• The Journal of Information Systems
• /
• v.31 no.1
• /
• pp.147-173
• /
• 2022

Purpose As the use of social network services has become common, it has become possible to freely communicate and establish relationships with other people anytime, anywhere for communication and information sharing. Influencers who have a strong influence on consumers' perceptions and attitudes through their own opinions and stories have appeared on various social media channels such as YouTube. Recently, companies utilize influencers with a large number of followers to check interactions with customers to understand customer attitudes and opinions about products in real time. Start-ups with insufficient resources need to quickly examine customer responses to reduce the probability of failure after product planning. The Lean process of creating an MVP and quickly confirming and learning the market response should be repeated over and over again. Findings In this paper, we try to suggest that the YouTube platform can play a sufficient role as a customer experiment space through examples. The case company is a company that has successfully commercialized products by continuously interacting with customers through the YouTube platform for the first four months of its founding. This paper is expected to be helpful in the experimental process for prospective founders and early founders to examine customer responses to reduce the probability of market failure before commercialization. Design/methodology/approach This paper analyzed the YouTube channel data of case companies based on the netnography methodology and presented the contents of the lean process management carried out in the experimental stage and the post-production stage through interview research.

• International Journal of Advanced Culture Technology
• /
• v.10 no.3
• /
• pp.146-155
• /
• 2022

The purpose of this study is to investigate the recyclability of Shenlong in China using SWOT. The main analysis results are as follows. First, provided that the company's current capacity utilization rate is seriously insufficient, reducing staff is one among the effective ways. Second, Shenlong should open a web store to cater to young people's online shopping behavior, and further expand the brand visibility using national mainstream media and online shopping platforms like Taobao and JingDong to market Dongfeng Peugeot and Dongfeng Citroen on the whole network. Third, under the premise of maintaining the present best-selling models, Shenlong should appropriately reduce the amount of models, adjust the assembly capacity ratio of every model and every displacement in real time per the newest market trends, increase the agility of auto companies' production, and timely meet the wants of domestic consumers. Fourth, dual-brand coordination and channel integration are very necessary, and also the profitability and profitability of dealers are going to be further improved, thereby increasing sales. Fifth, target building new energy leading products of Shenlong, strive to attain the forefront of the industry within the sales of recent energy vehicles within 5 years, and gradually expand new energy vehicle products from passenger vehicles to passenger vehicles and commercial vehicles. Finally, the marketing field of Shenlong Automobile should achieve "three major changes", that is, change from a goal-driven type to a demand-driven type, cancel the bundling of outlet invoicing goals and delivery incentive tiers; start from basic capabilities, and set pragmatic and challenging goals; focus Channels, to realize following the activation of outlets, and single store sales increase.

• East European & Balkan Studies
• /
• v.36
• /
• pp.247-268
• /
• 2013

The ever-increasing informal economy in post-socialist Eastern Europe forces one to wonder about what transition to post-socialism is for and about. Informal economy, which refers to unregistered work and services to was rampant in the socialist period across Eastern Europe and the Soviet Union. It was considered as a pathological phenomenon of the socialist system and exposing the rigidity and inefficiency of the command economy amongst the socialist regimes. The ordinary people of the Eastern bloc had to resort to all sorts of informal channels to get hold of goods and services constantly in short supply, especially at the last decade of the really existing socialism. However, it is ironical to observe the same old informal economy, considered pathological, even more thriving in the new era of post-socialism in Eastern Europe. After all, the system has changed into the capitalism, the antipode to socialism. It should be mentioned that the function of informal economy is seen to be even more intensified, from a means to make living better in the socialist time to a means for survival and sustenance in the post-socialist period. It follows from the socialist experience that the deficiency of the ruling system could not be indefinitely borne out. Real remedies should be sought out before it will be too late.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.13 no.5
• /
• pp.19-28
• /
• 2017

Various methods for reducing the load on the server have been implemented in performing face recognition remotely by the spread of IP security cameras. In this paper, IP surveillance cameras at remote sites are input through a DSP board equipped with face detection function, and then face detection is performed. Then, the facial region image is transmitted to the server, and the face recognition processing is performed through face recognition distributed processing. As a result, the overall server system load and significantly reduce processing and real-time face recognition has the advantage that you can perform while linked up to 256 cameras. The technology that can accomplish this is to perform 64-channel face recognition per server using distributed processing server technology and to process face search results through 250 camera channels when operating four distributed processing servers there was.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.113-125
• /
• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.20 no.6
• /
• pp.538-544
• /
• 2000

A phased array ultrasonic nondestructive inspection system is being developed to obtain images of the interior of steel structures by modifying a medical ultrasound imaging system. The medical system consists of 64 individual transceiver channels that can drive 128 array elements. Several modifications of the system were required mainly due to the change of sound speed. It was necessary to fabricate array transducers for steel structure and to obtain A-scan signal that is necessary for the nondestructive testing. Boundary diffraction wave model was used for the prediction of radiation beam field from array transducers, which provided guidelines to design array transducers. And a RF data acquisition board was fabricated for the A-scan signal acquisition along a selected un line within an image. For the proper beam forming in the transmission and reception for steel structure, delay time was controlled. To demonstrate the performance of the developed system and fabricated transducers, images of artificial specimens and A-scan signals for selected scan lines were obtained in a real time fashion.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.6
• /
• pp.185-190
• /
• 2023

Recently, tracking radar requires the development of millimeter wave tracking radar to acquire target information with high resolution in various environments. The development of millimeter wave tracking radar requires the development of transmission and receiving components that can be applied to the millimeter wave tracking radar, as well as verification of the applicability of the tracking radar. In order to verify the applicability of the developed transmitting and receiving components, it is necessary to develop a signal acquisition device that can control the transmitting and receiving components using the operating concept of a tracking radar and check the status of the received signal. In this paper, we implemented a signal acquisition device that can confirm the applicability of components developed for millimeter wave tracking radar. The signal acquisition device was designed to process in real time the OOOMHz center frequency and OOMHz bandwidth signals input from 4 channels to verify the received signal. In addition, component control applying the tracking radar operation concept was designed to be controlled by communication such as RS422, RS232, and SPI and generation of control signals for the transmission and receiving time. Lastly, the implemented signal acquisition device was verified through a signal acquisition device performance test.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.195-211
• /
• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.4
• /
• pp.57-63
• /
• 1997

In this paper, we study the efficient feature vector extraction method and front-end processing to improve the performance of the speech recognition system using KT(Korea Telecommunication) database collected through various telephone channels. First of all, we compare the recognition performances of the feature vectors known to be robust to noise and environmental variation and verify the performance enhancement of the recognition system using weighted cepstral distance measure methods. The experiment result shows that the recognition rate is increasedby using both PLP(Perceptual Linear Prediction) and MFCC(Mel Frequency Cepstral Coefficient) in comparison with LPC cepstrum used in KT recognition system. In cepstral distance measure, the weighted cepstral distance measure functions such as RPS(Root Power Sums) and BPL(Band-Pass Lifter) help the recognition enhancement. The application of the spectral subtraction method decrease the recognition rate because of the effect of distortion. However, RASTA(RelAtive SpecTrAl) processing, CMS(Cepstral Mean Subtraction) and SBR(Signal Bias Removal) enhance the recognition performance. Especially, the CMS method is simple but shows high recognition enhancement. Finally, the performances of the modified methods for the real-time implementation of CMS are compared and the improved method is suggested to prevent the performance degradation.

• Journal of Distribution Science
• /
• v.15 no.10
• /
• pp.93-103
• /
• 2017

Purpose - Sports and the media have been developed together through a close relationship. During the past decade, the media landscape and the coverage of sports events have been changed. Sports fans can use the sports content at the time they want, on the platform they prefer. Furthermore, thanks to the advanced information technology, sports fans are likely to be more engaged in sport in communication technology-friendly stadium. However, the literature on the relationship between sports and the media has heavily focused on the differences of media types, clear distinction between media suppliers and consumers, and the limited media extension. Given the limitation of prior research, therefore, it has not fully reflected the change in society and culture, the importance of media recipients or consumers, and the mediating characteristic of the media. In order to generate further insights for sport media related industry and its society, it is necessary to comprehend the contemporary phenomena of real world situation in new media and sport and to discuss how new media influence sport and how their relationship is changing in managerial context. The purpose of this study is to identify new media cases as distribution channels in sports context and is to develop insights by discussing its role and meaning of new media in sport society. Research design, data, and methodology - The study employed the theory-centered review and case analysis. In order to explain phenomena of the role of new media in contemporary sport and to generate related insights in sport context, the study reviewed the new media cases applied in sport industry and interpreted their meaning by employing medium theory, remediation theory, and new media theory. Results - The study discussed the limitation of prior sport media research and identified the characteristics of sport as new media such as remediating, extending sensory organs, reiterating physical space and electronic space. Conclusions - The study derived the characteristics of sport as new media, in a sport setting, and through sports settings. Findings would assist to comprehend the role of new media in spectating sport and provide insights for sport media study.