• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.38 no.7
• /
• pp.503-512
• /
• 2001

The general DSP algorithm, like orthogonal transform or filter processing, needs efficient hardware architecture to compute inner product. The typical MAC architecture has high cost of silicon. Because of this reason, the distributed arithmetic without multiplier is widely used for implementing inner product. This paper presents the optimization to reduce required hardware in distributed arithmetic by using extraction method of adder sharing component. The optimization process uses Boltzmann-machine which is one of the neural network. This proposed method can solve problem that is increasing complexity depending on depth of inner product and compose optimal summation-network with the minimum FA and FF in a few time. The designed DCT by using Proposed method is more efficient than a ROM-based distributed arithmetic.

• Journal of Fashion Business
• /
• v.25 no.3
• /
• pp.90-107
• /
• 2021

This study concludes that communication based on interaction between broadcasting hosts and consumers is differently characterized by fashion live commerce types. Subcategories of the types of fashion live commerce were created and used in the analyses of domestic consumer awareness. Three subcategories were created: The department store type, Designer brand type, and Influencer host type. Comments representing consumers' awareness that appear immediately during real-time broadcasting were collected and used for the analyses. The frequency and TF-IDF-based top keywords were selected to analyze the semantic network and CONCOR, and the top keywords were analyzed by deriving the values of degree of centrality. The analysis identified that a group of product attributes and a group of live commerce offered value were common between the three types. As for the group characteristics classified by type, for the department store types, brand attributes, benefits, and values from pursuing the products were identified. For designer brand types, a group of viewers' responses and inquiries were identified. It is interpreted that the satisfaction value gained from hosts with product expertise has been clustered. Influencer host types have affirmed a group of external product values. A close relationship is formed and it is thought to have led a group of values to trust the external image of the product. This study carries significance in analyzing real-time comment data from consumers using fashion live commerce to empirically reveal the characteristics of each type.

• Information Systems Review
• /
• v.23 no.4
• /
• pp.69-86
• /
• 2021

As artificial intelligence technology advances, personalized recommendation systems using big data have attracted huge attention. In the case of beauty products, product preferences are clearly divided depending on customers' skin types and sensitivity along with individual tastes, so it is necessary to provide customized recommendation services based on accumulated customer data. Therefore, by employing deep learning methods, this study proposes a neural network-based recommendation model utilizing both product search history and context information such as gender, skin types and skin worries of customers. The results show that our model with context information outperforms collaborative filtering-based recommender system models using customer search history.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.2
• /
• pp.84-94
• /
• 2018

In recent years, the diminishing of operation and maintenance cost using advanced maintenance technology is attracting many companies' attention. Especially, the heavy machinery industry regards it as a crucial problem since a failure of heavy machinery requires high cost and long downtime. To improve the current maintenance process, the heavy machinery industry tries to develop a methodology to predict failure in advance and to find its causes using usage data. A better analysis of failure causes requires more data so that various kinds of sensor are attached to machines and abundant amount of product usage data is collected through the sensor network. However, the systemic analysis of the collected product usage data is still in its infant stage. Many previous works have focused on failure occurrence as statistical data for reliability analysis. There have been less works to apply product usage data into root cause analysis of product failure. The product usage data collected while failures occur should be considered failure cause analysis. To do this, this study proposes a methodology to apply product usage data into failure cause analysis. The proposed methodology in this study is composed of several steps to transform product usage into failure causes. Various statistical analysis combined with product usage data such as multinomial logistic regression, T-test, and so on are used for the root cause analysis. The proposed methodology is applied to field data coming from operated locomotive and the analysis result shows its effectiveness.

• Convergence Security Journal
• /
• v.8 no.3
• /
• pp.19-24
• /
• 2008

Common Criteria is a standard to estimate safety of information protection product such as network-level firewall system and intrusion detection system. Recently, CC version is changed from CC v.2.3 to CC v.3.1. CC v.3.1 estimation methodology requires a secured dictionary accomodation preparation for information protection product. In this research, progressed CC v3 base composition product test and research about vulnerability analysis method. Further, this paper presents specific plan sorting composition style information protection product examination methodology to existing principle and detailed methodology.

• Archives of design research
• /
• v.16 no.2
• /
• pp.35-48
• /
• 2003

Home networking technology connects individual home appliances through a wired or wireless network and makes possible new functions that were impossible when they were used independently. However, the new functions must not simply be confusing arrays of functions that are possible to implement, but those absolutely necessary to the users. To develop innovative information appliances with such functions, scenarios were used and played guiding roles in suggesting new product ideas, making design mockups, and producing videos to show natural situations where the products would be used in home of the future. In the phase of suggesting new product ideas, user action scenarios in the home, generated by a team consisting of experts in the fields of cognitive engineering, user interface, computer science, cultural anthropology, interaction design, and product design, helped the team identify user needs and design factors necessary to fulfill those needs and suggest new product ideas from the design factors. In the phase of making design mockups, the procedures of using the products were described in the scenario format. Based on the scenarios the s쇼les and the user interfaces of them were designed. In the phase of producing videos, the interactions between the user and the product were embodied in the course of professional writers'arranging the scenarios of using the products for the scripts of the videos. Videos were produced to show the actual situations where the design mockups would be used in home of the future and the dynamic aspects of interaction design.

• Journal of the Korea Safety Management & Science
• /
• v.10 no.4
• /
• pp.189-198
• /
• 2008

At present, companies write daily work record or use bar-code in order to collect distribution flow data in real time. However, it needs additional works to check the record or read the bar-code with a scanner. In this case, human error could decrease accuracy of data and it would cause problems in reliability. To solve this problem, RFID (Radio Frequency Identification) is introduced in many automatic recognition sector recently. RFID is a technology that identification data is inserted into micro-mini IC chip and recognize, trace, and manage object, animal, or person using wireless frequency. This is being emerged as the core technology in future ubiquitous environment. This study is intended to suggest RFID application method in franchise business. Traceability and visibility of individual product are supplied based on EPCglobal network. It includes DW system which supplies various assessment data about product in supply chain, financial transaction system which is based on product transaction and position information, and RFID middleware which refines and divides product data from RFID tag. With the suggested application methods, individual product's profile data are supplied in real time and it would boost reliability to customer and make effective cooperation with existing operation systems (SCM, CRM, and e-Business) possible.

• Journal of Convergence for Information Technology
• /
• v.9 no.9
• /
• pp.20-26
• /
• 2019

With the development of ICT technology and the promotion of smartphone penetration, purchasing services that purchase various products through online market are being activated. In particular, due to advances in storage and delivery technology, sales of short food materials can be purchased online. Therefore, in this paper, we propose an integrated solution that enables advertisement effect, ordering and delivery through a purchase service even if there is no sales knowledge and sales network in a small shopping mall where only offline sales can be performed. The proposed system is able to efficiently view the product information by category through image search for the product that the user desires, so that the seller of the registered product can efficiently sell without any additional advertisement.

• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.599-614
• /
• 2021

This paper proposes a digital signage system based on an intelligent recommendation model. The proposed system consists of a server and an edge. The server manages the data, learns the advertisement recommendation model, and uses the trained advertisement recommendation model to determine the advertisements to be promoted in real time. The advertisement recommendation model provides predictions for various products and probabilities. The purchase index between the product and weather data was extracted and reflected using correlation analysis to improve the accuracy of predicting the probability of purchasing a product. First, the user information and product information are input to a deep neural network as a vector through an embedding process. With this information, the product candidate group generation model reduces the product candidates that can be purchased by a certain user. The advertisement recommendation model uses a wide and deep recommendation model to derive the recommendation list by predicting the probability of purchase for the selected products. Finally, the most suitable advertisements are selected using the predicted probability of purchase for all the users within the advertisement range. The proposed system does not communicate with the server. Therefore, it determines the advertisements using a model trained at the edge. It can also be applied to digital signage that requires immediate response from several users.

• Asia pacific journal of information systems
• /
• v.31 no.4
• /
• pp.448-471
• /
• 2021

Compared to consumers' focus, in the past, on the functional aspect of fashion products, consumers recently tend to place more importance on their impressive and memorable experiences in purchasing process. As consumer's interest changes from functional aspects to individual experience in purchasing process, fashion brands try to convey the identity of the brand through creating favourable consumers' experiences. Therefore, this study explores the effect of individuals' aesthetic experiences with fashion brands' SNS accounts on their attitudes. More specifically, the study evaluates whether consumers enjoy the flow of fashion brands' SNS accounts and form purchase intentions through their aesthetic experiences and product placement. Through a survey, empirical testing was done to investigate the effect of the aesthetic experience on of flow and purchase intentions. The current study tests the interaction effect among perceived aesthetic experience, narrative images, and product placement employing 2×2×2 MANOVA. The findings herein reveal that the aesthetic experience affects flow and purchase intention, and that there is a statistically significant interaction effect between aesthetic experience, narrative images, and product placement.