Reviewerly/exHarmony huggingface dataset:
Design and Implementation a System for Monitoring the COVID19 Patients Based on the Internet of Thing Applications

The Corona Virus (COVID-19) was spread in about 215 countries in 2019. The number of people affected by the epidemic has increased dramatically. Iraq is one of the countries affected by the Coronavirus. Hundreds of Iraqi doctors have died because they contact directly with patients. One of the most serious challenges is the high rate of conduction through contact with people infected with this virus. The impact of the coronavirus can be reduced by using one of the advanced technology methods. The internet of things (IoT) is one of these applications. This paper shows that the role of smart surveillance in reducing the risks of covid-19. To avoid face-to-face interaction, physical contact, and maintain social distancing, the smart monitor is designed in this paper. It is used to monitor the health parameters that are affected when infected with covid-19, such as heart rate, oxygen level, blood pressure, and body temperature in real-time and remotely. This will reduce the workload, workload on the medical staff, and reduce the infection with the covid-19.
Comparative Analysis of Prediction Models for Cryptocurrency Price Prediction (May 2022)

The decentralization of cryptocurrencies has greatly reduced the level of central control over them, impacting international relations and trade. Further, wide fluctuations in cryptocurrency price indicate an urgent need for an accurate way to forecast this price. This project proposes a method to predict fluctuations in the prices of cryptocurrencies, which are increasingly used for online transactions worldwide. This project proposes a novel method to compare the efficiency of five different models predicting the cryptocurrency price by considering various factors such as market cap, volume, circulating supply, and maximum supply based on deep learning techniques such as the Linear Regression, Support vector regression (SVR), Auto Regressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and a hybrid model of ARIMA and LSTM which are effective learning models for training data. The hybrid model outperforms the LSTM and ARIMA model after comparing RMSE values. The proposed approach is implemented in Python and validated for benchmark datasets.
Revisiting conclusions on the empiric segmentation of high-risk patients

The authors provide feedback on generalizations made regarding interventions for high-risk populations in previous research.
Video Based Human Activity Recognition Surveillance System

It is argued that current state-of-the-art methods of home surveillance such as motion detection technology like CCTV intrusion alert are insufficient, in particular to cater the modern need of whole automation with vulnerabilities such as requiring human involvement. We propose an alternative system, a video-based Human Activity Recognition (HAR) approach using the combination of Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM) algorithm, to dealwith the identified shortcomings. Our proposal does not require any changes to the existing home security protocols and is easily implemented using only low-cost, commercial-off-the-shelf hardware. We can easily use the traditional surveillance camera for computer vision tasks. We evaluate our approach using real-world activity data collected via video-based sensor. We quantify its effectiveness, by plotting Loss and accuracy curves. Our results show that the video-based HAR approach can provide full automation in home surveillancesystem compared to conventional CCTV motion detectors by an accuracy of more than 93%. Further system’s accuracy can be increased and we can achieve significantly better results by implementing LRCN (Long Term Recurrent Convolution Network) approach.
Designing a metalanguage of translation issues 1

Assessing and assuring translation quality is one of the main concerns for translation service providers (TSPs), machine translation (MT) industries, and translation teaching institutions. This chapter first describes several requirements that issue classification schemes, or the metalanguages of translation issues, must satisfy, and then our methodology for developing an issue classification scheme, especially aiming at a consistent human assessment, of English-to-Japanese translations, produced by learner translators. From a linguistic point of view, identifying and classifying translation issues in TDs during the revision process can be considered as an instance of text annotation task. Thus, key elements in designing an annotation scheme and their implementations discussed in the literature of linguistics, especially in computational linguistics, are helpful in designing and developing an issue classification scheme.
ASA-Net: Deep representation learning between object silhouette and attributes

Object silhouette and semantic attributes are respectively verified for their effectiveness as auxiliary supervision in image recognition. It encourages us to propose a novel zero-shot recognition model, Attribute-Segmentation-Attribute network (ASA-Net), which jointly conducts object segmentation, attribute prediction and recognition in a multi-task learning manner. Firstly, a feature extraction module is pre-trained based on smooth attribute and category annotations. This module is then adopted to initialize the feature encoding module of a multi-scale segmentation CNN to generate coarse-to-fine object silhouettes. Finally, the segments are multiplied with the original image to obtain regions of interest, and semantic features of these regions are extracted and combined to predict attributes. The obtained attribute prediction is further projected into the category space to accomplish the zero-shot recognition task. Experimental results on two public benchmarks indicate that our ASA-Net performs better than baseline and existing methods in attribute prediction and segmentation tasks, as well as the unseen object recognition. The source code is publicly available online (https://github.com/YsSue/ASA-Net.git).
TECHNOGENY: THE GENIUS LEARNING UNIT

Fragmented knowledge, the lack of adequate synthetic learning units, its forms and content, the contradiction of the Education faces humans to nowadays existential problems, like global challenges of climate change, pandemics, wars, poverty, international terrorism, migration, etc. In the article the author presents more than 40 years of sociogenic innovation on the author science Technogeny, dedicated to construction of virtual models of the origin and development of learning and self-improvement seeking to gain necessary for success practice skills and arts. Grounding on the Virtualics, as virtual modelling metatheory and World development spiral virtual models, it gives opportunity to apply virtual approach to the Learning phenomenon and its transition qualities from the Past through Nowadays and towards the Future. Anthropogenic analysis of gaming as a learning procedure enabled to define the action programme of an animal or human as the natural learning unit, which is also a practical Natural knowledge unit. Composed learning virtual model evidently confirmed transition of the form of learning from the Education to Self-Improvement through Education contradiction resonance sinusoid. The learning form transits three qualitative leaps of a virtual trichotomy: autocratic face-to-face education, democratic blended learning, and virtual liberal Self-Improvement. The content of learning is transiting from Metaphysics (academic scholastics) to Virtualics (Smart Innovation). Matrixes of learning form and content fixed clear trends from an Old to the New qualities of the learning. Genius learning unit and virtual Self-Improvement tools innovations and application for forty years of international pedagogic innovations enabled to confirm the right path to the future of learning towards virtual Smart Innovation. COVID-19 pandemic gave additional confirmation of this learning development direction.
Anxiety in times of pandemic: Analysis of Latin American scientific production

A retrospective study was conducted in which articles on anxiety in times of pandemic published and indexed in the Scopus database were examined, and whose authors are affiliated with Latin American institutions. Latin American scientific production on anxiety continues to increase. Brazil is the country that contributes the highest production, representing 44.67% of production, followed by Mexico, Argentina and Peru. Research on psychological variables and their relationship with COVID-19 in Latin America is still limited with respect to world production. It is necessary to increase the collaboration of international authors through the formation of professional and academic groups within and outside the region.
Hiding Information through Reverse-Phase Audio Steganography Technique

Steganography is employed in the study and application of techniques that allow hiding messages or objects inside other imperceptible objects, called carriers. Hence, such a procedure tries to hide messages within other objects to establish a covert channel of communication, becoming the act of communication unnoticed by observers who have access to that channel. In this work steganography is used to send audio messages, covered by another audio message, using techniques of phase inversion of an audio signal.
Dense Pixel-Level Interpretation of Dynamic Scenes With Video Panoptic Segmentation

A holistic understanding of dynamic scenes is of fundamental importance in real-world computer vision problems such as autonomous driving, augmented reality and spatio-temporal reasoning. In this paper, we propose a new computer vision benchmark: Video Panoptic Segmentation (VPS). To study this important problem, we present two datasets, Cityscapes-VPS and VIPER together with a new evaluation metric, video panoptic quality (VPQ). We also propose VPSNet++, an advanced video panoptic segmentation network, which simultaneously performs classification, detection, segmentation, and tracking of all identities in videos. Specifically, VPSNet++ builds upon a top-down panoptic segmentation network by adding pixel-level feature fusion head and object-level association head. The former temporally augments the pixel features while the latter performs object tracking. Furthermore, we propose panoptic boundary learning as an auxiliary task, and instance discrimination learning which learns spatio-temporally clustered pixel embedding for individual thing or stuff regions, <i>i.e</i>., exactly the objective of the video panoptic segmentation problem. Our VPSNet++ significantly outperforms the default VPSNet, <i>i.e</i>., FuseTrack baseline, and achieves state-of-the-art results on both Cityscapes-VPS and VIPER datasets. The datasets, metric, and models are publicly available at https://github.com/mcahny/vps.
ORGANIZATION OF CAREER GUIDANCE ACTIVITIES IN SECONDARY SCHOOL (BY EXAMPLE OF ALTAI TERRITORY)

The article considers the problem of organizing career guidance activities in modern educational institutions. The author focuses on the analysis of information presented on the official websites of the general education schools of Altai Krai as an important component of the vocational guidance work of the school. The legal support of career guidance activities in accordance with modern requirements is also considered. The author proposes some ways to solve the stated problem using both the traditional methods that have shown their effectiveness, and the innovative techniques that correspond to the urgent needs of modern students and the society as a whole.
Analysis of the Application Prospect of Computer Image Processing Technology in UI Design

In order to improve the interface experience effect of the mobile terminal software, this paper improves the UI design by combining computer image processing technology and improves the diffusion algorithm for images by improving the diffusion model, improving the diffusion coefficient and adaptively selecting the diffusion threshold. Moreover, this paper has carried out deep research on coordinate transformation and image interpolation and stored the result of coordinate transformation in the coordinate transformation table and weight table. In addition, this paper proposes an improved digital scan conversion method based on a lookup table and constructs an improved UI design system model. Through the analysis of experimental data, it can be seen that the application effect of computer image processing technology in UI design is very good, and it can effectively promote the improvement of UI design technology.
Axiological Aspects of Educational Activity in Postmodern Philosophy

The relevance of the chosen topic of the article is determined by the need to improve the system of educational activities in postmodernism.&#x0D; The article provides a theoretical analysis of developments on the topic, substantiates axiological (spiritual, moral, aesthetic and other values, their relationship with each other, with social, cultural factors and human personality; section philosophy) perspectives of educational activities in postmodern philosophy, gives a description of axiological areas of academic activity in postmodern philosophy; the main directions of the philosophy of education in the epoch of postmodernism are determined; the vision of a new paradigm of education in the works of researchers and scientists is presented.&#x0D; The article analyses the understanding of the problems of education in the European philosophical and pedagogical tradition of the XX-XXI century, gives a brief overview of systematic works on the philosophy of education of prominent Western researchers of these problems, taking into account their proposed educational values. Based on the analysis, the article's author concludes that it is necessary to critically review several traditions for the philosophy of education and the choice of approaches in understanding the values of modern education.&#x0D; The article's author notes the emergence of new axiological paradigms of education in the philosophy of education of the late XX - early XXI century, associated with the development of cultural-centric and global-historical trends in philosophy.
Contact Improvisation as a Force for Expressive Reciprocity With Young Children Who Don’t Speak

Movement can be a powerful force for sensory connection and expression in young children who sometimes don’t speak. Their kinaesthetic curiosity naturally experiments with—and forms spontaneous relationships through—touching, sensing, and moving-with the world around them. This article wonders what might happen if children’s connective movements are invited through the speculative method of contact improvisation, not as an alternative to speech or way of interpreting meaning, but simply as a space for the transmission of forces, sensations, intimacy, and reciprocity. I consider what these shared forces or sensations of expression are that generate intimacy, joy, and reciprocity beyond words.
Data-driven Soil Cultivation Promoted by NTT DATA

To promote soil cultivation, we at NTT DATA are using information and communication technology to collect soil-diagnosis data and information on farming operations throughout Japan and compile a database of that information.This database will enable data-driven initiatives in the domain that has relied on past experience and intuition of farmers.The data in the database are normalized by conducting soil analysis using a nationally standardized method that makes it possible to understand not only the characteristics of individual fields but also regional characteristics.We have also developed and are testing a technology for measuring soil composition from satellite images as a means of reducing the time and labor required to collect soil samples for soil diagnosis.
In-depth understanding of LSTM and its recent advances in lung disease diagnosis

Of late, long short-term memory (LSTM) has proven its worth in medical diagnosis. Hence, there is a need to explore this special version of recurrent neural network (RNN), which can learn long-term dependencies. LSTM addresses the short-term memory problem of basic RNNs. In this paper, an in-depth study of LSTM is done with the help of a few real-life examples. Some of the recent advances of LSTM in COVID-19 and other lung disease diagnoses have also been discussed.
Pelaksanaan Layanan Referensi Di Perpustakaan Iain Kediri

The service of reference aims to assist library users in finding information, by answering questions using reference collections, and providing guidance on finding and how to use reference collections. This study wants to answer two questions; firstly theimplementation of reference services at the IAIN Kediri library, secondly, the obstacles that occur in the implementation of reference services, and how to resolve these obstacles. This research is a qualitative research, which is trying to describe the implementation of reference services at the IAIN Kediri Library. The data source of this research is field data obtained from observations and documentation and interviews with reference librarians. The results of this study indicate that the reference services at the IAIN Kediri library are search services, reference collection utilization services and collection utilization training services. In the implementation of reference services, there are a number of obstacles as follows: first, the competence of human resources for librarians, second, the lack of complete collections and third, the lack of promotion of reference services. To overcome this problem, it can be done through tiered education for reference librarians, collaborating with various parties and conducting regular evaluations to build a quality culture (corporate culture) in the library.
High-Quality Image Enhancement Algorithm Using Kinetic Gas Molecular Optimized (KGMO) Hyperbolic Tangent Function

One of the main steps in various digital image-based applications such as classification, segmentation and prediction etc., is to improve the visibility of digital images.In order to improve the visual efficiency of images, contrast enhancement (CE) is an important preprocessing technique.Depending on the capturing environment, the quality of the image varies, and CE is an important approach to improve the image quality.However, excessive CE resulting in loss of detail and an unnatural appearance of the target image.This paper proposes a new CE using the Kinetic Gas Molecular Optimized Hyperbolic Tangent Function (KGMO-HTF).This is used here to optimize the brightness of the picture α and the sensitivity parameter of the brightness esteems β with hyperbolic tangent (tanh) function.Different parameters such as Enhancement Mean Error (EME), Absolute Mean Brightness Error (AMBE) and Discrete Entropy (DE) are measured to evaluate efficiency of proposed method.Experimental findings are illustrated by CE-KGMO-HTF methods that perform better than conventional methods of CE.
Restorative Juvenile Justice: Level of Implementation and Level of Awareness among Residents in Tangub City

This study aimed to determine the level of implementation and awareness of the juvenile restorative justice program in Tangub City during calendar year 2018-2019. This study made use of non-experimental quantitative research design utilizing descriptive, frequency count, percentage and mean. On the level of implementation of the program, the community respondents exhibited low level of response while the Philippine National Police and the CSWD exhibited a high level of responses. On the level of awareness, the respondents also exhibited a high level of response. It is recommended that the implementers may include or emphasize the community's active participation in juvenile restorative programs. This will encourage them to get involved and recognize the importance of their engagement, maybe resulting in fewer minor-related offenses. The implementers may look into the process on the way the programs are implemented. This will encourage them to examine probable flaws in the execution of the juvenile restorative justice program in order to make adjustments to the overall process of implementation, which could lead to the program's overall success. The implementers may consider looking into the victim's need for reformation and rehabilitation, as well as their family's general engagement. This is critical to ensure that the victims and their families believe the government is on their side, because if the implementers neglect this, retaliation may ensue. Further studies are warranted.
Madā Inqirāiyyati Kitāb Durus al-Lughah Li ash-Shaff al-Awwal bi Ma’hadi Dārissalam Gontor

This study aims to determine the readability level of the Durusullughah Al-Arabiyyah book and determine the percentage of common words in the Durusullughah Al-Arabiyyah book and its relationship with the readability level of the book. This study uses a mix-method approach (qualitativequantitative), with a descriptive presentation. The primary sources of this research are the result of the Cloze Test against the Durusulluguhah AlArabiyyah book and the Al-Munawwir Dictionary, with secondary sources in the form of books, articles, and other reliable references. The results showed that 235 sample people answered 100 points of the Cloze Test with a truth level of 75%, this level indicates the intermediate level or teaching level. The comparison of words in the Cloze test text with words in the AlMunawwir dictionary shows 96%. This figure shows that 96% percent of the words in the Cloze test text that represent the book Durusullughah, are in al-Munawwir’s dictionary. The high percentage of common words in a book indicates a high level of readability of the book. It can be concluded, that the book Durusullughah Al-Arabiyyah is a textbook that is easy to learn by students who use the Al-Munawwir Dictionary for daily learning.
Canteen Automation System Using Android

Abstract: Smart Canteen project, a method for ordering food items online, applicable to any canteen industry. The key benefit of this technique is that it makes the ordering procedure much easier for both the customer and the canteen staff. When a consumer uses the ordering application, it is interactive and features an up-to-date menu with all available options that is dynamically priced based on the options selected. The item will be added to the order after selection, and the consumer can confirm these details at any time before checking out using the Android app. This system too significantly relaxes the cafeteria and relaxes the entire order reception Automation. When customer’s order is confirmed through the android application, it is updated in the database of server and can be retrieved in near real time from the canteen android application end. In the application itself, all items in the order will be displayed along with the item details. Related order options and delivery details, short and easy to understand. The cafeteria staff can process the order as soon as it is placed and can track their records if needed.