Role of Neural Network in Mobile Ad Hoc Networks for Mobility Prediction

The MANETs differ from traditional networks in a lot of aspects, such as high channel error rates, unusual channel features, frequent link breaks, and intense link layer contentions. These characteristics significantly reduce network connectivity, which affects overall network latency, network overhead, network throughput (i.e. the amount of data successfully transferred via a MANETs in a predetermined amount of time), and packet delivery ratio (PDR). For effective network resources preparation and organization in MANETs, the mobility forecast of MN and units is essential. This effectiveness would allow for better planning and higher overall quality - of - service, including reliable facility availability and efficient management of energy. In this research, we suggest to use ELMs, which are renowned for their ability to approximate anything, to model and forecast the mobility of each node in a MANET. Mobility-aware topology control methods and location-assisted routing both leverage mobility prediction in MANETs. It is assumed that each MN taking part in these protocols is aware of its current mobility data, including location, velocity, and movements direction angle. This approach predicts both the locations of future nodes and the distances between subsequent nodes. The interaction or relationship between the Cartesian longitude and latitude of the erratic nodes is better captured by ELMs than by multilayer perceptron’s, resulting in mobility prediction that is based on several conventional mobility models that is more precise and realistic

Role of Deep Learning in Mobile Ad-hoc Networks

The portable capability of MANETs has specially delighted in an unexpected expansion. A massive need for dynamic ad-hoc basis networking continues to be created by advancements in hardware design, high-speed growth in the wireless network communications infrastructure, and increased user requirements for node mobility and regional delivery processes. There are several challenging issues in mobile ad-hoc networks, such as machine learning method cannot analyze features like node mobility, channel variation, channel interference because of the absence of deep neural layers. Due to decentralized nature of mobile ad hoc networks, its necessitate to concentrate over some extremely serious issues like stability, scalability, routing based problems such as network congestion, optimal path selection, etc. and security

MATLAB based Brain Tumour Extraction using Artificial Neural Network

Brain tumour is the major cause of mortality among children and adults. The chance of survival can be greater when the tumour is detected correctly at its early stage. This paper presents a neural network techniques for the classification of magnetic resonance brain image. The proposed technique consists of three stages, features extraction from gray scale MR Image using gray level co-occurrence matrix, MR image segmentation using k-mean clustering method and classification of MR Image into normal and abnormal (tumourous) image using feed-forward neural network. This technique have been developed on MATLAB version 7.5.0 platform

An Efficient and Reliable Data Transmission Service using Network Coding Algorithms in Peer-to-Peer Network

Network coding is a progressive enhancement in natural network routing that increases throughput and reliability for unicast, multicast, and even broadcast transmissions. P2P networks are ideal for implementing network coding algorithms for two reasons: I. A P2P network's topology isn't predetermined. As a result, designing a topology that is compatible with the network coding algorithm is much easier. II. Every peer is an end host in this network.  As a result, instead of saving and sending the message, complex network coding operations, such as encoding and decoding, are now easier to perform. The objective of this work is to use the best features of network coding algorithms and properly apply them to P2P networks to create an efficient and reliable data transmission service. The goal of the network coding algorithm is to make better use of network resources and thus increase P2P network capacity. An encoding algorithm that enables an intermediate peer to produce output messages by encoding (that is, computing a function of the data it receives. The decoder's role is to obtain enough encoded packets so that the original information can be recovered. This research work has measured an amount of hypothetical and applied consequences in which the network coding procedure or a variation of it is used to improve performance parameters such as throughput and reliability in P2P network data transmission based on network coding. The comparison of data transmission between network routing and network coding algorithms was the main focus of this paper.  According to our simulations, the new network coding systems can reach 15% to 20% upper throughput than supplementary P2P network routing systems

A Survey on Human Face Recognition Invariant to Illumination”,

ABSTRACT Human face recognition is one of the research areas in the current era of the research. It is one the widely used biometric technique for identification and verification of the human face. There are many challenges to face recognition which degrade the performance of the algorithm. The illumination variation problem is one of the well-known problems in face recognition in uncontrolled environment. In this paper an extensive and up-to-date survey of the existing techniques to address this problem is presented. Different authors have given so many techniques for illumination reduction from the face image but still some combined survey is missing so we have tried to fill that gaps in this paper. We have collected various preprocessing techniques suggested by different authors and shown their results in a tabular form. After preprocessing we can use any of the recognition method for face recognition. There are so many online face databases available so we can use any of them

Prescription audit of outpatients in tertiary care government hospital

Background: Prescription audit is a tool as well as a technique by its application,all professionals will improve the quality of prescribing drugs. Standards of medical treatment can be assessed by prescription audit. It is based on documented evidences to support diagnosis, treatment and justified utilization of hospital facilities. Prescription audit is a quality improvement process that seeks to improve patient care. In this background the present study was conducted. The objectives of the study were to know the frequently prescribed drugs in OPD, number of the drugs used per prescription and to find out the rationality.Methods: Study was conducted at Sri Chamarajendra Hospital, HIMS, Hassan in OPD of General Medicine.1000 prescriptions were collected and noted down the frequently used medication, number of drugs prescribed and their type of formulations for the particular diagnosis.Results: From the study it is noted that 1910 drugs out of 1000 prescriptions were prescribed which is approximately 1.91 drugs per prescription about 55% of the prescriptions contained single drug. Very few received 4-5 drugs (7%). Almost all the drugs in prescriptions were in Generic names. Around 95% of prescriptions doses were mentioned in mg, ml etc. The most commonly prescribed drugs in order are Antibiotics, antidiabetics antihypertensives, bronchodilators, steroids antiemetics and ORS were prescribed.Conclusions: Polypharmacy was not found in our prescriptions which indicates our prescriptions improved the patient conditions. This type of study will ensure to know the ‘P’ drug development and select the essential medicine list for various levels of health care

Web3 Chain Authentication and Authorization Security Standard (CAA)

Web3 is the next evolution of the internet, which uses blockchains, cryptocurrencies, and NFTs to return ownership and authority to the consumers. The potential of Web3 is highlighted by the creation of decentralized applications (dApps), which are more secure, transparent, and tamper-proof than their centralized counterparts, allowing for new business models that were previously impossible on the traditional internet.Web3 also focuses on user privacy, where users have more control over their personal data and can choose to share only what they want. The emergence of Web3 represents an exciting new frontier in blockchain technology, and its focus on decentralization, user privacy, and trustless systems has the potential to transform the way we interact with the internet.Web3 authentication is required for enhanced security, increased privacy, and simplified user interface. Traditional login procedures and an authorization flow using web3 authentication work together seamlessly. However, there are several challenges associated with Web3, including scalability and regulatory issues. Chain Authentication and Authorization (CAA) is a multi-layer security mechanism that allows users to choose the security layer that suits them, just like a heavy iron chain, where the user and CAA developers act as blacksmith and form their security protocol that suits them. CAA is a solution to the challenges associated with Web3 authentication and authorization, and it focuses on creating a secure and decentralized authentication and authorization system that is scalable, flexible, and user-friendly

Factors associated with polypharmacy in geriatrics

Background: In population with advancing age, the prevalence of medical co-morbid conditions is high and they are prone for complications. Hence the apprehension of using multiple drugs is more. Using more than 5 drugs per day is referred to as Polyphrmacy. Sometimes treatment causes more harm than the disease proper. So, optimizing drug therapy in these aging population is a challenging task for physician. Polypharmacy can also lead to increase in drug interactions, adverse drug reactions and medication errors. Hence the present study was taken up to study drug utilization pattern and factors leading to polypharmacy in geriatrics. The objectives of the study were to study the number and type of drug use and to know the different factors leading to polypharmacy.Methods: Cross sectional study was carried out among 60 geriatric persons ≥60 years of age present in old age home in Hassan. The study was done after taking the consent. All the prescriptions and medications being used along with history were collected and documented. The total number of drugs being used and names of all drugs were noted down and analysed. Results were analysed using descriptive statistics.Results: Among 60 geriatrics 38% males and 62% females age ranges from 60- 87 years. Average number of drugs used per day per person is 5.03 (Males 6.2 and Females 3.8) in 58.03% of individuals. Most common group of drug used is Gastro intestinal system (78.3%) and most common drug being used is Tab. Ranitidine 140mg (50%). Next group is NSAIDs (68.33%) and most common drug being used is Tab. Diclofenac (46.7%). Antihypertensive drugs were prescribed in 53.3% of geriatrics, most commonly prescribed drug is Tab. Amlodipine (5mg). Self medication was found in 100%. Most common group of drugs used as self medication are GIT drugs, supplements and NSAIDs. In supplements (used in 63.3%), Cap. B Complex is widely used (50%).Conclusions: Polypharmacy was found in 58.3% of individuals and highest in age group between 71-75 years and self medication was found to be the most important factor leading to polypharmacy. To counteract the problems associated with Polypharmacy, interventional studies are needed to improve the quality of life of geriatrics patients

A questionnaire based study on the knowledge, attitude, practice of staff nurses about pharmacovigilance in a tertiary care hospital

Background: Adverse drug reactions (ADR) - one of the global problems of major concern leading to morbidity and mortality. Spontaneous reporting of ADR is the cornerstone of Pharmacovigilance (PV) programme and it is important to reduce the risk of drug related harm to the patient. The active participation of healthcare professionals (Doctors, Nurses, Pharmacist) play a major role in the success of Pharmacovigilance. The objective of the study was to assess the knowledge, attitude, practice of Staff Nurses about Pharmacovigilance in a tertiary care hospital.Methods: A Cross sectional, Observational questionnaire based study was carried out using a pre designed KAP questionnaire. Study included 100 staff nurses who were working in Hassan institute of medical sciences (HIMS). The results were analyzed using descriptive statisticsResults: In our study 65% participants knows the correct definition and 48.8% knows the important purpose of Pharmacovigilance and 77.5% aware of existence of ADR reporting system in India. There was huge gap between ADR experienced (53.8%) and ADR reported (21.3%). The determinants of under reporting from our study include Lack of time / overburdened (33.7%) and lack of knowledge about ADR (31.25%).Conclusions: This study showed that majority of participants understand the need for reporting of ADR. In spite of that the reporting rate of ADRs by them is very low. Hence, there is a need to create awareness about the importance of reporting ADR by conducting many Pharmacovigilance programme