Reviewerly/exHarmony huggingface dataset:
Modified ELM-RBF with Finite Perception for Multi-label Classification

An improved multi-label classification algorithm based on ELM-RBF (Extreme Learning Machine for RBF Networks) is proposed in this article. On the one hand, different clustering analyses are applied to improve the stability of ELM-RBF model; on the other hand, a finite perception method is presented so as to keep the main feature, randomness, of ELM models in a reasonable degree. The main advantage of this F-ELM-RBF (ELM-RBF with Finite Perception) model is an adaptive ability to determine label thresholds which can distinguish the relevant labels from irrelevant labels more scientifically. Statistical experiments show that this algorithm has a good performance on different data sets.
Obstacle Avoidance Based on 2D-Lidar in Unknown Environment

This paper present a new obstacle avoidance algorithm based on 2D-lidar. The algorithm is applied to the problem of reactive navigation for onmi-directional mobile robots in the face of concave obstacles. Two-layer structures are involved in the proposed algorithm. The first layer aims at determining the current exit point. In the second layer, a basic planner is adopted, steering the robot move to the current exit. The core idea of the algorithm is to determine the exit point at each time step. To verify the effectiveness of the proposed algorithm, numerical simulations are presented. The algorithm is compared with potential field method. Results show that the proposed algorithm has good performance especially facing with concave obstacles.
Application Research on Information System Security Situational Awareness

Aiming at the problem of high complexity of situational awareness model in which the different test levels, control points and requirements are correlated with each other in the network security level protection test, an improved convolutional neural network security situational awareness method based on one-hot is proposed. Combining the advantages of feature selection of prior selection and posterior selection, the correlation prediction based on multiple different levels and different observation index points is realized. The experimental results show that the proposed method significantly improves the correlation discovery of different parameters between multiple levels, and reduces the classification prediction time. The accuracy of situational awareness is higher than that of deep learning based on feature data.
Employee Enrollment Decision Support System Using Analytical Hierarchy Process and Promethee Methods

Perseroan Terbatas (PT) Sumber Berkat Anugerah is one of the companies engaged in spare parts, vehicle accessories, home audio, and others. The stages of prospective employees’ enrollment in this company are still done manually, which causes many problems, such as the long processing time for the selection and the occurrence of human error during data saving. Based on the problems that occur, the Human Resources Department (HRD) wants a decision support system for new employees’ enrollment, which is expected to solve the problems that occur and produce a better and more accurate calculation result. This system was designed and built using the Analytical Hierarchy Process (AHP) method, which has advantage in determining priority weights and Promethee method that has advantage in the alternative rating process. The result of this system is the prospective employees ranking sorted from the highest to the lowest. The system has been built and tested by comparing the manual calculation results with the calculation results generated by the system. Usability testing on the system was done using the Usefulness, Satisfaction, and Ease of use (USE) Questionnaire and it can be concluded that the results of overall system user satisfaction have reached 85.2%.
CLASSIFICATION OF MAMMOGRAM IMAGES

Breast cancer is the most dangerous and incurable disease for women. Detecting breast cancer in early stages may increase the women life span. But it is not easy to identify the microcalcification in mammogram images because of its tiny size. In this paper, an author attempted to classify the mammogram images into cancer and non-cancer images by extracting low-level features. The extracted features are classified by a neural network and the SVM classifier. The neural network and the SVM classifier are trained by 150 images and tested by 50 images. The neural network accuracy is based on the mean square error and the regression analysis of the network. If the mean square error and the regression of the neural network attain low-value means, the accuracy of the network is high. Similarly, precision and recall are responsible for the SVM classifier. The database used here is the MIAS database.
A Mobile Visual Capture Robot Based on the Optimized Adaptive Iterative Training Algorithm

As artificial intelligence and visual recognition are advancing rapidly, visual recognition has been extensively used in commercial and industrial fields. However, industrial robots usually face some limitations (e.g. only identifying and capturing a certain area, and the grasping error is large). The current research results are mainly used to improve the recognition accuracy, but the grasp accuracy is largely ignored. To reduce the limitations of the existing industrial robots, reduce the grasp error, a mobile grasping robot based on visual recognition (e.g. color and shape) was independently designed in this study. The robot identifies the environment in a plan view using the OPENMV image sensor, and it calculates the optimal course of action using the path planning algorithm to optimize the overall capture efficiency. On that basis, a mathematical model of the three-dimensional position of a single ball is built, the angle of rotation of each joint of the mechanical arm is inversely deduced. And then, the overall pose state parameter of the mechanical arm is obtained through the positive solution of the D-H parameter method. Finally, the above-mentioned processed data is transferred to the host computer using the serial communication protocol, with the robot arm to grab one by one. Based on the prior art, adaptive iterative training learning is introduced in the process of grasping. The results of tests suggest that the grasping error of robot is greatly reduced to less than 1%.
Hardware Implementation of Sun Tracking Solar Panel Using 8051 Micro-Controller

The Solar Panel consists of a number of solar cells If the solar panel is continuously aligned with Sun rotation, In this paper, a solar tracking hardware implementation is offered to the Sun's movement throughout the day. The affordable solar panel design is based on 8051 micro-controller, dc motor and light sensor aligned in a simple circuit. The main goal is to get the current solar panel output.The output of the proposed solar tracking panel is found to be 32.17%higher as compared to the static Flat solar panel.
Multi-variance Performance Constrained Robust Fuzzy Control for Fuzzy Model-Based Discrete-time Stochastic Systems

In this paper, the multiple performance problems including the stochastic behaviors, perturbations, and transient behaviors of time response are considered for the discrete-time nonlinear systems. Based on the Takagi-Sugeno fuzzy model, a robust fuzzy controller design method is proposed to achieve the requirements of the above performances. Firstly, the covariance control theory is applied to achieve stability and also suppress the energy of the system under the effects of stochastic behaviors. Secondly, the robust control theory is applied to deal with the perturbations in the system state and input. Thirdly, the pole placement theory is applied to obtain better transient behaviors by locating the closed-loop poles in the given region. Moreover, all the theories are combined into each other such that the multiple performance requirements can be satisfied, simultaneously. To verify the proposed robust fuzzy controller design method, a numerical example for the control of a nonlinear discrete-time stochastic system is provided.
Historical Record Organization and Compilation of the Joseon History in the Japanese Imperialism

이 글은 일제가 1906년 통감부를 설치한 이후부터 1938년 조선사편수회를 설치하여 고도서와 역사 사료를 정리하여 『조선사』 (35권)을 편찬하기까지 과정을 다룬 연구이다. 일제는 1906년 통감부를 설치하면서 조선의 내정을 간섭해왔고, 규장각을 장악해가면서 조선의 역사자료를 정리하였다. 규장각에 보존하고 있었던 왕실 사료뿐 아니라 전국의 사고에 있던 『조선왕조실록』 등 주요 기록을 이관하면서 조선의 상황을 파악하고자 한 것이다. 일제는 1910년에 조선을 병탄한 후에 특별히 취조국과 참사관실을 설치하여 통감부 시기의 사료 정리를 이어받아 조선의 규장각에서 소장하고 있었던 고도서와 고문헌을 정리하고, 역사 자료를 정리하였다. 일제는 1915년에는 중추원에서 ‘조선반도사 편찬사업’을 시작하였다. ‘조선반도사 편찬사업’은 조선인 동화를 목표로 출범하였다. 1915년 7월부터 1918년 12월까지 3년간 실시하기로 결정하였다. 당시 중추원 서기관이었던 오다 간지로(小田幹治郞)이 사업을 총괄하였으며, 중추원에 참여하고 있었던 조선인들이 동원되었다. ‘조선반도사 편찬사업’은 자료 수집이 지연되어 사업기한이 연장되다가, 1919년 3.1운동 등 당시의 시대적 변화 속에서 완결되지 못하였다. 1922년 12월에 ‘조선사편찬위원회규정’이 공포되고 ‘조선사편찬위원회’가 조직되면서 새롭게 역사편찬이 시작되었다. 그 편찬위원회는 1925년 6월 ‘조선사편수회’로 상설화되면서 조선사 편찬 작업은 탄력을 받게 되었다. ‘조선사편수회’에서 핵심적 역할을 담당한 인물은 쿠로이타 가쓰미(黑板勝美)였다. 『조선사』 편찬은 1932년 3월 첫 권을 발간한 이래 1938년 3월 마지막 35권을 간행하면서 완결되었다.This article deals with the process from the establishment of the Japanese Resident-General in 1906 to the compilation of the Joseon History (35 volumes) by organizing ancient books and historical materials in 1938. In 1906, the Japanese colonial government established the Japanese Resident-General and intervened in the internal affairs of Joseon. Also, Japanese Resident-General took control of the Kyujanggak to organize historical data of Joseon. The Japanese colonial government wanted to understand the situation of Joseon by transferring key records, including royal historical records that were preserved at Kyujanggak and “True Record of the Joseon Dynasty that were preserved at several libraries. After annexation treaty in 1910, the Japanese established a bureau of inquiry(取調局) and a councilor s office(參事官室) to collect historical records from Japanese Resident-General. They summarized ancient books and ancient texts that were held by Kyujanggak of the Joseon Dynasty, and put together. In 1915, Japan started Joseon Peninsula History Compilation Project in Jungchuwon. The Joseon Peninsula History Compilation Project was launched with the aim of assimilating Joseon people. It was decided to run for three years from July 1915 to December 1918. Kanji Odaro(小田幹治郞), then a secretary of the Central Committee, was in charge of the project, and Joseon people who were participating in the Jungchuwon were mobilized. However, Joseon Peninsula History Compilation Project was delayed due to a delay in data collection, and was not completed amid the changes of the times, such as the March 1st Movement in 1919. In December 1922, the Rule of Compilation Committee of Joseon History(朝鮮史編纂委員會規定) was promulgated and the Compilation Committee of Joseon History(朝鮮史編纂委員會) was organized. The Compilation Committee gained power when the Compliation Organization of Joseon History(朝鮮史編修會) was established in June 1925. Kuroita Gasumi(黑板勝美) played a key role in the Compliation Organization of Joseon History. The compilation of Joseon History started publish in March 1932, and was completed in March 1938, when the last 35 volumes were published.
Research on Combination and Optimization of Path Planning Algorithm Based on Bridge Crane

The path planning of bridge crane is affected by multiple factors (crane spreader size, cargo size, obstacles, frequent braking of cart and trolley), so it is not simple to carry out traditional path planning, regardless of safety and practical operability. In the paper, a visual sensor equipped with a panoramic camera is used to collect environmental information of the work area to create an environmental map, which provides guarantee for subsequent path planning. The unit decomposition method is used to divide the whole environment map into several sub-regions to generate fuzzy paths, and then the grid method is used to generate a plane grid map based on the unit decomposition method to decompose several sub-areas. The above steps lay the foundation for the subsequent improved A* algorithm to search for a specific path. By combining the three methods of unit decomposition method, grid method and improved A* algorithm to make best use of the advantages and bypass the disadvantages. Thereby better achieving the effect of path planning.
Exploring the Development Path of Informatization Innovation of University Education Management

Under the background of the continuous innovation and research and development of various emerging technologies, many universities have gradually strengthened the construction of information management systems for education management. This paper will briefly describe the informationization of college education management, and put forward the current informationization of education management in colleges and universities, and propose a new path for the development of education management information innovation in colleges and universities.
FPGA Implementation of Modified Swarm Optimization Based Control Strategy for a Mobile Robot

In this paper the auto control strategy for a mobile robot is provided with the novel algorithm of modified particle swarm optimization algorithm (MPSO). Original taken image is preprocessed and then the features are extracted. The preprocessing involves the two important characters of resizing and RGB to gray conversion for getting the gray level image and avoid the colour image. Then the modified sobel edge detection algorithm is used to show the lines, and curves. After detecting the edges, filters are used to remove the unwanted noise. The simulation is done in MATLAB and Xilinx environment. The power, frequency, delays, and the logic utilization is measured. Then the result is compared with existing particle swarm optimization.
Research on Novel Method of the Branch Series Resonance Recognize

For the identification of series resonance in power system branches, the identification method of branch series resonance based on port equivalent method is proposed. First of all, a typical three–bus test system is used to analyze the series resonance of the branch. It is found that the branch series resonance can be identified by the port equivalent admittance formed between the bus node and the reference node. Then, by establishing the node port association matrix and using the node impedance matrix, the multi-port Theven in equivalent impedance matrix is obtained, then the equivalent admittance matrix of the port is formed, and the load branch of the node is eliminated, as well as the effect of the node load branch on the series resonance of the identification branch is eliminated. The algorithm effectively utilizes the node admittance matrix commonly used in power system. Finally, the feasibility and correctness of the three-bus system and IEEE9 network system are proved by simulation analysis. The validity of this novel formulation is confirmed through theoretical analysis and case studies.
DEVELOPMENT OF INTERACTIVE MULTIMEDIA BASED CHILDREN'S WORK SHEET (LKA) IN LEARNING AND READING IN CHILDREN OF 5-6 YEARS

Abstract Interactive learning is multimedia-based learning by combining and synergizing all media consisting of text, photos, videos, animation, and programmed music. Interactive multimedia-based learning in children aged 5-6 years can foster children's learning interest and motivation. the problem raised in this study is that the teacher's lack of knowledge of technology and teachers is not following the development of science and technology in the development of learning media, so that the learning activities carried out are not optimal. Like LKA teachers have not used a specific learning strategy to create fun and meaningful learning. One of the innovations that can help in overcoming the above problems is the development of interactive multimedia-based LKA. Interactive LKA is the right medium to develop listening and reading skills in early childhood. Listening skills will be the basis for developing other language skills, listening is important before having the skills to speak, read and write Reading skills can improve children's knowledge, by reading children will get information. Through the LKA it is expected that students will desire to learn and be actively involved in listening and reading skills so that the learning process is carried out well and the expected goals are achieved. Key words: LKA Interactive Multimedia Reading, Listening and Reading
Dual Homed Networks Policy

The purpose of this policy is to minimize the potential exposure to the University from unauthorized access to the University’s IT Resources
An Ui Design Optimization Strategy for General App in Big Data Environment

Due to the huge amount of increasing data, the requirements of people for electronic products such as mobile phones, tablets, and notebooks are constantly improving. The development and design of various software applications... | Find, read and cite all the research you need on Tech Science Press
Quantum Error Correction: Decoders for the Toric Code

Quantum error correction is needed for future quantum computers. Classical error correcting codes are not suitable for this due to the nature of quantum mechanics. Therefore, new codes need to be developed. A promising candidate is the toric code, a surface code, because of its locality and its high error correcting capability and thresholds (the error probability below which increasing the size of the code decreases the failure rate). This thesis provides an introduction to quantum error correction and the stabilizer formalism, which is used to introduce the toric code. Several decoders are looked at, including the Minimum Weight Perfect Matching (MWPM) decoder and a recently developed decoder, the Union-Find (UF) decoder. The UF decoder is useful because of its almost-linear time complexity, while only reducing the threshold by a marginal amount compared to the MWPM decoder. In this thesis, the time complexity of the weighted growth version of the UF decoder is analysed. The toric code and the decoders have been implemented and simulated, and the thresholds have been determined. For the MWPM decoder, the threshold was determined to be 11.5±0.2%, which is not in agreement with the threshold in literature of 10.3%, and should not be possible according to the optimal threshold of about 11%. This probably is a result of the low grid sizes (up to a gridsize of 11) of the code used due to the time needed to simulate the MWPM decoder. For the UF decoder, the threshold found was 9.7 ± 0.9%, which is in agreement with the threshold of 9.9% found by N. Delfosse and N. Nickerson. The time complexity of the UF decoder has also been determined, and is indeed almost-linear as expected by the analysis.
An Image Mosaic Algorithm Based on Improved ORB

Due to the lack of scale invariance in ORB (Oriented FAST and Rotated BRIEF) algorithm, image mosaic in complex scenes, high mismatch rate, and easy to produce mosaic seams in synthetic images, etc. In this paper, an improved ORB algorithm for image mosaic based on BRISK feature extraction is proposed. Firstly, the FAST9-16 of BRISK algorithm is introduced to detect corner points and solve the scale invariance problem. Then ORB algorithm is used to describe feature points, and Hamming distance is used to roughly match image features. Then KNN algorithm and PROSAC (Progressive Sample Consensus) algorithm are used to refine and purify the matching points to further improve the accuracy. Finally, image seamless fusion and mosaic are completed by gradual-in-gradual-out weighted average fusion. The experimental results show that the proposed algorithm has good performance in image scaling, rotation and illumination intensity. It is a real-time image mosaic method with high accuracy and good mosaic effect.
Dual Pattern Compression Using Data-Preprocessing for Large-Scale GPU Architectures

Graphics Processing Units (GPUs) have been widely accepted for diverse general purpose applications due to a massive degree of parallelism. The demand for large-scale GPUs processing a large volume of data with high throughput has been rising rapidly. However, in large-scale GPUs, a bandwidth-efficient network design is challenging. Compression techniques are a practical remedy to effectively increase network bandwidth by reducing data size transferred. We propose a new simple compression mechanism, Dual Pattern Compression (DPC), that compresses only two patterns with a very low latency. The simplicity of compression/decompression is achieved through data remapping and data-type-aware data preprocessing which exploits bit-level data redundancy. The data type is detected during runtime. We demonstrate that our compression scheme effectively mitigates the network congestion in a large-scale GPU. It achieves IPC improvement by 33% on average (up to 126%) across various benchmarks with average space savings ratios of 61% in integer, 46% (up to 72%) in floating-point and 23% (up to 57%) in character type benchmarks.
Fast Image Multi-style Transfer and Its Quality Assessment

Image style transfer based on deep learning is an image processing method, which uses deep convolutional neural networks (CNN) to yield artistic images with some specific styles by segregating and restructuring the styles and contents of images [1]. Considering that several drawbacks still exists in the neural style transfer, such as the intrinsic limitation of single style transfer and the time-consuming process of optimizing model. At this time, we could remedy aforesaid weaknesses by the means of making use of fast multi-style transfer and its image quality assessment (IQA). On one hand, it aims to solve the monotony of color and the loss of stereoscopy results from single style image. On the other hand, it evaluates the synthesized image quality in real time, and makes the feedback of IQA to model itself for modifying relevant parameters of the algorithm, providing reference for selecting appropriate time to stop iterating to save immediate model. In this paper, we present the improved approaches for image style transfer to obtain preferable visual effect and save significant time.
Development of computerized monitoring and control system of the mobile robot’s positioning on large ferromagnetic surfaces based on intelligent techniques. Thesis and study of the mathematical model of a caterpillar mobile robot for vertical movement

The article considers the synthesis and study of a mathematical model of a caterpillar mobile robot (MR) with separate main clamping magnets for moving and performing specified technological operations along inclined and vertical ferromagnetic surfaces. The authors have developed the mathematical models of MR's individual elements and the robot as a whole, taking into account the basic features of its structural design. The resulting mathematical model allows studying the MR’s behavior in different production conditions under spatial motion on an inclined surface and can be applied for further synthesis of the automatic control system for positioning such robots.
Requirements Complexity Ranking using Natural Language Processing and Complexity Class Correlation with Defect Severity

This paper addresses the risks to delivery schedule and product quality from non-periodic temporal detection of high severity defects in software projects. The non-periodicity in time and lack of a time boundary in detecting severe defects primarily stems from subjective scheduling of development and testing of product features. One solution is to objectively determine complexity and ranking of requirements to drive the project development and test sequence that uncovers high severity defects early in the life cycle phases. Requirements complexity is strongly correlated with defect severity as measurements show. Applying natural language processing, key words are identified in the given set of requirements, their weights measured to determine the complexity class distribution and ranking that drives the scheduling. The complexity and defect correlation-based sequencing mitigates the risks by discovery of high severity defects in a temporal saw tooth pattern providing the project team sufficient time to fix defects and mitigate the risks.