Reviewerly/exHarmony huggingface dataset:
Professionalism of Teacher Educators at DIETs in Purvanchal Region

The objective of this research paper is to explore the concept of teacher educator’s professionalism by studying the perceptions of in-service DIETs teacher educators in Purvanchal Region of Uttar Pradesh. A descriptive survey was carried out at the In-Service Teacher Educators’ of different District Institute of Education and Training (DIETs) .This research data were collected by using anonymously filled professionalism perception questionnaires by teacher educators and pupil teachers. The major focus of this study was concerned with professionalism dimensions (knowledge, skill. Spirit, standard, and supportive environment), in relation to teacher educators. The second objective was related to level of professionalism as in dimension perceived by pupil teacher. Sample of study, teacher educators and pupil teachers were 84 and 300 respectively collected from thirteen different DIETs of Purvanchal Region of Uttar Pradesh.
Extracting The User’s Perception About Aadhaar From Print Media Articles

With the advent of technology, agencies have started storing identity data of the users in distributed repositories for improved targeting and ease of the implementation of the commercial and governmental policies. Social networking portal, public registers, social security portals, various ID’s and e-commerce portal are among the popular agencies, who are using these disintegrated yet identifiable digital identities for individuals. This study aims to investigate the user’s perceptions about these stored identities. An experimental test-bed of this research is Aadhaar, the Indian identity repository where media and public reaction has been widely different.As observed in literature, texts generated in un-controlled environment such as Twitter, Facebook etc. are noisy, unstructured and short,it is imperative for us to conduct a pilot on controlled data such as a corpus of newspaper articles. English language articles published in the `The Hindu’ and the ‘ProQuest’ are used as the primary data to extract the view’s in terms of topic, though Internet or the online texts are not all-inclusive. Machine learning tools, such as topic modeling and sentiment analysis are employed to extract the perceptions. The impact of the articles of the aforesaid media houses are also analyzed in terms of neutral, positive and negative polarity
Pelatihan Peningkatan Perpustakaan Sekolah sebagai Sumber Belajar bagi Lembaga Pendidikan NU Maarif Se Malang Raya

Realizing According to Law No. 43 of 2007 that every school operates a library that meets the national library standards by taking into account the National Library Standards. Libraries are required to have a collection of textbooks designated as compulsory textbooks in the education unit concerned in sufficient numbers to serve all students and educators. To make this happen, libraries must have competent human resources in their fields. The implementation method used is exposure/lecture, discussion and mentoring via WhatsApp group. The training was held in one day, starting with the pre-test and post-test. The training materials include Library Management, Classification and Cataloging and Library Automation. From the pre-test results, it was found that the category was very poor with an average score of 33 and an average post-test score of 92 with a very satisfying category. From the increase in the pre-test to post-test scores, it was found that this training was able to provide knowledge of school library management based on library automation.
PROMOTING LEARNER AUTONOMY IN A READING CLASS BY FACILITATING SELF-ACCESS LEARNING DURING THE COVID 19 PANDEMICS

Being an autonomous learner is one of the most important and universal purposes of foreign language education. Especially, when it comes to the situation when the students must practice independent study at home in this case due to the pandemics of Covid19 in Indonesia. This research investigates the application of a self-access language learning approach to foster learner autonomy in an emergency virtual reading class during the covid 19 pandemics of students in STBA LIA, Jakarta. It focuses on finding out how a self-access language learning approach fosters learner autonomy on virtual reading class during the pandemics; to what extent learners have the learning autonomy in the emergency virtual reading class. Qualitative analysis was done by describing data from two surveys and learners’ two assignments. The results show that a self-access language learning approach is beneficial to manage learning which promotes learner autonomy. Learners become more independent as they have to be responsible with their learning.
Influence of different wavelet bases and threshold estimation on noise reduction of substation fault signals under different SNR

Abstract With the rapid development of power industry, the number of substations is also increasing, and the voltage level is also higher and higher, and the types of equipment are diverse. The detection of equipment fault signal in substation is an important part to ensure the normal operation of electric power. Only timely detection of fault signal and corresponding processing can ensure the overall operation of substation. But the fault signal often contains a lot of white noise, which will interfere with our judgment of the fault point. How to extract the effective signal from the noisy signal becomes particularly important, but under different signal-to-noise ratio, the selection of different wavelet basis and threshold estimation also have a great impact on the noise reduction effect. In this paper, we choose different wavelet bases and threshold estimation under several different signal-to-noise ratios to study their influence on the effect of signal denoising.
Real Time Emotion Recognizer And Classifier For Facial Expressions Based On Machine Learningapproach

There are various fields in deep learning that are known for their big success one such technique is computer vision. In computer vision the detection of face emotion is done using the convolutional neural networks technique where the model can be trained to analyze images or videos. In this paper we propose a system that recognizes the emotions that a person is having at any point of time by checking the emotion from frame to frame in a video medium. It consist of a multistage image processing to extract feature representations. We characterize six emotions based on the boundary of the face and compare it with the existing databases to get the most accurate emotion from the six.
Economic Growth of CEMAC: Does Institutional Quality Matter?

Several factors have often been noted to explain the poor performance of the CEMAC economies. In addition to the traditional factors of economic growth, institutional variables are crucial in explaining the growth of countries. This paper aimed at investigating the relationship between institutional quality and economic growth using neo-institutional theory and neoclassical theory of growth. First difference and system Generalized Method of Moments are applied on the six countries of the Central African Economic and Monetary Community for the period of 1996 to 2014. All the coefficients of the institutional variables are positive except for the quality of regulation and control of corruption. There is a positive and significant relationship between political stability and economic growth in CEMAC zone. This study recommends that political stability should be reinforced for an increase in the economic growth of the CEMAC zone.
ANALISIS KESALAHAN TERJEMAHAN TEKS PANDUAN DARI BAHASA INDONESIA KE BAHASA INGGRIS

The study aims at analyzing translation errors done by the 5th semester students at STBA LIA who were taking Indonesian-ENglish Translation Workshop. There are 28 participants in this study and the data are the translation of manual text which has been adapted and analyzed by using the 12 translation editing and revision by Mossop (2014). These parameters are normally used by editors in editing and revising translation work. The findings show that from that of 12 parameters, the mostly found parameters are mechanics with 46% occurrences, accuracy 13 %, sublanguage 11%, whereas the other parameters such as smoothness has 8.4% occurrences, layout 7.4%, idiom 7%, completeness 4%, and logic 3.2%. The conclusions show that the participants do not have problems at understanding the source text, but they do experience problems in the English’s, as the target language, grammar and natural language usage in English. In addition, they also have problems in choosing the right terminology, and also the usage of writing.&#x0D;
Improved grey wolf algorithm for optimization problems

The grey wolf optimization (GWO) is a nature inspired and meta-heuristic algorithm, it has successfully solved many optimization problems and give better solution as compare to other algorithms. However, due to its poor exploration capability, it has imbalance relation between exploration and exploitation. Therefore, in this research work, the poor exploration part of GWO was improved through hybrid with whale optimization algorithm (WOA) exploration. The proposed grey wolf whale optimization algorithm (GWWOA) was evaluated on five unimodal and five multimodal benchmark functions. The results shows that GWWOA offered better exploration ability and able to solve the optimization problem and give better solution in search space. Additionally, GWWOA results were well balanced and gave the most optimal in search space as compare to the standard GWO and WOA algorithms.
ZERO – Detect objects without training examples by knowing their parts

Current object recognition techniques are based on deep learning and require substantial training samples in order to achieve a good performance. Nonetheless, there are many applications in which no (or only a few) training images of the targets are available, whilst they are well-known by domain experts. Zero-shot learning is used in use cases with no training examples. However, current zero-shot learning techniques mostly tackle cases based on simple attributes and offer no solutions for rare, compositional objects such as a new product, or new home-made weapons. In this paper we propose ZERO: a zero-shot learning method which learns to recognize objects by their parts. Knowledge about the object composition is combined with state-of-the-art few-shot detection models, which detects the parts. ZERO is tested on the example use case of bicycle recognition, for which it outperforms few-shot object detection techniques. The object recognition is extended to detection by localizing it, by taking into account knowledge about the object’s composition, of which the results are studied qualitatively
PENERAPAN METODE FRAME BY FRAME DALAM PEMBUATAN ANIMASI TATA CARA HAJI SESUAI SUNNAH RASUL MENGGUNAKAN APLIKASI 3DS MAX

Advances in technology in the field of information are developing very rapidly at this time, especially information in the field of animation. The animation is a visual form that moves and is used to present information and learning that is difficult to understand if delivered in general. The use of animation media is specially made to find out the procedures for the Hajj pilgrimage in order to increase knowledge for someone who wants to perform the Hajj or want to know the Hajj procedures because Hajj is the fifth pillar of Islam where if someone carries it out, much wisdom will be gained. Information about the pilgrimage procedures is packaged with 3D animation and created using 3Ds Max application and the Frame by Frame method, where all movements of the animation are arranged using frames.
NEW SCHOOL IN NEW COMMUNITIES: THE ROLE OF THE EDUCATIONAL INSTITUTION IN THE DEVELOPMENT OF THE COMMUNITY

Proceedings Article published 2020 in APPLIED AND FUNDAMENTAL SCIENTIFIC RESEARCH
A national vision for information and communication technologies in education: reflections on Singapore's ICT technologies Masterplans

Purpose The purpose of this study is to examine the reform initiatives that began with a focus towards change in the teaching and learning in Singapore classrooms with technology integration. Design/methodology/approach The methodology used in this study is review and descriptive narrative of educational technology polices, initiatives and projects. Findings The Ministry of Education, Singapore, has ensured that schools had infrastructure, leadership and necessary teacher training to successfully implement the initiatives. Originality/value The descriptions of the implementations are valuable lessons for other national systems in the region and beyond, seeking to integrate information and communications technology (ICT) in their education systems.
Designing Smart Ring for the Health of the Elderly: The CloudIA Project

This paper describes the design and development of a wearable device, able to monitor physiological data, movement and falls, for fragile older person who require health care. Some approaches of Universal Design and Human-Centred Design were used, which allowed to evaluate and design the interaction between the person and the system. From a design point of view, studies on wearability and the most appropriate landmarks of the human body were carried out, suitable for monitoring heartbeat, movement and falls. From an engineering point of view, the main challenge was the miniaturization of the electronic components for the development of a wearable device to be placed on a small surface of the body, able to allow the performance of daily activities without altering the natural movements of the user, also considering the physical limitations of older and fragile people. Our results indicate how digital technologies, specifically wearable, can be a resource to support the independence and psycho-physical well-being of old people. The next step of the research program concerns the experimentation with a significant sample of typical users (elderly and socio-health professionals), both in nursing home and at home.
Bullying y ciberbullying: su relación con habilidades sociales en estudiantes de la Ciudad de México

espanolLos objetivos de esta investigacion fueron identificar y determinar la relacion entre las conductas de bullying, ciberbullying y habilidades sociales que presentan una muestra de estudiantes de educacion basica y media superior, para lo cual se llevo a cabo un estudio en dos fases; en la primera, se aplico la Escala de Bullying y Habilidades Sociales que evalua los tres tipos de conductas antes mencionadas (Chavez y Aragon, 2014) a 416 estudiantes; en la segunda, se aplico la Escala Modificada a 449. Los resultados muestran que las conductas de bullying van del orden de 12% a 44% y de ciberbullying de 9% a 25.8%, y que los estudiantes que poseen mayores habilidades sociales presentan menos bullying y ciberbullying, mientras que los estudiantes que presentan mas conductas de enojo encubierto y dificultad para expresar sentimientos y emociones, presentan mas comportamientos de bullying y ciberbullying. EnglishThe objectives of this research were to identify and to determine the relationship among the behaviors of bullying, cyberbullying and social skills presented by a sample of students in elementary, secondary and high school education. A two-phase study was carried out; in the first phase, the Bullying and Social Skills Scale (Chavez and Aragon, 2014) was applied to 416 students and in the second phase, the Modified Scale was applied to 449. The results show that bullying behaviors are in the range from 12% to 44% and cyberbullying behaviors from 9% to 25.8%. Students who have greater social skills have lower bullying and cyberbullying behaviors, while students who refer more covert anger behaviors and those who have greater difficulty in expressing their feelings and emotions show more bullying and cyberbullying behaviors.
Nutting Memorial Library: Celebration of Scholarly Work: Marine Transportation

The Library hosts a Celebration of Scholarly Work each year. Many faculty have their research from the past year nominated and highlighted in this week-long display. This site hosts work from this year's celebration.
BENIFITS OF INTERNET OF THINGS

In this paper we are discussing about internet of things which is booming technology in the today’s world the internet of things the name from itself we come to know that it is an internet or the interconnection of different things the thing is essentially are the devises or the non living things internet of things is a categorization where we interconnect on the nonliving things on device and try to communicate or establish of protocol between them that they can effectively and they can perform in a good manner and all the device are in the home connected to each other are like router, mobiles, tablets, laptops, and many devices like temperature monitoring that these all are connected to the internet of things. The primary commitments are to distinguish the proper arrangements for the foundation and the administration of social connection between things. To depict a conceivable design for the Internet of things that incorporates the functionalities to coordinate things into interpersonal organization. The goals being sought after by the Social Internet of Things (IoT) worldview are clear to enable people to force standards to secure their protection and just access the after effect of self-governing between question associations happening on the articles' social system.
Normative Rule Extraction from Implicit Learning into Explicit Representation

Normative multi-agent research is an alternative viewpoint in the design of adaptive autonomous agent architecture. Norms specify the standards of behaviors such as which actions or states should be achieved or avoided. The concept of norm synthesis is the process of generating useful normative rules. This study proposes a model for normative rule extraction from implicit learning, namely using the Q-learning algorithm, into explicit norm representation by implementing Dynamic Deontics and Hierarchical Knowledge Base (HKB) to synthesize useful normative rules in the form of weighted state-action pairs with deontic modality. OpenAi Gym is used to simulate the agent environment. Our proposed model is able to generate both obligative and prohibitive norms as well as deliberate and execute said norms. Results show the generated norms are best used as prior knowledge to guide agent behavior and performs poorly if not complemented by another agent coordination mechanism. Performance increases when using both obligation and prohibition norms, and in general, norms do speed up optimum policy reachability.
Efficient Encryption then Compression Systems Using Advanced Algorithms for JPEG Images

A new grayscale-based block scrambling image encryption scheme is presented to enhance the security of Encryption-then-Compression (EtC) systems, which are used to securely transmit images through an untrusted channel provider. The proposed scheme enables the use of a smaller block size and a larger number of blocks than the new encryption scheme. Images encrypted using the proposed scheme include less color information due to the use of grayscale images even when the original image has three color channels. These features enhance security against various attacks, such as jigsaw puzzle solver and brute-force attacks. Moreover, it allows the use of color sub-sampling, which can improve the compression performance, although the encrypted images have no color information. In an experiment, encrypted images were uploaded to and then downloaded from Social networking sites, and the results demonstrated that the proposed scheme is effective for EtC systems, while maintaining a high compression performance using advanced compression algorithms.
Time series analysis for predicting Covid-19 infection using Facebook prophet model

The International fright due to the occurrence of COVID has created an emergency act in the field of healthcare, bio medical and drug discovery process. However, finding the feasible solution to introduce a drug is a time-consuming process due to pre-clinical and post-clinical testing process. Prediction and estimation of COVID-19 can help the medical practitioners and government authorities to take preventable measure against the outcomes of COVID-19.From December 2019 to April 2020, 2844712 cases of COVID-19 have been informed, which includes 201315 deaths according to European Centre for Disease Prevention and Control. This drastic condition should be treated not only physicians and other health care providers. There are two types of time series forecasting techniques. The first technique time-domain approach models the forthcoming values as a function of previous and current values. The groundwork of this approach is the time series regression of current values of a time series on its own past values. The assessments of the model are applied for forecasting process. The second technique known as Frequency domain models are based on the interpretations of time using sines and cosines functions. These interpretations are known as Fourier representations. Overall, the technique utilizes regressions on sines and cosines function, to model the behavior of the data. The proposed work used Facebook Prophet model for Time Series Analysis to forecast the trend for the year 2021. The models will act as an inference tool to take decisions during pandemic conditions. © 2021 Karadeniz Technical University. All rights reserved.
Особенности проявлений креативности активных пользователей цифровых технологий

Medvedskaya E. I. Features of the manifestations of creativity of active users of digital technologies
A Survey of Handwritten Signature Verification System Methodologies

Signature is a biometric trait of humans which is used to confirm human identity. Signature is used in authentication and authorization for many official transactions such as bonds, cheques, and card transactions. There are two types of signatures: 1) Online signature, 2) Offline signature. Online signature generates dynamic parameters like velocity, pressure, intensity, force, etc. Offline signature verification consists of mainly 4 components: preprocessing, feature extraction, recognition, and verification. This paper presents a review of offline signature verification methodologies. This paper concentrates the most on the neural network for recognition and verification of signatures.
Modeling And Analyzing Cloud Auto-Scaling Mechanism Using Stochastic Well-Formed Coloured Nets

Auto-scaling is one of the most important features in Cloud computing. This feature promises cloud computing customers the ability to best adapt the capacity of their systems to the load they are facing while maintaining the Quality of Service (QoS). This adaptation will be done automatically by increasing or decreasing the amount of resources being leveraged against the workload’s resource demands. There are two types and several techniques of auto-scaling proposed in the literature. However, regardless the type or technique of auto-scaling used, over-provisioning or under-provisioning problem is often observed. In this paper, we model the auto-scaling mechanism with the Stochastic Well-formed coloured Nets (SWN). The simulation of the SWN model allows us to find the state of the system (the number of requests to be dispatched, the idle times of the started resources) from which the auto-scaling mechanism must be operated in order to minimize the amount of used resources without violating the service-level agreements (SLA).