K-Nearest-Neighbor-Based Service Broker Policy for Data Center Selection in Cloud Computing Environment

Cloud Computing offers various resources as servicesto the internet users. This arise a very important issue in selectingthe appropriate data center(s) to serve users' requests. One of theimportant components in the cloud computing environment is theservice broker, which's responsible for selecting an adequate datacenter to serve a user request. Many of broker policies areimplemented in the cloud computing environment. AK-Nearest-Neighbor-Based service broker policy for data centerselection in the cloud computing environment is proposed in thispaper. This policy used a list of distinctive features andcharacteristics for each data center and user's request. Theresults show that the proposed policy outperformed therandom-based policy in terms of Average Response Time (ART)and Average Processing Time (APT)

Investigating the security issues of multi-layer IoMT attacks using machine learning techniques

The Internet of Medical Things (IoMT) plays a significant role in the healthcare system as it improves effectiveness and efficiency of treatment by continuously monitoring patients using smart home sensor and wearables (Fig. 1), early disease diagnosis using data collected from the Internet of Medical Things (IoMT) devices and assisting doctors in deciding the best treatment and acting immediately if necessary. Additionally, it helps to reduce the number of hospital visits, limiting carbon footprint.IoMT devices are vulnerable to Multi-layer attacks because most of these devices are resource-constrained and portable, which is why there is not that much implementation of security features in these devices and making them a prime target for intruders looking to steal patients’ sensitive information and healthcare records. Multi-layer attacks are a group of attacksexploiting multiple layers of IoMT architecture. Denial-of-service (DoS) and Man-In-The-Middle (MITM) attacks, for instance, can target the three layers of the IoMT system and lead to serious consequences, such as theft of patients’ sensitive data and reputational damages. The main aim of the project is to create a robust IDS for IoT devices

Safeguarding IoMT: Semi-automated Intrusion Detection System (SAIDS) for detecting multilayer attacks

The Internet of Medical Things (IoMT) plays a significant role in the healthcare system as it improves effectiveness and efficiency of treatment by continuously monitoring patients using smart home sensor and wearables (Fig. 1). IoMT devices are vulnerable to Multi-layer attacks that are exploiting multiple layers of IoMT architecture (Fig. 2). Denial-of-service (DoS) and Man-In-The-Middle (MITM) attacks, for instance, can target the three layers of the IoMT system and lead to serious consequences, such as theft of patients’ sensitive data and reputational damages [2]. This project aims to create a robust detection system for multilayer attacks using a Semi-automated Intrusion Detection System (SAIDS) for IoT devices. To achieve this aim, we have focused on the following objectives: • Explore a variety of feature selection algorithms. • Apply feature weighting. • Integrating human and machine learning approaches to work together. • Increase detection efficiency by utilizing significant features

Loop based scheduling for high level synthesis

This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. It partitions the control flow graph of the input specification into subgraphs before scheduling the different paths of each subgraph. Benchmark tests as well as simulation results on the scheduling algorithm indicate that the proposed algorithm results in sizeable reduction in runtime

Loop based scheduling for high level synthesis

This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. It partitions the control flow graph of the input specification into subgraphs before scheduling the different paths of each subgraph. Benchmark tests as well as simulation results on the scheduling algorithm indicate that the proposed algorithm results in sizeable reduction in runtim

Exome sequencing identifies nonsegregating nonsense ATM and PALB2 variants in familial pancreatic cancer.

We sequenced 11 germline exomes from five families with familial pancreatic cancer (FPC). One proband had a germline nonsense variant in ATM with somatic loss of the variant allele. Another proband had a nonsense variant in PALB2 with somatic loss of the variant allele. Both variants were absent in a relative with FPC. These findings question the causal mechanisms of ATM and PALB2 in these families and highlight challenges in identifying the causes of familial cancer syndromes using exome sequencing

Loop based scheduling for high level synthesis

This paper describes a new loop based scheduling algorithm. The algorithm aims at reducing the runtime processing complexity of path based scheduling techniques. It partitions the control flow graph of the input specification into subgraphs before scheduling the different paths of each subgraph. Benchmark tests as well as simulation results on the scheduling algorithm indicate that the proposed algorithm results in sizeable reduction in runtim

Factors Associated with Influenza Vaccination of Hospitalized Elderly Patients in Spain

Vaccination of the elderly is an important factor in limiting the impact of influenza in the community. The aim of this study was to investigate the factors associated with influenza vaccination coverage in hospitalized patients aged ≥ 65 years hospitalized due to causes unrelated to influenza in Spain. We carried out a cross-sectional study. Bivariate analysis was performed comparing vaccinated and unvaccinated patients, taking in to account sociodemographic variables and medical risk conditions. Multivariate analysis was performed using multilevel regression models. We included 1038 patients: 602 (58%) had received the influenza vaccine in the 2013-14 season. Three or more general practitioner visits (OR = 1.61; 95% CI 1.19-2.18); influenza vaccination in any of the 3 previous seasons (OR = 13.57; 95% CI 9.45-19.48); and 23-valent pneumococcal polysaccharide vaccination (OR = 1.97; 95% CI 1.38-2.80) were associated with receiving the influenza vaccine. Vaccination coverage of hospitalized elderly people is low in Spain and some predisposing characteristics influence vaccination coverage. Healthcare workers should take these characteristics into account and be encouraged to proactively propose influenza vaccination to all patients aged ≥ 65 year