Reviewerly/exHarmony huggingface dataset:
Bidirectional Joint Attention Mechanism for Target Tracking Algorithm

In this paper, we propose a target tracking algorithm SiamMT based on Siamese network architecture. The attention mechanism is introduced to solve the problem of semantic information loss caused by the classical traditional Siamese network architecture. Aiming at the problem that the target feature is not prominent and comprehensive, a bidirectional feature enhancement network model is proposed. The local and global attention mechanisms of MobileNet and Transformer are used to enhance and update bi-directional features, and then the attention mechanism and classification regression network are combined to form a fusion prediction network. This fusion mechanism effectively integrates local and global features, and breaks the limitations of the search domain method by making full use of spatial information and motion information. In order to solve the problem of complexity and inefficiency of tracking network, lightweight network MobileNet is introduced as an enhanced network with local features. Finally, the experiments on OTBIOO and LaSOT long-term benchmark show that the tracker in this paper has higher accuracy and success than other advanced trackers.
Evaluation of the MOOCs Quality and Its Effectiveness for Teachers’ Training in the Field of Digital Competences and Their Use in Education: A Case Study

This study presents the research results obtained after the assessment of the digital competences of the pre-service and in-service teachers after their completion of the MOOC “Contemporary ICT Tools and Innovative Methods of Creative Education”. The paper provides a short description of the MOOC, requirements to pass the course and analysis of the learning outcomes through the students’ self-evaluation and feedback. The MOOC was developed in Polish and English within the project “MOOCs for Sciences of Education” and hosted on the Polish MOOCs platform Navoica (www.navoica.pl) within the framework of the competition, initiated by of Ministry of Education and Science of Poland and National Center for Research and Development (NCBR ‒ Narodowe Centrum Badań i Rozwoju) on “Direction to the MOOC”. Keeping in mind that Massive Open Online Courses (MOOCs) have developed into a mainstream for universities, education reformers and startup companies, especially in the time of the COVID-19, the study is believed to contribute to the development of the MOOC pedagogy, and address the question of the MOOCs effectiveness for students’ learning outcomes and satisfaction. The experimental MOOC “Contemporary ICT Tools and Innovative Methods of Creative Education”, which was aimed at enhancing teachers’ digital competences, contained 8 modules, and was attended by more than 90 students through its 1st edition in 2020‒2021. The conclusions of the MOOC in focus and overall recommendations on enhancing the MOOCs effectiveness for formal education and learning outcomes have been evaluated based on the research data and provided accordingly. The selected statistical analyses and the data comparisons were made using Wilcoxon’s test at the significance level alpha = 0.05. The normality of the distributions of the studied variables was checked using the Shapiro Wilk test.
Quaternion Graph Wavelet Transform for Color Texture Classification

The utilization of color and texture information is an important research direction in image processing and pattern recognition. Quaternion graph wavelet transform can combine the structure and relationship between samples to provide richer information at different scales. Therefore, this paper proposes a color texture classification method based on quaternion graph wavelet transform. Specifically, the quaternion graph wavelet transform is used to decompose the color texture. Then the local quaternion singular value decomposition is performed on the subband coefficients to extract local texture information and the Weibull distributions are used to model effective singular values. Finally, experiments on two datasets using the nearest neighbor classifier measured by KL divergence demonstrate that the proposed method is effective for color texture classification.
Solving parameterized generalized‎ ‎inverse eigenvalue problems via Golub-Kahan bidiagonalization

In this study, we present two two-step methods to solve parameterized generalized inverse eigenvalue problems that appear in diverse areas of computation and engineering applications. At the first step, we transfer the inverse eigenvalue problem into a system of nonlinear equations by using of the Golub-Kahan bidiagonalization. At the second step, we use Newton's and Quasi-Newton's methods for the numerical solution of system of nonlinear equations. Finally, we present some numerical examples which show that our methods are applicable for solving the parameterized inverse eigenvalue problems.
The number of irreducible polynomials over finite fields with vanishing trace and reciprocal trace

We present the formula for the number of monic irreducible polynomials of degree n over the finite field $${\mathbb {F}}_q$$ where the coefficients of $$x^{n-1}$$ and x vanish for $$n\ge 3$$ . In particular, we give a relation between rational points of algebraic curves over finite fields and the number of elements $$a\in {\mathbb {F}}_{q^n}$$ for which Trace $$(a)=0$$ and Trace $$(a^{-1})=0$$ .
Cryptanalysis on Reduced-Round 3D and Saturnin

Abstract 3D is an Advanced Encryption Standard (AES)-like cipher employed 3D structure proposed in 2008. The main innovation of 3D is the multi-dimensional state, generalizing the design of Rijndael and allowing block sizes beyond the 256-bit boundary. Saturnin, a lightweight block cipher has been selected as a second-round candidate in the National Institute of Standards and Technology standardization for lightweight cryptography. It also employs a 3D structure and provides high security against quantum and classic attacks. The exchange-equivalence attacks proposed by Bardeh and Rønjom consider how quadruples of plaintexts confirm distinguishable properties for AES. It is similar to the principle of yoyo attack, but it can find a longer number of rounds of distinguisher. In this paper, we investigate the exchange-equivalence attack on 3D and yoyo attack on Saturnin. Our new results turn out to be the first secret-key chosen plaintext distinguisher for 10-round 3D. The complexity of the distinguisher is about $2^{364.2}$ in terms of data, memory and computational complexity. For Saturnin, we propose the first six-super-round impossible differential yoyo attack, which is suitable for the two-S-layer version. Compared with the previous impossible differential attacks in the design report of Saturnin, the attacks presented here are the best in terms of the complexity under the chosen-plaintext scenario.
Implementation of the User Centered Design method on the Mobile Web

The application of the User Centered Design (UCD) method is needed to improve the school website by redesigning it. The problems experienced by schools are usually in the form of a static website and an unattractive web appearance. This will be detrimental to the school, because the website is a door for information and school promotion. posting important news and announcements on the website in the hope that students and parents can obtain information more quickly and accurately. The UCD method starts from the plan, design, prototype and review. This step begins with interviews, field observations and distributing questionnaires to website users. Such as teachers, students, parents and the general public. The results provide a lot of input and optimize the appearance of mobile-based websites to attract more interest and better access by users. With the hope that students and parents can get information on news and important announcements more quickly and accurately on the website.
Applying NLP techniques to characterize what makes an online review trustworthy

Users spend a significantly amount of time reading and exchanging reviews online in e‑commerce and eWOM communities that help them with their purchase decisions. Source credibility theory is gaining more importance as some online reviews are currently being damaged by those fake reviews that promote an untruthful image not only of the products but also of those online websites. Thus, trustworthiness of online reviews is a key aspect not only for the users that want to make more informed decisions regarding the products, but also for the websites whose credibility might be affected. In this regard, this study proposes a classification system using two Natural Language Processing (NLP) models that can predict trustworthy online reviews (helpful and truthful) applied to the product category “Cell phones &amp;amp; accessories” of Amazon. After using a keyword extractor among those trustworthy online reviews we can characterize their most important features. The results reveal that those features are related to brands, physical and technical features and the UX of the mobile phones.
The Role of E-Training in Improving the Quality of Work Life for Workers in Business Organizations: a field study

Purpose: The purpose of this research is to improve the quality of work life for workers in the Egyptian tourism sector through the e-training entrance. Practical implications: Companies seek to adopt improving the quality of life for workers in the Egyptian tourism sector in order to have strategic solutions to promote Egyptian tourism locally and globally in light of the development strategy. Originality/Value: The e-training programs should be geared towards adopting the quality of work life for employees. A research paper covering the framework of achieving development for the Egyptian tourism sector under study. Results: The Egyptian tourism sector needs to adopt e-training in seminars, workshops, modern curricula and additional training, with continuous evaluation of the performance of the various services provided to promote Egyptian tourism globally.
Main challenges to the development of the system of higher education in modern Russia

The article considers the main challenges of the development of the system of higher education in modern Russia, due to the growing confrontation with the United States of America and its Western European allies. The expediency of revising the principles of the Bologna system, the need to reform strategic goals and objectives of the Russian higher education, the need for the inevitability of reforming public administration in this area to ensure the priority of national interests in the training of modern qualified specialists for various spheres of public life of the Russian Federation are substantiated.
Leadership Style and Employees' Commitment to Service Quality: An Analysis of the Mediation Pathway via Knowledge Sharing

Very little attention has been given to understanding the commitment to service quality and desirable outcomes in the hotel industry. This study investigates the impact of directive and participative leadership on the frontline commitment to service quality through the mediation of knowledge sharing. This will eventually help us to generate the employees' commitment to service quality (CSQ) desirable behavior. The survey was distributed to 37 hotels. A total of 235 frontline employees participated in the survey. The study findings show that directive leadership has a negative relationship with CSQ. On the other hand, participative leadership positively influences CSQ. Notably, knowledge sharing mediates between directive leadership, participative leadership, and commitment to service quality. There were positive linkages between commitment to service quality and desirable outcomes, job performance, and organizational citizenship behavior (OCB) and negative relation to turnover intention.
Protection of Literary Works In The Digital Ecosystem

The world wide web and internet revolution has made communication and the dissemination of information on a scale hitherto thought impossible. It has also made information available and accessible to a global audience on a scale that could only be imagined before its advent. With the possibility engendered by technology comes concerns among authors and owners of copyright over the facility with which this revolution has made infringements of copyrighted works not only possible, but also difficult to occlude. Creativesâ€™ frustration is heightened by the seeming inadequacy of traditional copyright regimes to guarantee watertight protection of works in the digital ecosystem. In view of this, therefore, it becomes imperative for creatives to ensure their works receive maximum protection not only under traditional copyright regimes but also under technology-enabled protective mechanisms. Hopefully, some countries have amended their copyright legislations to bring same into conformity with the realities of the digital age. Other nations are in the process of the amendments of their copyright statutes. It is expected that these legislations and technology, through hybridization, will stem the incidence of copyright infringements by online pirates.
RANCANG BANGUN SISTEM ABSENSI KARYAWAN LAPANGAN PADA PT. ALBANY CORONA LESTARI CABANG LEBAK BERBASIS WEB

Attendance is an important thing for an agency or company. Attendance says it is important because it can affect the salary or wages of an employee and attendance can also see the performance of an employee who is often present or absent. Therefore, the attendance process requires accuracy in its implementation so as not to hinder company performance. The purpose of this research is to design an employee attendance information system which is expected to help the performance of the company, especially in the Human Resources sector, to be faster and more practical. The research method used in this employee attendance information system is descriptive research method, while for the development of the system using a waterfall which includes requirements, system analysis, system design, system creation, system implementation, and system maintenance which is expected to assist in developing systems with work experience this clerk. This application development program uses a web-based application. In this system the data processing becomes more effective and efficient. The search for data is guaranteed to be easier.
A New Anonymization Model for Privacy Preserving Data Publishing: CANON

Data privacy is a challenging trade-off problem between privacy preserving and data utility. Anonymization is a fundamental approach for privacy preserving and also a hard trade-off problem. It enables to hide the identities of data subjects or record owners and requires to be developed near-optimal solutions. In this paper, a new multidimensional anonymization model (CANON) that employs vantage-point tree (VPtree) and multidimensional generalization for greedy partitioning and anonymization, respectively, is proposed and introduced successfully for the first time. The main concept of CANON is inspired from Mondrian, which is an anonymization model for privacy preserving data publishing. Experimental results have shown that CANON takes data distribution into consideration and creates equivalence classes including closer data points than Mondrian. As a result, CANON provides better data utility than Mondrian in terms of GCP metric and it is a promising anonymization model for future works.
Automated Structured Data Extraction from Scanned Document Images

AbstractDigital technologies are now becoming part of all the sectors be it banking, automobile, infrastructure, and more. These technologies are empowered by “Data”. This is raising the need for the digitization of documents to fulfill the need for data for driving the digital transformation throughout sectors. Digitization requires the extraction of a huge amount of data from paper-based documents. Automating data extraction from paper-based documents can help in dealing with large volumes of data at a lower cost with lesser efforts. A solution is proposed which uses open-source components to automate the process of data extraction from scanned documents with minimal user input. The solution is capable of generating the structured output reflecting the document layout with the data in a document. The solution is capable of extracting data from tables and stamps present in documents in a well-structured format. The solution is driven by a configuration file, which can help in fine-tuning different processes to improve extracted data. The solution generates an XML for the scanned document which can be used further for storing and processing the data present in paper-based documents by different digital processes.KeywordsAutomationImage processingDocument extractionTemplate less extractionOptical character recognitionStructured data extractionTable extractionScanned document XML
Innovative Low-Cost Perimeter Security Gadget With In-built Mechanism to Ensure Confidentiality, Authenticity and Non-Repudiation

The concept is to capture and preserve the intruder’s details in unattended mode. A camera is integrated with a processing unit and counter arrangement to ensure authenticity and non-repudiation of the captured images of the intruder before court of law. Ownership claim is justified concocting confidential data sharing of visual cryptography. Signal quality is retained and unauthorized tampering of secret data resisted. Entire procedure indulges: Message Digest M is generated using SHA-2 from the date and time stamp of the acquired image, two shares are generated from MAC address (K) of the network card and encryption is done using AES involving encoding using Hamming 1 – bit technique. The cover image is prepared in DCT domain to restrict JPEG compression. Sensitive data is embedded in restricted areas of DCT transformed image. Extraction of secret data verifies an intruder. The experimental results prove its efficacy over existing conventional system.
Working With Statistics

Abstract In this chapter, Maggie Koerth, a senior science writer at FiveThirtyEight, offers detailed, practical, and user-friendly advice for journalists seeking to decipher the often-complex challenges of statistics in research. One of the most important things you can do any time you are presented with statistics, she writes, is to ask where they came from. How were these data collected? How do the people who collected the data define important terms (especially ones you think you know the definition of instinctively)? Has the way the data were selected changed over time? She also provides a guide to critical terms and ideas in statistics, from p values to risk and probability. The most important thing to know, she adds, is that numbers can—and should—be questioned. That’s the big rule. Everything else is just helping narrow down what questions to ask—and asking them.
Making the Thing

Abstract This chapter discusses the game production process, with a focus on ideation, prototyping, and iterative design. It aims to provide readers with a starting point for putting the ideas of previous chapters into practise, without depending on any particular tools or budget requirements. Various brainstorming strategies are discussed as a primer on design thinking, before moving on to examine the entire development process at a high level. The chapter espouses an iterative, agile approach to game creation. Several techniques supporting iterative and user-centric design are explained, including user stories and personas, competitive evaluation, and rapid prototyping.
Kramer’s Razor and the Freedom of Expression

Abstract Matthew Kramer argues that we can define the bounds of free speech with a sharp and absolute distinction between communication-dependent and communication-independent restrictions. On Kramer’s view, government may never legitimately target speech where the wrong it seeks to prevent essentially depends on communication as its means. By contrast, it can punish speech that helps to effect a wrong that could be committed by non-communicative means. I argue, in response, that it is a mistake to think that such a distinction can avoid the hard, political work of weighing costs and benefits and making more contextualized decisions. If we want simultaneously both to forbid solicitation of criminal acts, and to protect radical advocacy that marches up to the line of sedition, we must leave a grey area, one responsive to the relative dangers of speech and its repression. Philosophy can clarify the conditions of our quandary but it cannot resolve them.
Learning to Cooperate with Human Evaluative Feedback and Demonstrations

Cooperation is a widespread phenomenon in nature that has also been a cornerstone in the development of human intelligence. Understanding cooperation, therefore, on matters such as how it emerges, develops, or fails is an important avenue of research, not only in a human context, but also for the advancement of next generation artificial intelligence paradigms which are presumably human-compatible. With this motivation in mind, we study the emergence of cooperative behaviour between two independent deep reinforcement learning (RL) agents provided with human input in a novel game environment. In particular, we investigate whether evaluative human feedback (through interactive RL) and expert demonstration (through inverse RL) can help RL agents to learn to cooperate better. We report two main findings. Firstly, we find that the amount of feedback given has a positive impact on the accumulated reward obtained through cooperation. That is, agents trained with a limited amount of feedback outperform agents trained without any feedback, and the performance increases even further as more feedback is provided. Secondly, we find that expert demonstration also helps agents’ performance, although with more modest improvements compared to evaluative feedback. In conclusion, we present a novel game environment to better understand the emergence of cooperative behaviour and show that providing human feedback and demonstrations can accelerate this process.
Evaluation of a Coreference Resolution Model on Mention Patterns with Common Ground

Efficient communication between humans and AI requires the AI to understand references that are made during the conversation.For this, the AI needs to establish common ground with the human in order to make correct judgments and take the right actions [1].Common ground is the shared information that speakers rely on during a conversation, which is built up over time as the speakers share more interactions [2].In our research, we focus on the role of common ground in resolving third-person references in humanrobot social interaction.In social dialogue, these references are often vague and contextdependent.Especially in a conversation between two well-acquainted individuals, the references to people they both know can become highly ambiguous.Through shared interactions, these references become increasingly efficient (i.e.shorter).This comes at the cost of intelligibility for outsiders who do not share the common ground [3].For machines that have no understanding of the common ground then, these references are difficult to interpret and relate to other references.In future work, we aim to approach this problem by building a reference resolution model which utilises a knowledge-rich approach and builds up common ground with a human in an interactive setting, where the robot and the human can coordinate to form the common ground together.In preparation for this, here we first investigate the limitations of existing reference resolution models in social interaction scenarios by evaluating to what extent they utilise common ground in resolving vague references in social dialogue.Our expectation is that these models do not fare well with references that require long-distance common ground knowledge, but that providing them with the relevant background knowledge will improve performance.Machine learning-based coreference resolution models can achieve impressive performance (e.g.[4,5]).However, most datasets used in coreference resolution tasks consist of snippets of formal text, e.g. from news articles.These datasets are not useful for