• Smart Media Journal
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• v.13 no.6
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• pp.54-61
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• 2024

Recently, due to the increase in domestic and international online e-commerce platforms and the increase in container traffic at domestic ports, the operating ratio of large trucks has increased, and the number of truck fires is continuously increasing. In particular, spontaneous combustion is the most common cause of truck fires. Various academic approaches have been attempted to prevent truck fires, but due to the lack of research on the spontaneous tire ignition phenomenon that occurs during braking, this research directly designed and manufactured an experimental device to establish an environment similar to the braking system of a truck. A non-contact temperature sensor was installed on the brake device of the experimental device to collect temperature data generated from the brake device. Based on the data collected from the temperature sensor of the brake device and the temperature sensor on the tire surface, the ARIMA model among the time series prediction models was used to Appropriate parameters were selected to suit the temperature change trend, and as a result of comparing and analyzing the measured and predicted data, an accuracy of over 90% was obtained. Based on this, a plan was proposed to reduce the rate of fires in trucks by providing real-time warnings and support for truck drivers to respond to overheating phenomena occurring in the braking system.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Wind and Structures
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• v.38 no.1
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• pp.15-42
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• 2024

A flexible-base coupled-two-beam (CTB) discrete model with equivalent tuned mass dampers is used to assess the effect of soil-structure interaction (SSI) and different types of lateral resisting systems on the design of passive dynamic absorbers (PDAs) under the action of along-wind and across-wind loads due to vortex shedding. A total of five different PDAs are considered in this study: (1) tuned mass damper (TMD), (2) circular tuned sloshing damper (C-TSD), (3) rectangular tuned sloshing damper (R-TSD), (4) two-way liquid damper (TWLD) and (5) pendulum tuned mass damper (PTMD). By modifying the non-dimensional lateral stiffness ratio, the CTB model can consider lateral deformations varying from those of a flexural cantilever beam to those of a shear cantilever beam. The Monte Carlo simulation method was used to generate along-wind and across-wind loads correlated along the height of a real shear wall-frame building, which has similar fundamental periods of vibration and different modes of lateral deformation in the xz and yz planes, respectively. Ambient vibration tests were conducted on the building to identify its real lateral behavior and thus choose the most suitable parameters for the CTB model. Both alongwind and across-wind responses of the 144-meter-tall building were computed considering four soil types (hard rock, dense soil, stiff soil and soft soil) and a single PDA on its top, that is, 96 time-history analyses were carried out to assess the effect of SSI and lateral resisting system on the PDAs design. Based on the parametric analyses, the response significantly increases as the soil flexibility increases for both type of lateral wind loads, particularly for flexural-type deformations. The results show a great effectiveness of PDAs in controlling across-wind peak displacements and both along-wind and across-wind RMS accelerations, on the contrary, PDAs were ineffective in controlling along-wind peak displacements on all soil types and different kind of lateral deformation. Generally speaking, the maximum possible value of the PDA mass efficiency index increases as the soil flexibility increases, on the contrary, it decreases as the non-dimensional lateral stiffness ratio of the building increases; therefore, there is a significant increase of the vibration control effectiveness of PDAs for lateral flexural-type deformations on soft soils.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.131-160
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• 2023

An amendment to Medical Law allowing permanent face-to-face treatment has been proposed in the 21st National Assembly, with five different bills introduced. However, each proposed amendment focuses on different aspects, and the issue is currently in a state of 'ongoing review' due to factors such as opposition from the medical profession and political considerations. However, from the perspective that the introduction of non-face-to-face treatment should be institutionalized and legislated prioritizing patient safety, certain directions are proposed. These include focusing on returning patients as the primary target, chronic diseases as the focal conditions, outpatient medical institutions as the implementing agencies, restricting non-face-to-face means primarily to video systems, and legally exempting healthcare professionals from responsibility for incidents beyond their control. The proposed directions also emphasize establishing the right to demand face-to-face treatment. It is suggested to legislate initial standards that ensure a minimum level of safety and gradually expand the scope of non-face-to-face treatment through future research, evaluation, and similar step-by-step approaches.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.314-323
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• 2024

Recently, a score-penalty method has been used for the acoustic passive tracking of marine mammals. The interesting aspect of this technique lies in the loss function, which has a penalty term representing the mismatch between the measured signal and the modeled signal, while the traditional time-domain matched-field processing is positively considering the match between them. In this study, we apply the score-penalty method into the depth estimation of a passive target with a known source waveform. Assuming deep ocean environments with uncertainties in the sound speed profile, we evaluate the score-penalty method, comparing it with the time-domain matched field processing method. We shows that the score-penalty method is more accurate than the time-domain matched field processing method in the ocean environment with weak mismatch of sound speed profile, and has better efficiency. However, in the ocean enviroment with strong mismatch of the sound speed profile, the score-penalty method also fails in the depth estimation of a target, similar to the time-domain matched-field processing method.

• Journal of Microbiology and Biotechnology
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• v.34 no.2
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• pp.457-466
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• 2024

Cellobiose dehydrogenases (CDHs) are a group of enzymes belonging to the hemoflavoenzyme group, which are mostly found in fungi. They play an important role in the production of acid sugar. In this research, CDH annotated from the actinobacterium Cellulomonas palmilytica EW123 (CpCDH) was cloned and characterized. The CpCDH exhibited a domain architecture resembling class-I CDH found in Basidiomycota. The cytochrome c and flavin-containing dehydrogenase domains in CpCDH showed an extra-long evolutionary distance compared to fungal CDH. The amino acid sequence of CpCDH revealed conservative catalytic amino acids and a distinct flavin adenine dinucleotide region specific to CDH, setting it apart from closely related sequences. The physicochemical properties of CpCDH displayed optimal pH conditions similar to those of CDHs but differed in terms of optimal temperature. The CpCDH displayed excellent enzymatic activity at low temperatures (below 30℃), unlike other CDHs. Moreover, CpCDH showed the highest substrate specificity for disaccharides such as cellobiose and lactose, which contain a glucose molecule at the non-reducing end. The catalytic efficiency of CpCDH for cellobiose and lactose were 2.05 × 10⁵ and 9.06 × 10⁴ (M^-1 s^-1), respectively. The result from the Fourier-transform infrared spectroscopy (FT-IR) spectra confirmed the presence of cellobionic and lactobionic acids as the oxidative products of CpCDH. This study establishes CpCDH as a novel and attractive bacterial CDH, representing the first report of its kind in the Cellulomonas genus.

• Korean Journal of Ecology and Environment
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• v.37 no.1 s.106
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• pp.36-46
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• 2004

We evaluated the effect of limiting nutrients and N/P ratio on the growth of phytoplankton in a small eutrophic reservoir from November 2002 to December 2003. Nutrient limitation was investigated seasonally using nutrient enrichment bioassay (NEB). DIN/DTP and TN/TP ratio (by weight) of the reservoir during the study period ranged 17${\sim}$187 and 13${\sim}$60, respectively. Most of nitrogen in the reservoir account for $NO_3$-N, but sharp increase of ammonia was evident during the spring season. Seasonal variation of dissolved inorganic phosphorus concentration was relatively small. DTP ranged 26.5${\sim}$10.1 ${\mu}g\;P\;L^{-1}$, and the highest and lowest concentration was observed in August and December, respectively. Chlorophyll a concentration ranged 28.8${\sim}$109.7 ${\mu}g\;L^{-1}$, and its temporal variation was similar to that of cell density of phytoplankton. Dominant phytoplankton species were Bacillariphyceae (Melosira varians) and Chlorophyceae (Dictyosphaerium puchellum) in Spring (March${\sim}$April). Cyanophyceae, such as Osillatoria spp., Microcystis spp., Aphanizomenon sp. dominated from May to the freezing time. TN/TP ratio ranged from 46 to 13 (Avg. 27${\pm}$6) from June to December when cyanobacteria (Microcystis spp.) dominated. p limitation for algal growth measured in all NEB experiments (17cases), while N limitation occurred in 8 out of 17 cases. The growth rates of phytoplankton slightly increased with decreasing of DIN/DTP ratio. Evident increase was observed in the N/P ratio of > 30, and it was sustained with DTP increase until 50 ${\mu}g\;P\;L^{-1}$. Under the same N/P mass ratio with the different N concentrations (0.07, 0.7and 3.5 mg N $L^{-1}$), Microcystis spp. showed the highest growth rate in the N/P ratio of< 1 with nitrogen concentration of 3.5 mg N $L^{-1}$). The responses of phytoplankton growth to phosphate addition were clearly greater with increase of N concentration. These results indicate that the higher nitrogen concentration in the water likely induce the stronger P-limitation on the phytoplankton growth, while nitrogen deficiency is not likely the case of nutrient limitation.

• Asia pacific journal of information systems
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• v.23 no.1
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• pp.87-106
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• 2013

In the service-oriented economy, knowledge and skills are considered core resources to secure competitive advantages and service innovation. Knowledge management capability, which facilitates to produce, share, accumulate and reuse knowledge, becomes as important as knowledge itself to create service value. Along with knowledge management capability, dynamic capability and operational capability are the key capabilities related to managing service delivery processes. Previous studies indicated that these three capabilities are related to service innovation. Although separately investigate the relationship between the three capabilities. The purpose of this study is 1) to define variables that have effects on service innovation including knowledge management capability, dynamic capability and operational capability, and 2) to empirically test to identify relationship among variables. In this study, knowledge management capability is defined as the capability to manage knowledge process. Dynamic capability is regarded as the firm's ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments. Operational capability refers to a high-level routine that, together with its implementing input flows, confers upon an organization's management a set of decision options for producing significant outputs of a particular type. The proposed research model was tested against the data collected through the survey method. The survey questionnaire was distributed to the managers who participated in an educational program for management consulting. Each individual who answered the questionnaire represented a knowledge based service firm. About 212 surveys questionnaires were sent via e-mail or directly delivered to respondents. The number of useable responses was 93. Measurement items were adapted from previous studies to reflect the characteristics of the industry each informant worked in. All measurement items were in, 5 point Likert scale with anchors ranging from strongly disagree (1) to strongly agree (5). Out of 93 respondents, about 81% were male, 82% of respondents were in their 30s. In terms of jobs, managers were 39.78%, professions/technicians were 24.73%, researchers were 12.90%, and sales people were 10.75%. Most of respondents worked for medium size enterprises (47,31%) in their, less than 30 employees (46.24%) in their number of employees, and less than 10 million USD (65.59%) in terms of sales volume. To test the proposed research model, structural equation modeling (SEM) technique (SPSS 16.0 and AMOS version 5) was used. We found that the three organizational capabilities have influence on service innovation directly or indirectly. Knowledge management capability directly affects dynamic capability and service innovation but indirectly affect operational capability through dynamic capability. Dynamic capability has no direct impact on service innovation, but influence service innovation indirectly through operational capability. Operational capability was found to positively affect service innovation. In sum, three organizational capabilities (knowledge management capability, dynamic capability and operational capability) need to be strategically managed at firm level, because organizational capabilities are significantly related to service innovation. An interesting result is that dynamic capability has a positive effect on service innovation only indirectly through operational capability. This result indicates that service innovation might have a characteristics similar to process innovation rather than product orientation. The results also show that organizational capabilities are inter-correlated to influence each other. Dynamic capability enables effective resource management, arrangement, and integration. Through these dynamic capability affected activities, strategic agility and responsibility get strength. Knowledge management capability intensify dynamic capability and service innovation. Knowledge management capability is the basis of dynamic capability as well. The theoretical and practical implications are discussed further in the conclusion section.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.43-61
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• 2016

Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.