• 한국균학회소식:학술대회논문집
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• 2018.05a
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• pp.13-13
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• 2018

Alternaria is a ubiquitous fungal genus, widely distributed in the environment and a range of different habitats. It includes both plant pathogenic and saprophytic species, which can affect crops in the field or cause post-harvest spoilage of plant fruits and kernels. Numerous Alternaria species cause damage to agricultural products including cereal grains, fruits and vegetables, and are responsible for severe economic losses worldwide. Most Alternaria species have the ability to produce a variety of secondary metabolites, which may play important roles in plant pathology as well as food quality and safety. Alternariol (AOH), alternariol monomethyl ether (AME), tenuazonic acid (TeA), tentoxin (TEN) and altenuene (ALT) are considered the main Alternaria compounds thought to pose a risk to human health. However, food-borne Alternaria species are able to produce many additional metabolites, whose toxicity has been tested incompletely or not tested at all. Both alternariols are mutagenic and their presence in cereal grain has been associated with high levels of human esophageal cancer in China. TeA exerts cytotoxic and phytotoxic properties, and is acutely toxic in different animal species, causing hemorrhages in several organs. The possible involvement of TA in the etiology of onyalai, a human hematological disorder occurring in Africa, has been suggested. Altertoxins (ALXs) have been found to be more potent mutagens and acutely toxic to mice than AOH and AME. Other metabolites, such as TEN, are reported to be phytotoxins, and their toxicity on animals has not been demonstrated up to now. Vegetable foods infected by Alternaria rot are obviously not suitable for consumption. Thus, whole fresh fruits are not believed to contribute significantly with Alternaria toxins to human exposure. However, processed vegetable products may introduce considerable amounts of these toxins to the human diet if decayed or moldy fruit is not removed before processing. The taxonomy of the genus is not well defined yet, which makes it difficult to establish an accurate relationship between the contaminant species and their associated mycotoxins. Great efforts have been made to organize taxa into subgeneric taxonomic levels, especially for the small-spored, food associated species, which are closely related and constitute the most relevant food pathogens from this genus. Several crops of agricultural value are susceptible to infection by different Alternaria species and can contribute to the entry of Alternaria mycotoxins in the food chain. The distribution of Alternaria species was studied in different commodities grown in Argentina. These food populations were characterized through a polyphasic approach, with special interest in their secondary metabolite profiles, to understand their full chemical potential. Alternaria species associated with tomato, bell pepper, blueberry, apples and wheat cultivated in Argentina showed a surprisingly high metabolomic and mycotoxigenic potential. The natural occurrence of Alternaria toxins in these foods was also investigated. The results here presented will provide background for discussion on regulations for Alternaria toxins in foods.

• Spatial Information Research
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• v.22 no.5
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• pp.9-18
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• 2014

According to the recent development of the ubiquitous computing environment, the use of spatio-temporal data from sensors with GPS is increasing, and studies on the Semantic Sensor Web using spatio-temporal data for providing different kinds of services are being actively conducted. Especially, the W3C developed the SSNO(Semantic Sensor Network Ontology) which uses sensor-related standards such as the SWE(Sensor Web Enablement) of OGC and defines classes and properties for expressing sensor data. Since these studies are available for the query processing about non-spatio-temporal sensor data, it is hard to apply them to spatio-temporal sensor data processing which uses spatio-temporal data types and operators. Therefore, in this paper, we developed the SWE based on SSNO which supports the spatio-temporal sensor data types and operators expanding spatial data types and operators in "OpenGIS Simple Feature Specification for SQL" by OGC. The system receives SensorML(Sensor Model Language) and O&M (Observations and Measurements) Schema and converts the data into SSNO. It also performs the efficient query processing which supports spatio-temporal operators and reasoning rules. In addition, we have proved that this system can be utilized for the web service by applying it to a virtual scenario.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.67-81
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• 2006

While the existing Web focuses on the interface with human users based on HTML, the next generation Web will focus on the interaction among software agents by using XML and XML-based standards and technologies. The inference engine, which will serve as brains of software agents in the next generation Web, should thoroughly understand the Semantic Web, the standard language of the next generation Web. As abasis for the service, the W3C (World Wide Web Consortium) has recommended SWRL (Semantic Web Rule Language) which had been made by compounding OWL (Web Ontology Language) and RuleML (Rule Markup Language). In this research, we develop a backward chaining inference engine SMART-B (SeMantic web Agent Reasoning Tools -Backward chaining inference engine), which uses SWRL and OWL to represent rules and facts respectively. We analyze the requirements for the SWRL-based backward chaining inference and design analgorithm for the backward chaining inference which reflects the traditional backward chaining inference algorithm and the requirements of the next generation Semantic Web. We also implement the backward chaining inference engine and the administrative tools for fact and rule bases into Java components to insure the independence and portability among different platforms under the environment of Ubiquitous Computing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1283-1293
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• 2014

In ubiquitous environment, data are changing rapidly and new data is coming as times passes. And sometimes all of the past data will be lost if there is not sufficient space in memory. Therefore, there is a need to make rules and combine it with new data not to lose all the past data or to deal with large amounts of data. In making decision trees and extracting rules, the weight of each of rules is generally determined by the total number of the class at leaf. The computational problem of finding a minimum finite state acceptor compatible with given data is NP-hard. We assume that rules extracted are not correct and may have the loss of some information. Because of this precondition. this paper presents a new approach for refining rules. It controls their weight of rules of previous knowledge or data. In solving rule refinement, this paper tries to make a variety of rules with pruning method with majority and minority properties, control weight of each of rules and observe the change of performances. In this paper, the decision tree classifier with extended data expression having static weight is used for this proposed study. Experiments show that performances conducted with a new policy of refining rules may get better.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.193-200
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• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Spatial Information Research
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• v.17 no.3
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• pp.361-370
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• 2009

As the increasing interests of spatial information for different application area such as disaster management, there are many researches and development of indoor spatial data models and real-time evacuation management systems. The application requires to determine and optical paths in emergency situation, to support evacuees and rescuers. The optimal path in this study is defined to guide rescuers, So, the path is from entrance to the disaster site (room), not from rooms to entrances in the building. In this study, we propose a time-dependent optimal routing algorithm to develop real-time evacuation systems. The network data that represents navigable spaces in building is used for routing the optimal path. Associated information about environment (for example, number of evacuees or rescuers, capacity of hallways and rooms, type of rooms and so on) is assigned to nodes and edges in the network. The time-dependent optimal path is defined after concerning environmental information on the positions of evacuees (for avoiding places jammed with evacuees) and rescuer at each time slot. To detect the positions of human beings in a building per time period, we use the results of evacuation simulation system to identify the movement patterns of human beings in the emergency situation. We use the simulation data of five or ten seconds time interval, to determine the optimal route for rescuers.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.39-46
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• 2007

Research on human identification in ubiquitous environment has recently attracted a lot of attention. As one of those research, gait recognition is an efficient method of human identification using physical features of a walking person at a distance. In this paper, we present a human shape extraction and tracking for gait recognition using geodesic active contour models(GACMs) combined with mean shift algorithm The active contour models (ACMs) are very effective to deal with the non-rigid object because of its elastic property. However, they have the limitation that their performance is mainly dependent on the initial curve. To overcome this problem, we combine the mean shift algorithm with the traditional GACMs. The main idea is very simple. Before evolving using level set method, the initial curve in each frame is re-localized near the human region and is resized enough to include the targe region. This mechanism allows for reducing the number of iterations and for handling the large object motion. The proposed system is composed of human region detection and human shape tracking modules. In the human region detection module, the silhouette of a walking person is extracted by background subtraction and morphologic operation. Then human shape are correctly obtained by the GACMs with mean shift algorithm. In experimental results, the proposed method show that it is extracted and tracked efficiently accurate shape for gait recognition.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1491-1497
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• 2013

Radio frequency identification (RFID) is an important and essential components of ubiquitous computing, with the development of wireless communication technologies and mobile computing environment. Recently, RFID becomes the mainstream application that helps fast handling and uniquely identifying the physical objects. It utilizes the electromagnetic energy for data transmission from a tag to a reader in the presence of arbitrary interference and noise. In order to employ the portable mobile RFID reader, a tag-collision problem between two or more adjacent tags should be considered. In this paper, we present the operation of RFID system in which numerous tags are present in the interrogation zone of a single reader at the same time. Since there may exist a number of tagged objects in the narrow area, multiple RFID tags may interfere each other, caused to degrade the data reliability and efficiency of the RFID system. In order to suppress interference signals from multiple neighboring tags, we present an application of Gold code for RFID communication system, which uses spread spectrum technique. In this RFID system, data bits are spreaded in each tags with the unique Gold code and the spreaded data bits are despreaded in the reader with the same Gold code. The performance analysis of the considered RFID anti-collision system is illustrated via computer simulation examples.

• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.431-438
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• 2007

RFID system is core technology that construct ubiquitous environment for replacement of barcode technology. Use ratio of RFID system rapidly increase because the technology has many good points such as identification speed, storage space, convenience etc. But low-cost tag operates easily by query of reader, so the system happened user privacy violent problem by tag information exposure. The system studied many ways for security application, but operation capability of low-cost tag is about $5K{\sim}10K$ gates, but only $250{\sim}3K$ gates allocated security part. So it is difficult to apply security to the system. Therefore, this scheme uses dividing 64 bits and reduces arithmetic, so proposed scheme provide mutual authentication that can apply to low-cost RFID system. Existing methods divide by 4 and used 96 bits. However, that reduces 32 bits length for lightweight and reduced from communication number of times of 7 times to 5 times. Also, because offer security by random number than existing scheme that generate two random numbers, that is more efficient. However, uses hash function for integrity that was not offered by XOR arithmetic and added extension of proposed scheme. Extended scheme is not offered efficiency than methods that use XOR arithmetic, but identification distance is mode that is proposed secure so that can use in for RFID system.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.285-298
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• 2009

According to the development of ubiquitous technologies, sensor networks is used in various area. In particular, medical field is one of the significant application areas using sensor networks, and recently it has come to be more important according to standardization of the body sensor networks technology. There are special characteristics of their own for medical sensor networks, which are different from the one of sensor networks for general application or environment. In this paper, we propose a hierarchical medical sensor networks structure considering own properties of medical applications, and also introduce transmission mechanism based on hierarchical structure. Our mechanism uses the priority and threshold value for medical sensor nodes considering patient's needs and health condition. Through this way Cluster head can transmit emergency data to the Base station rapidly. We also present the new key establishment mechanism based on key management mechanism which is proposed by L. Eschenauer and V. Gligor for our proposed structure and transmission mechanism. We use key provisioning for emergency nodes that have high priority based on patients' health condition. This mechanism guarantees the emergency nodes to establish the key and transmit the urgent message to the new cluster head more rapidly through preparing key establishment with key provisioning. We analyze the efficiency of our mechanism through comparing the amount of traffic and energy consumption with analysis and simulation with QualNet simulator. We also implemented our key management mechanism on TmoteSKY sensor board using TinyOS 2.0 and through this experiments we proved that the new mechanism could be actually utilized in network design.