Recently, epidemic of covid-19 causes rapid increase in demand for untact video conferences. In existing server-client based video conference systems such as Zoom, Google Meet, etc., the server generates the conference key and controls the access rights of meeting members and their contents with it. In this case, the server can fabricate or repudiate the meeting. So, the privacy of the meeting members is not guaranteed. It’s necessary to make the conference key distribution scheme where all participants can verify the trustfulness without help of the server. The smart contract is the program stored to the blockchain. Its contents cannot be altered due to the property of the blockchain, and everybody can verify the execution results of it. In this study, we propose the smart contract based conference key distribution scheme. The proposed scheme is consisted of smart contract deployment, conference key generation and verification stages. The smart contract replaces the role of existing trustful server and the meeting members can generate the conference key according to the protocols implemented on it. The proposed scheme can be applied to the video conference systems and only the meeting members can access the conference key.
This study analyzed the effect of the number of deaths of circulatory system diseases according to 12-day short-term exposure of carbon monoxide from January 2010 to December 2018, and predicted the future treatment cost of circulatory system diseases according to increased carbon monoxide concentration. Data were extracted from Air Korea of Korea Environment Corporation and Korea Statistical Office, and analyzed using Poisson regression analysis and ARIMA intervention model. For statistical processing, SPSS Ver. 21.0 program was used. The results of the study are as follows. First, as a result of analyzing the relationship between the impact of short-term carbon monoxide exposure on death of circulatory system diseases from the day to the previous 11 days, it was found that the previous 11 days had the highest impact. Second, with the increase in carbon monoxide concentration, the future circulatory system disease treatment cost was estimated at 10,123 billion won in 2019, higher than the observed value of 9,443 billion won at the end of December 2018. In addition, when summarized by month, it can be seen that the cost of treatment for circulatory diseases increases from January to December, reflecting seasonal fluctuations. Through such research, the future for a healthy life for all citizens can be realized by distributing various devices and equipment utilizing IoT to preemptively respond to the increase in air pollutants such as carbon monoxide.
In this paper, we propose a optimal CW(Conention Window) synchronization scheme in IEEE 802.11 WLANs. IEEE 802.11 WLANs support DCF(Distributed Coordination Function) mode for the MAC(Medium Access Control) operation. In DCF, the CW increases exponentially according to the collisions and becomes minimum CW according to the success of data transmissions. However, since the base minimum CW value is hardware or standard specific, the number of active stations and network status are not considered to determine the CW value. Even though the researches on optimal CW have beend conducted, they do not consider the optimal CW synchronization among mobile stations which occur network performance degradation. Therefore, this paper calculates the optimal CW value and shares it with mobile stations in the network.
자율주행 시스템은 빅데이타를 기반으로 하여 딥러닝 시스템을 기반으로 하고 있으며, 사용되는 데이타는 다양한 센서를 이용하여 수집된다. 그런 센서에 있어서 소형화와 고성능화는 자율주행 시스템 뿐만 아니라 IoT 기반의 다양한 제품에서도 요구되고 있다. 특히, 소형화는 센서의 소형화 뿐만 아니라 센서를 설치하기 위한 기구의 소형화도 동시에 요구하고 있다. 그런 점에서 금속 기구는 센서를 고정하기 위한 가장 좋은 방법을 제시해 주고 있다. 하지만, 소형센서를 위한 금속 기구 형상을 가공하는 것이 어렵거나, 제작 비용이 높아질 수 있다. 이를 위한 대안으로 본 연구에서는 금속 필라멘트를 기반으로 한 FDM (Fused deposition modeling) 공정을 제시하고, 금속 FDM의 기초가 되는공정에 대한 연구를 진행하였다. 금속 FDM 공정을 통해서 얻어지는 금속 부품은 탈지-소결의 후 과정을 통해서 만들어진다. 본 연구에서는 출력 시 설정 변수인 내부 채움 비율(Infill rate) 과 소결 공정 후 밀도 사이에 관계를 조사하였다. 이는 내부 채움 비율과 후 처리 이후 얻어지는 시편의 밀도가 다를 수 있음을 기반으로 하고 있으며, 금속 FDM 공정이후 얻어지는 출력물의 밀도를 높이기 위한 기초 연구로 의미가 크다고 할 수 있다.
Along with the aging of the population, the number of dementia patients is increasing, and the social and economic burden is also increasing. Currently, the effective way to manage dementia patients is to identify patients with dementia early. However, in rural and island areas where medical staff are scarce, there is a problem that it is difficult to visit a hospital and get an early examination. Therefore, we propose a remote early detection system for dementia to solve the problems. The remote dementia early diagnosis system is a system that allows a patient to receive examination and treatment from a remote dementia expert using remote medical technology based on real-time image communication. The remote early diagnosis system for dementia consists of a local client system used by medical staff at health centers in the island, an image server that transmits, stores and manages images, and an expert client used by remote dementia experts. The local client subsystem satisfies the current medical law's remote collaboration by allowing the patient to use it with the health center's medical staff. In addition, expert clients are used by dementia experts, and can store/manage patient information, analyze patient history information, and predict the degree of dementia progression in the future.
It was reported that a mobile application was designed to easily provide natural dyeing information such as natural dye related resources, colors and dyed fabrics in 2007. Since studies on the linkage, application, etc. between natural dye dyeing and IoT are still lacking, diversity of information on the change of dyeing pattern by natural dye dyeing is required. In this study, it was to construct dyeing information by natural dyes, e.g., Lithospermum erythrorhizon, on silk, which has been traditionally used as many fibers in Korea. The extraction of the dye from L. erythrorhizon was carried out under pH4. The dried root of L. erythrorhizon showed dark brownish purple. Silk fabric by a without a mordant typically showed a purple dyed pattern. In the staining by sodium tartrate plus citric acid, silk fabric was stained clear brown. Interestingly, the mordant of iron (II) sulfate, the silk fabric was dyed in a light gray color rather than black. When the mordant of aluminum potassium sulfate was treated with L. erythrorhizon-extracted dye, the results were almost the same as when the mordant was not treated. When the degree of dyeing was evaluated numerically, the treatment of the mordant of potassium dichromate was about 50% darker, and the dyeing by iron (II) sulfate was about 75% darker. These results will be helpful in the study of applying various dye colors using L. erythrorhizon, and it will provide information on dyeing controller and database system construction by dyeing parameters such as dyeing degree, pH concentration, and chromaticity change.
This study intends to the estimate the determinants and state dependence of long-term care services in Korea. For this purpose, we analyzed the transition patterns among three states of long-term care service utilization over time by using the Korea Welfare Panel Study data with the random effect multinomial logit model. It is found that the result showed a strong state dependence in long-term care service utilization. Especially, long-term care insurance for the elderly showed a strong state dependence among others. Among the individual demographic characteristics, the higher the age, the higher the probability of using long-term care insurance for the elderly, while the lower the probability when married. The characteristics of the residential region showed that the residents of the urban-rural integrated region had a significantly higher probability of using long-term care insurance than the reference region. The results of this study suggest that the long-term care service users have a strong state dependence, which means that it is important to take into account the increase in the utilization period of existing users in future demand forecasting.
In this paper, I provided an approximation function using logarithm integral for the counting function of consecutive deca primes. Several personal computers and Mathematica were used to validate the approximation function . I found the real value of and approximate value of for various ≤ . By the result of theses calculations, most of the error rates are margins of error of 0.005%. Also, I proved that the sum ∞ of reciprocals of all primes with difference 10 between primes is finite. To find ∞, I computed the sum of reciprocals of all consecutive deca primes for various ≤ and I estimate that ∞ probably lies in the range ∞ ±× .
Recently, many difficulties have been faced in all parts of the world due to the impact of COVID-19. Personally, household income is decreasing sharply as many jobs disappear, and economically, many SMEs are increasingly going bankrupt. It is known that this phenomenon is highly likely to continue for the time being. In such a situation, the smart factory support project provides opportunities for difficult SMEs to improve productivity and change the corporate structure. In this study, the current status of smart factory promotion was examined, and problems occurring in the process of promoting smart factory support projects were identified. The improvement plans were derived so that more efficient projects could be promoted in the future.
In this paper, we developed a web-based DApp system based on a private blockchain by applying machine learning techniques to automatically identify Android malicious apps that are continuously increasing rapidly. The optimal machine learning model that provides 96.2587% accuracy for Android malicious app identification was selected to the authorized experimental data, and automatic identification results for Android malicious apps were recorded/managed in the Hyperledger Fabric blockchain system. In addition, a web-based DApp system was developed so that users who have been granted the proper authority can use the blockchain system. Therefore, it is possible to further improve the security in the Android mobile app usage environment through the development of the machine learning-based Android malicious app identification block chain DApp system presented. In the future, it is expected to be able to develop enhanced security services that combine machine learning and blockchain for general-purpose data.
In order to verify the effectiveness of the tea culture treatment program to mitigate the relative aggressiveness, the research will target 10 women aged 70 or older who use the P City-based Senior Citizens' Day Care Center to apply the tea culture treatment program to alleviate the relative aggressiveness of the elderly and examine its effects. As a result of the analysis, the score of reactive relational aggressiveness and leading relational aggression is 0.21 lower than the pre-exam average, indicating that the leading relational aggression of the elderly who participated in the tea culture therapy program is reduced than before the program. Based on these analysis results, practical suggestions were made for alleviating aggression among senior citizens using the Center for the Elderly.
본 논문은 스마트 팩토리(Smart Factory) 디지털 트윈(Digital Twin) 구축을 위해서 다양한 산업용 센서(IoT/ 비 IoT)로부터 센서데이터를 획득하기 위한 표준 노드(Node)를 생성하고 그룹별/공정별 존(Zone)을 연동하여 상호호환적인 데이터의 교환 기능을 제공함으로써 데이터의 안정성을 확보하고 스마트 팩토리의 디지털 트윈(Digital Twin) 을 위한 효과적인 존 마스터(Zone Master) 플랫폼 구축 방안을 제시하였다. 존 마스터(Zone Master) 플랫폼의 Process는 독립된 시스템 간의 센서 객체 및 센서 상호작용이 어떻게 수행하는지를정의해 주기 위한 인터페이스 명세를 포함하고 있으며 고유의 데이터 교환 규칙에 대한 개별 정책들을 수행하고 있다. 존 마스터 플랫폼 프로세서의 실행 통제를 위한 인터페이스는 시스템관리, 자료교환의 협상(publish-subscribe)을 위한 선언 관리, 센서 객체의 등록 및 상태 정보를 통신하기 위한 객체 관리, 속성 소유권 공유를 위한 소유권 관리, 데이터 동기화를 위한 시간 관리, 데이터 교환에 대한 Route 정보를 위한 자료 분배 관리를 제공한다.
According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.