Diabetes prediction in healthcare systems using machine learning algorithms on Hadoop cluster
Health care systems are merely designed to meet the needs of increasing population globally. People around the globe are affected with different types of deadliest diseases. Among the different types of commonly existing diseases, diabetes is a ...
SORD: a new strategy of online replica deduplication in Cloud-P2P
In online Cloud-P2P system, more replicas can lead to lower access delay but more maintenance overhead and vice versa. The traditional strategies of online replica deduplication usually utilize the method of dynamic threshold to delete the redundant ...
A hybrid technique for gender classification with SLBP and HOG features
Gender classification from facial images plays a significant role in biometric technology viz. gender medicine, surveillance, electronic banking system and human computer interaction. However, it has many challenges due to variations of pose, ...
Improved security and routing path learning in MANETs using Beer–Quiche game theoritical model in cloud computing
In anAdhoc Cloud as a Service (Adhoc Cloud is used over MANETs), the attackers try to interrupt the data packets being broadcasted in the network between the nodes, which travels from source to destination. To solve this problem, Beer–Quiche ...
RFTL: improving performance of selective caching-based page-level FTL through replication
The internal nature of flash memory technology, makes its performance highly dependent on workload characteristics causing poor performance on random writes. To solve this, Demand-based Flash Translation Layer (DFTL) which selectively caches page-level ...
Visual and textual features based email spam classification using S-Cuckoo search and hybrid kernel support vector machine
Spam mail classification has been playing a vital role in recent days due to the uncontrollable growth happening in the electronic media. Literature presents several algorithms for email spam classification based on classification methods. In this ...
A survey of privacy preserving schemes in IoE enabled Smart Grid Advanced Metering Infrastructure
Integration of renewable resources and increased growth in energy consumption has created new challenges for the traditional electrical network. To adhere to these challenges, Internet of Everything (IoE) has transformed the existing power grid into a ...
An efficient categorization of liver cirrhosis using convolution neural networks for health informatics
Accurate categorization of cirrhosis liver image in ultrasound modality is of great importance in medical diagnosis and treatment. Health informatics is important as it provides quick predictions on diseases based on nearness of symptoms. ...
Upkeeping secrecy in information extraction using ‘k’ division graph based postulates
The prevailing mechanisms for extracting useful information might offer enhanced results in extraction of useful data for creating classification policies. The goal is to administer the disputes prevailing within the categorization for supervised ...
Revamping data access privacy preservation method against inside attacks in wireless sensor networks
Despite more privacy preservation techniques available in wireless sensor networks (WSN), no modest technique dealt with compromised nodes. Among several applications, healthcare applications fit into WSNs environment for patient monitoring from ...
Cloud and IoT-based emerging services systems
The emerging services and analytics advocate the service delivery in a polymorphic view that successfully serves a variety of audience. The amalgamation of numerous modern technologies such as cloud computing, Internet of Things (IoT) and Big Data is ...
Software defect prediction techniques using metrics based on neural network classifier
Software industries strive for software quality improvement by consistent bug prediction, bug removal and prediction of fault-prone module. This area has attracted researchers due to its significant involvement in software industries. Various ...
Instance selection and feature extraction using cuttlefish optimization algorithm and principal component analysis using decision tree
Instance selection and feature extraction is one of the most important task in data mining, due to the huge amount of data is constantly being produced in many fields. If the dataset is very large means most of the existing machine learning ...
A design and development of an intelligent jammer and jamming detection methodologies using machine learning approach
Nowadays, the utilization of mobile phones has increased rapidly. Due to this evolution schools, mosques, prisons, etc., require silence and security. This is achieved by using the mobile phone jammers. An intelligent mobile jammer is designed for ...
Multi-biometric authentication system using finger vein and iris in cloud computing
Multi biometric system can be used in cloud computing to achieve higher data security. Biometric authentication refers to automated methods used to identify a person by the features such as face, iris, vein, finger print, palm print etc. In this ...
Internet of Things: information security challenges and solutions
Keeping up with the burgeoning Internet of Things (IoT) requires staying up to date on the latest network attack trends in dynamic and complicated cyberspace, and take them into account while developing holistic information security (IS) approaches for ...
Association rules and deep learning for cryptographic algorithm in privacy preserving data mining
Security in database is important as it contains sensitized information. Data mining provides mechanisms for intermediate representation of data. Privacy preservation is vital due to the security aspects. Privacy denotes mechanisms for allowing ...
Towards optimal scheduling policy for heterogeneous memory architecture in many-core system
With the advent of Intels second-generation many-core processor (Knights Landing: KNL), high-bandwidth memory (HBM) with potentially five times more bandwidth than existing dynamic random-access memory has become available as a valuable computing ...
Prediction of software fault-prone classes using an unsupervised hybrid SOM algorithm
In software engineering fault proneness prediction is one of the important fields for quality measurement using multiple code metrics. The metrics thresholds are very practical in measuring the code quality for fault proneness prediction. It helps ...
Towards Sustainable High-Performance Transaction Processing in Cloud-based DBMS
Cloud-based databases often decouple database instances from physical storage to provide reliability and high availability to users. This design can robustly handle a single point of failure but needs substantial effort to attain good performance. In ...
Handling high web access utility mining using intelligent hybrid hill climbing algorithm based tree construction
With an eye on locating the sequences from web data the most talented solution web usage mining is elegantly employed. In this regard, the modern technique is plagued by several constraints like the forward reference of web access sequence, making ...
A simulation provenance data management system for efficient job execution on an online computational science engineering platform
In the past few years an online simulation service platform (named EDISON) has been applauded by several computational science and engineering communities in several countries. Though armed with multiple computing clusters and high-end storage resources,...
Optimized neural network for spectrum prediction using genetic algorithm in cognitive radio networks
Cognitive radio based dynamic spectrum access mechanism is a revolution in wireless communication which alleviates the spectrum utilization problem. Here cognitive users uses spectrum sensing techniques, to sense the bands before transmitting on ...
OMBM: optimized memory bandwidth management for ensuring QoS and high server utilization
Latency-critical workloads such as web search engines, social networks and finance market applications are sensitive to tail latencies for meeting service level objectives (SLOs). Since unexpected tail latencies are caused by sharing hardware resources ...
Mitigating combinatorial attacks in node to node communication using high level security measures based on analysis of efficiency factor through regression and deviation
In this contemporary world, mobile ad-hoc networks emerges as an imperative field in computer science. An application of MANET is vehicular networks (VANET) which gives its maximum coverage towards real time actions like vehicular traffic control ...
A resource recommendation method based on dynamic cluster analysis of application characteristics
With the development of cloud computing technology, many scientists want to perform their experiments in cloud environments. Because of the pay-per-use method, it is cost-optimal for scientists to only pay for the cloud services needed for their ...
An effective pose invariant face recognition system with the aid of ABC optimized ANFIS
Utilizing a stocked up database of faces, Face recognition recognizes or verifies one or else more individuals in the specified still or else video images of a scene. This is owing to its abundant vital applications in security, human–computer ...
On the effect of using rCUDA to provide CUDA acceleration to Xen virtual machines
Nowadays, many data centers use virtual machines (VMs) in order to achieve a more efficient use of hardware resources. The use of VMs provides a reduction in equipment and maintenance expenses as well as a lower electricity consumption. Nevertheless, ...
Performance evaluation of support vector machine classification approaches in data mining
At present, knowledge extraction from the given data set plays a significant role in all the fields in our society. Feature selection process used to choose a few relevant features to achieve better classification performance. The existing feature ...
Cluster based effective prediction approach for improving the curable rate of lymphatic filariasis affected patients
The objective for global elimination of human lymphatic filariasis is by 2020. Public health department major problem is to predict the severity of the lymphatic filariasis disease grade levels and its control measures in patients. The grades are ...
