• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.39-58
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• 2014

As the importance of big data and related technologies continues to grow in the industry, it has become highlighted to visualize results of processing and analyzing big data. Visualization of data delivers people effectiveness and clarity for understanding the result of analyzing. By the way, visualization has a role as the GUI (Graphical User Interface) that supports communications between people and analysis systems. Usually to make development and maintenance easier, these GUI parts should be loosely coupled from the parts of processing and analyzing data. And also to implement a loosely coupled architecture, it is necessary to adopt design patterns such as MVC (Model-View-Controller) which is designed for minimizing coupling between UI part and data processing part. On the other hand, big data can be classified as structured data and unstructured data. The visualization of structured data is relatively easy to unstructured data. For all that, as it has been spread out that the people utilize and analyze unstructured data, they usually develop the visualization system only for each project to overcome the limitation traditional visualization system for structured data. Furthermore, for text data which covers a huge part of unstructured data, visualization of data is more difficult. It results from the complexity of technology for analyzing text data as like linguistic analysis, text mining, social network analysis, and so on. And also those technologies are not standardized. This situation makes it more difficult to reuse the visualization system of a project to other projects. We assume that the reason is lack of commonality design of visualization system considering to expanse it to other system. In our research, we suggest a common information model for visualizing text data and propose a comprehensive and reusable framework, TexVizu, for visualizing text data. At first, we survey representative researches in text visualization era. And also we identify common elements for text visualization and common patterns among various cases of its. And then we review and analyze elements and patterns with three different viewpoints as structural viewpoint, interactive viewpoint, and semantic viewpoint. And then we design an integrated model of text data which represent elements for visualization. The structural viewpoint is for identifying structural element from various text documents as like title, author, body, and so on. The interactive viewpoint is for identifying the types of relations and interactions between text documents as like post, comment, reply and so on. The semantic viewpoint is for identifying semantic elements which extracted from analyzing text data linguistically and are represented as tags for classifying types of entity as like people, place or location, time, event and so on. After then we extract and choose common requirements for visualizing text data. The requirements are categorized as four types which are structure information, content information, relation information, trend information. Each type of requirements comprised with required visualization techniques, data and goal (what to know). These requirements are common and key requirement for design a framework which keep that a visualization system are loosely coupled from data processing or analyzing system. Finally we designed a common text visualization framework, TexVizu which is reusable and expansible for various visualization projects by collaborating with various Text Data Loader and Analytical Text Data Visualizer via common interfaces as like ITextDataLoader and IATDProvider. And also TexVisu is comprised with Analytical Text Data Model, Analytical Text Data Storage and Analytical Text Data Controller. In this framework, external components are the specifications of required interfaces for collaborating with this framework. As an experiment, we also adopt this framework into two text visualization systems as like a social opinion mining system and an online news analysis system.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.475-482
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• 2013

Several approaches to recommendation systems have been studied. One of the most successful technologies for building personalization and recommendation systems is collaborative filtering, which is a technique that provides a process of filtering customer information based on such information profiles. Collaborative filtering systems, however, have a sparsity if there is not enough data to recommend. In this paper, we suggest a movie recommendation system, based on the weighted personal propensity and the collaborating filtering system, in order to provide a solution to such sparsity. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a weighted personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the optimal personalization factors.

• Journal of Periodontal and Implant Science
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• v.47 no.5
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• pp.328-338
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• 2017

Purpose: Chronic periodontitis is an inflammatory disease induced by pathogenic bacterial accumulation. A novel index, the periodontal inflamed surface area (PISA), represents the sum of the periodontal pocket depth of bleeding on probing (BOP)-positive sites. It is advantageous for data processing and analysis because it can be treated as a continuous variable to quantify periodontal inflammation. In the present study, we evaluated correlations between PISA and periodontal classifications, and examined PISA as an index integrating the discrete conventional periodontal indexes. Methods: This study was a cross-sectional subgroup analysis of data from a prospective cohort study investigating the association between chronic periodontitis and the clinical features of ankylosing spondylitis. Data from 84 patients without systemic diseases (the control group in the previous study) were analyzed in the present study. Results: PISA values were positively correlated with conventional periodontal classifications (Spearman correlation coefficient=0.52; P<0.01) and with periodontal indexes, such as BOP and the plaque index (PI) (r=0.94; P<0.01 and r=0.60; P<0.01, respectively; Pearson correlation test). Porphyromonas gingivalis expression and the presence of serum P. gingivalis antibodies were significant factors affecting PISA values in a simple linear regression analysis, together with periodontal classification, PI, bleeding index, and smoking, but not in the multivariate analysis. In the multivariate linear regression analysis, PISA values were positively correlated with the quantity of current smoking, PI, and severity of periodontal disease. Conclusions: PISA integrates multiple periodontal indexes, such as probing pocket depth, BOP, and PI into a numerical variable. PISA is advantageous for quantifying periodontal inflammation and plaque accumulation.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.107-112
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• 2018

In this paper, optical flow based keypoint detection and tracking technique is proposed for the collaboration between flying drone with vision system and ground robots. There are many challenging problems in target detection research using moving vision system, so we combined the improved FAST algorithm and Lucas-Kanade method for adopting the better techniques in each feature detection and optical flow motion tracking, which results in 40% higher in processing speed than previous works. Also, proposed image binarization method which is appropriate for the given marker helped to improve the marker detection accuracy. We also studied how to optimize the embedded system which is operating complex computations for intelligent functions in a very limited resources while maintaining the drone's present weight and moving speed. In a future works, we are aiming to develop collaborating smarter robots by using the techniques of learning and recognizing targets even in a complex background.

• Journal of Biosystems Engineering
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• v.42 no.1
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• pp.23-43
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• 2017

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.26-36
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• 2022

Recently, studies have been conducted to cluster vehicles and disseminate safety messages in a VANET environment for driver safety and smoothy traffic. This paper proposes cluster management scheme for safety message dissemination through V2V communication and V2I communication in a VANET environment with high vehicle density and mobility. The proposed scheme reduces packet loss by selecting CH considering reception quality, total data owned by vehicles, moving speed, and connected vehicles, and maintaining cluster head candidates, which are the main agents of message dissemination, considering frequent cluster departures and subscriptions. In addition, the proposed scheme reduces duplicate messages by utilizing clusters by collaborating with a Road side unit(RSU). To prove the excellence of the proposed scheme, various performance evaluations are performed in terms of message packet loss and the number of RSU processing requests. As a result of performance evaluation, the cluster management scheme proposed in this paper shows better performance than the existing scheme.

• The Journal of Fisheries Business Administration
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• v.18 no.1
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• pp.59-97
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• 1987

Tuna and tuna fishing extend over most of the tropical waters of the world oceans, especially, this study of the Indian Ocean and the fish and the fishing vessels are highly mobile. No country can deal in isolation with the problems of its tuna fishery and of any tuna fishery in its waters, without collaborating with other countries. This cooperation is often best established through some formal international mechanism. The essential requirements are for information-on the resources, the fishery, the trade-and to identify where management actions are needed to consore the resources or to maintain the economic or social function of the fishery. These will also usually require some form of international mechanism. With the changes in the Law of the Sea, the siuuation in respect of management of tuna-considered among the highly migratory species, requirng special treatment-has also changed. At present there are both uncertainty regarding tuna management and political arguments as to how such management can be best implemented. Bearing this in mind, together with the fact that only few tuna stocks have shown clear evidence of serious depletion through over-exploitation, present emphasis will be placed on information requirements. This study included compiling the data necessary to review the state of stoks in the Indian Ocean tuna fishing grounds. Information on the resources-where the fish are, their quantity, their movements, etc. is important, whether in planning development of new fisheries, or considering the need for collaboration with other countries (in ascertaining to what extent their catches may affect catches of the natoinal fleet) or for conservation measures. A major source of information is the statistics of for conservation measures. A major source of information is the statistics of catch and fishing effort from existing commercial vessels. These need to be assembled for all fisheries on the same stock on an oceanwide basis. The statistical data also need to be analysed and intepreted, and combined with biological data(e.g., on growth, mortality and migration rates) to provide information that is intelligible and useful for administrators and other decision-makers. This must also be undertaken on a resource-wide or ocean-wide basis. Finally, because of the world-wide similarities in the methods of datching, processing and marketing fish, there is a particular tut not exclusive need in those countries just beginning to develop their tuna fisheries-to have ready access to a syntheis of information on tuna, tuna biology and tuna fisheries and tuna fisheries economics and management on the Indian Ocean.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.287-300
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• 2021

Collaborative Cyber-Physical Systems (CCPS) are those systems that contain tightly coupled physical and cyber components, massively interconnected subsystems, and collaborate to achieve a common goal. The safety of a single Cyber-Physical System (CPS) can be achieved by following the safety standards such as ISO 26262 and IEC 61508 or by applying hazard analysis techniques. However, due to the complex, highly interconnected, heterogeneous, and collaborative nature of CCPS, a fault in one CPS's components can trigger many other faults in other collaborating CPSs. Therefore, a safety assurance technique based on fault criticality analysis would require to ensure safety in CCPS. This paper presents a Fault Criticality Matrix (FCM) implemented in our tool called CPSTracer, which contains several data such as identified fault, fault criticality, safety guard, etc. The proposed FCM is based on composite hazard analysis and content-based relationships among the hazard analysis artifacts, and ensures that the safety guard controls the identified faults at design time; thus, we can effectively manage and control the fault at the design phase to ensure the safe development of CPSs. To justify our approach, we introduce a case study on the Platooning system (a collaborative CPS). We perform the criticality analysis of the Platooning system using FCM in our developed tool. After the detailed fault criticality analysis, we investigate the results to check the appropriateness and effectiveness with two research questions. Also, by performing simulation for the Platooning, we showed that the rate of collision of the Platooning system without using FCM was quite high as compared to the rate of collisions of the system after analyzing the fault criticality using FCM.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.3
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• pp.67-76
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• 2020

With the fast development in wireless communications and vehicular technologies, vehicular ad hoc networks (VANETs) have enabled to deliver data between vehicles. Recently, VANETs introduce a Vehicular Cloud (VC) model for collaborating to share and use resources of vehicles to create value-added services. To construct a VC, a vehicle should search vehicles that intend to provide their own resource. The single-hop search cannot search enough provider vehicles due to a small coverage and non-line-of-sights of communications. On the other hand, the multi-hop search causes very high traffics for large coverage searching and frequent connection breakages. Recently, many Roadside Units (RSUs) have been deployed on roads to collect the information of vehicles in their own coverages and to connect them to Internet. Thus, we propose a RSU-aided vehicular resource search and cloud construction mechanism in VANETS. In the proposed mechanism, a RSU collects the information of location and mobility of vehicles and selects provider vehicles enabled to provide resources needed for constructing a VC of a requester vehicle based on the collected information. In the proposed mechanism, the criteria for determining provider vehicles to provide resources are the connection duration between each candidate vehicle and the requester vehicle, the resource size of each candidate vehicle, and its connection starting time to the requester vehicle. Simulation results verify that the proposed mechanism achieves better performance than the existing mechanism.