• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Journal of IKEEE
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• v.18 no.4
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• pp.552-558
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• 2014

This paper suggests how to design a ZigBee-chip-based communication module to remotely measure radiation level. The suggested communication module consists of two control processors for the chip as generally required to configure a ZigBee system, and one chip module to configure a ZigBee RF device. The ZigBee-chip-based communication module for remote radiation measurement consists of a wireless communication controller; sensor and high-voltage generator; charger and power supply circuit; wired communication part; and RF circuit and antenna. The wireless communication controller is to control wireless communication for ZigBee and to measure radiation level remotely. The sensor and high-voltage generator generates 500 V in two consecutive series to amplify and filter pulses of radiation detected by G-M Tube. The charger and power supply circuit part is to charge lithium-ion battery and supply power to one-chip processors. The wired communication part serves as a RS-485/422 interface to enable USB interface and wired remote communication for interfacing with PC and debugging. RF circuit and antenna applies an RLC passive component for chip antenna to configure BALUN and antenna impedance matching circuit, allowing wireless communication. After configuring the ZigBee-chip-based communication module, tests were conducted to measure radiation level remotely: data were successfully transmitted in 10-meter and 100-meter distances, measuring radiation level in a remote condition. The communication module allows an environment where radiation level can be remotely measured in an economically beneficial way as it not only consumes less electricity but also costs less. By securing linearity of a radiation measuring device and by minimizing the device itself, it is possible to set up an environment where radiation can be measured in a reliable manner, and radiation level is monitored real-time.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.7
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• pp.711-719
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• 2011

A study of miniaturization of an L-band orthomode transducer(OMT) for field experiments of radar backscatter is presented in this paper. The proposed OMT is not required the additional waveguide taper structures to connect with a standard adaptor by the newly designed junction structure which bases on a waveguide taper. Total length of the OMT for L-band is about 1.2 ${\lambda}_o$(310 mm) and it's a size of 60 % of the existing OMTs. And, to increase the matching and isolation performances of each polarization, two conducting posts are inserted. The bandwidth of 420 MHz and the isolation level of about 40 dB are measured in the operating frequency. The L-band scatterometer consisting of the manufactured OMT, a horn-antenna and network analyzer(Agilent 8753E) was used STCT and 2DTST to analysis the measurement accuracy of radar backscatter. The full-polarimetric RCSs of test-target, 55 cm trihedral corner reflector, measured by the calibrated scatterometer have errors of -0.2 dB and 0.25 dB for vv-/hh-polarization, respectively. The effective isolation level is about 35.8 dB in the operating frequency. Then, the horn-antenna used to measure has the length of 300 mm, the aperture size of $450{\times}450\;mm^2$, and HPBWs of $29.5^{\circ}$ and $36.5^{\circ}$ on the principle E-/H-planes.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.2
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• pp.239-272
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• 2014

The rights and obligations of the Member States of ITU in the domain of international frequency management of the spectrum/orbit resource are incorporated in the Constitution and Convention of the ITU and in the Radio Regulations that complement them. These instruments contain the main principles and lay down the specific regulations governing the major elements such as rights and obligations of member administrations in obtaining access to the spectrum/orbit resource, as well as international recognition of these rights by recording frequency assignments and, as appropriate, any associated orbits, including the geostationary-satellite orbits used or intended to be used in the Master International Frequency Register (MIFR) Coordination is a further step in the process leading up to notification of the frequency assignments for recording in the MIFR. This procedure is a formal regulatory obligation both for an administration seeking to assign a frequency in its network and for an administration whose existing or planned services may be affected by that assignment. Regulatory problem lies in allowing administrations to fulfill their "bringing into use" duty for preserving his filing simply putting any satellites, whatever nationlity or technical specification may be, into filed orbit. This sort of regulatory lack may result in the emergence of the secondary market for satellite orbit. Within satellite orbit secondary market, the object of transaction may be the satellite itself, or the regulatory rights in rem, or the orbit registered in the MIFR. Recent case of selling the Koreasat belongs to the typical example of orbit transaction between private companies, the legality of which remains doubtedly controversial from the perspective of international space law as well as international transaction law. It must be noted, however, that the fact is the Koreasat 3 and its filed orbit is for sale.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.61-75
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• 2011

A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.97-107
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• 2011

Nowadays there are a lot of issues about copyright infringement in the Internet world because the digital content on the network can be copied and delivered easily. Indeed the copied version has same quality with the original one. So, copyright owners and content provider want a powerful solution to protect their content. The popular one of the solutions was DRM (digital rights management) that is based on encryption technology and rights control. However, DRM-free service was launched after Steve Jobs who is CEO of Apple proposed a new music service paradigm without DRM, and the DRM is disappeared at the online music market. Even though the online music service decided to not equip the DRM solution, copyright owners and content providers are still searching a solution to protect their content. A solution to replace the DRM technology is digital audio watermarking technology which can embed copyright information into the music. In this paper, the author proposed a new audio watermarking algorithm with two approaches. First, the watermark information is generated by two dimensional barcode which has error correction code. So, the information can be recovered by itself if the errors fall into the range of the error tolerance. The other one is to use chirp sequence of CDMA (code division multiple access). These make the algorithm robust to the several malicious attacks. There are many 2D barcodes. Especially, QR code which is one of the matrix barcodes can express the information and the expression is freer than that of the other matrix barcodes. QR code has the square patterns with double at the three corners and these indicate the boundary of the symbol. This feature of the QR code is proper to express the watermark information. That is, because the QR code is 2D barcodes, nonlinear code and matrix code, it can be modulated to the spread spectrum and can be used for the watermarking algorithm. The proposed algorithm assigns the different spread spectrum sequences to the individual users respectively. In the case that the assigned code sequences are orthogonal, we can identify the watermark information of the individual user from an audio content. The algorithm used the Walsh code as an orthogonal code. The watermark information is rearranged to the 1D sequence from 2D barcode and modulated by the Walsh code. The modulated watermark information is embedded into the DCT (discrete cosine transform) domain of the original audio content. For the performance evaluation, I used 3 audio samples, "Amazing Grace", "Oh! Carol" and "Take me home country roads", The attacks for the robustness test were MP3 compression, echo attack, and sub woofer boost. The MP3 compression was performed by a tool of Cool Edit Pro 2.0. The specification of MP3 was CBR(Constant Bit Rate) 128kbps, 44,100Hz, and stereo. The echo attack had the echo with initial volume 70%, decay 75%, and delay 100msec. The sub woofer boost attack was a modification attack of low frequency part in the Fourier coefficients. The test results showed the proposed algorithm is robust to the attacks. In the MP3 attack, the strength of the watermark information is not affected, and then the watermark can be detected from all of the sample audios. In the sub woofer boost attack, the watermark was detected when the strength is 0.3. Also, in the case of echo attack, the watermark can be identified if the strength is greater and equal than 0.5.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Investigative Magnetic Resonance Imaging
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• v.18 no.4
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• pp.341-351
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• 2014

Purpose : In this study, the medication effects of Milnacipran and Pregabalin, as well known as fibromyalgia treatment medicine, in fibromyalgia syndrome patients were compared through the change of BOLD signal in pain related functional MRI. Materials and Methods: Twenty fibromyalgia syndrome patients were enrolled in this study and they were separated into two groups according to the treatment medicine: 10 Milnacipran (MLN) treatment group and 7 Pregabalin (PGB) treatment group. For accurate diagnosis, all patients underwent several clinical tests. Pre-treated and post-treated fMRI image with block-designed pressure-pain stimulation for each group were obtained to conduct the statistical analysis of paired t-test and two sample t-test. All statistical significant level was less than 0.05. Results: In clinical tests, the clinical scores of the two groups were not significantly different at pre-treatment stage. But, PGB treatment group had lower Widespread Pain Index (WPI) and Brief Fatigue Inventory (BFI) score than those of MLN treatment group at post-treatment stage. In functional image analysis, BOLD signal of PGB treatment group was higher BOLD signal at several regions including anterior cingulate and insula than MLN treatment group at post-treatment stage. Also, paired t-test values of the BOLD signal in MLN group decreased in several regions including insula and thalamus as known as 'pain network'. In contrast, size and number of regions in which the BOLD signal decreased in PGB treatment group were smaller than those of MLN treatment group. Conclusion: This study showed that MLN group and PGB group have different medication effects. It is not surprising that MLN and PGB have not the same therapeutic effects since these two drugs have different medicinal mechanisms such as antidepressants and anti-seizure medication, respectively, and different detailed target of fibromyalgia syndrome treatment. Therefore, it is difficult to say which medicine will work better in this study.