Reviewerly/exHarmony huggingface dataset:
Research on variable scale target tracking method based on multi feature fusion

Illumination, rotation, deformation and other problems have always been the main problems affecting the target tracking effect, especially when the scale changes in the process of target movement, the whole target frame will drift. In order to solve the problem of real-time accurate tracking when the size of the target fluctuates greatly, many problems exist at the same time. Based on KCF algorithm, LBP features are fused adaptively by using feature weighting method, and variable scale updating strategy is added. A variable scale tracking method under multi feature fusion is proposed. In this paper, video sequences from obt-50 and obt-100 datasets are selected for simulation experiments, and the proposed algorithm is compared with KCF algorithm. The position error is improved by 1%–2%, and the overlap accuracy is improved by 2%–3%, which verifies the robustness of the algorithm. When complex background, illumination, rotation, deformation and scale change appear in the process of target motion, the algorithm can solve the above problems.
Ways to Promote Students’ Deep Learning in English Teaching Based on Computer Technology

Abstract The current economic and social development is inseparable from computers. Computer technology has not only brought tremendous changes to all aspects of society, but also brought opportunities to the reform of our country’s education industry. Adding computer technology to the process of English teaching can effectively promote students’ deep learning. At the same time, this teaching model has already appeared in many schools in our country. This article explores the convenience brought about by the way that computer technology promotes students’ deep learning of English by using both teachers and students. This article first explains the application and research of computer technology in traditional English teaching, and analyzes the case of improving students’ classroom teaching and extracurricular collaboration by introducing computer technology and multimedia technology under computer technology. This research conducted a survey of 120 sophomore English majors and 38 English teachers in a language university. The survey method used questionnaire surveys, interview surveys and practice classroom methods to explore the reform of deep learning in English teaching. Under the path, students’ understanding of computer technology promotes English teaching. This article also explores the impact of computer technology on English teachers through a survey of English teachers, including the changes in their traditional teaching methods and teaching concepts, the challenges of practical teaching methods, and the repositioning of teacher-student relationships. The experimental results show that, the deep learning path that computer technology promotes English teaching has changed the traditional English teaching method and rebuilt a new English teaching concept. Its classroom is more practical and interactive, and it is also more conducive to the cultivation of students’ autonomous learning ability.
ANALYSIS OF FACTORS AFFECTING EFFECTIVE AND EFFICIENT ENGLISH LEARNING

Analysis of factors that influence effective English learning. The writing method uses the library research method. From thediscussion, it can be concluded that there are two types of learning theories that influence further learning theories, namely thetheory of behaviorism and cognitivism. Based on these two theories, language learning activities can be successful(successful) if carried out with experience accompanied by a stimulus so that it produces a response as well as being givenreinforcement (award). The award in question does not have to be in the form of objects. Meanwhile, based on the theory ofcognitivism, humans learn by themselves because they see and hear. Therefore, language learning activities must providemore examples as well as direct application (application) by students. There are four aspects of language skills that becomethe reference for language learning in schools, namely listening skills (listening), speaking skills, reading skills and writingskills.
Rely more or less, for better or for worse: Intertwining reliability and preferences

Abstract Dealing with preferences is a ubiquitous part of our daily lives, and thus, preference forms an integral part of our daily decision-making processes. If we consider preferences among groups of agents, deliberation often leads to changes in preferences of an agent, influenced by the opinions of others, depending on how reliable these agents are according to the agent under consideration. Sometimes, it also leads to changes in the opposite direction, i.e. reliability over agents gets updated depending on their preferences. There are various formal studies of preference change based on reliability and/or trust, but not the other way around—this work contributes to the formal study of the latter aspect, i.e. on reliability change based on agent preferences. In process, some policies of preference change based on agent reliabilities are also discussed. We introduce a novel formal study of the relevant changes in agent reliabilities in decision-making scenarios, which is an integral part of artificial intelligence studies in the current day. A two-dimensional hybrid language is proposed to describe such processes, and axiomatizations and decidability are discussed.
Calibrating Function Complexity in Enhancement Project for Improving Function Points Analysis Estimation

Producing a good software product on time and within budget, the initial software estimation takes a significant role. Reality has shown that most software fails because the initial software estimation is not correct. Many researchers have proposed methods for software estimation. It has been developed since the 70s of the last century, but it is still of great interest until now. We also know that creating a new software product is difficult; it is even more difficult to innovate. In the framework of this paper, we propose an improved method based on the FPA method of IFPUG. We named this proposed model is Calibrating Function Complexity in Enhancement Project (CFCEP). This method is based on the Linear Regression technique to give coefficients of function complexity. The experimental results based on the ISBSG dataset show that the estimation based on this new coefficient gives much better results than using the coefficients of the standard FPA method.
A FPGA-Based Heterogeneous Implementation of NTRUEncrypt

Nowadays, the lattice-based cryptography is believed to be thwarting future quantum computers. The NTRU (Nth-degree truncated polynomial ring unit) encryption algorithm, abbreviated as NTRUEncrypt, is belonging to the family of lattice-based public-key cryptosystems. Comparing to other asymmetric cryptosystems such as RSA and elliptic curve cryptography (ECC), the encryption and decryption operations of NTRU significantly rely on basic polynomial multiplication, which makes it faster compared to those alternatives. This paper proposes the first heterogeneous implementation of NTRUEncrypt on FPGA (Altera Stratix V) and CPU using OpenCL, which has shown that this kind of lattice-based cryptography lends itself excellently for parallelization and achieves high throughput as well as energy efficiency.
Pose Estimation of GIS Pipeline Based on Spatial Transformation Network

Abstract The manual flange structure alignment between GIS pipelines in the power system is inefficient and difficult to accurately align. To solve this problem, combined with the research results in the field of deep learning named spatial transformation network, a new pose estimation method based on single camera is proposed. In view of the high similarity between the moving flange and the static flange at the pixel level, the spatial transformation network is used to find the pixel mapping relationship of the two flange images. Thereby establishing the mapping relationship between the pixel coordinates of the two flange images and then using multiple points. In the perspective method, the pixel coordinates are mapped to the world coordinates to obtain the estimation of the position of the key point in the flange, and then the direction vector of the flange is calculated according to the position of the key point. Since there is a pixel coordinate transformation relationship between the static flange and the movable flange. Only the position of the key point in the static flange can be inversely solved by measuring the position of the key point in the static flange. Experiments show that, compared to the traditional method of measuring flange pose based on instrument measurement and linear regression, the method proposed in this paper can accurately measure the pose of the flange structure. And it can rely as little as possible on the measurement of the key points of the moving flange by the instrument.
PyDPLib: Python Differential Privacy Library for Private Medical Data Analytics

Pharmaceutical and medical technology companies accessing real-world medical data are not interested in personally identifiable data but rather in cohort data such as statistical aggregates, patterns, and trends. These companies cooperate with medical institutions that collect medical data and want to share it but they need to protect the privacy of individuals on the shared data. We present PyDPLib, a Python Differential Privacy library for private medical data analytics. We illustrate an application of differential privacy using PyDPLib in our platform for visualizing private statistics on a database of prostate cancer patients. Our experimental results show that PyDPLib allows creating statistical data plots without compromising patients’ privacy while preserving underlying data distributions. Even though PyDPLib has been developed to be used in our platform for reporting the radiological examinations and procedures, it is general enough to be used to provide differential privacy on data in any data analytics and visualization platform, service or application.
FairShare: For Allocation and Enforcing Bandwidth Guarantee in Cloud Datacenters

Virtual Data Centers (VDCs) are systems developed to host different network resources on behalf of tenants. VDCs can be rapidly adjusted as tenants' needs change but still faced challenges that system administrates often manage to resolve. One main challenge is bandwidth guarantee between tenants, which is caused by the lack of predictability and network congestion management. This challenge is also highly contributed by the default setting of best sharing effort, which led to network resources are not evenly shared. This paper introduces FairShare, a novel model for VDCs bandwidth guarantee and enforcement strategy for fair bandwidth allocation between virtual nodes in VDCs. The proposed model is designed to enhance VDC bandwidth allocation guaranteed virtual to physical mapping and enforce fair virtual resource allocation. We demonstrate that our approach achieves VDC performance improvement, seamless and even bandwidth distribution in VDC through simulation and evaluation.
The Impacts of Covid-19 Pandemic on French Language Testing: Delf/Dalf in Indonesia: Case Study

The covid-19 pandemic outbreak has globally affected various aspects of life, including teaching and learning processes. This paper aims to identify the changes in French language examinations conducted in Indonesia during the outbreak and explore the French language testing conditions, such as the worldwide standardized exams in the French language like DELF: Diploma in the French Language and DALF: Advanced Diploma in the French language. This study employs a descriptive qualitative method by collecting the data through observations, interviews with the French Language Institution and the parties involved in teaching and learning processes, and finally, through documentation. The online version of this test is inexistent. Therefore, the results should allow DELF/DALF examination providers to think about an alternative for an online examination. As shown by the findings on the IFI Indonesia website, it can be concluded that: (1) some examinations, including the French language tests, have been cancelled, (2) the number of test-takers has reduced, (3) the people who are in charge of language testing have made efforts to redress this issue to adapt to this situation.
Multimodal Discourse Analysis of Chinese Medicine Documentary Based on Elan and Face Feature Extraction Algorithm

Multimodal discourse analysis of Chinese medicine documentary based on the Elan and face feature extraction algorithm is conducted in this paper. The so-called intelligent video surveillance system is based on digital and networked video surveillance. But different from the general networked video surveillance, it is a higher-end video surveillance application. With this idea, the face analytic model is combined for the core systematic analysis. Therefore, this research work proposes the theoretical framework of inter-symbolic complementarity to explain the complementary relationship between images and texts in multimodal discourse. The Elan is combined for the Chinese medicine documentary analysis. The simulations are considered for performance estimation.
On the Capacity of Privacy-Preserving and Straggler-Robust Distributed Coded Computing

Distributed computing can well exploit the computation resources in edge and cloud for many applications of large-scale machine learning, which also raises concerns on data privacy and straggling effect. A promising method to address these issues is using codes. In our work, we design a general computation framework that incorporates multi-stage computing tasks with multiple inputs and can be expressed as a multi-variable arbitrary-degree polynomial function <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$f,$</tex> with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$N$</tex> distributed servers as workers, over a batch of data <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$D$</tex> that consists of data from different sources. We propose a privacy-preserving and straggler-robust coding scheme based on Lagrange polynomials, which can address up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$S$</tex> straggling workers and up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L$</tex> colluding workers. We prove the optimality of the proposed scheme in terms of downlink communication efficiency, defined as the amount of bits of desired results versus that of the downloading results, and obtain an explicit expression of the capacity: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$C= \frac{N-{S}-d(L-1)-1}{d(N-S)},$</tex> which is the supremum of downlink communication efficiency over all feasible encoding schemes, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$d$</tex> is the degree of function f.
The Kolmogorov–Chentsov Theorem and Sample Path Regularity

While constructions of probability distributions of stochastic processes indexed by uncountable parameter spaces, e.g., intervals, can be readily achieved via the Kolmogorov extension theorem, the regularity of the sample paths is not mathematically accessible in such constructions, for the simple reason that sample path properties that depend on uncountably many time points, e.g., continuity, do not define measurable events in the Kolmogorov model. In this chapter we consider a criterion, also due to Kolmogorov (Published in Slutsky (Giorn Ist Ital Attuari 8:183–199, 1937).) and to Chentsov (Chentsov (Theor Probab Appl 1:140–144, 1956)) for Hölder continuous versions of processes and random fields. In addition to providing a tool for construction of k-dimensional Brownian motion, it yields the construction of continuous random fields such as the Brownian sheet. The chapter concludes with a demonstration of nowhere differentiability of the (continuous) Brownian paths.
Real-Time Routing Plan Based on Modified Ant Colony Algorithm

In this paper, the situation of the real-time routing plan problems firstly is analyzed. In order to solve these problems, we propose a new optimization algorithm based on ant colony algorithm (modified ant colony algorithm, M-ACA) to optimize them. In M-ACA algorithm, the solution space is dispersed according to the minimum flight distance, and the judgment method of point’s validity in the basic ACA is changed. Simulation results show that modified ant colony algorithm (M-ACA) owns excellent and complete performance in solving real-time routing plan problems, and can quickly find out the feasible path, which can avoid all the threats, meanwhile, due to learning mechanism, updating mechanism and cooperative mechanism, M-ACA has strong search ability and stability.
Interpretable deep learning by disentangling features using modified Siamese network

In recent years, deep learning has entailed great progresses, but this success is seen as a triumph of empiricism. Despite the efforts made in the understanding of the deep models, the gap between the theoretical interpretability and the empirical success of deep models is still large. At present, the interpretability analysis of deep learning is mostly done after the training process. In this work, a novel method is proposed to extract interpretable features during the training process. Particularly, a modified Siamese network is used to disentangle features using a specially designed loss function. After a feature extractor, a fully connected layer is used to divide the output of the Siamese network into four different parts from which the new loss function is designed. The feature extractor used in the Siamese network may be different types of CNN. It is found that the proposed method can effectively disentangle the features at the semantic level, and the disentangled features can be used to effectively improve the classification accuracy in occluded face recognition.
Service Recommendation based on Smart Contract and DIKW

With the development of Internet technology, the number of Web services is growing rapidly, and various types of service recommendation systems emerge in a rapid stream. Although all major service recommendation systems show efficient data processing and service recommendation performance, most of the existing service recommendation systems are developed based on a centralized platform, with functions and data concentrated on a central server. There are still many problems with this over-centralized authority, such as data tamper, data leakage and so on. In response to the above problems, we designed and implemented a service recommendation system based on smart contracts and DIKW (Data, Information, Knowledge and Wisdom). The system data is stored in the blockchain, which effectively prevents data from being tampered. At the same time, the operating environment of the system is the decentralized environment of the Ethereum alliance chain, which overcomes the centralization drawbacks of the traditional service recommendation system and provides a new solution to the existing problems in the service recommendation domain.
Mobile Virtual Reality in Secondary Education: An Exploratory Study in the Course of Biology

The integration of Virtual Reality (VR) in education has shown positive results on learners' engagement and outcomes. Nonetheless, such studies are usually conducted in controlled laboratory environments which have been set up to provide optimal experiences. Even though the outcomes of these works provide useful insights, they also raise serious questions about their validity and applicability in the actual classroom context. Under this consideration, we performed an empirical study in which the potential of an affordable mobile-VR solution was explored in the context of a Biology course (upper secondary education). The experiment lasted for three weeks during which different topics were explored and investigated. Participants' ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n=35$</tex> ) perception toward VR and knowledge advancement were monitored during the whole course of the study with the key findings suggesting that mobile-VR can provide an affordable yet diverse learning experience. In this work we highlight the benefits as well as the limitations/shortcomings of this method on the basis of which we provide researchers, educators, and (educational) developers recommendations related to the benefits and shortcomings of this approach. Finally, considering the current circumstances and the ‘new norms’ (i.e., remote teaching) exploring the potential of this method in distance learning contexts is highly advisable.
Research on PHP Implementation and Online Intelligent Promotion of "Pharmaceutical Affairs Management and Regulations" Platform

With the development of society, people’s requirements for the fairness and openness of "pharmaceutical management and regulations" are constantly increasing. In this context, China’s pharmaceutical management teaching needs continue to expand. In order to build an online platform for pharmaceutical management, enrich Management methods to enhance management effects. This article is based on PHP language and WEB development technology to realize the construction of the online platform of "Pharmaceutical Affairs Management and Regulations" and online intelligent promotion.
Irreducible polynomials from a cubic transformation

Let R(x)=g(x)/h(x) be a rational expression of degree three over the finite field Fq. We count the irreducible polynomials in Fq[x], of a given degree, that have the form h(x)deg⁡f⋅f(R(x)) for some f(x)∈Fq[x]. As an example of application of our results, we recover the number of irreducible transformation shift registers of order three, which were computed by Jiang and Yang in 2017.
Revolutionizing Education Sector by Leveraging Blockchain Technology

Education is a fundamental aspect of life for each student which cannot be modified but which, during crisis time, may turn the shape into a new digital pedagogical method. The online and print retention of educational data has become a standard. The education industry tried to shift all its activities online by applying lockdowns because of the Covid-19 epidemic. However, this change made it difficult to deal legally with certain procedures, such as document verification and LOR approval. In this article, we compare and propose our approach to several already existing techniques for tackling the issue at hand.
The Place of Virtual Reality in E-Retail

The global pandemic of COVID-19 pushed the technological barriers and forced both retailers and potential customers to seek new ways of mutual interaction. Even though considered as mostly exclusive to the gaming industry, virtual reality has been gaining more interest outside its original niche. However, it is not clear how this new technology is going to be accepted by average customers in e-retail. This chapter focuses on defining the concept of virtual reality and providing an overview of aspects associated with virtual immersion. Further, the effects of virtual immersion are examined on a group of university students and put in a perspective with their intention to use this technology for shopping purposes in the future. The main emphasis is put on the comparison of hedonic and utilitarian factors of virtual reality adoption in e-retail.