Reviewerly/exHarmony huggingface dataset:
FGNAS: FPGA-Aware Graph Neural Architecture Search

The success of gragh neural networks (GNNs) in the past years has aroused grow-ing interest and effort in designing best models to handle graph-structured data. Asthe neural architecture search technique has been witnessed to rival against humanexperts in discovering performant network topologies, recently, it has been appliedto the field of graphic network engineering. However, such works on graphic NASso far are purely software design and not considering hardware constraints at all.To address this problem, we propose the first SW-HW codesign framework forautomating the deployment of GNNs. Using FPGA as the target platform, ourframework is able to performs the FPGA-aware graph neural architecture search(FGNAS). To evaluate our design, we experiment on benckmark datasets, namelyCora, CiteCeer, and PubMed, and the results show FGNAS has better capabil-ity in optimizing the accuracy of GNNs when their hardware implementation isspecifically constrained.
Evaluation of Sustainability Determinants of Small Farming Systems via Participatory Modeling and Fuzzy Multi-Criteria Processes: The Case Study of Heliciculture in Greece

Feasibility and sustainability of small-scale farming systems are the most critical factors that determine future investments of urban agro-farming while promoting eco-systematic livelihood development and biodiversity. The determination and the diversification of the ambivalent and heterogeneous factors that affect the investment decision making of small farming systems is studied in this work via the application of participatory modeling methodology of regional stakeholders. Defuzzification of the participants' categorical feedback is succeeded applying Fuzzy Analytical Hierarchy Process (F-AHP) to set the pairwise weight matrix of the determinants suggested by the stakeholders. At a second phase, an innovative Fuzzy Cognitive Map (FCM) model is utilized to determine the weighted inter-causalities between all agricultural, environmental, and socio-economic criteria from the F-AHP output. Apart from the concept circumscription, we use the FCM to provide an in-depth scenario analysis including steady state and dynamic evaluation of driver concepts to receiver concepts in the model. The methodology is applied for the case study of heliciculture farming systems in Greece. Results show that sustainability is affected primarily by agricultural and inventory factors and secondarily by social and environmental factors identifying such cradle-to-farm gate life cycle assessment to be of low carbon footprint.
Η τεχνολογία της επαυξημένης πραγματικότητας και σχεδιασμός εφαρμογής

Augmented reality (AR) is one of the biggest technological trends in recent years. AR allows the user to experience the real world, which has been enhanced with digital objects. In this dissertation we will answer the question what is augmented reality. We will also refer to the ways of applying augmented reality as well as the techniques used to implement such applications. Finally, we will design an augmented reality application that includes face, image and plane detection and analyze how it is developed.
How To Find A Legit Online Tutor

The number of online tutors has increased over the years. Now, nearly anyone with a good internet connection and knowledge on a subject can set up a ...
Rethinking Parameter Counting: Effective Dimensionality Revisited

Neural networks appear to have mysterious generalization properties when using parameter counting as a proxy for complexity. Indeed, neural networks often have many more parameters than there are data points, yet still provide good generalization performance. Moreover, when we measure generalization as a function of parameters, we see double descent behaviour, where the test error decreases, increases, and then again decreases. We show that many of these properties become understandable when viewed through the lens of effective dimensionality, which measures the dimensionality of the parameter space determined by the data. We relate effective dimensionality to posterior contraction in Bayesian deep learning, model selection, width-depth tradeoffs, double descent, and functional diversity in loss surfaces, leading to a richer understanding of the interplay between parameters and functions in deep models. We also show that effective dimensionality compares favourably to alternative norm- and flatness- based generalization measures.
Evaluation of communicative competence of experts in the field of education

The article considers the content and specificity of the communication competences of an expert in the field of education. The subjective factors influencing the development of the expert's communication skills were identified. Its communication functions in the process of expertise are described, communication barriers and typical errors in providing information to the subjects are presented. On the basis of the developed criteria, a parametric-index model of evaluating an expert's communicative competences is constructed which it is possible to carry out selection experts for research on pedagogical objects.
LibGuides: Scandinavian Studies: Libraries & Archives

Scholarly resources in Scandinavian Studies, including Denmark, Finland, Greenland, Iceland, Norway, and Sweden. The resources organized here are all freely available and have undergone a selection and evaluation process.
Social and behaviour change communication (SBCC) strategies and the fight against drug abuse in calabar south local government area, cross river state

This research sought to show how SBCC strategies can be used in curbing drug abuse where conventional approaches have failed. The efforts of the Nigerian Drug Law Enforcement Agency (NDLEA) in the fight was scrutinized. A qualitative research design was adopted where In-depth interviews and Focus Group Discussions were adopted as data collection methods. Data gathered were analysed using the constant comparative technique. Findings revealed that the agency’s efforts have not yielded the needed success owing to a number of challenges. Also, the research identified certain gaps in the agency’s campaign activities occasioned by the absence of a suitable communication strategy that is participatory in nature. The researcher therefore recommended that communication activities must be designed using participatory processes while working with existing social and cultural platforms and networks.
A year of change: An analysis of how covid-19 has impacted the data privacy profession in 2020

COVID-19 has brought unprecedented change to countless occupations, and for privacy professionals it has been no exception. As we are approaching the end of the year, this paper summarises the main data privacy challenges faced by privacy professionals due to the pandemic in 2020 and how it has impacted the data privacy profession as such. Has COVID-19 resulted in a shift leading to a new normal for the profession, or has it been business as usual? Taking also into consideration other meaningful events that have shaped 2020, such as the Black Lives Matter movement, Schrems II and Brexit, the paper concludes with what this year has meant for data privacy and an outlook on what to expect next. ©Henry Stewart Publications.
Bibliometric study of the Indian journal of economics

This paper presents Bibliometric study of The Indian Journal of Economics during the period of 2012 to 2019.Researcher has to examined 229 articles has been published during the period of study. The paper examined year wise distribution of articles, subjectwise distribution of articles, in Authorship pattern 397 author was dected, 229 articles have received 3529 citations, Subject facet highest no of articles published i,e. 64 papers have published in commerce. Singh D V is the most prominent author he published 14 authors during the study. Such as Geographical distribution of publication New Delhi is the top total 27 articles published, highest length of articles is 64 pages during the span of study have been analyzed. Keywords: Bibliometric study.
Features of adaptation of first-year students to the conditions of study at the university

The article is devoted to the problem of adaptation of first-year students to the conditions of development of educational programs at the University. The article deals with the problems of students' adaptation to higher education. It describes the difficulties that students have during their studies. The authors consider the im-portance of developing the level of adaptation from school, thereby preparing future students for the new sys-tem in advance. A research was conducted to determine the level of adaptation of students of the pedagogical faculty of the specialty «Preschool education and upbringing» E.A. Buketov of Karaganda University. The results of the study showed that the problem of adaptation of first-year students is one of the most im-portant problems and is still a traditional subject of discussion, and as such, adaptation is the foundation of training in junior courses. Students enter the student team, develop skills and abilities of rational organization of mental activity, realize the vocation to the chosen profession develops an optimal mode of work, also adapts to the teaching staff. Based on the results of the study, conclusions were drawn and recommendations were developed to speed up the process students’ adaptation to the system of education in higher education
This Online eLibrary 2020 is in the process of update

The Online eLibrary 2020 is in the process of update! It is planned to be more user-friendly with a lot of useful functions and other tools for citing and metrics as well as free user export in bib format. All peer-reviewed and published papers from conference proceedings 2020 will be shortly published online here: https://www.sgemsocial.org/index.php/peer-review/jresearch
Developing Digital Learning of English Vocabulary for Students Grade 2 Primary Educational Service Phichit Area 1

Abstract This research to study 1) develop a digital media learning of English vocabulary for grade 2 and 2 students) to compare the learning achievement of english vocabulary for first grade students. And after studying with digital media the scope of the content is about 5 types of vocabulary: body, family, vegetable, fruit and zoo, and creating storyboards of digital learning media. After that, develop digital learning media with Adobe Captivate 3 program, when the development of digital learning media is complete, the materials that have been tested for grade 2 students at Bueng Si Fai School have tried 30 people to compare. Learning achievement English vocabulary for Grade 2 students before and after learning with digital media Learning was found that English vocabulary achievement for Grade 2 students before and after studying with media. Digital learning Are different Where after learning with digital learning materials, there are more results in scoring Therefore, it can be concluded that Learning digital media can improve academic achievement English vocabulary for 2nd grade students. Keywords: Digital Learning, English Vocabulary, Students, Primary Educational Service Phichit Area 1
PENERAPAN PENDEKATAN KOMUNIKATIF (COMMUNICATIVE APPROACH) DENGAN SOSIODRAMA DAN INTERVIEW UNTUK MENINGKATKAN KEMAMPUAN BERBICARA DALAM PEMBELAJARAN KAIWA (PERCAKAPAN BAHASA JEPANG)

This research is based on student difficulty in speaking Japanese. Considering speaking Japanese (kaiwa) in learning Japanese is one of the important things, therefore, an appropriately approach is needed to facilitate students in speaking Japanese. The purpose of this study is to describe the ability to speak Japanese with a Communicative Approach with Sociodrama and Interview, ability to speak with the Translation Method, differences in speaking skills using the Communicative Approach with Sociodrama and Interview and Translation Methods, and the quality of the Communicative Approach with Sociodrama and Interview according to students' opinions in kaiwa learning, The research method is a quantitative experimental method, with Pretest-Posttest Control Group Design. The sample of this study were participants of the Class C LPK Minori course of 2019 academic year. The instruments used were tests and questionnaires. Finding shows that the participant speaking skill is higher in course using the Communicative Approach with Sociodrama and Interview than students used the Translation Method. This finding is supported by questionnaire result indicating that most students consider Kaiwa learning by using the Communicative Approach with Sociodrama and Interview very interesting and can improve their Japanese language skills.Keywords: Japanese, kaiwa, communicative.
Node-Adaptive Regularization for Graph Signal Reconstruction

A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem. In this paper, we propose a node-adaptive regularization for graph signal reconstruction, which surmounts the conventional Tikhonov regularization, giving rise to more degrees of freedom; hence, an improved performance. We formulate the node-adaptive graph signal denoising problem, study its bias-variance trade-off, and identify conditions under which a lower mean squared error and variance can be obtained with respect to Tikhonov regularization. Compared with existing approaches, the node-adaptive regularization enjoys more general priors on the local signal variation, which can be obtained by optimally designing the regularization weights based on Prony's method or semidefinite programming. As these approaches require additional prior knowledge, we also propose a minimax (worst-case) strategy to address instances where this extra information is unavailable. Numerical experiments with synthetic and real data corroborate the proposed regularization strategy for graph signal denoising and interpolation, and show its improved performance compared with competing alternatives.
The Legal Framework of Cybercrime in Palestine

Abstract The rate of committing cybercrimes in Palestine has increased in recent years due to the increased use of the Internet and social media, in addition to the absence of deterrent legislation to combat these crimes. Palestine suffers from legal problems in the field of criminal legislation due to the duplication of penal laws applied in the West Bank and Gaza Strip. This article will discuss the legal framework of cybercrimes in Palestine. The researcher will mainly use historical, analytical, and library research methods for this purpose. The results indicate that the legal framework regulating cybercrimes in Palestine is not unified, and the difference in legislation regulating cybercrimes in Palestine has led to different penalties for cybercrimes, which violates the principle of equality stipulated in the Palestinian Basic Law (Palestinian Interim Constitution). The benefit of this article is to propose some recommendations to develop Palestinian laws in order to combat cybercrimes.
LibGuides: HACC User Support: Chat with User Support

Tech support provides effective and timely technical support for all HACC students, faculty, and staff.
The components and qualities of meaningful user experience design for Chinese elderly

User experience design is like a pyramid, and the bottom layer is functional and usable. Nowadays, more and more interaction design research focuses on meaningful user experience at the top of the pyramid. This also means that measuring a good interaction design is more focused on whether it is able to achieve the psychological needs of users. After reviewing the understanding and research of meaningfulness in philosophy, psychology, and design, it is found that meaningful user research now stays at the framework and definition levels. In order to realize the gradual application in practice, this study narrowed the target group to the Chinese elderly group and conducted semi-structured interviews with the Chinese elderly and the interaction designers who designed for them. Laddering theory is used to analyze the interview content at three levels of attributes-consequences-values. After completing the conversion of qualitative data to quantitative data, the analysis obtained the components and quality of meaningful user experience for Chinese seniors. For Chinese elderly interviewees, there are six meaningful user experience components: belongings and love, self-esteem, self-realization, aesthetic, social participant and social value. There are also four interaction design attributes that older users value more. Ftom the interaction designer's data, there are four components of belongings and love, selfesteem, self-realization, social participant, and three design attributes. The study also conducted an in-depth analysis and comparison of the two sets of data and obtained the similarities and differences of meaningful user experience from the perspectives of Chinese elderly and interaction designers. The research results help us to further transform the meaningful user experience into practice and conduct an in-depth analysis of the Chinese seniors' pursuit of meaningfulness in the user experience.
Learning Movement Strategies for Moving Target Defense

The field of cybersecurity has mostly been a cat-and-mouse game with the discovery of new attacks leading the way. To take away an attacker's advantage of reconnaissance, researchers have proposed proactive defense methods such as Moving Target Defense (MTD). To find good movement strategies, researchers have modeled MTD as leader-follower games between the defender and a cyber-adversary. We argue that existing models are inadequate in sequential settings when there is incomplete information about rational adversary and yield sub-optimal movement strategies. Further, while there exists an array of work on learning defense policies in sequential settings for cyber-security, they are either unpopular due to scalability issues arising out of incomplete information or tend to ignore the strategic nature of the adversary simplifying the scenario to use single-agent reinforcement learning techniques. To address these concerns, we propose (1) a unifying game-theoretic model, called the Bayesian Stackelberg Markov Games (BSMGs), that can model uncertainty over attacker types and the nuances of an MTD system and (2) a Bayesian Strong Stackelberg Q-learning (BSS-Q) approach that can, via interaction, learn the optimal movement policy for BSMGs within a reasonable time. We situate BSMGs in the landscape of incomplete-information Markov games and characterize the notion of Strong Stackelberg Equilibrium (SSE) in them. We show that our learning approach converges to an SSE of a BSMG and then highlight that the learned movement policy (1) improves the state-of-the-art in MTD for web-application security and (2) converges to an optimal policy in MTD domains with incomplete information about adversaries even when prior information about rewards and transitions is absent.
WordsWorth Scores for Attacking CNNs and LSTMs for Text Classification

Black box attacks on traditional deep learning models trained for text classifica- tion target important words in a piece of text, in order to change model prediction. Current approaches towards highlighting important features are time consuming and require large number of model queries. We present a simple yet novel method to calculate word importance scores, based on model predictions on single words. These scores, which we call WordsWorth scores, need to be calculated only once for the training vocabulary. They can be used to speed up any attack method that requires word importance, with negligible loss of attack performance. We run ex- periments on a number of datasets trained on word-level CNNs and LSTMs, for sentiment analysis and topic classification and compare to state-of-the-art base- lines. Our results show the effectiveness of our method in attacking these models with success rates that are close to the original baselines. We argue that global importance scores act as a very good proxy for word importance in a local context because words are a highly informative form of data. This aligns with the manner in which humans interpret language, with individual words having well- defined meaning and powerful connotations. We further show that these scores can be used as a debugging tool to interpret a trained model by highlighting rele- vant words for each class. Additionally, we demonstrate the effect of overtraining on word importance, compare the robustness of CNNs and LSTMs, and explain the transferability of adversarial examples across a CNN and an LSTM using these scores. We highlight the fact that neural networks make highly informative pre- dictions on single words.
Deterministic and Efficient Interactive Coding from Hard-to-Decode Tree Codes.

The field of Interactive Coding studies how an interactive protocol can be made resilient to channel errors. Even though this field has received abundant attention since Schulman's seminal paper (FOCS 92), constructing interactive coding schemes that are both deterministic and efficient, and at the same time resilient to adversarial errors (with constant information and error rates), remains an elusive open problem. An appealing approach towards resolving this problem is to construct an efficiently encodable and decodable combinatorial object called a tree code (Schulman, STOC 93). After a lot of effort in this direction, the current state of the art has deterministic constructions of tree codes that are efficiently encodable but require an alphabet of size logarithmic (instead of constant) in the depth of the tree code (Cohen, Haeupler, and Schulman, STOC 18). We emphasize that we still lack (even heuristic) candidate constructions that are efficiently decodable. In this work, we show that tree codes that are efficiently encodable, but not efficiently decodable, also imply deterministic and efficient interactive coding schemes that are resilient to adversarial errors. Our result immediately implies a deterministic and efficient interactive coding scheme with a logarithmic alphabet (i.e., 1/ log log rate). We show this result using a novel implementation of hashing through deterministic tree codes that is powerful enough to yield interactive coding schemes.
NAIVE BAYES ALGORITHM TO PREDICT STUDENT SUCCESS IN A COURSE

Good coordination between lecturers is needed to ensure the relatively uniform quality of education from the delivery of material by the different lecturers. By knowing the success information from several classes, it is expected that the success of other classes can be predicted. This research is using a quantitative analysis method with Naive Bayes Algorithm methodology in passing decisions on IIT (Introduction to Information Technology ) subject. The result gives the pattern of training data in mean and standard deviation towards three attributes, i.e. tasks, mid-semester and final exam score, which can classify or predict graduation for new data test. The pattern of this equation can also be used for other class classification, on the same or different subjects.
This is the second article in the test

Through the cooperation of many people and registering accounts with different identities, the whole process and all-round test of the contribution system can be carried out, including but not limited to the use of the author's identity for contribution, the use of publishing editor's identity for contribution process service, the use of journal editor's identity for manuscript, column editor's identity for manuscript review, and the use of editor's identity for arrangement and proofreading Editing, typesetting and proofreading of manuscripts.
Biggest Mistakes To Avoid When Hiring A Web Developer

Hiring can be tricky when it comes to software and technologies. Often companies know about the requirements they need to complete the project but do not ...