting neovascularization , immunilogic properties that limiting the spread of infection, providing soft tissue coverage are very effective in treatment esophageal fistulas. Also, congenital broncho-esophageal fistula [ BEF ] is a rare disease entity which was reported about 100 cases around the world. We experienced 27 years old female patient with Braimbridge type I congenital BEF. We performed division of BEF using stapler and pericardial patch coverage of esophageal side with concomittent left lower lobectomy. This patient was complicated with postoperative esophageal leakage with empyema thoracis. We have successfully managed these problems with re-thoracotomy and re-closure of esophageal fistula using Right Gastroepiploic Artery based pedicled omental flap wrapping around the esophageal anastomosis site. It is felt that pedicled omental flap is a very effective method to manage esophageal complication such as postoperative esophageal leakage.