농업 이미지 처리를 위한 빅데이터 플랫폼 설계 및 구현

반퀴엣뉘엔 ( Van-quyet Nguyen ),신응억뉘엔 ( Sinh Ngoc Nguyen ),둑티엡부 ( Duc Tiep Vu ),김경백 ( Kyungbaek Kim ) 한국정보처리학회 2016 한국정보처리학회 학술대회논문집 Vol.23 No.2

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

The Role of Zn Doping on the Catalytic Activity of the Nanoparticle Perovskite La0.7Sr0.3MnO3

Tran Thi Minh Nguyet,Nguyen Quang Huan,Tran Que Chi,Do The Chan,Nguyen Doan Thai,Nguyen Cong Trang,Luu Tien Hung,Le Van Tiep,Nguyen Van Qui 한국물리학회 2008 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.52 No.5

The nanometer complex oxide La0:7Sr0.3Mn0.6Zn0.₄O₃ was prepared by using a Sol-Gel method with citric acid as a ligand. The in uence of Zn doping of La0.7Sr0.₃MnO₃ on the structure, the morphology, the surface properties and on the catalytic activity of material was studied by using X-ray diraction (XRD), transmission electron microscopy (TEM), a high-resolution images and selected area electron diraction (SAED), physical adsorption and temperature programmed surface reaction (TPSR) methods. The results showed that perovskite La0:7Sr0:3Mn0:6. Zn0.₄O₃ could well catalyse propene oxidation in the temperature range 190 { 280 ℃, which was reduced to 100 { 120 ℃ for catalyst La1-χSrχMnO₃ The nanometer complex oxide La0:7Sr0.3Mn0.6Zn0.₄O₃ was prepared by using a Sol-Gel method with citric acid as a ligand. The in uence of Zn doping of La0.7Sr0.₃MnO₃ on the structure, the morphology, the surface properties and on the catalytic activity of material was studied by using X-ray diraction (XRD), transmission electron microscopy (TEM), a high-resolution images and selected area electron diraction (SAED), physical adsorption and temperature programmed surface reaction (TPSR) methods. The results showed that perovskite La0:7Sr0:3Mn0:6. Zn0.₄O₃ could well catalyse propene oxidation in the temperature range 190 { 280 ℃, which was reduced to 100 { 120 ℃ for catalyst La1-χSrχMnO₃

Secrecy Capacity of the Primary System in a Cognitive Radio Network

Nguyen, Van-Dinh,Hoang, Tiep M.,Shin, Oh-Soon IEEE 2015 IEEE Transactions on Vehicular Technology VT Vol.64 No.8

<P>With fast growth of wireless services, secrecy has become an increasingly important issue for wireless networks. In this paper, we investigate the secrecy capacity of the primary system in a cognitive radio system based on artificial noise, which has been proposed for dealing with the eavesdropper. We first consider a special case of one eavesdropper and two regimes of the eavesdropping channel condition. Specifically, we analyze the impact of interference generated by a secondary system toward the primary system in a cognitive radio system. The channel state information (CSI) of the primary channel is assumed to be perfectly known at both the primary transmitter and receiver, whereas that of the eavesdropper is partially known. Under these assumptions, we derive analytical expressions for the ergodic secrecy capacity in the cases of strong eavesdropping channel and weak eavesdropping channel and analyze the impact of the secondary system on the primary ergodic secrecy capacity. Moreover, we extend the analysis to the general case of arbitrary eavesdropping channel condition and arbitrary number of eavesdroppers. Some numerical results will be also presented to verify the analysis.</P>

Design and Implementation of Geo-Social Information based Personalized Warning Notification System

Tiep Vu Duc,Quyet Nguyen-Van,Kyungbaek Kim 한국스마트미디어학회 2016 스마트미디어저널 Vol.5 No.2

In case of a emergency situation or a natural disaster, a warning notification system is an essential tool to notify at-risk people in advance and provide them useful information to survive the event. Although some systems have been proposed such as emergency alert system using android, SMS, or P2P overlay network, these works mainly focus on a reliable message distribution methods. In this paper, we proposed a novel design and implementation of a personalized warning notification system to help inform not only the at-risk people but also their family and friends about the coming disaster as well as escape plan and survival information. The system consists of three main modules: the user selection module, the knowledge based message generator, and message distribution modules. The user selection module collects the list of people involved in the event and sorts them based on their level of involvement (their location, working position and social relationships). The knowledge based message generator provides each person with a personalized message that is concise and contains only the necessary information for the particular person based on their working position and their involvement in the event. The message distribution module will then find a best path for sending the personalized messages based on trustiness of locations since network failures may exist in a disaster event. Additionally, the system also have a comprehensive database and an interactive web interface for both user and system administrator. For evaluation, the system was implemented and demonstrated successfully with a building on fire scenario.

Design and Implementation of Geo-Social Information based Personalized Warning Notification System

김경백,Duc, Tiep Vu,Nguyen-Van, Quyet,Kim, Kyungbaek 한국스마트미디어학회 2016 스마트미디어저널 Vol.5 No.2

In case of a emergency situation or a natural disaster, a warning notification system is an essential tool to notify at-risk people in advance and provide them useful information to survive the event. Although some systems have been proposed such as emergency alert system using android, SMS, or P2P overlay network, these works mainly focus on a reliable message distribution methods. In this paper, we proposed a novel design and implementation of a personalized warning notification system to help inform not only the at-risk people but also their family and friends about the coming disaster as well as escape plan and survival information. The system consists of three main modules: the user selection module, the knowledge based message generator, and message distribution modules. The user selection module collects the list of people involved in the event and sorts them based on their level of involvement (their location, working position and social relationships). The knowledge based message generator provides each person with a personalized message that is concise and contains only the necessary information for the particular person based on their working position and their involvement in the event. The message distribution module will then find a best path for sending the personalized messages based on trustiness of locations since network failures may exist in a disaster event. Additionally, the system also have a comprehensive database and an interactive web interface for both user and system administrator. For evaluation, the system was implemented and demonstrated successfully with a building on fire scenario.

Study on Fibrosis Change with Transient Elastography in Chronic Hepatitis B Virus Treatment with Tenofovir

( Ha Phuong Linh ),( Hoang Van Tiep ),( Dinh Cong Dang ),( Nguyen Khac Hung Manh ) 대한간학회 2020 춘·추계 학술대회 (KASL) Vol.2020 No.1

Background: Tenofovir disoproxil fumarate (TDF) is one of the first optimal choices to be used in the treatment of chronic hepatitis B. FibroScan is non-invasive methods to assess liver fibrosis. Aims: To evaluate the therapeutic effect of TDF on fibrosis via FibroScan after treatment. Methods: This study was conducted in 63 chronic hepatitis B patients who had the indication of antiviral therapy at 103 Cam Khe Clinic from March 2019 to March 2020. All patients with chronic hepatitis B treated with TDF during 6 months. Liver fibrosis stages was appreciated using transient hepatic elastography by Fibroscan before and after 6 months treatment. Results: The average age of patients was 46 years, with men accounted for 69% of the total. After treatment, normalization of ALT 71.26%, viral response of 90.23%, HBV DNA below the detection level was 66.3%. Liver fibrosis evaluated by FibroScan before and after 6 months treatment were 7.15 ± 1.56 kPa, and 3.58 ± 1.19 kPa eveluated by FibroScan. Conclusions: TDF was effective for patients after treatment on liver fibrosis assessed by FibroScan in chronic hepatitis B patients.

Study on Correlation between Serum Ferritin Levels and Liver Stiffness Assessed by Fibroscan in Patients with Chronic Hepatitis C

( Ha Phuong Linh ),( Hoang Van Tiep ),( Dinh Cong Dang ),( Nguyen Khac Hung Manh ) 대한간학회 2020 춘·추계 학술대회 (KASL) Vol.2020 No.1

Aims: Chronic hepatitis C is a major infectious disease which is mainly cause of morbidity worldwide in patients with liver disease, and liver transplantation. Raised ferritin levels play an important role of intervening the process which is associated with hepatic injury. Screening with non-invasive strategies can detect the disease at early stage and intervention could be initiated. To determine correlation between serum ferritin levels and liver stiffness values in patients of chronic hepatitis C. Methods: A cross-sectional study was conducted at 103 Cam Khe Clinic from May 2019 to April 2020. 93 patients with chronic hepatitis C fulfilling inclusion criteria were included in this study. Liver fibrosis stages was appreciated using transient hepatic elastography by Fibroscan, the activities of serum liver function biomarker enzymes and serum ferritin levels were determined by automated analyser. Results: The average age of patients was 48 years, with men accounted for 78% of the total. The mean serum ferritin value was 148.19 ng/ml, liver stiffness measurements range from 12.5 to 75.5 kPa, with a median value of 17.39 ± 15.98 kPa. Significantly elevated levels of serum ferritin (P<0.001), were detected in patients with severe fibrosis compared to mild fibrosis. Concentration of serum ferritin was increased with the evolution of fibrosis in all stages from F0 to F4 and this increase was significant (P<0.01) in cirrhotic patients (F4). There was a positive correlation between serum level of ferritin and progression of fibrosis (0.979391) (r = 0.976). Conclusions: There is significant correlation between serum ferritin and liver stiffness. Serum ferritin concentration may be used as liver fibrosis biomarkers.

Applying advanced machine learning techniques in the early prediction of graduate ability of university students

Nga Pham,Pham Van Tiep,Tran Thu Trang,Hoai-Nam Nguyen,최규석,Ha-Nam Nguyen 한국인터넷방송통신학회 2022 International Journal of Internet, Broadcasting an Vol.14 No.3

The number of people enrolling in universities is rising due to the simplicity of applying and the benefit of earning a bachelor's degree. However, the on-time graduation rate has declined since plenty of students fail to complete their courses and take longer to get their diplomas. Even though there are various reasons leading to the aforementioned problem, it is crucial to emphasize the cause originating from the management and care of learners. In fact, understanding students' difficult situations and offering timely Number of Test data and advice would help prevent college dropouts or graduate delays. In this study, we present a machine learningbased method for early detection at-risk students, using data obtained from graduates of the Faculty of Information Technology, Dainam University, Vietnam. We experiment with several fundamental machine learning methods before implementing the parameter optimization techniques. In comparison to the other strategies, Random Forest and Grid Search (RF&GS) and Random Forest and Random Search (RF&RS) provided more accurate predictions for identifying at-risk students.

Formation of Color Centers and Concentration of Defects in Boron Carbide Irradiated at Low Gamma Radiation Doses

Matlab Nabi Mirzayev,Ravan Nadir Mehdiyeva,Sevinj Zellabdin Melikova,Sakin Hamid Jabarov,Thabsile Theodora Thabethe,Saphina Biira,Mirze Abdulla Kurbanov,Nguyen Van Tiep 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.74 No.4

In the present work, boron-carbide (B4C) samples (purity of 99.5% and density of 1.80 g/cm3) were irradiated by using gamma radiation from a 60Co gamma source. Gamma irradiation of the samples was carried out at doses 48.5, 97, 145.5 and 194 kGy. The samples were analysed using a UV-V Gary 50 Scan spectrophotometer. The eect of dierent irradiation doses on the defects created in the B4C samples was investigated. In the B4C samples, the formation processes for color centers depended on the gamma irradiation dose. The calculated activation energies at room temperature essential for the formation of F and F+ color centers ranged from 1.89 - 2.05 eV.