Abstract:Blockchain is an expanding list of records, called blocks, that are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. By design, a blockchain is resistant to modification of the data.To counter these problems of traditional databases, blockchain technology can be used instead. Blockchain technology is a decentralised storage network, where each data of each user/ customer is stored in blocks within their host systems, but the difference here is that, each block is connected with each other over the decentralized network using the hash values. Credential Verification is performed to check if the customer is original. Usual applications of customer profiling are done in the bank and security sector, where every new customer or user must undergo a background validation before his/her data is stored on the database. In usual practice, all the data collected by the banks are stored in a single, centrally controlled database. There are numerous disadvantages of the current system of storage of data. It is easy for the hackers to break through the database security and get all the customer’s all details. Once the hacker or any unauthorized user accesses any one rows of the database, that person can access the entire database of sensitive information. In order to tackle this problem, one solution is to use decentralized blockchain technology replacing the old centrally owned database system. In this technology, every user’s data will be stored in the blockchain. How blockchain works is that each block contains some data and using a cryptographic technique called secured hash algorithm 256 (sha256), the hash value of length 256 bits is calculated for every block. This hash value of a particular block is stored inside the next block, creating the blockchain. The use of blockchain here provides immense security as if the data of the block is accessed without authorization, and if the data is changed, the entire hash value for the block will be changed, and when this happens that particular block will get disconnected from the chain, and hence give an error signal. The blocks are stored in a server, but no human intervention can actually access these blocks, but only smart contract code blocks can access the blocks. Once the data is stored on the blockchain, it cannot be modified without authorization from the user. To use blockchain with authentication, facial recognition and audio recognition are used as security measures. The facial recognition model was trained using SVM and KNN for comparison purpose. KNN approach gave an accuracy of 96 % whereas the SVM approach gave an accuracy of 98%. The threshold for distance calculation was 0.58, at which it gave the maximum accuracy. Also the blockchain creation was done using python and hash for every block was calculated using SHA-256. Audio recognition was performed using Multi-Layer Perceptron model. An accuracy of 88 percent was achieved.

Keywords:Blockchain, Python, Machine Learning, Neural Network

Abstract:The study set out to find out the effects of experimental work and get a better understanding of the increased thermal conductivity of PCM, in this case, Paraffin Wax (PW). Experimentally concluded that using Alumina and Copper nanoparticles produced the most excellent thermal conductivity and that Alumina and Copper's nanoparticles had the most significant impact on the conductivity of PCM. Furthermore, mass fractions of prepared PW-Alumina and PW-Copper composites via sonication were 5%, 10%, and 15%, respectively. PW and composite PCMs were examined with scanning electron microscopy for their morphology (SEM). Thermophysical property testing methods were employed as the standard testing procedures. Latent heat and specific heat were measured with a differential scanning calorimeter (DSC). Heat pipe apparatus was used to conductively test thermal conductivity (which was discovered using SEM). In this study, improved thermal conductivity and latent heat were observed in composite PCMs. The enhancement ratio was 10% to 80%, at 15% total weight. Three-stage was measured using a thermocouple and piezoelectric pressure transducer, while temperature data was measured using a temperature logger. Once the experiment reached steady-state temperature, it took 35 seconds to move on to the next stage

Keywords:The study set out to find out the effects of experimental work and get a better understanding of the increased thermal conductivity of PCM, in this case, Paraffin Wax (PW). Experimentally concluded that using Alumina and Copper nanoparticles produced the most excellent thermal conductivity and that Alumina and Copper's nanoparticles had the most significant impact on the conductivity of PCM. Furthermore, mass fractions of prepared PW-Alumina and PW-Copper composites via sonication were 5%, 10%, and 15%, respectively. PW and composite PCMs were examined with scanning electron microscopy for their morphology (SEM). Thermophysical property testing methods were employed as the standard testing procedures. Latent heat and specific heat were measured with a differential scanning calorimeter (DSC). Heat pipe apparatus was used to conductively test thermal conductivity (which was discovered using SEM). In this study, improved thermal conductivity and latent heat were observed in composite PCMs. The enhancement ratio was 10% to 80%, at 15% total weight. Three-stage was measured using a thermocouple and piezoelectric pressure transducer, while temperature data was measured using a temperature logger. Once the experiment reached steady-state temperature, it took 35 seconds to move on to the next stage

Abstract:WSNs (Wireless Sensor Networks) are distinguished by their elements' low energies & thus useful protocols for better optimization are often important. WSN has important applications, like structural health monitoring, aim military monitoring, habitat monitoring, etc. Due to the availability of cheaper and smarter sensors, but with battery support, they have advanced. Heterogeneous WSNs can enhance network existence and have improved networking and service efficiency than homogenous WSNs. The research, therefore, proposes grid clustering & fuzzy-model-based scheme to optimize network lifetime and energy- efficient data aggregation for distributed WSN. Grid clustering is utilized for cluster formation as well as cluster head (CH) selection. A Fuzzy Sugeno Model is often used for select parameter-based data aggregator nodes, like neighborhood overlap, distance & algebraic connectivity. Eventually, the mobile sink's dynamic relocation is carried out using the simulated annealing algorithm inside the grid-based clustered network region. The experimental findings showed that the proposed data aggregation scheme offers superior energy efficiency and network life performance in contrast with earlier schemes.

Keywords:Clustering, Heterogeneous WSN, Grid-based clustering, Fuzzy Sugeno, Simulated Annealing.

Abstract:High power flowing medium chemical laser have apparently achieved significant level power levels capable of target destruction. Few flowing medium lasers are still working towards these power levels and are at various stages of development. All Liquid medium lasers employing aprotic liquid, Lewis acid and rare earth ions termed as Liquid Laser (LL) are one amongst them. Development of these lasers essentially requires in depth understanding of multiple disciplines with overlapping influences. Safe operation of Liquid Laser is a critical concern, which needs to be sufficiently addressed prior to laser experimentation. This entails not only safe handling of subsystems, but also safety of human being/operator from any potential hazards posed by the chemicals employed in the laser system. The present paper discusses both manual and automatic safety schemes using suitable acquisition and control system for flowing medium Liquid laser.

Keywords:Liquid Laser, Flowing medium, Acquisition and Control, Laser Diodes, Hydrogen Chloride (HCl)

Abstract:Learning is a very integral part of smart education system even called to be as a smart-work method of educating. The contemporary challenge is to easily integrate the e-learning education system into a smart educational environment, considered that to be in rural areas with one of the most emerging technology called Internet of things (IoT). The e-learning services rely on a software system that allows access to all the materials that are related to the education and makes them electronically available to all students/teachers on the internet using whenever they need and at wherever they are being stated. The whole system of e-learning system is a critical part of the educational process as it reflects on the usage of the complex system too. In this paper, the design and implementation of e-learning systems through ToI (Things on Internet) stereopticon is described. The proposed ToI Stereopticon for Rural E-Learning Education System is designed using off-the-shelf and open-source software engineering model, programming tools, raspberry pi circuit as hardware and database models. The system is tested to prove the new design concepts and features. The method used in the back-end and front-end design and implementation allows flexible usage and integration of the whole system by the educational institutions in rural areas.

Keywords:Android Studio, Database, E-Learning, Education, Educator, Firebase, Internet of things (IoT), Institution, LED-Projector, Raspberry-Pi, Raspicast, System of System (SoS).