Search results for: Yong Yang
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 547

Search results for: Yong Yang

187 Solid Circulation Rate and Gas Leakage Measurements in an Interconnected Bubbling Fluidized Beds

Authors: Ho-Jung Ryu, Seung-Yong Lee, Young Cheol Park, Moon-Hee Park

Abstract:

Two-interconnected fluidized bed systems are widely used in various processes such as Fisher-Tropsch, hot gas desulfurization, CO2 capture-regeneration with dry sorbent, chemical-looping combustion, sorption enhanced steam methane reforming, chemical-looping hydrogen generation system, and so on. However, most of two-interconnected fluidized beds systems require riser and/or pneumatic transport line for solid conveying and loopseals or seal-pots for gas sealing, recirculation of solids to the riser, and maintaining of pressure balance. The riser (transport bed) is operated at the high velocity fluidization condition and residence times of gas and solid in the riser are very short. If the reaction rate of catalyst or sorbent is slow, the riser can not ensure sufficient contact time between gas and solid and we have to use two bubbling beds for each reaction to ensure sufficient contact time. In this case, additional riser must be installed for solid circulation. Consequently, conventional two-interconnected fluidized bed systems are very complex, large, and difficult to operate. To solve these problems, a novel two-interconnected fluidized bed system has been developed. This system has two bubbling beds, solid injection nozzles, solid conveying lines, and downcomers. In this study, effects of operating variables on solid circulation rate, gas leakage between two beds have been investigated in a cold mode two-interconnected fluidized bed system. Moreover, long-term operation of continuous solid circulation up to 60 hours has been performed to check feasibility of stable operation.

Keywords: Fluidized bed, Gas leakage, Long-term operation, Solid circulation.

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186 An Energy Efficient Protocol for Target Localization in Wireless Sensor Networks

Authors: Shun-Kai Yang, Kuo-Feng Ssu

Abstract:

Target tracking and localization are important applications in wireless sensor networks. In these applications, sensor nodes collectively monitor and track the movement of a target. They have limited energy supplied by batteries, so energy efficiency is essential for sensor networks. Most existing target tracking protocols need to wake up sensors periodically to perform tracking. Some unnecessary energy waste is thus introduced. In this paper, an energy efficient protocol for target localization is proposed. In order to preserve energy, the protocol fixes the number of sensors for target tracking, but it retains the quality of target localization in an acceptable level. By selecting a set of sensors for target localization, the other sensors can sleep rather than periodically wake up to track the target. Simulation results show that the proposed protocol saves a significant amount of energy and also prolongs the network lifetime.

Keywords: Coverage, energy efficiency, target localization, wireless sensor network.

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185 Development of a New Piezoelectrically Actuated Micropump for Liquid and Gas

Authors: Chiang-Ho Cheng, An-Shik Yang, Chih-Jer Lin, Chun-Ying Lee

Abstract:

This paper aims to present the design, fabrication and test of a novel piezoelectric actuated, check-valves embedded micropump having the advantages of miniature size, light weight and low power consumption. This device is designed to pump gases and liquids with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micropump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micropump, the displacement of the piezoelectric actuator and the deformation of the check valve, simultaneously. The micropump with check valve 0.4 mm in thickness obtained higher output performance under the sinusoidal waveform of 120 Vpp. The micropump achieved the maximum pumping rates of 42.2 ml/min and back pressure of 14.0 kPa at the corresponding frequency of 28 and 20 Hz. The presented micropump is able to pump gases with a pumping rate of 196 ml/min at operating frequencies of 280 Hz under the sinusoidal waveform of 120 Vpp.

Keywords: Actuator, Check-valve, Micropump, Piezoelectric.

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184 Relationships between Information Transparency, Corporate Governance and D&O Insurance

Authors: Shu-Lin Lin, Ching-Chien Yang

Abstract:

This study examines the influence of information transparency and corporate governance on purchase directors and officers liability (D&O) insurance decisions. The results show that companies with greater information transparency have significant demand for D&O insurance. Greater transparency in voluntary disclosures is significantly and positively associated with demand for insurance, indicating that increasing the degree of information disclosure reduces information asymmetry for insurers, which stimulates their willingness to provide greater protection. Analysis of insured and uninsured subsamples indicates that uninsured companies have superior corporate governance compared to insured companies. Although insured companies tend to have weaker corporate governance structures, they appoint Big 4 firms or industry experts to compensate for the weakness of their corporate governance. Empirical results indicate that purchasing D&O insurance can strengthen external corporate governance and increase companies’ willingness to voluntarily provide more transparent information.

Keywords: Directors and officers liability (D&O) insurance, information transparency, corporate governance, Big 4.

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183 Evaluation of the Contribution of Starting Pitchers in a Professional Baseball Team by Grey Relational Analysis

Authors: Chih-Cheng Chen, Yung-Tan Lee, Shih-Yang Lee, Shih-Kuei Huang, Tien-Tze Chen, Qiu-Jun Chen

Abstract:

The evaluation of the contribution of professional baseball starting pitchers is a complex decision-making problem that includes several quantitative attributes. It is considered a type of multi-attribute or multi-criteria decision making (MADM/MCDM) problem. This study proposes a model using the Grey Relational Analysis (GRA) to evaluate the starting pitcher contribution for teams of the Chinese Professional Baseball League. The GRA calculates the individual grey relational degree of each alternative to the positive ideal alternative. An empirical analysis was conducted to show the use of the model for the starting pitcher contribution problem. The results demonstrate the effectiveness and feasibility of the proposed model.

Keywords: Starting pitchers, Grey Relational Analysis, Chinese Professional Baseball

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182 The Main Steamline Break Transient Analysis for Advanced Boiling Water Reactor Using TRACE, PARCS, and SNAP Codes

Authors: H. C. Chang, J. R. Wang, A. L. Ho, S. W. Chen, J. H. Yang, C. Shih, L. C. Wang

Abstract:

To confirm the reactor and containment integrity of the Advanced Boiling Water Reactor (ABWR), we perform the analysis of main steamline break (MSLB) transient by using the TRACE, PARCS, and SNAP codes. The process of the research has four steps. First, the ABWR nuclear power plant (NPP) model is developed by using the above codes. Second, the steady state analysis is performed by using this model. Third, the ABWR model is used to run the analysis of MSLB transient. Fourth, the predictions of TRACE and PARCS are compared with the data of FSAR. The results of TRACE/PARCS and FSAR are similar. According to the TRACE/PARCS results, the reactor and containment integrity of ABWR can be maintained in a safe condition for MSLB.

Keywords: ABWR, TRACE, PARCS, SNAP.

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181 Submicron Size of Alumina/Titania Tubes for CO2-CH4 Conversion

Authors: Chien-Wan Hun, Shao-Fu Chang, Jheng-En Yang, Chien-Chon Chen, Wern-Dare Jheng

Abstract:

This research provides a systematic way to study and better understand double nano-tubular structure of alunina (Al2O3) and titania (TiO2). The TiO2 NT was prepared by immersing Al2O3 template in 0.02 M titanium fluoride (TiF4) solution (pH=3) at 25 °C for 120 min, followed by annealing at 450 °C for 1 h to obtain anatase TiO2 NT in the Al2O3 template. Large-scale development of film for nanotube-based CO2 capture and conversion can potentially result in more efficient energy harvesting. In addition, the production process will be relatively environmentally friendly. The knowledge generated by this research will significantly advance research in the area of Al2O3, TiO2, CaO, and Ca2O3 nano-structure film fabrication and applications for CO2 capture and conversion. This green energy source will potentially reduce reliance on carbon-based energy resources and increase interest in science and engineering careers.

Keywords: Alumina, titania, nano-tubular, film, CO2.

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180 Design and Fabrication of an Array Microejector Driven by a Shear-Mode Piezoelectric Actuator

Authors: Chiang-Ho Cheng, Hong-Yih Cheng, An-Shik Yang, Tung-Hsun Hsu

Abstract:

This paper reports a novel actuating design that uses the shear deformation of a piezoelectric actuator to deflect a bulge-diaphragm for driving an array microdroplet ejector. In essence, we employed a circular-shaped actuator poled radial direction with remnant polarization normal to the actuating electric field for inducing the piezoelectric shear effect. The array microdroplet ejector consists of a shear type piezoelectric actuator, a vibration plate, two chamber plates, two channel plates and a nozzle plate. The vibration, chamber and nozzle plate components are fabricated using nickel electroforming technology, whereas the channel plate is fabricated by etching of stainless steel. The diaphragm displacement was measured by the laser two-dimensional scanning vibrometer. The ejected droplets of the microejector were also observed via an optic visualization system.

Keywords: Actuator, nozzle, microejector, piezoelectric.

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179 Using RASCAL and ALOHA Codes to Establish an Analysis Methodology for Hydrogen Fluoride Evaluation

Authors: J. R. Wang, Y. Chiang, W. S. Hsu, H. C. Chen, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih

Abstract:

In this study, the RASCAL and ALOHA codes are used to establish an analysis methodology for hydrogen fluoride (HF) evaluation. There are three main steps in this study. First, the UF6 data were collected. Second, one postulated case was analyzed by using the RASCAL and UF6 data. This postulated case assumes that fire occurring and UF6 is releasing from a building. Third, the results of RASCAL for HF mass were as the input data of ALOHA. Two postulated cases of HF were analyzed by using ALOHA code and the results of RASCAL. These postulated cases assume fire occurring and HF is releasing with no raining (Case 1) or raining (Case 2) condition. According to the analysis results of ALOHA, the HF concentration of Case 2 is smaller than Case 1. The results can be a reference for the preparing of emergency plans for the release of HF.

Keywords: RASCAL, ALOHA, UF6, hydrogen fluoride.

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178 A Straightforward Approach for Determining the Weights of Decision Makers Based on Angle Cosine and Projection Method

Authors: Qiang Yang, Ping-An Du

Abstract:

Group decision making with multiple attribute has attracted intensive concern in the decision analysis area. This paper assumes that the contributions of all the decision makers (DMs) are not equal to the decision process based on different knowledge and experience in group setting. The aim of this paper is to develop a novel approach to determine weights of DMs in the group decision making problems. In this paper, the weights of DMs are determined in the group decision environment via angle cosine and projection method. First of all, the average decision of all individual decisions is defined as the ideal decision. After that, we define the weight of each decision maker (DM) by aggregating the angle cosine and projection between individual decision and ideal decision with associated direction indicator μ. By using the weights of DMs, all individual decisions are aggregated into a collective decision. Further, the preference order of alternatives is ranked in accordance with the overall row value of collective decision. Finally, an example in a chemical company is provided to illustrate the developed approach.

Keywords: Angel cosine, ideal decision, projection method, weights of decision makers.

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177 Numerical Analysis on the Performance of Heatsink with Microchannels

Authors: Jer-Huan Jang, Han-Chieh Chiu, Wei-Chung Yeih, Jia-Jui Yang, Chien-Sheng Huang

Abstract:

In this paper, numerical simulation is used to investigate the thermal performance of liquid cooling heatsink with microchannels due to geometric arrangement. Commercial software ICEPAK is utilized for the analysis. The considered parameters include aspect ratio, porosity and the length and height of microchannel. The aspect ratio varies from 3 to 16 and the length of microchannel is 10mm, 14mm, and 18mm. The height of microchannel is 2mm, 3mm and 4mm. It is found short channel have better thermal efficiency than long channel at 490Pa. No matter the length of channel the best aspect ratio is 4. It is also noted that pressure difference at 2940Pa the best aspect ratio from 4 to 8, it means pressure difference affect aspect ratio, effective thermal resistance at low pressure difference but lower effective thermal resistance at high pressure difference.

Keywords: thermal resistance, liquid cooling, microchannels, numerical analysis, pressure difference

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176 Graphene/h-BN Heterostructure Interconnects

Authors: Nikhil Jain, Yang Xu, Bin Yu

Abstract:

The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h- BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h- BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: Two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects.

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175 Identification of Spam Keywords Using Hierarchical Category in C2C E-commerce

Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

Abstract:

Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like ebay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C E-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C E-commerce.

Keywords: Spam Keyword, E-commerce, keyword features, spam filtering.

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174 Infrared Camera-Based Hand Gesture Space Touch System Implementation of Smart Device Environment

Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

Abstract:

This paper proposes a method to recognize the tip of a finger and space touch hand gesture using an infrared camera in a smart device environment. The proposed method estimates the tip of a finger with a curvature-based ellipse fitting algorithm, and verifies that the estimated object is indeed a finger with an ellipse fitting rectangular area. The feature extracted from the verified finger tip is used to implement the movement of a mouse and clicking gesture. The proposed algorithm was implemented with an actual smart device to test the proposed method. Empirical parameters were obtained from the keypad software and an image analysis tool for the performance optimization, and a comparative analysis with conventional research showed improved performance with the proposed method.

Keywords: Infrared camera, Hand gesture, Smart device, Space touch.

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173 Analysis and Control of Camera Type Weft Straightener

Authors: Jae-Yong Lee, Gyu-Hyun Bae, Yun-Soo Chung, Dae-Sub Kim, Jae-Sung Bae

Abstract:

In general, fabric is heat-treated using a stenter machine in order to dry and fix its shape. It is important to shape before the heat treatment because it is difficult to revert back once the fabric is formed. To produce the product of right shape, camera type weft straightener has been applied recently to capture and process fabric images quickly. It is more powerful in determining the final textile quality rather than photo-sensor. Positioning in front of a stenter machine, weft straightener helps to spread fabric evenly and control the angle between warp and weft constantly as right angle by handling skew and bow rollers. To process this tricky procedure, the structural analysis should be carried out in advance, based on which, its control technology can be drawn. A structural analysis is to figure out the specific contact/slippage characteristics between fabric and roller. We already examined the applicability of camera type weft straightener to plain weave fabric and found its possibility and the specific working condition of machine and rollers. In this research, we aimed to explore another applicability of camera type weft straightener. Namely, we tried to figure out camera type weft straightener can be used for fabrics. To find out the optimum condition, we increased the number of rollers. The analysis is done by ANSYS software using Finite Element Analysis method. The control function is demonstrated by experiment. In conclusion, the structural analysis of weft straightener is done to identify a specific characteristic between roller and fabrics. The control of skew and bow roller is done to decrease the error of the angle between warp and weft. Finally, it is proved that camera type straightener can also be used for the special fabrics.

Keywords: Camera type weft straightener, structure analysis, control, skew and bow roller.

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172 Design of Reconfigurable Supernumerary Robotic Limb Based on Differential Actuated Joints

Authors: Qinghua Zhang, Yanhe Zhu, Xiang Zhao, Yeqin Yang, Hongwei Jing, Guoan Zhang, Jie Zhao

Abstract:

This paper presents a wearable reconfigurable supernumerary robotic limb with differential actuated joints, which is lightweight, compact and comfortable for the wearers. Compared to the existing supernumerary robotic limbs which mostly adopted series structure with large movement space but poor carrying capacity, a prototype with the series-parallel configuration to better adapt to different task requirements has been developed in this design. To achieve a compact structure, two kinds of cable-driven mechanical structures based on guide pulleys and differential actuated joints were designed. Moreover, two different tension devices were also designed to ensure the reliability and accuracy of the cable-driven transmission. The proposed device also employed self-designed bearings which greatly simplified the structure and reduced the cost.

Keywords: Cable-driven, differential actuated joints, reconfigurable, supernumerary robotic limb.

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171 An Auxiliary Technique for Coronary Heart Disease Prediction by Analyzing ECG Based on ResNet and Bi-LSTM

Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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170 Photo Mosaic Smartphone Application in Client-Server Based Large-Scale Image Databases

Authors: Sang-Hun Lee, Bum-Soo Kim, Yang-Sae Moon, Jinho Kim

Abstract:

In this paper we present a photo mosaic smartphone application in client-server based large-scale image databases. Photo mosaic is not a new concept, but there are very few smartphone applications especially for a huge number of images in the client-server environment. To support large-scale image databases, we first propose an overall framework working as a client-server model. We then present a concept of image-PAA features to efficiently handle a huge number of images and discuss its lower bounding property. We also present a best-match algorithm that exploits the lower bounding property of image-PAA. We finally implement an efficient Android-based application and demonstrate its feasibility.

Keywords: smartphone applications; photo mosaic; similarity search; data mining; large-scale image databases.

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169 Text Mining of Twitter Data Using a Latent Dirichlet Allocation Topic Model and Sentiment Analysis

Authors: Sidi Yang, Haiyi Zhang

Abstract:

Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: Text mining, Twitter, topic model, sentiment analysis.

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168 Analysis of Lightweight Register Hardware Threat

Authors: Yang Luo, Beibei Wang

Abstract:

In this paper, we present a design methodology of lightweight register transfer level (RTL) hardware threat implemented based on a MAX II FPGA platform. The dynamic power consumed by the toggling of the various bit of registers as well as the dynamic power consumed per unit of logic circuits were analyzed. The hardware threat was designed taking advantage of the differences in dynamic power consumed per unit of logic circuits to hide the transfer information. The experiment result shows that the register hardware threat was successfully implemented by using different dynamic power consumed per unit of logic circuits to hide the key information of DES encryption module. It needs more than 100000 sample curves to reduce the background noise by comparing the sample space when it completely meets the time alignment requirement. In additional, an external trigger signal is playing a very important role to detect the hardware threat in this experiment.

Keywords: Side-channel analysis, hardware threat, register transfer level, dynamic power.

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167 Scheduling Method for Electric Heater in HEMS Considering User’s Comfort

Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo Jin-O Kim

Abstract:

Home Energy Management System (HEMS), which makes the residential consumers, contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance, which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it represents impacts of the comfort level on the scheduling result.

Keywords: Load scheduling, usage pattern, user’s comfort, copula function, branch, bound, electric heater.

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166 The Effectiveness of ICT-Assisted PBL on College-Level Nano Knowledge and Learning Skills

Authors: Ya-Ting Carolyn Yang, Ping-Han Cheng, Shi-Hui Gilbert Chang, Terry Yuan-Fang Chen, Chih-Chieh Li

Abstract:

Nanotechnology is widely applied in various areas so professionals in the related fields have to know more than nano knowledge. In the study, we focus on adopting ICT-assisted PBL in college general education to foster professionals who possess multiple abilities. The research adopted a pretest and posttest quasi-experimental design. The control group received traditional instruction, and the experimental group received ICT-assisted PBL instruction. Descriptive statistics will be used to describe the means, standard deviations, and adjusted means for the tests between the two groups. Next, analysis of covariance (ANCOVA) will be used to compare the final results of the two research groups after 6 weeks of instruction. Statistics gathered in the end of the research can be used to make contrasts. Therefore, we will see how different teaching strategies can improve students’ understanding about nanotechnology and learning skills.

Keywords: Nanotechnology, science education, project-based learning, information and communication technology.

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165 System Identification and Performance Improvement to a Micro Gas Turbine Applying Biogas

Authors: Chun Hsiang Yang, Cheng Chia Lee, Chiun Hsun Chen

Abstract:

In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.

Keywords: Micro Gas Turbine, Biogas; System Identification, Distributed power supply system

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164 Explanatory of Relationship between Learning Motivation and Learning Performance

Authors: Chih Chin Yang

Abstract:

In this paper, the relationship between learning motivation and learning performance is explored by using exchange theory. The relationship is concluded that external performance can raise learning motivation and then increase learning performance. The internal performance should be not completely neglected and the external performance should be not attached important excessively. The parents need self-study and must be also reeducated. The existing education must be improved in raise of internal performance. The incorrect learning thinking will mislead the students, parents, and educators of next generation, when the students obtain good learning performance in the learning environment with excess stimulants. Over operation of external performance will result abnormal learning thinking and violating learning goal. Learning is not only to obtain performance. Learning quality and learning performance will be limited as without learning motivation. The best learning motivation is, the best learning performance is. The learning for reward is not good for learning performance. Strategies of promoting life-long learning are including the encouraging for learner, establishment of good interaction learning environment, and the advertisement of the merit and the importance of life-long learning, which can let the learner with the correct learning motivation.

Keywords: exchange theory, learning motivation, learning performance, learning quality

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163 A Novel Prediction Method for Tag SNP Selection using Genetic Algorithm based on KNN

Authors: Li-Yeh Chuang, Yu-Jen Hou, Jr., Cheng-Hong Yang

Abstract:

Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, research is limited by the cost of genotyping the tremendous number of SNPs. Therefore, it is important to identify a small subset of informative SNPs, the so-called tag SNPs. This subset consists of selected SNPs of the genotypes, and accurately represents the rest of the SNPs. Furthermore, an effective evaluation method is needed to evaluate prediction accuracy of a set of tag SNPs. In this paper, a genetic algorithm (GA) is applied to tag SNP problems, and the K-nearest neighbor (K-NN) serves as a prediction method of tag SNP selection. The experimental data used was taken from the HapMap project; it consists of genotype data rather than haplotype data. The proposed method consistently identified tag SNPs with considerably better prediction accuracy than methods from the literature. At the same time, the number of tag SNPs identified was smaller than the number of tag SNPs in the other methods. The run time of the proposed method was much shorter than the run time of the SVM/STSA method when the same accuracy was reached.

Keywords: Genetic Algorithm (GA), Genotype, Single nucleotide polymorphism (SNP), tag SNPs.

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162 Grating Scale Thermal Expansion Error Compensation for Large Machine Tools Based on Multiple Temperature Detection

Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

Abstract:

To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detection is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15μm/10m and the accuracy of the machine tool is significant improved.

Keywords: Thermal expansion error of grating scale, error compensation, machine tools, integral method.

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161 An Effective Noise Resistant FM Continuous-Wave Radar Vital Sign Signal Detection Method

Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

Abstract:

To address the problem that the FM continuous-wave (FMCW) radar extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a backpropagation (BP) neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise, accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal to-noise ratio of the sign signals.

Keywords: Frequency modulated continuous wave radar, ICEEMDAN, BP Neural Network, vital signs signal.

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160 Design and Fabrication of Micro-Bubble Oxygenator

Authors: Chiang-Ho Cheng, An-Shik Yang, Hong-Yih Cheng

Abstract:

This paper applies the MEMS technology to design and fabricate a micro-bubble generator by a piezoelectric actuator. Coupled with a nickel nozzle plate, an annular piezoelectric ceramic was utilized as the primary structure of the generator. In operations, the piezoelectric element deforms transversely under an electric field applied across the thickness of the generator. The surface of the nozzle plate can expand or contract because of the induction of radial strain, resulting in the whole structure to bend, and successively transport oxygen micro-bubbles into the blood flow for enhancing the oxygen content in blood. In the tests, a high magnification microscope and a high speed CCD camera were employed to photograph the time evolution of meniscus shape of gaseous bubbles dispensed from the micro-bubble generator for flow visualization. This investigation thus explored the bubble formation process including the influences of inlet gas pressure along with driving voltage and resonance frequency on the formed bubble extent.

Keywords: Micro-bubble, nozzle, oxygenator, piezoelectric.

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159 Visualization of Latent Sweat Fingerprints Deposit on Paper by Infrared Radiation and Blue Light

Authors: Xiaochun Huang, Xuejun Zhao, Yun Zou, Feiyu Yang, Wenbin Liu, Nan Deng, Ming Zhang, Nengbin Cai

Abstract:

A simple device termed infrared radiation (IR) was developed for rapid visualization of sweat fingerprints deposit on paper with blue light (450 nm, 11 W). In this approach, IR serves as the pretreatment device before the sweat fingerprints was illuminated by blue light. An annular blue light source was adopted for visualizing latent sweat fingerprints. Sample fingerprints were examined under various conditions after deposition, and experimental results indicate that the recovery rate of the latent sweat fingerprints is in the range of 50%-100% without chemical treatments. A mechanism for the observed visibility is proposed based on transportation and re-impregnation of fluorescer in paper at the region of water. And further exploratory experimental results gave the full support to the visible mechanism. Therefore, such a method as IR-pretreated in detecting latent fingerprints may be better for examination in the case where biological information of samples is needed for consequent testing.

Keywords: Forensic science, visualization, infrared radiation, blue light, latent sweat fingerprints, detection.

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158 User Intention Generation with Large Language Models Using Chain-of-Thought Prompting

Authors: Gangmin Li, Fan Yang

Abstract:

Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behavior data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: Personalized recommendation, generative user modeling, user intention identification, large language models, chain-of-thought prompting.

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