Electronic medical records concepts and data management

Healthcare information (Clinical Data) is associated with every individual, young or old, rich or poor, belonging to any country. Clinical data is very extensive. Everyday some new diseases and new symptoms are being seen and the human race is struggling to find cures. There are many diseases whose diagnosis, symptoms, and possible treatment are known but unfortunately that rare knowledge is not available to every individual in the world. This initiates all the vision behind presenting a paper on EMR/ EHR and its Data Management. The thesis reviews the concept of EMR/ EHR thus explaining its concepts, importance, market need etc. Thesis will also explain privacy and security related to clinical data in electronic format which is a very important as any electronic data is prone to hacks and data loss. To manage and utilize such amount of data, there is need of extensive data management and so the thesis explains the concepts of Datawarehouse, its importance, ETL, Schemas etc. As part of explaining these concepts a mini EMR/EHR Datawarehouse is designed which explains various subject areas possible in any EMR Datawarehouse. Last but not the least, the thesis comments on the Future of EMR/ EHR and the World Vision on this revolutionary change

Classification of Darknet Traffic by Application Type

The darknet is frequently exploited for illegal purposes and activities, which makes darknet traffic detection an important security topic. Previous research has focused on various classification techniques for darknet traffic using machine learning and deep learning. We extend previous work by considering the effectiveness of a wide range of machine learning and deep learning technique for the classification of darknet traffic by application type. We consider the CICDarknet2020 dataset, which has been used in many previous studies, thus enabling a direct comparison of our results to previous work. We find that XGBoost performs the best among the classifiers that we have tested

BitFed, A Centralized Cryptocurrency with Distributed Miners

Bitcoin is a decentralized peer-to-peer electronic currency wherein all the payments are sent from one transactor to another directly [1]. Financial institutions are not present in the protocol, hence, there are lower processing fees. The distributed nature provides resilience to Bitcoin transactions, and it operates on mathematical principles and cryptographic proofs. As per Bitcoin generation algorithm, the number of bitcoins in existence will never surpass 21 million, which will lead to deflation and encourage hoarding. In this project, we have implemented a Bitcoin-like currency in order to mitigate the issue of deflation [7]. The idea for our protocol is based on the US Federal reserve, which is the gatekeeper of the US economy and promotes the stability of prices by preserving the purchasing power of dollar over a long period of time. Our approach to fix the Bitcoin deflation issue is by creating BitFed, a centralized authority that decides the rate of issuance of bitcoins each day while otherwise maintaining the decentralized nature of protocol. Specifically, the BitFed plays no role in verifying transactions. In order to prove that this approach is viable, we have developed a simulator in Java that emulates the Bitcoin protocol with the BitFed and tested it by introducing cheaters in the network. The system has no forks when majority of the miners are good (more than 51 percent). After this we see several forks in the system, since the network is controlled by cheaters

Assessing the physiological and pathological functions of tissue Transglutaminase using FRET analysis

Tissue Transglutaminase (TG2) is a cross-linking enzyme that links proteins by the formation of covalent bonds and confers resistance to proteolytic degradation. TG2 acts as a cell adhesion protein by binding to matrix fibronectin, cell surface heparan sulphates and integrins. TG2 has been implicated in a variety of diseases such as neurodegenerative disease, fibrosis and cancer. However, little is known about the mechanisms involved in its secretion, intracellular or extracellular activation or how these are regulated. The activity of TG2 is tightly controlled by GTP binding and calcium is required for its activation. TG2 assumes two strikingly different conformations, a catalytically inactive compact one in the presence of GTP and an active extended one in the presence of Ca2+. This conformation change affects the functions of TG2 including its transamidating activity, its affinities and juxtaposition of binding sites for fibronectin, heparan sulphates and integrins. To study this, a FRET (Förster Resonance energy Transfer) sensor was constructed using the fluorescent proteins CFP and YFP fused to the N and C terminus of TG2, respectively. The FRET sensor has demonstrated different fluorescent characteristics depending on the conformation of TG2 and was used to monitor the conformational change that is induced by calcium or GTP binding

A Novel Way of Assessing Software Bug Severity Using Dictionary of Critical Terms

AbstractDue to increase in demands of software and decreased delivery span of software, assuring the quality of software is becoming a challenge. However, no software can claim to be error free due to the complexity of software and inadequate testing. There is a well-known principle of testing, which states that exhaustive testing is impossible. Hence, maintenance activities are required to ensure smooth functioning of the software. Many open source software provides bug tracking systems to aid corrective maintenance task. These bug tracking systems allow users to report the bugs that are encountered while operating the software. However, in software maintenance, severity prediction has gained much attention recently. Bugs having higher severity should be fixed prior to the bugs having lesser severity. Triager analyzes the bug reports and assesses the severity based upon his/her knowledge and experience. But due to the presence of a large number of bug reports, it becomes a tedious job to manually assign severity. Thus, there is growing need for making the whole process of severity prediction automatic. The paper presents an approach of creating a dictionary of critical terms specifying severity using two different feature selection methods, namely- info gain and Chi square and classification of bug reports are performed using Naïve Bayes Multinomial (NBM) and K-nearest neighbor (KNN) algorithms

VIRTUAL REALITY AND BLOGGING IN TOURISM: APPROACHED TOWARDS CREATING BETTER TOURIST EXPERIENCE

Virtual reality in tourism (virtual tourism) and blogging are highly valuable for visitors and travellers since they allow them to undertake a scouting trip before embarking on their adventure, avoid being hassled and avoid crowds while learning more about the location they are visiting or have already been. This paper provides an overview and analysis of the relationship between virtual tourism, blogging, and making the image of tourist destinations through promotion virtually and via blogs. According to the study\u27s findings, virtual tourism cannot replace the actual experience, but it can assist in recreating it if the user has previously visited the location, bringing out new nuances in their experience, or giving them a taste of the destination ahead of time if they have not yet visited. Also, when it comes to digital marketing for tourism, blogging is the frosting on the cake because it is utilized for promotion and communication throughout the pre-travel period, focusing on behavioural factors

Vitamin B12 Production by Lactobacillus Species Isolated from Milk Products

An investigation entitled “Studies on production of Vitamin B12 by Lactobacillus species isolated from milk products” was conducted in the Division of Microbiology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, to study the capability of mutants generated out of UV and EMS mutagens of native Lactobacillus isolates, for Vitamin B12 production potential.  In this study 8 isolates of Lactobacillus were isolated from curd and kaladi. Screening and Quantification of isolates was done on Vitamin B12 assay medium. The Vitamin B12 production by Lb-7 was 0.39 mg/g DCW. Lb-7, the fastest growing strain was selected for strain improvement, that was done by UV and EMS mutagens. Based on performance during screening, UV mutant was taken up for fermentation optimisation studies. The Vitamin B12 production by UV mutant was 0.63mg/g DCW. Three fermentation parameters i.e temperature, pH and inoculum load were optimized for mutant to enhance Vitamin B12 production. The Vitamin B12 production at 25°C was 2.05 mg/g DCW, 5.5 pH was 1.55mg/g DCW and 108 inoculum load was 1.53mg/g DCW. Best results were recorded at 25°C, 5.5 pH and 108 cfu/ml of microbial load. An increase in temperature, pH and inoculum load caused decrease in Vitamin B12 production due to death of cells