295 research outputs found
GUISET: A CONCEPTUAL DESIGN OF A GRID-ENABLED PORTAL FOR E-COMMERCE ON-DEMAND SERVICES
Conventional grid-enabled portal designs have been largely influenced by the usual functional requirements such as security requirements, grid resource requirements and job management requirements. However, the pay-as-you-use service provisioning model of utility computing platforms mean that additional requirements must be considered in order to realize effective grid-enabled portals design for such platforms. This work investigates those relevant additional
requirements that must be considered for the design of grid-enabled portals for utility computing
contexts.
Based on a thorough review of literature, we identified a number of those relevant additional
requirements, and developed a grid-enabled portal prototype for the Grid-based Utility
Infrastructure for SMME-enabling Technology (GUISET) initiative â a utility computing platform.
The GUISET portal was designed to cater for both the traditional grid requirements and some of
the relevant additional requirements for utility computing contexts. The result of the evaluation of
the GUISET portal prototype using a set of benchmark requirements (standards) revealed that it
fulfilled the minimum requirements to be suitable for the utility context
A Scalable Cluster-based Infrastructure for Edge-computing Services
In this paper we present a scalable and dynamic intermediary infrastruc-
ture, SEcS (acronym of BScalable Edge computing Servicesââ), for developing and
deploying advanced Edge computing services, by using a cluster of heterogeneous
machines. Our goal is to address the challenges of the next-generation Internet
services: scalability, high availability, fault-tolerance and robustness, as well as
programmability and quick prototyping. The system is written in Java and is based
on IBMâs Web Based Intermediaries (WBI) [71] developed at IBM Almaden
Research Center
Data management in cloud environments: NoSQL and NewSQL data stores
: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the large number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and even more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL and NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to practitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities in the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling, and security related capabilities. Features driving the ability to scale read requests and write requests, or scaling data storage are investigated, in particular partitioning, replication, consistency, and concurrency control. Furthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and the suitability of various solutions for different sets of applications is examined. Consequently, this study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages
Adaptive intelligent tutoring for teaching modern standard Arabic
A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyThe aim of this PhD thesis is to develop a framework for adaptive intelligent tutoring systems (ITS) in the domain of Modern Standard Arabic language. This framework will comprise of a new approach to using a fuzzy inference mechanism and generic rules in guiding the learning process. In addition, the framework will demonstrate another contribution in which the system can be adapted to be used in the teaching of different languages. A prototype system will be developed to demonstrate these features. This system is targeted at adult English-speaking casual learners with no pre-knowledge of the Arabic language. It will consist of two parts: an ITS for learners to use and a teachersâ tool for configuring and customising the teaching rules and artificial intelligence components among other configuration operations. The system also provides a diverse teaching-strategiesâ environment based on multiple instructional strategies. This approach is based on general rules that provide means to a reconfigurable prediction. The ITS determines the learnerâs learning characteristics using multiple fuzzy inferences. It has a reconfigurable design that can be altered by the teacher at runtime via a teacher-interface. A framework for an independent domain (i.e. pluggable-domain) for foreign language tutoring systems is introduced in this research. This approach allows the system to adapt to the teaching of a different language with little changes required. Such a feature has the advantages of reducing the time and cost required for building intelligent language tutoring systems. To evaluate the proposed system, two experiments are conducted with two versions of the software: the ITS and a cut down version with no artificial intelligence components. The learners used the ITS had shown an increase in scores between the post-test and the pre-test with learning gain of 35% compared to 25% of the learners from the cut down version
Recommended from our members
Towards an aspect weaving BPEL engine
This position paper proposes the use of dynamic aspects and
the visitor design pattern to obtain a highly configurable and
extensible BPEL engine. Using these two techniques, the
core of this infrastructural software can be customised to
meet new requirements and add features such as debugging,
execution monitoring, or changing to another Web Service
selection policy. Additionally, it can easily be extended to
cope with customer-specific BPEL extensions. We propose
the use of dynamic aspects not only on the engine itself
but also on the workflow in order to tackle the problems of
Web Service hot deployment and hot fixes to long running
processes. In this way, composing aWeb Service "on-the-fly"
means weaving its choreography interface into the workflow
Automated Injection of Curated Knowledge Into Real-Time Clinical Systems: CDS Architecture for the 21st Century
abstract: Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an âimplementation concernâ requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge Artifact specification, for example, carries no reasonable expectation that it may be imported and deployed into a live system without significant burdens. Dramatic reduction of the time and effort gap in the research and application cycle could be revolutionary. Doing so, however, requires both a floor-to-ceiling precoordination of functional boundaries in the knowledge management lifecycle, as well as formalization of the human processes by which this occurs.
This research introduces ARTAKA: Architecture for Real-Time Application of Knowledge Artifacts, as a concrete floor-to-ceiling technological blueprint for both provider heath IT (HIT) and vendor organizations to incrementally introduce value into existing systems dynamically. This is made possible by service-ization of curated knowledge artifacts, then injected into a highly scalable backend infrastructure by automated orchestration through public marketplaces. Supplementary examples of client app integration are also provided. Compilation of knowledge into platform-specific form has been left flexible, in so far as implementations comply with ARTAKAâs Context Event Service (CES) communication and Health Services Platform (HSP) Marketplace service packaging standards.
Towards the goal of interoperable human processes, ARTAKAâs treatment of knowledge artifacts as a specialized form of software allows knowledge engineers to operate as a type of software engineering practice. Thus, nearly a century of software development processes, tools, policies, and lessons offer immediate benefit: in some cases, with remarkable parity. Analyses of experimentation is provided with guidelines in how choice aspects of software development life cycles (SDLCs) apply to knowledge artifact development in an ARTAKA environment.
Portions of this culminating document have been further initiated with Standards Developing Organizations (SDOs) intended to ultimately produce normative standards, as have active relationships with other bodies.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201
A Reference Software Architecture for Social Robots
Social Robotics poses tough challenges to software designers who are required
to take care of difficult architectural drivers like acceptability, trust of
robots as well as to guarantee that robots establish a personalised interaction
with their users. Moreover, in this context recurrent software design issues
such as ensuring interoperability, improving reusability and customizability of
software components also arise.
Designing and implementing social robotic software architectures is a
time-intensive activity requiring multi-disciplinary expertise: this makes
difficult to rapidly develop, customise, and personalise robotic solutions.
These challenges may be mitigated at design time by choosing certain
architectural styles, implementing specific architectural patterns and using
particular technologies.
Leveraging on our experience in the MARIO project, in this paper we propose a
series of principles that social robots may benefit from. These principles lay
also the foundations for the design of a reference software architecture for
Social Robots. The ultimate goal of this work is to establish a common ground
based on a reference software architecture to allow to easily reuse robotic
software components in order to rapidly develop, implement, and personalise
Social Robots
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
Big Data Now, 2015 Edition
Now in its fifth year, OâReillyâs annual Big Data Now report recaps the trends, tools, applications, and forecasts weâve talked about over the past year. For 2015, weâve included a collection of blog posts, authored by leading thinkers and experts in the field, that reflect a unique set of themes weâve identified as gaining significant attention and traction.
Our list of 2015 topics include:
Data-driven cultures
Data science
Data pipelines
Big data architecture and infrastructure
The Internet of Things and real time
Applications of big data
Security, ethics, and governance
Is your organization on the right track? Get a hold of this free report now and stay in tune with the latest significant developments in big data
- âŚ