Reviewerly/exHarmony huggingface dataset:
Review of the Lineal Complexity Calculation through Binomial Decomposition-Based Algorithms

The ubiquity of smart devices and IoT are the main forces behind the development of cryptographic primitives that preserve the security of this devices, with the resources constraints they face. In this sense, the development of lightweight cryptographic algorithms, where PRNGs are an essential part of them, provides security to all these interconnected devices. In this work, a family of sequence generators with hard characteristics to be analyzed by standard methods is described. Moreover, we introduce an innovative technique for sequence decomposition that allows one to extract useful information on the sequences under study. In addition, diverse algorithms to evaluate the strength of such binary sequences have been introduced and analyzed to show which performs better.
Teaching Reform of Java Web Programming Course Based on the Concept of OBE

Combined with the actual teaching situation of Java Web Programming course in Colleges and universities, this paper analyzes the problems existing in the teaching process of Java Web Programming course, introduces the concept of OBE, clarifies the teaching objectives, reconstructs the teaching content, focuses on the teaching evaluation and optimizes the assessment process, so as to comprehensively improve the students' knowledge, ability and quality.
The Role of Governance in Quality Education in Sub-Saharan Africa

This paper examines the governance-“education quality” nexus in a panel of 49 sub-Saharan African countries over the period 2000-2012. Ordinary Least Squares (OLS) and Quantile regression (QR) are employed as estimation strategies. The following findings are established. First, from the OLS, governance variables are negatively correlated with poor education quality. Second, with regards to QR, about half of the governance dynamics are not significantly correlated with poor education quality in the lowest quantile of poor education quality. With the exception of corruption-control, the other governance dynamics are negatively correlated with poor education quality in a non-monotonic pattern.
The Influence Of Blended Learning Face To Face Driver Model Type Learning On Learning Interests And Learning Outcomes In Simulation Digital

&lt;p&gt;The purpose of this research is to find out how the influence of the use of blended learning model face to face driver model on student interest and learning outcomes. And to find out how effective the improvement in learning outcomes and learning interests of students uses blended learning type face to face driver model. The research method used in this study is an experimental method with true experimental design research design. The study involved class X TKJ students at SMK Sakti Gemolong as participants, who were selected using cluster random sampling techniques. The treatment given to the experimental class is in the form of a blended learning model face to face driver model, while the control class is done with conventional learning. The research method used is quantitative. Data were collected by questionnaire method and learning achievement test. Analysis of the questionnaire is used to obtain data on student interest in learning, then to the analysis of the learning outcomes test is used to obtain student learning outcomes data on the blended learning model face to face driver model. The results of this study are 1) there is an influence of the use of blended learning models face to face driver model on student learning outcomes with a significant level .836. 2) there is an influence of the use of blended learning type face to face driver model of learning interest of students with a significant level. 3) there is an effectiveness in increasing student learning outcomes by using blended learning models face to face driver model with a total score gain of 0.5142 compared to 0.4274 (control class). 4) there is effectiveness in increasing students' interest in learning by using a blended learning model face to face driver model with a total score gain of 0.2131 compared to 0.0740 (control class).&lt;/p&gt;
Security algorithm on Cloud Storage System

The cloud computing basic idea was given by 1960 by Professor John, "The future computers will be just like, the telephone services and according to requirement we use their services" and this computer idea has been play a vital role in industry". The combination of distributed, grid computing and virtualization is known as cloud computing, and these systems are interconnected group of systems and dynamically provision and offering the one or more unified cloud-computing resources. SLA is known as service level agreement and playing a vital role between clients and service provider. The SLA service level agreement is a negotiation between the users and cloud provider. The cloud service provider's objective is to provide their services, to clients qualitative, more secure, abrupt, scalable, more responsive, cost-efficient, on demand and automatically provisioned services just like: storage services, computation services, network system etc. Cloud services are geographically dispersed everywhere throughout the world in a transparent way and help to improve business execution by making a commitment to decrease the expense of conveying IT assets to any association. Cloud services implementation helping to reduce in a organization is controlling IT resources the cost. These cloud services demands are day by day rapidly increase as financial model applied in cloud computing is "Pay-per-Use".
Optimisation of Material Flows in the Concept Urban Mining Based on the Use of Long-Term Storage Depot

Purpose: The purpose of the chapter is to improve material flows in urban areas with the help of long-term storage depots for mineral construction waste remaining after the demolition of buildings and structures for their further use as recycling materials. Design/methodology/approach: Urbanized territories are depots of material resources that are most efficiently used within the framework of circular economy and replace with them fully or partially natural resources. This concept is called urban mining. The authors identify a way to optimize the flow of mineral resources using long-term storage depots and calculate its efficiency using a specific example. Findings: It is shown that the studied method significantly optimizes the flow of mineral resources during the transition to circular economy and the introduction of the concept of urban mining. At the same time, with the given parameters, the current and maximum volumes of long-term storage depots are calculated, as well as the time when the system reaches a reduction in the generated waste in comparison with the volume of their recycling. Outlook—further research assignments: The project is at the initial stage of development and implies the use of optimization algorithms and machine learning for multivariate analysis and decision-making in real time with its further implementation.
Induction with Generalization in Superposition Reasoning

We describe a dataset expressing and proving properties of graph trails, using Isabelle/HOL. We formalize the reasoning about strictly increasing and decreasing trails, using weights over edges, and prove lower bounds over the length of trails in weighted graphs. We do so by extending the graph theory library of Isabelle/HOL with an algorithm computing the length of a longest strictly decreasing graph trail starting from a vertex for a given weight distribution, and prove that any decreasing trail is also an increasing one. This preprint has been accepted for publication at CICM 2020.
On some typical problems to be solved in primary schools

One of the main requirements of school mathematics education in this article is the formation of an independent-minded creative thinker, a creative approach to the performance of educational tasks. The concept of “problem ” is one of the most important tools in developing independent thinking of primary school students in mathematics. In math classes, students seek to analyze connections between subjects through problems. In particular, typical arithmetic problems play a special role in enhancing the student's logical thinking, creative activity, as well as expanding their free, independent thinking.
Examining the Trends of Educational Variables in the Past Affecting Egypt’s Ability to Becoming Future-Proof in Facing Unemployment

This study aims to investigate the relationship between some educational variables and unemployment in Egypt, thus determining the most important educational variables influencing the high rates of unemployment during the period (2002–2012). According to the data that were available from each source for the synthesis of time series, it could be sufficient to examine the trends in the past as a suitable retrieval case. By excluding any fluctuations such as epidemics or revolutions affecting the systems of government, the findings may be utilized in shaping the future by decision makers in Egypt in optimal manner. Thus, it can determine the priorities of the Egyptian government when dealing seriously in order to solve the unemployment problem appropriately, with regard to the reduction of unemployment rates in the near future. More importantly, the results have shown that the number of graduates of theoretical facilities has a significant impact on increasing the number of unemployed in Egypt, according to the target period by the current study. Keywords: education, unemployment, Higher Education Systems (HES), Egypt
A Fully Adaptively Secure Threshold Signature Scheme Based on Dual-Form Signatures Technology

In <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mfenced open="(" close=")" separators="|"> <mrow> <mi>t</mi> <mo>,</mo> <mi>n</mi> </mrow> </mfenced> </math> threshold signature schemes, any subset of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>t</mi> </math> participants out of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>n</mi> </math> can produce a valid signature, but any fewer than <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mi>t</mi> </math> participants cannot. Meanwhile, a threshold signature scheme should remain robust and unforgeable against up to <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <mi>t</mi> <mo>−</mo> <mn>1</mn> </math> corrupted participants. This nonforgeability property is that even an adversary breaking into up to <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6"> <mi>t</mi> <mo>−</mo> <mn>1</mn> </math> participants should be unable to generate signatures on its own. Existential unforgeability against adaptive chosen message attacks is widely considered as a standard security notion for digital signature, and threshold signature should also follow this accordingly. However, there are two special attack models in a threshold signature scheme: one is the static corruption attack and the other is the adaptive corruption attack. Since the adaptive corruption model appears to better capture real threats, designing and proving threshold signature schemes secure in the adaptive corruption model has been focused on in recent years. If a threshold signature is secure under adaptive chosen message attack and adaptive corruption attack, we say it is fully adaptively secure. In this paper, based on the dual pairing vector spaces technology, we construct a threshold signature scheme and use Gerbush et al.’s dual-form signatures technology to prove our scheme, which is fully adaptively secure in the standard model, and then compare it to other schemes in terms of the efficiency and computation.
Feasibility Analysis of Integrating Augmented Reality Application into Education System to Improve Students’ Learning Experience

Abstract Integrating Augmented Reality (AR) application into education system can improve students’ learning experience, this study analyzes the feasibility of the application of augmented reality technology in education through literature review. It also commend the AR use survey of three disciplines in education industry, including potential advantages, challenges and learning experience, and takes PDCD mode as AR resource development mode. Then it analyzes the advantages and disadvantages of its intelligent learning environment and technology in education, the utilization of AR is considered a suitable tool to incorporate in the education industry.
Self-attention based sentiment analysis with effective embedding techniques

The problem of sparse vector representation exists in handling the large-scale data and also semantics of words are not considered in many existing works of sentiment analysis. Effective word embedding techniques improve the task of sentiment analysis by overcoming the above two problems. It is a challenging task, when the review is expressed in multiple sentences and the entire sentence needs to be considered instead of individual words to determine the sentiment. To achieve this task, we have proposed a novel LSTM-based deep learning architecture that applies a sentence embedding using universal sentence encoder along with an attention layer. To evaluate the proposed approach, we have carried out various experiments on IMDB data set. From the experimental results, it is observed that the proposed method is significantly better than the other word-embedding-based approaches with an improvement of 5% and we have achieved a F1 score of 89.12% for our approach.
BoneNet: Real-time 3D Human Pose Estimation By Generating Multiple Hypotheses with Bone-map Representation

When developing new products, brand designers must analyse related products, which is a complicated and time-consuming process.Modern product design often requires complex engineering processes; product development requires extensive knowledge but there is also a demand for shorter product design cycles.Therefore, we propose a method based on extension theory and the analytic hierarchy process for identifying product-related knowledge, to aid the development of new products.First, based on our understanding of extenics, matter-element and relational meta-models of product form, function, and structure are established.Then, we define different primitives of brand identity.Finally, using an "extensional analytic hierarchy process" (EAHP), a hierarchy is established and the weights of different primitives are calculated.Various combinations of primitives are used to facilitate knowledge transfer for computer-aided intelligent design.Design data for multiple cases are analysed to verify the feasibility and effectiveness of the method.The method was verified in a physiological signal experiment, and the results show that the method can effectively accumulate product knowledge.Rapid data mining is important for market competitiveness.
Governance, Capital Flight and Industrialisation in Africa

The study examines the role of governance in modulating the effect of capital flight on industrialisation in Africa. The empirical evidence is based on Generalised Method of Moments and governance is bundled by principal component analysis, namely: (i) political governance from political stability and “voice and accountability”; (ii) economic governance from government effectiveness and regulation quality; and (iii) institutional governance from corruption-control and the rule of law. First, governance increases industrialisation whereas capital flight has the opposite effect; and second, governance does not significantly mitigate the negative effect of capital flight on industrialisation. Policy implications are discussed.
Multi-Tier Accent Classification For Improved Transcribing

Corporate companies are becoming more aware of gathering public sentiment, which is facilitated with the presence and vast usage of social networks and media platforms. This is a big data problem, and thus automated machine learning systems are deployed. The process requires the analysis of textual mentions, visual illustrations of the brand and/or respective location, as well as audio mentions of the corporate identity and respective products. When focusing on gathering sentiment analysis from the spoken language, the problem of accent recognition is evident across native and non-native English speakers. Thus, in this research, we investigate the key features of accent recognition, calibrate a proposed system based on previous research using the Wildcat Corpus, and apply on a recent dataset, the Common Voice. Finally applying to a custom dataset gathered from an online media platform. We propose a novel hierarchical classifier solution, trained on the Common Voice dataset and tested on the custom dataset. Our three-tier solution achieved 86% and 89% in the first two levels of accents, and 59% at the final level. From this research, we highlight the issues around the considered datasets and propose a number of recommendations for future researchers. In this research we are not improving or comparing any existing works, but rather offer new insights on the Common Voice dataset. We are presenting a hierarchical classifier for the accent classification problem as proposed.
Mobile Learning through WhatsApp: EFL Students’ Perceptions

Rapid development of technology and the use of mobile learning enable students to choose the most effective device and application as a learning tool to improve their language skills. WhatsApp as a feasible application is nowadays taken into consideration since they often use it in their learning during Covid-19 Pandemic. This study aimed to investigate the EFL university students’ perceptions on using WhatsApp application in their language learning. 21 EFL students from English Department who joined a Qualitative Data Analysis class were involved as the participants of this study. Questionnaires and semi-structured interviews were employed as the data collection instruments. The findings indicated that WhatsApp seemed to be used well as a medium of learning by students and it could help students to improve their language skills particularly in writing and reading skills. It was proved from their positive response and comments on using that application. However, the students faced some challenges dealing with their concentration on messages since they were distracted by the other messages delivered and the mobile internet connection problem.
PRSafe: Primitive Recursive Function based Domain Specific Language using LLVM

General Purpose programming languages such as C++, Python suffer from resource management and input errors because they are Turing-complete. The goal of this paper is to introduce a prototype functional Domain Specific Language that is Non-Turing complete called PRSafe. The design of PRSafe is based on the memory and input properties of Primitive Recursive Functions (PRFs). Hence, all computations must terminate. For the language implementation, we use the Lex and Bison softwares for lexing and parsing respectively and LLVM compiler infrastructure for code generation and optimization. PRSafe is designed such that syntactically and semantically, it prohibits the creation of Turing-complete programs. It is eventually intended to be a mathematically verifiable compiler with better user-friendly error-diagnostics for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$e$</tex> BPF programs than the eBPF verifier.
Optimal affine image normalization approach for optical character recognition

Optical character recognition (OCR) in images captured from arbitrary angles requires preliminary normalization, i.e. a geometric transformation resulting in an image as if it was captured at an angle suitable for OCR. In most cases, a surface containing characters can be considered flat, and a pinhole model can be adopted for a camera. Thus, in theory, the normalization should be projective. Usually, the camera optical axis is approximately perpendicular to the document surface, so the projective normalization can be replaced with an affine one without a significant loss of accuracy. An affine image transformation is performed significantly faster than a projective normalization, which is important for OCR on mobile devices. In this work, we propose a fast approach for image normalization. It utilizes an affine normalization instead of a projective one if there is no significant loss of accuracy. The approach is based on a proposed criterion for the normalization accuracy: root mean square (RMS) coordinate discrepancies over the region of interest (ROI). The problem of optimal affine normalization according to this criterion is considered. We have established that this unconstrained optimization is quadratic and can be reduced to a problem of fractional quadratic functions integration over the ROI. The latter was solved analytically in the case of OCR where the ROI consists of rectangles. The proposed approach is generalized for various cases when instead of the affine transform its special cases are used: scaling, translation, shearing, and their superposition, allowing the image normalization procedure to be further accelerated.
Progressive computer test capabilities of the candidates proposed for the post of physical education teacher

The research aims to use progressive test capabilities to identify the capabilities of prospective teachers of Physical Education, who desire to work as teachers in schools of education in all categories. This research was conducted using a descriptive research method and a total sample consisted of 60 experts, including 10 academic experts from the Curriculum and Instruction Department, 10 directors of Physical Education, 10 managers of schools, 5 experts in computer and 25 graduate students. The survey used questionnaires in collecting data. The questionnaire which was designed by the researchers sought to test prospective physical education teacher’s performance with themes such as work under pressure, work amid distractions, speed of decision-making, power of observation, the level of intelligence, memory and concentration and synergies neuromuscular. The most important recommendations for the selection of prospective Physical Education teachers is to use the test proposed computer to learn about the capabilities of the candidates and the possibility of using the programme to develop the capacity of teachers. Keywords: Test capabilities, computerised test, test the capabilities of physical education teachers, teacher’s capabilities development.
Robust Hybrid Interval-Probabilistic Approach for the Kidnapped Robot Problem

For a mobile robot to operate in its environment it is crucial to determine its position with respect to an external reference frame using noisy sensor readings. A scenario in which the robot is moved to another position during its operation without being told, known as the kidnapped robot problem, complicates global localisation. In addition to that, sensor malfunction and external influences of the environment can cause unexpected errors, called outliers, that negatively affect the localisation process. This paper proposes a method based on the fusion of a particle filter with bounded-error localisation, which is able to deal with outliers in the measurement data. The application of our algorithm to solve the kidnapped robot problem using simulated data shows an improvement over conventional probabilistic filtering methods.