Blockchain and its Application

In this research investigation into Blockchain Technology, its current use and other pos-sible implementation of this protocol are explored. Blockchain offers opportunities for developing advanced digital services. While current research on this becoming the most important issue which must be well addressed. As part of the fourth industrial revolution since the invention of the steam engine, electricity, information technology, Blockchain Technology has been applied in many areas such as finance, judiciary, and commerce. In this current paper, we focused on its potential Voting Application and explore how Blockchain Technology can be used to solve Health Care Issues, Land Registry, Any Fi-nancial Sector, etc. Some innovative applications of using blockchain technology for different sectors we also discussed

Modelling an Aircraft Landing System in Event-B (Full Report)

The failure of hardware or software in a critical system can lead to loss of lives. The design errors can be main source of the failures that can be introduced during system development process. Formal techniques are an alternative approach to verify the correctness of critical systems, overcoming limitations of the traditional validation techniques such as simulation and testing. The increasing complexity and failure rate brings new challenges in the area of verification and validation of avionic systems. Since the reliability of the software cannot be quantified, the \textit{correct by construction} approach can implement a reliable system. Refinement plays a major role to build a large system incrementally from an abstract specification to a concrete system. This paper contributes as a stepwise formal development of the landing system of an aircraft. The formal models include the complex behaviour, temporal behaviour and sequence of operations of the landing gear system. The models are formalized in Event-B modelling language, which supports stepwise refinement. This case study is considered as a benchmark for techniques and tools dedicated to the verification of behavioural properties of systems. The report is the full version of a paper published for the ABZ 2014 Case Study. i

Two-warehouse Inventory Model with Multivariate Demand and K-release Rule

AbstractIn this paper, we’ve projected a two-warehouse inventory model for deteriorating things beneath the impact of inflation and continuance of cash, wherever demand follows a rare combination of the linear time variable and on-hand inventory level. In one in the entire warehouse (OW), time-varying linear deterioration was thought-about and within the different (RW) weibull distributed deterioration was studied. Here, shortages were allowed and part backlogged. The stock is transferred from the RW to the OW following a bulk unharness rule. The target here is to seek out the optimum amount to that ought to be ordered and also the optimum variety of cycles during which the number from RW should be transferred to OW to maximize world wide web profit per unit time. The model has additionally been exemplified with the many numerical examples. The results have additionally been understood diagrammatically

Investigation of Ethyl Acetate Extract/Fractions of Acacia nilotica willd. Ex Del as Potent Antioxidant

This study was planned to evaluate the antioxidant activity of ethyl acetate extract/fractions of Acacia nilotica Willd. Ex. Del extracted with different solvents of increasing and decreasing order of solvent polarity. The antioxidative activities, including the 1’-1’ diphenylpicryl-hydrazyl (DPPH) radical-scavenging effects, hydroxyl radical scavenging potential, chelating ability, reducing power and lipid peroxidation inhibition in rat tissue homogenate were studied in vitro. It was found that the antioxidative effect provided by extract/fractions was strongly concentration dependent and increased on fractionating the extract into water and ethyl acetate fractions. In general, the antioxidative activity increased with increasing extract/fractions concentration to a certain extent, and then leveled off with further increase in antioxidant activity. From a comparison of the antioxidant potential and IC 50 values for different antioxidative reactions, it seemed that extract/fractions were more effective in scavenging DPPH and hydroxyl radicals than reducing, chelating heavy metals and lipid peroxidation inhibitory potential

Stem Cell Antigen CD34 In Native And Engineered Form Alter Its Binding Ability To Stromal Cells And Ligands: A Classical Example Of Clinical Benefits Of Therapeutic Genetic Engineering Of Stem Cells In Transplantation

CD34 is a highly glycosylated surface-expressed sialomucin and, because it is present on hematopoietic stem cells (HSCs), has demonstrated immense clinical utility in their enumeration in aphaeresis products, immunoaffinity purification for transplantation, and disease monitoring. The success of CD34 based reagents in identifying hematopoietic progenitors led to the assumption that CD34 is expressed on cells with regenerative potential and is sufficient for hematopoietic reconstitution in marrow-ablated recipients. However, its role has not been identified in substantial detail. 

With the advent of the fact that CD34 binds adapter protein like CRK-L in cytosol and CD34 knock out studies identified a a signaling role, CD34 antigen has been proposed to play a signaling function. Since it is a sialomucin, a member of the group adhesion molecules, we attempted to identify a role by over-expreesing its gene in cell lines. We report here that CD34 and engineered forms (Ser306 & Tyr318) significantly regulates adhesion to stromal cells, like mesenchymal stem cells and bone marrow ligands. These enhance binding of cells overexpressing CD34 by upregulating integrins and we therefore propose that such cells may effectively potentiate the success of transplantation through greater homing if they are used for transfusion

Convolutional Neural Networks Exploiting Attributes of Biological Neurons

In this era of artificial intelligence, deep neural networks like Convolutional Neural Networks (CNNs) have emerged as front-runners, often surpassing human capabilities. These deep networks are often perceived as the panacea for all challenges. Unfortunately, a common downside of these networks is their ''black-box'' character, which does not necessarily mirror the operation of biological neural systems. Some even have millions/billions of learnable (tunable) parameters, and their training demands extensive data and time. Here, we integrate the principles of biological neurons in certain layer(s) of CNNs. Specifically, we explore the use of neuro-science-inspired computational models of the Lateral Geniculate Nucleus (LGN) and simple cells of the primary visual cortex. By leveraging such models, we aim to extract image features to use as input to CNNs, hoping to enhance training efficiency and achieve better accuracy. We aspire to enable shallow networks with a Push-Pull Combination of Receptive Fields (PP-CORF) model of simple cells as the foundation layer of CNNs to enhance their learning process and performance. To achieve this, we propose a two-tower CNN, one shallow tower and the other as ResNet 18. Rather than extracting the features blindly, it seeks to mimic how the brain perceives and extracts features. The proposed system exhibits a noticeable improvement in the performance (on an average of $5\%-10\%$) on CIFAR-10, CIFAR-100, and ImageNet-100 datasets compared to ResNet-18. We also check the efficiency of only the Push-Pull tower of the network.Comment: 20 pages, 6 figure

AUTOMATED TIMETABLE GENERATOR USING PARTICLE SWARM OPTIMIZATION

The timetabling problem at universities is an NP - hard problem un der multiple constraints and limited resources. Thus a technique that can handle constraints is needed to optimize the problem. Thi s pape r focuses on Particle Swarm Optimization (PSO) for findin g optimal solution s t o th e proble m of course Timetabling a t a Punjabi U niversity Patiala . PSO is a promising scheme for solving NP - hard problems due to its fast convergence and fewer parameter settings . There are tw o objective s i n this . First provide a detaile d introductio n t o the topic of timetabling, Particle Swa rm Optimization thei r metho d an d thei r variations . Th e se c ond objective i s t o appl y the m t o th e proble m o f Course Timetabling . The proposed algorithm is tested using the timetabling data from Department of Computer Science, Punjabi University , Patiala

Developmental Performance Ranking of SAARC Nations: An Application of TOPSIS Method of Multi-Criteria Decision Making

To be developed, nations are trying to cope up with the fast-changing economy and technology of the world. But the development of a nation does not depend only on these two factors rather several other indicators are essential to a country’s development. The present study deals with the progress of the SAARC (South Asian Association for Regional Cooperation) countries towards development through social, economic and environmental stability. This study aims at analyzing the comparative developmental performance of the SAARC nations in accordance with the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). In this study, we have prioritized the 8 SAARC nations based on 4 indicators (economic, demographic, health and environment indicators) and 20 variables using the multi-criteria decision-making method (MCDM). The result showed that Sri Lanka has prioritized 1st followed by Bhutan. India has been ranked 4th and Afghanistan was least prioritized

Developmental Performance Ranking of SAARC Nations: An Application of TOPSIS Method of Multi-Criteria Decision Making

To be developed, nations are trying to cope up with the fast-changing economy and technology of the world. But the development of a nation does not depend only on these two factors rather several other indicators are essential to a country’s development. The present study deals with the progress of the SAARC (South Asian Association for Regional Cooperation) countries towards development through social, economic and environmental stability. This study aims at analyzing the comparative developmental performance of the SAARC nations in accordance with the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs). In this study, we have prioritized the 8 SAARC nations based on 4 indicators (economic, demographic, health and environment indicators) and 20 variables using the multi-criteria decision-making method (MCDM). The result showed that Sri Lanka has prioritized 1st followed by Bhutan. India has been ranked 4th and Afghanistan was least prioritized