• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.1-10
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• 2014

Probabilistic risk assessment (PRA) has been used in various technological fields to assist regulatory agencies, managerial decision makers, and systems designers in assessing and mitigating the risks inherent in these complex arrangements. Has PRA delivered on its promise? How do we gage PRA performance? Are our expectations about value of PRA realistic? Are there disparities between what we get and what we think we are getting form PRA and its various derivatives? Do current PRAs reflect the knowledge gained from actual events? How do we address potential gaps? These are some of the questions that have been raised over the years since the inception of the field more than forty years ago. This paper offers a brief assessment of PRA as a technical discipline in theory and practice, its key strengths and weaknesses, and suggestions on ways to address real and perceived shortcomings.

• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.73-96
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• 2019

This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.63-66
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• 2021

The technological advancement in computer vision has made system like grab-and-go grocery a reality. Now all the shoppers have to do now is to walk in grab the items and go out without having to wait in the long queues. This paper presents an intelligent retail environment system that is capable of monitoring and tracking customer's activity during shopping based on their interaction with the shelf. It aims to develop a system that is low cost, easy to mount and exhibit adequate performance in real environment.

• Advances in aircraft and spacecraft science
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• v.8 no.4
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• pp.331-344
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• 2021

Airframe internal and external specifications are the product of intensive intellectual efforts and technological breakthroughs distinguishing each aircraft manufacturer. Therefore, geometrical information characterizing aircraft primary aerodynamic surfaces remain classified. When attempting to model real aircraft, many members of the aeronautical community depend on their personal expertise and generic design principles to bypass the confidentiality obstacles and sketch real aircraft airfoils, which therefore vary for the same aircraft due to the different designers' initial assumptions. This paper presents a photogrammetric shape prediction method for deriving geometrical properties of real aircraft airframe by utilizing their publicly accessible static and dynamic visual content. The method is based on extracting the visually distinguishable curves at the fairing regions between aerodynamic surfaces and fuselage. Two case studies on B-29 and B-737 are presented showing how to approximate the sectional coordinates of their wing inboard airfoils and proving the good agreement between the geometrical and aerodynamic properties of the replicated airfoils to their original versions. Therefore, the paper provides a systematic reverse engineering approach that will enhance aircraft conceptual design and flight performance optimization studies.

• Advances in Energy Research
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• v.8 no.3
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• pp.125-136
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• 2022

Entropy generation along with exergetic analysis is carried out using turbulent nanofluid flow in the heat exchanger. To obtain the optimized percentage constituent of nanofluid, the nanofluid volume concentrations is varied for the given input conditions. For different Reynolds number of the fluid and heat capacity rate ratio between the streams, the heat transfer improvements are studied in terms of nano particles diameter. Parametric analysis is carried out for a counterflow heat exchanger using turbulent nanofluid flow with exergetic efficiency along with entropy generation number as performance parameters. The exergetic efficiency provides realistic approach in the design of nanofluid applications in heat exchanger leading to conservation of energy.

• Educational Technology International
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• v.24 no.2
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• pp.143-168
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• 2023

This study aims to analyze the perceptions and educational needs of pre-service teachers for the use of Artificial Intelligence (AI) in education. To this end, we collected survey data from 25 undergraduate students who were enrolled in a teacher education college in Seoul. The purpose of the survey was to measure the importance and current performance for instructional AI use based on the technological, pedagogical, and content knowledge (TPACK) framework, and to explore the priority of educational needs using Borich's needs analysis and the Locus for Focus model. The results of the study confirmed that Ethics and TPK competencies are prioritized. Additionally, the results indicated a high demand for practical knowledge that can be implemented in the practice of education. Based on the results, it is necessary to develop a teacher education program that focuses on ethical aspects and teaching strategy competencies in AI-based education.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.35-44
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• 2024

This investigation primarily focuses on the generational characteristics of satellites utilized in the existing Global Navigation Satellite System (GNSS) and Regional Navigation Satellite System (RNSS), with a central emphasis on comparing the operational status of the latest generation satellites. Variations among satellite generations in physical attributes, energy consumption, and timekeeping are observed, enabling an exploration of the developmental trends over successive generations. Through a comparative analysis of the latest generation satellites, particularly in terms of performance, this study aims to furnish essential insights into the satellites employed within each system. Consequently, it will contribute to a foundational understanding of the past, present, and future GNSS satellites.

• Electronics and Telecommunications Trends
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• v.39 no.1
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• pp.74-82
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• 2024

Music is a means of emotional expression and self-expression. In addition, it allows to interact with others and communicate with the world. Music may be considered as inaccessible for people with hearing impairment, who are sometimes discriminated from the music community. We explore trends in various technologies and research that enable everyone to access and enjoy music through experiences that leverage new and innovative technological approaches and bridge the gap between people with and without hearing impairment. Various aspects of haptic systems are being studied, but most of them are performance-oriented and focus only on technical functions. As research matures, more detailed and new studies that converge with various senses are being attempted. These studies will likely evolve into influential research areas that can positively affect the lives of people in terms of accessibility and inclusion by providing detailed functions and stimuli to specific users, including those with hearing impairment.

• Clinical Endoscopy
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• v.55 no.5
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• pp.594-604
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• 2022

Over the past decade, technological advances in deep learning have led to the introduction of artificial intelligence (AI) in medical imaging. The most commonly used structure in image recognition is the convolutional neural network, which mimics the action of the human visual cortex. The applications of AI in gastrointestinal endoscopy are diverse. Computer-aided diagnosis has achieved remarkable outcomes with recent improvements in machine-learning techniques and advances in computer performance. Despite some hurdles, the implementation of AI-assisted clinical practice is expected to aid endoscopists in real-time decision-making. In this summary, we reviewed state-of-the-art AI in the field of gastrointestinal endoscopy and offered a practical guide for building a learning image dataset for algorithm development.

• Journal of Internet Technology
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• v.20 no.4
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• pp.1157-1166
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• 2019

A Wireless Body Area Network (WBAN) allows the seamless integration of miniaturized sensor nodes in or around a human body, which may cause damage to the surrounding body issue due to high temperature. Although various temperature aware routing protocols have been proposed to prevent temperature rise of sensor nodes, most of them accommodate single traffic transmission with no mobility support. We propose a Forwarder based Temperature Aware Routing Protocol (FTAR) that supports multiple traffic transmission for normal and critical data. Normal data is forwarded directly to the sink through forwarding nodes which are selected among mobile nodes attached to the arms and legs, while critical data is forwarded to the sink through static nodes attached to fixed body parts with no mobility. We conduct extensive simulations of FTAR, and conclude that FTAR has good performance in terms of hot spot generation ratio, hot spot duration time, and packet delivery ratio.