Reviewerly/exHarmony huggingface dataset:
A Rational Approach to Improve Access Time of Apriori Algorithm by Applying Inner Join in a Arm to Redefining Fis in Textual Data

Now the Days Data mining is observed as most demanding field in current era and its scope and contribution in research is beyond the expectation for next upcoming decades. Among the various techniques of data mining, Association Rule Mining (ARM) (8) plays a remarkable role and Apriori Algorithm is one of the most popular method to define frequent item sets(FIS) over huge amount of transactional data sets. Now, we are going to re-evaluate access time which consumes in scanning of database again and again for n-times looking for n-element FIS. Here, we conclude and compare our proposed New-Apriori Algorithm with the original Apriori algorithm (5) through experimental result to calculating frequent items on numerous groups of transactions with minimal support, for both Apriori and New-Apriori to improve in its performance by reducing the scan time, spent on accessing the database by 61.65% to 73.65% for uniform support and 81% for variable support.
Data Mining and Machine Learning Techniques for Credit Card Fraud Detection

In the recent era, everybody is dealing with digital data. In such a scenario, individual one heavily depends on credit card. Therefore, the demand of online transactions and usage of e-commerce sites are rising at the rapid rate. The online payments are the main cause of increasing crime rate heavily. Hence, it is the biggest challenge for the IT sector to identify and solve such critical problems. This critical issue can be tackled with the help of machine learning. This paper mainly emphasis on various data mining algorithms such as C4.5, CART algorithms, J48, Naïve Bayes algorithm, EM algorithm, Apriori algorithm, and SVM, and inform the accuracy and precision of the result. The machine learning finds the genuine and non-genuine transition using learning pattern matching and classification technique. The machine learning also normalized the data, identified the anomalies in transaction, and provided appropriate results.
SAFE CONCENTRATION OF HYDROGEN SULFIDE (H2S) FOR PEOPLE LIVING CLOSE TO LANDFILL (CASE STUDY IN CIPAYUNG LANDFILL, DEPOK, WEST JAVA)

Cipayung landfill operating with open dumping system which accepts waste from 11 subdistricts in Depok City, West Java has exceeded its capacity. The height of the waste heap reaches 30 meters. This study aims to analyze potential health risk caused by H2S in people living around the landfill. This study uses descriptive quantitative method with analysis health risk approach by calculating the Risk Quotient value. The samples number in the study is 90 people who are living in ï£ 500 meters radius from Cipayung landfill. Data collected by questionnaire and measuring H2S ambient concentration at 9 points around the residential areas which have ï£ 500 meters distances to Cipayung landfill. The highest measurement result of H2S is 0.0042 mg/m3 with highest RQ value calculation is 2.4. Out of 90 respondents, 90% had respiratory symptoms during living near the landfill and the most frequent symptom of respiratory symptoms was coughing (87,8%). It needs cross-sectoral cooperation in monitoring and controlling H2S concentrations originating from the Cipayung landfill to reduce the health risk of people living close to the Cipayung Landfill.
The Adoption of Mobile Banking Services in Jordanian Banks and Factors Affecting the Customers

There are several factors that impact a customer's decision to accept a mobile banking (m-banking) service in Jordan. UTAUT was used as a theoretical framework for this study, which was conducted using a quantitative approach. Using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, a theoretical model was developed and tested. Also, connection and numerous direct relapse investigations were performed to evaluate the attack of yields of this model with the outcomes got from the overview. It was tracked down that a person's expectation to embrace m-banking administrations in Jordan is altogether affected by a few factors whose impacts decline in the request: individual imaginativeness, working with conditions, social impact, exertion hope, and execution anticipation. The consequences of this examination are relied upon to add to an inside and out comprehension of what segment and different variables mean for the reception of m-banking administrations in non-industrial nations and assume a basic part in working fair and square of their reception.
SVM Classifier: Identify Linear Separability Of NAND And NOR Logic Gates

Abstract-Artificial Neural Network plays vital role to resolve several real-life problems. Those problems would be impossible or difficult to solve by human or statistical principles. ANN produces better results on large data set as it has self-learning capabilities. The most frequently used family of ANN is pattern classification. Generally, patterns are obtained from real world and get together based on definite attributes in specific regions. Data is classified based on knowledge by recognizing patterns. This study underlines linear separability of Boolean logic gates according to classification. We considered Boolean functions NAND and NOR for classification task. Our problem statement related to this study is, “There is significant difference between the performance of classifier regarding NAND, NOR Boolean logic gates using Support Vector Machine”. Zoo data set is used to carry out the experiment. Accuracy score is measured using Support Vector Machine (SVM). For actual and predicted data set, classification report and confusion matrix is produced. For classification SVM is emerged as a promising technique. Usually, SVM gives remarkable performance as compare to other Machine Learning classifiers methods. As a result, SVM produces outstanding performance on classification problem. Keywords- Boolean Functions, NAND, NOR, Linear Separability, Support Vector Machine (SVM), Confusion Matrix.
Performance Management in Cloud Computing

Cloud service providers encounter a challenge in managing remote resources due to the dynamic nature of the cloud environment. The complexity of the process is increased by the requirement of maintaining service quality in line with customer expectations, as well as the extremely dynamic nature of cloud-hosted applications. As a result of developments in big data learning methodologies, traditional systems have given way to intricate systems. In the existing studies, it is shown that the resource adjustment decision-making process is intimately linked to the system's behavior, including resource utilization and application components. The most essential requirements and restrictions in cloud resource management, as well as workload and anomaly analysis approaches in the context of cloud performance management, are discussed in this paper. The related works are provided, with major methodologies in current studies ranging from data analysis to performance techniques. Finally, a list of open challenges is compiled, taking into account the identified gaps in the overall direction of the tasks under consideration.
Improved sun flow optimization (I-SFO) algorithm based de-centralized information flow control for multi-tenant cloud virtual machines

Security concerns are frequently regarded as a difficult
Secure Coding and Software Vulnerabilities in Implementation Phase of Software Development

The methodology in software development has shifted from waterfall to agile, which has earned appreciation as cost-effective development due to its speedy software delivery, under limited time constraints. At the same time, cyber attacks have become more surreptitious that are pretending threats to software. Security elements and practices in software development phases eliminate software vulnerabilities. Vulnerabilities happen in the software due to the unavailability of security practices during the levels of software enhancement. Software development using secure coding practices can resist the software from exploitation. Thus, the paper focuses on the detailed view of security weaknesses in the implementation stage of the software development life cycle (SDLC). The paper explains the non-compliant codes which expose vulnerabilities that can benefit the attackers to gain unauthorized access, therefore providing the mitigation to furnish a complaint code resistant to exposure. Both secure and vulnerable features can be curved from the source code. This paper concentrates on the human aspects of software security, including human actions and motivation. This paper enables us to learn about and promote secure coding standards for frequently used programming languages, regardless of the device used for programming.
Predicting Popularity of Online Videos Using Support Vector Regression with Gaussian Radial Basis Functions

A wide ranges of recently downloaded videos are economically significant when it comes to the capacity to forecast recent Top-N videos and their aspirations in life. Though numerous efforts have been made to predict video popularity, conventional algorithms do not have the efficacy to foresee top-class viewed videos compared with the whole video set. The truth that almost all videos in the online video system are deceptive is the reason for this occurrence. Thus models should learn to maximize their productivity across the whole video set in an uncomfortable way. The effectiveness of the top-N viewed content, therefore, is essential in most situations in the current study.
DigiVoter: Blockchain Secured Digital Voting Platform with Aadhaar ID Verification

The Election Commission of India has talked about India's Electronic Voting Machines (EVMs) as dependable and impeccable, yet comparable electronic voting machines utilized around the world have shown to experience the ill effects of genuine security issues. This research aims to build a digital voting platform secured with the revolutionary concept of blockchain. A naive implementation of the same using Python for biometric authentication and NodeJs to create the blockchain is presented. It secures the blocks using 512-bit SHA-2 (Secure Hashing Algorithm 2). For authentication of users, the proposed model incorporates the use of biometric data which will be mapped to the cryptic unique Aadhaar card number of the voter. Thus, a platform is proposed to make the voting procedure easier, secured, and fault tolerant using blockchain. The results show secure vote casting by biometric authentication and saving in an immutable distributed fashion, thus keeping it safe from being altered.
The evolution of ITE in India

From an evolutionary perspective, this chapter provides an overview of the emergence, spread and scaling-up of the ITE initiative in India over a decade. This evolution is summarized into five phases of these impressive innovations that address the digital divide and the needs of underserved children and young people in India: emergence, establishment, scaling-up with partnerships, scaling-up through teacher professional development and, finally, evolution continues. This overview complements other chapters in this book that provide detailed descriptions of ITE and its impact on more than 400,000 young people and the communities that support them. Recognition of evolution in this chapter aims to inform the sustainability of ITE and to guide others in the purposeful deployment of digital devices and connectivity to address the complex needs of education for young people, especially those living in challenging educational contexts.
Comparative Analysis of Threshold Multi-Keyword Search with Searchable Encryption of Reduced Computation Keyword Search for Cloud-Based Group Data Sharing

To reduce the computation cost of multi-keyword search for cloud-based group data sharing. Materials and methods: Multi-Keyword Advanced Encryption Standard algorithm (MAES) and Searchable Encryption RSA algorithm (SERSA) was iterated 10 times (sample size =20) for calculating the computational cost of multi-keyword search. The Shamir’s Secret key technique used with MAES algorithm helps to reduce the computation cost of multi-keyword search. Results and discussion: MAES appears to have better reduced cost (1.86 sec) compared to SERSA algorithm (2.05 sec). There was a statistical significance difference between MAES and SERSA with the value p=0.026 (p &lt;0.05). Conclusion: MAES algorithm with Shamir's Secret key provides better reduced computation cost of multi-keyword search compared to SERSA.
Estimation of Solar Insolation Along with Worldwide Airports Situated on Different Latitude Locations: A Case Study of Rajasthan State, India

Insolation is known as the amount of solar energy that actually passes through the atmosphere and strikes a given area on the Earth's ground surface over a specific time. Solar insolation works as fuel for power plants. The renewable sources can be used in small and decentralized power plants or in large generation systems. They are modular and can be built in small-sized modules to be used at different locations. Solar insolation depends on direction, tilt angle, and latitude along with environmental condition. India is a developing country and, due to economic and operational issues, prefers fixed and two- or three-seasonal tilt angles in place of single and dual axis tracking. This study aimed towards solar insolation at Bikaner location in the Rajasthan Desert, in different directions and different tilt angles along with a particular month. Along with the Rajasthan Desert solar insolation study, a study of percentage increment in solar insolation by using a double seasonal tilt angle instead of a fixed tilt angle for 14 airport locations worldwide on different latitudes in the Northern and Southern Hemispheres.
Measuring Graphs

On our adventurous journey, we formalised in the previous chapter the generation of various finite random graph models in terms of suitable algebraic objects and obtained representations of these models which reside beyond their classical or algorithmic descriptions. This approach naturally paves the way for a more rigorous investigation of the vast plethora of graph-theoretical measures that typically are, or only can be, considered in tedious and demanding numerical studies, or under stringent limitations in asymptotic assessments. In this chapter, we will exemplify how the properties of the algebraic objects governing the generation of graphs can be exploited, and how parametrised expressions for a variety of graph measures can be obtained. Here we must restrict our gaze into the sheer limitless realm of possibilities to a few selected directions. By highlighting some of the differences to already available results from a conceptual and mathematical vantage point, we will continue to argue for the necessity of a study of networks at finite scales, for which our operator graph-theoretical framework presents itself as one viable approach.
Summarizing Table

This chapter summarizes the seven dimensions of this Brief into tables where the known relations and the related properties are listed.
Our Understanding of Computer Literacy in Education

The purpose of this review of literature and studies is to gain insights on how to improve the levelsof computer literacy among teachers in the elementary school level. After an extensive review of available literature and studies, seven themes emerged reflecting the insights gained.
The Causal Effect of International Trade on Poverty in West Africa

The study examined the relationship between trade and migration and poverty and income inequality in the West African sub-region.The study included all the 16 countries within the West African bloc.The study adopted approaches such as pooled OLS, Fixed Effect models, PPML, two-stage least square instrumental variable estimator and PPML-2SLS.The study explored the correlation between international trade and poverty and also evaluated the effect of international trade on poverty and inequality in West Africa.The result indicated that there was negative correlation between international trade and poverty.In addition, it was observed regional trade flows reduce headcount poverty in the sub-region.The recommends that there should be liberalization in the subregion as that results in reduction in poverty.It will be worth exploring the link between trade and illegal migration on macroeconomic indicators of countries in the sub-region
Account + GST Inventory Management ERP System (Using Cloud Storage)

Abstract: An ERP system or Enterprise Resource Planning System has been one of the most effective and useful implementations that have been highly effective and useful. The ERP’s are extremely capable of providing a robust organization and streamlining of the entire business with ease. The ERP’s have been extensively used in the recent years due to the immense cost benefits and effective management of the entire processes of running an organization. Deployment of ERP’s is an extremely costly procedure as it is an extensive and detailed implementation, which is the reason why most of it was concentrated towards the large corporations. This has also been the reason why most of these innovative approaches were not as accessible for the medium and small businesses. The high cost also prevented many researchers in accessing these systems and implementing various improvements. Therefore, there is a need for an effective approach for designing a useful approach towards an ERP for the purpose of managing a small to medium organizations. This approach will be defined effectively in the future versions of this research study. Keywords: Enterprise Resource Planning System, Cloud Storage.
Security Analysis of Symmetric Password

Cryptography is a field of computer science which deals with the integrity and confidentiality of the data sent across the internet.It converts the data into a meaningless form, from which the attacker will not be able to infer any useful information.One of the most used types of cryptography for data hiding is symmetric key cryptography.In this paper, we have given a summarized form of all the reviews done on symmetric key cryptographic algorithms along with their advantages and disadvantages.We have also proposed a solution that helps us to overcome the disadvantage of the AES cryptographic algorithm.
Automatic generation of impossible shapes from line-drawing characters

In recent years, there are signs and advertisements that use optical illusions. By using the optical illusion, it is easy to not only attract attention but also leave an impression. In addition, characters are always used in advertisements. The design of characters to be impressive is called lettering. Accordingly, we expect that adding an illusion to the lettering process can generate more impressive characters. However, it takes a lot of experience and time to take the illusion into account when lettering. In this paper, we add the illusion of impossible shapes to the lettering process to automatically generate more memorable characters. An impossible shape is a figure which can be recognized visually as a three-dimensional projection, but which cannot exist in reality. In this method, the strokes and contours are extracted from line-drawing characters. Then, the projected image is created by using them. Finally, impossible shape is generated by applying an optical illusion to the projected image.
The Relationship Between Online Course Learning Intention and Learners’ Learning Behavior: The Moderating Effect of Teacher Guidance

In order to explore the relationship between learners' learning intention and learning behavior in online course learning, and the moderating effect of teacher guidance on the relationship between learning intention and learning behavior, this study analyzed the online course learning in five schools, and found that: (1) Learners ' online learning intention positively predicts learning behavior at the initial stage of the course and negatively predicts learning behavior at the end stage of the course. (2) Teacher guidance plays a significant moderating role between learning intention and learning behavior at the beginning and end of the course. In the learning of online course, for learners with strong willingness to learn, teacher guidance is conducive to strengthening learners' initial learning behavior; for learners with poor learning willingness, the learning behavior of learners can be improved through the adjustment of teacher guidance in the end of the course. This shows that online course learning requires learners to have higher learning willingness and more autonomous learning ability.
Estimating the number of table tennis rallies in a match video

In this paper, we propose a method for estimating the number of rallies in table tennis match videos. A play scene is extracted from a video by using frame similarity, and a ball area is detected in an upper side of the table with frame difference and color thresholding. The detected ball is either a receive ball by the upper side player or the high toss service by the bottom player. The high toss service is removed with the collision sound of the ball and table or racket. Experiments of estimating the number of rallies show the accuracy of 63.7 % with 157 play scenes of T-League match videos in Japan.
The Effect of Implementing the Interactive Board in Teaching English Language on Improving the Writing Skill of Students with Learning Difficulties and Their Attitudes towards it in the Southern Mazar District

This study aimed to reveal the effect of implementing the interactive board in teaching English language on improving the writing skill of students with learning difficulties and their attitudes towards it in the Southern Mazar District.The scale included seven questions distributed over seven criteria and an attitude scale consisted of (20) items with a triple Liker scale.The study sample consisted of (50) male and female students in two sections, in the first semester of the academic year 2021/2022.They were chosen by the purposive method.One of the sections was randomly chosen as an experimental group with (25) male and female students taught using the interactive board, and the second group as a control group with (25) male and female students taught through the traditional method.The study results showed that there was a statistically significant difference at the significance level (α = 0.05) between the two arithmetic means for the performance of the two study groups on the writing skills test collectively and individually attributed to the variable of teaching method in favor of the performance of the experimental group which was taught writing skills using the interactive board compared to the performance of the control group which was taught using the traditional method where the effect size was also high.The study also showed that there were no statistically significant differences at the significance level (α = 0.05) between the arithmetic means of the performance of the two study groups on the writing skills test collectively and individually ascribed to the gender variable, and the interaction among the variables of teaching method and gender.The results also showed positive attitudes of the experimental group towards the use of the interactive board.
Research on Network Learning Behavior Analysis and Teaching Strategy Based on Deep Learning

With the development of Internet and communication technology, wisdom education in the new era has also become the focus of research.This paper studies the online learning behavior based on deep learning, analyzes the students' behavior pictures and identifies the students' identity, marks and actions, and finally carries out the statistical analysis of students' learning behavior based on the real situation of the classroom, establishes the evaluation model of teaching effect and carries out empirical research.Experiments show that the target action recognition accuracy of AEB is 90.54%, indicating that the recognition effect of AEB is good.