• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.109-118
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• 2012

This paper theoretically derives an algorithm to discover a new type of workflow-based knowledge from workflow models, which is termed workflow-based affiliation network knowledge. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict a series of workflow-based knowledge from workflow models and their execution histories. So, this paper proposes a knowledge discovery algorithm which is able to discover workflow-based affiliation networks that represent the association and participation relationships between activities and performers defined in ICN-based workflow models. In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to derive its corresponding workflow-based affiliation network knowledge.

• Interdisciplinary Bio Central
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• v.4 no.1
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• pp.2.1-2.7
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• 2012

Introduction: Histone deacetylases (HDAC) are a class of enzymes that remove acetyl groups from ${\varepsilon}$-N-acetyl lysine amino acids of histone proteins. Their action is opposite to that of histone acetyltransferase that adds acetyl groups to these lysines. Only few HDAC inhibitors are approved and used as anti-cancer therapeutics. Thus, discovery of new and potential HDAC inhibitors are necessary in the effective treatment of cancer. Materials and Methods: This study proposed a method using support vector machine (SVM) to classify HDAC8 inhibitors and non-inhibitors in early-phase virtual compound filtering and screening. The 100 experimentally known HDAC8 inhibitors including 52 inhibitors and 48 non-inhibitors were used in this study. A set of molecular descriptors was calculated for all compounds in the dataset using ADRIANA. Code of Molecular Networks. Different kernel functions available from SVM Tools of free support vector machine software and training and test sets of varying size were used in model generation and validation. Results and Conclusion: The best model obtained using kernel functions has shown 75% of accuracy on test set prediction. The other models have also displayed good prediction over the test set compounds. The results of this study can be used as simple and effective filters in the drug discovery process.

• Management & Information Systems Review
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• v.32 no.3
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• pp.285-297
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• 2013

In this study, price discovery among the KOSPI200 markets(KOSPI200 spot, KOSPI200 Futures and The ETFs) is investigated using the vector error correction model(VECM). The main findings are as follows. KODEX200(KOSEF200), KOSPI200 spot and Futures are cointegrated in most cases. Daily data from KODEX200(KOSEF200), KOSPI200 spot and KOSPI200 futures show that the movements of the three markets are interrelated. Specially, KODEX200 contains the most information, followed by the KOSPI200 spot and futures markets. KODEX200 contribute to the price discovery process. Namely KODEX200 plays a more dominant role in price discovery than the KOSPI200 spot and futures.

• Journal of The Korean Association For Science Education
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• v.23 no.3
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• pp.215-228
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• 2003

The present study is to analyze the arguments about the generation of declarative scientific-knowledge in the philosophy of science and invent a structured model of the process of scientific-knowledge generation with the types of the generated scientific-knowledge. The invented model shows that scientific-knowledge generation is a distinctive process with the processes of inductive, abductive, and deductive thinking. Furthermore, inductive process is included with observation, which is consisted of simple observation and operative observation, and rule-discovery which is involved with the processes of commonness discovery, classification, pattern discovery, and hierarchical relationship. Also, abductive process has two components. One component generates question and second component generates hypothesis in which the process consists of representing question situation, identifying experienced situation, identifying causal explicans, and generating hypothetical explicans. Finally, deductive process is involved with logical inventing test method and evaluation criteria, concrete inventing test method and evaluation criteria, evaluating hypothesis, and making conclusion.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.112-116
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• 2004

· Dynamic Pricing vs. Fixed Pricing Auctions make both buyers and sellers engage in the price discovery process, Auctions of various kinds will replace the fixed pricing model that now pervades much of the web(pmitted)

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3369-3385
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• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• Journal of The Korean Association of Information Education
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• v.21 no.6
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• pp.619-627
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• 2017

The purpose of this study is to verify the effectiveness of the Development-oriented model (Discovery-Design-Development: DDD) for developing students' Computational Thinking skills in software education. DDD is a class model that learns the process of developing SW to solve real-life problems through three stages of Discovery, Design, and Development. In order to verify the effectiveness of the DDD, first grade students at G university who did not have SW education class were tested. As a result, the students who experienced SW development through DDD maintained the learning motivation of SW education before and after, especially the confidence area increased significantly. In addition, students also noted that the Design phase was particularly helpful in improving CT abilities and the DDD was a significant help in understanding of decomposition and algorithms.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.73-86
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• 2012

This paper theoretically derives an algorithm to discover a new type of social networks from workflow models, which is termed workflow-based social network intelligence. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict from workflow models and their execution histories. So, this paper proposes an algorithm, which is termed ICN-based workflow-based social network intelligence discovery algorithm, to be classified into the type of discovery techniques, which are able to discover workflow-based social network intelligence that are formed among workflow performers through a series of workflow models and their executions, In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to generate its corresponding workflow-based social network intelligence.

• IE interfaces
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• v.25 no.1
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• pp.52-63
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• 2012

Up-to-date enlargement of the scale of global outsourcing has brought about the need of systematic and efficient tools for competitive supplier discovery located in various areas. A web-based business supporting system, referred to as Excellent Manufacturer Scouting System(EMSS), is being developed to serve core business functions including supplier discovery, negotiation, and collaboration between overseas buyers and domestic suppliers throughout the process of supply chain formation. In this paper, a supplier assessment model devoted to evaluation of core manufacturing capability is proposed by targeting small and medium sized mold companies. The assessment model will eventually be loaded to EMSS. Even if many well-designed models for supplier assessment have been presented in literature, most of them limit the evaluation criteria to somewhat general information on a given supplier, such as cost, delivery time, quality, rather than core manufacturing capability itself. This research is pioneering work on supplier assessment from the viewpoint of manufacturability. The proposed assessment model classifies assessment indices into six criteria, which have been drawn by intensive survey and analysis of the mold industry. Actual assessment indices for each criterion are also presented along with an exemplary evaluation result.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.215-226
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• 2002

Considering the rapid process of media's breakthrough and diverse patterns of consumptions's analysis, a uniform analysis might be much rooms to be desired for interpretation of new phenomena. In special, the products happening intensive sails on around an anniversary or fresh food have the restricted marketing hours. Moreover, traditional association rule discovery algorithms might not be appropriate for analysis of sales pattern given in a specific time because existing approaches require iterative scan operation to find association rule in large scale transaction databases. in this paper, we propose an incremental candidate set management model based on twin-hashing technique to find association rule in special sales pattern using database trigger and stored procedure. We also prove performance of the proposed model through implementation and experiment.