• Convergence Security Journal
• /
• v.24 no.2
• /
• pp.89-104
• /
• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.16 no.2
• /
• pp.44-49
• /
• 2007

An agent is an abstract unit for problem solving in the field of distributed artificial intelligence, and an agent-based system is designed and implemented based on the definition of agent as its central concept. Agent modeling is advantageous to abstraction, disintegration and structuring for describing complex system, so its application is increased in various areas including air traffic control, power transmission, e-commerce and medicine. There is no agreed definition of agent but agents have common points as follows: autonomy, reactivity, pro-activeness and cooperation. An agent-oriented modeling is an approach of a concept different form existing object-oriented modeling. This study proposed the agent application for E-Beam manufacturing system. To evaluate the performance of the proposed process design, we used the JADE library. The JADE toolkit provides a FIPA-compliant agent platform and a package to develp Java agents. It provides a basic set of functionalities that are regarded as essential for an autonomous agent architecture.

• Asia pacific journal of information systems
• /
• v.16 no.1
• /
• pp.71-84
• /
• 2006

Case-based reasoning (CBR) is a reasoning technique that reuses past cases to find a solution to the new problem. It often shows significant promise for improving effectiveness of complex and unstructured decision making. It has been applied to various problem-solving areas including manufacturing, finance and marketing for the reason. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still a challenging issue. Most of the previous studies on CBR have focused on the similarity function or optimization of case features and their weights. According to some of the prior research, however, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. In spite of the fact, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the novel approach to Korean stock market. Experimental results show that the GA-optimized k-NN approach outperforms other AI techniques for stock market prediction.

• Journal of Multimedia Information System
• /
• v.7 no.1
• /
• pp.11-16
• /
• 2020

Deep Learning has become the most important technology in the field of artificial intelligence machine learning, with its high performance overwhelming existing methods in various applications. In this paper, an interactive window service based on object recognition technology is proposed. The main goal is to implement an object recognition technology using this deep learning technology to remove the existing eye tracking technology, which requires users to wear eye tracking devices themselves, and to implement an eye tracking technology that uses only usual cameras to track users' eye. We design an interactive system based on efficient eye detection and pupil tracking method that can verify the user's eye movement. To estimate the view-direction of user's eye, we initialize to make the reference (origin) coordinate. Then the view direction is estimated from the extracted eye pupils from the origin coordinate. Also, we propose a blink detection technique based on the eye apply ratio (EAR). With the extracted view direction and eye action, we provide some augmented information of interest without the existing complex and expensive eye-tracking systems with various service topics and situations. For verification, the user guiding service is implemented as a proto-type model with the school map to inform the location information of the desired location or building.

• The Research Journal of the Costume Culture
• /
• v.25 no.5
• /
• pp.708-717
• /
• 2017

Industrial innovation in Britain, during the eighteenth and nineteenth centuries, stimulated the introduction of the factory system and the migration of people from rural agricultural communities to urban industrial societies. The factory system brought elevated levels of economic growth to the purveyors of capitalism, but forced people to migrate into cities where working conditions in factories were, in general, harsh and brutal, and living conditions were cramped, overcrowded and unsanitary. Industrial developments, known collectively as the 'Industrial Revolution', were driven initially by the harnessing of water and steam power, and the widespread construction of rail, shipping and road networks. Parallel with these changes, came the development of purchasing 'middle class', consumers. Various technological ripples (or waves of innovative activity) continued (worldwide) up to the early-twenty-first century. Of recent note are innovations in digital technology, with associated developments, for example, in artificial intelligence, robotics, 3-D printing, materials technology, computing, energy storage, nano-technology, data storage, biotechnology, 'smart textiles' and the introduction of what has become known as 'e-commerce'. This paper identifies the more important early technological innovations, their influence on textile manufacture, distribution and consumption, and the changed role of the designer and craftsperson over the course of these technological ripples. The implications of non-ethical production, globalisation and so-called 'fast fashion' and non-sustainability of manufacture are examined, and the potential benefits and opportunities offered by new and developing forms of social media are considered. The message is that hand-crafted products are ethical, sustainable and durable.

• Proceedings of the KIEE Conference
• /
• 2002.11b
• /
• pp.241-243
• /
• 2002

Recently, great efforts are concentrated on the autonomous, adaptive protection schemes with advanced artificial intelligence and digital technology. It is highly required for a next generation protective system not only to detect and to clear a fault, but also to fit itself to the changing environment. In this paper it is suggested an evaluation method for the protection ability of a protective system in a distributed system. The suggested method is of bottom-up scheme, in other words, protection ability is estimated from the lowest level of parameters in each protective devices to the highest level of the whole protective system. This feature makes it possible to evaluate the protection ability either for the protective device(or a system), or for a protected system. And, in addition, it is enabled that the protectability concept can be applied in the design stage of a protective system for a distribution network. The proposed method is applied to a simple distributed network to show its effectiveness.

• Journal of Distribution Science
• /
• v.17 no.12
• /
• pp.55-62
• /
• 2019

Purpose: The number intelligent homecare products are focused on the development of technology, resulting in a lack of realistic environments or requirements for consumers. The purpose of this paper is to define the consumer and context for intelligent homecare products and to develop a usability evaluation scale. Research design, data and methodology: For this study, first, consumer and contexts related to intelligent homecare products were analyzed through literature review. Second, the primary usability evaluation factors were derived for intelligent homecare products by collecting the factors related to usability evaluation and conducting in-depth interviews with experts. Third, the second usability evaluation factors were derived through survey and statistical analysis based on the derived usability evaluation factors. Results: As a result, users of intelligent homecare products were classified as primary users and secondary consumers and six related contexts. The usability evaluation scale was established with four factors - Functionality, Error, Convenience, and Emotion - and 13 items. Conclusions: This study can be the basis for developing and distributing products that meet the consumer environment and requirements related to intelligent homecare products that will contribute to securing the competitiveness of companies and developing the technology and service value of related industries.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.10
• /
• pp.4214-4230
• /
• 2020

This paper introduces a pilot allocation scheme for massive MIMO systems based on deep convolutional neural network (CNN) learning. This work is an extension of a prior work on the basic deep learning framework of the pilot assignment problem, the application of which to a high-user density nature is difficult owing to the factorial increase in both input features and output layers. To solve this problem, by adopting the advantages of CNN in learning image data, we design input features that represent users' locations in all the cells as image data with a two-dimensional fixed-size matrix. Furthermore, using a sorting mechanism for applying proper rule, we construct output layers with a linear space complexity according to the number of users. We also develop a theoretical framework for the network capacity model of the massive MIMO systems and apply it to the training process. Finally, we implement the proposed deep CNN-based pilot assignment scheme using a commercial vanilla CNN, which takes into account shift invariant characteristics. Through extensive simulation, we demonstrate that the proposed work realizes about a 98% theoretical upper-bound performance and an elapsed time of 0.842 ms with low complexity in the case of a high-user-density condition.

• Smart Structures and Systems
• /
• v.15 no.5
• /
• pp.1363-1372
• /
• 2015

Smart structures and intelligent systems play pivotal roles in numerous areas of applied sciences ranging from civil engineering to computer and communications systems engineering. Although such structures and systems have been intensively deployed in these areas, they have been, interestingly, very rarely deployed in the field of cultural heritage preservation.This paper presents one of thefirst such attempts. A new methodology is describedthat deploys smart structures andlinks them with artificial intelligence methods.These solutions are referred toas advanced hybrid engineering artefacts. By their use,important environmental factors can be monitoredin hard to access, remote or unsafe locationsby minimizing the need for human involvement. In addition toproviding safety the methodologyalso reduces costs and, most importantly,providesa new way to modelany particular micro-environment in a much more efficient way than this is possible with traditional ways. Last but not least, although themethodology has been developed for cultural heritage preservation, its application areas are much broader and it is expected that it will find its applicationin other domains like civil engineering and ecology.

• The Research Journal of the Costume Culture
• /
• v.2 no.1
• /
• pp.93-104
• /
• 1994

Nowadays computer technology is being applied in various areas of apparel design. In particular, since the task of pattern making is to be performed by a set of predefined drawing rules, the effect of computer application in pattern making will be significant, There have been a large number of studies on pattern making program. For instance, the previous studies have developed computer programs for pattern making of women's wear, men's wear, children's wear, Han-Bok, etc. Most of them have focused on the development of computer program for a particular kind of apparel only and, however, have disregarded the feasibility of developing a multi-purposed computer program so that is just can be modified to adopt for various styles. For example, by widening the hem-wide of the basic H-Line skirt and then connecting its waist line and widened hem-wide, we can draw the A-Line skirt. Therefore, we have developed a program which can make a pattern for the basic skirt and can mae, with a slight change of he program, other patterns for various style as well. The objective of this paper is to identify and organize modules which will be used for developing a general pattern making computer system. This general pattern making system is a computer program by which we can draw a variety of apparel styles. This system is restricted to skirt pattern making only. there presentation scheme used in organizing these modules is an AND-OR tree, the one being often used in representing a complex problem in artificial intelligence domain.