Earticle

Network virtualization (NV) increases Internet flexibility by separating policies from mechanisms. This makes developing new applications, managing the Internet, and supporting different applications much easier. In this study, we introduce a multi-layer architecture which combines multi-level multiprotocol label switching (MPLS) technology with NV. The proposed architecture combines the high speed advantage of MPLS with the high flexibility of NV. We use MPLS in MPLS technique and encapsulate each MPLS packet within another when it encounters a new virtual network. Our architecture has the potential to improve Internet flexibility and pave the way for deployment and commercialization of NV in next generation networks.

Background: Xanthosine treatment has been previously reported to increase mammary stem cell population and milk production in cattle and goats. However, the underlying molecular mechanisms associated with the increase in stem cell population and milk production remain unclear. Methods: Primiparous Beetal goats were assigned to the study. Five days post-partum, one mammary gland of each goat was infused with xanthosine (TRT) twice daily (2×) for 3 days consecutively, and the other gland served as a control (CON). Milk samples from the TRT and CON glands were collected on the 10th day after the last xanthosine infusion and the total RNA was isolated from milk fat globules (MEGs). Total RNA in MFGs was mainly derived from the milk epithelial cells (MECs) as evidenced by expression of milk synthesis genes. Significant differentially expressed genes (DEGs) were subjected to Gene Ontology (GO) terms using PANTHER and gene networks were generated using STRING db. Results: Preliminary analysis indicated that each individual goat responded to xanthosine treatment differently, with this trend being correlated with specific DEGs within the same animal’s mammary gland. Several pathways are impacted by these DEGs, including cell communication, cell proliferation and anti-microbials. Conclusions: This study provides valuable insights into transcriptomic changes in milk producing epithelial cells in response to xanthosine treatment. Further characterization of DEGs identified in this study is likely to delineate the molecular mechanisms of increased milk production and stem or progenitor cell population by the xanthosine treatment.

The first full-scale countermeasures against flood disasters were carried out at 17th century in Japan. The Saga Plain is one of the places that include such flood damage prevention facilities. At present, several facilities are left and can be seen as historic remains. It is significantly useful to find out and restore these remains and clarify their functions to consider a future flood control including catchment basin operations. In this study, overflow embankments and open levees are focused on the investigated field for estimating a controlled water flow spreading the retarding basin with sediment transports. A geotechnical sampling method is adopted in this research to obtain a plate-like sample that can be easily analyzed for estimating water flow velocity, flow direction and a process of sediment settling. An additional investigation of numerical simulation is implemented to estimate water flow on the retarding basin from the overflow embankment. Flow analysis of theriver gave a boundary condition for anotherdetail simulation of flood flow on the retarding basin. The results of geotechnical investigation and hydraulic approach show the inundated water flow is controlled in the retarding basin of the residential area. The result of this study gives a quantitative evaluationof the flood control including catchment basin operations for the river basin management.

Since the last few decades, information technology outsourcing has been observed as an instrument for technology transfer and rapid economic development, with the potential to change the fate of the nation. However, many emerging countries, including Nepal, continue to struggle to establish a foothold in the international market; they are perplexed about their path toward outsourcing, and they still have ineffective laws and policies in place. A snowball sampling method was used to collect quantitative data inside Kathmandu valley among outsourcing companies, freelancers, consultants, and policymakers. Data were properly tested for reliability using Cronbach’s Alpha, analysed using exploratory followed by confirmatory factor analysis, and results were confirmed using convergent and discriminant validity. Second-level validation was performed by partial least squares. The researcher has validated a multidimensional structural model with interdependencies between 8 unobserved and 33 observed variables using path analysis and proposed an information technology outsourcing success model for emerging markets from the vendor’s perspective. Similarly, a latent variable ‘setup quality’ was identified as a new construct omitted by previous researchers in the study of IS success. The model shall be interpreted as “the system dimensions - setup quality, system quality and service quality influence the characteristics – communication quality, user satisfaction, and usage of the products or services. The positive impact of mediating factors leads to individual and organizational benefits, resulting in the overall success of information technology outsourcing.”

차세대 이동통신 관련 경쟁기업의 기술적 역량분석을 위해 특허정보 분석을 실시하였다. 특허정보의 분석 방법으로는 출원인 분석, 기술분류 분석, 지표분석 등 여러 분석방법을 활용하였다. 경쟁기업의 기술적 역량분석 1단 계로 특허활동도(Patent Activity:PA)가 높은 출원인을 선별하였고, 2단계로 기술자립도(Technological Independence:TI) 가 높은 기술분류를 선별하였다. 그리고 1단계와 2단계 결과를 매칭하여 특허활동도가 높은 주요 출원인 중에서 기술 자립도가 높은 기술분류에 대한 포트폴리오를 작성하였다. 이와 같은 과정을 통해 경쟁기업간에 집중적으로 연구되고 있는 중요 기술 포트폴리오를 분석할 수 있다. 이 분석 결과는 기업의 R&D계획, 특허전략 수립 등 전략적 R&D 관 리 수행을 돕는 역할을 할 것이다.

Patent information analysis has been carried out for technological capability analysis of competitors relating to next generation mobile communication. Various analysis methods, such as applicant analysis, technology classification analysis, indicator analysis and the like have been utilized as a method of analyzing patent information. As a first step for the technological capability analysis of competitors, applicants having high patent activity(PA) were selected, and as a second step therefor, technology classifications showing high technological independence (TI) were selected. Furthermore, portfolios for technology classifications showing high technological independence in the patents of main applicants having high patent activity by matching results the first and second steps together were prepared. Through such a process, portfolios for important technologies which have been concentrically researched by competitors could be analyzed. Accordingly, the present analysis results will help to carry out strategic R&D management, such as the establishment of company R&D plans and patent strategies.

National park sound analysis technology can be used in various fields such as park environment management, climate change monitoring, endangered species monitoring and habitat quality management. The purpose of this study is to propose a national park management plan using sound environmental analysis technology. The study site was Mudeungsan national park. The study period was 2017. The national park sound environment analysis was classified into 1) noise mapping, 2) Trail sound classification, and 3) soundscape analysis. As a result of the noise mapping, the noise region (over 40dB) was 27.6%, the quiet zone (less than 30dB) was 35.3%. The average number of major noise sources per day was 19 automobiles, 10 military loudspeakers, and 17 airplanes. As a result of the trail sound analysis, the very noisy route was 18.4% and the quiet route was 13.8%. As a result of the soundscape analysis, the main types of high noise sound were automobile, machine, loudspeaker, airplane sound. As a result of this study, it was confirmed that Mudeungsan National Park is exposed to intense noise.

최근, 스마트폰의 사용자 수는 스마트폰 성능 향상 및 다양한 서비스 제공으로 인해 매우 빠르게 증가하고 있다. 스마트폰 사용자들은 클라우드 서비스, 게임, 뱅킹 서비스, 모바일 서비스 등의 다양한 서비스를 사용한다. 오늘날의 모바일 보안 솔루션은 악성코드를 검출하거나 모바일 장치를 관리하는 수준에 그치고 있다. 이에 인증서, 법인 문서, 개인의 신용 카드 번호와 같은 보안에 민감한 정보에 대해 서비스 해킹 및 누설을 방지하는 기술이 필요하다. 모바일 보안 기술은 피해가 발생한 사례가 있었던 만큼 최근에 관심이 증가하고 있다. 이러한 문제를 해결하기 위해서 모바일 가상화, ARM Trustzone, Globalplatform과 같은 다양한 모바일 장치의 보안 기술이 연구되었다. 따라서 본 논문에서는 정보 유출 및 해킹을 방지하기 위한 인증, 보안 정책 및 액세스 제어, 암호/키 관리, 세이프 스토리지 등의 모바일 가상화 기술과 ARM의 Trustzone의 효율적인 방법을 제안한다.

Today, a number of users using smartphone is very rapidly increasing by development of smartphone performance and providing various services. Also, they are using it for enjoying various services(cloud service, game, banking service, mobile office, etc.). today's mobile security solution is simply to detect malicious code or stay on the level of mobile device management. In particular, the services which use sensitive information, such as certificate, corporation document, personal credit card number, need the technology which are prevented from hacking and leaking it. Recently, interest of these mobile security problems are increasing, as the damage cases been occurred. To solve the problem, there is various security research such as mobile virtualization, ARM trustzone, GlobalPlatform for mobile device. Therefore, in this paper, I suggested efficient method that uses the mobile virtualization techniques of certification, security policy and access control, password/key management, safe storage, etc. and Trustzone of ARM for preventing information leakage and hacking.

The purpose of this study is to review the way how to use big data to improve the government’s crisis & emergency management capability to respond to public health crises and to suggest the future directions for improving the scientific application of big data analysis. This study classifies the specific manifestations of big data during the COVID-19 epidemic, and analyzes the advantages of using big data. Using big data to improve the government’s crisis management capabilities is mainly reflected in the following aspects: advancement of precision in response to the epidemic; promotion of the government’s internal and external cooperation; enhancement of the ability to respond to internet public opinion; promotion of the transformation of public decision-making from traditional experience to intelligent and scientific. In order to better integrate big data with public crisis governance, this study is concluded with a discussion of suggestions: improvement of big data application capabilities; enhancement of big data governance; people-oriented and paying attention to internet public opinion; innovation of public decision-making methods for big data governance.

치안, 보안, 상업 또는 군사 목적으로 드론을 사용하려는 모든 조직에서 자율 무기를 개발할 경우 의미 있는 인간 통제가 결여된다면 상당한 문제가 될 수 있다. AI 및 드론 기술의 발전, 실 제 적용, 대중의 논쟁 및 윤리적 우려를 고려할 때, 본 논문에서는 감시, 수색, 그리고 실외 범죄 현장 매핑의 치안 측면에서 세 가지 뚜렷한 드론 기술의 사용을 제안하고자 한다. 드론 사용에 관한 경찰 의사결정의 윤리는 항상 의무론적(절차 및 규칙 준수) 윤리와 공리주의적(결과 기반) 윤리 사이의 긴장 속에서 일어나게 된다. 따라서, 영국이나 한국에서 경찰기관이 감시활동을 위 해 드론을 사용할 때 고려해야 하는 윤리가 간단한 것이 아니고 복잡한 양상을 띠게 된다. 본 연 구에서는 초점집단인터뷰를 통해 윤리적 도전과 한계점에 대해서 추가적으로 논의하였고, 관련 분야의 윤리적 도전에 대한 이해가 사회정치적 맥락에 내재되어 있음을 발견하였다.

The issues of the development of autonomous weapons lacking meaningful human control are significant for any organisation that seeks to use drones for policing, security, commercial or military purposes. Against this background of advances in AI and drone technology, practical application, public controversy and ethical concern, we aim to propose the use of drone technology in three distinct aspects of policing: surveillance, search, and outdoor crime scene mapping. The ethics of police decision-making around the use of drones will always take place within that tension between deontological (process and rule-following) ethics and utilitarian (outcome-based) ethics. Such are the ethical complexities that must be considered when using drones for police surveillance, either in the UK or in the Republic of Korea. Using Focused Group Interview ethical challenges are further discussed and it is found that an understanding of ethical challenges in the field is embedded in the socio-political context.

We studied consumer reactions and awareness to the Self-Service Technology (SST) environment during the Coronavirus disease-19 (COVID-19) pandemic. This study adopted the Absorption Capacity Model as the main framework of empirical studies. In combination with the model, consumers' intention to use SST for four stages of time was identified to track the social impact of COVID-19. Using latent growth model and structural equation model, this study set organizational and environmental characteristics as the first stage of the model, and assimilation and trust as the middle stage. The results of the study showed that organizational and environmental characteristics have a positive effect on assimilation and trust, except for environmental characteristics. Consumers' SST assimilation stimulate immediate intent to use kiosks. While, consumer trust in kiosks has been shown to have a positive effect on both immediate and continuous intentions to use kiosks during the COVID-19 period.

In this study, we analyzed animal registration data to identify the most popular dog breeds raised in South Korea. And then, a dataset was collected for the identified dog breeds and used to perform transfer learning on the YOLOv8 model to develop a breed classification model, and the classification accuracy was measured for each dog breed. The accuracy of classifying dog breeds by breed was confirmed to be at least 84% and up to 100%.

We invented a wearable device that can measure voiding time and fre-quency by checking a habitual series of characteristic motions among men. This study collected and analyzed urination time data collected smart bands worn by patients to resolve the clinical issues posed by using voiding charts. By developing a smart band-based algorithm for assessing urination time in patients, this study aimed to explore the fea-sibility of urination management systems. This study aimed to assess urination time based on a patient’s posture and changes in posture. Motion data were obtained from a smart band on the arm. An algorithm that identifies the three stages of urination (forward movement, urina-tion, backward movement) was developed based on data collected from a 3-axis accelerometer and tilt angle data. Therefore, we analyze hidden Markov model (HMM)-based sequential data to determine uri-nation time. Real-time data were acquired from the smart band. For data corresponding to a specific duration, the value of the signals was calculated and then compared with the set analysis model to calculate the time of urination. The final accuracy of the algorithm was calculated based on clinical guidelines for urologists. The experiment showed a high average accuracy of 92.5%, proving the robustness of the pro-posed algorithm. The proposed urination time recognition technology draws on acceleration data and tilt angle data collected via a smart band; these data were then analyzed using a classifier after applying the HMM method.

The purpose of this study was to explore the feasibility of a urination management system by developing a smart band-based algorithm that recognizes the urination interval of women. We designed a device that recognizes the time and interval of urination based on the patient’s spe-cific posture and posture changes. The technology used for recognition applied the Radial Basis Function kernel-based Support Vector Ma-chine, a teaching and learning method that facilitates multidimensional analysis by simultaneously judging the characteristics of complex learning data. In order to evaluate the performance of the proposed recognition technique, we compared actual urination and device- sensed urination. An experiment was performed to evaluate the perfor-mance of the recognition technology proposed in this study. The effica-cy of smart band monitoring urination was evaluated in 10 female pa-tients without urination problems. The entire experiment was performed over a total of 3 days. The average age of the participants was 28.73 years (26–34 years), and there were no signs of dysuria. The final accuracy of the algorithm was calculated based on clinical guidelines for urologists. The experiment showed a high average accuracy of 91.0%, proving the robustness of the proposed algorithm. This urination behavior recogni-tion technique shows high accuracy and can be applied in clinical set-tings to characterize urination patterns in female patients. As wearable devices develop and become more common, algorithms that detect specific sequential body movement patterns that reflect specific physi-ological behaviors could become a new methodology to study human physiological behavior.

Jabon (Anthocephalus cadamba) is a promosing fast growing wood species that is widely planted in community forests and industrial plantation forests but the wood has a relatively low density, durability, and mechanical properties which limited its application as structural timbers. One of the alternative utilizations of jabon wood is by converting into wood pellet for bioenergy. The aim of this study was to improve the properties of wood pellets from jabon through rapid torrefaction using Counter-Flow Multi Baffle (COMB) reactor, a pilot plant for torrefaction of biomass with a capacity of 20 kg/h that has a main advantage of performing torrefaction within a short period of time. Wood pellets were classified according to its length and then torrefied at 300°C with a residence time of 3 min. Torrefied pellets (black pellets) were succesfully produced. The initial moisture content of the long and short pellets of 12.76% and 12.47% decreased up to 2.85% and 2.61% after torrefaction. Water immersion test for 1 min, 5 min, 30 min, 1 h, 6 h, 12 h, and 24 h showed that the raw pellets (control) fully disintegrated after 30 min, while black pellets showed no significant disintegration even after 24 h test which is an advantage for long period storage of pellets. The initial calorific values of long and short pellets of 17.69 MJ/kg and 17.35 MJ/kg increased up to 31.79 MJ/kg and 32.02 MJ/kg after torrefaction. The results proposed that rapid torrefaction using COMB could provide a great improvement in bioenergetic properties of wood pellets from fast growing species as jabon wood.

이 연구는 유러닝 이용 교육에서 신기술의 발전에 따라 나타나는 특징과 문제점 들을 사례를 분석하여 연구하였다. 이러한 유비쿼터스 환경에서 인간은 컴퓨터 능력을 갖고 있는 장치와 상호 교류가 가능하며, 유러닝을 통해 학생들은 열린 자세를 갖으며 스스로 공부하는 데 동기부여를 갖게 된다. 이는 학습과 의사소통을 효율적으로 할 수 있게 하며, 시간과 비용 에너지를 절약 할 수 있게 한다. 국내▪외 사례에서 살펴보았듯이 유러닝의 발전을 도모하기 위해서는 여러 가지 측면에서 고려되어야 할 것이지만, 교육, 학습태도, 관습, 인간관계 등에 있어 현재 보다 훨씬 광범위하게 수집되어 오용되거나 유출되는 문제를 반드시 해결해야 할 분야이다. 이를 위해 법이나 제도 그리고 윤리적 관점에서 고려되어야 할 것으로 본다.

This paper provides the emerging flow of new communication technology using ubiquitous learning (u-Learning). In the intelligent Ubiquitous environment, humans and devices with computing abilities become interoperable. u-Learning will lead students to open their minds to the world and motivate self-learning, which may lead them to learn and communicate more efficiently, and save time, cost and energy. Through case research, regarding education, learning attitude, custom and, personal relations, one must solve the fundamental issues of misuse and outflow problems regarding personal information that will be widely collected in detail than the present condition, and in order for this not to happen, further support of the law and system, plus ethical perspectives must be considered in order to progress.