Reviewerly/exHarmony huggingface dataset:
Research on Short-Term Scheduling Strategy of Water-Landscape Multi-Energy Complementary System Based on Particle Swarm Algorithm

Wind power, photovoltaic and hydropower (referred to as scenery and water) complementary power generation system is an important innovative mode to improve the overall efficiency of clean energy utilization. With the vigorous development of clean energy, how to solve the problem of flexibility demand brought by the large-scale grid connection of new energy has become the core and difficult point in the research and development of multi-energy complementary system. In this paper, we firstly consider the uncertainty of scenery output and use regression analysis to predict the scenery output; secondly, we make use of the good regulation performance of hydropower units to smooth out the uncertainty of scenery output and propose a short-term scheduling model based on adaptive variational particle swarm optimization algorithm to efficiently and accurately define the output size of hydropower units. The development of short-term optimal dispatching strategy will help promote the healthy development of clean energy in China.
New linear codes derived from skew generalized quasi-cyclic codes of any length

This article studies skew generalized quasi-cyclic codes (SGQC-codes) over finite fields for any length n. We derive generator polynomials and cardinality of SGQC codes. Moreover, we show that the dual of any length SGQC-code is also an SGQC-code. Our search results lead to the construction of fifteen new 2-generator SGQC codes over the finite field F4 with minimum distances exceeding the minimum distances of the previously best known F4-linear codes with comparable parameters.
Distance learning for Indonesian Mathematics Students with Hearing Impairments in Pandemic Situation: A Case Study

The purpose of this study was to identify the distance learning process of deaf students during the pandemic. This research is qualitative research with a case study approach. The subjects of this study were mathematics teachers, deaf students, and stakeholders. The research was carried out at the SLBN Kota Magelang and SLB-B YPPALB Magelang . Data collection techniques in this study were carried out by questionnaires, interviews, and document studies. The main instrument in this study was the researcher, while the auxiliary instruments were questionnaires and interview guidelines. The validity used in this research is source triangulation. The results showed that the mathematics distance learning process for deaf students could be implemented in various ways and could be adapted to school conditions and student conditions. Distance learning can be done with the help of media in hand-out modules taken at school before the mathematics learning schedule is implemented. In addition, the distance learning process on the mathematics topic of deaf students can also be carried out through learning videos with additional translated texts. Deaf students can simultaneously watch videos and read explanations from math teachers.
Study on Calculation of Lightning Intrusive Wave Overvoltage in 750kV AIS Distribution Swtichgear

Surge arrester are usually used in the substations to limit lightning overvoltage and protect equipment operation. According to the characteristics of 750kV substation system condition, single-line and layout of the substation, it is established by using electromagnetic transient calculation program-EMTP that the calculation model of lightning intrusion wave overvoltage of 750kV switchgear. By calculating the lightning overvoltage under different surge arrester configuration schem, the surge arrester configuration scheme which meets the equipment insulation requirements and has excellent economic effect is obtained. In 750kV substation, on the premise of setting a set of 600kV surge arrester in the main transformer circuit, it is proposed that 600kV surge arrester should be installed in the bus, main transformer and outgoing line circuit.
50 Years of translation structures

Abstract In this paper the term translation structure will denote any geometric object canonically constructed from an elementary abelian group. Hence, translation weak affine spaces, translation planes, linear sets, translation ovoids of polar spaces, translation generalized quadrangles and linear MRD-codes are examples of translation structures. I will present my personal excursus in the theory of finite translation structures, from the pioneering times of B. Segre, A. Barlotti and G. Tallini to these days. My aim is not to give a complete survey of the known results but to describe the influence of translation structures in proofs or disproofs of some conjectures in different areas of Finite Geometries and how valuable tool they were giving significant contributions in different areas of Discrete Mathematics.
Learning to Pronounce as Measuring Cross-Lingual Joint Orthography-Phonology Complexity

Machine learning models allow us to compare languages by showing how hard a task in each language might be to learn and perform well on. Following this line of investigation, we explore what makes a language “hard to pronounce” by modelling the task of grapheme-to-phoneme (g2p) transliteration. By training a character-level transformer model on this task across 22 languages and measuring the model’s proficiency against its grapheme and phoneme inventories, we show that certain characteristics emerge that separate easier and harder languages with respect to learning to pronounce. Namely the complexity of a language's pronunciation from its orthography is due to the expressive or simplicity of its grapheme-tophoneme mapping. Further discussion illustrates how future studies should consider relative data sparsity per language to design fairer cross-lingual comparison tasks.
Fuzzy Halpern and Shoham's interval temporal logics

The most representative interval temporal logic, called HS, was introduced by Halpern and Shoham in the nineties. Recently, HS has been proposed as a suitable formalism for modern artificial intelligence applications; however, when dealing with real-life data one is not always able to express temporal relations and propositional labels in a definite, crisp way. In this paper, following the seminal ideas of Fitting and Zadeh, we present a fuzzy generalization of HS, called FHS, that partially solves such problems of expressive power. We study FHS from both a theoretical and an application standpoint: first, we discuss its syntax, semantics, expressive power, and satisfiability problem; then, we define and solve the time series FHS finite model checking problem, to serve as the basis of future applications.
DeepGlobal: A framework for global robustness verification of feedforward neural networks

Feed forward neural networks (FNNs) have been deployed in a variety of domains, though achieving great success, also pose severe safety and reliability concerns. Existing adversarial attack generation and automatic verification techniques cannot formally verify a network globally, i.e., finding all adversarial dangerous regions (ADRs) of a network is out of their reach. To address this problem, we develop a global robustness verifiable FNN framework DeepGlobal with four components: 1) a rule-generator finding all potential boundaries of a network by logical reasoning; 2) a new network architecture Sliding Door Network (SDN) enabling rule generation in a feasible way; 3) a selector which selects real boundaries from the generated potential boundaries; 4) a filter finding ADRs with meaningful adversarial examples. The ADRs can be represented by the identified real boundaries. We demonstrate the effectiveness of our approach on both synthetic and real datasets.
MDFA: A New Multiple Dynamic Flip Algorithm for Mobile-based Apps Development

Mobile user is getting increase in number for various reasons. With these increase in trending, there’s a proportionate need to invent a faster and easier mechanism in developing the mobile application (apps). This paper presents the Multiple Dynamic Flip Algorithm (MDFA), a new algorithm in developing mobile-based applications that serves as the mobile apps framework. The algorithm developed allows the data to be stored in the database and the administration of the system can only change the data according to the categories of data that have been systematically arranged in the database. The modified custom data will continue to be updated through the mobile application that has been developed. This method allows changes to information and data to be done automatically without requiring users to run back to mobile- based programming. For information, usually the process of updating information needs to be generated back in mobile- based programming and needs to be uploaded back in the play store or apple store and users must download the application software back. By using this MDFA algorithm, the problem is no longer needed and can be solved more quickly. This MDFA has been tested in the development of two mobile-based applications, namely eMobile Anti-Drug Awareness for Agensi Anti Dadah Kebangsaan (AADK) and Bread on Mobile (BOM).
Low-Light Image Enhancement via Transformer-based Network

Low-light image enhancement (LLE) deals with problems that exist in images with insufficient lighting to improve visual quality. It is a challenging task in that it needs to consider not only brightness recovery but also complex issues like color distortion and noise. In order to address this difficult problem, we propose a residual learning method, unlike the previous method of learning the mapping relationship between low-light (LL) images and nature-light (NL) images. We also propose a novel transformer-based convolutional neural network that can perform illumination enhancement on LL images. The proposed network consists of several Back Projection blocks and several transformer blocks. The Back Projection blocks perform lightening and darkening processes iteratively to learn the residual for normal-light estimations. The transformer blocks can effectively enhance the ability of the network to learn spatial features. We compared our method with the current excellent LLE methods on the LOL dataset, and the experimental data showed that the method proposed in this paper is state of the art in PSNR, SSIM, NIQE matrics.
Design of English Guiding Resource Information Management Platform based on Random Search Algorithm: Java Framework Reconstruction

The system is based on B/S mode, using Java as the development language and SSM as the development framework; using RESTful style for API interface development; using random search algorithm as the design mode, MySQL as the background database. It analyzes the actual needs of teaching management in colleges and departments in the new era at this stage, and designs the cost function in the random search algorithm Bu-1-genetic algorithm and pattern search. Based on the analysis of the relationship between JavaEE and the Web, this paper proposes an English resource management system application framework that is hierarchical and allows expansion while adding Web technology ideas by using the cross-platform and cross-application characteristics of JavaEE.
A new improved projection algorithms of virtual reality panoramic video and application in physical education

SUMMARY Data storage and transmission have become the two biggest challenges it currently faces. In our study, we proposed an improved octahedral projection layout method. Performing an equivalent process on every patch to rework into an isosceles right‐angled triangle, combine into varied squares based on varied needs, and finally combine into a completely continuous interior and a facet magnitude relation of 2:1 flat parallelogram. Furthermore, the area‐preserving uniform projection method is also proposed. Moreover, applying virtual reality technology to Tai Chi teaching using research methods such as literature, expert interviews, questionnaires, teaching experiments, and mathematical statistics, the data of the basic physical quality test of the students in the experimental group and the control group were compared and analyzed to verify the scientific hypothesis that the VR technology could improve the teaching effect of Tai Chi. Results show that different from the compact layout of the initial octahedral projection, the approach proposed in our study has removed the inner discontinuous borderlines and possessed top boundary continuity. Students gain a good situational experience while deepening their understanding and memory of the details of Tai Chi movements, and the learning process is interesting and impressive.
Development of an Automated and Electronic Transport System

The Automated and Electronic Transport System for the Blind is a project developed with the use of new advancements in microcontroller and sensor technology applied in electronic-controlled vehicles. This study uses a Product Development Design wherein the researchers focused on developing an Automated and Electronic Transport System for the Blind which included designing the sub-systems responsible for the operation of the transport system and its physical appearance, determining the appropriate components and suitable materials for the transport system and evaluating its performance in terms of its functionality, and safety. It has an automated navigation system responsible for controlling the movement of the transport system from one station to another. The researchers incorporated object detection and automatic speed regulation for the safety of the passenger. The transport system was integrated with a manual operation controlled by a yoke for direction and speed, a pedal for the braking system, and switches for other peripherals. The transport system can operate at a maximum speed of ten kilometers per hour during its automated operation which matches the maximum speed of existing electric wheelchairs in the market. The prototype can carry a maximum weight capacity of one hundred kilograms (100 kg). The researchers gathered data in evaluating its performance in terms of its functionality and safety. It can be used by visually-impaired persons in schools, industrial plants, parks, other persons with disability.
Construction of developmental educational environment during the e-learning process in higher educational institution

The article reveals the essence of e-learning and its benefits, means of ensuring the effectiveness of e-learning. The aim of the article is to reveal the concept of "developmental educational environment", the essence and structure of the technology of building such an environment in the e-learning process. The following methods are used: theoretical analysis of scientific literature on a research topic, modeling, in order to describe the methods of constructing a situation of reflection, and implementation of exercises for joint activities in the educational process.&#x0D; The article reveals the concept of "developmental educational environment" as an electronic space in which the student transforms from a reader into an active seeker of new information. The examples of its use in various educational and (or) professional situations are presented. The technology of construction of such an environment in the process of e-learning is characterized, namely its components: conceptual, content, procedural and control-corrective. The process of presenting educational information, which is based on a certain concept (system of concepts) and its properties, in conditions of e-learning is presented. Psychological and pedagogical conditions of e-learning are presented, such as an implementation of free choice of learning trajectory by each student; problem-based learning; stimulation of intellectual activity; ensuring interaction with students. The general technique of construction of tasks for team work is presented, the characteristics of mental development of students in the process of work on such tasks are described. It is proven that the implementation of this technology in the educational process allows to bring up each student's desire for achievements in education and professional activities.
ARSearch: Searching for API Related Resources from Stack Overflow and GitHub

Stack Overflow and GitHub are two popular platforms containing API-related resources for developers to learn how to use APIs. The platforms are good sources for information about API such as code examples, usages, sentiment, bug reports, etc. However, it is difficult to collect the correct resources regarding a particular API due to the ambiguity of an API method name. An API method name mentioned in the text would only refer to one API, but the method name could match with different APIs. To help people in finding the correct resources for a particular API, we introduce ARSearch. ARSearch finds Stack Overflow threads that mention the particular API and their relevant code examples from GitHub. We demonstrate our tool by a video available at https://youtu.be/Rr-zTfUD_z0.
The Problem of Existence of Virtual Objects from the Philosophical Perspective

I consider the problem of existence of virtual objects, mainly their mode of existence, while omitting the issue of the criteria of their existence. I present and analyze the concepts of modes (forms, kinds) of existence of virtual objects proposed in the literature of the subject, and then I demonstrate my own position on the issue. My position on the existence of virtual objects has certain points coinciding with the already postulated views, but at the same time it differs from them in some basic aspects. In my view virtual objects are “born” in human individual consciousness as the objects of specific creative states of the mind. So initially they are private objects belonging to the individual subjective sphere. However, their final and ready forms emerge in complex processes of objectifying and autonomizing the respective private conscious states and their objects. In these processes the private objects are transformed into objects intersubjectively accessible and existing in the collective cultural sphere. In both their forms, initial and final, virtual objects are non-material entities: first subjective, then objective. The ontic status of virtual objects is very similar to the status of intangible ideas and all the non-material objects created by the human mind. The main difference consists in that virtual objects are expressed by the use computers programmes, while other non-material objects created by human beings are expressed by use of words, pictures, literature and art works, etc.
A hybrid feature selection technique using chi-square with genetic algorithm

A huge amount of information is available in different fields like information technology and computer science. A new hybrid feature selection technique via using chi-square with genetic algorithm (GA). An automatic text categorization mechanism was required to identify whether the text is going to a specific category or not. Thus, this technique is used to select the importance and unimportance features via developing the training model. For the existing GA-based, terms and documents are used together as features in the training model and obtain the perfect weights for the features. To evaluate the efficiency of document categorization techniques on the suggested approach, experiments results are conducted utilizing the Naïve Bayes (NB) and C4.5 decision tree classifiers based on two different datasets (BBC sport and BBC news datasets) collection for text categorization. From the empirical findings, it can observed that the hybrid technique can allow to obtain high categorization efficiency depend on the performance evaluation metrics accuracy, precision, recall and F1-score.
Research on person Re-ID based on joint attention mechanism

Re-ID is a technology to judge whether there is a specific pedestrian in the image or video. Attention mechanism is applied into Re-ID to optimize the feature representation and improve the discrimination characteristics of features. This paper studies the mechanism of Dual Joint Attention (DJA), which optimizes feature representation by paying attention to local important features and capturing global context in spatial domain and channel domain respectively. And use DJA to build a model. In the classification of the model, A-softmax is used as the loss function which clusters the features in the angle space by imposing the multiplicative angle interval constraint, so as to directly integrate the metric learning into the classification. Experiments show that mAP and Rank-1 are significantly improved.
Enabling Practical Cloud Performance Debugging with Unsupervised Learning

Abstract-Cloud applications are increasingly shifting from large monolithic services to complex graphs of loosely-coupled microservices. Despite their benefits, microservices are prone to cascading performance issues, and can lead to prolonged periods of degraded performance. We present Sage, a machine learning-driven root cause analysis system for interactive cloud microservices that is both accurate and practical. We show that Sage correctly identifies the root causes of performance issues across a diverse set of microservices and takes action to address them, leading to more predictable, performant, and efficient cloud systems.
Similar Neighborhood Search and Key-Point Clustering in Forgery Detection

The most frequent ways of tampering using digital photos is copy-move. In the detection of copy-move forgeries detection, key-point-based detection has been proven to be effective (CMFD). This work provides an efficient CMFD approach for locating tampered regions by cluster SIFT key-points and seeking related neighborhoods. The key-points are basis of scale and colour, aggregated into many smaller clusters, and matched independently in the suggested method, which reduces the high temporal complexity imposed by SIFT's over the high dimensional in matching. A unique localization approach is devised to analyze the comparable neighbors of matched pairs based on based on two similarity indices, then label the tampered areas into pixels iteratively so as to precisely find Pixel-level tampered regions. The manipulation of digital photographs via image processing is described in this article. The suggested method outperforms existing state-of-the-art techniques measured by in terms of forgery location accuracy, matching time complexity, detection reliability, and forgery detection reliability, the experimental results suggest.
Development of a Class Model for Creative Problem-Solving Using Coaching Techniques in Business

The purpose of this study is to develop a class model for creative problem-solving using coaching techniques. Regarding the research method, a draft of the class model was devised, and the final form was derived through expert verification. Concerning the final draft, the validity of the teaching model was verified by professors who were employed by companies that specialized in the teaching of creative problem solving and by experts with a doctorate in education. Unlike the draft instructional model, the final instructional model included the application of coaching techniques to each stage of the creative problem-solving model. Consequently, a model focusing on the creative problem-solving technique was developed. The class model for creative problem-solving developed in this study provides a class model to educate businesses to solve problems creatively. Therefore, I expect that the model can help teachers to introduce creative problem-solving education and to provide education that is more systematic.