Reviewerly/exHarmony huggingface dataset:
Virtual and augmented reality for positive social impact

This workshop invites researchers and industry practitioners designing Virtual Reality and Augmented Reality applications for positive social impact to join us in Perth, Australia, to discuss the research and industry landscape and identify opportunities for collaboration with like-minded professionals. Participants will have an opportunity to share their experiences with other attendees, and will discuss the challenges they have experienced in working with VR and AR applications. This workshop will aim to help researchers to overcome these challenges and, as an outcome, plans will be made for future workshops to establish and promote positive social impact as a long-Term research focus for VR and AR researchers in Australasia.
Designing Problem Based STAD Learning Models to Improve Students’ Writing Skill

This research was conducted to develop a learning model by using the ADDIE model. The problem-Based STAD learning model was designed by Analysis, Design, Development or Production, Implementation or Delivery, and Evaluations. This research was done in the English Language Education Study Program of the University of Pahlawan Tuanku Tambusai in Writing II. Based on the result of data analysis, it can be concluded that 1) The Problem-based STAD Type Learning Model has been produced through the ADDIE development model. 2) Problem-based STAD Type Learning Model that has met the criteria of validity. 3) The model is valid with the characteristics of the suitability of the research model development with the ADDIE procedure. English teachers can use this model to improve students’ skills in writing and motivate the students in writing English text.
Dynamical learning of non-Markovian quantum dynamics

We study the non-Markovian dynamics of an open quantum system with machine learning. The observable physical quantities and their evolutions are generated by using the neural network. After the pre-training is completed, we fix the weights in the subsequent processes thus do not need the further gradient feedback. We find that the dynamical properties of physical quantities obtained by the dynamical learning are better than those obtained by the learning of Hamiltonian and time evolution operator. The dynamical learning can be applied to other quantum many-body systems, non-equilibrium statistics and random processes.
Methods to Eye Gaze Interaction for Authentication

One of the methods touted to reduce shoulder surfing during onscreen authentication is eye gaze input. Eye gaze authentication methods have thus far relied on a few methods for selection of on screen objects, namely dwell time, blinking, eye gestures and pursuit of moving objects. This paper surveys the literature on the various approaches. From analysis of the advantages and drawbacks of the surveyed approaches, we find that the dwell method has advantages in security and usability. We then describe a method designed previously by the authors that enhances the dwell method by making use of peripheral vision. The proposed method is in the ideation stage.
Tracking probabilistic truths: a logic for statistical learning

Abstract We propose a new model for forming and revising beliefs about unknown probabilities. To go beyond what is known with certainty and represent the agent’s beliefs about probability, we consider a plausibility map, associating to each possible distribution a plausibility ranking. Beliefs are defined as in Belief Revision Theory, in terms of truth in the most plausible worlds (or more generally, truth in all the worlds that are plausible enough). We consider two forms of conditioning or belief update, corresponding to the acquisition of two types of information: (1) learning observable evidence obtained by repeated sampling from the unknown distribution; and (2) learning higher-order information about the distribution. The first changes only the plausibility map (via a ‘plausibilistic’ version of Bayes’ Rule), but leaves the given set of possible distributions essentially unchanged; the second rules out some distributions, thus shrinking the set of possibilities, without changing their plausibility ordering.. We look at stability of beliefs under either of these types of learning, defining two related notions (safe belief and statistical knowledge), as well as a measure of the verisimilitude of a given plausibility model. We prove a number of convergence results, showing how our agent’s beliefs track the true probability after repeated sampling, and how she eventually gains in a sense (statistical) knowledge of that true probability. Finally, we sketch the contours of a dynamic doxastic logic for statistical learning.
The opportunities of interactive technologies for enhancing the self-actualization of non-linguistic students studying a foreign language (exemplified by business game)

The article is devoted to studying the opportunities of interactive technologies for enhancing the self-actualization of non-linguistic students studying a foreign language, exemplified by the method «business game». Interactive technologies form the learning environment where a student acts as a subject of multidirectional interaction «student — teacher» / «student — student». They contribute to forming the deliberate student’s competency and to taking the full advantage of their creative and mental potentials. Business game is intended to improve the skills of foreign language communication, to develop the social competency, to raise the proficiency in the foreign language not only as a subject of study but also as a mean of professional communication. There are the main aspects of business game which form the mechanism of enhancing the self-actualization of non-linguistic students studying a foreign language: individual constituent, collective constituent, feedback, emotional background. Individual constituent is internal conditions, collective constituent is external stimulating conditions. The author demonstrates how the role ranking in business game helps activate the cognitive interest of students and their readiness to search for the creative non-typical solutions of problematic situations. Business game mobilizes the mechanisms of students’ interpersonal perception — identification and empathy. Feedback makes cognitive, communicative and personal-conceptual aspects of study more active, actualizes the personal and group forms of reflexion. The emotional constituent of business game is the emotional atmosphere which by means of positive emotional experiences can contribute to enhancing the motivation for learning-creative activities and cognitive interest, to developing students’ needs for personal growth and self-fulfilment. Business game is a powerful motivational resource for enhancing the self-actualization of students studying a foreign language.
Garbot - Semantic Segmentation for Material Recycling and 3D Reconstruction Utilizing Robotics

Semantic segmentation directly from the images of landfills can be utilized in the earth movers to segregate the garbage autonomously. Generally, Various segregation methods are available for garbage segregation such as IOT based waste segregation, Conveyor belt segregation in which none of them are directly from landfills. Semantic segmentation is one of the important tasks that maps the path towards the complete scene understanding. The aim of this paper is to present a smart segregation method for garbage by using semantic segmentation with DeepLab V3+ Model using the framework(Backbone model) of Xception-65 with the mean accuracy of 75.01%. This paper features the segmentation with the GarbotV1dataset which has major classifications such as Plastic, Cart-board, Wood, Metal, Sponge. The paper also contributes a method for reconstructing the segmented images to build a 3D map and this exploits the use of earth moving vehicles to navigate autonomously by localizing the segmented objects.
Recognition of Hand Gestures Using Image Processing

This paper presents a far better approach in recognizing the hand gestures supporting curvature of perimeter. Hand gestures are an integral part of communication, especially, if we are communicating any foreign language. Recognition of mitt is a characteristic and natural approach to connect with the PC, where collaborations with the computer can be expanded through various dimensional utilization of hand gestures as contrasted with elective info techniques. The aim of this project is to investigate various techniques for HGR (hand gesture recognition) using detection of the finger tips.This system algorithms makes use of image processing toolboxes of Mat lab, computer vision to access the webcam. The difficult and clumsy interface devices for human-computer interaction (HCI) can be solved by using webcam hand gestures.
THE SCALE OF PRIORITY FOR THE CONSTRUCTION OF IRRIGATION CHANNELS FOR STAKEHOLDERS PERCEPTIONS OF THE IRRIGATION SERVICE IN SIDOARJO REGENCY

Sidoarjo Regency is one of the megapolitan Gerbang Kertosusilo. The planted area during the rainy season and dry season reaches 30,000 ha. The area of paddy fields continues to decline, namely 26,334 ha (2002), 22,460 ha (2010), and an estimated 13,544 ha (2009–2029). Sidoarjo Regency Irrigation Service as executor of irrigation management is of course inseparable from construction project activities. In the implementation of the construction of new irrigation networks as well as in rehabilitation and maintenance, it is necessary to implement project management. Before the project is implemented, it must first be submitted through proposals from the village level. In following up the proposal the writer used the Analytic Hierarchy Process (AHP) analysis method. With four aspects that affect the determination of the proposal: The results of the analysis obtained the weight of each criterion as follows: Service Area (ha) 0.3179, Cost 0.3159, Benefits 0.3217, and Network Conditions 0.0445. The results of the above analysis obtained priority ranking from the first to the last sequence as follows: Plengsengan Gedangrowo Channel, Normalization of Reform Channels, Installation of floodgates, Plengsengan ChannelsDs. Suwaluh, Rehabilitation of Ketawang Canal Kec. Sukodono, Rehabilitation of Candi Subdistrict Channel, Plengsengan Channel Ds. Suwaluh, Plengsengan Channels Purboyo II Ds. Popoh, Plengsengan Irrigation Channels Dsn. Kesimbuk, Plengsengan Channel Mangetan Kanal.
A Comparative study of C4.5 and Naïve Bayes Algorithms

Abstract: In this fast and growing age large amount of data is generated and save or store somewhere daily. These data are included many information. They may be financial data, scientific, medical science related data, engineering data and many other types of data. Analyzing such data is an important need. Data Mining is a technique which providing tools to discover knowledge from data. It includes so many techniques for KDD such as classification, clustering, regression etc. In this paper a comparative study of C4.5 and Naïve Bayes Data mining classification techniques has been done. The experiment is based on weather data. That includes parameters like temperature, humidity, wind speed etc. Weka tool is used here for the experiment. Keywords: Data Mining, Classification, Naïve Bayes, C4.5.
Two-dimensional complex wavelet with directional selectivity used in fringe projection profilometry: publisher’s note

This publisher’s note contains corrections to Opt. Lett. 46 , 3653 ( 2021 ) OPLEDP 0146-9592 10.1364/OL.420460 .
Divide-and-Conquer Federated Learning Under Data Heterogeneity

Federated Learning allows training of data stored in distributed devices without the need for centralizing training-data, thereby maintaining data-privacy. Addressing the ability to handle data heterogeneity (non-identical and independent distribution or non-IID) is a key enabler for the wider deployment of Federated Learning. In this paper, we propose a novel Divide-andConquer training methodology that enables the use of the popular FedAvg aggregation algorithm by over-coming the acknowledged FedAvg limitations in non-IID environments. We propose a novel use of Cosine-distance based Weight Divergence metric to determine the exact point where a Deep Learning network can be divided into class-agnostic initial layers and class-specific deep layers for performing a Divide and Conquer training. We show that the methodology achieves trained-model accuracy at-par with (and in certain cases exceeding) the numbers achieved by state-of-the-art algorithms like FedProx, FedMA, etc. Also, we show that this methodology leads to compute and/or bandwidth optimizations under certain documented conditions.
Hash Tables for a Digital Lexicon

This paper deals with the construction of digital lexicons within the scope of Natural Language Processing. Data Structures called Hash Tables have demonstrated to generate good results for Natural Language Interface for Databases and have data dispersion, response speed and programming simplicity as main features. The storage of the desired information is done by associating a key through the hashing functions that is responsible for distributing the information in this table. The objective of this paper is to present the tool called Visual TaHs that uses a sparse table to a real lexicon (Lexicon of Herbs), improving performance results of several implemented hash functions. Such structure has achieved satisfactory results in terms of speed and storage when compared to conventional databases and can work in various media, such as desktop, Web and mobile.
Evaluation of Leachate Quality at Municipal Solid Waste Landfill Site: Case Study in Sliwung, Situbondo Regency, East Java, Indonesia

Objective: This study aims to evaluate the quality of landfill leachate that has been treated in a wastewatertreatment plant.Mathods: Leachate samples were taken for 12 months (January-December) in 2018. The leachate qualityparameters studied were: BOD5, COD, TSS, total N, and heavy metals (Hg and Cd).Results: The results showed that the BOD5 quality met environmental quality standards in May, June, July,September, October and December, COD exceeded environmental quality standards, TSS met environmentalquality standards in February, March, August, and December, N total met quality standards environment for11 months, only December did not meet environmental quality standards, heavy metals (Cd and Hg) werebelow environmental quality standards.Conclusion: The Sliwunglandfill to conduct an approach study that can reduce the BOD5, COD, and TSSvalues so that they do not exceed the specified quality standards.
THE EFFECT OF USING SOCIAL MEDIA FOR LEARNING ENGLISH TO THE STUDENTS’ LEARNING ACHIEVEMENT OF ENGLISH LANGUAGE EDUCATION STUDY PROGRAM DURING COVID-19 PANDEMIC

In this research is carried out in order to find out  how far the effect of using social media for learning English to the students’ learning achievement of English Language Education Program during covid-19 pandemic is. And in this research the writer takes all the students of first and third semester as the object of this research, they are 40 students. For getting the needed data, the writer applies the library and field research. The library research is applied based on the needs of the books as the sources of theories and informations, and the field research is applied based on the need of data from the field, in this case from the English Study Program, Teacher Training and Education Faculty of Graha Nusantara University. And as the instrument for collecting the data the writer uses the written test. After getting the data, the next step which is done by the writer is analyzing it by using the statistical analysis. After analyzing the data, it has been got that the value of rXY is 0.79. By consulting this value to the table of interpretation given before, it is known that it can be categorized into the high correlation. It means using social media for learning English give significant effect to the students learning achievement of English Language Education Program during covid-19 pandemic. So the hypothesis of this research:“ there is a significant effect of using social media for learning English to the students’ learning achievement of English Language Education Program during covid-19 pandemic”is accepted.
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning.

Several families of continual learning techniques have been proposed to alleviate catastrophic interference in deep neural network training on non-stationary data. However, a comprehensive comparison and analysis of limitations remains largely open due to the inaccessibility to suitable datasets. Empirical examination not only varies immensely between individual works, it further currently relies on contrived composition of benchmarks through subdivision and concatenation of various prevalent static vision datasets. In this work, our goal is to bridge this gap by introducing a computer graphics simulation framework that repeatedly renders only upcoming urban scene fragments in an endless real-time procedural world generation process. At its core lies a modular parametric generative model with adaptable generative factors. The latter can be used to flexibly compose data streams, which significantly facilitates a detailed analysis and allows for effortless investigation of various continual learning schemes.
A Proposed Framework for Developing User-Centred Mobile Healthcare Applications for the Biggest Annual Mass Gathering (Hajj) Post COVID-19

The Hajj pilgrimage being the largest annual mass gathering globally with two to three million participants from over 180 counties, will remain a high priority for diseases surveillance for future epidemics or any other international public health emergencies with rapid scalability.This paper highlights the importance of monitoring mass gatherings during a pandemic and how mHealth applications can reduce the burden on health facilities during a mass gathering and tackle future infectious diseases outbreaks.The paper also highlights the importance of developing a user-centred application when designing for a diverse group of users with a shared purpose.As a result, a framework has been proposed to update the current applications or design and develop future mobile health applications.The framework has been developed based on the rationale and evidence found in the literature.
Fault-Tolerance System Design in the Internet of Things Network with Blockchain Validation

An Internet of Things (IoT) network contains huge heterogeneous sensing devices, architectures, and protocols. In this extensive IoT network, fault detection and management is a critical and time-consuming task. In this paper, a fault-tolerance system is proposed for the Internet of Things network using Blockchain integrity and security validation method, and this network will detect faults and provide solutions automatically to maintain the efficiency of the network. Fault-tolerance automation creates a significant impact in the extensive IoT network for its sustainability. The outcome presented in this paper shows that the blockchain-based network is highly fault-tolerant as compared to the centralized and cryptographic method-based network.
IoT Automated Spy Drone to Detect and Alert Illegal Drug Plants for Law Enforcement

Survey shows that a lot of people grow psychoactive drugs unofficially/illegally in their garden, fields, and forests. This happens majorly in the rural/village area where there is no proper inspection in the private fields and gardens. Growth of these sorts of plants and their sale in illegal market affect the future of India, as many youngsters are drug addicted. An automated spy drone is designed to reveal the persons/groups planting and growing psychoactive drugs unofficially in their private land and identify them. Whenever the spy drone system identifies these psychoactive drugs, it immediately delineates the inspection office. Spy drone is designed and trained to identify the marijuana plant using machine learning and artificial intelligence algorithms through vision sensor. Vision sensors can capture the images using camera to identify the presence of desired images. This sensor differs from the image inspection. Camera, light, and controller are integrated together, which makes the operation simple. A fully autonomous smart spy drone can take up its flight using the shortest planning algorithm once the coordinates are marked. It also changes its altitude in case of any obstacles in its flight path. As this drone is embedded with a GPS tracker, the inspection officer can monitor its location. Once the area of interest has been searched, it intelligently saves the location and chooses another location, as this drone is automated. It reduces the sales of the drug in our country and in near future, our country may be drug-free.
Literacy as an Effective Media for Distance Learning

The emergence of the phenomenon of distance learning as online learning during the pandemic is concerned about the quality of achieving learning objectives. Finally, distance learning becomes an option so that the implementation of higher education can still be carried out like conventional learning. This restlessness opens opportunities for literacy methods as an effective medium in distance learning. The purpose of this research is to explain that literacy is not limited to reading and writing skills. Familiarize students with reading and accessing information before learning is a positive habit for organizing the brain and critical analysis skills. The research method used in research during this pandemic is a literature study "library research" (library research) with a qualitative approach. The type of data used is secondary data obtained from various sources such as books, journals, scientific writings as well as observations of online learning at the research campus. The research findings refer to several references, that literacy is the local wisdom of the Indonesian people, has practical goals that can be utilized and developed as a renewal in the era of educational technology. Thus, during this pandemic, literacy has been developed in various aspects of learning life such as technology, culture, politics, finance, information, and so on. The impact of literacy effectively has made students able to study independently and learn actively. Mastery of technology in literacy creates student learners, thinkers, researchers, and agents of change. The use of literacy as a medium for distance learning is an opportunity that this learning provides an opportunity for anyone to learn. The effectiveness of literacy as a medium in distance learning is very important to be developed with the mastery of digital technology