• Asia pacific journal of information systems
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• 제20권1호
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• pp.81-99
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• 2010

Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.

• 한국환경성돌연변이발암원학회:학술대회논문집
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• 한국환경성돌연변이발암원학회 2003년도 추계학술대회
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• pp.34-63
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• 2003

Occupational and environmental exposure to manganese continue to represent a realistic public health problem in both developed and developing countries. Increased utility of MMT as a replacement for lead in gasoline creates a new source of environmental exposure to manganese. It is, therefore, imperative that further attention be directed at molecular neurotoxicology of manganese. A Need for a more complete understanding of manganese functions both in health and disease, and for a better defined role of manganese in iron metabolism is well substantiated. The in-depth studies in this area should provide novel information on the potential public health risk associated with manganese exposure. It will also explore novel mechanism(s) of manganese-induced neurotoxicity from the angle of Mn-Fe interaction at both systemic and cellular levels. More importantly, the result of these studies will offer clues to the etiology of IPD and its associated abnormal iron and energy metabolism. To achieve these goals, however, a number of outstanding questions remain to be resolved. First, one must understand what species of manganese in the biological matrices plays critical role in the induction of neurotoxicity, Mn(II) or Mn(III)? In our own studies with aconitase, Cpx-I, and Cpx-II, manganese was added to the buffers as the divalent salt, i.e., $MnCl_2$. While it is quite reasonable to suggest that the effect on aconitase and/or Cpx-I activites was associated with the divalent species of manganese, the experimental design does not preclude the possibility that a manganese species of higher oxidation state, such as Mn(III), is required for the induction of these effects. The ionic radius of Mn(III) is 65 ppm, which is similar to the ionic size to Fe(III) (65 ppm at the high spin state) in aconitase (Nieboer and Fletcher, 1996; Sneed et al., 1953). Thus it is plausible that the higher oxidation state of manganese optimally fits into the geometric space of aconitase, serving as the active species in this enzymatic reaction. In the current literature, most of the studies on manganese toxicity have used Mn(II) as $MnCl_2$ rather than Mn(III). The obvious advantage of Mn(II) is its good water solubility, which allows effortless preparation in either in vivo or in vitro investigation, whereas almost all of the Mn(III) salt products on the comparison between two valent manganese species nearly infeasible. Thus a more intimate collaboration with physiochemists to develop a better way to study Mn(III) species in biological matrices is pressingly needed. Second, In spite of the special affinity of manganese for mitochondria and its similar chemical properties to iron, there is a sound reason to postulate that manganese may act as an iron surrogate in certain iron-requiring enzymes. It is, therefore, imperative to design the physiochemical studies to determine whether manganese can indeed exchange with iron in proteins, and to understand how manganese interacts with tertiary structure of proteins. The studies on binding properties (such as affinity constant, dissociation parameter, etc.) of manganese and iron to key enzymes associated with iron and energy regulation would add additional information to our knowledge of Mn-Fe neurotoxicity. Third, manganese exposure, either in vivo or in vitro, promotes cellular overload of iron. It is still unclear, however, how exactly manganese interacts with cellular iron regulatory processes and what is the mechanism underlying this cellular iron overload. As discussed above, the binding of IRP-I to TfR mRNA leads to the expression of TfR, thereby increasing cellular iron uptake. The sequence encoding TfR mRNA, in particular IRE fragments, has been well-documented in literature. It is therefore possible to use molecular technique to elaborate whether manganese cytotoxicity influences the mRNA expression of iron regulatory proteins and how manganese exposure alters the binding activity of IPRs to TfR mRNA. Finally, the current manganese investigation has largely focused on the issues ranging from disposition/toxicity study to the characterization of clinical symptoms. Much less has been done regarding the risk assessment of environmenta/occupational exposure. One of the unsolved, pressing puzzles is the lack of reliable biomarker(s) for manganese-induced neurologic lesions in long-term, low-level exposure situation. Lack of such a diagnostic means renders it impossible to assess the human health risk and long-term social impact associated with potentially elevated manganese in environment. The biochemical interaction between manganese and iron, particularly the ensuing subtle changes of certain relevant proteins, provides the opportunity to identify and develop such a specific biomarker for manganese-induced neuronal damage. By learning the molecular mechanism of cytotoxicity, one will be able to find a better way for prediction and treatment of manganese-initiated neurodegenerative diseases.

• 대한방사선치료학회지
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• 제31권1호
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• pp.43-49
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• 2019

목 적: 움직이는 장기에 취약한 Pencil Beam Scanning(PBS)을 보완하기 위해 고안된 Layered Rescanning PBS 기법을 Moving Phantom에 적용하여 Single Scan PBS와 선량비교를 통해 Homogeneity를 비교해 본다. 대상 및 방법: Matrix X(IBA, Belgium)와 Moving Phantom(standard imaging, USA)을 이용하였다. 가상의 tumor $10{\times}10{\times}5cm$에 AP 방향에서 200 cGy의 선량을 조사하였다. 치료계획은 single scan PBS, rescan 4, 8, 12회 총 4가지로 하였고 각 치료계획별로 3번씩 반복 측정하였다. 측정 시 Moving Phantom의 호흡주기는 한 cycle당 4초로 설정 후 S-I 방향 움직임 2 cm으로 설정하였다. 추가로 beam on time을 측정하였다. 결 과: PTV 내에서 $D_{max}$의 평균값은 single scan, 4, 8, 12회 rescan 순서로 각각 $246.47{\pm}18.8cGy$, $223.43{\pm}8.92cGy$, $222.47{\pm}7.7cGy$, $213.9{\pm}6.11cGy$ $D_{min}$의 평균값은 각각 $165.53{\pm}4.32cGy$, $173.13{\pm}11.94cGy$, $184.13{\pm}8.04cGy$, $182.67{\pm}4.38cGy$으로 $D_{mean}$ $192.77{\pm}6.98cGy$, $196.7{\pm}4.01cGy$, $198.17{\pm}4.96cGy$, $195.77{\pm}3.15cGy$으로 측정되었다. 그리고 rescan 횟수가 늘어날수록 Homogeneity Index가 1에 가까워졌으며, beam on time은 평균 2분 15초, 3분 15초, 4분 30초, 5분 37초로 rescan 횟수가 증가할수록 치료시간이 증가되었다. 측정하는 과정에서 MU가 낮은 선량 layer에서는 설정한 rescan 횟수만큼 실제로 rescan하지 못하는 문제점이 발견되었다. 결 론: 장기 움직임이 있는 종양 치료 시 Layered Rescanning PBS을 적용했을 때 single scan PBS보다 균일한 선량분포를 확인할 수 있었다. 그리고 rescan 횟수가 증가할수록 균일한 선량분포를 보였다. single scan PBS와 12회 Layered rescanning 비교 시 HI 수치가 0.32 향상되었다. 추후 연구를 통하여 호흡동조 방사선치료가 불가능환자에게 적용이 가능할 것으로 사료된다.

• 공업화학
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• 제32권3호
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• pp.268-276
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• 2021

최근 무선통신 기기가 보편화됨에 따라 이로부터 발생하는 전자기파를 제어할 수 있는 방법에 대한 관심이 높아지고 있다. 전자기파 제어 물질로 가장 흔히 사용되는 것은 자성 물질이지만 제품에 적용 시 제품이 무겁고 두꺼워지는 특징 때문에 일반 전자기기에 사용하기에는 문제가 있어 이를 해결하기 위해 가볍고 두께가 얇은 고분자 유연메타 전자소자가 제시되었다. 또한 고분자 유연메타 전자소자는 단일 제품을 다양한 곡률에 적용할 수 있어 곡면 형상이 많은 전자기기에 사용하기에도 적합하다. 그러나 이러한 고분자 유연메타 전자소자를 곡면에 적용하기 위해서는 곡률변화에 따른 전자기파 제어 특성의 안정성 평가가 필수적으로 요구된다. 이에 본 연구에서는 도선 면적이 일정할 때 도선 길이에 따른 저항 변화율이 전자기파 제어 특성과 역의 관계라는 점을 활용하여 고분자 유연메타 전자소자의 전기적 특성 변화를 통해 전자기파 제어 특성을 예측할 수 있는 방법을 개발하였고, 이를 이용하여 고분자 유연메타 전자소자의 곡률 안정성 평가를 수행하였다. 그 결과 곡률 반경이 감소할수록 도선 길이에 따른 저항 변화율이 증가하였고, 곡률 유지 시간에 의한 변화는 없었다. 또한 곡면 적용 시 도선에 영구적인 변화와 곡면 제거 시 회복 가능한 변화가 복합적으로 발생하였고, 이러한 변화의 원인이 곡면 적용 시 가해진 인장응력에 의해 생성된 도선 내 수직방향 크랙이라는 사실도 밝혀냈다.

• 한국방재안전학회논문집
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• 제16권2호
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• pp.15-32
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• 2023

홍수 유량측정은 직접 하천에 접촉하는 방식의 경우 측정인력의 안전 문제와 다수의 인력이 필요한 점 등 어려운 점이 많다. 최근 이러한 문제점을 해결하기 위해 현장에서 측정이 간편하고, 수면에 접촉하지 않는 비접촉방식의 전자파표면유속계 활용이 증가하고 있으나 돌발적이고 급변하는 현장 여건의 적용에 있어 어려움이 있다. 따라서, 홍수 상황에서 표면유속을 이용한 유량산정방법은 이론적이고, 경제적인 접근이 필요하다. 본 연구에서는 전자파표면유속계 측정자료와 수위-유량관계곡선식 자료를 수집하여 표면유속을 이용한 지표유속법과 유속분포법을 적용 및 분석하였다. 전반적으로 동수반경 3 m 이상 또는 평균유속 2 ㎧ 이상에서는 모든 방법이 측정유량 및 환산유량과 유사한 결과로 분석되었다. 그리고 대상지점 중 수위-유량관계곡선식 고수위 범위에서 최대유속 발생 위치 구간의 최대 표면유속을 이용하여 지표유속법과 유속분포법으로 유량을 산정하였고, 환산유량과의 평균 상대오차가 모두 10% 이내로 비교적 일치하였다. 홍수시 한 개의 최대 표면유속 측정과 지표유속법 및 유속분포법을 이용한 유량산정방법은 고수위 외삽 개발에 적용할 경우 외삽추정 구간에 대한 신뢰도를 제고할 수 있을 것으로 판단되었다. 따라서, 본 연구결과를 토대로 한 표면유속을 이용한 유량산정방법은 신속하고 효율적인 홍수 유량측정 방안이 될 것으로 기대된다.