• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.17-24
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• 2023

Mobile apps frequently request permission to access sensitive data for user convenience. However, while using mobile applications, sensitive and personal data has been leaked even if users do not allow it. To deal with this problem, Google App Store has required developers to disclose how the mobile app handles user data in a privacy policy. However, users are not certain that the privacy policy describes all the app's behavior. They have no choice but to rely on the privacy policy to confirm how the app uses data. This study designed a system that checks the reliability of privacy policies by analyzing the privacy policy texts and mobile apps. First, the system extracts and analyzes the privacy policy texts to check which personal data the privacy policy discloses that the mobile apps can collect. After analyzing which data apps can access using android static analysis, we compare both results to analyze the reliability of privacy policies. For the experiment, we collected the APK files and metadata of about 13K android apps registered in the Google Play Store and preprocessed the apps by four conditions. According to the comparison between privacy policies and mobile app behavior, many apps can access more personal data than disclosed in the privacy policy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.562-565
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. However, this irregular weight distribution is not possible to be recognized with the current weight measurement system for vehicles on roads. To address this limitation, we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles from the CCTV, black box, and hand-held camera point of view. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data. From the result, we believe that public big data can be utilized more efficiently and applied to the development of an object detection-based overloaded vehicle detection model.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.95-104
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• 2009

This paper proposes the noise robust algorithm to detect the starting point of music. Detection of starting point of music is necessary to solve computational-waste problem and retrieval-comparison problem with inconsistent input data in music content based retrieval system. In particular, such detection is even more necessary in time sequential retrieval method that compares data in the sequential order of time in contents based music retrieval system. Whereas it has the long point that the retrieval is fast since it executes simple comparison in the order of time, time sequential retrieval method has the short point that data starting time to be compared should be the same. However, digitalized music cannot guarantee the equity of starting time by bit rate conversion. Therefore, this paper ensured that recognition rate shall not decrease even while executing high speed retrieval by applying time sequential retrieval method through detection of music starting point in the pre-processing stage of retrieval. Starting point detection used minimum wave model that can detect effective sound, and for strength against noise, the noises existing in mute sound were swapped. The proposed algorithm was confirmed to produce about 38% more excellent performance than the results to which starting point detection was not applied, and was verified for the strength against noise.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.179-189
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• 2001

This paper aims at faster processing and retrieval in fingerprint identification systems by reducing the amount of preprocessing and the size of the feature vector. The distribution of fingerprint directions is a set of local directions of ridges and furrows in small overlapped blocks in a fingerprint image. It is extracted initially as a set of 8-direction components through the Gabor filter bank. The discontinuous distribution of directions is smoothed to a continuous one and visualized as a direction image. Then the center of the distribution is selected as a reference point. A feature vector is composed of 192 sine values of the ridge angles at 32-equiangular positions with 6 different distances from the reference point in the direction image. Experiments show that the proposed algorithm performs the same level of correct identification as a conventional algorithm does, while speeding up the overall processing significantly by reducing the length of the feature vector.

• New & Renewable Energy
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• v.7 no.2
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• pp.10-17
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• 2011

Korea is the 11th largest energy consumption country and 96% of its total energy consumption depends on imports from overseas. Therefore it is a very important task to secure renewable energy sources which can reduce both the carbon-dioxide emission and dependency on overseas energy imports. Among the various renewable energy sources, organic wastes are important sources. In Korea, 113 million toe of methane is generated from organic wastes annually, but only 3.7% is effectively used for energy conversion. Thus, it is very important to make better use of organic wastes, especially for power generation. The goals of this project are to develope the fuel supplying system of Bio Gasturbine (GT) for 5MW-class co-generation system. The fuel supplying system mainly consists of $H_2S$ removal system, Bio Gas compression system, Siloxane removal system and moisture separating systems. The fuel requirement of 5MW-class GT is at around 60% of $CH_4$, $H_2S$ (<30 ppm), Siloxane(<10 mg/$nm^3$) and supply pressure (> 25 bar) from biogas compressor. Main mechnical charateristics of Bio Gasturbine system have the specific performance; 1) high speed turbine speed (12,840 rpm) 2) very clean emmission NOx (<50 ppm) 3) high efficiency of energy conversion rate. This paper focuses on the development of design technology for food waste biogas pretreatment system for 5MW-class biogas turbine. The study also has the plan to replace the fuel of gas turbine and other distributed power systems. As the increase of bioenergy, this system help to contribute to spread more New & Renewable Energy and the establishment of Renewable Portfolio Standards (RPS) for Korea.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.509-516
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• 2002

This paper proposes an efficient algorithm which recognizes the mixed document image consisting of the images, texts, tables, and straight lines. This system is composed of three steps. The first step is the detection of rotation angle for complementing skewed images, the second is detection of erasing an unnecessary background region and last is the classification of each component included in document images. This algorithm performs preprocessing of detecting rotation angles and correcting documents based on the detected rotation angles in order to minimize the error rate by skewness of the documentation. We detected the rotation angie using only horizontal and vertical components in document images and minimized calculation time by erasing unnecessary background region in the detecting process of component of document. In the next step, we classify various components such as image, text, table and line area included in document images. we applied this method to various document images in order to evaluate the performance of document recognition system and show the successful experimental results.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.73-81
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• 2007

This paper presents how to recognize the new-type vehicle license plate using multi-link recognizer after extract the features from characters. In order to assist this task, this paper proposed FE-MCBP to recognize each character that got through image preprocess, extract range of vehicle license plate and extract process of each character. FE-MCBP is the recognizer based on the features of the character, The recognizer is employed to identify the new-type vehicle licence plates which have both the hangul and the arabic numeral characters. And its recognition rate is improved 9.7 percent than the back propagation recognizer before. Also it makes use of extract of linear component and region coordinate generation technology to normalize a image of the tilted vehicle license plate. The recognition system of the new-type vehicle license plate make possible recognize a image of the tilted vehicle license plate when using this system. Also, this system can recognize the tilted or imperfect vehicle licence plates.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.435-442
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• 2007

To reduce damage from high concentration ozone in the air, we have researched how to predict high concentration ozone before it occurs. High concentration ozone is a rare event and its reaction mechanism has nonlinearities and complexities. In this paper, we have tried to apply and consider as many methods as we could. We clustered the data using the fuzzy c-mean method and took a rejection sampling to fill in the missing and abnormal data. Next, correlations of the input component and output ozone concentration were calculated to transform more correlated components by modified log transformation. Then, we made the prediction models using Dynamic Polynomial Neural Networks. To select the optimal model, we adopted a minimum bias criterion. Finally, to evaluate suggested models, we compared the two models. One model was trained and tested by the transformed data and the other was not. We concluded that the modified transformation effected good to ideal performance In some evaluations. In particular, the data were related to seasonal characteristics or its variation trends.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.581-587
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• 2005

This paper presents a hybrid face recognition method of both the first moment of image and the independent component analysis(ICA) of fixed point(FP) algorithm based on Newton method. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. FP-ICA is also applied to find a set of independent basis images for the faces, which is a set of statistically independent facial features. The proposed method has been applied to the problem for recognizing the 48 face images(12 persons o 4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than conventional FP-ICA without preprocessing. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2003.04a
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• pp.126-127
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• 2003

원예산물의 밀도나 비중은 내부성분, 숙도, 내부붕괴(internal breakdown)와 같은 생리장해에 큰 영향을 받기 때문에, 밀도를 측정함으로써 내부품질에 대한 간접적인 판정이 가능하다고 보고되고 있다. 이 연구는 수박의 밀도와 당도와의 상관관계를 구명하고자 수행하였으며, 이를 위해 밀도의 실시간 계측시스템을 개발하였다. 현재 농산물의 밀도를 어느 정도 측정 정밀도를 유지하면서도 신속하게 측정할 수 있는 방법은 부력법(platform scale method)이다. 이 방법은 일정 크기의 용기에 물을 가득 채운 후 대상물을 담가 배제된 물의 무게를 측정하여 밀도를 환산한다. 그러나 매번 측정할 때마다 물을 보충하고, 물을 계량해야하는 등 전처리과정이 복잡하고, 1회 측정하는데 3~5분 정도가 소요되는 단점이 있고, 또한 인력 측정시 반복간 오차가 클 것으로 예상된다. 따라서 이 연구에서는 이 같은 계측상의 번거로움을 해소하고 동시에 신속하고 반복간 측정정밀도를 높일 수 있도록 수박 밀도 실시간 계측시스템을 설계 제작하였다. 시스템은 투명아크릴 수조($\Phi$400$\times$500), 로드셀, 프레임, 채반, 전기모터, 제어장치 및 컴퓨터로 구성하였다. 밀도 계측은 인장형 로드셀(CAS SB-20L, Max. 20kg)을 사용하여 대기중에서와 수박을 완전히 물에 잠기도록 한 후 무게를 각각 측정하여 밀도를 환산하였다. 밀도 계측시스템에 이용한 AD변환기의 분해능은 12bit이고, 수박의 무게 측정범위를 4~10kg로 가정할 때 20kg 로드셀의 1 digit(1bit)로 발생되는 오차는 0.09~0.24%FS 이었고, 따라서 이 시스템의 밀도 해상도는 0.001g/㎤이하였다. 시스템 평가를 위해 탄력이 좋은 고무풍선에 수박 크기 정도로 물을 채워 고정채반에 넣고 밀도를 측정한 결과 1.002g/㎤을 나타냈다. 즉 물의 이론밀도인 1g/㎤에 근접한 값을 보여 정확한 밀도 계측이 가능한 것으로 판단되었다. 또한 밀도 계측시스템의 측정 반복간 정밀도를 파악하기 위해 수박 6개를 임으로 선정하여 3반복 측정 시험한 결과, 측정표준편차가 0.001~0.004g/㎤로 해상도보다는 다소 높았으나 대체로 양호한 결과를 나타냈다. 수박 35개를 이용하여 개발 계측시스템과 사람이 직접 부력법으로 밀도를 측정 비교한 결과, 계측시스템에 의해 측정된 수박 밀도가 사람이 측정했을 때 보다 낮게 측정되었다. 수박의 외관인자(무게, 길이, 직경, 체적), 밀도와 당도의 상관관계 구명시험을 위해 원예연구소 시험포장에서 재배된 삼복꿀수박 총 74개를 공시재료로 하였고, 시험은 출수일별로 10~14개씩 수확하여 외관인자, 밀도, 당도를 각각 측정하고, 이들 인자들간의 상관관계를 구명하였다. 외관인자들간에는 높은 상관관계를 보였으나, 외관인자들과 밀도, 외관인자들과 당도, 밀도와 당도와는 매우 낮은 상관관계를 나타냈다.