• Electronic Materials Letters
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• v.14 no.6
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• pp.718-724
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• 2018

With the development of photovoltaic industry, the cost of photovoltaic power generation has become the significant issue. And the metallization process has decided the cost of original materials and photovoltaic efficiency of the solar cells. Nowadays, double printing process has been introduced instead of one-step printing process for front contact of polycrystalline silicon solar cells, which can effectively improve the photovoltaic conversion efficiency of silicon solar cells. Here, the relative cheap Cu paste has replaced the expensive Ag paste to form Ag/Cu composite front contact of silicon solar cells. The photovoltaic performance and the cost of photovoltaic power generation have been investigated. With the optimization on structure and height of Cu finger layer for Ag/Cu composite double-printed front contact, the silicon solar cells have exhibited a photovoltaic conversion efficiency of 18.41%, which has reduced 3.42 cent per Watt for the cost of photovoltaic power generation.

• Research in Mathematical Education
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• v.18 no.1
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• pp.41-54
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• 2014

This study investigated the visual-mental capability of pre-service and in-service mathematics teachers as well as academicians making a career change to mathematics teachers with regard to manipulations of two geometric shapes (from 2- to 3-dimensional). Moreover, it investigated whether there are differences between the visual-mental capability of these participant groups. Findings illustrate that most of the participants demonstrate an adequate visual capability relating to the task dealing with a cube. Conversely, very low percentage of participants manifested a visual-mental capability in a task requiring the identification of a solid resulting from rotation of a square page, whose diagonal serves as the rotation axis. The study indicates that learners' high visual view should be developed in order to enhance their visual-mental capability.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.3
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• pp.7-17
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• 2022

Media improvisation among lecturers in colleges is inevitable because of insufficient media resources for utilization. The study investigated media improvisation in the state -owned colleges of education in the South-West, Nigeria. The study is anchored on Media Richness Theory. Stratified sampling technique was adopted to select 812 lecturers. Media improvisation scale (r = .71) was used for data collection and T-test statistical method was adopted for data analysis. The result showed that there was no significant differences between media improvisation of Art/Social Science and Science lecturers (Crit - t = 1.96, Cal. t = 821, df = 278, p>.05) and that of lecturers in the School of Art/Social Sciences and Vocational/Technical Education (Crit. t = 1.96, Cal. t = .136, df = 276, p>.05). Significant difference did not exit between that of the Schools of Languages and Education (Crit. t = 1.96, Cal. t = 1.946, dif. = 288 p<.05) . It is recommended that media improvisation of lecturers in schools should be encouraged and improved upon.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.273-278
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• 2023

Aesthetic education in a variety of forms in the sublimation of the people's feelings, sublimation of the soul. It is of great significance to inherit and develop rural culture and to maintain cultural diversity. At present, rural characteristic industry is an important form of development to promote rural economic development, protect rural cultural diversity and continue rural culture. It is of great practical significance to guide the development direction of rural characteristic industry, strengthen the value connotation of rural characteristic industry and stimulate the endogenous power of rural characteristic industry. At the same time, it is of great significance to promote the development of aesthetic education and broaden the path of aesthetic education.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.62-71
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• 2024

The Study analyzed the effect of private education costs and housing prices on the total fertility rates in 16 metropolitan cities in Korea from 2009 to 2021, and estimated the contribution rates of each variable on the decrease in the total fertility rate. Using a dynamic panel data model considering the time series correlation of the total fertility rates, the total fertility rates for the year was positively (+) affected by the total fertility rates of the previous year, and the increase in apartment sales and Jeonse prices in the previous year reduced the total fertility rates. In addition, the increase in private education costs per capita in the previous year was analyzed to consistently reduce the total fertility rates.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.409-414
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• 2024

This paper utilizes artificial intelligence to analyze vocational training evaluation data for people with disabilities and selects the optimal prediction model using various machine learning algorithms. It predicts the job categories most likely to employ trainees based on data such as gender, age, education level, type of disability, and basic learning abilities. The goal is to design customized training programs based on these predictions to enhance training efficiency and employment success rates.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2179-2188
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• 2015

Recently, many researches have been done to solve the challenging problem of Blind Source Separation (BSS) problems in the underdetermined cases, and the “Two-step” method is widely used, which estimates the mixing matrix first and then extracts the sources. To estimate the mixing matrix, conventional algorithms such as Single-Source-Points (SSPs) detection only exploits the sparsity of original signals. This paper proposes a new underdetermined mixing matrix estimation method for time-delayed mixtures based on the receiver prior exploitation. The prior information is extracted from the specific structure of the complex-valued mixing matrix, which is used to derive a special criterion to determine the SSPs. Moreover, after selecting the SSPs, Agglomerative Hierarchical Clustering (AHC) is used to automaticly cluster, suppress, and estimate all the elements of mixing matrix. Finally, a convex-model based subspace method is applied for signal separation. Simulation results show that the proposed algorithm can estimate the mixing matrix and extract the original source signals with higher accuracy especially in low SNR environments, and does not need the number of sources before hand, which is more reliable in the real non-cooperative environment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.817-825
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• 2016

In this paper, we introduce a flexible gripper that we have engineered to precisely pinch in parallel and compliantly grasp objects. As found in most conventional industrial grippers, the parallel pinching property is essential for precise manipulation. On the other hand, the grippers with a flexible structure are more adept at grasping objects with arbitrary shapes and softness. To achieve these disparate properties, we introduce a flexible gripper mechanism composed of multiple flexible beam structures. Utilizing these beam structures, the proposed gripper is able to grasp arbitrarily shaped objects. Additionally, a unique combination of flexible beams enables the gripper to pinch objects using the parallel fingertips for enhanced precision. A detailed description of the proposed mechanism is provided, and an analysis of the strength and stiffness of the fingertip and finger body is presented. The Results section compares the theoretical and experimental analyses and verifies the properties and performance of the proposed gripper.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3204-3220
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• 2021

We perform the task of video object segmentation by incorporating a conditional random field (CRF) and convolutional neural networks (CNNs). Most methods employ a CRF to refine a coarse output from fully convolutional networks. Others treat the inference process of the CRF as a recurrent neural network and then combine CNNs and the CRF into an end-to-end model for video object segmentation. In contrast to these methods, we propose a novel higher-order CRF model to solve the problem of video object segmentation. Specifically, we use CNNs to establish a higher-order dependence among pixels, and this dependence can provide critical global information for a segmentation model to enhance the global consistency of segmentation. In general, the optimization of the higher-order energy is extremely difficult. To make the problem tractable, we decompose the higher-order energy into two parts by utilizing auxiliary variables and then solve it by using an iterative process. We conduct quantitative and qualitative analyses on multiple datasets, and the proposed method achieves competitive results.