• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3205-3211
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• 2013

Background: Bladder cancer is the second most incident malignancy among Lebanese men. The purpose of this study was to investigate potential risk factors associated with this observed high incidence. Methods: A case-control study (54 cases and 105 hospital-based controls) was conducted in two major hospitals in Beirut. Cases were randomly selected from patients diagnosed in the period of 2002-2008. Controls were conveniently selected from the same settings. Data were collected using interview questionnaire and blood analysis. Exposure data were collected using a structured face-to-face interview questionnaire. Blood samples were collected to determine N-acetyltransferase1 (NAT1) genotype by PCR-RFLP. Analyses revolved around univariate, bivariate and multivariate logistic regression, along with checks for effect modification. Results: The odds of having bladder cancer among smokers was 1.02 times significantly higher in cases vs. controls. The odds of exposure to occupational diesel or fuel combustion fumes were 4.1 times significantly higher in cases vs controls. The odds of prostate-related morbidity were 5.6 times significantly higher in cases vs controls. Cases and controls showed different clustering patterns of NAT1 alleles. No significant differences between cases and controls were found for consumption of alcohol, coffee, tea, or artificial sweeteners. Conclusions: This is the first case-control study investigating bladder cancer risk factors in the Lebanese context. Results confirmed established risk factors in the literature, particularly smoking and occupational exposure to diesel. The herein observed associations should be used to develop appropriate prevention policies and intervention strategies, in order to control this alarming disease in Lebanon.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.63-71
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• 2014

This paper proposes an algorithm that forms the clusters on the basis of hop distance in order to improve the actor coverage and connectivity in the sink-based wireless sensor and actor networks. The proposed algorithm forms the clusters that are distributed evenly in the target area by electing the CHs(Cluster Heads) at regular hop intervals from a sink. The CHs are elected sequentially from the sink in order to ensure the connectivity between the sink and the actors that are located on the CHs. Additionally, the electing are achieved from the area of the higher rate of the sensors density in order to improve the actor coverage. The number of clusters that are created in the target area and the number of the actors that are placed on the positions of the CHs are reduced by forming the clusters with regular distribution and minimizing the overlap of them through the proposed algorithm. Simulations are performed to verify that the proposed algorithm constructs the actor network that is connected to the sink. Moreover, we shows that the proposed algorithm improves the actor coverage and, therefore, reduces the amount of the actors that will be deployed in the region by 9~20% compared to the IDSC algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.113-119
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• 2008

Conventional 1-1-1 cooperative protocol offers path-loss gain as advantage of multi-hop and spatial diversity which is equivalent to MIMO system. This protocol is enable to get higher reliability and reduction of power consumption than those of the single-hop or multi-hop. But the 1-1-1 cooperative protocol get only the diversity order 2 and limited path-loss reduction gain because this protocol has a single cooperative relay. We propose 1-2-1 cooperative protocol using two cooperative relays R1, R2. The 1-2-1 cooperative protocol can improve path-loss reduction and increase diversity order 3. Moreover, the cooperative relay R2 attains diversity order 2. The signaling method in transmission uses DF (Decode and Forward) or DR (Decode and Reencode) and 1-2-1 DF/DR cooperative protocol are applied to clustering based wireless sensor networks (WSNs). Simulations are performed to evaluate the performance of the protocols under Rayleigh fading channel plus AWGN (Additive White Gaussian Noise).

• Molecules and Cells
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• v.38 no.1
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• pp.14-19
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• 2015

Eph receptors and their ligands, ephrins, represent the largest group of the receptor tyrosine kinase (RTK) family, and they mediate numerous developmental processes in a variety of organisms. Ephrins are membrane-bound proteins that are mainly divided into two classes: A class ephrins, which are linked to the membrane by a glycosylphosphatidylinositol (GPI) linkage, and B class ephrins, which are transmembrane ligands. Based on their domain structures and affinities for ligand binding, the Eph receptors are also divided into two groups. Trans-dimerization of Eph receptors with their membrane-tethered ligands regulates cell-cell interactions and initiates bidirectional signaling pathways. These pathways are intimately involved in regulating cytoskeleton dynamics, cell migration, and alterations in cellular dynamics and shapes. The EphBs and ephrinBs are specifically localized and modified to promote higher-order clustering and initiate of bidirectional signaling. In this review, we present an in-depth overview of the structure, mechanisms, cell signaling, and functions of EphB/ephrinB in cell adhesion and migration.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.52.2-52.2
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• 2019

In the last decades, the use of type Ia supernovae (SN) as standard candles has allowed us to understand the geometry of the Universe as they help to measure the expansion rate of the Universe, especially in combination with other cosmological probes such as the study of cosmic microwave background radiation anisotropies or the study of the imprint of baryonic acoustic oscillations on the galaxy clustering. Cosmological parameter constraints obtained with type Ia SN are mainly affected by intrinsic systematic errors. But there are other systematic effects related with the correlation of the observed brightness of Supernova and the large-scale structure of the Universe such as the effect of peculiar velocities and gravitational lensing. The former is relevant for SN at low redshifts while the latter starts being relevant for SN at higher redshifts. Gravitational lensing depends on how much matter is along the trajectory of each SN light beam. In order to account for this effect, we consider a statistical approach by defining the probability distribution (PDF) that a given supernova brightness is magnified by a given amount, for a particular redshift. We will show that different theoretical approaches to define the matter density along the light trajectory hugely affect the shape and width of the PDF. This may have catastrophic effects on cosmology fits using Supernova lensing as planned for surveys such as the Dark Energy Survey or future surveys such the Large Synoptic Survey Telescope.

• Journal of Information Science Theory and Practice
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• v.11 no.1
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• pp.14-30
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• 2023

The purpose of this study is to compare research trends in the information and communication technology (ICT) field between North and South Korea and analyze the differences by using data mining. Frequency analysis, clustering, and network analysis were performed using keywords from seven South Korean and two North Korean ICT academic journals published for five years (2015-2019). In the case of South Korea (S. Korea), the frequency of research on image processing and wireless communication was high at 16.7% and 16.3%, respectively. North Korea (N. Korea) had a high frequency of research, in the order of 18.2% for image processing, 16.9% for computer/Internet applications/security, and 16.4% for industrial technology. N. Korea's natural language processing (NLP) sector was 11.9%, far higher than S. Korea's 0.7 percent. Student education is a unique subject that is not clustered in S. Korea. In order to promote exchanges between the two Koreas in the ICT field, the following specific policies are proposed. Joint research will be easily possible in the image processing sector, with the highest research rate in both Koreas. Technical cooperation of medical images is required. If S. Korea's high-quality image source is provided free of charge to N. Korea, research materials can be enriched. In the field of NLP, it calls for proposing exchanges such as holding a Korean language information conference, developing a Korean computer operating system. The field of student education encourages support for remote education contents and management know-how, as well as joint research on student remote evaluation.

• The Korea Journal of Herbology
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• v.28 no.6
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• pp.9-14
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• 2013

Objectives : Cnidii Fructus is prescribed as the fruit of Cnidium monnieri (L.) Cusson or Torilis japonica (Houtt.) DC. in Korea pharmacopoeia. Although there are differences in the composition of useful components, two species have been used without distinction. In order to discriminate them, DNA sequencing and taste pattern analysis were used in this study. Methods : Primers ITS 1 and ITS 4 were used to amplify the intergenic transcribed spacer(ITS) region of nuclear ribosomal DNA from seven T. japonica and six C. monnieri samples. Taste pattern of samples were measured by using taste-sensing system SA402B equipped with five foodstuff sensors(CT0, C00, AAE, CA0, and AE1). The five initial taste(sourness, bitterness, astringency, umami, and saltiness) and three aftertaste(aftertaste of bitterness, astringency, and umami) of two species were compared. Results : According to the results of ITS region sequence analysis, two species showed 94 base pairs differences. The similarity of two sequences was 85%. From the taste pattern analysis, sourness, bitterness, aftertaste of bitterness(aftertaste-B), and umami showed a different pattern. Especially, bitterness and aftertaste-B of C. monnieri were significantly higher than T. japonica. In addition, two species were shown to have two markedly different clustering by these two flavors. Conclusion : T. japonica and C. monnieri were effectively discriminated using DNA sequencing and taste pattern analysis. These methods can be used to identify the origin of traditional medicine in order to maintain therapeutic efficacy.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1661-1670
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• 2016

In this paper, we present a risk prediction system and customized evacuation pathfinding algorithm in fire scenarios. For the risk prediction, we apply a multi-level clustering mechanism using collected temperature at sensor nodes throughout the network in order to predict the temperature at the time that users actually evacuate. Based on the predicted temperature and its reliability, we suggest an evacuation pathfinding algorithm that finds a suitable evacuation path from a user's current location to the safest exit. Simulation results based on FDS(Fire Dynamics Simulator) of NIST for a wireless sensor network consisting of 47 stationary nodes for 1436.41 seconds show that our proposed prediction system achieves a higher accuracy by a factor of 1.48. Particularly for nodes in the most reliable group, it improves the accuracy by a factor of up to 4.21. Also, the customized evacuation pathfinding based on our prediction algorithm performs closely with that of the ground-truth temperature in terms of the ratio of safe nodes on the selected path, while outperforming the shortest-path evacuation with a factor of up to 12% in terms of a safety measure.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.577-586
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• 2001

This study proposes a theoretical methodology for deriving a rainfall intensity-duration- frequency (I-D-F) curve using a simple rectangular pulses Poisson process model. As the I-D-F curve derived by considering the model structure is dependent on the rainfall model parameters estimated using the observed first and second order statistics, it becomes less sensitive to the unusual rainfall events than that derided using the annual maxima rainfall series. This study has been applied to the rainfall data at Seoul and Inchon stations to check its applicability by comparing the two I-D-F carves from the model and the data. The results obtained are as followed. (1) As the duration becomes longer, the overlap probability increases significantly. However, its contribution to the rainfall intensity decreases a little. (2) When considering the overlap of each rainfall event, especially for large duration and return period, we could see obvious increases of rainfall intensity. This result is normal as the rainfall intensity is calculated by considering both the overlap probability and return period. Also, the overlap effect for Seoul station is fecund much higher than that for Inchon station, which is mainly due to the different overlap probabilities calculated using different rainfall model parameter sets. (3) As the rectangular pulses Poisson processes model used in this study cannot consider the clustering characteristics of rainfall, the derived I-D-F curves show less rainfall intensities than those from the annual maxima series. However, overall pattern of both I-D-F curves are found very similar, and the difference is believed to be overcome by use of a rainfall model with the clustering consideration.