Reviewerly/exHarmony huggingface dataset:
Speedy Paint Machine / Muhammad Hafizie Ruslan

Locus Company that have been named by my own self have new product to introduce to the consumers which is the Automatic Paint Wall Machine. The company is targeting in supply for this paint machine since it is people need best the way to paint wall in short time.Paint machine a customer-friendly which is helps people saving time and ease to paint the wall. As many years passed by, the living accommodation cost is always increasing.Nowadays, there are some company cannot afford to buy paint machine that is increasingly sophisticated. Therefore, this product can help the consumer to have this technology that is affordable and easy to use. The company target market will be based on big hardware store since this store mostly provides the best equipment or tools for users. For initial intensive selling effort, the company has set the target customers in other words, types of customer groups that would buy our product. My company target customer is for working Contractor Company and family or parent who needs this product to paint the wall they needed without hiring the workers. It is because this product is designed to save time and ease in paint the wall. It will minimize the time for people that not have much time on spending to this kind of activity.
Inclusion School Education Facilities And Infrastructure

Children with special needs need special services due to developmental disorders in children. In terms of disabilities, children with special needs are themselves physically and psychologically limited. Government Regulation No.17 of 2010 Article 129 paragraph 3 states that students with disabilities include, among others: blind, deaf, speech impaired, mentally retarded, mentally disabled, disabled, learning difficulties, slow learning, autism, motor disorders, including victims of drug abuse, and additives, as well as those with disorders that have not yet been identified. Not much different from Ministerial Regulation No. 70 of 2009 article 3 paragraph 2 states that blind, deaf, speech impaired, mentally retarded, mentally disabled, disabled, learning difficulties, slow learning, autism, motor disorders, including victims of drug abuse, and additives, they who have abnormalities, as well as a marker. This study aims to see the availability of facilities and infrastructure for inclusive elementary schools in Bekasi, Indonesia. In addition, this research is also to see the educational background of the teaching staff in these inclusive schools and the readiness of the teaching staff to face any updates to information about special needs and disabilities. This study used a qualitative method with a descriptive approach, the results of this study found that not all schools have the facilities and infrastructure in accordance with government regulations, besides that the background of teaching staff in inclusive schools from the four schools was only found with one person with a special educational background.
Application of Financial Social Accounting Matrix (FSAM) for Analyzing Real-Financial Linkages of Iranian Economy

Prevailing views in Iran suggest that financial sector mobilizes more resource to services than to the commodity producing sectors. On account of double counting in intermediate inputs, the conventional multipliers derived from the Financial Social Accounting Matrix (FSAM) cannot solve this problem. As an alternative to conventional multipliers, FSAM GDP multipliers which indicate the growth performance of financial system of economy are proposed. Using a newly constructed 2016 FSAM for Iran, both conventional and GDP multipliers of Real Social Accounting Matrix (RSAM) and FSAM have been worked out. The overall findings are as follows: First- the average conventional and GDP multipliers in FSAM are larger than their corresponding figures in RSAM. Second- in RSAM, the average conventional multipliers of commodity producing sectors are larger than services whereas the GDP multipliers give the opposite pictures which support the prevailing opinions in Iran. Third- With respect to conventional and GDP multipliers at the sectoral level, the results show that in the case of conventional multipliers, 8 out of 10 top highest multipliers are commodity producing sectors whereas GDP multipliers give exactly the opposite trend which vindicates the resource mobilization of financial sector towards the service sectors.
Machine Learning Algorithm for Sentiment Analysis in Twitter Data

Growth range of interpersonal communication destinations like twitter have a large number of individuals share their musings step by step as tweets. As tweet is trademark short and fundamental method for articulation. So right now, we concentrated on feeling investigation of Twitter information. The Notion Investigation sees as territory of content information excavating and NLP. The exploration of assessment investigation of Twitter information can be acted in various perspectives. Right now, we have taken near investigation of various strategies and approaches of supposition examination having twitter as a data, gathering general assessment by dissecting large social information has pulled in wide consideration because of its intelligent and ongoing nature. For this, ongoing investigations have depended on both internet-based life and feeling examination so as to join enormous occasions by following individuals' conduct. The proposed approach comprises of first building a unique word reference of words' extremity dependent on a chose set of hashtags identified with a given subject, at that point, characterizing the tweets under a few classes by presenting new highlights that unequivocally calibrate the extremity level of a post. To approve our methodology, we arranged the tweets identified with the 2016 US political race. The after effects of model tests have played out a decent exactness in recognizing like and unlike process of subroutine methods.
A SPEAKING LESSON PLAN DESIGN BASED ON CONTEXTUAL APPROACH

The lesson plan is an important part of teaching. To produce a good and systematic lesson plan, English lecturers must be skilled, creative, and innovative to enable students to absorb language learning knowledge easily and effectively. This paper aims to describe information about contextual-based English speaking lesson planning. This study can be useful for English lecturers and researchers as a guide that can help English lecturers to teach speaking English using a contextual approach. This review paper explores the body of research on the term problems of English speaking skills in primary school teacher education, aspects of lesson plans, activity in teaching speaking, teaching cycle, and models of lesson plan using teaching speaking based on contextual approach. The more lecturers apply planning, the better they can internalize planning skills and the better they teach.
Comparison between Machine Learning Algorithms Used for Sentiment Analysis

Sentiment analysis otherwise called opinion mining is the artificial intelligence technique used to analyze and predict the user emotions which can be positive, negative or neutral in a given text using some of the machine learning & deep-learning libraries or models. It is one of the most trending ongoing research area in the artificial intelligence, most of the researchers and business models use this approach for the text mining and analyzing the human sentiments. It is very dif icult to analyze a large number of data set manually this is where the sentiment analysis model comes into play, movie reviews can be used as dataset for training and preprocessing the data. Sentiment analysis on the raw text is a very complicated task due to various reasons such as a sarcastic text or positive and negative sentiment used in the same text. using machine learning algorithms such as logistic regression and naive bayes classification over a cleaned and processed data which is obtained after using tf-idf vectorization on the dataset. This model gives the accuracy and precision of around 95% and can be used in various business models.
Secure Three Layer User Authentication System

Secure Three layer user authentication is a real-time eye tracking which is vital for hand free blink-based password entry. PIN’s (Password Authentication Numbers) are extensively used for security and authentication. PINs are largely used for safety reasons. Password authentication works when a user enters the password using his hands, which might lead to cracking the password through techniques like shoulder surfing or thermal tracking. Authentications with eye blink techniques, does not leave any traces behind as there is no movement or contact with the keyboard during password entry and thus provides a safe environment. Eye tracking helps in locating the image frames sequentially and tracks the center of the eye. This project introduces an application in which we are combining eye blink tracking PIN entry, face detection/recognition and OTP (One Time Password) to avoid shoulder surfing and thermal tracking attacks.
Deep social grouping network for large scenes with multiple subjects

In computer vision, more attention has been paid to group analysis, and the group detection in images becomes a key technology of human analysis on groups. The existing social grouping methods only focus on small scenes with fixed number of persons and cannot deal with large scene images in the real world. This paper proposes the first fine-grained social grouping framework for gigapixel large scene images based on deep learning, which consists of a graph-guided global-to-local partition strategy and a deep grouping network that learns an implicit respresentation for social pairs. The framework has achieved accurate grouping on large scene images. Our method is also applicable to small scene images, and has outperformed the existing methods. The relevant code and the training dataset will be released soon.
The Effect Of Object - Oriented Programming (Adobe - Flash) Based Multimedia Learning Methods On English For Tourism Courses

The purpose of this study are (1) to know an influence on the development of Adobe-Flash multimedia programs on the ability of students to improve vocabulary skills in English For Tourism courses. (2) to find the percentage of the influence of the development of multimedia programs on the ability of students to improve vocabulary skills in English For Tourism courses. This research is an experimental research. The program implementation technique for this research is a preliminary test used to measure students' vocabulary abilities of the material being taught while the final test is carried out to determine student learning outcomes after being treated using Multimedia-based Object- Oriented Programming (Adobe- Flash) learning methods in the eyes English for Tourism lecture.
Digital Preservation of Cultural Heritage: Interactive Documentary of Malay Male Traditional Clothes

This project aims to create a digital archive of Malay Male Traditional Clothes in order to preserve a piece of Malay Heritage Culture. The Malay Male Traditional Clothes, popularly known as Melayu, is a long-standing Malay cultural habit. Men wear Baju Melayu on significant occasions like Friday prayers and formal parties. Many components of the Malay cultural inheritance, however, are increasingly losing their relevance in society as a result of current global pressures. Much of Malay traditional history has been neglected as a result of the Malays' lack of understanding and appreciation. As a result of the introduction of technology and education, the Malays have absorbed many western influences. The problem was that there was no good documentation for Malay Male Traditional Clothes in the archive that could be used as a guide for the younger generation or society. This project will investigate an interactive documentation platform for preserving Malay traditional cultural heritage for men's clothing as part of a strategy to study Malaysia's Malay heritage culture, as well as create a proper film documentary of Malay traditional cultural heritage for men's clothing and evaluate the video documentary's efficacy as a medium for delivering the preservation message. The video production method, which includes pre-production, production, and pre-production, will be employed for this project. This effort will be tried on a group of 20 people, including Malaysians and young people. This initiative is intended to serve as a springboard for Malay cultural heritage preservation initiatives that would serve as a model for future generations in Malaysia.
A study about the research 'What does the Mean Mean' using R

We installed the Shining package to RStudio and carefully learned its functions. However, as the R Shiny package mainly focused on the interactive nature of histogram with different distribution types, we are interested to investigate about the visualization of mean.
Sentiment analysis of legal emails using Plutchik's Wheel of Emotions in quantified format

Sentiment analysis, which automatically extracts expressions from text, has gained a great deal of analysis attention within the past decade. Sentiment analysis for social networking sites has become an emerging field in text mining, however once we quote email that is wide employed in communication in our everyday tasks analysis into email sentiment analysis isn't to identical proportion. Earlier very less work has been done in extracting emotions from emails. The aim of this paper is to perform sentiment analysis and quantify the emotional intentions expressed in emails and highlighting the dominant one by using Machine learning models like Naive Bayes, Support vector machine (SVM), RNN (Recurrent Neural Network), Convolution Neural Network (CNN), Word2Vec and comparing the performance of these model. We have classified the emotion into eight totally different classes of the Plutchik’s emotion wheel: joy, trust, fear, surprise, sadness, expectation, anger, and disgust. we have used TF-IDF (Term Frequency Inverse Document Frequency) for feature extraction, to train Naive-Bayes classifiers and SVM. We have trained all our models on Dens-Dataset and predict emotions from the document passed to that later, which resulted in achieving maximum accuracy using RNN. Dens-Dataset has 10,710 entries containing emotions, which are in Plutchik's wheel.
Mummy Kitchenware / Nur Syafiqah Mat Syet

Mummy Kitchenware is a tool that sell all multipurpose kitchen tools that designed in smaller, innovative, attractive colors and sizes can that can easily-to-grip while traveling or picnic. This product offers reasonable price and quality product.Our product helps to solve customer problem of having difficulties to pack at an instant for a lot of tools. This will help in reducing time consuming of customers since they do not have to think what tool to be brought as well as how to storage them.Furthermore, Mummy kitchenware are estimated to have great potential sales for a year and also look into consideration factors that influence sales before estimate the final market size such as semester break for university students.Lastly but not least, the management team provide good facilities and staff welfare are to maintain the quality of work for employee. Mummy kitchenware have a management structure that determines relationship between activities and the members, and subdivided and their assign roles, responsibilities and authority to carry out different tasks to maintainthe organizations.
Heuristics based Dynamic Multi Task scheduling framework using Differential Equation for distributed computing

Task scheduling on the heterogeneous distributed computing architectures have driven a new initiative on heuristics based paradigm to handle dynamic distributed workloads. Due to the expanding volume and the variety of Multi tasking work flows, task scheduling is often processed on scheduler. However existing scheduler has been modelled using map reduce architecture to task execution with map task and reduce task components. Despite of many advantageous, those model results in performance degradation such as make span and tardiness. In order to eliminate those issues, a new Heuristics based Dynamic Multi Task scheduling framework using Differential Equation for distributed computing has been proposed in this paper. The optimal scheduling solution has been generated using heuristics through differential equation that can quickly identify the efficient resource for execution. Heuristics of task scheduling include the ordering of system resources and predicting the worst case behaviour of the system on the map task and reduce task is based on the adaptive schemes. Further heuristics computes the priority of the task assigned to the resources on the task locality allocation strategies to particular resources. Finally trajectory of the task has been computed on aspect of best configuration on different communication modes towards its task propagation and efficient execution resource. Simulation results of the proposed architecture has been proven to be highly scalable on the proposed distributed computing architecture against traditional state of art approaches on the Google workloads and improves the make span and reduces the tardiness on the task execution.
OUTLIERS DETECTION IN THE STEREO-VISUAL ODOMETRY BASED ON HIERARCHICAL CLUSTERIZATION

This paper presents an approach to stereo-visual odometry without explicitly calculatingoptical flow. Visual odometry is a method of obtaining navigation information by processing asequence of frames from onboard cameras. There are two approaches to processing video information- using well-localized areas of the image - feature points and using all high-contrast pixels- a direct method. The direct method works by using the intensities of all high-contrast pixels inthe image, making it possible to reduce the computational complexity spent searching, describing,and matching feature points and increasing the accuracy of motion estimation. However, methodsof this class have a drawback - the presence of moving objects in the frame significantly reducesthe accuracy of the estimation of motion parameters. Outlier detection techniques are used toavoid this problem. Classical methods for detecting outliers in input data, such as RANSAC, arepoorly applicable and have high computational costs due to the computationally complex functionof rating hypotheses. This work aims to describe and demonstrate an outlier detection approachbased on the hierarchical clustering algorithm, which selects the statistically most probable solution,bypassing the stage of rating each hypothesis, which significantly reduces the computationalcomplexity. For hierarchical clustering, a measure of the distance between hypotheses with lowsensitivity to errors in estimating motion parameters is proposed. An extension of the stereo-visualodometry algorithm is also proposed to work in more complex visibility conditions due to the transitionfrom the intensity representation of the image to a multichannel binary one. Transformingan image to a multichannel binary representation gives invariance to changes in image brightness.However, it requires modification of nonlinear optimization algorithms to work with binary descriptors.As a result of the work, it has been shown that the proposed outlier detection algorithmcan operate in real-time on mobile devices and can serve as a less resource-intensive replacementfor the RANSAC algorithm in problems of visual odometry and optical flow eviction. Qualitativemetrics of the proposed solution are demonstrated on the KITTI dataset. The dependences of theperformance of the algorithm on the parameters of the algorithm are given.
The tightness of multipartite coherence from spectrum estimation

Detecting multipartite quantum coherence usually requires quantum state reconstruction, which is quite inefficient for large-scale quantum systems. Along this line of research, several efficient procedures have been proposed to detect multipartite quantum coherence without quantum state reconstruction, among which the spectrum-estimation-based method is suitable for various coherence measures. Here, we first generalize the spectrum-estimation-based method for the geometric measure of coherence. Then, we investigate the tightness of the estimated lower bound of various coherence measures, including the geometric measure of coherence, $l_1$-norm of coherence, the robustness of coherence, and some convex roof quantifiers of coherence multiqubit GHZ states and linear cluster states. Finally, we demonstrate the spectrum-estimation-based method as well as the other two efficient methods by using the same experimental data [Ding et al. Phys. Rev. Research 3, 023228 (2021)]. We observe that the spectrum-estimation-based method outperforms other methods in various coherence measures, which significantly enhances the accuracy of estimation.
Use of augmented reality as a means of cognitive development of preschool-age children

The article analyzes the research of domestic and foreign scientists who consider augmented reality as a modern means of learning. Aspects of research of the problem of introduction of AR in education are defined, in particular: increase of efficiency of training and motivation of children through use of AR-applications on smartphones; formation of reading culture by means of augmented reality technology; introduction of augmented reality technology in the educational process of preschool education; prospects for the use of augmented reality in the educational process. The practical significance of the use of augmented reality in working with preschool children is considered, in particular: the specifics of publications of works of art with AR-applications, which should be used in working with preschool children; the possibilities of coloring books for preschool children created with the help of augmented reality technology are clearly demonstrated. The conducted experimental research gives grounds to believe that the use of augmented reality technology in classes with older preschool children is appropriate and useful, provided that the methodological recommendations for the use of AR-applications on smartphones. It is established that the use of AR in the educational process has a number of features and benefits, in particular, augmented reality technologies have a positive effect on the emotional and volitional sphere of children, increase children's motivation to learn new things, stimulate children's interest in learning new themes, develop emotional intelligence and creative thinking children, create effect of miracle, bring the characters of augmented reality books closer to children, and children are immersed in augmented reality, compensate for the underdevelopment of creative imagination in children, cause qualitative changes in the educational process of preschool education.
Aggregation in quantum networks

When packets of information go through a network, each packet can be transmitted on a different route. The aggregation of quantum network provides a potential for us to use communication channels more efficiently and may contribute robust transmissions of quantum information with less quantum resources. To evaluate this possibility, we use multiplexing of independent quantum channels to distribute quantum error correction over the network. In this talk we also apply spatial-temporal single photon multiplexing and observe a significant saving in the quantum communication resources, and further we discuss how such quantum networks differ from their classical counterparts.