Showing 1–12 of 48 results
A big data analytics framework for scientific data management
The Ophidia projectرایگان!
The Ophidia project is a research effort addressing big data analytics requirements, issues, and challenges for eScience. We present here the Ophidia analytics framework, which is responsible for atomically processing, transforming and manipulating array-based data. This framework provides a common way to run on large clusters analytics tasks applied to big datasets. The paper highlights the design principles, algorithm, and most relevant implementation aspects of the Ophidia analytics framework. Some experimental results, related to a couple of data analytics operators in a real cluster environment, are also presented.
A new convex objective function for the supervised learning of single-layer neural networks
This paper proposesرایگان!
This paper proposes a novel supervised learning method for single-layer feedforward neural networks. This approach uses an alternative objective function to that based on the MSE, which measures the errors before the neuron’s nonlinear activation functions instead of after them. In this case, the solution can be easily obtained solving systems of linear equations, i.e., requiring much less computational power than the one associated with the regular methods. A theoretical study is included to proof the approximated equivalence between the global optimum of the objective function based on the regular MSE criterion and the one of the proposed alternative MSE function. Furthermore, it is shown that the presented method has the capability of allowing incremental and distributed learning. An exhaustive experimental study is also presented to verify the soundness and efficiency of the method. This study contains 10 classification and 16 regression problems. In addition, a comparison with other high performance learning algorithms shows that the proposed method exhibits, in average, the highest performance and low-demanding computational requirements.
A survey and challenges in routing and data dissemination in vehicular ad hoc networks
In this paper, we suرایگان!
In this paper, we survey recent results in vehicular ad hoc networks (VANETs) data dissemination. We describe methods proposed to enforce dissemination scope such as geocast/broadcast and multicast. A growing category consisting of methods designed to achieve disruption tolerance in vehicular networks is presented. We describe the key ideas of representative technologies in each category. In addition, we consider location service and security issues that are crucial for data dissemination in VANET. We conclude by sharing our thoughts on further challenges.
A Survey of Security and Privacy in Big Data
Big data has been arرایگان!
Big data has been arising a growing interest in both scientific and industrial fields for its potential value. However, before employing big data technology into massive applications, a basic but also principle topic should be investigated: security and privacy. In this paper, the recent research and development on security and privacy in big data is surveyed. First, the effects of characteristics of big data on information security and privacy are described. Then, topics and issues on security are discussed and reviewed. Further, privacy-preserving trajectory data publishing is studied due to its future utilization, especially in telecom operation.
A systematic review of economic analyses of telehealth services using real time video communication
Background: Telehealth is the delivery of health care at a distance, using information and communication technology. The major rationales for its introduction have been to decrease costs, improve efficiency and increase access in health care delivery. This systematic review assesses the economic value of one type of telehealth delivery – synchronous or real time video communication – rather than examining a heterogeneous range of delivery modes as has been the case with previous reviews in this area. Methods: A systematic search was undertaken for economic analyses of the clinical use of telehealth, ending in June 2009. Studies with patient outcome data and a non-telehealth comparator were included. Cost analyses, noncomparative studies and those where patient satisfaction was the only health outcome were excluded. Results: 36 articles met the inclusion criteria. 22(61%) of the studies found telehealth to be less costly than the non-telehealth alternative, 11(31%) found greater costs and 3 (9%) gave the same or mixed results. 23 of the studies took the perspective of the health services, 12 were societal, and one was from the patient perspective. In three studies of telehealth to rural areas, the health services paid more for telehealth, but due to savings in patient travel, the societal perspective demonstrated cost savings. In regard to health outcomes, 12 (33%) of studies found improved health outcomes, 21 (58%) found outcomes were not significantly different, 2(6%) found that telehealth was less effective, and 1 (3%) found outcomes differed according to patient group. The organisational model of care was more important in determining the value of the service than the clinical discipline, the type of technology, or the date of the study.
Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore
In this study, withرایگان!
In this study, with Singapore as an example, we demonstrate how we can use mobile phone call detail record (CDR) data, which contains millions of anonymous users, to extract individual mobility networks comparable to the activity-based approach. Such an approach is widely used in the transportation planning practice to develop urban micro simulations of individual daily activities and travel; yet it depends highly on detailed travel survey data to capture individual activity-based behavior. We provide an innovative data mining framework that synthesizes the state-of-the-art techniques in extracting mobility patterns from raw mobile phone CDR data, and design a pipeline that can translate the massive and passive mobile phone records to meaningful spatial human mobility patterns readily interpretable for urban and transportation planning purposes. With growing ubiquitous mobile sensing, and shrinking labor and fiscal resources in the public sector globally, the method presented in this research can be used as a low-cost alternative for transportation and planning agencies to understand the human activity patterns in cities, and provide targeted plans for future sustainable development.
Age Synthesis and Estimation via Faces: A Survey
Human age, as an impرایگان!
Human age, as an important personal trait, can be directly inferred by distinct patterns emerging from the facial appearance. Derived from rapid advances in computer graphics and machine vision, computer-based age synthesis and estimation via faces have become particularly prevalent topics recently because of their explosively emerging real-world applications, such as forensic art, electronic customer relationship management, security control and surveillance monitoring, biometrics, entertainment, and cosmetology. Age synthesis is defined to rerender a face image aesthetically with natural aging and rejuvenating effects on the individual face. Age estimation is defined to label a face image automatically with the exact age (year) or the age group (year range) of the individual face. Because of their particularity and complexity, both problems are attractive yet challenging to computer-based application system designers. Large efforts from both academia and industry have been devoted in the last a few decades. In this paper, we survey the complete state-of-the-art techniques in the face image-based age synthesis and estimation topics. Existing models, popular algorithms, system performances, technical difficulties, popular face aging databases, evaluation protocols, and promising future directions are also provided with systematic discussions.
An energy efficient approach to extend network life time of wireless sensor networks
The energy consumptiرایگان!
The energy consumption in wireless sensor networks is a significant matter and there are many ways to conserve energy. The use of mobile sensors is of great relevance to minimize the total energy dissipation in communication and overhead control packets. In a WSN, sensor nodes deliver sensed data back to the sink via multi hopping. The sensor nodes near the sink will usually consume more battery power than others; consequently, these nodes will quickly drain out their battery energy and decrease in the network lifetime of the WSN. The presence of mobile sinks causes increased energy reduction in their proximity, due to more relay load under multi hop communication. Moreover, node deployment technique can also be used to improve the life time of the network. Performance comparisons have been done by simulations between different routing protocols and our approach show efficient results.
CogNet: A Network Management Architecture Featuring Cognitive Capabilities
It is expected thatرایگان!
It is expected that the fifth generation mobile networks (5G) will support both human-to-human and machine-tomachine communications, connecting up to trillions of devices and reaching formidable levels of complexity and traffic volume. This brings a new set of challenges for managing the network due to the diversity and the sheer size of the network. It will be necessary for the network to largely manage itself and deal with organisation, configuration, security, and optimisation issues. This paper proposes an architecture of an autonomic selfmanaging network based on Network Function Virtualization, which is capable of achieving or balancing objectives such as high QoS, low energy usage and operational efficiency. The main novelty of the architecture is the Cognitive Smart Engine introduced to enable Machine Learning, particularly (near) realtime learning, in order to dynamically adapt resources to the immediate requirements of the virtual network functions, while minimizing performance degradations to fulfill SLA requirements. This architecture is built within the CogNet European Horizon 2020 project, which refers to Cognitive Networks.
Determinants of choice of semantic web based Software as a Service: An integrative framework in the context of e-procurement and ERP
The ever increasingرایگان!
The ever increasing Internet bandwidth and the fast changing needs of businesses for effectiveness with the partners in the procurement chain and is leading organizations to adopt information systems infrastructures that are cost effective as well as flexible. The question seems to be: what is driving organizations to go in for Software as a Service (SaaS) based e-procurement and ERP, rather than the packaged model of software provisioning? Whereas there have been studies reporting technology, cost, quality, network externalities and process as the main variables in the utility function of the user, but most of the studies have modelled either one or two in the their models. The study is exploratory in nature and tries to identify, classify and rank dimensions affecting SaaS sourcing decisions. In this study, we developed an integrative framework to identify the determinants of choice of SaaS in the specific context of SaaS based e-procurement and ERP. The framework was then analyzed using the extended Analytic Hierarchy Process (AHP) method suggested by Liberatore (1987) and the relative importance and the weights of the criteria identified using data collected on 8 users and 9 service providers of SaaS based e-procurement and ERP. Although the analysis helped in identifying quality and costs as the two most important determinants of choice of SaaS based eprocurement and ERP, but the other criteria such as network externality benefits, technology and process were also found to be significant determinants of choice.
Environmental, Health, and Safety Guidelines for Fish Processing
The Environmental, Hرایگان!
The Environmental, Health, and Safety (EHS) Guidelines are technical reference documents with general and industryspecific examples of Good International Industry Practice (GIIP)1. When one or more members of the World Bank Group are involved in a project, these EHS Guidelines are applied as required by their respective policies and standards. These industry sector EHS guidelines are designed to be used together with the General EHS Guidelines document, which provides guidance to users on common EHS issues potentially applicable to all industry sectors. For complex projects, use of multiple industry-sector guidelines may be necessary. A complete list of industry-sector guidelines can be found at: www.ifc.org/ifcext/enviro.nsf/Content/EnvironmentalGuidelines The EHS Guidelines contain the performance levels and measures that are generally considered to be achievable in new facilities by existing technology at reasonable costs. Application of the EHS Guidelines to existing facilities may involve the establishment of site-specific targets, with an appropriate timetable for achieving them. The applicability of the EHS Guidelines should be tailored to the hazards and risks established for each project on the basis of the results of an environmental assessment in which site-specific variables, such as host country context, assimilative capacity of the environment, and other project factors, are taken into account.