• 유통과학연구
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• 제12권3호
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• pp.99-103
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• 2014

Purpose - The objective of this study was to examine the volatility of the exchange rate of the Somali shilling (SoSh) during 2010, especially the exchange rate between the Somali shilling and US dollar. Research design, data, and methodology - The study employed aquantitative research design; the data was analyzed using contents analysis for the data pertaining to the exchange rate between the US dollar and Somali Shilling in 2010. Results - The main findings were that the exchange rate was very volatile during 2010 because of three sources: (1) Imbalance of demand and supply in the money market, (2) People adopting the US dollar as the medium of exchange forgoods and services, thereby reducing the circulation of the SoSh, and (3) Lack of a strong central bank. Conclusions - The study suggested three possible remedies: the establishment of an effective central bank that matches the demand and supply of the currencies, adoption of the Somali shilling as the official currency base for the prices of commodities, and minimizing the imports into the country and maximizing its exports, to support the strengthening of the Somali shilling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1272-1290
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• 2013

Privacy-preserving collaborative filtering schemes are becoming increasingly popular because they handle the information overload problem without jeopardizing privacy. However, they may be susceptible to shilling or profile injection attacks, similar to traditional recommender systems without privacy measures. Although researchers have proposed various privacy-preserving recommendation frameworks, it has not been shown that such schemes are resistant to profile injection attacks. In this study, we investigate two memory-based privacy-preserving collaborative filtering algorithms and analyze their robustness against several shilling attack strategies. We first design and apply formerly proposed shilling attack techniques to privately collected databases. We analyze their effectiveness in manipulating predicted recommendations by experimenting on real data-based benchmark data sets. We show that it is still possible to manipulate the predictions significantly on databases consisting of masked preferences even though a few of the attack strategies are not effective in a privacy-preserving environment.

• 인터넷정보학회논문지
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• 제10권6호
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• pp.81-98
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• 2009

협업적 여과는 추천 시스템을 구축하는데 가장 널리 보급된 정보 여과 기법으로 사용자 각 개인의 관심에 적합한 정보 및 아이템을 추천함으로써 사용자들의 의사 결정에 도움을 준다. 그러나 협업적 여과 기법은 우수한 추천 성능에도 불구하고, 최근에는 실링 공격이라 일컫는 악의적인 목적을 가진 사용자들의 추천 결과 조작에 쉽게 노출될 수 있는 문제가 새로운 이슈로 대두되고 있다. 본 논문에서는 협업적 여과의 실링 공격 문제들을 보완하기 위해, 추천 시스템에서 발생할 수 있는 실링 공격의 유형을 분석하고 악의적인 사용자의 조작된 선호도가 시스템에 미치는 영향을 최소화하기 위한 강건한 신뢰 모델 구축 방법을 제시한다. 그리고 그 모델을 적용하여 신뢰할 수 있는 아이템 추천 및 선호도 예측 방법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1341-1368
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• 2024

The concept of privacy-preserving collaborative filtering (PPCF) has been gaining significant attention. Due to the fact that model-based recommendation methods with privacy are more efficient online, privacy-preserving memory-based scheme should be avoided in favor of model-based recommendation methods with privacy. Several studies in the current literature have examined ant colony clustering algorithms that are based on non-privacy collaborative filtering schemes. Nevertheless, the literature does not contain any studies that consider privacy in the context of ant colony clustering-based CF schema. This study employed the ant colony clustering model-based PPCF scheme. Attacks like shilling or profile injection could potentially be successful against privacy-preserving model-based collaborative filtering techniques. Afterwards, the scheme's robustness was assessed by conducting a shilling attack using six different attack models. We utilize masked data-based profile injection attacks against a privacy-preserving ant colony clustering-based prediction algorithm. Subsequently, we conduct extensive experiments utilizing authentic data to assess its robustness against profile injection attacks. In addition, we evaluate the resilience of the ant colony clustering model-based PPCF against shilling attacks by comparing it to established PPCF memory and model-based prediction techniques. The empirical findings indicate that push attack models exerted a substantial influence on the predictions, whereas nuke attack models demonstrated limited efficacy.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.443-446
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• 2003

The vibration mode shape changed by the phase angle that can be controlled by phase-shifting ESPI system is discussed. For the phase-shifting ESPI experiment the stroboscopic illumination by using AOM(Acousto-Optic Modulator) is needed, and the initial phase angle can be adjusted by the program. The vibration mode shape is changed when the initial phase angle is changed. We examined the vibration mode shape change due to the initial phase angle change at each resonance frequency. Through this study, we found that in the vibration testing using phase-shilling ESPI the vibration mode shape is improved in the quality by adjusting exact phase angle and the error of the quantitative vibration analysis can be reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• 한국자동차공학회논문집
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• 제10권2호
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• pp.234-242
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• 2002

In this research, a transmission control unit was developed for a wheel loader on the basis of 16-bit microcontroller system. The TCU has the basic functions which include shifting control algorithm, actuation of six proportional solenoid valves, signal conditioning for four speed sensors, remote data monitoring capability with RF-module and duty cycle identification system which could identify the duty cycles from PWM signals. In order to design the control system, the overall transmission structure of the wheel loader was investigated and its characteristics of shifting were analyzed in advance. For the purpose of identifying the existing control algorithm and acquire some information about the shifting performance, the shifting experiments were performed for various shifting conditions with the conventional TCU. From the previous work on the conventional TCU, the shifting scheme was designed with the open-loop control which is based on the experimental data only to verify the feasibility of the developing TCU's shilling capability. The experimental results show comparable shifting characteristics to that of conventional TCU though the tests were performed at restricted shilling conditions. Hence, we could have the confidence for the development of the wheel loader automatic transmission TCU and its shifting quality could be improved with the adoption of appropriate feedback control scheme.

• 지능정보연구
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• 제13권3호
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• pp.119-140
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• 2007

추천 시스템은 정보의 홍수 속에서 사용자로 하여금 자신에게 더욱 가치 있고 흥미로운 정보를 선별할 수 있도록 돕는 자동화된 정보 여과 시스템이다. 최근 분산 컴퓨팅 환경에 대한 연구가 활발히 진행되면서, 지금까지의 중앙 서버에서 모든 정보를 관리하는 중앙 집중 방식의 추천 시스템에서 P2P 환경의 접근 방식으로 선회하고 있다. 협력적 여과는 상업적인 추천 시스템에서 가장 많이 사용하는 정보 여과 기법이지만, 그 성공에도 불구하고 확장성(scalability)과 데이터의 희박성(sparsity), 악의적인 사용자의 공격(shilling attack)에 대한 방어 등에 관련된 여러 제약을 갖는다. 중앙 집중 방식에서 분산된 방식으로의 변화는 추천의 신뢰성과 개인 정보의 남용 가능성에 관련한 문제점을 일부 해결할 수 있으나, 조작된 사용자 프로파일을 사용하여 추천을 조작하려는 의도를 갖는 악의적인 사용자의 공격에는 중앙 집중 방식과 마찬가지로 취약할 수 있다. 본 논문에서는 개인 정보의 오남용과 악의적인 사용자의 공격에 관련된 문제점을 해결하고, 분산된 환경에서 효과적인 협력적 여과를 수행하여 추천의 성능과 정확성을 높이기 위한 멀티 에이전트 기반의 추천 프레임워크를 제안한다. 추천의 신뢰성을 높이기 위해 사용자간의 신뢰 정보를 사용하며, 각 사용자의 개인 에이전트와 이동 에이전트간의 정보교환을 통해 효과적으로 신뢰 정보를 전파하고 분산된 유사도 계산의 효율성을 높였다.

• 전기의세계
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• 제46권8호
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• pp.31-33
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• 1997

현대 사회는 전기 에너지 없이는 하루도 유지될 수 없는 사회이다. 최근의 대도시 인구집중현상으로 전력수요의 밀도가 급격히 높아짐에 따라 전력전송의 중요성이 날로 증대되고 있으며, 이를 위한 전력 케이블은 전기 에너지를 전달하는 현대 문명 사회의 동맥으로 인정되고 있다. 전력 케이블은 1812년 러시아에서 shilling이 고무 절연선을 최초로 사용한 이후 절연 재료 및 생산 기술의 발전에 힘입어 현재에는 신뢰성 높은 제품이 송전 및 배전 선로에 사용되고 있다. 이러한 전력 케이블은 지절연 케이블과 고체절연 케이블로 대별되며, 케이블 상호간의 접속 및 가공선 또는 전기 기기와의 접속을 위해 접속함과 함께 실선로에 포설된다. 본 고에서는 전력 케이블과 그 접속함에 대한 기술 동향에 대하여 서술하고자 한다.

• 제어로봇시스템학회논문지
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• 제9권1호
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• pp.37-43
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• 2003

A faster autofocusing method is proposed. The searching speed of microscope camera is limited by the long focusing time due to too much sampled digital image data. The improvement of autofocusing speed based on the down sampling is discussed analytically and is proved by experiments. The anticipated aliasing is found negligible in shilling rate of focus measure.