International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE)
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IJMLNCE Editorial Note Volume No 04, Issue No 02
No full textIt gives me pleasure to present the editorial preface of the International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) Volume 04 No 02 (2020). This issue comprises five manuscripts contributed by authors.
The first paper of this issue titles, "Edge detection of Friction Stir Welded Joints by using Fourier Transformation," is contributed by Akshansh Mishra et. Al. In the manuscript, the authors have implemented two machine learning-based image processing techniques. They stated that visual inspection had played a vital role in the beginning era of science. Nowadays, image processing is finding application for defects analysis of the manufactured parts in many industrial processes. We have implemented two machine learning-based image processing techniques in recent work, i.e., Fourier Transformation operator and Laplacian operator for the surface defects detection in Friction Stir Welded joints. In conclusion, The quality of the weld surface in the Friction Stir Welding process depends on the input parameters such as Tool Rotational Speed (rpm), Tool Traverse Speed (mm/min), and an Axial Force (kN).
The second paper, titled "Utilize Machine Learning Methods to Detect Plaintext Passwords," is authored by Nada Alnoaimi et. Al. In this article, information security explores, where the author states that every company is a target today, no matter its type. Hackers and cybercriminals are after data which they can monetize in many ways. Being proactive and have a defensive and protective plan in place, such as evaluating and assessing IT security, is an excellent recipe for avoiding data breaches and, consequently, business disasters. Why not utilizing a machine learning platform could be trained to search text in a computer resource, detect a string of plaintext characters, and analyze the string of characters to predict or detect a plaintext password on a computer resource asset. The machine will be able to catch a plaintext password in a character string by analyzing plaintext character strings for typical password complexity, such as, for example, including at least one uppercase letter, lowercase letter, number, unique character, and text length (for example, minimum of eight characters). It will also predict a level of certainty that a character string includes a password and output a confidence score based on the expected level of certainty. Finally, it will categorize the confidence score in any number of prediction certainty levels, including, for example, three groups – high, medium, or low.
S Nagaprasad et al. contributed the third article for this issue titled "Heart Disease Prediction Propagation approach." Data mining methods are used to test complex data, and regression processing based on input data sets is used to estimate results. A variety of prediction analysis methods have been implemented in recent years. The clustering method k-means and SVM ( support vector machine) are a statistical, computational technique for clustering and defining primary data to detect cardiac disorders. In this study, the Back Propagation Method is used in tandem with the k-means clustering algorithm to cluster knowledge for improved prediction research performance. The implemented algorithm\u27s output is found in the cardiac disorder data sample collected from the UCI depositor. Within this sample, there are 66 attributes.Nonetheless, a subgroup of 14 qualities is needed for every study. The Cleveland platform is utilized in particular for machine-learning investigators. The research designed correlates with the current techniques, precision, error identification, and deployment time (using the numerical mean).
The Fourth article, title "Discovering Trending Topics from the Tweets By Odia News Media During Covid-19," was contributed by Swarupananda Bissoyi et. Al. This paper explores the Covid-19 pandemic\u27s onset, and the lockdown imposed because it has significantly fueled news consumption. News portals, including the ones in Odia language, are actively feeding news related to Covid-19 to their consumers via their websites and Twitter handles. The news items didn\u27t restrict to Covid-19 alone; they also touched various domains of life like education, healthcare, administration, politics, movies, etc. Discovery of the news trends provides a bird\u27s eye view of the issues and topics popular in the online community. This could be of interest to advertisers, marketers, researchers, sociologists, and policymakers. This paper applies Topic Modeling to discover the trends from the tweets made by the Odia news media from 20th March 2020 to 31st August 2020, the period which saw the emergence of both lockdowns and unlocks in India. We found that during this period, the Odia news media didn\u27t restrict themselves to report news surrounding Covid-19; rather they reported other happenings as well.
In the fifth and last article of this issue, titled "Designing Hand-Held Vibration Measuring Device for Industrial Machines," is contributed by Thi Dieu Linh Nguyen et al., In this manuscript, the authors discuss that Evaluating the quality of industrial machines, the vibration meter is used to measure the actual vibration of the machine. The two most important parameters describing machine vibration, amplitude, and frequency, are the basis for determining the cause of vibrations. Spectral analysis of the vibration signal will give information about the vibration level and choose which part of the machine the vibration signal is caused. This paper presents the manufacturing of vibration measuring devices with simple structure, compact size, and high accuracy at a reasonable price. The spectral analysis method of vibrating signals and real-time spectrum display of the measured vibration signals
I am sure that these five papers included in the International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) Volume 04 No 02 (2020) will be useful to the research community. At this end, I am thankful to the Editorial board member for their timely support in the review. I am looking forward to receiving your unpublished research work for Volume 05 No 01 (2021)
Exploring the implementation of artificial intelligence in the public sector
No full textThe evolution of artificial intelligence boosts its usage in the private sector, however the public administration seems to lag behind. This paper intends to identify the advantages and potential challenges for the implementation of the artificial intelligence in the public sector. The practical value of this paper lies in the fact that becomes a useful tool for decision makers that aim to adopt this technology in public organizations
Transfer Learning for Detecting Covid-19 Cases Using Chest X-Ray Images
No full textThe COVID-19 pandemic is a global health crisis that have already infected more than 3.5 million people and caused more than 250 thousand deaths around the globe. That is why it is critical to develop a more efficient way to detect and treat this illness. This paper utilizes transfer learning techniques to detect normal, COVID-19, and viral pneumonia cases from Chest X-Ray images. Four pre-trained models on ImageNet were chosen as the base model, which are ResNet50, VGG19, DenseNet121, and InceptionV3. The performance metrics of each fine-tuned model are overall similar. With an average recall, precision, f1-score, and accuracy of 97.42%, 97.42%, 97.23%, 98.3% respectively
Analysis of Cloud Computing Security Issues and Risks
No full textIn the world of computer networking, cloud computing makes a technical shift of computing services being provided locally to being provided remotely by third party service providers. The data which was previously kept under control of users now under the control of service providers cloud computing brings many financial and functional benefits as well as serious security concerns that may threaten business continuity and corporate reputation. The definition of cloud computing is still blurry in a large part, because of the magnitude of the security risks and the virtually unlimited amount of information being published over the unsecure platform.
The purpose of this paper is to assess how security risk factors are affecting the existing and prospective cloud users’ cloud usage strategies. Are they simply betting that financial benefits will surpass security risks, or are they confident that cloud providers are capable of assuring an equal or higher level of security than on-premise systems?
This survey, through the examination of published materials and studies, analyzes existing issues along with available countermeasures in order to evaluate the overall assurance level of cloud security. The primary goal of the survey is to assess how security concerns have affected or will affect the respondents’ decision on adopting cloud and its services. This study includes basics of cloud computing by adding its characteristics, models and their categories. Analysis also embraced the existing security concerns faced by researchers and their imposed methodologies
Efficient Distributed Web Crawler Using Hefty and Enhanced Bandwidth Algorithms for Drug Website Search
No full text
Rrefabricate a proficient search structure is very important due to current scale of the web. Information are mined by Search engines from the web and a program called web crawler which surfs the web in an efficient manner. Distributed crawler belongs to a variant of web crawler, uses a dispersed computation method. In this paper, we design and implement the concept of Efficient Distributed Web Crawler using enhanced bandwidth and hefty algorithms. Mostly Web Crawler doesn’t have any distributed cluster performance system and any implemented algorithm. In this paper a novel Hefty Algorithm and enhanced bandwidth algorithm are combined together for better distributed crawling system. The hefty algorithm, implemented to provide the strong and efficient surfing results while applying on the drug web search. We also implemented Enhanced Bandwidth algorithm to improve the efficiency of proposed crawler
The Economic Impact of Social Media Fraud and it\u27s Remedies
No full textThis paper presents the economic impact of social media fraud in Bangladesh and its IT-based prevention model. Online privacy and security problems become a big concern of online day by day. Many types of problems growing up here, for example, phishing, hacking, sabotage, etc. Social media is a popular and powerful tool to express personal life and also business purposes in Bangladesh. Social communicating websites such as Facebook, Twitter, WhatsApp, and LinkedIn are popular social sites. Facebook is the most popular one. By these media people communicate with their other friends, family and share thoughts, photos, videos and lots of data and also many types of business and commerce have developed on social media. Presently, people just depend on it, so it’s marketing value increases day by day well. As well as some Tech fraud groups have been formed and wake up to hack money in some tricky way in this big virtual society. At present, social media is one of the key areas for fraudsters. We will show in this paper based on our study in two ways, (i) how much money is being spent through it; (ii) IT-based prevention model of this problem. 
Discovering Trending Topics from the Tweets By Odia News Media During Covid-19
No full textThe onset of the Covid-19 pandemic and the lockdown imposed due to it has fueled the news consumption significantly. News portals including the ones in Odia language are actively feeding news related to Covid-19 to their consumers via their websites and Twitter handles. The news items didn\u27t restrict to Covid-19 alone; they also touched a variety of domains of life like education, healthcare, administration, politics, movies, etc. Discovery of the news trends provides a bird’s eye view of the issues and topics that are popular in the online community. This could be of interest to advertisers, marketers, researchers, sociologists, and policymakers. This paper applies Topic Modeling to discover the trends from the tweets made by the Odia news media from 20th March 2020 to 31st August 2020, the period which saw the emergence of both lockdowns and unlocks in India. We found that during this period the Odia news media didn’t restrict themselves to report news surrounding Covid-19; rather they reported other happenings as well
Edge detection of Friction Stir Welded Joints by using Fourier Transformation
No full textFriction Stir Welding process often results good quality weld joints in comparison to the weld joint fabricated by the conventional welding process. But there are chances of formation of various defects if the input parameters are not selected properly. In our case study, we have constructed an image based defect recognition system by using Fourier transformation method. Five types of filters i.e. Ideal Filter, Butterworth Filter, Low pass Filter, Gaussian Filter and High Pass Filter were used. The results showed that the high pass filter has more capability to detect the edges in comparison to other four filters. It was also observed that Ideal filter has a lot of distortions when compared to the Gaussian Filter and Butterworth Filter
IJMLNCE Editorial Note Volume No 03, Issue No 03
No full textThe International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) with ISSN: 2581-3242 is now indexed in popular databases such as BASE (Bielefeld Academic Search Engine), CNKI Scholar, CrossRef, CiteFactor, Dimensions, DRJI, Google Scholar, Index Copernicus, JournalTOCs, J-Gate, Microsoft Academic, PKP-Index, Portico, ROAD, Scilit, Semantic Scholar, Socolar or WorldCat-OCLC. We are now proud to present the ninth volume of the journal, Volume No-03 Issue No-03, with some high-quality papers written by international authors and covering different aspects related to machine learning and collaborative engineering.
Phan Trong-Thanh and Doan Van Thang published a work entitles “Joint Spatial Geometric and Max-margin Classifier Constraints for Facial Expression Recognition Using Nonnegative Matrix Factorization”. In this paper, they have presented the constrained NMF approach for problem the facial expression recognition. The proposed MNMF_SGR performs well in facial expression recognition task and its effectiveness has been proven in their model. To summarize, with many constraints allows them to build models effectively and specifically on high dimensional, sparse and noisy datasets. For their future work, more sophisticated and efficient way to tune kernel functions will be explored. They also plan to apply the proposed method to problems in other fields, such as bioinformatics and computer vision. Studying the convergence rate for MNMF_SGR and increasing the efficiency, they should be all in consideration.
Praneet Amul Akash Cherukuri published his article “Recommender System for Educational & Corporate Sector In Prediction of Domain Recommendations & Analysis using Machine Learning”. In this manuscript he suggest that his model has a huge impact on the educational institutions and the corporate sector of today\u27s highly competitive world. The model proposes a simple and cross-sector solution to both the corporate and educational sectors that could result in the huge increase of employability solving the problem of wrong decision making of job aspirants as well as mistakes made by the organization whereby suffering losses from those decisions. Hence it could benefit every academician in evaluating his/her students as well as their academic performance in a more sophisticated and a single independent platform that has analysis related to current world trends and scenarios. The model has a vast scope of improvement as well as can provide great accuracy with positive results in the future.
Akshansh Mishra published his article “Understanding Machine Learning for Friction Stir Welding Technology”. In this manuscript, he suggest that there is a loss of time and materials if the optimization of the Friction Stir Welding parameters is done through experimental studies which further leads to increase in the cost of the experiment. Machine Learning approach like Artificial Neural Network and image processing overcome these issues. So, it can be concluded that the mechanical and microstructure properties can be predicted and also the defects formation can also be observed by the implementation of various Machine Learning tools in the Friction Stir Welding process.
Anoop et al. published a work entitled “Study of Energy Efficient Algorithms for Cloud Computing based on Virtual Machine Migration Techniques”. This survey outlined some of the very recent approaches in knowledge graph-based recommendation systems. As knowledge graph is one of the effective representation mechanisms for knowledge that has been unearthed from unstructured text, it got wider acceptance among research communities. A knowledge graph represents entities and relationships as nodes and edges respectively and a large number of meaning-aware applications and algorithms can operate on this graph. One such application is recommendation systems that suggest a user with items based on their previous interactions with the system. Knowledge graph based recommendation systems became very popular recently primarily due to its ability to supply side information for augmenting data and thus enhancing the quality of recommendations. This paper discusses some of the very prominent approaches reported very recently in the recommendation literature. Some interesting research dimensions are also discussed towards the end of this paper. This survey will be useful for the researchers and practitioners who wish to work on entity knowledge graphs based recommendation systems.
Finally Amrit Kaur Saggu and Shivani Agarwal published a work entitled “Performance Evaluation of LAR protocol using real dataset on Highway and City Scenario” In this work they have evaluated the performance of Location Aided Routing protocol (LAR) for Vehicular Ad-hoc Networks (VANETs) in terms of throughput, packet delivery ratio and routing overhead. They have considered two scenarios namely highway and city scenario. For highway they have taken Delhi highway data from OSM map and for city scenario taken real traces of Bologna Ringway dataset. For each of these scenarios the performance is evaluated by considering variation in terms of number of vehicles and simulation time. They observe that with the increase in simulation time the throughput increases for both highway and city scenario. The packet delivery ratio and overhead tend to decrease with increase in simulation time
The Performance Enhancement Systems of Human Iris Pattern and Recognition Method through Digital Authentication Application
No full textHuman iris and recognition patterns have been recognized as the best biometric marking ever found, owing to the uniqueness of iris and the textured iris patterns tend to remain natural, unchangeable and recognizable through existence. Mathematical analyses of the special stable patterns formed within the iris include Iris detection methods and a comparative analysis is carried out utilizing an established database. In this document, a clean electoral system is created to build a fraud-free ID list of electors. To find the Iris and Eyes, the algorithm of canny edge detection is used, Dougman\u27s normalization procedure is used, object filters are added and finally the corresponding process is conducted for the Euclidian set. Biometric authentication confirms our identification by being a simple and increasingly secure method. We implement a weighted, majority voting process for all biometric authentication systems utilizing a bit wise contrast between inscription and biometric models to resolve this problem and to enable Iris identification in less than ideal images. We also observed that the approach outdoes the current majority and efficient bit sorting strategies through a set of tests with the database CASIA iris. Our approach is an easy and efficient way to boost the accuracy of established iris detection systems