The negative impact of stroke in society has led to concerted efforts improve the management and diagnosis stroke. With an increased synergy between technology medical diagnosis, caregivers create opportunities for better patient by systematically mining archiving patients’ records. Therefore, it is vital study interdependency these risk factors health records understand their relative contribution prediction. This paper analyzes various electronic effective Using statistical techniques...

Data replication has been widely used as a mean of increasing the data availability large-scale cloud storage systems where failures are normal. Aiming to provide cost-effective availability, and improve performance load-balancing storage, this paper presents dynamic management scheme referred CDRM. A novel model is proposed capture relationship between replica number. CDRM leverages calculate maintain minimal number for given requirement. Replica placement based on capacity blocking...

Generally, a parallel application consists of precedence constrained stochastic tasks, where task processing times and intertask communication are random variables following certain probability distributions. Scheduling such tasks with on heterogeneous cluster system processors different computing capabilities to minimize application's expected completion time is an important but very difficult problem in distributed computing. In this paper, we present model scheduling applications systems....

In the recent past, security-sensitive applications, such as electronic transaction processing systems, stock quote update which require high quality of security to guarantee authentication, integrity, and confidentiality information, have adopted heterogeneous distributed system (HDS) their platforms. This is primarily due fact that single parallel-architecture-based systems may not be sufficient exploit available parallelism with running applications. Most security-aware applications end...

The thermal profile of multicore systems vary both within an application's execution (intra) and also when the system switches from one application to another (inter). In this paper, we propose adaptive management approach improve lifetime reliability by considering inter- intra-application variations. Fundamental is a reinforcement learning algorithm, which learns relationship between mapping threads cores, frequency core its temperature (sampled on-board sensors). Action provided...

Homomorphic encryption is an emerging form of that provides the ability to compute on encrypted data without ever decrypting them. Potential applications include aggregating sensitive a cloud environment and computing in compromising privacy. There have been several recent advances resulting new homomorphic schemes optimized variants. We implement evaluate performance two variants, namely Bajard-Eynard-Hasan-Zucca (BEHZ) Halevi-Polyakov-Shoup (HPS), most promising scheme CPU GPU. The...

Nowadays, cloud-supported Internet of Things (Cloud-IoT) has been broadly deployed in smart medical systems, where the limitations (IoT)-associated devices terms data access, storage, scalability, and computing are solved through use cloud architectures. However, with rapid development equipment increasing number devices, it will be extremely difficult to program or manage such an expanding massive IoT system traditional single-cloud platforms. In this article, we design implement a...

Fully homomorphic encryption (FHE) is a powerful cryptographic primitive to secure outsourced computations against an untrusted third-party provider. With the growing demand for AI and usefulness of machine learning as service (MLaaS), need training inference artificial neural networks rising. However, computational complexity existing FHE schemes has been strong deterrent this. Prior works suffered from accuracy degradation, lack scalability, ciphertext expansion issues. In this paper, we...

Object detection at night is a challenging problem due to the absence of image annotations. Despite several domain adaptation methods, achieving high-precision results remains an issue. False-positive error propagation still observed in methods using well-established student-teacher framework, particularly for small-scale and low-light objects. This paper proposes two-phase consistency unsupervised network, 2PCNet, address these issues. The network employs high-confidence bounding-box...

In this paper, we address several issues that are imperative to grid environments such as handling resource heterogeneity and sharing, communication latency, job migration from one site other, load balancing. We these by proposing two algorithms, which MELISA (modified ELISA) LBA (load balancing on arrival). The algorithms differ in the way is carried out shown be efficient minimizing response time large small-scale heterogeneous environments, respectively. MELISA, applicable large-scale...

Mobile crowdsensing leverages mobile devices (e.g., smart phones) and human mobility for pervasive information exploration collection; it has been deemed as a promising paradigm that will revolutionize various research application domains. Unfortunately, the practicality of can be crippled due to lack incentive mechanisms stimulate participation. In this paper, we study novel Crowdsensing Scheduling (MCS) problem, where owner announces set sensing tasks, then users (carrying devices) compete...

Traditionally, the "best effort, cost free" model of Supercomputers/Grids does not consider pricing. Clouds have progressed towards a service-oriented paradigm that enables new way service provisioning based on "pay-as-you-go" model. Large scale many-task workflow (MTW) may be suited for execution due to its scale-* requirement (scale up, out, and down). In context scheduling, MTW must considered users' budget constraints. this paper, we address problem scheduling present budget-conscious...

Content distribution networks (CDNs) built on clouds have recently started to emerge. Compared conventional CDNs, cloud-based CDNs the benefit of cost efficient hosting services without owning infrastructure. However, resource provisioning and replica placement in cloud involve a number challenging issues, mainly due dynamic nature demand patterns. To deal with this nature, paper proposes set novel algorithms solve joint problem caching (i.e., placement) for an emphasis handling Firstly, we...

Studies have identified various risk factors associated with the onset of stroke in an individual. Data mining techniques been used to predict occurrence based on these by using patients' medical records. However, there has limited use electronic health records study inter-dependency different stroke. In this paper, we perform analysis identify impact prediction. We also provide benchmark performance state-of-art machine learning algorithms for predicting

In this paper, we present an automated procedure to determine the presence of cardiomegaly on chest X-ray image based deep learning. The proposed algorithm CardioXNet uses learning methods U-NET and cardiothoracic ratio for diagnosis from X-rays. learns segmentation task ground truth data. OpenCV is used denoise maintain precision region interest once minor errors occur. Therefore, Cardiothoracic (CTR) calculated as a criterion U-net segmentations. End-to-end Dense-Net neural network...

A compact, light-weight and low-power wireless vital signs monitoring system based on Wireless Body Area Network (WBAN) protocol has been developed. The system, VySys, includes two compact wearable biosensor devices for continuous capturing transmission, a gateway to relay the message collected from biosensors cloud, finally client apps access display stored data in cloud. Both can last 24 hours weigh less than 22 g 44 g, respectively.They consist of proprietary in-house bio-sensing...

This paper presents a new strategy for load distribution in single-level tree network equipped with or without front-ends. The is distributed more than installment an optimal manner to minimize the processing time. deviation and improvement over earlier studies which done only one installment. Recursive equations general case, their closed-form solutions special case has identical processors links, are derived. An asymptotic analysis of performance respect number installments carried out....

Fault-tolerant scheduling is an imperative step for large-scale computational grid systems, as often geographically distributed nodes co-operate to execute a task. By and large, primary-backup approach common methodology used fault tolerance wherein each task has primary copy backup on two different processors. In this paper, we identify cases that may happen when dependent tasks with approach. We derive important constraints must be satisfied. Further, show these play crucial role in...

In this paper, we propose distributed algorithms referred to as resource-aware dynamic incremental scheduling (RADIS) strategies. Our strategies are specifically designed handle large volumes of computationally intensive arbitrarily divisible loads submitted for processing at cluster/grid systems involving multiple sources and sinks (processing nodes). We consider a real-life scenario, wherein the buffer space (memory) available (required holding loads) varies over time, have deadlines...

Energy and reliability optimization are two of the most critical objectives for synthesis multiprocessor systems-on-chip (MPSoCs). Task mapping has shown significant promise as a low cost solution in achieving these standalone or tandem well. This paper proposes multi-objective design space exploration to determine tasks an application on system voltage/frequency level each (exploiting DVFS capabilities modern processors) such that platform is improved while fulfilling energy budget...

In many network applications, Bloom filters are used to support exact-matching membership query for their randomized space-efficient data structure with a small probability of false answers. this paper, we extend the standard filter Locality-Sensitive Filter (LSBF) provide Approximate Membership Query (AMQ) service. We achieve by replacing uniform and independent hash functions locality-sensitive functions. Such replacement makes storage in LSBF be locality sensitive. Meanwhile, is space...