Ashish Sharma

GLA University · Department of Computer Engineering & Applications

In the current technological era, the reliability growth model depicts the failure in software that is employed for estimating the reliability of software. Conventional software reliability growth model (SRGMs) usually presume that faults in software are immediately corrected once a software fault is found and no new faults are introduced. This con...

An NFT (non-fungible token) marketplace is a platform where people can buy and sell one-of-a-kind digital items such as art work, music, and videos. These items are represented by NFTs, which are not exchangeable for other tokens or assets and are stored on a blockchain. The growing use of blockchain technology and the desire for individuals to own...

Heart disease is a serious terminal condition in most parts of the world. The acute lack of medical professionals, expertise, and technology to identify important signs. So a smart and efficient model and technology is required to lead early diagnosis of heart disease. The current study proposes a new experience-based method namely HSPUCD (Heart st...

An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consuming process. The development of machine learning (ML), as well as deep learning (DL), has set a new path in medical image diagnosis. In this study, we proposed a novel multi-scale feature fusion of a convolution neural network (CNN) and an improved canny...

To effectively treat cardiac patients before a heart attack occurs, a precise prognosis of heart disease is necessary. Recently, machine learning-based algorithms for predicting and diagnosing heart disease have been described. However, the lack of a sophisticated framework that can use several sources of data to forecast cardiac disease means that...

Skin burn identification is a very critical job to identify the burn location and its impact on the body. The current paper aims with the objective to identify the burn location and its impact so that the severity can be measured to provide effective treatment. The solution is derived using the Machine Learning model using CNN. The treatment can be...

Recently, cloud computing is an evolving research field deployed for computing by many researchers. The computing is offered as a service in cloud which is regarded as novel technology. In order to meet customer necessitates, various services are offered on the basis of customer dynamic request continuously in cloud computing, and it is the foremos...

Bone cancer is considered a serious health problem, and, in many cases, it causes patient death. The X-ray, MRI, or CT-scan image is used by doctors to identify bone cancer. The manual process is time-consuming and required expertise in that field. Therefore, it is necessary to develop an automated system to classify and identify the cancerous bone...

The field of medical science is going to take advantage of Machine learning. It has increased dramatically over the last decade. Nowadays, you can see other innovations used in medical sciences, such as machine learning and deep learning. They can help to diagnose the illness or cause. It can also aid in the healing process by keeping notes. At a s...

The use of information technology in the healthcare industry use so many types of electronic medium to maintain and process the information for all type of patients can be single or group of patients. Complexity heterogeneous behavior of data is also a challenge. Healthcare services dynamic demands the efficient incorporation of knowledge from vari...

Growing items industry plays a vital role in the economy of most of the countries. Growing item industries consists of live stocks like sheep, fishes, pigs, chickens etc. In this paper, we developed a mathematical model for growing items by considering various operational constraints. The aim of the present model is to optimize the net profit by op...

An EOQ model for perishable items is presented in this study. The deterioration rate is controlled by preservative technology. This technology only enhances the life of perishable items. So, retailers invested in this technology to get extra revenue. The Weibull deterioration rate is considered for the ramp type demand. Shortages consider partially...

Data mining, an excellent development technology for discovering and gathering essential knowledge from vast data collection that can help analyze and draw up trends for decision-making in the industry. Talking about the medical sphere, data mining can be used to uncover and withdraw useful data and trends that can be helpful in clinical diagnostic...

The era of technology is going to be changed so frequently, data size keeps on increasing exponentially, and as the data is increasing day by day, many new things are coming up in front that has to be considered in while getting information from the dataset. One of the most popular algorithms based on frequent itemsets is the Apriori algorithm. As...

The use of technology in the field of medical sciences has increased a lot since the last decade. Nowadays, you can see many technologies like computers and cameras used in medical sciences. They not only help in detecting the disease or the cause but also help in the curing process by maintaining records. The use of computers for image processing...

With the current advancement of technology, real-time software has been extensively utilized in several complex systems. The eternally rising complexity of software formulates it exceptionally hard to maintain the reliability of software and has strained extraordinary awareness in software industries. Nearly all reliability-based software reliabili...

In real life, many products (e.g. Fruits, vegetables, and fashionable items) degrade naturally following a trapezoidal type demand rate. Inventory, Procurement, pricing and replenishment decision are imperative in case of deteriorating items. In the light of these aspects, we developed a price and time-dependent inventory model with trapezoidal dem...

Deterioration rate may be constant or varies with time. In real life time dependent deterioration is observed in many products like fruits, bakery products, milk products etc. Generally deterioration rate increases as the time passes. In this paper we present an inventory model for the trapezoidal type demand function and time dependent deteriorati...

The performance of students was bad instead of the extreme effect of its teachers in a Portuguese school. The core problem is there low performance in two of the main subjects i.e., Portuguese language and mathematics. Now as the technology has improved in years so several machine learning techniques can be used based to analyze the performance. Th...

Burn is one of the serious public health problems. Usually, burn diagnoses are based on expert medical and clinical experience and it is necessary to have a medical or clinical expert to conduct an examination in restorative clinics or at emergency rooms in hospitals. But sometimes a patient may have a burn where there is no specialized facility av...

In the real world there are so many businesses for which the major concern is the location of facility/store so that they can satisfy the demand in an efficient manner. Therefore the companies perform extensive survey for the finding the right location before the setup of facility/store. These surveys generate the probabilistic data. In the light o...

The main objective of facility location problem is the utilization of the facility by maximum number of possible customers so that the profit is maximized. For instance, in some services like wireless sensor networks, Wi-Fi, repeaters, etc., where the service area is limited, some specific equipment is installed in such a way that it could be used...

Solutions for facility location problems are numerous. As the problem is NP hard, continuous efforts have been made to find more efficient techniques. The nature of the facility adds to its variety. A popular approach has been based on geometric solutions. Other methods have also been tried; one of them is based on density applied for large databas...

Many real time applications, they are generated continues flow of data streams have became more popular now a days. Therefore many researches attracted clustering data streams. Most of data stream clustering algorithms based on distance function which find out clusters with spiracle of shape clusters and unable to deal noisy data. Therefore density...

Vertex cover is one of the best known NP-Hard optimization problem, that plays central role in computer science and it has real world application in the areas of circuit design, computational biochemistry, telecommunications, and network flow. This paper presents a new heuristic solution for vertex cover problem. This technique is computationally e...

DBSCAN is a pioneer density based clustering algorithm. It can find out the clusters of different shapes and sizes from the large amount of data which is containing noise and outliers. But the clusters detected by it contain large amount of density variation within them. It can not handle the local density variation that exists within the cluster....