Search results for: Chris Cheng
328 Preparation and Characterization of Nanostructured FeN Electrocatalyst for Air Cathode Microbial Fuel Cell (MFC)
Authors: Md. Maksudur Rahman Khan, Chee Wai Woon, Huei Ruey Ong, Vignes Rasiah, Chin Kui Cheng, Kar Min Chan, E. Baranitharan
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The present work represents a preparation of non-precious iron-based electrocatalyst (FeN) for ORR in air-cathode microbial fuel cell by pyrolysis treatment. Iron oxalate which recovered from the industrial wastewater and Phenanthroline (Phen) were used as the iron and nitrogen precursors, respectively in preparing FeN catalyst. The performance of as prepared catalyst (FeN) was investigated in a single chambered air cathode MFC in which anaerobic sludge was used as inoculum and palm oil mill effluent as substrate. The maximum open circuit potential (OCV) and the highest power density recorded were 0.543 V and 4.9 mW/m2, respectively. Physical characterization of FeN was elucidated by using Brunauner Emmett Teller (BET), X-Ray Diffraction (XRD) analysis and Field Emission Scanning Electron Microscopy (FESEM) while the electrochemical properties were characterized by cyclic voltammetry (CV) analysis. The presence of biofilm on anode surface was examined using FESEM and confirmed using Infrared Spectroscopy and Thermogravimetric Analysis. The findings of this study demonstrated that FeN is electrochemically active and further modification is needed to increase the ORR catalytic activity.Keywords: iron based catalyst, microbial fuel cells, oxygen reduction reaction, palm oil mill effluent
Procedia PDF Downloads 334327 Astaxanthin Induces Cytotoxicity through Down-Regulating Rad51 Expression in Human Lung Cancer Cells
Authors: Jyh-Cheng Chen, Tai-Jing Wang, Yun-Wei Lin
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Astaxanthin has been demonstrated to exhibit a wide range of beneficial effects including anti-inflammatory and anti-cancer properties. However, the molecular mechanism of astaxanthin-induced cytotoxicity in non-small cell lung cancer (NSCLC) cells has not been identified. Rad51 plays a central role in homologous recombination and high levels of Rad51 expression are observed in chemo- or radioresistant carcinomas. In this study, astaxanthin treatment inhibited cell viability and proliferation of two NSCLC cells, A549 and H1703. Treatment with astaxanthin decreased Rad51 expression and phospho-AKT protein level in a time and dose-dependent manner. Furthermore, expression of constitutively active AKT (AKT-CA) vector significantly rescued the decreased Rad51 protein and mRNA levels in astaxanthin-treated NSCLC cells. Combined treatment with PI3K inhibitors (LY294002 or wortmannin) and astaxanthin further decreased the Rad51 expression in NSCLC cells. Knockdown of Rad51 enhanced astaxanthin-induced cytotoxicity and growth inhibition in NSCLC cells. These findings may have implications for the rational design of future drug regimens incorporating astaxanthin for the treatment of NSCLC.Keywords: astaxanthin, cytotoxicity, AKT, non-small cell lung cancer, PI3K
Procedia PDF Downloads 297326 Dyeing of Polyester/Cotton Blends with Reverse-Micelle Encapsulated High Energy Disperse/Reactive Dye Mixture
Authors: Chi-Wai Kan, Yanming Wang, Alan Yiu-Lun Tang, Cheng-Hao Lee Lee
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Dyeing of polyester/cotton blend fabrics in various polyester/cotton percentages (32/68, 40/60 and 65/35) was investigated using (poly(ethylene glycol), PEG) based reverse-micelle. High energy disperse dyes and warm type reactive dyes were encapsulated and applied on polyester/cotton blend fabrics in a one bath one step dyeing process. Comparison of reverse micellar-based and aqueous-based (water-based) dyeing was conducted in terms of colour reflectance. Experimental findings revealed that the colour shade of the dyed fabrics in reverse micellar non-aqueous dyeing system at a lower dyeing temperature of 98°C is slightly lighter than that of conventional aqueous dyeing system in two-step process (130oC for disperse dyeing and 70°C for reactive dyeing). The exhaustion of dye in polyester-cotton blend fabrics, in terms of colour reflectance, were found to be highly fluctuated at dyeing temperature of 98°C.Keywords: one-bath dyeing, polyester/cotton blends, disperse/reactive dyes, reverse micelle
Procedia PDF Downloads 150325 Exploring Gaming-Learning Interaction in MMOG Using Data Mining Methods
Authors: Meng-Tzu Cheng, Louisa Rosenheck, Chen-Yen Lin, Eric Klopfer
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The purpose of the research is to explore some of the ways in which gameplay data can be analyzed to yield results that feedback into the learning ecosystem. Back-end data for all users as they played an MMOG, The Radix Endeavor, was collected, and this study reports the analyses on a specific genetics quest by using the data mining techniques, including the decision tree method. In the study, different reasons for quest failure between participants who eventually succeeded and who never succeeded were revealed. Regarding the in-game tools use, trait examiner was a key tool in the quest completion process. Subsequently, the results of decision tree showed that a lack of trait examiner usage can be made up with additional Punnett square uses, displaying multiple pathways to success in this quest. The methods of analysis used in this study and the resulting usage patterns indicate some useful ways that gameplay data can provide insights in two main areas. The first is for game designers to know how players are interacting with and learning from their game. The second is for players themselves as well as their teachers to get information on how they are progressing through the game, and to provide help they may need based on strategies and misconceptions identified in the data.Keywords: MMOG, decision tree, genetics, gaming-learning interaction
Procedia PDF Downloads 357324 High Density Polyethylene Biocomposites Reinforced with Hydroxyapatite Nanorods and Carbon Nanofibers for Joint Replacements
Authors: Chengzhu Liao, Jianbo Zhang, Haiou Wang, Jing Ming, Huili Li, Yanyan Li, Hua Cheng, Sie Chin Tjong
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Since Bonfield’s group’s pioneer work, there has been growing interest amongst the materials scientists, biomedical engineers and surgeons in the use of novel biomaterials for the treatment of bone defects and injuries. This study focuses on the fabrication, mechanical characterization and biocompatibility evaluation of high density polyethylene (HDPE) reinforced with hydroxyapatite nanorods (HANR) and carbon nanofibers (CNF). HANRs of 20 wt% and CNFs of 0.5-2 wt% were incorporated into HDPE to form biocomposites using traditional melt-compounding and injection molding techniques. The mechanical measurements show that CNF additions greatly improve the tensile strength and Young’s modulus of HDPE and HDPE-20% nHA composites. Meanwhile, the nHA and CNF fillers were found to be effective to improve dimensional and thermal stability of HDPE. The results of osteoblast cell cultivation and dimethyl thiazolyl diphenyl thiazolyl tetrazolium (MTT) tests showed that the HDPE/ CNF-nHA nanocomposites are biocompatible. Such HDPE/ CNF-nHA hybrids are found to be potential biomaterials for making orthopedic joint/bone replacements.Keywords: biocompatibility, biocomposite, carbon nanofiber, high density polyethylene, hydroxyapatite
Procedia PDF Downloads 303323 Implementation of a Photo-Curable 3D Additive Manufacturing Technology with Grey Capability by Using Piezo Ink-jets
Authors: Ming-Jong Tsai, Y. L. Cheng, Y. L. Kuo, S. Y. Hsiao, J. W. Chen, P. H. Liu, D. H. Chen
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The 3D printing is a combination of digital technology, material science, intelligent manufacturing and control of opto-mechatronics systems. It is called the third industrial revolution from the view of the Economist Journal. A color 3D printing machine may provide the necessary support for high value-added industrial and commercial design, architectural design, personal boutique, and 3D artist’s creation. The main goal of this paper is to develop photo-curable color 3D manufacturing technology and system implementation. The key technologies include (1) Photo-curable color 3D additive manufacturing processes development and materials research (2) Piezo type ink-jet head control and Opto-mechatronics integration technique of the photo-curable color 3D laminated manufacturing system. The proposed system is integrated with single Piezo type ink-jet head with two individual channels for two primary UV light curable color resins which can provide for future colorful 3D printing solutions. The main research results are 16 grey levels and grey resolution of 75 dpi.Keywords: 3D printing, additive manufacturing, color, photo-curable, Piezo type ink-jet, UV Resin
Procedia PDF Downloads 561322 The Study of Elementary School Teacher’s Behavior of Using E-books by UTAUT Model
Authors: Tzong-Shing Cheng, Chen Pei Chen, Shu-Wei Chen
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The purpose of this research is to apply Unified Theory of Acceptance and Use of Technology (UTAUT) model to investigate the factors that influence elementary school teacher’s behavior of using e-books. Based on the literature review, a questionnaire was modified and used to test the elementary school teachers in Changhua. A total of 420 questionnaires were administered and 364 of them were returned, including 328 valid and 36 invalid questionnaires. The effective response rate is 78%. The methods of data analysis include descriptive statistics, factor analysis, Pearson’s correlation coefficient, one way analysis of variance (ANOVA) and simple regression analysis. The results show that: 1. There were significant difference in the Elementary school teachers’ “Performance Expectancy”, “Effort Expectancy”, “Social Influence”, and “Facilitating Conditions” depending on their different “Demographic Variables”. 2. “Performance Expectancy” and “Behavioral Intention to Use” are positively correlated. 3. “Effort Expectancy” and “Behavioral Intention to Use” are positively correlated. 4. There was no significant relationship between “Social Influence” and “Behavioral Intention to Use”. 5. There was significant relationship between “Facilitating Conditions” and “Use Behavior”.Keywords: e-books, UTAUT, elementary school teacher, behavioral intention to use
Procedia PDF Downloads 613321 Estimating X-Ray Spectra for Digital Mammography by Using the Expectation Maximization Algorithm: A Monte Carlo Simulation Study
Authors: Chieh-Chun Chang, Cheng-Ting Shih, Yan-Lin Liu, Shu-Jun Chang, Jay Wu
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With the widespread use of digital mammography (DM), radiation dose evaluation of breasts has become important. X-ray spectra are one of the key factors that influence the absorbed dose of glandular tissue. In this study, we estimated the X-ray spectrum of DM using the expectation maximization (EM) algorithm with the transmission measurement data. The interpolating polynomial model proposed by Boone was applied to generate the initial guess of the DM spectrum with the target/filter combination of Mo/Mo and the tube voltage of 26 kVp. The Monte Carlo N-particle code (MCNP5) was used to tally the transmission data through aluminum sheets of 0.2 to 3 mm. The X-ray spectrum was reconstructed by using the EM algorithm iteratively. The influence of the initial guess for EM reconstruction was evaluated. The percentage error of the average energy between the reference spectrum inputted for Monte Carlo simulation and the spectrum estimated by the EM algorithm was -0.14%. The normalized root mean square error (NRMSE) and the normalized root max square error (NRMaSE) between both spectra were 0.6% and 2.3%, respectively. We conclude that the EM algorithm with transmission measurement data is a convenient and useful tool for estimating x-ray spectra for DM in clinical practice.Keywords: digital mammography, expectation maximization algorithm, X-Ray spectrum, X-Ray
Procedia PDF Downloads 730320 A Multivariate 4/2 Stochastic Covariance Model: Properties and Applications to Portfolio Decisions
Authors: Yuyang Cheng, Marcos Escobar-Anel
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This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market.Keywords: stochastic covariance process, 4/2 stochastic volatility model, stochastic co-volatility movements, characteristic function, expected utility theory, verication theorem
Procedia PDF Downloads 152319 One-Shot Text Classification with Multilingual-BERT
Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao
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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.Keywords: OSML, BERT, text classification, one shot
Procedia PDF Downloads 101318 Development and Validation of the 'Short Form BASIC Scale' Psychotic Tendencies Subscale
Authors: Chia-Chun Wu, Ying-Yao Cheng
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The purpose of this study was developing the 'short-form BASIC scale' psychotic tendencies subscale so as to provide a more efficient, economical and effective way to assess the mental health of recruits. 1749 students from Naval Recruit Training Center participated in this study. The multidimensional constructs of psychotic tendencies subscale include four dimensions: schizophrenic tendencies, manic tendencies, depression tendencies, and suicidal ideation. We cut down the 36-item psychotic tendencies subscale to 25 items by using multidimension Rasch techniques. They were applied to assess model-data fit and to provide the validity evidence of the short form BASIC scale of psychotic tendencies subscale. The person separation reliabilities of the measures from four dimensions were .70, .67, .74 and .57, respectively. In addition, there is a notable correlation between the length version and short version of schizophrenic tendencies (scaled .89), manic tendencies (.96), depression tendencies (.97) and suicidal ideation (.97). The results have indicated that the development of the study of short-form scale sufficient to replace the original scale. Therefore, it is suggested that short-form basic scale is used to assess the mental health with participants being more willing to answer questions to ensure the validation of assessments.Keywords: BASIC scale, military, Rasch analysis, short-form scale
Procedia PDF Downloads 361317 Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure
Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng
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The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.Keywords: electro-rheological fluid, semi-active vibration control, shock absorber, type 2 fuzzy control
Procedia PDF Downloads 447316 The Profitability Management Mechanism of Leather Industry-Based on the Activity-Based Benefit Approach
Authors: Mei-Fang Wu, Shu-Li Wang, Tsung-Yueh Lu, Feng-Tsung Cheng
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Strengthening core competitiveness is the main goal of enterprises in a fierce competitive environment. Accurate cost information is a great help for managers in dealing with operation strategies. This paper establishes a profitability management mechanism that applies the Activity-Based Benefit approach (ABBA) to solve the profitability for each customer from the market. ABBA provides financial and non-financial information for the operation, but also indicates what resources have expired in the operational process. The customer profit management model shows the level of profitability of each customer for the company. The empirical data were gathered from a case company operating in the leather industry in Taiwan. The research findings indicate that 30% of customers create little profit for the company as a result of asking for over 5% of sales discounts. Those customers ask for sales discount because of color differences of leather products. This paper provides a customer’s profitability evaluation mechanism to help enterprises to greatly improve operating effectiveness and promote operational activity efficiency and overall operation profitability.Keywords: activity-based benefit approach, customer profit analysis, leather industry, profitability management mechanism
Procedia PDF Downloads 307315 Research on the Online Learning Activities Design and Students’ Experience Based on APT Model
Authors: Wang Yanli, Cheng Yun, Yang Jiarui
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Due to the separation of teachers and students, online teaching during the COVID-19 epidemic was faced with many problems, such as low enthusiasm of students, distraction, low learning atmosphere, and insufficient interaction between teachers and students. The essay designed the elaborate online learning activities of the course 'Research Methods of Educational Science' based on the APT model from three aspects of multiple assessment methods, a variety of teaching methods, and online learning environment and technology. Student's online learning experience was examined from the perception of online course, the perception of the online learning environment, and satisfaction after the course’s implementation. The research results showed that students have a positive overall evaluation of online courses, a high degree of engagement in learning, positive acceptance of online learning, and high satisfaction with it, but students hold a relatively neutral attitude toward online learning. And some dimensions in online learning experience were found to have positive influence on students' satisfaction with online learning. We suggest making the good design of online courses, selecting proper learning platforms, and conducting blended learning to improve students’ learning experience. This study has both theoretical and practical significance for the design, implementation, effect feedback, and sustainable development of online teaching in the post-epidemic era.Keywords: APT model, online learning, online learning activities, learning experience
Procedia PDF Downloads 136314 Violence Detection and Tracking on Moving Surveillance Video Using Machine Learning Approach
Authors: Abe Degale D., Cheng Jian
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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.Keywords: violence detection, faster RCNN, transfer learning and, surveillance video
Procedia PDF Downloads 108313 Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method
Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage
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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square
Procedia PDF Downloads 383312 Assisted Prediction of Hypertension Based on Heart Rate Variability and Improved Residual Networks
Authors: Yong Zhao, Jian He, Cheng Zhang
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Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.Keywords: feature extraction, heart rate variability, hypertension, residual networks
Procedia PDF Downloads 105311 A Study on the Stabilization of the Swell Behavior of Basic Oxygen Furnace Slag by Using Geopolymer Technology
Authors: K. Y. Lin, W. H. Lee, T. W. Cheng, S. W. Huang
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Basic Oxygen Furnace (BOF) Slag is a by-product of iron making. It has great engineering properties, such as, high hardness and density, high compressive strength, low abrasion ratio, and can replace natural aggregate for building materials. However, the main problem for BOF slag is expansion, due to it contains free lime or free magnesium. The purpose of this study was to stabilize the BOF slag by using geopolymeric technology, hoping can prevent BOF slag expansion. Geopolymer processes contain a large amount of free silicon. These free silicon can react with free-lime or free magnesium oxide in BOF slag, and thus to form stable compound, therefore inhibit the expansion of the BOF slag. In this study for the successful preparation of geopolymer mortar with BOF slag, and their main properties are analyzed with regard to their use as building materials. Autoclave is used to study the volume stability of these geopolymer mortar. Finally, the compressive strength of geopolymer mortar with BOF slag can be reached 33MPa in 28 days. After autoclave testing, the volume expansion does not exceed 0.2%. Even after the autoclave test, the compressive strength can increase to 35MPa. According to the research results can be proved that using geopolymer technology for stabilizing BOF slag is very effective.Keywords: BOF slag, autoclave test, geopolymer, swell behavior
Procedia PDF Downloads 136310 Using Closed Frequent Itemsets for Hierarchical Document Clustering
Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu
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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.Keywords: FIHC, documents clustering, ontology, closed frequent itemset
Procedia PDF Downloads 399309 Hsa-miR-326 Functions as a Tumor Suppressor in Non-Small Cell Lung Cancer through Targeting CCND1
Authors: Cheng-Cao Sun, Shu-Jun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, De-Jia Li
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Hsa-miRNA-326 (miR-326) has recently been discovered having anticancer efficacy in different organs. However, the role of miR-326 on non-small cell lung cancer (NSCLC) is still ambiguous. In this study, we investigated the role of miR-326 on the development of NSCLC. The results indicated that miR-326 was significantly down-regulated in primary tumor tissues and very low levels were found in NSCLC cell lines. Ectopic expression of miR-326 in NSCLC cell lines significantly suppressed cell growth as evidenced by cell viability assay, colony formation assay and BrdU staining, through inhibition of cyclin D1, cyclin D2, CDK4, and up-regulation of p57(Kip2) and p21(Waf1/Cip1). In addition, miR-326 induced apoptosis, as indicated by concomitantly with up-regulation of key apoptosis protein cleaved caspase-3, and down-regulation of anti-apoptosis protein Bcl2. Moreover, miR-326 inhibited cellular migration and invasiveness through inhibition of matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene CCND1 was revealed to be a putative target of miR-326, which was inversely correlated with miR-326 expression in NSCLC. Taken together, our results demonstrated that miR-326 played a pivotal role on NSCLC through inhibiting cell proliferation, migration, invasion, and promoting apoptosis by targeting oncogenic CCND1.Keywords: hsa-miRNA-326 (miR-326), cyclin D1, non-small cell lung cancer (NSCLC), proliferation, apoptosis
Procedia PDF Downloads 306308 Online Pose Estimation and Tracking Approach with Siamese Region Proposal Network
Authors: Cheng Fang, Lingwei Quan, Cunyue Lu
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Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.Keywords: computer vision, pose estimation, pose tracking, Siamese network
Procedia PDF Downloads 153307 Stray Light Reduction Methodology by a Sinusoidal Light Modulation and Three-Parameter Sine Curve Fitting Algorithm for a Reflectance Spectrometer
Authors: Hung Chih Hsieh, Cheng Hao Chang, Yun Hsiang Chang, Yu Lin Chang
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In the applications of the spectrometer, the stray light that comes from the environment affects the measurement results a lot. Hence, environment and instrument quality control for the stray reduction is critical for the spectral reflectance measurement. In this paper, a simple and practical method has been developed to correct a spectrometer's response for measurement errors arising from the environment's and instrument's stray light. A sinusoidal modulated light intensity signal was incident on a tested sample, and then the reflected light was collected by the spectrometer. Since a sinusoidal signal modulated the incident light, the reflected light also had a modulated frequency which was the same as the incident signal. Using the three-parameter sine curve fitting algorithm, we can extract the primary reflectance signal from the total measured signal, which contained the primary reflectance signal and the stray light from the environment. The spectra similarity between the extracted spectra by this proposed method with extreme environment stray light is 99.98% similar to the spectra without the environment's stray light. This result shows that we can measure the reflectance spectra without the affection of the environment's stray light.Keywords: spectrometer, stray light, three-parameter sine curve fitting, spectra extraction
Procedia PDF Downloads 248306 An Interactive Platform Displaying Mixed Reality Media
Authors: Alfred Chen, Cheng Chieh Hsu, Yu-Pin Ma, Meng-Jie Lin, Fu Pai Chiu, Yi-Yan Sie
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This study is attempted to construct a human-computer interactive platform system that has mainly consisted of an augmented hardware system, a software system, a display table, and mixed media. This system has provided with human-computer interaction services through an interactive platform for the tourism industry. A well designed interactive platform, integrating of augmented reality and mixed media, has potential to enhance museum display quality and diversity. Besides, it will create a comprehensive and creative display mode for most museums and historical heritages. Therefore, it is essential to let public understand what the platform is, how it functions, and most importantly how one builds an interactive augmented platform. Hence the authors try to elaborate the construction process of the platform in detail. Thus, there are three issues to be considered, i.e.1) the theory and application of augmented reality, 2) the hardware and software applied, and 3) the mixed media presented. In order to describe how the platform works, Courtesy Door of Tainan Confucius Temple has been selected as case study in this study. As a result, a developed interactive platform has been presented by showing the physical entity object, along with virtual mixing media such as text, images, animation, and video. This platform will result in providing diversified and effective information that will be delivered to the users.Keywords: human-computer interaction, mixed reality, mixed media, tourism
Procedia PDF Downloads 489305 Empirical Studies of Indigenous Reserved Land in Taiwan- An Example of a Truku Tribe in Hualien County
Authors: Chuanju Cheng
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In Taiwan, the system of indigenous reserved land was established in 1928 during the Japanese rule. The purpose of setting up indigenous reserved land is to support the livelihood of tribal peoples who live in the mountainous area. Since 1945, the KMT government has kept the indigenous reserved land; in principle, only indigenous people can use indigenous reserved land. However, the government also makes some exceptions for non-indigenous peoples to use the land. Furthermore, since 1966, an indigenous individual can have ownership (fee simple) over the land he/she uses. Recent studies showed that there are many problems regarding the indigenous reserved lands, such as indigenous peoples have been losing ownership of their land (both legally and illegally), mismatched data of the true owner and the nominal owner, overutilization of the reserved land and so on. Using a Truku tribe in Hualien County as an example, this paper tries to find out how many people still own indigenous reserved land, do land owners constantly utilize their lands, and if so, whether or not (and by what extent) the indigenous reserved land support the livelihood of tribal peoples? After ten months of working data-collecting, we’ve successfully collected 327 questionnaires (70% of total households); preliminary research results show that less than 5% of indigenous reserved land in and around that specific Truku tribe is owned by tribal people. And most of the landowners do not utilize indigenous reserved land. It seems that the indigenous reserved land system does not meet its legislative goals and needs to be redesigned.Keywords: indigenous people, truku nation, taiwan, indigenous reserved land, poverty, economic development
Procedia PDF Downloads 83304 Impact of Fischer-Tropsch Wax on Ethylene Vinyl Acetate/Waste Crumb Rubber Modified Bitumen: An Energy-Sustainability Nexus
Authors: Keith D. Nare, Mohau J. Phiri, James Carson, Chris D. Woolard, Shanganyane P. Hlangothi
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In an energy-intensive world, minimizing energy consumption is paramount to cost saving and reducing the carbon footprint. Improving mixture procedures utilizing warm mix additive Fischer-Tropsch (FT) wax in ethylene vinyl acetate (EVA) and modified bitumen highlights a greener and sustainable approach to modified bitumen. In this study, the impact of FT wax on optimized EVA/waste crumb rubber modified bitumen is assayed with a maximum loading of 2.5%. The rationale of the FT wax loading is to maintain the original maximum loading of EVA in the optimized mixture. The phase change abilities of FT wax enable EVA co-crystallization with the support of the elastomeric backbone of crumb rubber. Less than 1% loading of FT wax worked in the EVA/crumb rubber modified bitumen energy-sustainability nexus. Response surface methodology approach to the mixture design is implemented amongst the different loadings of FT wax, EVA for a consistent amount of crumb rubber and bitumen. Rheological parameters (complex shear modulus, phase angle and rutting parameter) were the factors used as performance indicators of the different optimized mixtures. The low temperature chemistry of the optimized mixtures is analyzed using elementary beam theory and the elastic-viscoelastic correspondence principle. Master curves and black space diagrams are developed and used to predict age-induced cracking of the different long term aged mixtures. Modified binder rheology reveals that the strain response is not linear and that there is substantial re-arrangement of polymer chains as stress is increased, this is based on the age state of the mixture and the FT wax and EVA loadings. Dominance of individual effects is evident over effects of synergy in co-interaction of EVA and FT wax. All-inclusive FT wax and EVA formulations were best optimized in mixture 4 with mixture 7 reflecting increase in ease of workability. Findings show that interaction chemistry of bitumen, crumb rubber EVA, and FT wax is first and second order in all cases involving individual contributions and co-interaction amongst the components of the mixture.Keywords: bitumen, crumb rubber, ethylene vinyl acetate, FT wax
Procedia PDF Downloads 173303 Agent-Based Modeling of Pedestrian Corridor Congestion on the Characteristics of Physical Space Form
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The pedestrian corridor is the most crowded area in the public space. The crowded severity has been focused on the field of evacuation strategies of the entrance in large public spaces. The aim of this paper is to analyze the walking efficiency in different spaces of pedestrian corridor with the variation of spatial parameters. The congestion condition caused by the variation of walking efficiency is modeled as well. This study established the space model of the walking corridor by setting the width, slope, turning form and turning angle of the pedestrian corridor. The pedestrian preference of walking mode varied with the difference of the crowded severity, walking speed, field of vision, sight direction and the expected destination, which is influenced by the characters of physical space form. Swarm software is applied to build Agent model. According to the output of the Agent model, the relationship between the pedestrian corridor width, ground slope, turning forms, turning angle and the walking efficiency, crowded severity is acquired. The results of the simulation can be applied to pedestrian corridor design in order to reduce the crowded severity and the potential safety risks caused by crowded people.Keywords: crowded severity, multi-agent, pedestrian preference, urban space design
Procedia PDF Downloads 219302 The Effect of Damping Treatment for Noise Control on Offshore Platforms Using Statistical Energy Analysis
Authors: Ji Xi, Cheng Song Chin, Ehsan Mesbahi
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Structure-borne noise is an important aspect of offshore platform sound field. It can be generated either directly by vibrating machineries induced mechanical force, indirectly by the excitation of structure or excitation by incident airborne noise. Therefore, limiting of the transmission of vibration energy throughout the offshore platform is the key to control the structure-borne noise. This is usually done by introducing damping treatment to the steel structures. Two types of damping treatment using on-board are presented. By conducting a statistical energy analysis (SEA) simulation on a jack-up rig, the noise level in the source room, the neighboring rooms, and remote living quarter cabins are compared before and after the damping treatments been applied. The results demonstrated that, in the source neighboring room and living quarter area, there is a significant noise reduction with the damping treatment applied, whereas in the source room where air-borne sound predominates that of structure-borne sound, the impact is not obvious. The subsequent optimization design of damping treatment in the offshore platform can be made which enable acoustic professionals to implement noise control during the design stage for offshore crews’ hearing protection and habitant comfortability.Keywords: statistical energy analysis, damping treatment, noise control, offshore platform
Procedia PDF Downloads 555301 The Intention to Use Telecare in People of Fall Experience: Application of Fuzzy Neural Network
Authors: Jui-Chen Huang, Shou-Hsiung Cheng
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This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.Keywords: fall, fuzzy neural network, health belief model, telecare, willingness
Procedia PDF Downloads 201300 Improvement of Mechanical Properties of Saline Soils by Fly Ash: Effect of Freeze-Thaw Cycles
Authors: Zhuo Cheng, Gaohang Cui, Yang Zheng, Zhiqiang-Pan
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To explore the effect of freeze-thaw cycles on saline soil mechanical properties of fly ash, this study examined the influence of different numbers of freezing and thawing cycles, fly ash content, and moisture content of saline soil in unconfined compression tests and triaxial shear tests. With increased fly ash content, the internal friction angle, cohesion, unconfined compressive strength, and shear strength of the improved soil increased at first and then decreased. Using the Desk-Expert 8.0 software and based on significance analysis theory, the number of freeze-thaw cycles, fly ash content, water content, and the interactions between various factors on the mechanical properties of saline soil were studied. The results showed that the number of freeze-thaw cycles had a significant effect on the mechanical properties of saline soil, while the fly ash content had a weakly significant effect. At the same time, interaction between the number of freeze-thaw cycles and the water content had a significant effect on the unconfined compressive strength and the cohesion of saline soil, and the interaction between fly ash content and the number of freeze-thaw cycles only had a significant effect on the unconfined compressive strength.Keywords: fly ash, saline soil, seasonally frozen area, significance analysis, qualitative analysis
Procedia PDF Downloads 147299 Field-Programmable Gate Arrays Based High-Efficiency Oriented Fast and Rotated Binary Robust Independent Elementary Feature Extraction Method Using Feature Zone Strategy
Authors: Huang Bai-Cheng
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When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.Keywords: feature extraction, real-time, ORB, FPGA implementation
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