Effects of an Aspirated Radiation Shield on Temperature Measurement in a Greenhouse (강제 흡출식 복사선 차폐장치가 온실의 기온측정에 미치는 영향)
-
- Journal of Bio-Environment Control
- /
- v.28 no.1
- /
- pp.78-85
- /
- 2019
This study was designed to examine the performance of an aspirated radiation shield(ARS), which was made at the investigator's lab and characterized by relatively easier making and lower costs based on survey data and reports on errors in its measurements of temperature and relative humidity. The findings were summarized as follows: the ARS and the Jinju weather station made measurements and recorded the range of maximum, average, and minimum temperature at
Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.
With the increasing complexity and irregularity of disaster types, the need for cultural asset preservation and management from a proactive perspective has increased as a number of cultural properties have been destroyed and damaged by various natural and humanistic factors. In consideration of these circumstances, the Cultural Heritage Administration enacted an Act in December 2005 to enforce the regular commission of surveys for the systematic preservation and management of cultural assets, and through a recent revision of this Act, the investigation cycle has been reduced from five to three years, and the object of regular inspections has been expanded to cover registered cultural properties. According to the ordinance, a periodic survey of city- or province-designated heritage is to be carried out mainly by metropolitan and provincial governments. The Seoul Metropolitan Government prepared a legal basis for commissioning regular surveys under the Seoul Special City Cultural Properties Protection Ordinance 2008 and, in recognition of the importance of preventive management due to the large number of cultural assets located in the city center and the high demand for visits, conducted regular surveys of the entire city-designated cultural assets from 2016 to 2018. Upon the first survey being completed, it was considered necessary to review the policy effectiveness of the system and to conduct a comprehensive review of the results of the regular surveys that had been carried out to enhance the management of cultural assets. Therefore, the present study examined the comprehensive management status of the cultural assets designated by the Seoul Metropolitan Government for three years (2016-2018), assessing the performance and identifying limitations. Additionally, ways to improve it were sought, and a DB establishment plan for the establishment of an integrated management system under the auspices of the Seoul Metropolitan Government was proposed. Specifically, survey forms were administered under the Guidelines for the Operation of Periodic Surveys of National Designated Cultural Assets; however, the types of survey forms were reclassified and further subdivided in consideration of the characteristics of the designated cultural assets, and manuals were developed for consistent and specific information technologies in respect of the scope and manner of the survey. Based on this analysis, it was confirmed that 401 cases (77.0%) out of 521 cases were generally well preserved; however, 102 cases (19.6%) were found to require special measures such as attention, precision diagnosis, and repair. Meanwhile, there were 18 cases (3.4%) of unsurveyed cultural assets. These were inaccessible to the investigation at this time due to reasons such as unknown location or closure to the public. Regarding the specific types of cultural assets, among a total of 171 cultural real estate properties, 63 cases (36.8%) of structural damage were caused by the failure and elimination of members, and 73 cases (42.7%) of surface area damage were the result of biological damage. Almost all plants and geological earth and scenic spots were well preserved. In the case of movable cultural assets, 25 cases (7.1%) among 350 cases were found to have changed location, and structural damage and surface area damage was found according to specific material properties, excluding ceramics. In particular, papers, textiles, and leather goods, with material properties that are vulnerable to damage, were found to have greater damage than those of other materials because they were owned and managed by individuals and temples. Thus, it has been confirmed that more proactive management is needed. Accordingly, an action plan for the comprehensive preservation and management status check shall be developed according to management status and urgency, and the project promotion plan and the focus management target should be selected and managed first. In particular, concerning movable cultural assets, there have been some cases in which new locations have gone unreported after changes in ownership (management); therefore, a new system is required to strengthen the obligation to report changes in ownership (management) or location. Based on the current status diagnosis and improvement measures, it is expected that the foundation of a proactive and efficient cultural asset management system can be realized through the establishment of an effective mid- to long-term database of the integrated management system pursued by the Seoul Metropolitan Government.
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we outlined the process of administrating the study. We performed three rounds. In the first and second rounds of the Delphi questionnaire, we gathered a set of exclusive factors for information privacy concern in context-aware personalized services. The respondents were asked to provide at least five main factors for the most appropriate understanding of the information privacy concern in the first round. To do so, some of the main factors found in the literature were presented to the participants. The second round of the questionnaire discussed the main factor provided in the first round, fleshed out with relevant sub-factors. Respondents were then requested to evaluate each sub factor's suitability against the corresponding main factors to determine the final sub-factors from the candidate factors. The sub-factors were found from the literature survey. Final factors selected by over 50% of experts. In the third round, a list of factors with corresponding questions was provided, and the respondents were requested to assess the importance of each main factor and its corresponding sub factors. Finally, we calculated the mean rank of each item to make a final result. While analyzing the data, we focused on group consensus rather than individual insistence. To do so, a concordance analysis, which measures the consistency of the experts' responses over successive rounds of the Delphi, was adopted during the survey process. As a result, experts reported that context data collection and high identifiable level of identical data are the most important factor in the main factors and sub factors, respectively. Additional important sub-factors included diverse types of context data collected, tracking and recording functionalities, and embedded and disappeared sensor devices. The average score of each factor is very useful for future context-aware personalized service development in the view of the information privacy. The final factors have the following differences comparing to those proposed in other studies. First, the concern factors differ from existing studies, which are based on privacy issues that may occur during the lifecycle of acquired user information. However, our study helped to clarify these sometimes vague issues by determining which privacy concern issues are viable based on specific technical characteristics in context-aware personalized services. Since a context-aware service differs in its technical characteristics compared to other services, we selected specific characteristics that had a higher potential to increase user's privacy concerns. Secondly, this study considered privacy issues in terms of service delivery and display that were almost overlooked in existing studies by introducing IPOS as the factor division. Lastly, in each factor, it correlated the level of importance with professionals' opinions as to what extent users have privacy concerns. The reason that it did not select the traditional method questionnaire at that time is that context-aware personalized service considered the absolute lack in understanding and experience of users with new technology. For understanding users' privacy concerns, professionals in the Delphi questionnaire process selected context data collection, tracking and recording, and sensory network as the most important factors among technological characteristics of context-aware personalized services. In the creation of a context-aware personalized services, this study demonstrates the importance and relevance of determining an optimal methodology, and which technologies and in what sequence are needed, to acquire what types of users' context information. Most studies focus on which services and systems should be provided and developed by utilizing context information on the supposition, along with the development of context-aware technology. However, the results in this study show that, in terms of users' privacy, it is necessary to pay greater attention to the activities that acquire context information. To inspect the results in the evaluation of sub factor, additional studies would be necessary for approaches on reducing users' privacy concerns toward technological characteristics such as highly identifiable level of identical data, diverse types of context data collected, tracking and recording functionality, embedded and disappearing sensor devices. The factor ranked the next highest level of importance after input is a context-aware service delivery that is related to output. The results show that delivery and display showing services to users in a context-aware personalized services toward the anywhere-anytime-any device concept have been regarded as even more important than in previous computing environment. Considering the concern factors to develop context aware personalized services will help to increase service success rate and hopefully user acceptance for those services. Our future work will be to adopt these factors for qualifying context aware service development projects such as u-city development projects in terms of service quality and hence user acceptance.
The purpose of this study was to investigate the recognition and satisfaction with the menu quality of food services in an immigration detention center. The survey was conducted from January 22, 2010 to April 22, 2010 by questionnaires. A survey with 265 respondents was conducted and data analyzed by the SAS Program. In analyzing leftovers, the most common was kimchi (37.61%), followed by breads (21.52%), and beans/bean curd (17.99%). The common cause for leftover were undesirable taste (31.84%), sickness or a lack of desire for eating (19.85%). In terms of cooking methods, stir-frying, broiling, and frying were highly preferred to steaming, boiling, and salting. In the analysis of preferences in the taste and satisfaction of food service, there were significant differences in hot, sour, bitter, and light tastes (p<0.05, p<0.01, p<0.001). Satisfaction was low with hot and light tastes, whereas sour and the bitter tastes showed a high degree of satisfaction. In the opinions for quality improvement, most immigrants wanted a tastier food supply (58.69%), a diverse food supply (40.54%), and clean utensils (36.68%). In the analysis of the gap between importance and performance, food taste, variety, and sanitation were recognized as poorly performed, causing major dissatisfaction with the food. The overall satisfaction score was 'average' (3 points out of 5 points) with 3.26 points. The satisfaction score showed insignificant difference depending on religions and duration of stay in Korea, but showed significant differences depending on nationality (p<0.001).
This study was conducted to identify daily caffeine intakes in beverages for elementary school children and to evaluate its effectiveness after nutrition education. The caffeine contents of 140 commercial beverages were analysed by high performance liquid chromatography-ultraviolet detector (HPLC-UV) and information about their consumption were obtained by surveying 267 children. Researchers gave nutrition education to the children, who were 6 to 11 years old and attended 9 classes of 3 elementary schools, by lecture, Powerpoint file and moving picture. Their preference and intake amount on beverages were investigated by questionnaire before and after nutrition education. The order on caffeine contents was coffee (
The purposes of this study were to investigate the genetic variations by backcrossing in commercial chickens. Backcrossing was carried out successively back to parent stock (P.S). Heritabilities and genetic correlation coefficients were estimated to verify the genetic variations. The data obtained from a breeding programme with commercial chickens (I strain) were collected from 1955 to 1987 at Poultry Breeding Farm, Seoul National University. Data came from a total of 1230 female offspring. The results obtained are summarized as follows: 1. The general performance (