Reviewerly/exHarmony huggingface dataset:
Room cleaning robot movement using A* algorithm and imperfect maze

Cleanliness is a mandatory requirement to help prevent virus spread. The cleaning process can be done automatically by humans or robotic devices. If a robot does this process, it is a must that the robot is able to explore the room autonomously. The robot movement in room tracking should reach all points without obstructions and return to its initial position. This study simulated the movement of a room explorer robot using the imperfect maze method, as well as searching a room that has not been explored using the A* algorithm. The A* algorithm was also used to find the shortest path to reach the initial place of the robot when the room exploration was completed. The results of the simulation showed that the imperfect maze could be used to explore the room well, and A* algorithm is quite optimal to be used for searching both the unexplored room and the path to return to its initial position&#x0D;
Population dependency and inflation: a study of high- and upper-middle-income countries

In recent years, whether demographic change creates an inflationary trend is examined frequently. Debates on whether the decrease in the population at active working age and the dependency ratio because of the increasing old age cause an inflationary trend points to an area where no consensus can be reached. In this context, the tendency of the total population dependency ratio, young population dependency ratio and elderly population dependency ratio to affect inflation, which represents population aging and demographic change, was examined in this study. Panel cointegration, panel ARDL and panel causality analysis methods were used in the study conducted on 29 Upper Middle and High Income country economies in the period covering 1980-2020. The main findings got from the study reveal that the elderly population dependency ratio, which is defined as the elderly population dependency in the short term, has a deflationary effect, while the young population dependence has an inflationary effect in the long term. Key words: population dependency, inflation, cointgration, panel data analysis, Dumitrescu-Hurlin panel causality
A NEW COMPUTATIONAL MODEL FOR TURKIC LANGUAGES MORPHOLOGY AND PROCESSING

Effective communication between representatives of different nations in the modern global world has become a very relevant problem. Towards its solution, considerable support can come from artificial intelligence tools and, in particular, from natural language processing components. Along this direction, this article proposes the development and the exploitation of new computational morphology model for Turkic languages, based on a complete set of endings (CSE - model). Based on the CSE-model of morphology, a methodology has been developed for the creation and use of universal programs (data-driven) for processing natural languages. These include word stemming, text segmentation and morphological analysis. One advantage of the proposed methodology is that it is oriented towards linguists that only have to prepare i) a list of complete sets of endings for new languages ​​according to the described method, and ii) a list of stop words that do not have endings. Then, based on the prepared lists, the developed universal programs for stemming, segmentation, morphological analysis are used. Experiments carried out for the Kazakh, Kyrgyz and Uzbek languages ​​show a high efficiency of the proposed morphology model, algorithms and tools.
Applying Geoaccumulation Index and Enrichment Factor for Assessing Metal Contamination in the Sediments of Euphrates River, Iraq

The current study looked into heavy metal poisoning of the Euphrates river which runs from Al-Kifl to Kufa in Iraq. One of the goals of this research was to determine the pollution levels and the contamination sources. We looked at six heavy metal (Cd, Pb, Zn, Cr, Fe, and Mn) characteristics in sediment, taking samples from six sites along the Euphrates every season from March 2020 to January 2021. To assess pollution levels, three indices were chosen: enrichment factor (EF), geo-accumulation index (I-geo) and contamination factor (CF). According to EF, the Cd and Pb elements recorded considerable enrichment, very high enrichment and extremely high pollution at practically all sites in four seasons, while the remainder of the HMs recorded deficiency to minimal enrichment and moderate enrichment. In all seasons, the geo-accumulation index showed significant contamination with Cr and moderate to low contamination with other metals. Except Cr in spring, which was recorded with moderate contamination, significant contamination and very high contamination, the CF values of all metals in all sites indicated no sediment contamination by these elements.
Information and Communication Technologies – a Contemporary Tool for Education

The research presents the advantages of using information and communication technologies in education. New applications are described which help in easier learning of the educational material. The opportunities that ICT provide for presenting information in an interesting way to motivate students are presented. Information and communication technologies (ICT) are an essential part of our daily lives. They have entered education at a very fast rate. School education has also changed in a short time. Teachers aim to use new methods and information and communication technologies to arouse students' interest in the educational process.
Informal Educators as a Subjects of Pedagogical Interaction in Pedagogy of Informal Education

The article presents the characteristics of informal educators as subjects of pedagogical interaction in Pedagogy of informal education, created by the author in 2020 as a new self-contained branch of pedagogy. Against the background of the new global and European goals until 2030, the prehistory of the PIE and the characteristics of informal education as a complex three-component category with integral meaning are presented. The features of informal educators as drivers of PIE are revealed. A relatively complete list of informal educators is compiled and their typology is shown according to two criteria. They are described through the six substantial questions of being. The personal qualities of the person who wishes to take on the role of an informal educator are specified: knowledge, skills and competences, psychological characteristics and attitudes. Examples are given of how each person can become an informal educator of himself or someone else, and how through informal education a hobby can become a profession.
General Purpose Recommendation System

A recommendation system is a class of information retrieval systems that provides personalized suggestions to users. Our approach is to generalize the process of creating a recommendation system so that it can be used effectively in multiple domains. This approach can be achieved by collaborative filtering by using the website’s clickstream analytics. Data related to user clicks can easily be extracted and this data's use is limited to analyse the user behaviour. We can use this extracted data to generate recommendations for the users and increase engagement on the website. The identifiers of users and items can be passed along with the user click rate to a supervised machine learning model of matrix factorization. We are using alternating least square (ALS) to predict the recommended items. The suggested system interfaces with the client system using a web API which will collect data and generate recommendations
Free Voluntary Reading to Promote Learners Autonomy in Vocabulary Acquisition: The Case of Universitas Internasional Batam

Purpose - The purpose of this study was to find out what strategies EFL students used to developvocabulary through personalized reading materials. In addition, this study was also conducted to findout how Free Voluntary Reading help students develop their vocabulary as EFL.&#x0D; Design/methodology/approach - This study uses a descriptive qualitative research design in answeringthe research questions. Researchers conducted in-depth interviews to the students of EFL class of 2019and 2020 in the English Language Education Department. There were 11 students (22,4%) who wereinterviewed in this research.&#x0D; Findings/results – The results showed that the strategies used by EFL students were as follows: readingauthentic materials, choosing reading materials according to genres, making notes about newvocabulary, and always looking for any content with English subtitles. In addition, the researcher alsofound out how several forms of Free Voluntary Reading helped the vocabulary development of EFLstudents.&#x0D; Originality/value - Free Voluntary Reading has an important influence on EFL students, especially indeveloping vocabulary.&#x0D; Paper type – Research paper
A Robust Audio Steganography Method Using Partial Knight Tour for Concealing Messages of Text and Image

The rapid growth in transfer of data over the Internet realized the need to secured data transmission. Moreover, there is a need to send message that contains a text and image. The steganography is the most promising technique for facilitating the secure communication without affecting the data quality. In this paper, we propose a robust audio steganography approach that hides secret messages of text and image in an audio WAV file using partial knight tour positions in 4×8 square blocks. The cover audio is divided into 4×8 (or 32) audio sample blocks. The secret data are converted to bits and selected 4×8 audio bytes then can hide ASCII codes of 4 characters. The hiding of secret data block is based on a random selected starting audio byte, and on a random selected tour of 32 predefined tours. The algorithm changes the least significant bit (LSB) of the audio bytes based, as mentioned, on randomly selected tours and randomly selected starting audio byte. The resulted stego file can be, then, transmitted over the communication channel such as Internet to the receiver side. After receiving, the extraction process is performed to extract the secret message. The proposed algorithm is implemented us[ing C# programming languages. The PSNR and MSE parameters are used to evaluate the efficiency of the proposed algorithm and they will be checked after implementation. The proposed technique provides a high quality of Peak Signal-to-Noise Ratio (PSNR) and Signal to Noise Ratio (SNR).
Legacy Data Center Network (DCN) Reviewed: considering Big Data Stream Mobile Computing (BDSMC) applications

Recently, Enterprises that operate over vast geographical areas uses multiple data centers to collect, store and process data in real time via energy-efficient acquisition, wirelessly transport clients or users data to the cloud. This paper seeks to technically review existing Data Center Networks (DCN) considering BDSMC applications. In this research, related works on Distributed Data Center Networks will be presented. Within the stream computing ecosystems, there are various network models but the pool of possible DCN topologies/architectures to adopt appears little and unfit for the purpose of BDSMC optimization. However, most related Data center architecture will be reviewed. Investigate efforts on both server centric and switch-centric models adaptable to BDSMC network layer. The extent of work done on distributed spine-leaf re-designed server-centric network construction so as to automatically harvest network interconnection into a ‘stellar’ dual-port server-centric SG network; how classical graph-based interconnection network translate network performance similar to generic works for BDSMC ecosystems. Review stellar transformation using the well-studied generalized hypercube family of interconnection networks for BDSMC ecosystems. The literature was searched from the databases: IEEE Xplore Digital Library, Springer Link Digital Library, and Google Scholar, IET Digital Library, Frontiers Library, ACM Digital Library repositories resulting in 98 papers after several eliminations ranging from year 2000-2022. In conclusion, state-of-the-art dual-port server-centric DCNs (FiConn, DCell, DPillar), etc, while looking at possible architectures with excellent comparative performance for BDSMC ecosystems. Research gaps are revealed for further study. Keywords: Data, Center, Network, Data Stream, Mobile Computing and applications
An introduction to deep learning for electromagnetics

This chapter provided a gentle introduction to DL, recalling the most used terms in this field as well as describing some of the most widespread architectures in the recent literature and their applications in EM.
THE USE OF NUMBERED HEAD TOGETHER (NHT) METHOD TO IMPROVE STUDENTS’ SPEAKING SKILL

English is used as communication in the world. It becomes an international language. There are four skills in English, namely speaking, listening, writing, and reading. Because English is used for communication, automatically speaking is most important in communication. But in reality, speaking is the lowest of them, so that to face this problem there must be some ways and solutions to improve the students speaking skills by using the unjoyful in the teaching-learning process. In this case, the researcher used cooperative learning to improve speaking skills. This study uses Class Action Research. Classroom action research can improve the teaching and learning process of speaking in class. The Classroom Action Research has four steps to conduct research. They are Planning, Implementing, Observing, and Reflecting. Every step has a different activity. The researcher always undergoes this process because it is a procedure to obtain the data result. The researcher has examined the speaking skills in tenth-grade excellent class program Madrasah Aliyah Al Amiriyyah Blokagung. Class Action Research conducted as much as these two cycles can improve speaking skills in students with a percentage number that is on the test Pre percentage amount 29,9% after the first cycle studies with cooperative learning, the number of percentages increased to 54,2%, but the number still has not reached the minimum value criteria of success of 80%, thus continuing the cycle II and the results of 83,3%. That amount has reached the minimum value criteria of success. From the description of the results of a classroom action research can be concluded that, learning cooperative learning model can improve speaking skills in the grade ten featured program Madrasah Aliyah Al Amiriyyah Blokagung 2020/2021 school year.
Impact of human resource management practices on employee engagement (An applied study on private banks in the City of Taiz)

The study aims to analyze the impact of human resource management practices on employee engagement in private banks in the city of Taiz . The study depended on the descriptive approach , and used a questionnaire consists of 47 questions which was designed according to five- Likert scale. Data were distributed and collected from (114) male and femal employees who work in private banks in the city of Taiz . The results indicate that the reality of implementing human resource management practices in private banks in city of Taiz is high and the level of employee engagement is also high. The results also show that there is a statistically significant effect of HRM practices (simultaneously) on employee engagement. Besides, the two dimensions of recruitment and selection (β = 0.255) and management of the work environment (β = 0.606) have a significant impact on employee engagement, while other dimensions have no effect. Moreover, the results show that human resource management practices explain 37.8% of the variance in employee engagement. That is, the greater improvement in human resource practices in private banks in the city of Taiz, the greater the employee engagement. Finally, suggestions can be made to managers of private banks in the city of Taiz to pay more attention to human resource management practices as being new strategies and an effective path for development, quality improvement and enhancing employee engagement .
AN APPROACH TO GENERATE AUTOMATIC QUESTION AND ANSWER USING MACHINE LEARNING

Today's time is the era of artificial intelligence and slowly things are based on artificial intelligence, in today's time, many questions arise in the minds of people and they need their answer as soon as possible. And in today's time, many times people find the answers to their questions or the answer to the question on the computer and the computer feeds inside itself already on the basis of the predefined answer, but many times it happens that we want to answer those questions. Which is in front of us in the form of an article, and in the matter of education, the same problem is faced by the children because in today's time when the epidemic has spread and the children are locked in their homes and they cannot go to school, at such a time, we have a There is a need for such a system which reads a sentence itself and prepares its own questions and answers, so that it will be difficult for the child to understand the lesson. Many times it also happens that people are a little educated and when they read a newspaper or article, they do not understand the essence of that news, at such a time if there is such a system that can question and answer a paragraph itself. How good it would be if we prepare the answer, we would have felt the need of such an artificial based system. But the system which is present in today's time does not give much better response.
IMPLEMENTATION OF DATA LEVEL APPROACH TECHNIQUES TO SOLVE UNBALANCED DATA CASE ON SOFTWARE DEFECT CLASSIFICATION

Defects can cause significant software rework, delays, and high costs, to prevent disability it must be predictable the possibility of defects. To predict the disability the metrics software dataset is used. NASA MDP is one of the popular software metrics used to predict software defects by having 13 datasets and is generally unbalanced. The reward in the dataset can reduce the prediction of software defects because more unbalanced data produces a majority class. Data imbalance can be handled with 2 approaches, namely the data level approach technique and the algorithm level approach technique. The data level approach technique aims to improve class distribution by using resampling and data synthesis techniques. This research proposes a data level approach using resampling techniques, namely Random Oversampling (ROS), Random Undersampling (RUS), Synthetic Minority Oversampling Technique (SMOTE), Tomek Link (TL) and One-Sided Selection (OSS) which are classified with Naïve Bayes was also validated using 10 Fold Cross-Validation, then evaluated with the Area Under ROC Curve (AUC). Prediction results based on the dataset obtained the best AUC value on MC2 with a value of 0.7277 using the Synthetic Minority Oversampling Technique (SMOTE). Prediction results based on the data level approach technique obtained the best average AUC value using Tomek Link (TL) with a value of 0.62587. Prediction results based on the dataset obtained the best AUC value on MC2 with a value of 0.7277 using the Synthetic Minority Oversampling Technique (SMOTE). Prediction results based on the data level approach technique obtained the best average AUC value using Tomek Link (TL) with a value of 0.62587. Prediction results based on the dataset obtained the best AUC value on MC2 with a value of 0.7277 using the Synthetic Minority Oversampling Technique (SMOTE). Prediction results based on the data level approach technique obtained the best average AUC value using Tomek Link (TL) with a value of 0.62587.
IMPLEMENTATION TRANSFER LEARNING CONVOLUTIONAL NEURAL NETWORK FOR POTHOLE DETECTION ON DRONE VIDEO

Pothole is one of the problems that can cause harm to a person or a lot of people and can even cost lives. So a lot of research has been done to detect potholes, especially image-based. This research uses Unmanned Aerial Vehicle (UAV) to get aerial video dataset and train Convolutional Neural Network (CNN) with the dataset. However, instead of doing learning from the beginning, transfer learning can be used to train CNN to recognize the object of a pothole and measure the value of its performance and what the optimal frame rate is. Then the results of this study indicate that the CNN model, ssd_resnet_50_fpn_coco gets an average performance value of 48.90 mAP. And the optimal frame rate with the average highest performance value at a frame rate of 30FPS with a value of 49.43 mAP, followed by 1FPS with a value of 48.36 mAP .&#x0D; Keywords: Performance, Transfer Learning, Convolutional Neural Network, Pothole Detection, Aerial Video.
Big data block impact within big data environment

Handling data is becoming more and more complex. A higher velocity of data is created as more people have access to data generating devices such as computers, mobile phones, medical devices, home appliances, etc. Data files, such as user activity logs, system logs and so on, are stored in HDFS big data platform in various sizes, which takes into consideration the business requirements, infrastructure parameters, administration decisions, and other factors. Dividing the data files (in various volumes) without taking into consideration the HDFS™ predefined block size, may create performance issues that can affect the system's activity. This paper presents how HDFS™ block design affects the performance of Apache™ Hadoop® big data environment by testing different architectures for reading, writing, and querying identical datasets. We designed three scenarios to illustrate different file divisions on the big data platform. The findings present a significant impact on the performance of a system in accordance with the architecture deployed.
Identification and Impact of Online Deceptive Counterfeit Products: Evidence from Amazon

With the proliferation of third-party sellers, counterfeiting has become a serious source of friction in online marketplaces. We apply natural language processing techniques to Amazon product reviews to generate a listing-level counterfeit probability, which in turn is used to classify ASIN (Amazon Standard Identification Number) listings as likely counterfeit or a likely authentic. We focus on two product categories, one a taste-based experience good (menâ€™s fragrances) and the other being a utilitarian product (wireless cell phone chargers). We embed the estimated counterfeit probability into a BLP-type choice model to investigate how counterfeiting intensity affects user demand and platform revenues. We confirm that consumer disutility is increasing in the counterfeit probability, more so for high-end or popular products. We further find a substitution effect between likely counterfeit and likely authentic products: a 10% decrease in the price of a likely counterfeit product is associated with an average 0.0011% decrease in the market share of a likely authentic product. We leverage our structural parameter estimates to run a number of counterfactual experiments. These experiments suggest that protecting authentic sellers by simply banning all likely counterfeit listings would drastically reduce platform revenues. Instead, the deployment of counterfeit detection algorithms, and reporting the results to users, would align the interests of authentic sellers with the welfare of the platform. Overall, our analysis provides a robust empirical platform for identifying deceptive online counterfeiting, and understanding its impact on the various stakeholders of an online retail platform.