Reviewerly/exHarmony huggingface dataset:
A Feedback Based Neural Branch Predictor for Branch Prediction

Branch predictors are very important in modern superscalar processor setups. They are responsible for determining the branch instructions that will run smoothly.This paper proposes a feedback neural branch predictor that is implemented in a neural network to improve processor performance. It is based on the concept of the perceptron branch predictor.This paper presents a feedback neural branch predictor that combines the multi-layer and single-layer branch predictor techniques.The proposed model is based on the feedback neural branch predictor method, which combines the multi-layer and single-layer techniques.In this paper, the multi-layer neural network has been studied to develop a neural branch predictor that can predict a misprediction event. When a prediction is made, the developed predictor can update the values of its neurons and weights.The proposed neural branch predictor can predict the weights and neurons of a given branch based on the observed misprediction. It can also update the weights and neurons when there's a misprediction. Thus by using the concept of the neural network in feedback neural branch predictor, the accuracy rate has increased to 97.10%.
“AI+ New Business” Teaching Reform of Integration of Production and Education

As the main direction of curriculum reform in the new era, AI-oriented teaching is an important foundation for realizing student employment and self-employment. Based on previous studies, this paper proposes an innovative teaching model that combines business courses and AI in a blended learning environment. The model includes three stages: enriching the construction of teaching content, focusing on the teaching process and evaluation, and innovating teaching methods. Relying on AI technology and combining online and offline teaching, the model is applied to practical teaching courses of business in private colleges and universities, to propose an ability-oriented teaching model that can effectively improve students' learning interest and participation.
A Kullback-Leibler Divergence-Based Locally Linear Embedding Method: A Novel Parametric Approach for Cluster Analysis

Numerous problems in machine learning require some type of dimensionality reduction. Unsupervised metric learning deals with the definition of intrinsic and adaptive distance functions of a dataset. Locally linear embedding (LLE) consists of a widely used manifold learning algorithm that applies dimensionality reduction to find a more compact and meaningful representation of the observed data through the capture of the local geometry of the patches. In order to overcome relevant limitations of the LLE approach, we introduce the LLE Kullback-Leibler (LLE-KL) method. Our objective with such a methodological modification is to increase the robustness of the LLE to the presence of noise or outliers in the data. The proposed method employs the KL divergence between patches of the KNN graph instead of the pointwise Euclidean metric. Our empirical results using several real-world datasets indicate that the proposed method delivers a superior clustering allocation compared to state-of-the-art methods of dimensionality reduction-based metric learning.
A SYSTEMATIC APPROACH TO THE MANAGEMENT OF AN EDUCATIONAL ORGANIZATION

The paper reveals the role and significance of the system approach in the management of an educational organization, describes its significance in solving issues of successful implementation of the pedagogical process, describes the features of the system approach in relation to the processes of management of the educational system, reveals the features and requirements of the system approach. The paper explores the possibilities of improving the development processes of an educational organization, highlights the main aspects of managerial activity in the logic of a systematic approach.
The Design of Web-Based Transaction Module in The Context of Implementing ERP in Procurement Company

Digital transformation is a continuous process of using new digital technology in the daily life of an organization or company, which includes the organization’s ability to adapt, respond, and position itself for success in the face of rapid technological evolution. This research uses a case study of a procurement company named PT. Tritunggal Powerindo Utama. The company is engaged in the water treatment plants and sewage treatment plants as well as a provider of various types of pumps and spare parts. This company still uses manual recording to document all transactions, which results in some problems such as lost documents and inaccurate reports. Based on these problems, a system will be developed in order to implement an ERP system that can automate the recording of transactions so that business processes can run smoothly. This system was developed using the agile method, because the agile method prioritizes cooperation between users and developer and is able to complete the system quickly and consistently. The system built in this research, can ultimately help companies to run their business processes more effectively because the data is integrated, monitoring can be done in real time, and reports can be made more easily.
Cabin topology modeling and its application research under damage control scenario

Cabin topological structure has great influence on the organization and implementation of damage control action, based on the Graph Theory, the cabin topology structure was established, and the algorithm design of four command elements under damage control scenario was realized, namely, the setting of protection boundary, the division of damage control zoning and the planning of damage control support path. The case analysis verified feasibility and reliability of the related algorithm. This study can improve the effectiveness of damage control command under the existing cabin layout and provides a new idea for the optimal design of cabin topology.
Metamorphism – the invisible life of the rocks

Three types of metamorphism are developed on the metamorphic complexes of the Rhodope Massif: a, widespread regional; b, high thermobaric in shear zones of friction and c, metasomatism, each with its own thermodynamic system. Friction generates energy that deforms, disintegrates and destroys minerals, subsequently recrystallized into new rocks.
Formation of tolerance to other cultures as a component of professional training of future managers for intercultural interaction in content and language integrated learning

Today, in connection with the aggravation of the international situation, teaching tolerance is of particular relevance. Currently, there is a contradiction between the tendencies towards globalization and the isolation of cultures, therefore, the problem of establishing intercultural ties and building an equal dialogue of cultures is acute. The aim of the research is to analyze the role of developing tolerance towards other cultures in preparation for intercultural interaction. In the research the author uses the method of analysis of scientific literature and diagnostic techniques. As a result of the experiment, the positive influence of the development of tolerance to other cultures on the preparation for intercultural interaction has been revealed. Thus, we can draw key conclusions that: preparation for intercultural interaction helps to overcome psychological barriers in learning a foreign language, promotes the disclosure of the student's personality, creates a healthy atmosphere in the student community and stimulates further learning; tolerance education should be more widely applied in educational institutions of various levels as the prevention of extremism in a tense intercultural environment.
Calculating method for circular interference fringe of Mach-Zehnder optical system

Optical interferometry technology is one of the most accurate and effective detection methods. For the refractive index distribution measurement of G-Lens, we propose a method to calculate the order of circular interference fringes produced by a Mach-Zehnder interference optical system. This method is not only limited to the refractive index measurement, but also suitable for applications which is measured via interference method. For example, the surface error measurement of optical components. Several specific works had been performed such as effective area masking, image preprocessing, fringe center relocation, central-radiation fringe fractional-level calculation and fitting of circular optical interference fringe images. Furthermore, the two-dimensional distribution of cross-sections and three-dimensional of fringe orders are also obtained. In addition, we propose a new primary and secondary location method for the gray value peaks and valleys of noisy interference fringes, and on the basis of this location, the relative gray fringe fractional-level calculation is performed, which effectively avoids uneven illumination, noise, and the influence of unfavorable factors such as poor circularity and over-density of large-order fringes on the fringe calculation. For the work content of G-Lens refractive index distribution measurement, the algorithm has good repeatability accuracy, and the specific value is about 0.3‰.
Unconditionally Secure Relativistic Quantum Qubit Commitment

Quantum qubit commitment is a stronger version of the quantum bit commitment. It is impossible to realize unconditionally secure quantum qubit commitment in nonrelativistic domain. In this paper, we propose an unconditionally secure relativistic quantum qubit commitment protocol for the first time, which will have some unique applications in the upcoming era of quantum network.
Block Python as a transition stage in learning programming

Learning programming is an integral part of the school informatics course. The teachers often start to teach programming with the "childish" language Scratch, which, despite its simplicity, makes it possible to write not only the simplest program, but also quite complex programs that reflect the basic principles of programming such as variables, loops, branches, etc. Continuing learning programming pupils can use Python, which is one of the most popular programming languages. The article proposes an approach to implementing the continuity of programming learning in the transition from learning Scratch to learning Python, namely, using the capabilities of the online educational platform EduBlocks. EduBlocks is an easy way to go from block programming to text-based programming. The main part of EduBlocks is the visual block editor. After completing the construction of the program in this editor, you can go to the "regular" Python editor. Python code is displayed in blocks, so pupils learn Python syntax while coding in a familiar block-level environment.
Research on the Construction of English Translation Corpus Based on Network Electronic Technology

The corpus is different from the electronic document. The construction of the corpus has a specific research purpose and specific use. Therefore, it strives to achieve a balance in the scope of corpus sampling and genre coverage. Corpus alignment is an important part of the construction of translation corpus. It refers to the establishment of correspondence between different language units of two or more language texts, that is, determining which language unit of the source language text and which language unit of the target language text are mutual translation relationship. The corpus alignment technology that this paper focuses on, based on the GIZA++ word alignment tool, designs a word alignment process based on dictionary fuzzy matching, and proposes strategies for online and offline English translation teaching models to shape college students' cultural confidence, so as to truly play the role of translation corpus.
Projective robustness for quantum channels and measurements and their operational significance

Abstract Recently, the projective robustness of quantum states was introduced in (Regula 2022 Phys. Rev. Lett. 128 110505). This demonstrates that the projective robustness is a useful resource monotone and can comprehensively characterize the capabilities and limitations of probabilistic protocols that manipulate quantum resources deterministically. In this paper, we will extend the projective robustness to any convex resource theory of quantum channels and measurements. First, we introduce the projective robustness of quantum channels and prove that it satisfies some good properties, especially sub-multiplicativity under any free quantum process. Moreover, we show that the projective robustness of channels quantifies the maximal advantage that a given channel outperforms all free channels in the simultaneous discrimination and exclusion of a fixed-state ensemble. Second, we define the projective robustness of quantum measurements and prove that it exactly quantifies the maximal advantage that a given measurement outperforms all free measurements in the simultaneous discrimination and exclusion of two fixed-state ensembles. Finally, within a specific channel resource setting based on measurement incompatibility, we show that the projective robustness of quantum channels coincides with the projective robustness of measurement incompatibility.
A study of extreme learning machine on small sample-sized classification problems

Abstract Extreme learning machine (ELM) is a special type of single hidden layer feedforward neural network that emphasizes training speed and optimal generalization. The ELM model proposes that the weights of hidden neurons need not be tuned, and the weights of output neurons can be calculated by finding the Moore-Penrose generalized inverse method. Thus, the ELM classifier is suitable to use in a homogeneous ensemble model due to the untuned random hidden weights which promote diversity even with the same training data. This paper studies the effectiveness of the ELM ensemble models in solving small sample-sized classification problems. The research involves two variants of the ensemble model: the normal ELM ensemble with majority voting (ELE), and the random subspace method (RS-ELM). To simulate the small sample cases, only 30% of the total data will be used as the training data. Experiment results show that the RS-ELM model can outperform a multi-layer perceptron (MLP) model under the assumptions of a Friedman test. Furthermore, the ELE model has similar performance as an MLP model under the same assumptions.
A Planning Method of Technical Standard Revision for Renewable Energy Generation Integration to Power Grids

Perfecting technical standards for renewable energy generation integration to a power grid and improving the planning of standard development and revision, can not only provide power grid companies with technical support for secure dispatching as well as avoiding abandonment of wind and solar energy generation, but also assist decision-making for grid companies to actively participate in the development and revision of technical standards concerning renewable energy generation integration. Given this background, this paper proposes a planning method for developing and revising technical standards for renewable energy generation integration into the power grid based on the well-established analytic hierarchy process (AHP). First, the missing standards are identified by establishing a framework of the standard system. Then, an AHP model is presented, and domain experts are invited to conduct group decision-making and scoring. Comparison matrices are constructed and consistency tests are carried out to determine the weight of each criterion as well as the score of each candidate standard. Next, the score of each candidate and annual revision capability are comprehensively considered, and the annual plan and roadmap of standard revision are formulated. Finally, an example is employed to demonstrate the proposed method.
Design of Speech Device Software using Optical Character Recognition Method

The purpose of this paper is to perform Optical Character Recognition and convert that recognized data (text) to speech. Optical Character Recognition is used to detect information from natural images and transfer them into words, symbols, and numbers. Known as computer vision, this is a sub-field of image processing that deals with the "sight and recognition" by a machine. It is a field of research in pattern recognition, artificial intelligence, and machine learning. Text-to-Speech (TTS) is a type of assistive technology that reads digital text aloud. The recent progress of text-to-speech synthesis (TTS) technology has allowed computers to read any written text aloud with a voice that is artificial but almost indistinguishable from real human speech. The Text- to – Speech software enables us to convert the recognized text into the computer-generated simulation of human speech audio. Implementing this software will be of use to several applications beyond just aiding visually challenged but can be used to convert physical documents to word or pdf documents. This can be used to assist virtual teaching, training, or learning for students in various environments.
Research on filling algorithm of incomplete data in north interface of optical fiber network

Northbound interface is the interface for manufacturers or operators to access and manage the network. Through it, the superior network management can obtain a large number of data such as configuration performance and operation and maintenance of optical network. For various reasons, there are usually missing values in real data sets. In order to improve the accuracy of filling missing values. In this paper, from the perspective of data mining, we use a variety of processing methods to fill the missing value of the north interface. In this paper, by analyzing the principle of KNN algorithm, decision tree algorithm, random forest algorithm and extreme random tree algorithm, the four algorithms are simulated in the missing value processing of northbound interface data respectively. The performance differences of various algorithms are compared and analyzed, and their advantages and disadvantages are compared. Finally, the most suitable algorithm for missing value processing of northbound interface data is found. Based on the simulation and experimental results, it is concluded that the extreme random tree algorithm has better filling effect in dealing with the missing values of the north interface.
An iterative feature selection procedure for a classification problem based on the method of logical analysis of data

Abstract An iterative procedure for selecting features for classifying observations is proposed. The main principles of the proposed iterative procedure are ranking and selection of features according to the frequency of their use when constructing logical patterns based on the method of logical analysis of data. The empirical confirmation of the expediency of this procedure is given.
Visual Sums of Integers in Polygonal Arrays

SummaryWe provide visual proofs about the sums of entries in odd-indexed polygonal arrays generalizing the classic visual proof about sums of odd numbers.
Research on the Construction of Computer Network Culture in Colleges and Universities Based on New Media Environment

The 21st century is a highly informationized era. Computer network has penetrated into all areas of people's lives and brought an unprecedented revolution to the way of cultural transmission. The development and popularization of computer network has had a profound impact on college students. Compared with traditional culture, network culture, as an information culture based on Internet, has some characteristics that traditional culture can't match. The combination of campus culture and computer network, so that students can more easily contact the campus culture through the computer network, at the same time, the correct, appropriate and timely use of computer network is a problem faced by our educators. This paper discusses the construction of campus culture under the new media environment of computer network. It is of great significance and value for the spread and development of campus culture and for college students to be more active in understanding, contacting and being influenced by good campus culture.
Separation logic and logics with team semantics

Separation logic is a successful logical system for formal reasoning about programs that mutate their data structures. Team semantics, on the other side, is the basis of modern logics of dependence and independence. Separation logic and team semantics have been introduced with quite different motivations, and are investigated by research communities with rather different backgrounds and objectives. Nevertheless, there are obvious similarities between these formalisms. Both separation logic and logics with team semantics involve the manipulation of second-order objects, such as heaps and teams, by first-order syntax without reference to second-order variables. Moreover, these semantical objects are closely related; it is for instance obvious that a heap can be seen as a team, and the separating conjunction of separation logic is (essentially) the same as the team-semantical disjunction. Based on such similarities, the possible connections between separation logic and team semantics have been raised as a question at several occasions, and lead to informal discussions between these research communities. The objective of this paper is to make this connection precise, and to study its potential but also its obstacles and limitations.