Automated System to Preventing Social Security Fund Misuse by Identifying Deceased Beneficiaries

Ensuring safe and convenient access to essential services, including pension retrieval, is crucial in the current digital era. Passwords and PINs are examples of traditional authentication systems that frequently expose people to fraud and identity theft. In order to replace these traditional methods with biometric verification (such as fingerprint and facial recognition), this project suggests a Web Biometric Credentialing System for pension retrieval. The system incorporates Auth0 for secure identity and   management   of   sessions and WebAuthn API for biometric authentication. This method greatly enhances security and user experience by enabling pensioners to verify their identity using biometric information. The technology makes sure that only authorized people can access sensitive financial data and, after successful verification, enables pensioners to safely retrieve their pension amounts. By lowering fraud, eliminating unwanted access, and streamlining the authentication procedure, the suggested solution improves security

GC-MS analysis of yellow pigmented Macrococcus equipercicus isolated from alfalfa rhizosphere soil fields of Coimbatore

The rhizosphere of plant possesses important microflora, which secretes wide chemical compounds including secondary metabolites necessary for plant growth and development. The microbial flora of alfalfa plant rhizosphere soil region was explored for functional activity and we found upto ten different pigmented colonies. Due to good functional diversity, this yellow pigmented colony was taken for further studies. Thus, the culture was molecularly characterized and identified for potent bioactive components responsible for antimicrobial activity. The selected culture mass was cultured and secondary metabolites were produced and extracted using ethyl acetate and subjected to GC-MS analysis. The antimicrobial study revealed selective activity against Streptococcus pneumonia, and Proteus sp with zone of inhibition to be 18 and 20 mm respectively.  Molecular identification of the isolate by 16S rRNA sequencing showed the isolate as Macrococcus equipercicus with 100 % similarity. Based on GC-MS analysis report 25bioactive compounds were identified and 13-docosenamide, hexadecanoic acid esters and quercetin were found in ethyl acetate extract. Conclusion: Thus the yellow pigmented gram positive cocci M.equipercicus isolated from Medicago sativa possessed wide antibacterial activity due to presence of quercetin. Through the studies, we were able to identify potent antibacterial compound producing bacteria from M. sativa plant rhizosphere soil

Performance assessment on manufacturing of unfired bricks using industrial wastes

This paper presents eco-friendly unburnt bricks made up of fly ash, waste plastic powder, waste glass powder, lime, gypsum and crusher sand as alternatives to conventional burnt clay bricks for sustainable development. The research focuses on the maximum utilization of industrial waste in eco-friendly unburnt brick production. Materials are characterized according to their chemical and geotechnical properties. In this research, we use a milled waste glass powder of size less than 600μm and plastic powder obtained from plastic waste of size less than 600μm are added along with crushed sand, gypsum, lime and fly ash with various mix proportions concerning FaL-G mix concept. All the proportions were taken on a weight basis. Compressive strength, water absorption, and efflorescence are the key parameters chosen for comparing the innovative brick with conventional fly ash brick. There are five different mixes (Type A, B, C, D & E) are made in this research. The plastic and glass powders are replaced by crusher sand at the increased rate of 2% in every mix whereas 2%,4%,6%,8%, and 10%. It was found that the type B bricks have 17.63% strength was increased when compared to base mix. From the test results, type B bricks have enhanced mechanical performance when compared to all other mixes

A Novel Eye Cataract Diagnosis and Classification Using Deep Neural Network

AbstractEye Cataract is one of the main causes of blindness. It affects mostly people at the age of 60.In India, half of the aged people have cataract or have already treated by a surgery. The cataract identification is highly complicated in an early stage. To achieve this, experts chose the concepts of Deep Learning. In this paper we proposed Dense-Net and U-Net to detect and classify the eye cataract. Further, we took 200 samples of eye image to determine the presence of cataract with its severity. Finally, the comparison of Dense-Net and U-Net are tabulated interms of accuracy, sensitivity, and specificity. Hence, it proven that U- Net gives 10% accurate results than Dense Net.</jats:p

Design and Analysis of a Self-balancing Bicycle Model

Abstract This paper discusses the design and analysis of a self-balancing bicycle model. The objective was to develop an efficient design that can be fabricated in the future. The different methods of balancing a bicycle were studied to develop an optimal design. Solidworks 17 and Ansys 18 have been used for modeling, simulation, and analysis of the structure. The use of a Control Moment Gyroscope (CMG) to balance the bicycle model was studied and the results show that the effect of precession increases with an increase in rpm and the weight of the flywheel. Thus, a bicycle model actuated with CMG is far more stable and less prone to accidental tilts and toppling than one without. The studied data can be used for future research.</jats:p

A SURVEY ON AUTOMATIC ATTENDANCE SYSTEM ALONG WITH TEMPERATURE USING IOT

Automatic attendance methods are very helpful for students and workers in order to make use of their time more effectively. Maintaining attendance is the most troublesome assignment in different organizations. In recent days we have seen abrupt increment in the utilization of biometric technology in the fields of IT, education institute, transportation, etc. Internet of things is also blooming parallel. Automatic attendance system is an implementation of internet of things through Arduino ide, thingspeak finger print scanner R305 in order to reduce the time consumed by the traditional attendance method. There are various technologies like RFID, fingerprint and face recognition technologies are introduced in order to save time and reduce efforts. In this paper we are going to compare those technologies and understand which is best among them.</jats:p