Prescription Based Recommender System for Diabetic Patients Using Efficient Map Reduce

Healthcare sector has been deprived of leveraging knowledge gained through data insights, due to manual processes and legacy record-keeping methods. Outdated methods for maintaining healthcare records have not been proven sufficient for treating chronic diseases like diabetes. Data analysis methods such as Recommendation System (RS) can serve as a boon for treating diabetes. RS leverages predictive analysis and provides clinicians with information needed to determine the treatments to patients. Prescription-based Health Recommender System (HRS) is proposed in this paper which aids in recommending treatments by learning from the treatments prescribed to other patients diagnosed with diabetes. An Advanced Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering is also proposed to cluster the data for deriving recommendations by using winnowing algorithm as a similarity measure. A parallel processing of data is applied using map-reduce to increase the efficiency & scalability of clustering process for effective treatment of diabetes. This paper provides a good picture of how the Map Reduce can benefit in increasing the efficiency and scalability of the HRS using clustering

Assessment of Response Time for New Multi Level Feedback Queue Scheduler

Response time is one of the characteristics of scheduler, happens to be a prominent attribute of any CPU scheduling algorithm. The proposed New Multi Level Feedback Queue [NMLFQ] Scheduler is compared with dynamic, real time, Dependent Activity Scheduling Algorithm (DASA) and Lockes Best Effort Scheduling Algorithm (LBESA). We abbreviated beneficial result of NMLFQ scheduler in comparison with dynamic best effort schedulers with respect to response time.Comment: 7 pages, 5 figure

On the handover security key update and residence management in LTE networks

In LTE networks, key update and residence management have been investigated as an effective solution to cope with desynchronization attacks in mobility management entity (MME) handovers. In this paper, we first analyse the impacts of the key update interval (KUI) and MME residence interval (MRI) on the handover performance in terms of the number of exposed packets (NEP) and signaling overhead rate (SOR). By deriving the bounds of the NEP and SOR over the KUI and MRI, it is shown that there exists a tradeoff between the NEP and the SOR, while our aim is to minimise both of them simultaneously. This accordingly motivates us to propose a multiobjective optimisation problem to find the optimal KUI and MRI that minimise both the NEP and SOR. By introducing a relative importance factor between the SOR and NEP along with their derived bounds, we further transform the proposed optimisation problem into a single-objective optimisation problem which can be solved via a simple numerical method. In particular, the results show that a higher accuracy of up to 1 second is achieved with the proposed approach while requiring a lower complexity compared to the conventional approach employing iterative searches

Internet Traffic Measurement: Trends and Impact to Campus Network

Abstract— University of Lampung (Unila) is an Institution of Higher Education located in Bandar Lampung. Since 2016, Unila has deployed Internet Access Management (IAM) to guarantee the healthiness of the campus network, as well as to enhance the effectiveness of the bandwidth usage. This study focused on internet traffic measurement, conducted in Unila’s campus network during February 1 until February 29, 2016. Overall, this study shows user behavior on their application. The trend data of monthly most popular URL Categories accessed by users was; 1st Computers & Technology with 30032328 hits or 39.1%, the 2nd was Search Engines & Portals with 14214611 hits or 18.5%. There were around 30-40 % of internet traffic was use for Streaming Media activity, it proves that the existence of Streaming Media Activity in Campus Network which contribute to network congestion. During a month doing internet measurement, we identify the most active device/user that are the 1st was Aruba Wireless Controller with total traffic flow 40.45%, the 2nd was CCR-1 with 26.2%, the 3rd was CCR-2 with 16.9%, and the 4th was Digital Library Server with total flow was 0.6%. Monthly uplink traffic total flow was 5889.92 GB while downlink traffic total flow was 61041.35 GB. We made a recommendation to Unila management for implementing traffic provisioning especially on streaming media activity specific on access to Google Global Cache (GGC), to overcome network congestion during peak time period on working hours. Keywords—internet access management, internet traffic measurement; traffic tren

Performance improvement in geographic routing for vehicular Ad Hoc networks

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and spee

Energy-Aware Server Provisioning by Introducing Middleware-Level Dynamic Green Scheduling

International audienceSeveral approaches to reduce the power consumption of datacenters have been described in the literature, most of which aim to improve energy efficiency by trading off performance for reducing power consumption. However, these approaches do not always provide means for administrators and users to specify how they want to explore such trade-offs. This work provides techniques for assigning jobs to distributed resources, exploring energy efficient resource provisioning. We use middleware-level mechanisms to adapt resource allocation according to energy-related events and user-defined rules. A proposed framework enables developers, users and system administrators to specify and explore energy efficiency and performance trade-offs without detailed knowledge of the underlying hardware platform. Evaluation of the proposed solution under three scheduling policies shows gains of 25% in energy-efficiency with minimal impact on the overall application performance. We also evaluate reactivity in the adaptive resource provisioning

The moderating role of organizational culture on the relationship between emotional intelligence and transformational leadership

The purpose of this empirical research is to examine the interrelated influences among emotional intelligence, organizational culture, and transformational leadership. In particular, the current study investigated the effect of emotional intelligence as a predictor of transformational leadership. The potential moderating effects of organizational culture on the relationships between the dimensions of emotional intelligence and transformational leadership were also examined. Data was collected from a sample of 333 academic leaders in 18 public universities in peninsular Malaysia. Transformational leadership was measured by using the Multifactor Leadership Questionnaire (MLQ-5x Short), emotional intelligence, using the Wong and Law Emotional Intelligence Scale (WLEIS), and organizational culture, using the Organizational Culture Assessment Instrument (OCAI). Structural equation modeling by means of partial least square bootstrapping resampling was used for hypotheses testing. Methodological improvements were made to overcome some of the challenges identified by past research that examined emotional intelligence and leadership. These concerns included common method variance, smaller sample sizes, relatively lower construct reliability, and researching sole organizations. The statistical results revealed a significantly positive relationship between transformational leadership and three of the independent variables, namely, self-emotion appraisal, others emotional appraisal, and use of emotion. The study of organizational culture as a moderator between the dimensions of emotional intelligence and transformational leadership was also unprecedented. Generally, organizational culture played an important role in moderating this relationship. However, the moderating effect of organizational culture as a whole construct, and clan and hierarchy type cultures were found significant only on the relationship between regulation of emotion and transformational leadership while adhocracy type culture negatively moderated the relationship between others emotional appraisal and transformational leadership. The results of this study contribute to the present pool of knowledge about the interrelationships of emotional intelligence, organizational culture and transformational leadership, showing that the power of leaders’ emotional intelligence on transformational leadership is expressed through a third moderating variable, organizational culture. Theoretically, the study is hopeful to further understandings of the predictive power of emotional intelligence dimensions on transformational leadership, as well as contribute insights as to the conditional effect of organizational culture on the relationship. The findings of the study will also help practitioners improve the selection and development of leaders

Software Test Case Generation Tools and Techniques: A Review

Software Industry is evolving at a very fast pace since last two decades. Many software developments, testing and test case generation approaches have evolved in last two decades to deliver quality products and services. Testing plays a vital role to ensure the quality and reliability of software products. In this paper authors attempted to conduct a systematic study of testing tools and techniques. Six most popular e-resources called IEEE, Springer, Association for Computing Machinery (ACM), Elsevier, Wiley and Google Scholar to download 738 manuscripts out of which 125 were selected to conduct the study. Out of 125 manuscripts selected, a good number approx. 79% are from reputed journals and around 21% are from good conference of repute. Testing tools discussed in this paper have broadly been divided into five different categories: open source, academic and research, commercial, academic and open source, and commercial & open source. The paper also discusses several benchmarked datasets viz. Evosuite 10, SF100 Corpus, Defects4J repository, Neo4j, JSON, Mocha JS, and Node JS to name a few. Aim of this paper is to make the researchers aware of the various test case generation tools and techniques introduced in the last 11 years with their salient features

Database management system performance comparisons: A systematic literature review

Efficiency has been a pivotal aspect of the software industry since its inception, as a system that serves the end-user fast, and the service provider cost-efficiently benefits all parties. A database management system (DBMS) is an integral part of effectively all software systems, and therefore it is logical that different studies have compared the performance of different DBMSs in hopes of finding the most efficient one. This study systematically synthesizes the results and approaches of studies that compare DBMS performance and provides recommendations for industry and research. The results show that performance is usually tested in a way that does not reflect real-world use cases, and that tests are typically reported in insufficient detail for replication or for drawing conclusions from the stated results.Comment: 36 page