• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• Journal of the Korean association of regional geographers
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• v.13 no.2
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• pp.143-155
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• 2007

There are many conflicts or interests among various stakeholders on the development of the coastal area. The integrated methodology, which is reflective of physical conditions, socio-economic circumstances, and people's sense of values, is thus needed to solve the problems. In this study, geographical information systems(GIS) and analytic hierarchy process(AHP) that arc one of multi-criteria analysis methodologies are loosely coupled to develop better analytic procedures for coastal assessment. Socio-economic and environmental parameters of the study area, Hampyung Bay area, are converted to a GIS system-applicable format, while AHP is used to assess the relative importance level of each parameter by calculating weighting factors. After standardizing and rasterizing spatial data from various sources. the weighting factors are applied to produce the layers for each parameter. Map algebra and overlay analyses are used to create the final layer according to the decision making logic or model proposed here. Cell values of that layer could be considered as spatial alternatives. In addition to this finding, the flexibility with the weighing factors enable decision-makers to understand the procedures and alternatives in relevance with selective strategies for coastal management.

• Journal of the Korean Geotechnical Society
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• v.39 no.4
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• pp.45-54
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• 2023

The settlement prediction during the design phase is primarily conducted using theoretical methods. However, measurement-based settlement prediction methods that predict future settlements based on measured settlement data over time are primarily used during construction due to accuracy issues. Among these methods, the hyperbolic method is commonly used. However, the existing hyperbolic method has accuracy issues and statistical limitations. Therefore, a weighted nonlinear regression hyperbolic method has been proposed. In this study, two weighting methods were applied to the weighted nonlinear regression hyperbolic method to compare and analyze the accuracy of settlement prediction. Measured settlement plate data from two sites located in Busan New Port were used. The settlement of the remaining sections was predicted by setting the regression analysis section to 30%, 50%, and 70% of the total data. Thus, regardless of the weight assignment method, the settlement prediction based on the hyperbolic method demonstrated a remarkable increase in accuracy as the regression analysis section increased. The weighted nonlinear regression hyperbolic method predicted settlement more accurately than the existing linear regression hyperbolic method. In particular, despite a smaller regression analysis section, the weighted nonlinear regression hyperbolic method showed higher settlement prediction performance than the existing linear regression hyperbolic method. Thus, it was confirmed that the weighted nonlinear regression hyperbolic method could predict settlement much faster and more accurately.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.4
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• pp.367-371
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• 2009

Analysis on optimality of the proportional navigation guidance(PNG) law is presented in this paper. While most of previous studies on optimality of PNG were relied on the linear formulation, this paper is based on the nonlinear formulation. The analysis shows that PNG is an optimal solution minimizing a range-weighted control energy, where the weighting function is an inverse of $\alpha$ power of the distance-to-target. We show that the navigation constant N is related to $\alpha$ directly. And also the conditions required to ensure the analysis result are investigated.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.797-804
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• 2017

A social network is a typical social science environment with both network and iteration characteristics. This research presents a reaction analysis model of how each node responds to social networks when given input such as promotions or incentives. In addition, the setting value of a specific node is changed while examining the response of each node. And we try to understand the reactions of the nodes involved. The reaction analysis model is constructed by applying various techniques such as unidirectional, fuzzy set, weighting, and cyclic feedback, so it can accommodate the complicated environment of practice. Finally, the implementation model is implemented using Vensim rather than NetLogo because it requires repetitive input, change of setting value in real time, and analysis of association between nodes.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.115-126
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• 2015

Although the frequency of use for community facilities in rural villages is growing as well as the importance of the facilities for urban-rural exchange is being highlighted, study on spatial location-analysis of the facilities for such multi-purpose is not so much. This study aims to find the spatial distribution forms of community facilities in rural villages such as community center and rural-pocket park through location-analysis, in order to provide available data for selecting location in the future. As the study area, Sojeong-myeon, Sejong Special City was selected. This study conducted GIS analysis for criteria of the location-evaluation model developed in this study. This study introduced the concept of time-distance for accessibility analysis. This paper also used linear-consecutive scoring method(LCSM) as a scoring method of criteria and Analytic Hierarchy Process(AHP) method for weighting values of criteria. The application results showed that the new model can generate the intensity of community facilities according to spatial distribution and accessibility from cities to the facilities.

• Water for future
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• v.26 no.3
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• pp.87-101
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• 1993

A finite element model RIV-FEM2 for the hydrodynamic study in a river is developed based on two-dimensional shallow water wave equation and dissipative Galerkin's method. RIV-FEM2 consists of pre-processing, analysis processing and post-processing. Pre- and analysis processing is programmed with Fortran-77 and post-processing with turbo-Pascal respectively. The model is tested with two dimensional problems, including flow through bends, bridges, and symmetric contraction. The two dimensional tests shows stable and efficient results for various situations. Applicability of the model is verified by applying to natural river. The model will provide a basic contribution to the hydrodynamic analysis in a river.

• Journal of the Korean Geosynthetics Society
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• v.12 no.3
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• pp.81-86
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• 2013

The object of this study is to determine checklists of agriculture reservoirs which local government managed at routine inspection by Analysis Hierarchy Process (AHP). Suggest definition of agriculture reservoirs and distinguish type of destruction of reservoirs through the analysis of domestic reservoirs or overseas. Draw damage factors of reservoirs from survey on specific area. Combine type of destruction and damage factors of reservoirs for decision of evaluation type of reservoirs. Then, determine optimized routine inspection checklists for agriculture reservoirs and reservoirs by means of AHP considering a weighting.

• Tunnel and Underground Space
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• v.24 no.5
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• pp.386-394
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• 2014

Drilling accuracy is known to be one of the most important factors determining blasting efficiency in mining by blast operation. Therefore analysing the causes of drilling error and preparing a countermeasure for minimizing drilling error are very important for blasting efficiency and safety. In this study, causes of drilling error are analyzed with dividing them into controllable factors and uncontrollable factors, and relationship between each cause is also comprehended through field measurement and AHP analysis. Finally, effective measures to help lower the drilling error are proposed with the results from weighting analysis for each factor.