Reviewerly/exHarmony huggingface dataset:
Handling All Unit Propagation Reasons in Exact Max-SAT Solvers

Unit propagation (UP) based method are widely used in Branch and Bound (BnB) Max-SAT solvers for detecting disjoint inconsistent subsets (IS) during the lower bound (LB) estimation. UP consists in assigning to true (propagating) all the literals which appear in unit clauses. The existing implementations of UP only consider the first unit clause causing the assignment of each variable, thus the propagations must be done and undone chronologically to ensure that all the unit clauses are properly exploited. Max-SAT BnB solvers transforms the formulas to ensure IS disjointness. These transformations remove clauses from the formula thus propagations are frequently undone. Since the propagations are undone in chronological order, many useless unassignments and reassignments are performed. We propose in this paper a new unit propagation scheme which considers all the unit clauses causing the assignment of the variables by UP. This new scheme allows to undo propagations in a non-chronological way and thus it reduces the number of redundant propagation steps made by BnB solvers. We also show how the information available with this new scheme can be used to influence the characteristics of the IS built by BnB solvers. We propose a heuristic which aims at reducing their size, and thus improving the quality of the LB estimation. We have implemented the new propagation scheme as well as the IS building heuristic in our solver MSsolver. We present and discuss the results of the experimental study we have performed.
Graph Convolution over the Semantic-syntactic Hybrid Graph Enhanced by Affective Knowledge for Aspect-level Sentiment Classification

Aspect-level sentiment classification (ASC), detecting and predicting the sentiment polarity of the given aspecs, has attracted increasing attention in the field of Natural Language Processing (NLP). Recent studies in ASC leveraged the graph based on the dependency tree of the context to incorporate the syntactic information and structure of a sentence for better relation extraction. Some researchers noted that existing methods ignored semantic relations or failed to consider affective dependency information, and then proposed several state-of-art methods tackling the above two limitations. However, these approaches failed to consider both informative relations simultaneously. Therefore, we explore and propose a novel solution based on semantic latent graph and SenticNet to leverage semantic and affective information. Specifically, we build a latent semantic graph based on self-attention networks to parse semantic relations within the contexts. In addition, we utilize affective knowledge from SenticNet to enhance the dependency graphs of sentences. Moreover, we use the gate mechanism to dynamically combine information from both the enhanced dependency graphs and latent semantic graphs. Experimental results on three benchmark datasets illustrate the effectiveness and state-of-the-art performance of our model.
EDUCATION OF THE FUTURE: AN ANALYSIS OF DEFINITIONS (LITERARY REVIEW)

The education of the future requires new approaches to the implementation of the target principles of this sphere of social activity. The reason for the transformation of educational principles and ideas is a cardinal change in the format of educational space associated with the active introduction of globalization factors and elements of information and digital technologies. The purpose of scientific exploration is to systematize the definitions of future education in the context of the content and format of educational activity. The objectives of the article are to identify the main priorities for the development of education in the short and long term. Methodology, which is able to ensure the implementation of goals and objectives of scientific research, is based on general scientific (analysis, forecasting, systematization), philosophical-scientific (synergetic), and prospective scientific and pedagogical (developmental pedagogy, digital pedagogy, pedagogical modeling) elements. A promising direction of research is structuring the definitions of future education in accordance with the actualization of certain clusters of the educational activity (socialization, digitalization, humanization). So, 4 clusters of definitions of future education perspectives are proposed: existential educational dimension, long-term educational strategies, short-term educational planning, futuristic projects in the educational space. The fundamental principle of planning of prospective models of education development will be the concept of education quality, which will include aspects of the purpose of education as a socio-cultural phenomenon and elements of the format of educational space.
A Deep Dilated Convolutional Self-attention Model for Multimodal Human Activity Recognition

Wearable-sensor-based Human Activity Recognition (HAR) has long been a hot topic in ubiquitous computing, which is benefit by the success of deep learning algorithms. The critical difficulties in multimodal sensing environments are how to represent the spatial-temporal dependencies while concurrently extracting features with high characterization. In this work, we propose a self-attention based deep dilated convolution network. Our method uses two channels, named temporal channel and spatial channel, respectively, to extract the readings-over-time and time-over-readings features from sensor signals. The self-attention mechanism helps directly capture the long time dependence of sensor signals. To extract local features while expanding the receptive field and avoiding information loss caused by pooling and upsampling, we use deep dilated convolution, which expanding the receptive field and avoiding information loss caused by pooling and upsampling. Extensive experiments on a self-built dataset and two available benchmark datasets (PAMAP2, OPPORTUNITY) reveal that the effectiveness of our proposed model is more competitive than the state-of-the-art methods in HAR tasks.
Theoretical and Conceptual Approaches to Cyber Theatre

The article addresses the question of integration and dispersion in theatre. Theatre is the art of representation, so it is presented as unified and integral, starting with Aristotle's principle of three unities, through Shakespeare, Calderón de la Barca's The Great Theatre of the World or Erwin Piscator and Walter Gropius's model of total theatre. With the outbreak of the coronavirus pandemic, theatre changed, not only by itself but also by necessity, becoming diffuse and imprecise. It broke with one of its foundations: the encounter between spectators and actors in a designated space. Theatre ceased to be a place of performance and the stage was moved to nowhere. Digital theatre assumed an anti-Aristotelian order; the classical principle of the three unities of place, time and action was broken. However, even though the pandemic shook the foundations of theatre and theatre used all the means offered by new technologies, the fundamental concepts of theatre and theatrical space were not abolished.
The Effect Of English Songs To Improve Student’s Listening Ability

This study aims to determine the student’s listening improvement by using instructional media for English Song, students grade VIII MTs. Muhammadiyah 13 Tanjung Morawa. The lack of students’ listening ability through was caused by the learning condition which was not using media so that the learning process run so monotonous and it impact to the students anthusiasm. This case made the students felt boring. In order to achieve the goals that have been determined, then this study uses a two group pretest and posttest experimental research methods. The number of samples in this research were 20 students. The result of t-observed was 5.8 and t-table was 1.68 it means that t-observed higher than t-table. Because the result of t-observed is higher than t-table, it means that by using the media English songs can showed a significant affect on the improvement of listening VIII MTs. Muhammadiyah 13 Tanjung Morawa. The reseacher sincerely expected that enthusiasm are able to try and apply the appropriate media and in accordance with the material to be taught, one of them is the use of English song media for listening improvement.
Protecting Cloud Information for Government Oversight Audits Using a Zero-Knowledge Protocol

The innovative paradigm of cloud computing as a service has made it one of the most well-known buzzwords in the IT industry.It claims to reduce operating and support expenses while enhancing adaptability, scalability, and dependability.Many would-be cloud customers are wary of making a wholesale switch to the platform because of safety concerns that have yet to be adequately addressed.In this research, we adopt a framework for security subsystems from cloud service providers and use it to examine the most pressing security concerns in cloud computing today.We discuss the strengths and weaknesses of the solutions that have been presented by other scholars.While much progress has been achieved, there is still a lot of work to do to ensure the safety of cloud computing.If cloud computing is going to overcome its security barriers and gain general use, then it has to become a lot better at dealing with consistency, multi-tenancy, and federation security challenges
Pembinaan keterampilan Desain Grafis Bagi Generasi Muda Di Perumahan Griya Elok Pengambiran Kota Padang

Perum Griya Elok is located in the Arai Pinag sub-district, Lubuk Begalung sub-district, Padang city, Perum Griya Elok has a population of approximately 500 residents where these residents come from various races and ethnic religions. The younger generation who are at Perum Griya Elok tend to be unemployed due to limited knowledge and education. That's why we, the devotees, propose to provide an understanding of community service about technology that can generate money, exemplified by coaching using graphic design such as being able to use Photoshop and Coreldraw. The use of Photoshop graphic design now is very promising among being able to do photo editing for weddings, and the Coreldraw application is very promising. Among the creation of logos, posters, billboards themselves really help the youth to develop skills. To make money. With this coaching held, the youth at Griya Elok housing are able to use tools in Photoshop, and make logos with Corel Draw, where in this coaching they are given lectures with practice by providing levels for beginners. The goal is to quickly understand the use of the application where the level itself is from the beginning to the editing process to the design of the image itself.for each language can only be written in one paragraph with the format of one column.
A precise cabin grasping method based on visual guidance

In this paper, aiming at the problems of the key link in the process of automatic transportation of the cabin - cabin grabbing, which has high requirements for safety, the conventional visual guided grabbing method has low accuracy, and the measured motion error cannot be effectively compensated, a visual grabbing safety strategy is proposed, which is verified by experiments combined with the domestic PLC platform. After experimental verification, this method detects position accuracy 0.03mm angle accuracy 0.02°. Meet the detection requirements in the grasping process. It can effectively improve the effectiveness of the automatic grab process of the cabin.
Cognitive Aspects of Cyber-Physical Systems for Pedagogical Rehabilitation: Towards a "STEAM" Approach to Inclusive Education

The paper presents the main ideas, motivating two ongoing research projects, justifying the need to move to STEAM education. The proposed novel type of cyber-physical systems - for pedagogical rehabilitation in inclusive education - is outlined. The role of puppet theatre in maximising the learning outcomes in inclusive education is substantiated. It has been also shown that integrating game, puppet theatre and social robotics is beneficiary in the classroom. Social robots have a significant potential for transition of the cognitive analysis of the behaviour of humans and robots from the physical to the social level. This is the core of the proposed in the paper approach for the STEAM education of the future.
Contact Tracing Applications During The Pandemic Era: A Systematic Literature Review

Covid 19 has become a global pandemic since 2019, which brings not only health problems, but also brings problems to all aspects of human life. There have been many efforts that have been carried out by countries around the world to overcome the pandemic. One of the efforts taken in almost all countries is the use of digital contact tracing applications whose main goal is to reduce the rate of transmission of the disease. But in reality, the use of these applications also brings a negative impact, especially related to the use of personal information. There are many articles that review the use of this application and its side effects. In this paper, we attempt to conduct a systematic literature review on various similar applications issued by various state institutions from previous publications researching the topic, and also discuss various issues related to these applications. It is hoped that the results can be used as a reference for the government to make improvements to similar applications and can also be used as a basis for researchers to be able to carry out further research. Especially by examining the antecedents for worldwide adoption of similar applications.
Preface: The 3rd International Conference of Information &amp; Communication Technology 2021 (ICICTM 2021)

First Page
A secure two-party PIR for privacy applications

The major drawback of existing information retrieval schemes in preserving user privacy is that they either exhibit computationally bounded privacy with intractability assumptions or perfect privacy with high bandwidth utilisation. Today, the essential requirement is to have a bandwidth efficient perfect privacy preserving information retrieval scheme in order to provide effective and guaranteed service to the information retrieving user. Therefore, in this paper, we have constructed a new single database perfect privacy preserving private block retrieval scheme called as 'pepperPBR' using quadratic residuosity as the underlying primitive where private block retrieval (PBR) is a natural extension to private information retrieval (PIR). In this paper, user generates O(6k) bit query and server generates O(2ku + o(n)) bit response where n is the database size, o(n) is the non-trivial server communication cost, u is the number of database blocks, k is the security parameter.
Sentiment Analytics on Chinese Product Boycott from Multiple Data Sources

Sentiment Analysis and Opinion mining is a technique recognizing and drawing out the personalized information underlying a different kind of documents such as text, audio, images and videos. This area of research tries to exaplain the feeling, opinions, emotions of people on something topics. The most relevant classifying a statement as ‘positive’ , ‘negative’ and ‘neutral’ from records/posts obtained from different source system such as Twitter, Facebook , Reddit etc. To predict the sentiment/result of recent Chinese Product Boycott campaign, This paper direct to operate on data received from 9 different sources. In the field of Trade and commerce where traders. Politians and Peoples need to catch public’s point of view, thinking and therefor evaluate people’s reaction about Chinese product. The reasoning behind performing this research is that, the prediction will also help to know what is reason behind this , Chinese product boycott analysis will have a major impact on relationship between India and China trade. Keyword : Sentiment, Chinese Product, Data Sources, Boycott
Backdoor Defence for Voice Print Recognition Model Based on Speech Enhancement and Weight Pruning

Voice print recognition is one of the most mature biometric authentication technologies, and the application of deep neural networks (DNNs) has led to a significant improvement in the accuracy of voice print recognition. However, DNN models can be attacked by backdoor attackers, which poses a serious threat to the security of model for voice print recognition. In this paper, a method is proposed for backdoor defence of voice print recognition model based on speech enhancement and weight pruning. Firstly, input samples are perturbed by superimposing various speech patterns, and the backdoor samples are determined based on the randomness (entropy value) of the prediction classes with perturbed inputs from a given deployment model (malicious or benign). Secondly, the backdoor samples are fed into a network (Deep Complex Convolution Recurrent Network) dedicated for speech enhancement, with which the backdoor samples can be denoised by removing the backdoor noise. Finally, the model is pruned using an automatic progressive weight pruning algorithm, which can avoid the accuracy degradation caused by neurons pruning. Experimental results on the AISHELL speech dataset show that the method not only reduces the success rate of backdoor attacks, but also greatly realizes the purification of the backdoor samples.
The effect of free writing technique on students’ writing ability

The purpose of this research is to solve students' problems in writing narrative text, such as they lack vocabulary and they are difficult in certain generic structures. Students are not interested in Writing skills. Students still have difficulty expressing their ideas and they are bored in writing. Students' writing skills, especially narrative texts, are still low. This research is an experimental research. The purpose of this study was to find out which is more significant between the influence of Free Writing Techniques on Students' Writing Ability in writing narrative texts. Teaching writing narrative texts using free writing techniques or teaching writing narrative texts using conventional methods. The research design used in this study was a quasi-experimental research. The score data was taken from class XI students of SMA N. 5 Pematangsiantar. Which consists of 150 students who were selected by taking classes XI IA3 and XI IA4 as samples. In this study, the scores for writing narrative texts in the control group and the experimental group were used as data collection. There are two data used in this study. Namely: pre-test and post-test. The data were analyzed using the t-test formula. After analyzing the data, the results showed that the t-test was 2.72 and t-table = 2.003. The results showed that the t-test value was higher than the t-table t-test &gt; t-table (2.72 &gt; 2.003). It can be concluded that the application of Free Writing Techniques has a significant effect on Students' Ability in Writing Narrative Texts.
Data-Driven Innovation for Sustainable Creative Practice

We present a film exhibiting eight case studies of projects dealing with the intersections of environmental sustainability, data and technology, which have all been led by and rooted in the creative industries in Scotland.The film highlights how the creative sector has been utilising data and technology to address the climate crisis, by responding artistically to environmental data, as well as developing tools and technologies to empower individual and systemic change.Through presenting the film, we demonstrate the synergies between HCI research and technology-focussed work in the creative industries, in context of the shared goal of sustainability.Our overarching aim is to promote discussion about how knowledge from the creative industries can be seen as a powerful resource to be learned from in HCI and to inspire further HCI design and research, as well as to demonstrate the potential value of collaborative work between creative practice and HCI.Climate Change.Sustainability.Creative Practice.Sustainable HCI.Figure 1.Stills from the film.Left: a still of Rebecca Kaye' artistic representations of environmental data.Middle: an image of Michael Begg's practice of developing musical compositions based on weather data, in this case, experimenting with the sonification of melting ice.Right: An image of Jeni Allison's studio, featuring yarn samples used for her knitwear customisation app.
Earth’s largest volcano has started erupting. What might we expect?

After months of heightened earthquake activity, Earth’s largest volcano has erupted for the first time in 38 years. Previous eruptions of Mauna Loa can give scientists some clues as to what this volcano has in store for Hawai’i.
Optimal Control of Manipulator Using Genetic Algorithm

(GA) is a Metaheuristic-based optimization method that addresses difficult optimization issues by simulating biological evolution and the survival of the fittest principle in natural contexts. The genetic algorithm (GA) method is presented and then assessed on a control issue to determine the optimal control structure for a certain time horizon. It is necessary to identify the various control parameters in order to execute the various control rules. This is ambiguous since there is no straightforward method for calculating these parameters for nonlinear systems. The introduction of the Genetic Algorithm, a metaheuristic optimization technique for determining the ideal nonlinear controller parameters, is our contribution. Using a dynamic model of a two-link rigid robot manipulator, the obtained results support the recommended optimal control strategy for the regulation and trajectory tracking problem, which is based on intelligent control and GA.
Automated Privacy Network Traffic Detection via Self-labeling and Learning

With the increasing popularity of mobile devices, privacy leakage has become more and more serious. The inappropriate behaviors of mobile APPs have brought substantial security risks to the public (e.g., location leakage). Existing solutions detect privacy leakage based on network traffic analysis. However, they can only detect unencrypted traffic, which leads to failures in the face of encrypted traffic. To solve this challenge, we designed an Automated Privacy Traffic Detection system (APTD). APTD can automatically generate self-labeling privacy traffic datasets, learn to identify the encrypted privacy traffic, and accurately assess the risk of privacy leakage. Due to its automation capability, APTD can directly support privacy leakage detection for newly-emerged applications without any system changes. To comprehensively evaluate APTD, we conducted an experiment on 2327 real-world mobile APPs. APTD automatically generated a labeled dataset containing 27343 real-world encrypted traffic traces. Based on the dataset, APTD identifies privacy traffic, and performs a privacy leakage risk assessment of APPs. The results show that APTD achieves 97% accuracy and 99% recall on our dataset and identifies 12 APPs that transmit high-risk privacy data.
The Effect of Using Cartoon Film on Students’ English Vocabulry Mastery

This study aims to determine whether there is a significant effect of cartoon film media on the vocabulary of English students. This type of research is quantitative research and was conducted using two classes, the experimental class consisted of 30 students and the control class consisted of 30 students. In the data collection technique, the researcher used pre-test, treatment and post-test by giving a reading comprehension test consisting of 10 multiple choice items for each test. The results of this study indicate that there is a significant influence from the use of cartoon film media. This can be seen from the difference between the students’ mean scores from the pre-test and post-test in the experimental class which increased from 44 to 75. The average post-test score in the control class was 52 while the post-test score in the experimental class was 75. Higher than the average value of the control class. That means, the cartoon film media strategy can improve students’ understanding of English vocabulary.