• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.317-325
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• 2022

The simple regression model (SRM) is used in this study to look at potential economic growth-influencing factors. The sample's period runs from 2005 to 2019. The data was gathered from various ministries and government agencies such as the Central Bank of Afghanistan's Statistical Bulletin, the World Bank, the United Nations (UN), World Bank open data, NASA, Ministry of Finance (MoF), Ministry of Economy (MoE), and Central Bank of Afghanistan's Statistical Bulletin (CBA), as well as the internet and news. There is an urgent need to ensure that taxes are collected in the most efficient manner possible because one of the enormous management gaps in Afghanistan over the last two decades has been tax evasion. According to the results of this study, tax evasion has a negative and significant impact on Afghanistan's economic growth. We can affirm that the subject of this article is among the most significant topics recently discussed in my country. If the right solutions are implemented, It can significantly contribute to quickening the cycle of the developing Afghan economy and turning it from an unstable to a sustainable one.

• Journal of Industrial Technology
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• 제22권A호
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• pp.101-105
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• 2002

Counters for various kinds of bank notes require high-speed distinctive point extraction and recognition for notes. In this paper we propose a new point extraction and data extraction method from specific parts of a bank note representing the same color. The recognition algorithm uses a back-propagation neural network that has coordinate data input. The proposed algorithm is designed to minimize recognition time.

• Journal of Korea Society of Digital Industry and Information Management
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• 제15권3호
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• pp.197-206
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• 2019

Telemarketing has been used in finance due to the reduction of offline channels. In order to select telemarketing target customers, various machine learning techniques have emerged to maximize the effect of minimum cost. However, there are problems that the class imbalance, which the number of marketing success customers is smaller than the number of failed customers, and the recall rate is lower than accuracy. In this paper, we propose a method that solve the imbalanced class problem and increase the recall rate to improve the efficiency. The hybrid sampling method is applied to balance the data in the class, and the stacked deep network is applied to improve the recall and precision as well as the accuracy. The proposed method is applied to actual bank telemarketing data. As a result of the comparison experiment, the accuracy, the recall, and the precision is improved higher than that of the conventional methods.

• Asia Pacific Journal of Corpus Research
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• 제2권2호
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• pp.1-15
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• 2021

The study aims to explore the use of metadiscourse in the Bank Negara Malaysia Governor's speeches based on Hyland's Interpersonal Model of Metadiscourse. The corpus data consist of 343 speech texts, which were extracted from the Malaysian Corpus of Financial English (MacFE), amounting to 688,778 tokens. Adopting both quantitative and qualitative approaches to data analysis the study investigates (1) the overall use of metadiscourse in the Bank Negara Governor's speech texts and (2) the functions of the most prominent metadiscourse resources used and their functions in the speech texts. The findings reveal that the Governor's speech texts to be interactional rather than interactive, revealing a rich distribution of interactional metadiscourse resources, namely engagement markers, self-mention, hedges, boosters and attitude markers throughout the texts. The interactional metadiscourse resources function to establish speaker-audience engagement and alignment of views, as well as to express degree of uncertainty and certainty and attitudes. The study concludes that the speech texts are not merely informational or propositional, but rather interpersonal.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제10권7호
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• pp.1307-1311
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• 2006

In this paper, we propose new speech feature parameter using the Matrix Factorization for appearance part-based features of speech spectrum. The proposed parameter represents effective dimensional reduced data from multi-dimensional feature data through matrix factorization procedure under all of the matrix elements are the non-negative constraint. Reduced feature data presents p art-based features of input data. We verify about usefulness of NMF(Non-Negative Matrix Factorization) algorithm for speech feature extraction applying feature parameter that is got using NMF in Mel-scaled filter bank output. According to recognition experiment results, we confirm that proposed feature parameter is superior to MFCC(Mel-Frequency Cepstral Coefficient) in recognition performance that is used generally.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.740-743
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• 2006

We identify two distinct finer-scale frontal bands: 'Mainland China Coastal Front' (MCCF) and 'Kuroshio Front' (KF). The MCCF is along the 50-m isobath with large temperature gradient. The front is a boundary between the Mainland China Coastal Current and the offshore shelf waters. On the other hand, the KF is extending from the northeastern coast of Taiwan toward the northeast and into the shelf of south ECS. It forms a broad semicircle-shape and curving along 100-m isobath, it also deviates from eastward at around 26.5N-122E and leaves the shelf of ECS. This front should be the boundary between the Kuroshio water and the other shelf waters.

• ETRI Journal
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• 제32권1호
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• pp.84-92
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• 2010

This paper proposes the semaphore authority management (SAM) controller to optimize the dual-port SDRAM (DPSDRAM) in the mobile multimedia systems. Recently, the DPSDRAM with a shared bank enabling the exchange of data between two processors at high speed has been developed for mobile multimedia systems based on dual-processors. However, the latency of DPSDRAM caused by the semaphore for preventing the access contention at the shared bank slows down the data transfer rate and reduces the memory bandwidth. The methodology of SAM increases the data transfer rate by minimizing the semaphore latency. The SAM prevents the latency of reading the semaphore register of DPSDRAM, and reduces the latency of waiting for the authority of the shared bank to be changed. It also reduces the number of authority requests and the number of times authority changes. The experimental results using a 1 Gb DPSDRAM (OneDRAM) with the SAM controllers at 66 MHz show 1.6 times improvement of the data transfer rate between two processors compared with the traditional controller. In addition, the SAM shows bandwidth enhancement of up to 38% for port A and 31% for port B compared with the traditional controller.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• 제57권
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• pp.199-219
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• 2013

The objective of this study is to find out whether Korean main banks may have efficiency against Indian major banks. For this purpose, DEA analysis is used for checking relative efficiency levels. The study proposes, as a result, Shinhan bank, Woori bank and Kookmin bank in Korea may consider entering into Indian banking industry because these three banks have relative efficiency against main Indian banks like Yes bank, ICICI bank. The results of the study comply with actual facts since Shinhan bank already came to Indian banking market at first. Shinhan bank have three branches like Mumbai, NewDelhi etc. Wooribank also entered into India in 2012 as second case among Korean banks. But Kookmin bank did not come to India yet so they should consider coming to India. As a preliminary measures, they can send one person as a expatriate to survey the Indian banking industry like KDB in Korea. If they can utilize their core competence in real estate field at India, they may positively think about entering into India as quickly as possible. Although many Korean firms have penetrated into Indian market recently, they almost belong to manufacturing sectors so Korean service firms like banks should consider more coming to India because the most hot sector for FDI in India remain service sector and many foreign service firms already rush to Indian market. If Korean service firms like banks delay FDI further, good market opportunities would not be there any more. DEA analysis can be one of tools to check investment feasibilities. Since India becomes a compulsory subject for most of Korean firms, to increase possibilities of success in India, such Korean banks may consider applying fast-mover investment strategies to the Indian business fields.

• Journal of Ginseng Research
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• 제34권1호
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• pp.41-46
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• 2010

Expensive herbs such as ginseng are always a possible target for fraudulent labeling. New mountain ginseng strains have occasionally been found deep within mountain areas and commercially traded at exorbitant prices. However, until now, no scientific basis has existed to distinguish such ginseng from commonly cultivated ginseng species other than by virtue of being found within deep mountain areas. Polymerase chain reaction (PCR) analysis of the internal transcribed spacer has been shown to be an appropriate method for the identification of the most popular species (Panax ginseng) in the Panax ginseng genus. A single nucleotide polymorphism (SNP) has been identified between three newly found mountain ginseng (KGD4, KGD5, and KW1) and already established Panax species. Specific PCR primers were designed from this SNP site within the sequence data and used to detect the mountain ginseng strains via multiplex PCR. The established multiplex-PCR method for the simultaneous detection of newly found mountain ginseng strains, Korean ginseng, and foreign ginseng in a single reaction was determined to be effective. This study is the first report of scientific discrimination of "mountain ginsengs" and describes an effective method of identification for fraud prevention and for uncovering the possible presence of other, cheaper ginseng species on the market.

• Asia-Pacific Journal of Business
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• 제11권3호
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• pp.199-215
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• 2020

Purpose - This article tries to test if the conditional consumption capital asset pricing model (CCAPM) with bank credit for household as a conditional variable can explain the cross-sectional variation of stock returns in Korea. The performance of conditional CCAPM is compared to that of multifactor asset pricing models based on Arbitrage Pricing Theory. Design/methodology/approach - This paper extends the simple CCAPM to the conditional version of CCAPM by using bank credit for household as conditioning information. By employing KOSPI and KOSDAQ stocks as test assets from the second quarter of 2003 to the first quarter of 2018, this paper estimates risk premiums of conditional CCAPM and a variety of multifactor linear models such as Fama-French three and five-factor models. The significance of risk factors and the adjusted coefficient of determination are the basis for the comparison in models' performances. Findings - First, the paper finds that conditional CCAPM with bank credit performs as well as the multifactor linear models from Arbitrage Pricing theory on 25 test assets sorted by size and book-to-market. When using long-term consumption growth, the conditional CCAPM explains the cross-sectional variation of stock returns far better than multifactor models. Not only that, although the performances of multifactor models decrease on 75 test assets, conditional CCAPM's performance is well maintained. Research implications or Originality - This paper proposes bank credit for household as a conditional variable for CCAPM. This enables CCAPM, one of the most famous economic asset pricing models, to conform with the empirical data. In light of this, we can now explain the cross-sectional variation of stock returns from an economic perspective: Asset's riskiness is determined by its correlation with consumption growth conditional on bank credit for household.