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Iris image quality assessment is a strategy of estimating data substance of iris imagery at the phase of iris acquisition or at early preprocessing stage. The information substance might be taken to be utilized for iris identification dependent on a single image. The image might be disposed of, or joined with other imagery to improve recognition abilities of an iris system. Evaluate quality metrics would be the rules in settling on choices with respect to additional means regarding gained imagery. Implement this algorithm on open source iris databases (IIT Delhi, UBIRIS and UPOL Iris Database). We compare with the support of quality measure parameters with both original iris image and enhanced iris images. The consequential images quality is tested by using quality measures like PSNR, MSE, MAXERR, L2RAT, it is found that quality has been enhanced. Hence it is shown that the recognition rate is rises.

Quality Measure, Iris Recognition System, Biometric, PSNR, MSE, MAXERR, L2RAT

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[10] Jenadeleh, M.; Pedersen, M.; Saupe, D. Blind Quality Assessment of Iris Images Acquired in Visible Light for Biometric Recognition. Sensors 1308, 2020.
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Sonali S. Gaikwad, Jyotsna S. Gaikwad, Ramesh R. Manza, "Statistical Evaluation of Image Quality Measures for Improving Iris Recognition Performance," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.1-5, 2021.

Everybody loves to be in front of the mirror at least once a day. Such a mirror can also be used as an intelligent device that can enable lot of opportunities. Intelligent mirror can help in effective parenting. Looking after child needs and keeping track of their activities like homework, eating, tuitions, sports/dance classes and others is difficult. The intelligent mirror can help by communicating child different alerts and messages, as soon as the child stands in front of mirror. Parents can keep updating instructions to mirror. Disabled people find difficulty in checking daily updates, keeping reminder systems and receiving notifications of their friends/relatives. They have to depend on someone to support all these tasks. Such people just need to be visible in front of the smart mirror and get all the required updates and notifications. Apart from these, every individual has lot of reminders, updates, and tasks to be done every day. Daily news, weather forecasts, streaming of desired videos, user interest driven advertisements need to be displayed as soon as user comes in front of mirror. The proposed intelligent mirror is developed using Raspberry Pi, two-way mirror, camera module, face recognition and server side technologies. An easy to use Android App has been developed in Kotlin to facilitate updating activity schedules, record and upload Audio messages, user to customize their interest and profile settings and view the history of schedules.

Smart Mirror, Convolution Neural Networks, Raspberry PI, IoT, Android

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[14] N. Vani, M. Varatharaj, P. Jayanthi, P.S. Vishal kumar, S. Maheswari, R. Nishanthakumar, "Opulent Futuristic Smart Sensing Garden," International Journal of Computer Sciences and Engineering, Vol.8, Issue.2, pp.35-38, 2020.
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Chetan K.R., "An Intelligent Mirror for Parenting, Supporting Aid and Personal Agent," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.6-15, 2021.

Kajal Devi, Harjinder Kaur, for a productive life, Marketing plays a critical role to fill individual life with value and excellence. Marketing is compulsory to provide things that individuals partake in to compete in the modern world. Predicting the academic performance of the Business is the most successive research in this era. A different set of approaches and methods are incorporated to increase Business performance. However, this is a challenging task due to the wrong course selection. In this paper, we have used the Cluster-based Linear Discriminant Analysis (CLDA) and Artificial Neural Network (ANN) based approaches for the prediction and classification of Business performance. The proposed study will provide the prospective business with the motivational comments and the video recommendations by which Business can choose the right subject and the comments will facilitate the Business with the insight reasons of dropout opted by other Business for this course. The outcomes of this study will help in the reduction of the number of dropouts. The Business will be able to choose an appropriate course for performance enhancement and carrier excel.

Cluster-based Linear Discriminant Analysis (CLDA), Business performance, Dropouts, Classification, Prediction, and machine learning

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Kajal Devi, Harjinder Kaur, "Emotion Analysis and Performance Perdiction Using Cluster Based LDA," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.16-24, 2021.

Data mining, text mining and opinion mining have occurred in one form or another since modern record keeping began. As the number of online shopping users is increasing, access to social media sites produces vast quantities of information in the form of user feedback, comments, blogs and tweets tests. For this reason, Sentimental analysis is required, which classifies these reviews to gain insights into the data generated by the user. The main problem with the analysis of the feeling is the uncertain mood of the user, such that the interpretation of what the user has written and what he actually thought is somewhat different. The problem analysed in the existing work is that the decision-making trees, particularly when a tree is very large, are likely to parallelize. Random forest classification is used to eliminate both errors due to bias and variance. In the proposed research, the improved technology is implemented with Random forest and optimization of the Ant colony search is hybridised with the proposed classifier in order to accomplish the classification of film screens by studying the sentiments.

Sentiment Analysis, Social Media, Movie Reviews, Data Mining

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[14] S. Tiwari, A. Verma, P. Garg, D. Bansal, “Social Media Sentiment Analysis on Twitter Datasets”, 6th International Conference on Advanced Computing and Communication Systems (ICACCS), 2020.

N.K. Deol, V. Thapar, J. Singh, "Movies Reviews Sentiment Analysis using Improved Random Forest Algorithm and ACO (Ant Colony Optimization) Approach," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.25-30, 2021.

Exact expectation of stock trade returns could be a difficult undertaking in view of unpredictable and non-direct nature of the monetary securities exchanges. The financial exchange information, as S&P500 Index is gigantic, perplexing, non-straight and noised. Foreseeing stock costs is a difficult undertaking as it relies upon different elements including however not restricted to worldwide economy, political conditions, organization`s monetary reports and execution and so on The speculation models utilizing this data have been a test. Along these lines, to augment the benefit and limit the misfortunes, procedures to anticipate estimations of the stock in advance by examining the pattern over the past couple of years, could end up being exceptionally valuable for making securities exchange developments [42,43]. This investigation proposes the accompanying momentary bit by bit technique: to consolidate two data sources that the financial backers can break down to settle on a choice. In the first place, the file information comprises the contribution for Profound Learning Neural Organization preparing, for addressing and estimating following day stock worth. Second, this exploration distinguishes the principal delegate endeavors, remembered for File, which address the List social inclination, utilizing Highlight Determination Investigation. At long last, the yields are supplemented and verified; the technique shows promising outcomes to upgrade the financial backer`s choice. Especially, for stock trade investigation, the data size is enormous and furthermore non-direct. To influence such an information proficient model is required which will recognize the secret examples and muddled relations during this huge informational index. AI strategies during this region have demonstrated to improve efficiencies by 60-86 percent when contrasted with the past techniques.

Stock Exchange, Machine Learning, Predict, Feature Selection and Forecasting

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S.K. Sharma, "Process Improvement in the Criteria of Investment on Stock Market Using Data Mining Techniques," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.31-38, 2021.

Data Mining plays an important role in the Business world and it helps to the marketing institution to predict and make decisions related to the business’ academic status. Predicting business’ performance becomes more challenging due to the large volume of data in marketing databases. Currently in Malaysia, the lack of existing system to analyse and monitor the performance of the business is not being addressed. There are two main reasons of why this is happening. First, the study on existing prediction methods is still insufficient to identify the most suitable methods for predicting the performance of the business in Malaysian’s institutions. Second, Due to the lack of investigations on the factors affecting student’s achievements in particular courses within Malaysian context. Therefore, a systematically literature review on predicting student performance by the proposed system is a web based which makes use of the mining techniques for the extraction of useful information. This work is dig insight into state and event-based approaches for predicting student performance. Comparative analysis is conducted to suggest regression-based algorithms of state-based framework lack accuracy and correlation-based algorithms under event driven approach outperforms classical regression algorithms. It is also concluded from pedagogical point of view, higher engagement with social media leads to higher final grades

Performance Prediction, Learning Analytics, Regression algorithm, correlation algorithms, social media

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Kajal Devi, Harjinder Kaur, "A Critical Analysis of Techniques Used For Learning Analytics Corresponding to Buiness," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.39-44, 2021.

In recent days, skin cancer is one of the most dangerous form of the cancers found in humans. Skin cancer is found in various types such as Melanoma, Basal and Squamous Cells Carcinoma among which Melanoma is the most unpredictable. The diagnosis of Melanoma cancer in early stage will be helpful to cure it. Melanoma is type of skin cancer that evolve from melanocytic cells. Because of Malignancy feature melanoma skin cancer is also defined as Malignant Melanoma. Melanoma cancers have so many stages which will increase the death rate of patients. So early diagnosis and treatment of Melanoma implicate higher chances of cure. Traditional methods to diagnose skin cancer are excruciating, invasive and time consuming. So to overcome this problem different techniques used for skin cancer detection. These techniques use Machine learning and image processing tools for the detection of Melanoma skin cancer. The input to the system is the skin lesion image and then by applying image processing techniques, it analyses to conclude about the presence of skin cancer. The lesion image analysis tools checks for various Melanoma parameters which are like Asymmetry, Border, Colour and Diameter (ABCD) by texture, size and shape analysis for image segmentation and feature stages. The extricated feature parameters are used to classify the image as Normal skin and Melanoma cancer lesion.

Melanoma, Image processing, Classification, Machine Learning

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A.S. Solanke, Y.M. Rajput, P.D. Deshmukh, "Review on Extraction and Classification of Skin Lesion towards Melanoma Cancer Using Machine Learning Techniques," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.45-47, 2021.

Now a day’s neural network plays a vital role in analyzing, interpreting and fitting models. In this paper by taking wind speed as dependent variable and minimum temperature, maximum temperature, visibility, temperature date and time as independent variables, we fitted. M5P, SMO Regression and zero regression models and CV parameter selection criteria is also used for above three models. For computational purpose WEKA Software is used. By measures of accuracy like mean absolute error, root mean square. Relative absolute error, root relative squared error are used to select the best model and also rank them.

Wind speed, Zero regression, M5P, SMO regression, WEKA

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B. Hari Mallikarguna Reddy, S. Venkatramana Reddy, B. Sarojamma, "Data Mining Techniques for Estimation of Wind Speed Using Weka," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.48-51, 2021.

In cloud computing data and applications have been maintained using remote servers that is distributed and it utilizes internet. The main advantage of using cloud computing is that it allow user to use applications over the internet and also share files at any computer over the internet. The use of cloud computing has tremendous impact over the IT industry and also it provides efficient use of resources like bandwidth, storage and processing. As the growth of cloud computing increases many users interact with each other and security issues are arising. The cloud computing growth is hampered by these security issues. There are risks of data breach, data loss, unauthorized access, denial of services etc. In this paper the analysis cloud computing security issues and also surveyed various techniques that are used to handle cloud security.

cloud computing, security

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Diksha Sagotra, Harjinder Kaur, "Techniques for Future Enhancement for Security of Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.52-58, 2021.

Secure communication in Computer Network is very important which can be achieved by Transport Layer Security (TLS) protocol. Various libraries have been created for the implementation of TLS functions by the researchers, of which each has wide support of the encryption algorithms, key exchange mechanism from which one can implement TLS for secure communications. In this paper, to find the best suitable SSL/TLS library, relative analysis of the six widely used libraries has been done based on various affecting parameter such Languages, Cryptographic Token Interface - PKCS#11, Thread Safety, and CPU Assisted Cryptography with AES-NI. Any organization can use an effective and efficient library that will provide the appropriate security and fulfill the expectation of the application.

Thread Safety, TLS, AES-NI

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Suresh Prasad Kannojia, Jitendra Kurmi, "Analysis of Cryptographic Libraries(SSL/TLS)," International Journal of Computer Sciences and Engineering, Vol.9, Issue.9, pp.59-62, 2021.