E-governance, i.e., the use of information technology for government activities to provide services, exchange information, etc. are becoming increasingly popular. One such area of e-governance is e-tendering. While e-tendering makes the tendering process more efficient, a trust deficit remains between the citizens and the government, due to the centralized management of the whole tendering process. Several research works provide a decentralized solution to make the process of e-tendering more secure, transparent, and fair. However, in the present time, the government posts the problems/issues currently they are dealing with; and seems interested in taking the suggestions from the citizens to make the better solution for the problem. Thus, in this paper, a permissioned blockchain-based approach to provide a transparent and fair tendering system with citizens’ active participation and tracking of funds is presented. In the proposed scheme, the citizens can see the tendering activities transparently and give ideas and suggestions to solve the government’s posted problems and receive a due credit of that contribution is a fair manner.

E-Governance: A Tendering Framework Using Blockchain With Active Participation of Citizens

The tendering process is generally used by governments and companies to procure goods or services from manufacturing companies or service providers However, e-tendering being the mostly used procurement method, there are various security implications present Blockchain technology can be used to solve these security implications as it heavily focuses on the decentralization of information and is secured by encryption integrated with undeniable block-based architecture for transaction management In this paper, how smart contracts (based on ethereum blockchain) can be employed to design a distributed e-tendering system is explored The project is divided into four sections, 1 Tender creation and publishing process, 2Bidding process on the tender, 3Evaluation, and Negotiation of the bid and 4Selection of the Winning bid Different algorithms are used to implement each process The security and audibility challenges are evaluated and compared to the current tendering process The main aim of this paper is to implement a fair, transparent and open tendering scheme

Blockchain-based e-Tendering System

The operations of many industries, such as banking, insurance, energy, healthcare, and retail, have been improved and transformed by the application of artificial intelligence. The education sector is the particular one which has more potential for artificial intelligence and its applications. Universities and colleges are currently facing a number of challenges, including high rates of dropouts and student disengagement in their classes, as well as the failure of traditional learning techniques in the face of ongoing outbreaks. Major issues in the educational sector can be resolved by the proper application of artificial intelligence and big data, which can facilitate learner-centred approaches as per the needs of today’s era. This can be better described as a personalised learning approach, in which the needs of each and every student can be considered and education can be provided uniquely for them. In this way, the educator can provide a better learning experience according to the needs and ability of the learners/students. Thus, it also assists in enhancing the motivational level of the learners and minimising the dropout rates of the students. The main purpose of the study is to examine the role of artificial intelligence and big data in the adaption of the E-learning system for imparting better education facilities to the students of various colleges and universities situated in Saudi Arabia. The sample dataset for this study was collected through a purposive sampling technique from the 290 students enrolled in numerous higher educational institutions. The collected data were analysed using SPSS and SmartPLS 3 software. The findings of this study reveal that AI and big data assist educators and students as well to run the teaching and learning process smoothly even in the period of an ongoing pandemic at the higher levels of the education system. It also explores the educational inferences of transpiring technologies in the ways of students’ “learning and institutions” teaching and their adaption. In recent eras, technological evolution and an increase in the adoption of latest technologies in the field of higher education have been scouted to forecast the essence of higher education globally in the near future, where AI will be the gist for universities. This study reveals some issues faced by higher educational institutions and students related to the adaptation of these technologies for learning, teaching, administration, and student support. The implications of the present study will be helpful for students and teachers to access educational resources effectively and for educational institutions to improve the efficiency and personalization of learning tasks. Furthermore, it will allow students to get more time with their respective teachers.

https://downloads.hindawi.com/journals/edri/2022/1263555.pdf

Artificial Intelligence and Big Data: The Advent of New Pedagogy in the Adaptive E-Learning System in the Higher Educational Institutions of Saudi Arabia

Artificial intelligence is the driving force of change focusing on the needs and demands of the student. The research explores Artificial Intelligence in Education (AIEd) for building personalised learning systems for students. The research investigates and proposes a framework for AIEd: social networking sites and chatbots, expert systems for education, intelligent mentors and agents, machine learning, personalised educational systems and virtual educational environments. These technologies help educators to develop and introduce personalised approaches to master new knowledge and develop professional competencies. The research presents a case study of AIEd implementation in education. The scholars conducted the experiment in educational establishments using artificial intelligence in the curriculum. The scholars surveyed 184 second-year students of the Institute of Pedagogy and Psychology at the Abay Kazakh National Pedagogical University and the Kuban State Technological University to collect the data. The scholars considered the collective group discussions regarding the application of artificial intelligence in education to improve the effectiveness of learning. The research identified key advantages to creating personalised learning pathways such as access to training in 24/7 mode, training in virtual contexts, adaptation of educational content to personal needs of students, real-time and regular feedback, improvements in the educational process and mental stimulations. The proposed education paradigm reflects the increasing role of artificial intelligence in socio-economic life, the social and ethical concerns artificial intelligence may pose to humanity and its role in the digitalisation of education. The current article may be used as a theoretical framework for many educational institutions planning to exploit the capabilities of artificial intelligence in their adaptation to personalized learning.

Artificial Intelligence in Education: AIEd for Personalised Learning Pathways

Sentiment analysis or opinion mining has come forth as an attractive research field in the past few years. Sentiment analysis extracts sentiments from the text for analysis and aggregation at different levels of detail. In aspect-level sentiment analysis, we aggregate sentiment for different aspects of entities. The bulk of the research work executed so far focuses on detecting explicit aspects but ignored implicit aspects, which are insinuated by other existing words and articulates of the sentence. Since a significant percentage of sentences contain implicit aspects, detection of implicit aspects becomes vital for sentiment analysis. This survey concentrates on implicit aspect detection, and a detailed discussion about state of the art is provided. The available methods are categorized depending on the algorithm applied. Quantitative evaluation for different methods as stated by authors is included for comparison purpose. Discussion about terminology, issues, and scope in the detection of implicit aspects is also included. The fine-grained sentiment information collected may be used in many applications in various domains. This survey aims to advocate the need for implicit aspect detection, determine existing efficient solutions, identify complications in implicit aspect detection, and suggest measures to improve performance, which comprise future research trends in implicit aspect detection.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09796523.pdf

A Survey on Implicit Aspect Detection for Sentiment Analysis: Terminology, Issues, and Scope

The use of Artificial Intelligence (AI) is now observed in almost all areas of our lives. Artificial intelligence is a thriving technology to transform all aspects of our social interaction. In education, AI will now develop new teaching and learning solutions that will be tested in different situations. Educational goals can be better achieved and managed by new educational technologies. First, this paper analyses how AI can use to improve outcomes in teaching, providing examples of how technology AI can help educators use data to enhance fairness and rank of education in developing countries. This study aims to examine teacher’s and student’s perceptions of the use and effectiveness of AI in education. Its curse and perceived as a good education system and human knowledge. The optimistic use of AI in class is strongly recommended by teachers and students. But every teacher is more adapted to new technological changes than students. Further research on generational and geographical diversity on perceptions of teachers and students can contribute to the more effective implementation of AI in Education (AIED).

https://iopscience.iop.org/article/10.1088/1742-6596/1714/1/012039/pdf

Evaluating Artificial Intelligence in Education for Next Generation

Banking sector is having a great significance or value in our everyday life. Each and every person makes the use of banking sector in two ways, (i) physical and (ii) online. Physical fraud can take place like stealing the credit cards, sharing bank account details with corrupt bank employees, etc. Online fraud takes place by sharing the card details on the Internet or over the phone with a wrong person. It may also include spamming and phishing. While carrying out the transactions and all the relations with the bank policies, customers and the banks may face many problems due to fraudsters and criminals, and the chances of getting trapped are very higher. These kinds of frauds can be credit card fraud, insurance fraud, accounting fraud, etc. which may lead to the financial loss to the bank or the customers. Thus, detection of these kinds of frauds are very important. Fraud detection in banking sector is based on the data mining techniques and their collective analysis from the past experiences and the probability of how the fraudsters can steal from customers and banks. Therefore this paper addresses the analysis of data mining techniques of how to detect frauds and overcoming it in banking sector.

Data Mining Techniques for Fraud Detection in Banking Sector

The problem with present tendering is its reach which is limited to number of people, though the internet is expanding and tendering is also not far from this, we have some online system for tendering but it is not secure as it should be because tendering has confidential data which is not supposed to be leaked and Blockchain solves that problem efficiently. The motive of this research is to find the better ways for tendering, as tendering is very essential part of businesses and development so improvement of this system leads to better development. Time efficiency, employment, fair system are some of the factors which can be improved by the proposed system of this research.

Efficient approach for Tendering by introducing Blockchain to maintain Security and Reliability

Cloud Computing has become prevalent in this day and age, and with the majority of the population dependent on it, it’s security issues have become a major concern. The Cloud Security System can be evaluated on the basis of three key components – Confidentiality, Integrity and Availability (CIA). These factors remain the same irrespective of the framework or architecture of the Data Security used. Hence the solutions can be determined on the basis of CIA. This paper presents a review on the fundamentals of Cloud Security and focuses on the importance of CIA for providing better solutions.

Effectiveness of Confidentiality, Integrity and Availability in the Security of Cloud Computing: A Review

Lung disease is one of the most harmful diseases in traditional days and is the same nowadays. Early detection is one of the most crucial ways to prevent a human from developing these types of diseases. Many researchers are involved in finding various techniques for predicting the accuracy of the diseases. On the basis of the machine learning algorithm, it was not possible to predict the better accuracy when compared to the deep learning technique; this work has proposed enhanced artificial neural network approaches for the accuracy of lung diseases. Here, the discrete Fourier transform and the Burg auto-regression techniques are used for extracting the computed tomography (CT) scan images, and feature reduction takes place by using principle component analysis (PCA). This proposed work has used the 120 subjective datasets from public landmarks with and without lung diseases. The given dataset is trained by using an enhanced artificial neural network (ANN). The preprocessing techniques are handled by using a Gaussian filter; thus, our proposed approach provides enhanced classification accuracy. Finally, our proposed method is compared with the existing machine learning approach based on its accuracy.

/pdf/aerial-separation-and-receiver-arrangements-on-identifying-247hvq4b.pdf

Radha Krishna Rambola

Papers

Evaluating Artificial Intelligence in Education for Next Generation

Data Mining Techniques for Fraud Detection in Banking Sector

Efficient approach for Tendering by introducing Blockchain to maintain Security and Reliability

Effectiveness of Confidentiality, Integrity and Availability in the Security of Cloud Computing: A Review

Aerial Separation and Receiver Arrangements on Identifying Lung Syndromes Using the Artificial Neural Network