Reviewerly/exHarmony huggingface dataset:
Detection of Phishing Websites using an Efficient Feature-Based Machine Learning Framework

Phishing is a cyber-attack which is socially engineered to trick naive online users into revealing sensitive information such as user data, login credentials, social security number, banking information etc. Attackers fool the Internet users by posing as a legitimate webpage to retrieve personal information. This can also be done by sending emails posing as reputable companies or businesses. Phishing exploits several vulnerabilities effectively and there is no one solution which protects users from all vulnerabilities. A classification/prediction model is designed based on heuristic features that are extracted from website domain, URL, web protocol, source code to eliminate the drawbacks of existing anti-phishing techniques. In the model we combine some existing solutions such as blacklisting and whitelisting, heuristics and visual-based similarity which provides higher level security. We use the model with different Machine Learning Algorithms, namely Logistic Regression, Decision Trees, K-Nearest Neighbours and Random Forests, and compare the results to find the most efficient machine learning framework.
IMPROVEMENT OF A SOLAR PANEL TRACKING SYSTEM USING ADDITIONAL MASS POSITION ADJUSTMENT

This study aims to obtain an effective solar panel tracking mechanism using energy-efficient electric actuators.Furthermore, we designed and implemented a semi-active solar tracking system.A tracking system is proposed to control solar panel orientation using a moving mass, a spring system, and an actuator.The weight of the moving mass and the spring constant are optimized to reduce actuator size.A stepper motor was used for this case.This electric drive is not the prime mover of the solar tracker; hence, it works against mass elements lighter than solar panel weight as used in the active solar tracker.Experimental results suggest that the average power required by the stepper motor is 0.21% of the energy generated by the solar tracking system.The results indicate that the proposed solar panel tracker works satisfactorily to control solar panel orientation.
The Knowledge-Based Economic Drivers in Arabic Gulf Countries

Over the past ten years, Arab Gulf countries have made it an explicit aim to transform their economies into a knowledge-based economy.Now the knowledge economies have expanded and become more essential for Arab Gulf states.It had become a strategic vision and plans for economic diversification.This paper aims to analyse the impact of knowledge-based economy on economic development in Arabic Gulf countries over the 1980-2015 period.This study employed a wide variety of dimensional index approach to a knowledge-based economy.The data allowed us to evaluate the impact of knowledge on economic growth extensively.Panel time series method was employed to analyse the role of knowledge-based economy on economic development, using the long-run FLOMS, DOLS and PMG regression analysis.This study found that three knowledge-based economy criteria, education, information and communication technology (ICT) and innovation, significantly influence Arabic Gulf countries' economic growth.The findings are useful for the regulators in the Gulf countries as input for their effort to create an economic environment conducive to enhancing the level of knowledge and, hence, economic growth.
Analysis of Speech among Some Ethnic Groups in West Africa

This research discusses the analysis of the concept of speech among some ethnic groups in West Africa. In fact, in West Africa, the art of speaking is brought to a high degree of perfection. According to those ethnic groups discussed in this paper, the speech possesses a mystical, talismanic power, which means that it has the power to protect and change the course of events. The Nommo's conception of life can illustrate this idea in that they consider that life itself lies on speech without which it can never exist. Also, they consider that there is a close relationship between speech and the speaker. However, speaking is more than just lining up words to be understood by the interlocutor, the audience. It is considered an art that must respect certain rules relating to the place, the time and the person speaking. In this sense, the researcher, in this paper, tries to analyze the concept of speech in these ethnic groups of West Africa. The research uses secondary data as the method, otherwise called “literature review”. In other words, the researcher proceeded to collect the data related to the paper's topic by downloading them and then proceeded to the analyzes and comments.
ESTIMATION OF EMBALMING CONTAMINANTS IN SOIL AND GROUNDWATER SAMPLES FROM CEMETERY LEACHATES IN MBAIORBO, MBADIM-MBATIAV LEACHFIELD IN GBOKO, NIGERIA

Selected organic and inorganic contaminants in soil and water around burial sites in Mbaiorbo, Mbadim-Mbatiav, Gboko, Nigeria was studied using standard analytical methods. Results of analysis revealed variations in some physicochemical parameters, concentrations of heavy and organic pollutants. Five sampling locations were chosen for collection of soil and water samples and one sampling location, about 2 km away from the cemetery e4was chosen for control sample. The soil parameters for analytical and control samples estimated were, pH 4.80±0.06 (4.89±03), Electrical conductivity (μS/cm) 148.37±0.18 (79.00±0.02), Total organic carbon (%) 1.837±0.04 (1.585±0.05), Organic matter (%) 3.167±0.03 (2.732±0.04) and Bulk density (g/cm) 1.32±0.03 (1.44±0.02). The water parameters estimated were, Temperature (oC) 28.00±0.00 (28.00±0.00), pH 5.27±0.06 (6.00±0.00), Electrical conductivity (μS/cm) 114.35±0.23 (88.23±0.11), Chloride (mg/L) 2.08±.004 (0.95±0.02) and Nitrate (mg/L) 0.8899±0.05 (0.6116±0.00). The concentrations in ppm of heavy metals in the soil analytical and control samples estimated were, As (was not detected, ND, in both samples), Cd 0.167 (0.146), Cr 0.332 (0.032), Ni ND (ND), Pb 0.354 (0.592), Cu ND (ND) and the heavy metals pollutants in the water analytical and control samples estimated were, As ND (ND) Cd 0.008 (0.009), Cr 0.334 (0.349), Ni ND (ND), Pb 0.142 (0.141), Cu ND (0.049), The concentrations in ppm of organic pollutants estimated were, Formaldehyde 0.04213 (ND), Ethanol 0.02022 (0.24654), n-propane 0.04665 (ND) Iso-butanol 0.08366 (0.89675) and Methanol ND (ND). Contamination factor and geo-accumulation index models used to estimate the level of soil and water pollution by heavy metals and organic pollutants revealed that the soil and water samples were highly contaminated with Cr but the level of organic pollutants in water were low. Green burial practice and strict monitoring of water quality in dug wells and streams in the vicinity of the burial sites from the study area is recommended.
Psychological dimensions in the drawings of children of financially poor families

The current research deals with an important category of society, namely, children in the primary education stage (fourth primary), which is an important stage of human development, as the child of different sex witnesses changes from different aspects of sexual, mental and emotional development. After the researcher took and looked at a group of drawings of children of financially poor families who are 9 years old, it became clear to them some characteristics and psychological dimensions that emerged clearly and tangibly, which were developed by children in the form of subconscious projections through shapes, colors and lines, in drawing children of poor families Of the parts of the human body, we clearly notice the psychological dimensions through drawing those parts, as it tends to draw (the size of the human head is large), which indicates that the child suffers from frustration or excessive sensitivity and excessive preoccupation with fantasies, and exaggeration in drawing the size of the head greatly expresses On the individual's need to depend on others.
Detection Of Water Levels In Sewering Channels As Flood Disaster Early Warning System

In 2020 a number of areas in DKI Jakarta were hit by floods, one of which was the North Tanjung Duren Village, Grogol Petamburan District, West Jakarta. The extreme rainfall of 377 mm/day has flooded almost all areas of DKI Jakarta and its surroundings. In addition, poor drainage causes water to stagnate, causing flooding. However, the absence of an early flood information system makes residents restless when the rainy season arrives. The Community Service (Community service activity) activity carried out aims to provide training to the community in the Tanjung Duren Utara Village area RW 04, RT 0010 regarding water level detection equipment placed in culverts. This tool serves to provide early information if the volume of water in the culvert is full of information in the form of a siren sound. The method used in this Community service activity activity is to provide online counseling and training to the community in RT 0010 / RW 04, North Tanjung Duren Village, Grogol Petamburan District, West Jakarta. The results obtained are an increase in public understanding regarding the dangers of flooding to household electricity, as indicated by the results of the pre-test and post-test which are obtained an average of 43 and 90, respectively. Public understanding of the dangers of flooding to electricity has increased up to 109.3%. In addition, the average partner satisfaction with the material presented is 92%, this shows that the material presented by the presenters team is very useful for the extension participants.
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application

A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others in most simulation scenarios according to the integrated mean square error and integrated classification error
Cybersecurity Awareness: A Critical Analysis of Education and Law Enforcement Methods

According to the international Anti-Phishing Work Group (APWG), phishing activities have abruptly risen over the last few years, and users are becoming more susceptible to online and mobile fraud. Machine Learning techniques have potential for building technical anti-phishing models, with a handful already implemented in the real time environment. However, majority of them have yet to be applied in a real time environment and require domain experts to interpret the results. This gives conventional techniques a vital role as supportive tools for a wider audience, especially novice users. This paper reviews in-depth, common, phishing countermeasures including legislation, law enforcement, hands-on training, and education among others. A complete prevention layer based on the aforementioned approaches is suggested to increase awareness and report phishing to different stakeholders, including organizations, novice users, researchers, and computer security experts. Therefore, these stakeholders can understand the upsides and downsides of the current conventional approaches and the ways forward for improving them.
Computer Vision based Polyethylene Terephthalate (PET) Sorting for Waste Recycling

Recycling plays a vital role in saving the planet for future generations as it allows keeping a clean environment, reducing energy consumption, and saving materials.Of special interest is the plastic material which may take centuries to decompose.In particular, the Polyethylene Terephthalate (PET) is a widely used plastic for packaging various products that can be recycled.Sorting PET can be performed, either manually or automatically, at recycling facilities where the post-consumed objects are moving on the conveyor belt.In particular, automated sorting can process a large amount of PET objects without human intervention.In this paper, we propose a computer vision system for recognizing PET objects placed on a conveyor belt.Specifically, DeepLabv3+ is deployed to segment PET objects semantically.Such system can be exploited using an autonomous robot to compensate for human intervention and supervision.The conducted experiments showed that the proposed system outperforms the state of the art semantic segmentation approaches with weighted IoU equals to 97% and Mean BFscore equals to 89%.
Nonlinear Attitude and Formation Estimation Spacecraft And Multi-Agent Systems

This dissertation examines the state and parameter estimation problem of monolithic spacecraft and multi-agent systems in conjunction with the control algorithms. Nonlinear filtering techniques are investigated and applied to the problems of attitude estimation and control of monolithic spacecraft, distributed flltering for attitude estimation and control of satellite formation flying (SFF), and estimation and control of a multi-agent system in consensus tracking with uncertain dynamic model. The main objective is to investigate the performance of nonlinear filtering techniques under fault-free and fault-prone scenarios. In essence, the core of this research has been placed on identifying techniques to improve the efficiency and reduce the variance of estimations in nonlinear filtering. The research is primarily dedicated to the investigation of adaptive unscented Kalman Filter (AUKF) and particle Filter (PF). A nonlinear filtering technique has been proposed for sequential joint estimation of a multi-agent system in consensus tracking with uncertain dynamic model. The new filter is called marginalized unscented particle Filter (MUPF). The proposed filter uses the Rao-Blackwellised principle to couple the particle filtering technique with unscented transform algorithm
The Relationship Between Use of Smartphone and Students Interest in Reading Book

Smartphones have become an essential part of students daily lives. Students use smartphones for various activities. Through smartphones, students can access various service sites that provide material resources such as scientific journals, scientific articles, ebooks, and others. This article aims to explain the relationship between the use of smartphones and students interest in reading books. In this research, the book in question is an ebook. The quantitative survey method was used in this study. The target of this research is students of class XII at VHS Negeri 1 Ciamis with a sample size taken 42% of the total number of 557 students, that is 233 people. The researcher used Kendalls Tau correlation test as a data analysis method. The correlation value of 0.063 and the significance value of 0.314 in this research results indicate that there is no significant relationship between the variables. The findings of this study show that there is a positive relationship between students interest in reading books and their use of smartphones, but the relationship between the two variables is very weak and insignificant at the 0.05 level, so the relationship cannot be generalized. This means that students rarely use smartphones to access ebooks but to use them for other purposes instead
The use of gamification tools in the practice of modern education

The purpose of the article is to formulate the problem of using various gamification tools: role – playing games, simulators, video games in the practice of modern education. The article analyzes and describes a step-by-step methodology for introducing gamification into the learning process, starting from analyzing the internal environment of an educational organization and determining the goals of introducing gamification on its basis to choosing a platform for gamification, selecting rules and creating a motivation system for students. The article substantiates the relevance of research on the use of gamification in solving various levels of pedagogical tasks. Based on a comparative analysis of foreign studies on gamification, the article highlights the main trends in the use of gamification tools in real pedagogical practice, identifies and describes three key segments of gamification in relation to basic education: game products, auxiliary tools for the main educational program and tools for the formation of various cultural skills. According to the results of the study, conclusions are formulated. The prospects for the development of the research topic are outlined.
A Novel Adaptable Sonar Image Pseudo-color Enhancement Method Using CIELab Space

A novel adaptable sonar image pseudo-color enhancement method using CIELab space is introduced in this paper. This method gets the pseudo-color image through establishing a nonlinear mapping relationship between the gray sonar image and the pseudo-color image. Firstly, this method gets the color information of the pseudo-color image and the intensity information of gray sonar image through the transformation form RGB space to CIELab space. Secondly, put the color information and the intensity information together and inversely transform them from CIELab space to RGB space. Then the pseudo-color image is obtained. As well, three objective evaluation methods will be used to evaluate the novel method. The experimental results show that the pseudo-color image obtained using the novel method has more rich colors and clear details, and it is a good sonar image pseudo-color enhancement method.
Ethereum and IOTA based Battery Management System with Internet of Vehicles

The era of Electric Vehicles (EVs) has influenced the very make and manufacture of vehicles resulting in low pollution and advanced battery life. On the other hand, the internet of things has also expanded allowing a number of devices to stay connected using the internet. Massive drawbacks faced by EVs today are the limitation in battery swapping and charging stations and limitation in the range of batteries used. This proposed paper aims to efficiently manage the best battery system apart from building the essential infrastructure. In some cases battery swapping option is also provided through other EV drivers or at registered stations. Hence a complete database of the EV network is required so that it is possible to swap and charge batteries successfully. An EV management using two blockchains as a data layer and network of the application is implemented in this work. The first step involves the development of a blockchain framework using Ethereum and the next step entails a direct acyclic graph. When integrated, these two methodologies prove to be an efficient platform that offers a viable solution for battery management in Electric Vehicles.
THE DIGITAL TEСHNOLOGY IN IT-EDUCATION: THE VIEW OF UKRAINIAN UNIVERSITY

The purpose of the publication is to analyze open educational resources for the availability of courses in the field of information technology (IT).Methods.To achieve this goal, theoretical methods of analysis of Internet sources and educational and scientific literature were used to determine the most relevant to date educational resources and IT courses.For the quantitative analysis of the study, mathematical methods were used, which allowed to determine the share of IT courses in different characteristics and thematic areas.The analysis is based on a study of the content of ten educational platforms that provide full or partial open access to their courses.(programming and software development, data structures, computer (information) security and computer networks, computer graphics, web graphics, design and visualization data, web design and Internet technologies, database and SQL management systems, artificial intelligence and modern robotics, blockchain and cryptography, operating systems). Results. The authors of the publication described their own results of quantitative analysis of educational platforms and open resources in the field of IT. The authors of the article substantiated the contradiction between the demand of the Ukrainian society for a competitive IT specialist and the content, methods, approaches to their professional training in Ukraine. The authors see the solution of contradictions by introducing open educational courses in the training of specialists in the field of IT. The article presents the characteristics of educational platforms, as well as the classification of IT courses Conclusions. The authors propose to use open educational resources to organize independent work in the frameworkof training courses in the Ukrainian reality; for the organization of distance learning; to improve the skills of teachers.
Comparative Study of Machine Learning Algorithms for Product Recommendation Based on User Experiences

As Machine Learning (ML) algorithms are becoming popular to solve everyday challenges, it is being used to make predictions on data across different industries. To obtain an advantage over the competitive pressures, a service or goods supplying firm needs a strong marketing strategy to understand their clients and grasp how people think, reason and choose among the various items and services supplied in the market. By effectively understanding its customers and their buying behaviour, a firm can maximize its internet strategy, enhance user experiences, foresee how consumers will respond to new business strategies, retain consumers who are loyal, design marketing strategies to create new consuming markets, and boost sales revenue. The purpose of this research is to investigate the purchasing behaviour of UK based e-commerce retailer customers to enable to provide better services and products. The data analysis conducted on customer data enables understanding of the type of products the customers are likely to purchase based on the description of their previous transactions. Four models based on supervised machine learning techniques were applied, namely Logistic Regression, K-Nearest Neighbour (KNN), Support Vector Machine (SVM) and Random Forest, and their performance was compared to predict the products that customers are most likely to purchase.
Preface of the Workshop Organizers

The First International Workshop on Requirement Engineering for Software startups and Emerging Technologies (RESET) is a part of IEEE International Requirements Engineering Conference 2021, held on 20th September, 2021. The workshop brought together requirements engineering researchers and practitioners to discuss the need for adapting conventional requirement engineering artifacts (i.e. requirement definition, metrics), processes and practices to software projects in startup context and/or dealing with emerging technologies like Artificial Intelligence (AI), Blockchain etc. Further, the workshop also presents research findings about designing AI powered software systems ethically. The workshop accepted eight high quality research articles from the United States of America (USA), Norway, Finland, Sweden, Germany and Vietnam. The workshop accepted articles describing original research (full length articles) and those describing novel ideas as well as initial research results (short length articles). The articles are accepted after two rounds of rigorous peer review based on originality, relevance, quality, and technical contribution.