Reviewerly/exHarmony huggingface dataset:
Online Shopping E-commerce Android Application and E-commerce Website Development

Abstract: We are designing an app that directly sells its products to the customer. As compared to other apps which have tie-ups with multiple retailers. Eg: Amazon is an online shopping App which is collaborated with multiple companies; So Amazon becomes the 3rd party vendor. Due to our App there will be no such 3rd party vendor in the whole sale process because by using our App customers will be directly connected to the manufactures of the products. By using this application customers can directly get the required products of the Company directly from the company that to in manufacturing rates. By using the website of our client one will be able to compare wide range of products and also be able to purchase those. This report will be consisting all the design plan of the app as well as the design plan for the client website &amp; Search Engine Optimization for the same. Keywords: E-Commerce, Website Development, Android App Development
Mentoring Program: How it improves teachers ability to engage pupils in a variety of activities in kindergarten

&lt;p&gt;At the beginning of the learning process, class routines in the form of basic talks, songs and games are one way for kindergarten children to get used to practicing English at a young age and building their self-confidence to communicate with their friends. Thus, the aim of this study was to elaborate the mentoring activity in training teachers on how to incorporate various activities into the classroom routine. Four female teachers of an Islamic private Kindergarten participated in the mentoring program. This is a case study design of qualitative research with classroom observation and interviews. The study revealed that teachers were able to demonstrate some classroom activities through short dialogues, songs and games. It indicated that mentoring activity is found to provide participants with benefits and satisfaction, as well as the potential to motivate them to practice with kindergarten children in classroom.&lt;/p&gt;&lt;p class="BODYPARAGRAP"&gt; &lt;/p&gt;
AI for Health-Related Data Modeling

Data modeling of health-related data from Data Center (DC) has positive effects for health monitoring, disease prevention, and healthcare research. However, health-related data has the characteristics of huge, high-dimensional, and non-normalized, which are not beneficial to direct analysis, so data needs to be preprocessed before data modeling. This paper focuses on the features of health-related data, and outlier detection during data preprocessing is studied. Meanwhile, we propose an improved algorithm for health-related data based outlier detection. The experimental results reveal that the proposed outlier detection algorithm has a smaller running time, and more outliers are detected compared to three baselines. In addition, local importance based random forest feature selection algorithm is proposed to measure the importance of each feature. The experimental results indicate that the proposed algorithm can select optimal feature subset to apply health-related data.
Artificial Intelligence or a Neoliberal Marketing Scheme?

&#x0D; &#x0D; &#x0D; Virtual influencers are a trending media curiosity, given that they can easily blur racial boundaries, as well as boundaries between authenticity and falsehood. One of the most popular stars of the virtual influencer world is Lil Miquela (@lilmiquela), a virtual avatar of ambiguous ethnicity who follows both popular fashion and politics to boost sponsored brands. This article situates Miquela within the performative ecology of Instagram, blurring the lines of her racial identity and authenticity as an emerging form of commodity activism online. As a 3-D Computer-Generated Image (CGI), Miquela’s racialized design poses questions about the representations of the Instagram category for ‘Black/Brown women,’ which are undermined by the appropriation of mixed-race features in her racially ambiguous design. Miquela is also a virtual influencer, and her creators at the technology and media company Brud label her as an “artificially created robot,” further blurring the boundaries between authenticity and falsehood in Miquela’s posts. These boundaries are further informed by the political economy of influencers on Instagram, which engages with the platform affordances of Instagram, namely the platform’s environment of commodity activism and its neoliberal logic. Pulling from André Brock’s Critical Technocultural Discourse Analysis (CTDA), this article examines how the platform affordances of Instagram and the political economy of influencers have significantly shaped the performative nature of Miquela’s racialized design, as well as her racial identity politics online. This article concludes with the potential empowerment of Black/Brown women in charge of art technology (e.g., Miquela), as well as the demand for government and platform regulations to significantly distinguish virtual influencers like Lil Miquela from human influencers.&#x0D; &#x0D; &#x0D;
Pedagogical activity of John Dewey in the electronic information and bibliographic resource "Outstanding teachers of Ukraine and the world"

The pedagogical ideas of American teacher and philosopher John Dewey in the domestic pedagogical discourse, in particular, in the fundamental scientific research of leading specialists in the field of innovative pedagogical science, lays the foundations for the civilization development of the educational system of Ukraine, in the content of which the educational paradigm of pragmatism is an effective tool for influencing the change of approaches to traditional educational practices, providing an opportunity for individual development in the modern educational system. The essence of the social and pedagogical heritage of the American philosopher, who defined learning as an active, creative process of personal development, is justified. It focuses on methodological principles of the social and educational concept of the scientist in the sense of modernization of historical education. On the basis of the study of historical sources, the leading directions of pedagogical activity of the teacher have been identified, and a comparative description of teaching methods in the traditional educational system and pedagogical theory of John Dewey has been made. The basic principles of learning (behind John Dewey) are highlighted: problems, interactivity, orientation towards personal development of students. It has been established that the idea of developing a child, according to John Dewey, should be in the interests of the child and directed to the formation of his or her progressive and active personality; focus it on identifying personal interest in acquiring new knowledge and its scope of application in one's own life. It is stated that the most important task of the teacher is to create conditions for the student's interest in obtaining new knowledge, to promote the education of active, proactive, independent and responsible people who are ready to plan, make decisions and be responsible for them. John Dewey's views have been proven to be an alternative to the traditional education System developed by the system of argument, which is based on exclusion from well-established norms of social growth, an orientation towards decision-making based on one 's own experience, which is more orderly and meaningful in content to shape the individual. It was concluded that in the context of the reform of historical education, interest in the philosophical and educational heritage of John Dewey, who proposed a model of a socially oriented school based on the development of a child, is again growing.
Embedding Hallucination for Few-shot Language Fine-tuning

Few-shot language learners adapt knowledge from a pre-trained model to recognize novel classes from a few-labeled sentences.In such settings, fine-tuning a pre-trained language model can cause severe over-fitting.In this paper, we propose an Embedding Hallucination (EmbedHalluc) method, which generates auxiliary embedding-label pairs to expand the finetuning dataset.The hallucinator is trained by playing an adversarial game with the discriminator, such that the hallucinated embedding is indiscriminative to the real ones in the finetuning dataset.By training with the extended dataset, the language learner effectively learns from the diverse hallucinated embeddings to overcome the over-fitting issue.Experiments demonstrate that our proposed method is effective in a wide range of language tasks, outperforming current fine-tuning methods.Further, we show that EmbedHalluc outperforms other methods that address this over-fitting problem, such as common data augmentation, semi-supervised pseudo-labeling, and regularization.
Sindrom Misogini Dalam Cerpen “Wah Wah Wah’ Karya Tsi Taura: Analisis Psikologi Sastra

Short stories as part of literature are the universe of reality in which there are events experienced by the actors. In the short story Wah Wah Wah, it can be seen the presence of a psychological phenomenon experienced by the main character. The psychological phenomenon was studied using a literary psychology approach and misogyny. The method used is a qualitative method with a hermeneutic approach. This approach is considered capable of maintaining the authenticity of the text. The results of this study indicate that the misogyny contained in the Wah Wah Wah short story is caused by trauma or the treatment of his wife, children, and daughter-in-law to the character Si Aku. Before marriage he did not hate women. This can be seen from his attitude towards his dead mother. He didn't hate his mother. Due to chronic misogyny, eventually gradually turned into a permanent mental disorder. This is because there is no treatment from a psychologist and family support. He experiences stress and his soul is disturbed or crazy.
Sentiment Analysis of International Relations with Artificial Intelligence

Geopolitical strategy is characterized by a dynamic and complex structure of entity relationships, geo-spatial data and human decisions. We employ machine and deep learning techniques to retrieve the sentiment between countries through scraping and analyzing news articles. The change in the sentiment score between countries allows to analyze historic developments of international relations as well as to evaluate the primary and secondary network effects of potential events and policy decisions on the global relationship structure. We find that the key for the most accurate real mapping of the sentiment score between countries is the maximization of the quantity of news while simultaneous minimization of the noise added by the news. Moreover, we show the potential of Artificial Intelligence (AI) to improve and forecast international relations. Keywords: Natural language processing, international relations, sentiment analysis, geo-political forecasting.
DETECTING ABUSIVE AND INSULTING COMMENTS ON SOCIAL MEDIA

Now a days, Social media has become a very important mode of communication. Billions of people communicate through various social networking sites. People are using these sites as a medium to express their views and opinions. As the faces of the coin, there are both pros and cons by using this medium. One of the major problems is the insulting and the abusive comments that we get on the social media. Hence, the need for good quality automated abusive language classifiers becomes important. Our project “Detecting Abusive and Insulting Comments on Social Media” aims at designing a system for automatically detecting comments on social media as abusive or non-abusive using machine learning algorithms such as Random Forest classifier and Artificial Neural Network techniques (ANN).
Design of hand detection based on attention and feature enhancement pyramids

Hand detection plays an important role in human–computer interaction. Because of the convenient and natural advantages of hands, hand detection is increasingly used in virtual reality, remote control, and other fields. However, since the complex background and the diversity of hand postures, the YOLOv4 algorithm for hand detection suffers from low accuracy and robustness. Therefore, A YOLOv4-HAND network, improved from YOLOv4, is proposed to solve the problem. We first use the dilation convolution to build the feature enhancement pyramid that enables the network to expand semantic information. Second, for better detection of different hand scales, we design a multiscale attention module to capture the correlation of channel information within different scales. Third, we design a head that incorporates a spatial attention module to compensate for the network’s lack of spatial contextual location information correlation. Finally, we use soft nonmaximum suppression to reduce the impact of occlusion. The results show that the YOLOv4-HAND detection network can achieve 83.22% and 93.95% mAP on the publicly available datasets Oxford hand and Egohands datasets. Compared with the most recent method, the YOLOv4-HAND network effectively improves the accuracy of hand detection for practical applications.
RECOMMENDATION SYSTEM FOR TOURISTS

This project uses statistics from previous tourism experiences to recommend travel areas to travelers. To recommend a traveling area, we use the C4.5 decision tree algorithm with some specific criteria. To promote new locations, all existing algorithms, such as collaboration algorithms and content filtering algorithms, employ the most recent user experience data. If the present user does not have any previous experience data, these algorithms will fail. Another solution to the problem is to utilize the C4.5 decision tree method to build the model based on prior users' experiences. When a new user enters a requirement the decision tree predicts the best and most accurate location. The decision tree does not require any additional user experience data. To use the decision tree model, you'll need a dataset. Pre-processing techniques can be used to eliminate empty or wrong values from this dataset, which can hurt the decision tree model. It is possible to remove the value. To predict or build the model, it may not be necessary to use all of the column values in the dataset. To remove unwanted features a feature selection algorithm is used. The MRMR feature selection algorithm is used to remove extraneous attributes, minimize the building model's execution time, and increase the system's correctness.
ELT During The Covid-19 Pandemic; Practices and Challenges

The purpose of this study is to evaluate the practices and challenges of online learning or so called Learning From Home (LFH) in English Department during the even semester 2019/2020 academic year. The subject of this study are 8 lecturers of English Department at STKIP Al Hikmah. This study employed descriptive qualitative research design. The instrument used is daily online teaching monitoring and evaluation questionnaire. The result of this study is categorized into five aspects namely 1) online learning applications frequently used by the lecturers are WhatsApp, Google Classroom, Schoology, Quizizz, E-mail, Zoom Cloud Meeting, Email, and Youtube 2) online learning activities frequently conducted by the lecturers are uploading materials, discussion forum, conducting quizzes, uploading assigment,, and video conferences, 3) scheduled assignment submission rate, 4) students’ participation rate and 5) challenges and alternative solution proposed by the lecturers during the online learning.
A Robust Business Specific Real-Time Sign Language Translator

Abstract: Communication is a great way of expressing yourself but not everyone is capable of communication. No, not everyone chooses to be silent, While some are born deaf and mute, others become one later in life due to certain conditions. The word “dumb” is quite offensive so I will address to someone who cannot speak as mute person throughout this paper. Returning to the topic this paper will enable a more effective way to fill the communication gap between deaf and mute person and normal person especially in places with crowd where special-abled person becomes nervous and anxious to make the business owner understand of his needs easily and are unable to express themselves. In order to remove this barrier and enable the effective communication between the special-abled buyer and the business owner, I have created our own data set of hand gestures and trained using Google Teachable Machine for common sentences that are exchanged between the buyer and seller. Keywords: Sign Language Translation, AI, Special-Abled Communication, Google Teachable Machine Model, OpenCV, Computer Vision, Machine Learning, Deep Learning.
CONTROLLING VIDEOLAN CLIENT MEDIA USING LUCAS KANADE OPTIMAL FLOW ALGORITHM AND OPENCV

In this project we've discussed a system which uses some dynamic hand gesture recognition technique to manage the media players like VLC media player. This project consist of certain modules which segments the foreground a part of the frame using detection of skin colour and approximate median technique. the popularity of hand gesture is finished by creating a call Tree, that uses certain features extracted from the segmented part. This hand gesture recognition technique introduces a replacement, natural thanks to interact with computers and is beneficial to several folks in our day-to-day life. Hand gestures are associated with the human hands in hand gesture recognition. This project is employed for controlling certain operations (Pause, Play, Volume up, Volume Down, Mute) on video player by mere hand gestures without getting in the rigmarole of pressing buttons or tapping onto the screen. this may be directly associated with our day to life like in presentations. We have considered hand gestures and their directional motion defines a gesture for the applying. during this application image retrieving is finished employing a Webcam. Some functions in VLC media players are used most often and these functions uses some predefined gestures. Shows the defined gestures in keeping with the VLC player control operation. We created a VLC Media Player Controller using Hand Gesture Recognition System to form ‘HUMAN LIFE EASY AND BETTER’. This project is implemented using two steps: (1.) Creation of Hand Gesture Recognition System: this is often done using image processing using OpenCV library. (2.) Controlling VLC Media Player using hand gestures: during this step we controlled the player using shell commands which were recalled using python commands through OS library
EDUCATION FINANCING MANAGEMENT: Study at Binamitra Cikarang Vocational High School

AbstractThis study aims to determine the Education Financing Planning, which is in SMK Binamitra Cikarang. The method used is descriptive qualitative research method. Respondents in this study were school principals, heads of administration, administrative staff, and several parents and guardians of students. The source of funds owned by Binamitra Vocational School comes from the foundation's own funds, funds from student guardians for education funding, funds from the central government (BOS) and funds from the district (BPMU), as well as temporary assistance from several companies. In the economic context, the total short-term cost is the same as the fixed cost plus the variable cost. By looking at the existing financing at Binamitra Vocational School, it is divided into three financing costs, namely investment costs, personal costs and operational costs. All of which are described in the RAPBS of Binamitra Vocational High School. From the results of the research, that for the running of the RAPBS at Binamitra Vocational School through the stages, namely: 1) planning, 2) implementation, and 3) reporting and evaluation. To avoid program errors, there must be an evaluation. Evaluation is usually done two weeks a month. From the results of data analysis, the research findings are as follows: the 100% agreed budget has not been fully realized, there are still changes to be improved.Keywords: Management, Education Financing, SMK Binamitra Cikarang
Machine Learning Techniques for Opinion Mining from Social Media

Expressing emotions through various channels is part of human life.Directly or indirectly, we somehow reflect our opinions through speech, writings, etc., in our daily life.Opinions containing emotional or sentimental words have huge impact in the society.Analyzing the emotions and sentiments of people has its own importance.For example, we can measure the well being of a society, prevent suicides, and measure the degree of satisfaction of their customers by analyzing the comments or the feedback.The world wide web sites like social media, forums, review sites, and blogs generate a large volume of data in the form of opinion, emotion, and sentiment about social events, government policies, political events etc. Increased use of technology has made people proactively express their opinion through social media sites like Twitter, Facebook, and Instagram.Decision makers can make use of social media content to understand how people react to policies, events, and consumer products.But, social media analytics is a complex task due to the challenges in the natural language processing of social media language.These messages do not adhere to grammatical standards.The unstructured data from the social media needs to be cleansed and well-structured for opinion mining.These messages often reflect the opinion, emotion, and sentiment of the
Two Image_Keys to Increase Security Level of Secret Data Cryptography

Color digital images are one of the most common types of digital data circulated through various social media, due to their use in important vital applications. The digital image may be confidential or of a personal nature, or it may provide a carrier of confidential data, which makes providing a secure method of protection for it extremely important in order to protect the image from penetration and protect it from any side that has nothing to do with the image. In this research, a secure method will be presented to protect data, and this method will be multi-purpose, as it can be used to protect short and long secret messages and protect digital images regardless of their type or size. The high level and difficult to penetrate degree of protection will be achieved through the use of two colored images to generate two secret private keys to be used in the process of encrypting and decrypting confidential data. This method will be applied in order to prove the extent to which this method fulfills the requirements of a good method of data cryptography by checking the calculated values of the quality parameters (MSE, PSNR and CC) during the encryption and decryption phase. The practical results of the proposed method will be compared with the results of the standard methods used in data cryptography process to prove the efficiency of this method and to indicate the extent of the effectiveness of this method by increasing the throughput of the cryptography and by minimizing the encryption-decryption time.
Finite-Key Analysis of 1-Decoy Method Quantum Key Distribution with Intensity Fluctuation

The decoy state quantum key distribution (QKD) protocol is proven to be an effective strategy against the photon number splitting attack. It was shown that the 1-decoy state protocol, easier to implement in the practical QKD system, outperforms the 2-decoy state protocol for block sizes of up to 108 bits. How intensity fluctuations influence the performance of the 1-decoy state protocol with finite resources remains a pending issue. In this paper, we present a finite-key analysis of the 1-decoy state protocol with intensity fluctuations and obtain the secret key rate formula about intensity fluctuations. Our numerical simulation results show that the stronger the intensity fluctuations, the lower the secret key rate for a small data block size of a few bits. Our research can provide theoretical implications for the selection of data size in the QKD system with intensity fluctuations.