Reviewerly/exHarmony huggingface dataset:
El U-Learning, un nuevo modelo pedagógico inclusivo en la universidad ecuatoriana

Technological advances in all human activities have ledto the emergence of new digital pedagogical models that promote access to training resources from anywhere. This research analyzes the application of U-learning as an inclusive pedagogical model in Ecuador’s higher education. A descriptive study was carried out, with the participation of100 students and 18 teachers from the eighth semester of the Computer Science career, Faculty of Philosophy, University of Guayaquil, through the use of online courses developed in the online platform Microsoft Teams, as well as the use of digital platforms (Facebook, YouTube, Twitter), the levels of acceptance, satisfaction and academic performance were evaluated, and the study was carried out during the second part of the semester under study. A structured questionnaire of 15 questions and 5 items was applied. The results showed high percentages in relation to the improvement of the academic performance of the students by being able to deliver their assignments and presentations on time. It was also recorded that this model provided equal opportunities ineducation for all students, and it was also reflected that it allows the reinforcement of knowledge acquired through the recorded classes available at all times. It was concluded that U-learning has a high potential for acceptance among the university community, promotes collaborative work, and improves individual and collective performance, so it is necessary to generate institutional policies that allow its incorporation into the curriculum within Ecuador’s higher education.
Penarapan Algoritma Prefix Code Dalam Kompresi File Video

Data compression technology is the process of converting a set of data into a lower coded representation of data that is not encoded with a certain encoding. Data compression is done by encoding each character into a shorter coded message, in order to save storage space requirements and time for data transmission. Compressing is used to speed up the sending process from uncoded characters to certain encoded characters. By compressing, large data will be reduced in size so as to save storage capacity. In this study, using the Prefix Code algorithm, by using this method the compression results are very good in making data transmission and transferring video file allocations easier and faster. By doing compression, large data will be reduced in size so that it can save storage space. There are many types of methods or algorithms in video file compression, but in this algorithm the writer only wants to know the compression process using the Prefix Code algorithm using the C1 code where the author has successfully compressed a video file with the prefix code algorithm using the C1 code has the ability to compress video file 37, 5% on a video file. Keywords : Compression , Video, File , Prefix Code, Algorithm .
Research Methods in Cognitive Psychology

Cognitive Psychology (CP) in the last 50 years has shown impressive development, producing a large body of data mainly concerned with specific elements of the complex cognitive architecture of the mind. The focus on single processes, in large part necessarily narrow and detailed, has not prevented the development of general concepts, paradigms, and models that can be useful to all areas of psychology.
Research on multimedia Video Synthesis based on color segmentation

Nowadays, the rapid development of film, television, animation and other multimedia industries requires more efficient video processing. Under the dual pressure of cost and time limitation, higher requirements are put forward for rapid video synthesis. Combining the commonly used RGB color space and HSV color space, a fast image segmentation method is proposed. Firstly, a Mask is calculated by using the threshold segmentation method. In order to reduce the influence of black on the final result, inrange used the second Mask to make the composition. The final result is multiplied by the original image, and the effect of black on threshold segmentation is effectively eliminated on the premise of not reducing efficiency and image quality, so as to achieve the most ideal effect. Compared with the previous real-time image segmentation processing, this method has been greatly improved in the degree of code simplicity, operation efficiency and cost. In the aspect of color extraction, as it is completed in the RGB color space domain, there is almost no color missing or redundant. The real-time segmentation and splicing of images can meet the basic needs of film and television shooting and greatly improve its efficiency.
Home Alone: The First English Coronavirus Lockdown and the Right to Liberty (Article 5 ECHR)

The unprecedented situation caused by the Coronavirus was the justification for the lockdowns that were imposed across the globe. Inevitably, measures of this kind engaged the fundamental right to liberty. This paper focuses on The Health Protection (Coronavirus, Restrictions) (England) Regulations 2020. In a democratic society, it is essential to make sure legislation complies with the human rights we are entitled to and to hold the legislator accountable if it is not. As a result, the movement restrictions that were hastily put in place should be critically evaluated, in order to ascertain whether this right was overlooked; While public health is a vital consideration, intrusive measures can only ever be justified if individual rights have been taken into consideration.
Robust Imitation via Decision-Time Planning

The goal of imitation learning is to mimic expert behavior from demonstrations, without access to an explicit reward signal. A popular class of approaches infers the (unknown) reward function via inverse reinforcement learning (IRL) followed by maximizing this reward function via reinforcement learning (RL). The policies learned via these approaches are however very brittle in practice and deteriorate quickly even with small test-time perturbations due to compounding errors. We propose Imitation with Planning at Test-time (IMPLANT), a new algorithm for imitation learning that utilizes decision-time planning to correct for compounding errors of any base imitation policy. In contrast to existing approaches, we retain both the imitation policy and the rewards model at decision-time, thereby benefiting from the learning signal of the two components. Empirically, we demonstrate that IMPLANT significantly outperforms benchmark imitation learning approaches on standard control environments and excels at zero-shot generalization when subject to challenging perturbations in test-time dynamics.
Strings-and-Coins and Nimstring are PSPACE-complete

We prove that Strings-and-Coins, the combinatorial two-player game generalizing the dual of Dots-and-Boxes, is strongly PSPACE-complete on multigraphs. This result improves the best previous result, NP-hardness, argued in Winning Ways. Our result also applies to the Nimstring variant, where the winner is determined by normal play; indeed, one step in our reduction is the standard reduction (also from Winning Ways) from Nimstring to Strings-and-Coins.
The Implications of Blockchain for Knowledge Sharing

Blockchain (BLK) is believed to have the potential to disrupt traditional business models through inherent features such as distributed, decentralized, peer to peer, and security-by-design. However, the academic community mostly dedicated its BLK research to financial and more recent supply chain disciplines, overlooking BLK implications in other domains. This research aims to fill the research gap of BLK implications for knowledge management by investigating the potential effects of BLK use for knowledge sharing. To do so, four state-of-the-art real use cases, namely, Orvium, ARTiFACTS, Everipedia, and Steem, have been reviewed and explored here. We identified the impact of BLK on the antecedents and benefits of knowledge sharing through content analysis of available data on websites and white papers of associated cases. The results were categorized according to benefits (cost reduction, growth, intangible benefits) and individual antecedents of knowledge sharing (intention, motivation, reciprocity, trust). The results of this research paper provide insights into the research community by presenting the current state and future research avenues.
SISTEM PAKAR IDENTIFIKASI KERUSAKAN PADA BUDIDAYA LEBAH MADU (Apis Cerena) MENGGUNAKAN METODE CERTAINTY FACTOR

Expert systems which are part of artificial intelligence and have an important role in the development of information technology in various fields, expert systems answer all the problems we have faced by providing the right solutions based on one's expertise in a field. The expert system for identifying damage to the management of Apis Cerana bee cultivation is a practical solution in treating and repairing damage caused by pests and diseases. Identification of damage to the management of Apis Cerana bee cultivation using a certainty factor method, which will be assessed for its accuracy level by an expert. The result of using certainty factor method is definite proof or not a fact or diagnosis of damage caused by pests and diseases in Apis Cerana bee cultivation. The percentage level of certainty of damage to the management of Apis Cerana beekeeping is obtained and determined by an expert and implemented into a Web-based system.
Adaptive Stacked Graph Filter

We study Graph Convolutional Networks (GCN) from the graph signal processing viewpoint by addressing a difference between learning graph filters with fully-connected weights versus trainable polynomial coefficients. We find that by stacking graph filters with learnable polynomial parameters, we can build a highly adaptive and robust vertex classification model. Our treatment here relaxes the low-frequency (or equivalently, high homophily) assumptions in existing vertex classification models, resulting a more ubiquitous solution in terms of spectral properties. Empirically, by using only one hyper-parameter setting, our model achieves strong results on most benchmark datasets across the frequency spectrum.
LibGuides: A Guide for Reluctant Teen Readers: Genres and Formats to Explore

This guide is a resource for teens (ages 13-18) who may be reluctant to read, who struggle to enjoy books, or who need a starting place for rekindling their previous love for reading.
Emergency remote teaching in low-resource contexts: How did teachers adapt?

The COVID-19 pandemic forced students and teachers to engage in emergency remote learning Remote learning is particularly challenging for students and teachers in low-resource contexts We aim to analyze the adaptation process of teachers who engaged in remote emergency teaching in low-resource contexts We conduct ten interviews with teachers who provided emergency online teaching in Lebanon We show that there was a decrease in synchronous student-teacher, student-content, and student-student interactions due to the scarcity of resources We also show how the teachers adapted their practice to cope with these challenges, and how their adaptation process increased asynchronous student-teacher and student-content interactions © ICCE 2020 - 28th International Conference on Computers in Education, Proceedings All rights reserved
Virtual Reality to Promote Real del Monte, Mexico

The development of a virtual reality app based on the old English Pantheon, located in the Magic Town of Real del Monte, Mexico, is addressed in this text. The purpose of the project is that people can take a virtual tour through the pantheon with a smartphone to know the charm and mystery of its tombs, as well as digitally preserve the place in spite of its continuous deterioration over time. All the stages of the creation of the virtual scenery are described in detail, such as: storyboard, 3D modeling, UV mapping, texturing, lighting, and rendering; as well as the stages to realize the application in virtual reality, such as: camera adaptation, plugins’ installation, creation of scripts, relation of camera to the character, and creation of the Android APK. This app offers new ways of advertising historical places of the region and, at the same time, promoting tourism
Development of mobile academic information system (AIS) UIN Syarif Hidayatullah Jakarta based on Android with performance evaluation based on ISO/ IEC 25010

Academic information systems are used to present information and organize administration related to academic activities. UIN Jakarta has an academic information system called AIS (Academic Information System) that can be accessed through a website or Android mobile application. 13 of 39 users complained about its performance. The author has interviewed one of PUSTIPANDA's staff and got information that the current version of AIS Mobile was built using hybrid Android. In terms of performance based on ISO/IEC 25010, an Android application built using native Android is better than using hybrid Android. Therefore, the author researched the development of AIS Mobile using native Android because it can create applications with the best performance. The results of the research are in the form of AIS Mobile applications that have better performance than the previous version.
The Killer Inside Us: Law, Ethics, and the Forensic Use of Family Genetics

A new era of criminal investigation has dawned in which decades-old cold cases are being solved through the forensic use of consumer genetic databases. Law enforcement increasingly harnesses the power of these databases to which individuals have uploaded their DNA in order to explore and understand their genealogy, health, and other highly personal attributes. By surreptitiously accessing these databases, law enforcement can track down criminal targets based on their family relation to any individuals populating the databases. While a growing number of cases have figured prominently in law enforcement’s use of these databases—none has demonstrated the power and reach of these databases as much as the Golden State Killer case. As that case demonstrates, alongside this new genetic search capability, new legal and ethical concerns emerge. This article identifies, through the example of the Golden State Killer case, those concerns and proposes the kind of balancing test that a court encountering a legal challenge to the forensic use of direct-to-consumer databases should perform. This challenge has not yet been made, but when it is, the courts will have to balance the potent crime-solving benefits of genetic search technology against the privacy interests of the various affected individuals. In the process, this article also examines applicable legal doctrine from various cases in which courts have grappled with expansive and probing technologies and their threat to reasonable expectations of privacy. Central foci are the courts’ mounting discomfort with the long-established third-party doctrine and, correspondingly, their emerging embrace of the equilibrium-adjustment theory of Fourth Amendment jurisprudence pursuant to which courts redraw Fourth Amendment protections as technology becomes more invasive.
A Comparison of NoSQL and Relational Database Management Systems (RDBMS)

Relational databases (RDBMS) have led the database market since its development by Edgar Codd in 1970 (Shuxin & Indrakshi, 2005). A more recent model that has appeared in the database market is known as NoSQL and it is quickly gaining ground. The new entrant is a non-relational data store which is being deployed massively in the scaled website settings where relational database features are less needed and Better-quality performance in the area of data retrieval matters. NoSQL also known as non-relational databases compliments relational databases and are now used by the world's largest organizations such as Facebook, Amazon, and Google. Both models are good in specific areas and for specific applications. Depending on what issues are to be solved by the company, it will determine the choice of a database model to be adopted. Some organizations, however, prefer to make use of a hybrid database which is the Combination of both NoSQL and relational databases otherwise referred to as multi-model database. The essence of this paper is to bring to the fore the importance of this relatively new technology and clearly show its architecture. NOSQL security features will be compared with the better-known relational databases for better understanding. This review will enable ease of choice for those who have the need for such databases or facilitate the choice to embrace the trending practice of combining the two in the same application to form a hybrid database
Exploiting Beam Search Confidence for Energy-Efficient Speech Recognition

With computers getting more and more powerful and integrated with our daily lives, the focus is increasingly shifting towards more human-friendly interfaces, making Automatic Speech Recognition (ASR) a central player as the ideal means of interaction with machines. Consequently, interest in speech technology has grown in the last few years, with more systems being proposed and higher accuracy levels being achieved, even surpassing Human Accuracy . While ASR systems become increasingly powerful, the computational complexity also increases, and the hardware support has to keep pace. In this paper, we propose a technique to improve the energy-efficiency and performance of ASR systems, focusing on low-power hardware for edge devices. We focus on optimizing the DNN-based Acoustic Model evaluation, as we have observed it to be the main bottleneck in state-of-the-art ASR systems, by leveraging run-time information from the Beam Search. By doing so, we reduce energy and execution time of the acoustic model evaluation by 25.6% and 25.9%, respectively, with negligible accuracy loss.
Long Run Leadership Production and Selection Model for Democracies in Africa

Within the broad agenda of economic development, we suggest a model of leadership production and selection which shows how the optimal number of people required to bridge the gap between actual and potential economic performance could be raised and selected into public office.The honesty and competence of those selected helps to overcome the considerable inertial against take-off of economic development by inculcating common values in peoples from across diverse groups.By imbibing common norms through the school system, we generate economics of scale which otherwise would not be available in scattered, self-governing and well-run communities.The selection process uses the school system to make social progress an important leadership concern and economic advancement an important part of individual utility function.In generating this special breed through the school system, the incompetent individuals are screened out from the competent individuals as well as the honest from the dishonest ones.The honest individuals are sorted into three ability categories for public governance for the three tiers of government in democratic societies.The ultimate aim is to motivate every family towards producing individuals whose characters and competences are compatible with the requirements of developmental states.
Data Processing System Hospitalization Web-Based In Hospital

Hospitals as health service agencies need the existence of an information system that is accurate and reliable, and sufficient enough to improve services to patients. Data management in hospitals is one of the important components in realizing an information system in hospitals, namely for managing health service data in the form of a web-based inpatient data processing system in hospitals. The object of this research is the inpatient installation at the General Hospital of Assalam Gemolong Sragen. The flow of inpatient data processing procedures at the Assalam Gemolong Sragen public hospital is still done manually, starting from inpatient registration to processing incoming patient data, leaving patients and moving patients having several problems. One of the efforts to overcome these obstacles is by building a webbased inpatient data processing information system in the hospital. This type of research is a descriptive study conducted with the method of data collection, observation and interviews using a cross sectional approach. The research method consists of 4 stages: system planning, system analysis, system design and system implementation. The aim of this research is to create a web-based inpatient data processing information system in the hospital so that it can improve the ongoing system and as input for decision making in the inpatient unit. The result of this study is a web-based inpatient data processing system at the Assalam Gemolong General Hospital in Sragen. Inpatient data processing system is made web-based with the hypertext prepocessor programming language (PHP) and data storage with MY SQL.
GN-Transformer: Fusing AST and Source Code information in Graph Networks

As opposed to natural languages, source code understanding is influenced by grammar relations between tokens regardless of their identifier name. Considering graph representation of source code such as Abstract Syntax Tree (AST) and Control Flow Graph (CFG), can capture a token’s grammatical relationships that are not obvious from the source code. Most existing methods are late fusion and underperform when supplementing the source code text with a graph representation. We propose a novel method called GN-Transformer to fuse representations learned from graph and text modalities under the Graph Networks (GN) framework with attention mechanism. Our method learns the embedding on a constructed graph called Syntax-Code Graph (SCG). We perform experiments on the structure of SCG, an ablation study on the model design and the hyper-paramaters to conclude that the performance advantage is from the fusion method and not the specific details of the model. The proposed method achieved state of the art performance in two code summarization datasets and across three metrics.
Stability of Model that Makes Automated Comparison Between Market Demands and University Curricula Offer

The stability of a model that makes automated comparison between labor market demands and university curricula has a great importance. The statistics that will be drawn from our model should be consistent results for the long time. Therefore, during our work, some cases are presented that prove the stability of the model. The first test will be by removing stop words to compare them later with the corpus that contains stop words. Various tests will also be conducted such as increasing the volume of the corps and deleting some contests from the corps. Another test that will be made is cross validation with different results. Finally, our model is compared with another model that compares textual content between different corpuses. All of these tests will prove the stability of our automated model that makes comparison between market demands and university curricula.
ARWALK: A Tool to Assist Indoor Navigation with Augmented Reality

Augmented reality is a useful technology for learning about people with Down Syndrome (DS).These people have impaired psychomotor skills in addition to having difficulties in understanding.This work proposes to create an internal navigation application with an augmented reality interface.It allows for greater autonomy and well-being of these people, supporting them in this type of environment.Based on tests performed in simulated environments, it can be useful for people with difficulties in locomotion and understanding.
The Relevance of Çatalhöyük Reflexive Diaries

This paper presents the results of the analysis of excavation diaries from Catalhoyuk recorded under the principles of the reflexive method as defined by Ian Hodder and his colleagues. The main purpose of the analysis was examining the content of excavation diaries to evaluate how this contributes to improving the credibility of primary data. The investigation led to the identification of relevant and trivial information for such purpose. Overall, this study suggests that archaeologists should be aware of such distinctions for producing higher quality records.