http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Design and Performance Analysis of Microstrip Patch Array Antennas with different configurations
A. De,C. K. Chosh,A. K Bhattacherjee 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.3
This abstract demonstrates simple, low cost and high gain microstrip array antennas with suitable feeding technique and suitable dielectric substrate for applications in the GHz frequency range. The objective of this paper is to design, and fabricate a 16 element rectangular microstrip patch array antenna. Therefore, a novel particle swarm optimization method based on IE3D was used to design an inset feed linearly polarized rectangular microstrip patch antenna array with sixteen elements. .Initially we set our antenna as a single patch and after evaluating the outcomes of antenna features; operation frequency, radiation patterns, reflected loss, efficiency and antenna gain, we transformed it to a 2x1 array. Finally, we analyzed the 2×2 array, then 4×2 array and finally 4 × 4 array to increase directivity, gain, efficiency and have better radiation patterns. The simulation has been performed by Zeland software version 14.0 and the desired antenna provides a return loss of -42.154dB at 2.45 GHz by using RT Duroid dielectric substrate with Єr= 2.45 and height , h= 1.58mm. The gain of the antenna is found to be 19.455 dBi and the side lobe is maintained lower than the main lobe. Since the resonant frequency of these antenna is around 2- 4 GHz, so these are suitable for S – band applications and can be used in WLAN communication systems.
Impact of zinc oxide nanoparticles on the bacterial community of Hydra magnipapillata
Ade Yamindago,Nayun Lee,Seonock Woo,Seungshic Yum 대한독성 유전단백체 학회 2020 Molecular & cellular toxicology Vol.16 No.1
Backgrounds Zinc oxide nanoparticles (ZnO NPs) are extensively used for various products. In this study, the effects of ZnO NPs exposure in diversity and community composition of the bacteria associated with H. magnipapillata were investigated. This study provides insight into possible impacts of ZnO NPs on aquatic organisms. Methods 454-pyrosequencing analysis of the bacterial 16S rRNA gene was applied to H. magnipapillata after exposure to 10 mg/L ZnO NPs (Ø 20 nm). Results Acute exposure to ZnO NPs changed the diversity and compositions of the associated bacteria. The composition of Curvibacter decreased, but Flectobacillus and Delftia increased; these two genera are known to have beneficial functions. Conclusion The changes in diversity and composition of the associated bacteria may indicate the possible mechanisms by which the associated bacteria maintain their mutual interactions and support the health of their host after exposure to ZnO NPs.
Toward Deep Learning-based Low Latency Communication in Industrial IoT
Ade Pitra Hermawan,Rizki Rivai Ginanjar,Dong-Seong Kim,Jae-Min Lee 한국통신학회 2019 한국통신학회 학술대회논문집 Vol.2019 No.6
This paper proposes a new direction in order to achieve high throughput and low latency communication in Industrial Internet of Things (IIoT) by utilizing Deep Learning(DL) technique. In order to achieve the goals, congestion in the network shall be avoided. We compare the performance of some DL algorithms in solving network congestion issue. In addition, future research trends regarding to maximize the system performance and to achieve high throughput and low latency communication in IIoT are suggested.
Real-time Data Recovery using Multi-directional LSTM in Wireless Sensor Networks
Ade Pitra Hermawan,Mareska Pratiwi Maharani,Dong-Seong Kim(김동성),Jae-Min Lee(이재민) 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.2
In this paper, an algorithm to recover missing data from the sensor in real-time is proposed. Since missing sensor data is a crucial issue in Industrial Internet of Things (IIoT), we employ two different long short-term memory (LSTM) algorithms to handle this issue. The unidirectional LSTM constantly estimates the upcoming data by learning from the previous information, while bidirectional LSTM utilize both past and future information to estimate the missing data. When the system does not receive the data from the sensor devices, the algorithms fill in the missing data based on the predicted value automatically. According to the simulation results, the proposed scheme significantly surpasses the previous works in terms of loss value.
Joint feature-sample selection and robust diagnosis of Parkinson's disease from MRI data
Adeli, Ehsan,Shi, Feng,An, Le,Wee, Chong-Yaw,Wu, Guorong,Wang, Tao,Shen, Dinggang Elsevier 2016 NeuroImage Vol.141 No.-
<P><B>Abstract</B></P> <P>Parkinson's disease (PD) is an overwhelming neurodegenerative disorder caused by deterioration of a neurotransmitter, known as dopamine. Lack of this chemical messenger impairs several brain regions and yields various motor and non-motor symptoms. Incidence of PD is predicted to double in the next two decades, which urges more research to focus on its early diagnosis and treatment. In this paper, we propose an approach to diagnose PD using magnetic resonance imaging (MRI) data. Specifically, we first introduce a joint feature-sample selection (JFSS) method for selecting an optimal subset of samples and features, to learn a reliable diagnosis model. The proposed JFSS model effectively discards poor samples and irrelevant features. As a result, the selected features play an important role in PD characterization, which will help identify the most relevant and critical imaging biomarkers for PD. Then, a robust classification framework is proposed to simultaneously de-noise the selected subset of features and samples, and learn a classification model. Our model can also de-noise testing samples based on the cleaned training data. Unlike many previous works that perform de-noising in an unsupervised manner, we perform supervised de-noising for both training and testing data, thus boosting the diagnostic accuracy. Experimental results on both synthetic and publicly available PD datasets show promising results. To evaluate the proposed method, we use the popular Parkinson's progression markers initiative (PPMI) database. Our results indicate that the proposed method can differentiate between PD and normal control (NC), and outperforms the competing methods by a relatively large margin. It is noteworthy to mention that our proposed framework can also be used for diagnosis of other brain disorders. To show this, we have also conducted experiments on the widely-used ADNI database. The obtained results indicate that our proposed method can identify the imaging biomarkers and diagnose the disease with favorable accuracies compared to the baseline methods.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A novel joint feature‐sample selection (JFSS) algorithm is proposed. </LI> <LI> The selected subset best builds a classification model; </LI> <LI> A robust classification framework is proposed that de‐noises the training data, while learning the classification model; </LI> <LI> In addition, the test data are also de-noised based on supervised cleaned training samples; </LI> <LI> The method is applied for Parkinson’s disease (PD) diagnosis, as PD‐data driven methods are scarce and not widely studied. </LI> <LI> New clinically important regions of interest (ROIs) are defined, specifically designed for PD diagnosis. </LI> </UL> </P>
A MEASUREMENT OF THE COSMIC MICROWAVE BACKGROUND B-MODE POLARIZATION WITH POLARBEAR
ADE, P.A.R.,AKIBA, Y.,ANTHONY, A.E.,ARNOLD, K.,ATLAS, M.,BARRON, D.,BOETTGER, D.,BORRILL, J.,CHAPMAN, S.,CHINONE, Y.,DOBBS, M.,ELLEFLOT, T.,ERRARD, J.,FABBIAN, G.,FENG, C.,FLANIGAN, D.,GILBERT, A.,GRA The Korean Astronomical Society 2015 天文學論叢 Vol.30 No.2
POLARBEAR is a ground-based experiment located in the Atacama desert of northern Chile. The experiment is designed to measure the Cosmic Microwave Background B-mode polarization at several arcminute resolution. The CMB B-mode polarization on degree angular scales is a unique signature of primordial gravitational waves from cosmic inflation and B-mode signal on sub-degree scales is induced by the gravitational lensing from large-scale structure. Science observations began in early 2012 with an array of 1.274 polarization sensitive antenna-couple Transition Edge Sensor (TES) bolometers at 150 GHz. We published the first CMB-only measurement of the B-mode polarization on sub-degree scales induced by gravitational lensing in December 2013 followed by the first measurement of the B-mode power spectrum on those scales in March 2014. In this proceedings, we review the physics of CMB B-modes and then describe the Polarbear experiment, observations, and recent results.
( Ade Sutrimo ) 서울대학교 간호과학연구소 2018 간호학의 지평 Vol.15 No.1
Purpose: The purpose of this study was to identify the latest evidence for interventions involving adolescent newlyweds, and the feasibility of premarital coaching (PMC). Methods: A narrative literature review design carried out through related studies was used for the present literature review. A diverse search from several databases was performed to create a critical appraisal and to develop a more integrated model for the PMC program. Studies that empirical, written in English, peer-reviewed, and published during 2008~2017 were included. Results: Six articles were selected for the review. The principal findings identified three major themes including underage period as a high-risk for marriage, development tasks of the newly married spouse, parenting self-efficacy and the psycho-educational approach of PMC to enhance parenting knowledge, skills, and readiness. Conclusion: It was found that content of PMC as the preparation of underage married couples were formulated based on coaching technic, various spouse and parenting educations, and adjusted based on couples’s preferences. Rigorous studies with measurement of long-term retentions are needed.