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This study analyzed the effects of Yeoju, Gangcheon, Yeoju 1, Neungseo, and Daesin in the Namhan River basin on eutrophication (chlorophyll-a trophic state index: TSI) from September 2012 to December 2018 by path analysis. Depend on the standardized path coefficient, the Yeoju area had a positive (+) effect at 0.792±0.024 (p

For the reduction of sodium consumption from foods with soups or sauces for noodles, NaCl mixture (LMC-salt) was prepared with the Lentinus edodes mycelium cell wall components from mycelia grown in submerged culture. NaCl was entrapped in their cavities and also deposited on the surface of mycelium cell wall. Noodles prepared with LMC-salt (Nm) enhanced the saltiness perception up to 40%, potentially by reducing “severance of flavor” as a consequence of slower release of entrapped NaCl in L. edodes cell wall, when compared to noodles prepared with NaCl (Nc) only. Compared to Nc, lightness was lower and redness was slightly higher resulting in higher color intensity in Nm. Overall textural properties did not show significant differences. Weight and volume of the cooked Nm were decreased, while turbidity of the soup was increased compared to Nc after cooking. Overall preference was slightly lower, but did not have significant specific negative attributes. These results could support a strategic approach to reduce total sodium consumption by enhancing saltiness of noodle in noodle dishes and consequently reducing uptake of soups or sauces that are leading sources of sodium intake.

Many hospitals have been built for people in silver age and these hospitals want to set various remote health care systems for the old people who are living in a place far from these hospitals. The systems processes are connected with each other and with networks as well. These systems handle many sensitive medical records and therefore the security of the health care systems has to be improved to protect these systems from cyber-attacks. Any penetration of these systems could cause serious privacy problem. To protect these systems security programs have to be used. Therefore, this paper suggests security policy compliance of medical contents which should be followed to improve level of security including DRM to protect against illegal alteration by an attacker.

'Omni-shopper' typically decides to buy after getting information through online channels and then visit offline stores to directly experience. Therefore, offline stores should be transformed into hands-on stores that fit the latest trends in user's buying pattern. The Fast Fashion brand requires a large store because there are various types of products, and omni-shopper finds the product they prefer, verify it in the store where various product lines are displayed and uses the fitting room to find the products they want. However, in the course of actual store use, the purchasing process is delayed due to the reasons such as environmental characteristics of large stores and the queues due to the lack of fitting rooms. To solve the above problems, a store management system is required to provide real-time information about the situation that may occur in offline stores to omni-shoppers as well as employees. In this paper, we propose a store management system for improving the shopping process of omni-shoppers of SPA brands. The proposed system provides information on inventory and display location of real-time products, as well as the fitting room reservation management for offline stores with WebApp. Through the proposed system, we can anticipate the effect of improving the entire shopping process by reducing queues at the fitting area, identifying the quantity of products to wear and reducing the shopping delay caused by congestion in the fitting area. To validate the proposed system, the experiment confirmed that Arena simulations improved the time required for the shopping process to 15.7% over the previous one.

In warehousing process, picking is the matter to be considered preferentially for reducing the operating coast and improving the production efficiency. While large warehouses apply considerable amount of IT technology on picking work, most small and medium warehouses carry out picking process manually. Although manual process involves numerous errors, small and medium companies have hard time introducing the picking system due to the cost issue. To solve such problem, this study suggests the monitoring system for smart picking at small and medium warehouses. The suggested system provides the monitoring service to worker and manager at warehouse for smart picking. Also, the system includes core features such as real-time data exchange, picking service, and monitoring on inventory status. The suggested system reduces time and expense for worker and manager at warehouse. Furthermore, this study shows the processing of smart picking based on the suggesting system.

Recently, the global fast fashion brands have shown a steady rise in market share and sales despite the economic downturn. Fast fashion brands have led consumers in their 20s and 30s to the stores by creating a self- shopping environment that allows them to shop on their own without any interference from employees. The main customers of fast fashion brands are people in their 20s and 30s who have strong individualistic tendencies and enjoy shopping alone at offline stores. They also show behavior of finalizing their purchase after collecting information through online channels and trying on items at the stores. In order to provide services tailored to their consumption characteristics, a device was installed in the store to provide real-time inventory and product information. However, customers still need assistance from employees in large stores to easily locate the desired products. Therefore, this study proposes a product location guidance service using RFID tags. The proposed system adds information of the location of shelves in the store to the product size, color and quantity information provided by existing RFID tags. It also provides real-time display locations through store queries after searching for products in the APP or scanning bar codes. The system proposed in this paper mainly focuses on the customer base of Fast Fashion stores to check the display location of products via APP.

A context-aware system is required for providing context-aware services to users in the Internet of things (IoT) environment. It consists of three primary tasks: gathering context data, abstracting the collected data, and providing services to users. In IoT environments, context data are generated by a large number of sensors, and this context data are part of the context-awareness services provided to the users. When the context-aware system provides context-aware services with their service descriptions, it is necessary to process the data gathered by abstracting and contextualizing them. Generally, the context-aware system encounters a problem in that the context representations between contextualized sensor data and their related service descriptions do not match well. We herein propose a context retrieval method that facilitates in obtaining context information for the context-aware system in IoT environments. The context-aware system communicates with an ontology module that handles input data described in a set of universal resource identifiers, as a triplet. The ontology module resolves each representation request from the context-aware system. The proposed method provides an ontology-based mapping procedure for the context representation problem described above.

Many hospitals and medical clinics have been using a wearable sensor in its health care system because the wearable sensor, which is able to measure the patients’ biometric information, has been developed to analyze their patients remotely. The measured information is saved to a server in a medical center, and the server keeps the medical information, which also involves personal information, on a cloud system. The server and network devices are used by connecting each other, and sensitive medical records are dealt with remotely. However, these days, the attackers, who try to attack the server or the network systems, are increasing. In addition, the server and the network system have a weak protection and security policy against the attackers. In this paper, it is suggested that security compliance of medical contents should be followed to improve the level of security. As a result, the medical contents are kept safely.

In order to recognize the situation and to provide robot services based on big data, it is necessary to implement a machine learning model capable of analyzing big data and a method for providing this data to the analysis model for learning. Previous researches have focused on the implementation of various data analysis models to analyze the collected big data. However, in these researches, it is difficult to recognize the new data which is not learned by the analysis model, and further research is needed to solve it. In this paper, we propose a data processing method to provide context-aware information in context-aware system based on big data to provide intelligent robot services. The proposed data processing method can convert the data generated in the domain in which the robot is running to learn data of the machine learning model and provide it, thereby continuously improving the accuracy of the machine learning model. In the experiment, the context-aware information is provided through the prototype of the context-aware system with the proposed method.

All countries make an effort to ensure the safety of agricultural products in the food distribution phase. Recently, as the market size of farm produces sales has increased through on-line shopping malls, there are various researches to offer traceable information about farm produces to customers conveniently and correctly. This paper designs and implements an integrated self-advertisement system for farm produces. By offering producer`s information and traceable information about farm produces directly through the suggested system, a producer can assure the safeness of the informations and a customer can have trust in the agricultural produces. Especially, because the suggested system does not need a heavy cost or a complicated registration process for producers, it can be used as convenient and safe advertisement means and help small-scale producers a lot in increasing sales profit.

There are many actively researched works on context-aware workflows for developing intelligent robot services. It is possible to describe not only the definition of robot services but also the contextual information of user`s surroundings which can be used as the transition conditions for executing those robot services. Therefore it is required to prepare a context-aware workflow document to support the intelligent robot services. In this paper, we propose a development tool which enables robot service developers to describe context-aware workflow documents and execute them. The tool users can write robot service workflows easily by using intuitive GUI of the tool. In the experiment, we showed processes of writing robot service workflows in scenario format, then automatically documenting and executing them.

To improve work efficiency and productivity in agricultural environment, which may naturally be protean, unpredictable and laborious, many researchers have made attempts to apply information technology in the field of conventional agriculture. Especially, they have great concern toward a reasonable and reliable service control model or architecture to control agricultural works automatically and smartly. This article proposes a framework to support context-aware or smart services in agricultural environments, based on a context-aware workflow model and USN/RFID. The suggested framework is focused on supporting autonomous agricultural services in the fields of growth control, protection against disease and insects, and the output control of the agricultural computing environment using a workflow model which is one of the successful service automation models, using contexts from various sensors in agricultural fields. The proposed framework, based on a context-aware workflow, can be greatly helpful in the d...

In ubiquitous computing environments, users want to receive the robot services regardless of various physical status or devices such as time, place, various sensors, and high-performance servers. Thus, the ubiquitous service robots have to provide users with automated services according to situational information that they properly recognize. Beyond these problems, robot software has to establish a foundation to support the functions with the network infrastructure that are not able to be solved by a single independent resource. On the basis of a robot middleware that is capable of minimizing dependencies among hierarchy structures, the robot software also has to provide execution environment to control the flow of robot application services. In this paper, we propose a layered architecture to provide users with automated services through ubiquitous robots. The proposed architecture is based on CAWL (Context-Aware Workflow Language) and RSEL (Robot Services Execution Language). CAWL easily represents the flow of robot services from user application service levels, and RSEL is able to support the composition and reusability of robot services through abstraction of robot device services. In our experiments, we applied the proposed architecture to an example of "booth guide robot service".

Sensor data abstraction is necessary to provide users with context-aware services. Sensor data abstraction mechanism in context-aware system usually consists of collecting data, converting, and context reasoning. For this mechanism in IoT environments, sensor data is used that is described in the pairs of key-value set or digit value. However, environmental data cannot be sufficiently formed since these sensors data are provided with these values. For example, it may need metadata of contexts and things description. In this paper, we propose a new conceptual metadata model for sensor data abstraction in IoT environments. The proposed model provides sensor data and their metadata as low-level context, which is a part of basic context for presenting given environment, to context-aware system. In the experiments, we describe a procedure to generate low-level context for sensor data abstraction based on the proposed model and to provide this information to the context-aware system.

We performed differential-display polymerase chain reaction to find up-regulated sequences in primary human gastric cancers, and cloned one up-regulated sequence, which was expressed in all the gastric cancer cells that we examined. The cloned sequence was identified as cytoskeletal-associated protein 2 (CKAP2). We also cloned a shorter splice variant, CKAP2-s. The CKAP2 or CKAP2-s protein in HeLa cells was localized to microtubule organizing centers (MTOC) and microtubules. This co-localization pattern was disrupted by nocodazole, a microtubule-destabilizing agent. These observations suggested that CKAP2 might be associated with microtubule networks. CKAP2 protein was detected in neither normal GI tract nor normal gastric mucosa. However, both CKAP2 and CKAP2-s mRNAs were up-regulated in 55% (23 out of 42 samples) of primary human gastric cancers by reverse transcriptase-polymerase chain reaction (RT-PCR). Moreover, CKAP2 proteins were detected in immunohistochemical staining in all the gastric cancer samples that we examined. CKAP2 protein-expressing cells were also found in gastric adenomas. The average number of CKAP2 protein-positive cells in adenocarcinomas was 48.8%, which was significantly higher than the number in tubular adenomas, 9.1%. When these points were taken together, we concluded that CKAP2 is up-regulated in primary human gastric adenocarcinomas at high frequency and might be useful for diagnosing and discriminating adenocarcinomas from tubular adenomas of the stomach.

These days, using robots has gradually been extending from the limited industrial areas in factories to service areas for the general public in everyday life. It is possible to imagine that end users easily control robots and they define new services by themselves as they wish in the near future. However, there are three issues to resolve to realize the future. Firstly, it is required to abstract robots' behaviors from primitive robot functions, and secondly, we need context awareness in order to provide users with the appropriate services. Lastly end users can define the robot services easily. In this paper, we propose three layered middleware architecture for automated robot services to resolve the problems. The lowest layer abstracts robots' behaviors in functional level, and the middle layer provides users with robot services based on the situational information. And the highest layer defines robot services by sequential order. End users can define practically a flow of robot services by using an intuitive GUI. We showed the availability and effectiveness of the layered middleware architecture with a prototype system, which presents the facile definition of robot services in application level, the control process of robot service, and the abstraction process of robot services.