Reviewerly/exHarmony huggingface dataset:
DEPTH DATA ASSISTED HUMAN ACTION RECOGNITION: A FINE GRAINED SURVEY

One of the most active research fields of computer vision [1] is video-assisted human action recognition. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All of the strategies are grouped into two categories: deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. Following that, we examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of both depth and skeleton-based techniques in this discussion.
RDC Library: RDC Library Services and Resources during COVID-19: Home

Information about Red Deer College Library services, resources, and spaces, during the COVID-19 Pandemic.
Authors' Awareness of International Publishing Standards and Legal Deposit Obligations

Knowledge and practice of publishing standards and legal deposit laws are the hallmarks of today's authorship. This paper investigates Nigerian authors' awareness of international publishing standards and their legal deposit obligations which are critical variables for both Universal Bibliographic Control and Universal Availability of Publications. The descriptive research design was adopted for this study which was conducted in Enugu State in South, East Nigeria. The population was made up of 70 librarians in the Nnamdi Azikiwe Library and the Department of Library and Information Science of the University. The data collected were analyzed using frequency counts, standard deviation and mean scores. The highest level of awareness of authors of international publishing standard was that 'web resources now have DOI', followed by ISBN for books, CIP for publications, the importance of CIP and ISMN for music publications. The study revealed that authors play critical roles in the maintenance of international publishing standards. While the authors were aware of their publishers' obligations, they were not aware of the provisions of the legal deposit law. A digital nervous system of shared responsibilities for the maintenance of international publishing standards and the implementation of legal deposit provisions in Nigeria, and indeed any other country is proposed. This is the mainstay of the paper's originality. It is argued that a functional identification and integration of the burgeoning stakeholders into a digital nervous system define the future from the foreground for improved international publishers' standard and compliance with the extant depository law, for Nigeria and indeed, for most developing countries.
Comparative analysis of generative adversarial networks

Every field in this world is moving towards automation. Technology proves to be a tool that can create automated processes. Generative Adversarial Networks (GANs) are discovering structure in data which allows them to create realistic data. In this paper, we provide a comparative analysis of the two generative models to generate images which are tested on MNIST and Fashion MNIST datasets. Out of GAN and DCGAN, we determine the method which is more efficient with the minimum number of losses on the basis of different parameters.
Energy and SLA aware Dynamic Threshold Selection Algorithm for efficient Migration of Virtual Machines

Cloud computing became a promising paradigm for entrepreneurs to host their applications, without any cark about their infrastructure needs. The key concept virtualization was introduced later to make the cloud services more efficient and reliable. Unpredictable request of load at runtime is the main reason for host oversubscription. In order to balance the load among the hosts of a datacenter, the live migration process was introduced recently, which moves the virtual machines of oversubscribed host to another host. Resource utilization threshold is the key value in finding the host oversubscription and any miscalculations in threshold selection leads to the exceeded SLA(Service Level Agreement) violations and energy consumption. Although many former threshold selection models like THR, MAD, IQR and LRR are introduced for threshold selection, they are still suffering in reducing the SLA violations and energy consumption. In order to address the above limitations in threshold selection process, we proposed the energy and SLA aware dynamic threshold selection algorithm (SLAPT), to ensure the efficient load balancing among the hosts.  Simulations with cloudsim toolkit, shown the proposed SLAPT threshold selection algorithm minimized the SLA violations and energy consumption, when compared to the former threshold selection models.
Some applications of independent compatible edges topology

In this article some applications of independent compatible edges topology τICE on directed graphsare introduced. This application includes some aspects. Firstly, medical applications such as voluntary movement of the muscle, work of heart, and pathway involving with neural sensation and motorresponse. Secondly, vital applications such as world wide web and operational problems recovery inairlines.
Bayesian Experimental Design for Intractable Models of Cognition

Author(s): Valentin, Simon; Kleinegesse, Steven; Bramley, Neil R; Gutmann, Michael; Lucas, Chris | Abstract: Bayesian experimental design (BED) is a methodology to identify designs that are expected to yield informative data. Recent work in cognitive science considered BED for cognitive models with tractable and known likelihood functions. However, as cognitive models have become more complex and richer, their likelihood functions are often intractable. In this work, we leverage recent advances in BED for intractable models and demonstrate their application on a set of multi-armed bandit tasks. We further propose a generalized latent state model that unifies two previously proposed models. Our experiments show that data gathered using optimal designs results in improved model discrimination and parameter estimation, as compared to naive designs. Furthermore, we find that increasing the number of bandit arms increases the expected information gain in experiments.
Improving Medical Image Decision Making by Leveraging Metacognitive Processes and Representational Similarity

Author(s): Hasan, Eeshan; Trueblood, Jennifer; Eichbaum, Quentin; Seegmiller, Adam; Stratton, Charles William | Abstract: Improving the accuracy of medical image interpretation is critical to improving the diagnosis of many diseases. Using both novices (undergraduates) and experts (medical professionals), we investigate methods for improving the accuracy of a single decision maker by aggregating repeated decisions from an individual in different ways. Our participants made classification decisions (cancerous versus non-cancerous) and confidence judgments on a series of cell images, viewing and classifying each image twice. We first applied the maximum confidence slating algorithm (Koriat, 2012), which leverages metacognitive ability by using the most confident response for an image as the `final response'. We also examined algorithms that aggregated decisions based on image similarity, leveraging neural network models to determine similarity. We found maximum confidence slating improves classification accuracy for both novices and experts. However, aggregating responses on similar images improves classification accuracy for novices and not experts, suggesting differences in the decision mechanisms of novices and experts.
HOW SHOULD AGENTS ASK QUESTIONS FOR SITUATED LEARNING? AN ANNOTATED DIALOGUE CORPUS

Intelligent agents that are confronted with novel concepts in situated environments will need to ask their human teammates questions to learn about the physical world. To better understand this problem, we need data about asking questions in situated task-based interactions. To this end, we present the Human-Robot Dialogue Learning (HuRDL) Corpus - a novel dialogue corpus collected in an online interactive virtual environment in which human participants play the role of a robot performing a collaborative tool-organization task. We describe the corpus data and a corresponding annotation scheme to offer insight into the form and content of questions that humans ask to facilitate learning in a situated environment. We provide the corpus as an empirically-grounded resource for improving question generation in situated intelligent agents.
Building a Knowledge Graph for the Air Traffic Management Community

Historically, most of the focus in the knowledge graph community has been on the support for web, social network, or product search applications. This paper describes some of our experience in developing a large-scale applied knowledge graph for a more technical audience with more specialized information access and analysis needs - the air traffic management community. We describe ATMGRAPH (NASA's Air Traffic Management (ATM) Knowledge Graph), a knowledge graph created by integrating various sources of structured aviation data, provided in large part by US federal agencies. We review some of the practical challenges we faced in creating this knowledge graph.
Transición de un ambiente educativo presencial a uno digital, en ausencia de un modelo educativo. Implicaciones para practica docente. Caso de estudio.

In this document we face the challenge to describe the events that occur and instrument the teaching practice in a context of sanitary emergency that demands the implementation of the digital thought, the structure of an academic community: quota, digital competitions disabled, unknown to the institutional educational model and demands an immediate operational response in a digital environment. The description, like an investigation purpose, is utilized for events in the process, predict the effects that will occur, while explaining the effect that has taken place. The study of an employed case let’s us explain a concrete reality, therefore the results are susceptible to recover an explanation to similar realities. The absence of an educational model, in a superior institution of education, conducive to a lack of standards needed for the leading of a proper transition from a real life face to face procedure to an online/ digital one,the lack of organization it’s really evident how it’s happens in the consolidation of a proper training of a digital abilities and knowledge used by teachers and students creating only for the use porpoise of being used as a tool of interaction between them. Not using the already known ones like a didactic design and the mediation of communication. We proposed the designe of a new general document created for a proper implementation of a new education practices, the new methodological theoretical Principles, and the indicators of a accomplishment of the advance to a digital environment for the sake of studies.
Cyber Crimes in the Age of Covid 19

The paper discusses the topic of rising cybercrime in the age of COVID-19. Various dimensions related to cybercrime such as rise in internet usage for remote activities, victimization and the aftermath of such crimes upon individuals and large corporations as well as the cyber security measures that lead to the identification of the contributing factors behind the rising rate of cybercrime. Qualitative research methodology has been adopted in this regard for the comprehensive analysis of secondary resources. Few secondary thematic analyses are provided here in this study to discuss and analyze the ratio of cybercrimes perfectly during COVID-19 pandemic situation. Few recommendations have been made regarding further investment in the cybercrime department and awareness raising programs for the prevention of cybercrime.
Inlier clustering based on the residuals of random hypotheses

We present an approach for motion clustering based on a novel observation that a signature for putative pixel correspondences can be generated by collecting their residuals with respect to model hypotheses drawn randomly from the data. Inliers of the same motion cluster should have strongly correlated residuals, which are low when a hypothesis is consistent with the data in the cluster and high otherwise. After evaluating a number of hypotheses, members of the same cluster can be identified based on these correlations. Due to this property, we named our approach Inlier Clustering based on the Residuals of Random Hypotheses (ICR). An important advantage of ICR is that it does not require an inlier-outlier threshold or parameter tuning. In addition, we propose a supervised recursive formulation of ICR (r-ICR) that, unlike many motion clustering methods, does not require the number of clusters to be known a priori, as long as annotated data are available for training. We validate ICR and r-ICR on several publicly available datasets for robust geometric model fitting.
Web-Based Decision Support System Determination of Recipients of Covid-19 Pandemic Social Assistance Using the SAW and AHP Methods

During the COVID-19 pandemic, this was not only followed by an increase in the number of positive cases caused by various reactions from people who did not care about this outbreak, but also followed by an increase in poverty, early community mobility, and security insecurity . The government plans to provide special social assistance for middle to lower class people in the face of this COVID-19 pandemic. The distribution of social assistance as a realization of the social safety net program during the COVID-19 pandemic leaves a lot of homework to do. Starting from data collection, the accuracy of target recipients of aid, to the distribution. The mechanisms for distributing aid are complicated and often not well targeted due to inappropriate criteria for beneficiaries and inaccurate / inaccurate data. Until there was a protest from residents who should have received assistance but they did not get this assistance, and vice versa. This study proposes the Analytical Hierarchy Process (AHP) method for weighting the value of each criterion and the Simple Additive Weighting (SAW) method for the ranking.
Fuzzy Logic Implementation Using the Tsukamoto Method as a Decision Support System for Students Scholarship Acceptance in Universities

Scholarships are a supporting factor for students in the universities. In the process of determining who receives the scholarship we need a decision-making process is subjective, with the criteria some students who have the ability or value that is not so different. With the existence of a system that supports decision making in determining who is entitled to a scholarship. This system is supported by the Tsukamoto fuzzy logic method which is based on data or human resources rules with criteria that have been determined by a group of people. Therefore, the results of this process will be given to students based on existing decisions.
REST API and Real-Time Notification of SIsKA-NG Mobile for the Academic Progress Information System

The objective of this research is to develop mobile information system (MIS) for the academic progress information system. This MIS was called SIsKA-NG mobile where its client application was used to monitor the academic progress related to thesis research of the postgraduate student at the authors’ study program. It involved the latest development in network and system, especially on the utilization of web service by using representational state transfer application programming interface (REST API) that was integrated with the existing SIsKA-NG web. Moreover, a real-time notification was developed by using a third-party service Firebase Cloud Messaging (FCM) for certain business processes, like account registration, examination registration, and examination schedule. All of those aspects constructed the back-end development while a certain cross-platform framework was used to construct the front-end development. Overall, this developed unique system was considered as the contribution of this research. Through the testing that involved System Usability Scale (SUS) evaluation, the average SUS score of 82.25, 79.25, and 77.5 was obtained, each from student, lecturer, and admin respondents. All of those scores are in grade A, A-, and B, respectively. They are higher than a score of 68.00 which means SIsKA-NG mobile was considered as a good usability product.
An improved teaching-learning-based optimization: briefly survey

Teaching-learning-based optimization algorithm (TLBO) considers a newly advanced heuristic algorithm that depends on the physical appearance of the teaching-learning procedure. Its goal at the reduction of facilely come down into local optimum when working on complicated optimization difficulties that have high dimensional, in this paper, we will review a viewpoint many studies that involved an improved or enhanced teaching-learning-based optimization, that interested by improved learner phase which included the population to avert the potential about overthrowing toward a local optimum. Also, strategies based on the Gaussian perturbation ban the TLBO algorithm from falling within local minima. In this paper also presented the role of an Improved Teaching-learning-based Optimization Algorithm to Determine Job Shop Scheduling issues.
Study on Proposed Resource Allocation Management for Cloud Computing Using Tabu Search Algorithm

Cloud computing is an emerging technology that provides computing resources depending on user demand. Some policies can be used to schedule this demand or supply of resources. The management of resource allocation should supply resources in a shorter time and at a lower cost. The services provided by cloud computing are software as service, platform as service and infrastructure as service. A dynamic optimised resource allocation management algorithm is designed in this paper based on three factors: optimum solution, deadline constraint, and cost constraint. The algorithm employs the Tabu Search Algorithm, which is then followed by prioritisation and task grouping.
Decoherence in the Three-State Quantum Walk

Quantum walks are dynamic systems with a wide range of applications in quantum computation and quantum simulation of analog systems, therefore it is of common interest to understand what changes from an isolated process to one embedded in an environment. In the present work, we analyze the decoherence in a three-state uni-dimensional quantum walk. The approaches taken into consideration to account for the environment effects are phase and amplitude damping Kraus operators, unitary noise on the coin space, and broken links.
Student competencies in the education system formation

Let's look at the basics of selecting and constructing teaching methods in a competency-based approach. To do this, we define the concepts of competence and competence. We can determine its structure and function. Then we develop the technology for designing basic and subject competencies. From this arise the principles of selection of teaching methods.
Low-Cost Optical Tracking Controller System for Fine Motor Rehabilitation in Children with Brain Damage: Formal Specification and Validation

Acquired brain damage in children is increasingly frequent, and as main deficit produces motor alterations that manifest as the child grows, affecting muscle tone, coordination and motor control, in order to influence these aspects, fine motor skills are intervened, since these involve a coordinated effort of the brain and muscles, having a direct impact on the learning capacity of children and can improve their independence and autonomy. Although traditional therapies have been proven with great effectiveness, there are also different rehabilitation systems that make use of tracking devices, however not all of them are accessible due to their high cost or the lack of specialists who master them. That is the reason a low-cost optical tracking Controller System is proposed to complement fine motor-oriented rehabilitation, allowing movements to be captured with precision and to obtain feedback on the accuracy of the exercises. In this paper we focus on the first stage referring to the formal specification of the requirements and their validation. The proposal is based on the Leap Motion optical tracking device and limited to exercises with a fine motor and wrist. The controller system aims to provide a better environment for users to run their rehabilitation process, in addition to considering the rehabilitation progress. The proposal uses formal specifications to reduce possible ambiguities in the face of a system that may cause future damage to its users if the rehabilitation is not carried out correctly, in the same way they are used to validate the main properties of the functional requirements. The formal specification language VDM ++ is used to describe the system properties for later modeling and validation through the VDMToolBox tool. As a result, a formal specification of 4 requirements and a 100% coverage analysis were achieved.
Preprocessing of Datasets Using Sequential and Parallel Approach: A Comparison

Rai, Shwetha Geetha, M. Kumar, PreethamData preprocessing is a technique in data mining to make the data read for further processing according to the requirement. Preprocessing is required because the data might be incomplete, redundant, come from different sources which may require aggregation, etc., and data can be processed either sequentially or in parallel. There are several parallel frameworks such as Hadoop, MPI, and CUDA to process the data. A survey has been done to understand these parallel frameworks, and a comparison between sequential and parallel approach is carried out to compare the efficiency of the two approaches.
Predictive articulatory speech synthesis with semantic discrimination

An articulatory speech sythesiser is presented that extends the Recurrent Gradient-based Motor Inference Model for Speech Resynthesis [1] with a classifier optimizing for semantic discrimination. The new design features show promising results in improving model performance.
Instructor Views on Technology Use and Coding Training

With the inclusion of the Information Technology and Software course in elementary and middle school curricula in Turkey, the Ministry of National Education has started to offer Technology Use and Coding courses. In this study, opinions of 12 instructors who taught Technology Use and Coding courses were consulted. The study aimed to determine the level of comprehension of the trainees through the evaluation of in-service training. The study was conducted as a case study, one of the qualitative research designs, and the data were collected using a semi-structured interview form. The data were analyzed using the MaxQDA 2020 software. As a result, it was determined that the trainees who attended the courses voluntarily were more willing to learn. The trainees who voluntarily attended these courses stated that they preferred these courses due to the popularity of coding training. While the duration of the course was found to be sufficient, it was determined that offering the courses after work hours caused a decrease in the motivation of the trainees. Inconvenience of training centers, lack of educational materials and insufficient number of instructors were stated as problems encountered in courses. It was observed that the attendees of the course liked the algorithm and block-based coding subjects, and that the instructors did not give enough importance to the subject of coding without computers.