Earticle

Single-view reconstruction (SVR) is a fundamental method in computer vision. Often used for reconstructing human-made environments, the Manhattan world assumption presumes that planes in the real world exist in mutually orthogonal directions. Accordingly, this paper addresses an automatic SVR algorithm for Manhattan worlds. A method for estimating the directions of planes using graph-cut optimization is proposed. After segmenting an image from extracted line segments, the data cost function and smoothness cost function for graph-cut optimization are defined by considering the directions of the line segments and neighborhood segments. Furthermore, segments with the same depths are grouped during a depth-estimation step using a minimum spanning tree algorithm with the proposed weights. Experimental results demonstrate that, unlike previous methods, the proposed method can identify complex Manhattan structures of indoor and outdoor scenes and provide the exact boundaries and intersections of planes.

Securities and investment services have and use large data. Investors started to invest through their own analysis methods. There are 22 major securities and investment companies in Korea and only 6 companies support open API. Python is effective for requesting and receiving, analyzing text data from open API. Daishin Securities Co. is the only open API that officially supports Python, and eBest Investment & Securities Co. unofficially supports Python. There are two important differences between CYBOS plus of Daishin Securities Co. and xingAPI of eBest Investment & Securities Co. First, we must log in to CYBOS plus to access the server of Daishin Securities Co. And the python program does not require a logon. However, to receive data using xingAPI, users log on in an individual Python program. Second, CYBOS plus receives data in a Request/Reply method, and zingAPI receives data through events. It can be thought that these points will show a difference in response time. Response time is important to users who use open APIs. Data were measured from August 5, 2021, to February 3, 2022. For each measurement, 15 repeated measurements were taken to obtain 420 measurements. To increase the accuracy of the study, both APIs were measured alternately under same conditions. A paired t-test was performed to test the hypothesis that the null hypothesis is there was no difference in means. The p-value is 0.2961, we do not reject null hypothesis. Therefore, we can see that there is no significant difference between means. From the boxplot, we can see that the distribution of the response time of eBest is more spread out than that of Cybos, and the position of the center is slightly lower. CYBOS plus has no restrictions on Python programming, but xingAPI has some limits because it indirectly supports Python programming. For example, there is a limit to receiving more than one current price.

Across the world, ‘housing’ comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price ‘return rate’ prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government’s data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

This paper presents a performance evaluation of real-time Linux for industrial real-time platforms. On industrial platforms, multicore processors are popular due to their work distribution efficiency and costeffectiveness. Multicore processors, however, are not designed for applications with real-time constraints, and their performance capabilities depend on their core configurations. In order to assess the feasibility of a multicore processor for real-time applications, we conduct a performance evaluation of a general processor and a low-power processor to provide an experimental environment of real-time Linux on both Xenomai and RT-preempt considering the multicore configuration. The real-time performance is evaluated through scheduling latency and in an environment with loads on the CPU, memory, and network to consider an actual situation. The results show a difference between a low-power and a general-purpose processor, but from developer's point of view, it shows that the low-power processor is a proper solution to accommodate low power situations.

Recently, to improve the performance of the strongest channel gain user in non-orthogonal multiple access (NOMA) with a non-uniform source and symmetric superposition coding (SSC), a novel bit-to-symbol (BTS) mapping have been proposed. However, only the performance of the user with the stronger channel gain was analyzed. Thus, we compare the bit-error rate (BER) of the new BTS scheme with that of uniform sources, especially for the user with weakest channel gain. First, we show that the performance of the novel BTS scheme for the user with weakest channel gain also improves, compared to that of the uniform sources. Furthermore, the signal-to-noise (SNR) gain of the new BTS scheme over the uniform sources is calculated. As a consequence, the novel BTS scheme would improve the performance of the user with weakest channel gain as well as that with the stronger channel gain for SSC NOMA with a non-uniform source.

As smart factory is the factory which produces the products according to the customer’s diverse demand and the changing conditions in it, it can be characterized by flexible production, dynamic reconstruction, and optimized production environment. To implement these characteristics, many kind of configuration elements in the smart factory should be connected to and communicated with each other. So the network is responsible for playing this role in the smart factory. As SDN (Software Defined Network) is the technology that can dynamically cope with the explosive increasing data amount and the hourly changing network condition, it is one of network technologies that can be applied to the smart factory. In this paper, we address SDN function and operation, SDN model suitable for the smart factory, and then performs the simulation for measuring this model.

Promote the application of scientific research and technological development results to production and social life; The commercialization of scientific and technological products through the science and technology market is an effective method to exploit intellectual property at universities and research institutes. Spin-off is a popular business model in developed countries to deploy and commercialize scientific and technological research results. However, in Vietnam, this concept is not popular as well as the number of spin-off businesses is not much and does not work effectively. This article focuses on clarifying the shortcomings and difficulties in establishing spinoff businesses in universities, thereby proposing solutions to develop spin-off businesses to exploit assets intellect at universities in Vietnam

Although research on the leader's or speaker's voice has been continuously conducted, existing research has a single point of view. Sound analysis of voice characteristics has been studied from engineering perspectives, and leadership trait theory has been studied from a business perspective. Convergence studies on leader voice and member cognition are being attempted today. Convergence research on voice has a positive effect on refinement of voice analysis, diversification of voice use, and establishment of voice utilization strategy. This study explains the current flow of research on convergence between speaker's voice and listener's perception, and suggests a direction for the future development of voice fusion research. Furthermore, in connection with AI in the 4th industrial age, new attempts for voice research are sought. First, advances in AI focus on strategically generating the voices needed for individual situations. Second, the voice corrected in real time will support the leader and speaker to utilize the desired voice type. Third, voices through AI based on big data will affect the cognition, attitude and behavior of individual listeners who members, customers, and students in more diverse situations. The purpose and significance of this study is to suggest the way to research the leader's voice recognized by members, and to suggest a method that can be applied in various situations.

The current research examines whether consumers’ preference for credit card benefits (i.e., general credit card benefits vs. credit card benefits related to green life) differs according to their pro-environmental disposition. Specifically, we predict that for consumers with high (vs. low) pro-environmental disposition, their preference for credit card benefits related to green life will be higher, while preference for general credit card benefits will not be different between low and high pro-environmental disposition groups. An online survey (N = 487) was conducted to test the hypotheses. Consistent with the hypotheses, the results indicate that (1) respondents with high pro-environmental donation intention, as compared to those with low proenvironmental donation intention, had higher preference for credit card benefits related to green life; and (2) there was no significant difference in preference for general credit card benefits between high and low proenvironmental donation intention groups. We suggest an important insight into how credit card companies approaching ESG issues can increase their consumers’ preference for credit card benefits relevant to green life, considering consumers’ individual differences such as pro-environmental disposition.

The purpose of this study was to develop hand creams among the types of cosmetics based on domestic pumpkins grown in Yangju. Pumpkins are mostly used for cooking, but because they contain a large amount of vitamin A, they can also be used as raw materials for cosmetics to prevent skin aging. The final design was researched and developed through a graphic expression of pumpkin characteristics, a design process, and a survey on preference for differentiated packaging design. The survey targets women in their 20s and 30s who directly purchase cosmetics, and an analysis of consumers' preference for brand product decisions showed that simple and modern designs suitable for cosmetics images topped the list. In addition, it showed a positive image of cosmetics development using local agricultural products and high brand value. We present the possibility that domestic pumpkin raw materials can be applied to cosmetics and aim to develop excellent cosmetics brands through consumer preference surveys

The purpose of this study is to provide insights into live streaming consumer purchase intention by drawing on congruence between consumer and influencer factors and live shopping contents factors during the spread of COVID-19. We surveyed 348 individuals who have watched Fresh Hema’s live streaming. SPSS and AMOS were used for data analysis. We determined that only actual congruity between influencer and consumer significantly influenced the consumer social experience. On the other hand, both the informativeness and entertainment value of live shopping contents positively impacted the consumer social experience. Additionally, social experience was significantly related to consumer co-experience and purchase intention. Moreover, the significant mediation effect of social experience was found amongst congruence between consumer and influencers, live shopping contents, co-experience, and purchase intention.

In each country, efforts are being made to replace engine-driven cars and motorcycles using fossil fuels with electric drive. Electrically driven vehicles have the advantage of no harmful gas or environmental pollution and low noise. In the motorcycle market, China accounts for more than 95% of the world, and the electric motorcycle market is being revitalized due to the strengthening of regulations. Japan is actively preparing to include electric motorcycles in ISO 26262, forming a TF team centered on electric motorcycle producers. Therefore, it is necessary to respond to standardization targeting China and Japan in Korea. In this study, we propose a proprietary transmission model that can be applied to small electric vehicles that can be operated in hilly domestic terrain. The proposed continuously variable transmission model is a continuously variable transmission system which moves the pin between the basic disk and the rotary disk using a spline to perform shifting. The proposed continuously variable transmission model is used in the pulley configuration by connecting the linear type spline and the inclined spline with the central axis of the basic disk and the rotational disk, respectively. In addition, it can be divided into two types according to the application of the auxiliary disk, and the production drawing is completed for the practical use of the model.

It is common for commercial vehicles to make the top part according to the use after making the bear chassis, and to connect various devices with the bear chassis. Various brackets used in bear chassis for the development of all automobiles, including commercial vehicles, play a role of connecting the components required for driving and operating the car to the car body. In commercial vehicles, components necessary for operation are installed in the bear chassis; that is, the bear chassis of commercial vehicles is a space where the devices required for driving and operating the vehicle are installed. The devices required for the configuration of the vehicle are drive, brake, exhaust and steering, etc. These devices are basically connected to the body, the front axis, or the rear axis. The part interlinking the apparatuses required for the vehicle drive to the car body or axis is bracket. In this study, we analyzed the boundary conditions to evaluate the stability of the three brackets that connect the components of the car to the front axis of the new type of 30-seater bus in the development process. In order to analyze the boundary conditions, the boundary conditions according to the driving condition of the vehicle were classified. For stress analysis to evaluate the stability of brackets according to the driving state of the vehicle, it is reasonable to give the bracket a boundary condition of harsh conditions.

The purpose of this study is to evaluate the efficiency of financial support for rural industry revitalization in eastern China. Comparative analysis of the efficiency of provincial financial support for rural industrial revitalization in eastern China can provide reference for various provinces to formulate financial policies for rural revitalization. In the research process, 5 evaluation indicators were selected using the panel data of the 2016-2021 "China Financial Statistical Yearbook" and "China Statistical Yearbook", and the DEA and Malmquist index methods were used for calculation. The results show that the average efficiency of financial support for rural revitalization in the 10 eastern provinces from 2015 to 2020 was generally higher, with the efficiency values all higher than 0.8, and reached 0.908 in 2017. The comprehensive efficiency of financial support for rural industry revitalization in Tianjin, Shanghai and Hainan has reached the best. From 2015 to 2020, the total factor productivity of financial support for rural industry revitalization in the eastern region has a "V"-shaped fluctuation. Total factor productivity has the fastest growth. The provinces are Beijing, Hebei and Shandong showing negative growth. It is recommended that relevant provinces improve their strategies for financial support for the revitalization of rural industries. The scope of future research should be expanded to most areas of China and the evaluation indicators should be optimized.

After COVID-19, the number of people with sleep disorders around the world is increasing. In particular, in the flow of the 4th industrial revolution, the differentiation of types and characteristics of the sleep industry is accelerating. Therefore, in this study, the characteristics of each type of sleep-related industry were reclassified from an industrial point of view, and based on this, an attempt was made to review the classification system that can help companies develop sleep products and improve related national systems. Based on the 10th standard industry classification, we compared input cost, value, and usability and analyzed common characteristics, treatments, and preventive effects based on this. A comprehensive taxonomy using matrix analysis was reviewed. As a result, in terms of cost (A), the most common sleeping products are general mattresses and general bedding. It is an IOT device (auxiliary device), and the value aspect (B, B/D) included sleep cafe, bedding rental and management service, and sleep consulting. In terms of utility (A/B), a total of 6 product groups including sleep aids (health functional foods) belong to this category, and in terms of treatment (A/C), a total of 3 product groups including sleep clinics (medical services) belong to this category. As for the product group (A/D) with both properties, it was found that non-insurance sleep treatment medical devices, sleep-related over-the-counter drugs, and some sleep monitoring applications belong to this category. Ultimately, it was found that the sleep industry classification enables the most active product development and composition according to the relative relationship between cost and utility, and treatment and utility. appeared to be necessary.

Corporate social responsibility (CSR) is the basic strategy for enterprises to obtain competitive advantages, and reflects the most basic value orientation and development concept of enterprises. The purpose of this study is to explore the relationship between corporate culture, innovation ability and core competitiveness of enterprises from the perspective of corporate social responsibility, and to establish a model and analyze the survey data of 32 agricultural science and technology enterprises in Tianjin by using SPSS23.0. As a result of the study, we found that corporate social responsibility (Ethical responsibility, Philanthropic responsibility) has a significant positive impact on corporate culture and innovation ability, corporate culture has a significant positive impact on innovation ability and corporate core competitiveness, and innovation ability has a significant positive impact on corporate core competitiveness. Therefore, it is suggested that agricultural science and technology enterprises should fulfill their social responsibilities, form a unique corporate culture, serve agriculture with science and technology, and constantly improve the ability of agricultural science and technology innovation, so as to enhance the core competitiveness of enterprises.

This study aims to find out the associative relationship between dementia and comorbidities. To conduct this study, we used KNHDIS(Korea National Hospital Discharge In-depth Injury Survey) data from 2009 to 2018 provided by the KDCA(Korean Disease Control and Prevention Agency) annually. We used MySQL for data preprocessing and R for data analysis. As a result of applying the Apriori algorithm criteria of support(≥ 0.01), confidence(≥ 0.6), and lift(>1), seventeen rules related to dementia were discovered. The diseases associated with dementia were diabetes mellitus, hypertension, disorders of lipoprotein metabolism, glomerular disorders in diabetes mellitus, renal diseases, cardiovascular disease, cerebrovascular disease, and other urinary system disorders. This study can be utilized as primary data for the care of patients with dementia and provides implications for improving effective dementia prevention policies.