bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Cloud Computing on Network Security and the Risk for Organization Behaviors
Authors: Ouda Alia J. , Yousif Ali N. , Hasan Ayat S. , Ibrahim Hassan M. , Shyaa Methaq A.
Published: January 2022

Cloud computing is currently provided consumer or business IT support via social media or by using the internet. Cloud computing on the other hand, is increasing the level of the network security risk due to the services are basically presented by a third party. This results in hard to control the privacy and data security. In addition, to maintain the service availability and support data collections. Cloud computing clouts several technologies such as virtualization, SOA, and Web 2.0, it is also claimed their security risk matters. In this paper, the most serious and important risks and threats of cloud computing are discussed. The main vulnerability is identifying through a review of the published works on the cloud computing environment with possible solutions to overcome these threats and risks.
Efficient Bandwidth Management for Load Balancing in Grid Computing
Authors: Almhanna Mahdi S. , Al-Turaihi Firas Sabah
Published: January 2022

Incoming Information Technology (IT) services appear with cloud computing perspectives that provide users access to IT resources anytime, anywhere. These services should be good enough for the user with some advantages for the cloud service provider. To achieve this goal, you must face many challenges, load balancing is one of these challenges. The most convenient option for some functions does not mean that option is always a good choice to achieve the entire work all the time. Resource overload and bad traffic that can lead to time exhaustion should be avoided, this can be obtained through appropriate load balancing mechanisms. This paper offers a simple solution for choosing the preferred server to distribute functions based on minimum bandwidth consumption.
Analysis of Online Social Behavior of Whatsapp Users
Authors: Dahiya Sonika , Saluja Aditi , Singhal Parteek , Johari Rahul
Published: January 2022

Whatsapp is the most popular social media platform that allows users to interact with each other by sending texts, emoji, images, voice notes, videos etc. Whatsapp users spend hours chatting with each other exchanging information and also sharing intimate feelings that are often touted as deep meaningful conversations. This paper focuses on the study of online social behavior of Whatsapp users which are primarily students in the age group of 18-25 years. 300Whatsapp chats from 30 university students have been collected and scrutinized to determine their online behavior in terms of being expressive on Whatsapp or not and also identifying their general mood on Whatsapp based on their emotional manifestation in the chats. This analysis can be of compelling interest to various psychological researchers, social media influencers and counselors.
Evaluating the Effectiveness of E-learning: Based on Academic Staff Evaluation
Authors: Al-Husseini Khansaa Azeez Obayes , Obaid Ali Hamzah , Kadhim Ola Najah
Published: January 2022

E-learning has become a popular learning method used in many local and international universities and in many educational institutions. The initial achievements of e-learning platforms and the online learning environment demonstrated outstanding advantages in distance education. However, it is necessary to conduct an evaluation of the educational process, and in particular an effective assessment of the learning environment via online-based e-learning platforms. Where this study aimed to identify the evaluation of the effectiveness of e-learning from the point of view of the teaching staff in the Technical Institute of Babel and the Technical Institute Al-Mussaib. To achieve the objectives of the study, the researchers prepared a questionnaire containing (32) questions, after verifying the tools of reliability and validity. The results of the study revealed that the evaluation of the effectiveness of e-learning was average and above average in some paragraphs of the questionnaire. The percentage (84,070) of faculty members use computers and smart phones to publish academic content through the use of the home internet, at a rate of (95,575) in the form of creating educational content in several forms, including video, audio and text at the same time.
The Impact of a Proposed Science Curriculum based on Digital Technologies on Students' Achievement and Motivation towards Learning Science
Authors: Alnajjar Eiad Abdulhalim Mohammad
Published: January 2022

The aim of many educational programs is to integrate digital technology education into all educational schemes. The goal of this study is to figure out whether using digital technology has an effect on learning chemistry subjects in schools. On top of that, this study focuses on researching the motivations for studying chemistry by employing digital technology. The study sample comprised 60 students from 7th grade in public secondary schools. One out of the two classes were used as the experimental group, while the other was served as the control group in a pre-and post-test quasi-experimental design. Traditional teaching techniques were primarily being executed in the control group, whereas digital technology-based teaching was focused on by the same teacher in the experimental group. A post-test was given to evaluate the degree of learning outcomes and accomplishment at the completion of the curriculum content. An in-depth questionnaire survey was also administered to get a good idea of how interested students are in using digital technology in their scientific learning education. Based on the findings, it was observed that the experimental group had a higher average success rate and higher learning achievement. The students in the experimental group showed higher motivation to learn science using digital technologies. The use of digital technology is an excellent method for active learning that both supports and increases academic accomplishments. This study will add to a small amount of previous research in this area by contributing to the limited number of studies that evaluate the efficacy of integrating digital technology in the teaching and learning process.
Challenges to Scaling up Mhealth in Ghana. A Framework for Assessing the Health System
Authors: Gyamfi Nana Kwame , Dayie Richard , Asiedu Eric Kofi
Published: January 2022

The promise for improving healthcare services has been confirmed by mobile device technology, but the decision-making process to acquire and use mHealth technologies on a scale is not directed. We apply a methodology to assess the potential and difficulties of efficient deployment of the mHealth at a scale in healthcare systems using the instance of Community Base Health Services (CBS) in Ghana. The advantage and difficulties of mHealth in community-based services in Ghana were examined in comprehensive research via a blend of key informant interviews, document reviews, and local project visits. The lessons gained from Ghana's local experience and elsewhere were based on a framework adjusted from 3 approaches to sustainable information and Communication Technology (ICT) evaluation. Four major characteristics of the system have been identified and evaluated: government stewardship and organizational, technical, and financial system. The prospects for successfully implementing mHealth in Ghana include the high penetration of mobile devices and a favorable e-health policy framework. Again, given a health system with a weal ICT setting and limited implementing ability, it is doubtful if the potential benefits of mHealth would benefit CBS through direct broad-scale adoption. The application of a healthcare system framework facilitates a systematic assessment of possible barriers to CBS growth in Ghana and is helpful for decision-making policy and practice for other small and medium enterprises.
Types of Attacks in Wireless Communication Networks
Authors: Hadi Teeb Hussein
Published: January 2022

One of the most important types that used to transfer data between nodes without using wires is a “wireless communication network”, where the transmission of data is censored remotely by using electromagnetic waves such as radio waves that usually implemented in the physical layer of the network. Continuous improvements in wireless network technology have reduced the security and speed differences between types of networks (wired and wireless), but in turn, increased security threats to wirelessly transmitted data. Wireless networks are weak in terms of "privacy protection" because anyone who is within the coverage area of a wireless network can attempt to break into that network. Hacking incidents have been reported frequently in places with shared free networks, and it has been observed that the places of open distributed networks of the Internet are most at risk of complete penetration of your phone or PC data. To solve this problem, several programs have been developed that provide protection for wireless networks that differ in terms of security. Some of them did not provide sufficient protection for wireless networks, such as Wired Equivalent Privacy (WEP), and others made progress in preventing intrusions compared to their predecessors, such as Wi-Fi Protected Access (WPA).
Analysis of Marketing Strategies in Dealing with Business Competition (Study on Ruba Muri Ikat Weaving MSME in Kupang City)
Authors: Bessie Juita L.D , Langga Anderias S.W. , Sunbanu Deitje N.S.
Published: January 2022

This research aims to identify internal and external factors and formulate appropriate marketing strategy for Ruba Muri Ikat Weaving MSME in dealing with the competition with other ikat Weaving MSME in Kupang City. This is a descriptive study using a combination of quantitative and qualitative methods. The research data obtained from observation, interviews and questionnaires. Respondents in the study amounted to 30 people. Data analysis using SWOT. Based on the grand strategy matrix show that Ruba Muri's marketing strategy is in the position of the Strength-Opportunities (SO) strategy with strategic priorities: product development strategies, implementing market development strategies, conducting vigorous promotions via social media, forward integration, and backward integration.
The Impact of Artificial Intelligence Applications on the Digital Marketing Development on the Telecommunications Companies in Jordan
Authors: Naji Dr. Loma Shafiq MOHD
Published: January 2022

This research mainly aims to analyze the main effect of the Artificial Intelligence applications; neural networks, expert systems and evolutionary computation, on digital marketing development. Specifically, the aim is to evaluate the new artificial intelligence applications in Jordan, especially those which can affect digital marketing development. Besides, the researcher designed questionnaires which were given on the basis of a technique of simple sampling. Moreover, they were applied on the Jordanian telecommunications companies. A number of 375 questionnaires were distributed. Furthermore, a number of 320 samples were gathered. The result was 85% response rate concerning all the respondents’ responses. The researcher relied on reliability test, descriptive analysis, and multiple regression tests, which were applied to achieve the objectives of this research. Furthermore, this study’s results reflected a positive effect of Artificial Intelligence applications; namely, expert systems, evolutionary computation as well as neural networks, on digital marketing development. However, Jordanian employees are concerned with Artificial Intelligence applications; expert systems, evolutionary computation as well as neural networks, on the basis of their perception’s analysis. Such applications can develop the digital marketing in the Jordanian telecommunications companies. Finally, this study’s results make it clear that companies have to improve those applications to enhance digital marketing world.
Improving Instrument Test Passing and Controlling based Digital Futsal Athletes: Quantitative Study
Authors: Irawan Roma , Albi Subro , . Umar , . Arsil , Komaini Anton , Budi Didik Rilastiyo
Published: January 2022

The problem in this research is that there is notest instrument passing and control designed according to the situation and condition of futsal athletes who follow digital developments in the West Sumatran environment, especially Padang State University. The purpose of this study was to make a prototype of a test instrument passing and control digital-based futsal athletes. This research is development research with a model design adapted from Borg & Gall. The research subjects were Futsal Athletes from the Faculty of Sport Science, Padang State University, and six experts, namely two Evaluation and Measurement Test experts, one Futsal Expert, and three IT Experts. The development of the test instrument for passing and control futsal athletes was carried out by testing the futsal athletes of Sport Science Faculty, Universitas Negeri Padang, Indonesia using a small group test of 30 people and a large group test totaling 177 people on futsal athletes in the city of Padang, where the method used was the expert validity method with an assessment using a questionnaire instrument and the method test and retest to test the reliability of the tool which was analyzed using the correlational r formula. The process of developing the test instrument for passing and control futsal athletes was carried out through the first stages, namely looking for potential problems, data collection, product design, design validation, design revision, product testing, product revision, usage trial, and product revision. Then the expert validation test was carried out with a questionnaire assessment so that 90% validity was obtained in the "Very Good / Decent" category and the validation level by the large group judge was 0.996 the "very high" category and the small group judge validation level was 0.997 "very high" with a small group reliability test of 0.997 and the large group of 0.996 with both reliability categories "High", the practicality value was 91% and the effectiveness value was 88%. Thus, it can be concluded that the test instrument is passing and control digital-based futsal athletes used as a measuring tool to measure passing and control.
The Efficacy of a Developed Educational Content that Complies with Quality of Digital Courses on Achieving Concepts of Islamic Education and Developing Motivation among Female Students of Educational Sciences Faculty in Jordan
Authors: Ibrahim Bassam Abdulla , Almobasher Dr. Zakaria Mahmoud
Published: January 2022

The study aimed to identify the impact of teaching a course on educational Islamic concepts through using a developed content, which complies with quality of digital courses, on concept achievement and motivation development among female students of Educational Sciences faculty in Jordan. To achieve its objectives, the study adopted the quasi-experimental approach. The sample comprised (50) female class teacher students who were selected from the faculty of educational sciences in Jordan, second semester 2020/2021. The sample was randomly divided into an experimental group that comprises (25) students who studied the developed learning content via distance education which complies with quality standards of digital courses, and a control one that comprises (25) students who studied the courses with the conventional way. The two instruments of the study: achievement test of Islamic concepts, and motivation standard for learning a subject on Islamic education, were both tested for validity and reliability. The findings revealed that there were differences with statistical significance at the function level (a = 0.05) between mean scores of the experimental group and those of the control counterpart, in concepts and in standard of motivation in favor of the experimental one. In light of such findings, the study recommends that quality standards should be used in designing the content of digital courses.
Women Workers: Social Aspects and Accessibility in The Residential Neighborhood and Probability to Commuting
Authors: Ranita Sylvia Vianty , Bachtiar Nasri , Siddin Fashbir Noor , Muharja Fajri , Putra Febriandi Prima
Published: January 2022

Women are often faced with considerations including the choice of mobility with or without commuting, which is inseparable from the role of social in the neighborhood. This study aims to analyze the probability of women workers commuting in Indonesia through social capital and accessibility from the neighborhood to the labor market. The logit model and marginal effect were applied in this research, using the 2018 microdata obtained from Indonesia National Labor Force Survey (Sakernas) and Indonesian Village Potential (Podes). These data are combined based on residence similarity at the district level of each individual. The results showed that trust and solidarity increase, the probability of women workers commuting declines by 3.9%. The group and networks level increases through women groups in the residential neighborhood area cause commuting probability to decline of 14.3% on women workers. The variable of facilities will increase with a rise in women workers' commuting probability by 2.5%. These results were controlled by sectoral variables, work, income, education, age, and marital status of women workers in Indonesia. The findings in this study explain the social aspect in the social capital approach originating from the residential neighborhood causes a decreased probability of that decision. The indicates that the social ties of traditional society are still attached to women workers in Indonesia. However, the accessibility in this article is that public transportation gives a positive probability to the decision to commute to women workers in Indonesia.
Persona Identification based on Social Media Profile Images for Personification and Safety
Authors: Gawade Prema Pandurang , Joshi Sarang Achyut
Published: January 2022

Personification is important to ensure safety in social media. Images embedded in social media data is an important source intelligently ensure the personal safety. Paper proposes an applied machine learning on embedded image media to extract important feature traits and understand the semantics of correlation of feature space to understand the personification of given user. A strong belief is calculated using cascaded method and this inference is applied to different ml algorithms to derive the overlap of feature space. This algorithm validates the proposed objective that the user with more overlap and correlation among feature space are highly personified with each other. Using this personification-based method, better safety is ensured to mitigate possible social media attacks.
Decision Support System Using CNN for Detecting the Type of Disease in Fruits and Vegetables
Authors: A. Parkavi , M.N. Pushpalatha , Alex Sini Anna , M.K. Premkumar
Published: January 2022

The life of people in modern society is changing rapidly because of the high improvements in technology and tools, in the engineering sector. This evolution is also impacting the way of working of people in society in different domains. Machine Learning, Image Processing and Data Analytics are facilitating this growth but not much. Their rate of explorations and innovations in the field of Agriculture is very less, even though people know the importance of this sector and the rate of contribution to the GDP of the country. There are many reasons for it, such as the new generation has lost interest in agriculture as there is a lot of risk in agriculture due to improper irrigation methods, abnormal weather conditions, pests and diseases and finally lack of knowledge to handle the situations. But a country like India needs to focus more on innovations in the agriculture sector as it is the backbone of the country. In our work, we have made an attempt to analyze and find the different patterns of the disease appearing on the vegetable/fruit and identify the category of the disease. So, the prediction of disease type is done based on the patterns implemented using Convolutional Neural Network, and the accuracy of the models is measured. In this study, we have focused on tomato vegetable which is a major crop worldwide. This work can also make it flexible with other predominant fruits/vegetables to analyze it’s patterns and predict the relevant diseases.
A Case Study on Design of Covid-19 Detection and Alerting System Using Machine Learning Techniques
Authors: A. Parkavi , V. Sangeetha , Alex Sini Anna , A. Syed Mustafa
Published: January 2022

Coronavirus or 2019-nCoV is not, at this point, pandemic but instead endemic, with in excess of 14 million complete cases all throughout the planet getting the infection. At present, there is no particular treatment or solution for Coronavirus, and hence living with the sickness and its manifestations is unavoidable. The connection coefficient examination between different needy and free highlights was done to decide a strength connection between every reliant element and autonomous component of the dataset before building up the models. The database is divided into two parts, 80% of the database is used for model training and the remaining 20% is used for model testing and evaluation. In 2019, early Coronavirus predictions is useful to reduce colossal weight on medical service panels through the diagnosis of coronavirus patients. In the proposed work in this paper, Naive Bayes, Decision tree, Support Vector Machine (SVM) and Artificial neural network (ANN) models are used for forecasting COVID-19 prediction and occurrences.
Automation of Internet of things Using Deep Learning on the Basis of Extraction of Data
Authors: Anam Mamoona , D. Harikrishnan , A. Prithiviraj , R. Regin , M. Kalyan Chakravarthi , K. Praghash
Published: January 2022

Sharing and reusing data across apps and industries is critical for the Internet of Things to realize its full potential. However, various IoT systems exist, each with its networks, depictions, and interaction swatches. To address this problem, On the one extreme, the Fed4IoT project has established an IoT virtualization software that merges data from various sources. It makes the data that users need accessible in their choice operating system, but on the other hand. Data is converted into an impartial, standard transfer protocol to make this possible. The preferred format is the next generation service interfaces, and it is now being standardized by the European Telecommunications Standardization Institute Industrial Standards Group on Frame of reference Data Governance. The elements particular basis of interpretation data to next-generation service interfaces, passed over to the particular platform and transformed to the destination format, are known as Something Shields. Hand-building thing visors are possible, but it requires time and work, partially due to the variety of low-level data many sensors provide. As a result, it's necessary to aid the human developer and, ideally, completely automate the gathering, enriching, and exporting data to NGSI-LD. Automation has many potential answers, but it frequently necessitates a huge amount of manually tagged datasets, which is impractical in numerous internet of things scenarios. Knowledge infusion identifies with an application method that uses expert knowledge to match a schema or ontology obtained from information supplied a discourse marker or ontology, setting the framework for identifying gathering as much information and support transformation.
Content Classification Tasks with Data Preprocessing Manifestations
Authors: Anam Mamoona , Rane Dr. Kantilal P. , Alenezi Ali , Mishra Ruby , Ramamurthy Dr. Swaminathan , Joseph Ferdin Joe John
Published: January 2022

Deep reinforcement learning has a major hurdle in terms of data efficiency. We solve this challenge by pretraining an encoder with unlabeled input, which is subsequently finetuned on a tiny quantity of task-specific input. We use a mixture of latent dynamics modelling and unsupervised goal-conditioned RL to encourage learning representations that capture various elements of the underlying MDP. Our approach significantly outperforms previous work combining offline representation pretraining with task-specific finetuning when limited to 100k steps of interaction on Atari games (equivalent to two hours of human experience) and compares favourably with other pretraining methods that require orders of magnitude more data. When paired with larger models and more diverse, task-aligned observational data, our methodology shows great promise, nearing human-level performance and data efficiency on Atari in the best-case scenario.
Mobile Ad Hoc Network Improvement against Jammers for Video Applications Using Riverbed Modeler (v17.5)
Authors: Nourildean Shayma Wail , Mohammed Yousra Abd , Salih Abdulkreem Mohammed
Published: January 2022

MANETs (Mobile Ad hoc Networks) had become the most important next generation wireless network technologies. It is made up of self-configurable mobile nodes, Intruders mieght decrease MANET functionality due to the dispersed and wireless nature of MANETs, and therefore they were vulnerable to numerous attacks at different levels. The important challenges for MANET were the security and routing protocols. This paper examined the impact of Jammer which it was a kind of DoS attack which interfere with the normal operation of network and show how the Jammer increased the delay and data dropped and decreased the throughput which they were the important parameters for the measurements of network performance. This performance could be improved using routing protocols (AODV, DSR, OLSR and GRP). Riverbed Modeler Academic Edition (17.5) was utilized for this study in number of modeled scenarios for video applications. The results address the impact of Jammers and show that the MANET's Routing Protocols could improve the throughput and data dropped of the network but on the expense of increasing the delay.
A Novel Image Encryption Approach for IoT Applications
Authors: Alawsi Wasan A. , Obayes Hadab Khalid , Hussain Saba M.
Published: January 2022

The rapid developments observed in the field of Internet of Things (IoT), along with the recently increasing dependence on this technology in home and financial applications, have made it necessary to pay attention to the security of information sent through these IoT applications. The present article proposes a new encryption method for important messages that are sent via IoT applications. The proposed method provides four levels of security for the confidential message (in this case, an image). The first level is represented by applying the Conformal Mapping on the secret image. The second level is represented by encoding the resulting image from the first level using the encryption and decryption (RSA) method, while the third level is the use of Less Significant Bit (LSB) as the hiding method to hide the message inside the cover image. The compression of the stego image using GZIP is the last level of security. The peak signal-to-noise (PNSR) metric was used to measure the quality of the resulting image after the steganography process. The results appear promising and acceptable. Therefore, it is suggested that this method can be applied to send secret messages through applications of special importance across the IoT.
Syariah Technology Financial Potential to Reach Non-bank Financing
Authors: Siahaan Matdio , Anantadjaya Samuel PD , Kurniawan I Made Gede Ariestova , Purba Anwar Soleh
Published: January 2022

The establishment of Syariah Financial Technology (FinTech) has answered the needs of the current transaction system. The presence of financial technology has made the current financial system run fast and efficiently. This research will explain and analyze the potential of Islamic Fintech in reaching non-bank financing. Data collection used in this research is descriptive qualitative method by directly observing the field. The analysis technique used in compiling the potential of Islamic FinTech is the matrix of Strengths, Opportunities, Weaknesses and Threats (SWOT). The results of the SWOT analysis show that there are several potentials for Islamic FinTech, including: 1) More potential investors and lenders considering that the majority of Indonesians are Muslim, 2) There are clear regulations related to Islamic FinTech in Indonesia, 3) Ease of access to services for all people, 4) Save operational costs and marketing costs for the company, and 5) The types of products offered to customers are more diverse, both in the form of financing and savings. So it can be concluded that with the existence of Technology Finance, the public will be more assisted and easier in conducting transactions between banks.
Learning Validation Control and Input Error Correction on Implementation of Computer Assisted Audit Techniques (CAATS) (Review New Trends in Sustainable Development of Learning Education Management Models for the Accounting Student)
Authors: Nasution Abdillah Arif , . Erlina , Muda Iskandar , Atmanegara Agung Wahyudhi
Published: January 2022

This study aims to determine the effect of Learning Model validation control and input error on the implementation of computer assisted audit techniques (CAATs). The data of this study were obtained by using a questionnaire that was used by students in the Accounting Information System course. Questionnaires that can be processed further are 73 questionnaires. The hypothesis was analyzed using Structural Equation Model (SEM) use the 3.0 SmartPLS applications. The research results obtained from this study are variable: Implementation of learning model of Validation Control and Input Error Correction variables have no effect on the implementation of Computer Assisted Audit Techniques (CAATs). The implementation of management in managing education for validation control and implementation of Computer Assisted Audit Techniques (CAATs) in universities must be supported by personnel resources and other resources that are used to realize the performance of high education organizations.
The Environmental Index of Kuwait: Ways and Chances of Development
Authors: Abuamer Dr. Fatena F R
Published: January 2022

This research aims to identify factors affecting the Kuwait Environment Performance Index by identifying the most important environmental problems in Kuwait, identifying the Global Environmental Performance Index and identifying Kuwait's position in the 2020 Global Environmental Performance Index (GII) and studying the most important factors of improving the environmental performance index in Kuwait.
Use of WhatsApp in Synchronous and Asynchronous Education in Students of the IV Cycle of Peruvian basic Education
Authors: Chiparra William Eduardo Mory , Suca-Apaza Guido Rene , Rosales-Dominguez Ediht Geobana , Mosquera-Torres Dino Fernando , Alarcón-Trillo Ana Yuli , Suazo-Zárate Jean Paul
Published: January 2022

The study proposed to delimit the use of WhatsApp and its relationship with synchronous and asynchronous education in students of the IV cycle of basic education. For this purpose, the correlational descriptive study method was used and 74 students were considered a sample. The result revealed the existence of a positive relationship expressed in Spearman's Rho = 0.315, p = .000; where it was found that the use of WhatsApp is an interactive technological resource that supports students in synchronous and asynchronous education. That is, WhatsApp is a didactic technological resource that supports synchronous and asynchronous learning, allowing students to build meaningful knowledge in a dynamic, attractive, interactive and autonomous way.
Web 3.0 Application to Improve the Digital Skills of University Teachers
Authors: Moreno Giancarlo Roosvelt Contreras , Relaiza Héctor Raúl Santa María , Salazar Katherine Talía Ganoza , Alejo Lizbeth Giovanna Toribio , Latour José Elias Plasencia
Published: January 2022

2020 was an atypical year for many sectors and especially for the education sector, face-to-face education in schools and higher education entities ceased to be applied, starting virtual education in the context of the health emergency caused by Covid-19. Teachers had to make changes and adapt to the new reality to acquire knowledge of web applications to develop digital skills, important elements, especially in the current context. The research had a non-experimental design, cross-sectional causal correlation. The sample consisted of 405 teachers from 4 public universities, selected by random non-probabilistic sampling. Questionnaires were used for both variables measured with a Likert scale from 1 to 4 points; 15 items were formulated to measure the web 3.0 variable and 21 items for the digital skills variable; The first questionnaire has an acceptable reliability value (Cronbach's Alpha = 0.901, 95% CI) and the second, self-regulated learning with an acceptable reliability value (Cronbach's Alpha = 0.921, 95% CI). The results indicate that the use of Web 3.0 applications allows teachers to publish content, Cloud Computing tools or E-Learnig tools, managing to develop digital competence for collaborative communication with students. Finally, the Web 3.0 application has a significant influence on digital skills.
A Study on Trend and Pattern of Beneficiaries of Prime Minister Employment Generation Scheme
Authors: Borkar Kunal Dhananjay M , Rodrigues Prof Anthony , Mascarenhas Alroy A.S.
Published: January 2022

MSME has been considered as one of the major dynamic forces for the economic development in developing economy. MSME’s continuous immense contribution towards manufacturing, exports, employment opportunities empowering rural youth by providing equitable opportunities directly or indirectly is strengthening the economy. The growth of enterprise sector is also developing a strong base for entrepreneurship development which is considered to be as one of the major indicator of economic development. Every new start up needs to raise capital to implement new ideas, easy availability of finance for same is acting as one of major challenge. The Government of India through its institution has made several arrangements by launching several schemes, financial assistance to meet the diverse financial requirement. In Goa the Prime Minister Employment Generation Program is managed by two Government agencies i.e. Khadi Village Industries and Department of Industries, Trade and Commerce. This paper is a sincere attempt to study the trend and pattern of financing start up entrepreneurs through Prime Minister Employment Generation Program by Department of Industries Trade and Commerce in Goa.
Analysis of Readiness to Organize Learning from Home for Early Childhood during the COVID 19 Pandemic Period in Indonesia
Authors: . Ismaniar , Rahmat Abdul , Arbarini Mintarsih , Isa Abd Hamid
Published: January 2022

This research was motivated by complaints from various parties about the less than optimal learning outcomes for children during the Covid 19 pandemic in Indonesia. This study aims to see the readiness of various parties to support the implementation of learning from home during the COVID-19 pandemic in Indonesia. This research is a descriptive research with a quantitative approach. The population of this study were educators and parents of children aged 3-6 years, research respondents found 450 people consisting of 325 PAUD educators and 125 AUD parents, who came from 5 provinces in Indonesia (West Sumatra, West Java, Central Java, East Java). Java and Gorontalo). Processing data using the percentage formula. Based on the results of data processing, conclusions can be drawn; 1) More than (an average of 53%) educators in PAUD institutions are already quite well prepared in dealing with learning activities from home, this can be seen from the readiness of learning plans, learning media, and learning applications used. However, there are still educators who are uncomfortable or unprepared because they have limited operational skills for learning applications, 2) Almost all early childhood parents (+ 47%) are not ready to face learning activities from home, because the media and supporting facilities they have are insufficient, limited knowledge and skills in using learning applications, the availability of internet networks, and the time limit for assisting children to learn due to economic factors. 3) Almost learning from early childhood (+48%) are not ready for learning activities from home because children are accustomed to learning to play with peers, so that they are tired of studying on their own from home, children are not independent and need intensive assistance from parents, and limited media and supporting learning facilities from home.
Network Attacks Detection Depend on Majority Voting – Weighted Average for Feature Selection and Various Machine Learning Approaches
Authors: Essa Hasanain Ali Al , Bhaya Wesam S.
Published: January 2022

Due to the enormous growth in Internet usage and computer networks in recent years, new risks and challenges have arisen to network security. Among lots of security problems, network attack is a significant one. For instance, Distributed Denial of Service (DDoS) attacks have become appealing to intruders, and these have presented destructive threats to network infrastructures. Thus, Intrusion Detection Systems (IDSs) and Machine Learning (ML) approaches play a key role to detect such attacks effectively and efficiently. An essential part of several classification issues is the feature selection phase because to detect DDoS attacks depends on how one selects the minimal and relevant features in the network traffics. Unlike recent studies, in this work, a real-life SNMP-MIB dataset is used, as well as, we suggest an Ensemble-Weighted average approach (EnWaFS) that excludes the irrelevant features. An EnWaFS approach consists of two methods, first, Ensemble features by using a majority-voting method that mixed the outcomes of three feature selection approaches, second, a weighted average method that gives one weight for each feature and diminishes also the number of attributes. To evaluate an EnWaFS approach, we have performed four Machine Learning classifiers Neural network (Multi-Layer Perceptron), Vector Support Machine (SVM), Naïve Bayes (NB), and Random Forest (RF) utilizing the optimal set of attributes. The results reveal that our EnWaFS approach can efficiently decrease the number of attributes from 34 to 12 and also, from four ML classifiers were used, the RF technique achieved better performance due to the accuracy, sensitivity (recall), F-1 measure, precision, true-positive-rate, and the false-positive-rate which is decreased.
Face Recognition Method based on Support Vector Machine and Rain Optimization Algorithm (ROA)
Authors: Nabat Zahraa Modher , Mahdi Mushtaq Talib , Shnain Shaymaa Abdul Hussein
Published: January 2022

One basic study direction in pattern recognition research domain is Face recognition. Face recognition-based Authentication is used widely. Face recognition is related to non-linear issue; therefore, some techniques of artificial intelligence have been used in last few years to face recognition. According to recent results, support vector system classifiers (SVM) have excellent face recognition accuracy in pattern recognition in comparison with other classification methods. Although, support vector machine training parameters selection has great effect on the performance of support vector machine. Here in the research, the novel Rain optimization algorithm and support vector machine algorithm (ROA-SVM)-based method of face recognition is provided. In ROA-SVM, Rain optimization algorithm is applied for optimizing SVM parameters at the same time. The average classification accuracy for the YALE dataset in the proposed method was 86% and for the base paper was 81%. Furthermore, in order to find optimal parameters in support vector machine, proposed ROA-SVM method efficiency has been improved by 5 percent in comparison with PSO-SVM basic research.
Improved MANET Routing Protocols Performance by Using Hybrid Cat and Particle Swarm Optimization (CPSO)
Authors: Hadi Ahmed Adnan , AL-Din Makki Seyed Vahab
Published: January 2022

The technology that used in communicating data and voice among certain mobile network nodes using wireless medium and radio spectrum transmission is called Mobile networking. Generally, Mobile refers to the intent, portable and lightweight devices that may be carried by their movie users. In this paper, we proposed a hybrid version of the swarm optimization model to improve the MANET routing protocols. The proposed optimization sets optimal parameters for the MANET networks. The proposed model combines between Particle Swarm Optimization (PSO) and Cat Swarm Optimization (CSO). The methodology which will be developed in this research can be used for revealing the MANT networks or mobile sensor networks the study involve enhance mechanism(s) that can be used to avoid degraded routing issues to increase the performance. The result the obtain by proposed model satisfy best result compared with both PSO and CSO.
Semantic Segmentation of Urban Street Scenes Using Deep Learning
Authors: Noori Amani Y. , Shaker Dr. Shaimaa H. , Azeez Dr. Raghad Abdulaali
Published: January 2022

Scene classification is essential conception task used by robotics for understanding the environmental. The outdoor scene like urban street scene is composing of image with depth having greater variety than iconic object image. The semantic segmentation is an important task for autonomous driving and mobile robotics applications because it introduces enormous information need for safe navigation and complex reasoning. This paper introduces a model for classification all pixel’s image and predicates the right object that contains this pixel. This model adapts famous network image classification VGG16 with fully convolution network (FCN-8) and transfer learned representation by fine tuning for doing segmentation. Skip Architecture is added between layers to combine coarse, semantic, and local appearance information to generate accurate segmentation. This model is robust and efficiency because it efficient consumes low memory and faster inference time for testing and training on Camvid dataset. The output module is designed by using a special computer equipped by GPU memory NVIDIA GeForce RTX 2060 6G, and programmed by using python 3.7 programming language. The proposed system reached an accuracy 0.8804 and MIOU 73% on Camvid dataset.
Resource Allocation Computing Algorithm for UAV Dynamical Statements based on AI Technology
Authors: Kovalenko Vadim , Rodakova Anna , Al-Khafaji Hamza Mohammed Ridha , Volkov Artem , Muthanna Ammar , Koucheryavy Andrey
Published: January 2022

An unmanned aerial vehicle (UAV) is one of the complex and relevant communication networks of 5G and 2030 networks. Development of technologies for virtualization (NFV), containerization and orchestration of data systems. NFV technology can be implemented not only in the data center but also on the switch or router. Thus, by analogy with the above-described trend, flying network segments can also use computing power to solve any problems. For example, deployment on virtual distributed capacities of a flying station controller, an internal network controller. Within the framework of this direction, there are a number of interrelated tasks that need to be resolved by the trends and capabilities of Artificial Intelligence technologies. This paper proposes an algorithm for searching for computing resources in real time. The article defined the criteria for choosing the head node and the cluster with the highest total resources, considered the possibility of implementing the function of the SDN controller in the UAV cluster, the main possible functions and tasks of the UAV, proposed a three-level architecture based on the separation of the functions performed by the UAV. In this work, simulation was carried out in the Matlab program to detect areas of increased load, form UAV clusters, select a head node in clusters and select one UAV cluster with the highest total resources for its subsequent migration to the area of increased load.
Study and Evaluation of Wireless Sensor Networks Performance
Authors: Shihab Luay Abdulwahid
Published: January 2022

This project analyses vehicle behavior from measurements of air pollutants (CO2) sound pollution levels, measured in ppm and decibels respectively. Such measurements are taken by a wireless sensor network mounted in the Baghdad Dora Express way, Iraq. Four sensor nodes and a coordinator form the wireless network based on the Zig bee norm. The sensor nodes wirelessly send the data to the coordinator, who displays the actions defined by the measurement curves through a graphic interface built in JAVA and store the data on a MySQL web server. The analysis of vehicle behavior considers noise levels and carbon dioxide concentration higher than their base reference value, measured in a certain period of time. Comparative and individual graphs of noise and carbon dioxide concentration taken in two days of measurement, belonging to the nodes, show greater vehicular activity in peak hours that are reduced at the end of the day and at midnight, in addition to the individual performance of the nodes within the network, which depends on the infrastructure of the Integrated Security System ECU911.
Understanding Research Methods in Development Context: A Synthesis Paper on Research in Development Arenas
Authors: Kanyamuna Vincent
Published: January 2022

Submitted for publication
Training of Small Farmers and Minority Agroforestry Landowners in Southeastern US – an Evolving Model
Authors: Christian Colmore , Fraser Rory , Herbert Berneece S. , Scott Chelsea
Published: January 2022

Traditionally, extension activities are aimed at the transferal of knowledge from professionals to small-farmers and landowners.  This process is supported by the Forestry Extension Model (FEM), which posit that professionals know what small-farmers and landowners need to learn, are the most credible source of land management information, and that small-farmers’/landowners’ education leads to sustainable land management practices.  Although recent studies have supported a shift to peer-to-peer landowner education, there is still a need for initial professional-to-small-farmer/landowner training.  Many underserved landowners lack forestry knowledge and practice and are usually unfamiliar with the available federal and state programs and resources. Therefore, they would require training before mentoring fellow small-farmers/landowners and gaining access to available resources.  This paper, based in part on the results of a questionnaire survey and small-famers/landowners training initiatives, outlines elements of an evolving ‘landowners training model’ – a model where aspects of the FEM have been applied in a setting conducive to peer-to-peer mentoring.