try to retrieve information about the donor. On the other hand, a donor might try to intentionally alter the normal execution of a user application to earn extra credits or wrong results may be generated unintentionally due to faulty hard- ware. Therefore, user applications and the donor’s resources need to be mutually protected from each other against intentional and unintentional harm. The appli- cations often use security mechanisms such as encryption, code signing, validation and consensus before accepting any results from the users [Dom08]. Techniques such as sandboxing [CCEB03], resource virtualisation [GN07], to name a few, are usually employed for protecting the resources. These security concerns are higher for an Internet-based desktop grid rather than a LAN-based desktop grid due to a lower level of trust between the users and the donors in the former case. The heterogeneity of resources presents another challenge while developing applications for desktop grids. This entails that the application code needs to be portable for executing in different environments which exist on a desktop grid. The use of interpreted code can overcome portability problems, but it is affected by poor performance and overheads which are associated with such systems. For example, System Virtual Machines may be employed which allow the users to precisely control the execution environment and protect the resources as well [FDF03]. The drawback of such techniques is that they require specialised compatible software to be installed and maintained on all the resources. The heterogeneity can also affect the accuracy of results generated by the tasks due to various hardware [TACBI05]. Proper load balancing in accordance with the different capabilities of the underlying hardware can have a great effect on overall efficiency.
Historically, the evolution of information technology has been characterized by innovation and the creation of new paradigms. This behavior has repeated itself with the appearance of cloud computing, a distributed computing model where sharedcomputationalresources (e.g., hardware, development platforms, and applications) are virtualized and offered as services, supported by a number of data centers all over the Internet (Armbrust et al. 2010, Foster et al. 2008, Vaquero et al. 2009).
Cloud computing is an emerging model that delivers ser- vices over the Internet by providing access to a wide range of sharedcomputationalresources hosted in data centers. The growth of cloud computing model has led to establishing numerous data centers around the world that consume huge amounts of power. Therefore, elim- inating any waste of power in cloud data centers is very necessary. This can be achieved by observing how power is delivered to the data centers’ resources, and how these resources are utilized to serve users’ jobs. Hence, the need for improving the existing resource allocation and management algorithms in cloud data centers, as well as proposing new ones, is highly required. This paper pre- sents previous research works that aimed to improve power efficiency of virtualized data centers. It is a valu- able guide for understanding the state of the art of how to manage the power consumed in such environments. Additionally, it leads to suggesting and adding new pro- posals for further enhancement.
What about entanglement, the second fundamental resource that is consumed in any DIRNG protocol? This quantum resource usually consists of m copies |ψi ⊗m of some bipartite entangled state |ψi shared between two separated devices A and B that can be prevented at will from interacting with one another. Though DIRNG protocols involve a single user, it is useful for exposition purposes to view these two de- vices as being operated by two agents, Alice and Bob, in two remote sublaboratories. The m copies |ψi ⊗m can either be stored prior to the start of the protocol inside quantum memories in Alice’s and Bob’s sublab- oratories, or each copy |ψi can be produced individu- ally during each execution round of the protocol, say by a source located between Alice and Bob.
Grid scheduling to appease the customer and provider satisfactions, such as Condor project [ 3 ] , which being gradually developed for about fifteen years, aim for high throughput. The ex- isting projects such as Alchemi aggregates the computing power of networked machines into a computational grid, Gridport aggregates service based applications, GridSim allows modeling and simulation of entities in the parallel and dis- tributed computing systems, Gridway provides globus submission framework, Maui executes batch scheduling for high performance comput- ing and so forth. Few projects namely Astro- grid, Avaki are orienting towards Data grids. Gridlab is a project aiming towards application development. Projects such as OptimalGrid and United Devices Metaprocessor Platform sched- ules and manages workloads considering load balancing. Albeit real time projects are emerg- ing exponentially, the challenge towards Grid scheduling is succinct.
A total of sixteen teams from three continents participated in this task, and fourteen of them submitted system description papers. Many different approaches were adopted by the participants, and we hope that these approaches help to advance the state of the art in Shallow Discourse Parsing. The training, development, and test sets were adapted from the Penn Discourse TreeBank (PDTB). In addition, we also annotated a blind test set following the PDTB guidelines solely for the shared task. The results on the blind test set were used to rank the participating systems. The evaluation scorer, also developed for this shared task, adopts an F1 based metric that takes into account the accuracy of identifying the senses and arguments of discourse relations as well as explicit discourse connectives. We hope that the data sets and the scorer, which are freely available upon the completion of the shared task, will be a useful resource for researchers interested in discourse parsing.
We explored a two-phase approach to event ex- traction, distinguishing general linguistic principles from task-specific aspects, in accordance with the generalization theme of the shared task. Our results demonstrate the viability of this approach on both abstracts and article bodies, while also pinpointing some of its shortcomings. For example, our error analysis shows that some aspects of semantic com- position algorithm (argument propagation, in partic- ular) requires more refinement. Furthermore, using the same trigger expression dictionary for all tracks seems to have negative effect on the overall perfor- mance. The incremental nature of our system de- velopment ensures that some of these shortcomings will be addressed in future work.
This volume contains papers describing the CoNLL-2014 Shared Task and the participating systems. This year, we continue the tradition of the Conference on Computational Natural Language Learning (CoNLL) of having a high profile shared task in natural language processing, centered on automatic grammatical error correction of English essays. The grammatical error correction task is impactful since it is estimated that hundreds of millions of people in the world are learning English as a second language, and they benefit directly from an automated grammar checker.
The UTurku team responded to a call for sup- porting analyses by providing predictions from their REL system for all BioNLP Shared Task main task datasets. These analyses were adopted by at least one main task participant as part of their system, and we expect that this resource will continue to serve to facilitate the study of the position of part- of relations in domain event extraction. The REL task will continue as an open shared challenge, with all task data, evaluation software, and analysis tools available to all interested parties from http:// sites.google.com/site/bionlpst/.
The distinguishing aspect of our approach is that by casting event extraction as a dependency parsing, we take advantage of standard parsing tools and tech- niques rather than creating special purpose frame- works. In this paper, we show that with minimal domain-specific tuning, we are able to achieve com- petitive performance across the three event extrac- tion domains in the BioNLP 2011 shared task.
A total of 17 participating teams submitted system output and 16 of them submitted system description papers. Many different approaches were adopted to perform grammatical error correction. We hope that these approaches help to advance the state of the art in grammatical error correction, and that the test set and scorer, which are freely available after the shared task, can be useful resources for those interested in grammatical error correction.
The challenge for educators is to ensure that the range of materials and resources presented offers students the ability to choose and connect with information that resonates and is relevant to them (a ‗tool box of ideas‘) whilst ensuring they graduate with sound and current work-based knowledge. An example of this tool-box of ideas is in a pre-service course focusing on physical activity for young children. The course incorporates resources that help students make connections with course content by including personally designed videos on infant massage, parachute play, balloon play, relaxation methods and activities to support diversity (just to name a few). Other popular resources are podcasts, radio interviews and episodes of interesting television programs used to highlight a particular issue or share an interesting perspective.
USAID’s East Africa Regional Mission previously funded the PREPARED programme, aimed at mainstreaming climate-resilient development planning and program implementation into the East African Community and its partner states’ development agendas. As a central component of the PREPARED Programme, this project targeted key development areas such as climate change adaptation, biodiversity conservation, and sustainable access to water supply, sanitation, and hygiene (WASH) and worked to strengthen the resiliency and sustainability of Eastern Africa Institutions. The programme ran from December 2012 until April 2018. The programme worked with the EAC Secretariat and its Partner States; Lake Victoria Basin Commission (LVBC); ICPAC; Famine Early Warning System Network (FEWS NET); and Regional Centre for Mapping Resources for Development (RCMRD). USAID saw the EAC Secretariat as being well positioned to partner on the PREPARED project, as it is a growing regional political and economic bloc that encouraged considerable regional cooperation on climate change, food security, biodiversity conservation, and water resource management at the policy and planning levels (USAID | Kenya and East Africa, 2016: 3). ICPAC was also a partner on the PREPARED project and it worked with the organisation to support and improve climate information management and coordination for regional and national institutions within the EAC region (USAID | Kenya and East Africa, 2016: 3).
Red Hat Enterprise Linux 6 features virtualization, based on the KVM hypervisor, fully inte- grated into the kernel. This approach delivers kernel improvements to all virtualized appli- cations, and ensures that the application environment is consistent for physical and virtual systems, simplifying the adoption of virtualization. To ensure forward compatibility, Red Hat Enterprise Linux 6 is able to run as a full or paravirtualized xen guest on a Red Hat Enterprise Linux 5 xen-based host. The ability to easily move guests between hosts can be used to consolidate resources onto fewer machines during quiet times, or free up hardware for maintenance downtime.
In the sequence diagram, a process object requests for the threads. If thread is available then it is to be assigned to the process and if not available, process will wait for thread assignment. When the thread is assigned it will send the request to the processors for assigning the criti- cal section which are attached under the distributed computing system. If processor is available then it will search for the critical section and as per the availability of critical section the process is executed after getting the resources from the resource object and finally the output data is transferred into the memory and the Memory ob- ject sends the output to the Process object. After the completion of execution the Process object is terminated. The entire working of dynamic modeling is shown be- low.
The challenge for educators is to ensure that the range of materials and resources presented offers students the opportunity to choose and connect with information that resonates with and is relevant to them (a tool box of ideas) whilst ensuring they graduate with sound and current work-based knowledge. An example of this tool-box of ideas is provided in a pre-service course focusing on physical activity for young children. The course incorporates resources that help students make connections with course content by including personally designed videos on infant massage, parachute play, balloon play, relaxation methods and activities to support diversity (just to name a few). Other popular resources are podcasts, radio
The remaining part of this paper is organized as follows. In section 2, we introduce how to generate the figure set in order to summarize the characteristics of the Ehrenstein illusory contours. Then, we recorded the subjects’ psychological reaction of the figures by changing the parameters of each figure in section 3. In the section 4, we introduce our computational solution that sorts out the characteristics of the Ehrenstein illusory contours. Then, we use the experimental data of the section 3 to prove the rationality of our solution in section 4. In section 5, we make an assessment of the accuracy of the model for analysis. Finally, we make a conclusion in section 6.