Reviewerly/exHarmony huggingface dataset:
NetVote: A Strict-Coercion Resistance Re-Voting Based Internet Voting Scheme with Linear Filtering

This paper proposes NetVote, an internet voting protocol where usability and ease in deployment are a priority. We introduce the notion of strict coercion resistance, to distinguish between vote-buying and coercion resistance. We propose a protocol with ballot secrecy, practical everlasting privacy, verifiability and strict coercion resistance in the re-voting setting. Coercion is mitigated via a random dummy vote padding strategy to hide voting patterns and make re-voting deniable. This allows us to build a filtering phase with linear complexity, based on zero knowledge proofs to ensure correctness while maintaining privacy of the process. Voting tokens are formed by anonymous credentials and pseudorandom identifiers, achieving practical everlasting privacy, where even if dealing with a future computationally unbounded adversary, vote intention is still hidden. It is not assumed for voters to own cryptographic keys prior to the election, nor store cryptographic material during the election. This property allows voters not only to vote multiple times, but also from different devices each time, granting the voter a vote-from-anywhere experience. This paper builds on top of the paper published in CISIS’19. In this version, we modify the filtering. Moreover, we formally define the padding technique, which allows us to perform the linear filtering scheme. Similarly we provide more details on the protocol itself and include a section of the security analysis, where we include the formal definitions of strict coercion resistance and a game based definition of practical everlasting privacy. Finally, we prove that NetVote satisfies them all.
Developing digital signal clustering method using local binary pattern histogram

In this paper we presented a new approach to manipulate a digital signal in order to create a features array, which can be used as a signature to retrieve the signal. Each digital signal is associated with the local binary pattern (LBP) histogram; this histogram will be calculated based on LBP operator, then k-means clustering was used to generate the required features for each digital signal. The proposed method was implemented, tested and the obtained experimental results were analyzed. The results showed the flexibility and accuracy of the proposed method. Althoug different parameters of the digital signal were changed during implementation, the results obtained showed the robustness of the proposed method.
Social Aspect of Student's Language Learning Style in Differentiated ESP Instruction

The study aims to investigate the possibility of using the Belbin Self-Perception Inventory (SPI) for the actualization of the social aspect of the language learning style in the differentiated English for specific purposes (ESP) learning of information technology (IT) students so as to determine the students' and teachers' attitudes to the use of Belbin's roles in the differentiated ESP instruction.To achieve the outlined aim, a mixed research design was employed which involved 180 university IT students and 10 teachers.For data collection we used the Belbin's SPI, students' self-assessment survey and ESP teachers' survey.The results showed that the students' team and functional roles were evident in each group, irrespective of the number of students in it.Communicative roles were found to be an integral part of functional, team, and social roles.Various interaction patterns were defined for students' functional roles.The findings suggested that in the context of social relations and the roles, the subject of a conversation, communicative behavior, professional knowledge, experience, and language potential of the interlocutors are different and reflect the specifics of the situation.To improve the students' communicative skills, three stages of role learning were suggested.The optimal group size for the differentiated ESP instruction was defined.The Belbin's roles were found suitable for groups of students with different English language proficiency levels.This study showed that the use of Belbin's approach to actualization of the social aspect of the language learning style in the differentiated ESP instruction can be effectively used in teaching IT students at university.
Intent Detection-Based Lithuanian Chatbot Created via Automatic DNN Hyper-Parameter Optimization

In this paper, we tackle an intent detection problem for the Lithuanian language with the real supervised data. Our main focus is on the enhancement of the Natural Language Understanding (NLU) module, responsible for the comprehension of user’s questions. The NLU model is trained with a properly selected word vectorization type and Deep Neural Network (DNN) classifier. During our experiments, we have experimentally investigated fastText and BERT embeddings. Besides, we have automatically optimized different architectures and hyper-parameters of the following DNN approaches: Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM) and Convolutional Neural Network (CNN). The highest accuracy=∼0.715 (∼0.675 and ∼0.625 over random and majority baselines, respectively) was achieved with the CNN classifier applied on a top of BERT embeddings. The detailed error analysis revealed that prediction accuracies degrade for the least covered intents and due to intent ambiguities; therefore, in the future, we are planning to make necessary adjustments to boost the intent detection accuracy for the Lithuanian language even more.
Design Thinking in Action: A DPR Case Study to Develop a Sustainable Digital Solution for Labor Resource Management

The construction industry is known for cost and time overruns as well as vulnerable to mistakes and reworks, leading to low productivity compared to other industries in the last fifty years.As of today, the development of digital technologies has transformed many other industries, from automotive to transportation and finance.However, even though new tools and technologies are emerging rapidly for the construction industry, the rate of innovation and innovation adoption is low.The traditional push approach can hardly address the varied and indeterminate sets of issues faced by each project team whose solutions might be unique and evolving.The Design Thinking approach, which resembles the pull strategy in the Lean concept, has great potential in searching for and developing sustainable and innovative solutions with the users.In this paper, the Business Process Improvement team in DPR Construction, a national technical builder, leveraged the Design Thinking approach to develop a sustainable digital solution hand in hand with the user leveraging a Low Code Application Platform.The approach yielded a result that eased the transition period for adoption and significantly improved the efficiency of the labor resource management process.
An Effective Adjustment to the Integration of Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Environments

Although particle swarm optimization (PSO) is a powerful evolutionary algorithm for solving nonlinear optimization problems in deterministic environments, many practical problems have some stochastic noise. The optimal computing budget allocation (OCBA) has been integrated into PSO in various ways to cope with this. The OCBA can mitigate the effect of noise on PSO by selecting the best solution under a limited evaluation budget. Recently, with the increasing complexity of PSO applications, the evaluation costs are also increasing rapidly, which has sparked the need for more efficient PSO in stochastic environments. This article proposes a simple yet effective adjustment to the integration of OCBA to further improve the efficiency of PSO. The proposed adjustment allows OCBA to expand its search space to find the global best position more correctly such that the entire swarm can move on a better direction under stochastic noise. The experimental results on various benchmarks demonstrate the improved performance of PSO by the proposed adjustment under a limited budget compared with the latest studies. In addition, the results regarding fighters' evasion flight optimization emphasize the practical need for the proposed adjustment.
Using WhatsApp for co-creation of learning resources: A case of a South African university

Although culturally diverse students have potential to create enriched learning resources, it is difficult to harness students’ agency and to aggregate individual contributions into a meaningful learning resource. This is one of the challenges facing higher education institutions in South Africa where institutions are increasingly cosmopolitan and culturally diverse, but production of knowledge has largely remained skewed in favour of those students with unlimited access to learning resources, the Internet and peer networks, anywhere, anytime. Although the appropriation of emerging technologies such as mobile phones has enabled a digital sharing culture, this social practice has not been harnessed for co-creation of learning resources. This article reports on a study that sought to uncover the extent to which the use of WhatsApp-enabled phones facilitated the co-creation of learning resources in a human resource management programme at a university of technology in South Africa. The article employed Amartya Sen’s capabilities framework to analyse WhatsApp interactions of 72 participants from underprivileged backgrounds. The article concludes that leveraging students’ capabilities, including rich culturally diverse knowledge, is not a mere outcome of access to a tool such as WhatsApp, but requires pedagogical designs that exploit the affordances of the tool.
VB-PTC: Visual Block Multi-Record Text Extraction Based on Sensor Network Page Type Conversion

Usually, in addition to the main content, web pages contain additional information in the form of noise, such as navigation elements, sidebars and advertisements. This kind of noise has nothing to do with the main content, it will affect the tasks of data mining and information retrieval so that the sensor will be damaged by the wrong data and interference noise. Because of the diversity of web page structure, it is a challenge to detect relevant information and noise in order to improve the true reliability of sensor networks. In this paper, we propose a visual block construction method based on page type conversion (VB-PTC). This method uses a combination of site-level noise reduction based on hashtree and page-level noise reduction based on linked clusters to eliminate noise in web articles, and it successfully converts multi-record complex pages to multi-record simple pages, effectively simplifying the rules of visual block construction. In the aspect of multi-record content extraction, according to the characteristics of different fields, we use different extraction methods, combined with regular expression, natural language processing and symbol density detection methods which greatly improves the accuracy of multi-record content extraction. VB-PTC can be effectively used for information retrieval, content extraction and page rendering tasks.
Entanglement Research for the Coupled Superconducting Phase Qubit and a Two-Level System

Entanglement can exist not only in the microscopic system (e.g., atom, photon, and ion trap) but also in macroscopic systems. According to recent research, entanglement can be achieved and controlled in superconducting devices. The quantum dynamics and entanglement mechanism of the coupled superconducting phase qubit and a two-level system (TLS) were demonstrated when the bipartite system was under microwave driving. Besides, the results reveal that when the system was experiencing decoherence, entanglement (concurrence) of the coupled superconducting phase qubit and TLS would oscillate damply with microwave driving time, even exhibiting concurrence sudden death and revival. The coupling effect of the superconducting qubit and TLS system and the resonant microwave together help to achieve entanglement, while concurrence death and concurrence revival are dependent on the decoherence source and mechanism, for example, the resonant microwave driving time acting on the bipartite coupling system. Furthermore, the simulation results show the entanglement of the coupled qubit and TLS system also depends on the purity of the initial states of the system. The article carried out a numerical simulation on the entanglement of different initial states, and the results showed that the entanglement of the coupled system changes with different initial states. For different initial states, entanglement, sudden death, and rejuvenation are still visible.
Lithuanian Pedagogic Corpus: Correlations Between Linguistic Features and Text Complexity

This paper discusses the problem of automatic CEFR (CEFR – Common European Framework of Reference for Languages: https://www.coe.int/en/web/common-european-framework-reference-languages/level-descriptions.) level assignment to texts. We address the correlations between the lexical, morphological and syntactic features and the different CEFR levels of the texts in the Lithuanian Pedagogic Corpus. Only the texts from coursebooks showed the correlation of investigated linguistic features with text complexity. In the coursebook sub-part of the corpus, we observed that higher language proficiency levels are associated with more complex linguistic features: their number increases in texts of higher CEFR levels from A1 to B2 (e.g., non-finite verb forms, participles, adverbial participles and half participles, dative and instrumental noun cases or longer sentences).
Smart hand gestures recognition using K-NN based algorithm for video annotation purposes

&lt;span&gt;Sign languages are the most basic and natural form of languages which were used even before the evolution of spoken languages. These sign languages were developed using various sign "gestures" that are made using hand palm. Such gestures are called "hand gestures". Hand gestures are being widely used as an international assistive communication method for deaf people and many life aspects such as sports, traffic control and religious acts. However, the meanings of hand gestures vary among different civilization cultures. Therefore, because of the importance of understanding the meanings of hand gestures, this study presents a procedure whichcan translate such gestures into an annotated explanation. The proposed system implements image and video processing which are recently conceived as one of the most important technologies. The system initially, analyzes a classroom video as an input, and then extracts the vocabulary of twenty gestures. Various methods have been applied sequentially, namely: motion detection, RGB to HSV conversion, and noise removing using labeling algorithms. The extraction of hand parameters is determined by a K-NN algorithm to eventually determine the hand gesture and, hence showing their meanings. To estimate the performance of the proposed method, an experiment using a hand gesture database is performed. The results showed that the suggested method has an average recognition rate of 97%. &lt;/span&gt;
Features and Inspirations of Performance Framework for Regional Universities in Australia

Regional universities are common around the world, and important to the higher education system. This paper mainly analyzes the features of performance framework for regional universities in Australia, and discusses how the framework inspires the performance evaluation of regional universities in China. Firstly, the main features of Australian regional universities were summarized as the diversity of students, the strong local features, and the important social influence. Then, the key components of the performance framework, namely, core, optional, and institution-specific measures, were introduced in great details. Drawing on the framework and the local conditions, several suggestions were put forward to promote the performance evaluation of regional universities in China: develop high-level universities, serve local development, and diversify evaluation standards. The research results help to promote higher education in China and beyond.
Understanding the bushmeat hunting crisis in African savannas using fuzzy cognitive mapping and stakeholder knowledge

Critical conservation issues such as bushmeat hunting, which exist in complex social, political, and policy landscapes, require the incorporation of diverse sources of knowledge as a key aspect of decision making.We demonstrate the utilization of both individual and collective stakeholder knowledge to contribute toward decision making.We used fuzzy cognitive mapping in a twostage process to investigate bushmeat hunting and consumption in Malawi as a case study, and arrived at models of the bushmeat hunting and consumption systems in the form of cognitive maps.We also explored the effect of three different intervention scenarios, namely wildlife farming, microenterprise initiatives, and ecotourism.We found that the concept of hunting was perceived as more complex than consumption, and that poverty, human population, and political will were shared as important drivers of both issues.The two-stage process we used indicated that individual and group phases were equally important.Key concepts were drawn out during the individual elicitation stage, while the participatory group phase allowed nuanced understanding of many of these concepts.We found that wildlife farming was predicted to be the most effective scenario for meeting many of the key state outcomes for both hunting and consumption.These results provide an example of using fuzzy cognitive mapping in a multistage process and illustrate its utility for arriving at decisions regarding interventions in complex social-ecological systems.
Virtual Professional Training Community Model for Developing Digital Teacher Competencies

This was a document research study.Its objectives were (1) to study the virtual professional training process to develop digital teacher competencies and (2) to synthesize digital teacher competencies.The data were analyzed by using the content analysis technique.The results of the research revealed the following.Digital Teacher Competency consisted of 6 aspects as follows: Part 1, Using digital technology; Part 2, Data information and knowledge; Part 3, Communication and collaboration; Part 4, Digital content creation; Part 5, Integrating digital pedagogy; and Part 6, Ethics using digital technology.The form of the virtual vocational training community to develop digital teacher competencies consisted of 4 parts, which were the following: 1) Input, 2) Process, 3) Output, and 4) Feedback.We were able to assess the suitability of the Virtual Professional Training Community Model for Developing Digital Teacher Competencies with 9 experts in information and communication technology in education.The evaluation results revealed that the Virtual Professional Training Community Model for Developing Digital Teacher Competencies was formed.Part 1, the suitability of the virtual professional training process to improve digital teacher competencies, was very suit-able.The mean was 4.63 and the standard deviation was 0.56.Part 2, the suitability of the details of the virtual professional training process to develop digital teacher competencies, reached the most suitable level.The mean was 4.56 and the standard deviation was 0.65.
Advances in colour transfer

Colour grading is an essential step in movie post‐production, which is done in the industry by experienced artists on expensive edit hardware and software suites. This paper presents a review of the advances made to automate this process. The review looks in particular at how the state‐of‐the‐art in optimal transport and deep learning has advanced some of the fundamental problems of colour transfer, and how far are we still from being able to automatically grade images.
An Effective Scheduling Method in the Cloud System of Collective Access, for Virtual Working Environments

This paper describes the cloud system of collective access to virtual working environments as a means of providing remote access to paid and free software, for students of educational institutions in secondary education.The problems of efficient cloud system scheduling and optimizing the usage of cloud virtual machines and paid software licenses has been studied in detail, herein.In addition, the mathematical model of cloud system resources control is presented, as well as, the functional model.Two evolutionary scheduling algorithms are proposed.Also, the UML class diagram of the cloud system simulator is described.The statistical analysis of the fitness function value distribution, to evaluate the proposed algorithms, is also performed.
Determinates of Capital Structure in Case of Private Commercial Banks in Ethiopia

This study was conducted on the title determinants of capital structure; evidence from private commercial banks in Ethiopia.To find out what determines capital structure, seven bank specific explanatory variables (Profitability, tangibility, growth, age, tax shield, size and liquidity) was selected and regressed beside the suitable capital structure measure (Debt to Equity Ratio).Fourteen private commercial banks, which had minimum of seven years life were selected for the study.Their audited financial statement from 2013 to 2019 was used as major source of data.Before the analysis of regression model test of CLRM assumptions such as normality, multicollinearity, heteroscedastcity and autocorrelation tests were conducted on the data.After these tests, Hauseman model specification test conducted and its result indicated that Fixed Effect Model was better to test hypotheses that emerge through the review of existing literature.Then inferential statistics regression was done by Fixed Effect Model (FEM).The regression result reveled that profitability, age, tax shield and size had significant effect on leverage.However, among the hypothesized capital structure determinants growth, asset tangibility and liquidity had insignificant effect on capital structure of Ethiopian private commercial bank.In addition, trade-off theory and the pecking order theory explained the capital structure behavior of banking industry in Ethiopia.
The Efficacy of Augmented Reality on Student Achievement and Perception among Teluk Intan Community College Student in Learning 3D Animation

This paper presents a research conducted in Teluk Intan Community College aimed to evaluate the effectiveness and usability of integrating the Augmented Reality (AR) technology as an aid for animation course in Teluk Intan Community College. The focus was to integrate AR tool as an aid for students in the task of 3D modelling. For this research, the intended outcome is to compare the effectiveness between using the AR tool and written tutorial. The AR tool which later be called as ARC-3DM (Augmented Reality Courseware for 3D Modelling) will be developed and be tested in the experiment. Quantitative approach and quasi-experimental design were used in the study. A total of 54 animation students are involved in the study. The students were divided into two groups: control and treatment. A pretest and posttest were conducted to both groups. System Usability Scale (SUS) Questionnaire were administered to treatment group after the posttest to evaluate usability. Statistical methods involved were descriptive analysis and the analysis of covariance (ANCOVA) with the pretest as the covariate at significant level of 0.05 was conducted to answer the hypothesis. The results indicate that the treatment group performed better than the control group in completing the task of 3D modelling. In terms of usability, the results showed that most of the students agreed on the usability in the ARC-3DM.