• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• 제9권10호
• /
• pp.797-808
• /
• 2019

In a closed workplace, the management of the workplace is important because the environmental data at the workplace has a great influence on the safety of workers. Today's industrial sites are transformed into data-based factories that collect and analyze data through sensors in those sites, requiring a management system to ensure safety. In general, a safety management system stores and manages data on a central server associated with a database. Since such management system introduces high possibility of forgery and loss of data, workers often suspect the reliability of the information on the management system. In this paper, we present a worker safety management system based on the EOS blockchain which is considered as third-generation blockchain technology. The developed system consists of a set of smart contracts on the EOS blockchain and 3 decentralized applications associated with the blockchain. According to the roles of users, the worker and manager applications respectively perform the process of initiating or terminating tasks as blockchain transactions. The entire transaction history is distributed and stored in all nodes participating in the blockchain network, so forgery and loss of data is practically impossible. The system administrator application assigns the account rights of workers and managers appropriate for performing the functions, and specifies the safety standards of IoT data for ensuring workplace safety. The IoT data received from sensor platforms in workplaces and the information on initiation, termination or approval of tasks assigned to workers, are explicitly stored and managed in the EOS smart contracts.

• Journal of the Korean Society of Radiology
• /
• 제17권3호
• /
• pp.411-416
• /
• 2023

The purpose of this study is to investigate the utilization of major learning tools among radiology science students and assess the accuracy of a conversational artificial intelligence service program, specifically a chatbot, in the context of the national radiologic technologist licensing exam. The survey revealed that 84.3% of radiology science students actively utilize electronic devices during their learning process. In addition, 104 out of 140 respondents said they use search engines as a top priority for efficient data collection while studying. When asked about their awareness of chatbots, 80% of participants responded affirmatively, and 22.9% reported having used chatbots for academic purposes at least once. From 2018 to 2022, exam questions from the first and second periods were presented to the chatbot for answers. The results showed that ChatGPT's accuracy in answering first period questions increased from 48.28% to 60%, while for second period questions, it increased from 50% to 62.22%. Bing's accuracy in answering first period questions improved from 55% to 64.55%, and for second period questions, it increased from 48% to 52.22%. The study confirmed the general trend of radiology science students utilizing electronic devices for learning and obtaining information through the internet. However, conversational artificial intelligence service programs in the field of radiation science face challenges related to accuracy and reliability, and providing perfect solutions remains difficult, highlighting the need for continuous development and improvement.

• Korean journal of food and cookery science
• /
• 제29권2호
• /
• pp.105-113
• /
• 2013

Consumer organizations usually lead the opinions of the consumers. This study was performed to investigate the perceptions and information needs of consumer organizations on food additives for the promotion of risk communication. A survey was conducted for 4 weeks in March 2012 by using a self-administered questionnaire consisting of 32 questions. Total 111 responses were collected for analysis. 'Safety (91.0%)' was the most important factor influencing the purchase of processed food, and both 'food additives (24.3%)' and 'environmental pollution (23.4%)' were considered as main risk factors. The longer the career of the members had, the higher negative perceptions on food additives (p<0.01). About 70% of the respondents who had known KFDA's researches on evaluating safety of food additives answered that researches were not enough to make sure the safety. Although lectures and other domestic organization were the main channels for getting information, 'TV' was considered as the most suitable way for it. 'Poor risk communication (32.4%)' was pointed out as the serious problem of government's food safety policy. Based on these results, consumer organizations' low level of trust on government should be overcome by continuous supply of information what they need to facilitate risk communication on food additives.

• Asia Marketing Journal
• /
• 제14권2호
• /
• pp.65-96
• /
• 2012

Brand has received much attention from considerable marketing research. When consumers consume product or services, they are exposed to a lot of brand related stimuli. These contain brand personality, brand experience, brand identity, brand communications and so on. A special kind of new crisis occasionally confronting companies' brand management today is the brand related rumor. An important influence on consumers' purchase decision making is the word-of-mouth spread by other consumers and most decisions are influenced by other's recommendations. In light of this influence, firms have reasonable reason to study and understand consumer-to-consumer communication such as brand rumor. The importance of brand rumor to marketers is increasing as the number of internet user and SNS(social network service) site grows. Due to the development of internet technology, people can spread rumors without the limitation of time, space and place. However relatively few studies have been published in marketing journals and little is known about brand rumors in the marketplace. The study of rumor has a long history in all major social science. But very few studies have dealt with the antecedents and consequences of any kind of brand rumor. Rumor has been generally described as a story or statement in general circulation without proper confirmation or certainty as to fact. And it also can be defined as an unconfirmed proposition, passed along from people to people. Rosnow(1991) claimed that rumors were transmitted because people needed to explain ambiguous and uncertain events and talking about them reduced associated anxiety. Especially negative rumors are believed to have the potential to devastate a company's reputation and relations with customers. From the perspective of marketer, negative rumors are considered harmful and extremely difficult to control in general. It is becoming a threat to a company's sustainability and sometimes leads to negative brand image and loss of customers. Thus there is a growing concern that these negative rumors can damage brands' reputations and lead them to financial disaster too. In this study we aimed to distinguish antecedents of brand rumor transmission and investigate the effects of brand rumor characteristics on rumor spread intention. We also found key components in personal acceptance of brand rumor. In contextualist perspective, we tried to unify the traditional psychological and sociological views. In this unified research approach we defined brand rumor's characteristics based on five major variables that had been found to influence the process of rumor spread intention. The five factors of usefulness, source credibility, message credibility, worry, and vividness, encompass multi level elements of brand rumor. We also selected product involvement as a control variable. To perform the empirical research, imaginary Korean 'Kimch' brand and related contamination rumor was created and proposed. Questionnaires were collected from 178 Korean samples. Data were collected from college students who have been experienced the focal product. College students were regarded as good subjects because they have a tendency to express their opinions in detail. PLS(partial least square) method was adopted to analyze the relations between variables in the equation model. The most widely adopted causal modeling method is LISREL. However it is poorly suited to deal with relatively small data samples and can yield not proper solutions in some cases. PLS has been developed to avoid some of these limitations and provide more reliable results. To test the reliability using SPSS 16 s/w, Cronbach alpha was examined and all the values were appropriate showing alpha values between .802 and .953. Subsequently, confirmatory factor analysis was conducted successfully. And structural equation modeling has been used to analyze the research model using smartPLS(ver. 2.0) s/w. Overall, R² of adoption of rumor is .476 and R² of intention of rumor transmission is .218. The overall model showed a satisfactory fit. The empirical results can be summarized as follows. According to the results, the variables of brand rumor characteristic such as source credibility, message credibility, worry, and vividness affect argument strength of rumor. And argument strength of rumor also affects rumor intention. On the other hand, the relationship between perceived usefulness and argument strength of rumor is not significant. The moderating effect of product involvement on the relations between argument strength of rumor and rumor W.O.M intention is not supported neither. Consequently this study suggests some managerial and academic implications. We consider some implications for corporate crisis management planning, PR and brand management. This results show marketers that rumor is a critical factor for managing strong brand assets. Also for researchers, brand rumor should become an important thesis of their interests to understand the relationship between consumer and brand. Recently many brand managers and marketers have focused on the short-term view. They just focused on strengthen the positive brand image. According to this study we suggested that effective brand management requires managing negative brand rumors with a long-term view of marketing decisions.

• Food Science of Animal Resources
• /
• 제27권1호
• /
• pp.117-121
• /
• 2007

The number of internet users and the scale of electronic on-line trading are on the increase due to the development of information technology and the internet. The aim of this study was to monitor the accuracy of country-of-origin labels and the indicated contents of meat available by electronic on-line trading by using a structural interview sheet for 100 on-line meat product markets. The result of this investigation showed a 100% level of accuracy for business name and telephone number whereas the company address, meat manufacturer and supplier, and business registration were less reliable. We also investigated the accuracy of site policy, e-mail address, and fax number. The results showed that the accuracy of fax numbers was the lowest. The product name and the kind of meat actually in the product showed a 100% level of conformity, while the price (96.3%), place of origin (93.6%), capacity (90.4%), meat parts (80.9%) and contents of the product (73.4%) showed a relatively low level of conformity. Serious safety issues were exposed by the disturbingly low 20.2% accuracy of indicated expiration dates and 5.3% accuracy of indicated manufacturing dates. To ensure food safety, it is essential to improve consumer understanding and trust regarding food safety through continuous public relations. More education and information are needed to raise consumer awareness of the facts versus myths regarding food safety.

• Journal of Nutrition and Health
• /
• 제53권2호
• /
• pp.190-202
• /
• 2020

Purpose: This study aims to evaluate the recognition, purchase, and intake status of edible insects in adults, who are the main consumers of edible insects, and to provide the information necessary to expand the production and consumption of edible insects and related products in the future. Methods: A total of 453 adults (172 males and 281 females) aged 19 years and older were surveyed regarding their awareness of edible insects, purchase and consumption experience, and intention to purchase and consume, and the differences between them were analyzed according to gender and age groups. Data collection took place from December 2018 to January 2019. Results: Those who had knowledge of edible insects accounted for 87.0%, whereas those who had more than average knowledge were 75.9%, suggesting recognition was relatively high. Men had more experience than women in purchasing or consuming edible insects and related products (45.9% vs. 31.0%, p < 0.01). In terms of age, experience was 22.5% in 20-30s, 44.6% in 40-50s, and 63.1% in 60s and older, showing significant growth as age increased (p < 0.001). The satisfaction level of edible insects was highest in taste (3.4 points), and especially for shape and appearance, it decreased as age reduced (p < 0.001). The most common reason for not being willing to use edible insects was feeling repulsive (4.1 points), which was significantly more common in women than in men (4.3 vs. 3.9, p < 0.001), and lower with age (p < 0.001). The most needed information display for using edible insects was country of origin (63.8%), the main nutrient in edible insects was protein (93.6%), and the most preferred form of products was powder (39.5%). Conclusion: According to the above results, the recognition of edible insects was high, whereas experience of using edible insects and intention to use edible insects were low especially in women and younger groups. The reason for this is that consumers are dissatisfied with edible insects due to their appearance. This study is expected to be used as basic data for expanding the production and consumption of edible insects and related products in the future.

• Journal of Intelligence and Information Systems
• /
• 제20권3호
• /
• pp.1-18
• /
• 2014

Over the past years RFID/SN has been an elementary technology in a diversity of applications for the ubiquitous environments, especially for Internet of Things. However, one of obstacles for widespread deployment of RFID technology is the inherent unreliability of the RFID data streams by tag readers. In particular, the problem of false readings such as lost readings and mistaken readings needs to be treated by RFID middleware systems because false readings ultimately degrade the quality of application services due to the dirty data delivered by middleware systems. As a result, for the higher quality of services, an RFID middleware system is responsible for intelligently dealing with false readings for the delivery of clean data to the applications in accordance with the tag reading environment. One of popular techniques used to compensate false readings is a sliding window filter. In a sliding window scheme, it is evident that determining optimal window size intelligently is a nontrivial important task in RFID middleware systems in order to reduce false readings, especially in mobile environments. In this paper, for the purpose of reducing false readings by intelligent window adaption, we propose a new adaptive RFID data cleaning scheme based on window sliding for a single tag. Unlike previous works based on a binomial sampling model, we introduce the weight averaging. Our insight starts from the need to differentiate the past readings and the current readings, since the more recent readings may indicate the more accurate tag transitions. Owing to weight averaging, our scheme is expected to dynamically adapt the window size in an efficient manner even for non-homogeneous reading patterns in mobile environments. In addition, we analyze reading patterns in the window and effects of decreased window so that a more accurate and efficient decision on window adaption can be made. With our scheme, we can expect to obtain the ultimate goal that RFID middleware systems can provide applications with more clean data so that they can ensure high quality of intended services.

• Journal of Korean Home Economics Education Association
• /
• 제35권1호
• /
• pp.35-52
• /
• 2023

This study investigated the utilization and satisfaction of lunchboxes according to food-related lifestyle. A sample of 819 adults who regularly purchased lunchboxes were studied. This study can provide basic data for effective menu development. The participants of the study were classified into 4 groups: a 'taste-seeking group', an 'economy-seeking group', 'a convenience-seeking group', and a 'health-seeking group'. The purchase price of lunchboxes was in the range of 3,500 to 4,000 won. The 'health-seeking group' was shown to spend the highest amount on lunchboxes, over 5,100 won. Information about lunchboxes was obtained primarily through convenience stores followed by Internet SNS (p<0.05). Most participants considered nutritional value when purchasing a lunchbox (p<0.001), of which protein, caloric, and sodium content were perceived as important. Moreover, lunchboxes with clean and hygienic aesthetics were preferred amongst the 'health-seeking group' (p<0.01). The 'economy-seeking group' had a higher satisfaction linked with taste (3.66) and quantity (3.60, p<0.001). Furthermore, in terms of the satisfaction with a menu variety the 'health-seeking group' showed the highest satisfaction with a score of 3.76, while the 'convenience-seeking group' ranked the lowest satisfaction with a score of 3.46 (p<0.05). All groups were satisfied with the convenience for purchasing lunchbox (p<0.001). Additionally, most participants preferred white rice (p<0.001) and meat (p<0.01) with cooked by fried and grilled. Lastly, in the content of the lunchbox use in the future, most participants indicated the intent for continuous use (p<0.01) and recommendation to others with the reason for the low price (19.2%) in the 'economy-seeking group', fresh ingredients (16.2%) in the 'convenience-seeking group', and nutritive (17.3%) in the 'health-seeking group', as well as for the convenience of purchase in the overall groups. Taken together, 'taste' and 'convenience' were the most important factors for all groups, while 'nutrition of food' and 'addition of condiments' scored relatively low on the satisfaction in all groups. Therefore, we recommend for the growth of the convenience store lunchbox market, that it is necessary to improve the quality of the lunchbox by developing various menus based on lifestyle group and fortifying nutrition.

• Journal of Internet Computing and Services
• /
• 제14권6호
• /
• pp.71-84
• /
• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Management & Information Systems Review
• /
• 제37권1호
• /
• pp.139-154
• /
• 2018

R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.