Collaborative personal profiling for web service ranking and recommendation

Web service is one of the most fundamental technologies in implementing service oriented architecture (SOA) based applications. One essential challenge related to web service is to find suitable candidates with regard to web service consumer’s requests, which is normally called web service discovery. During a web service discovery protocol, it is expected that the consumer will find it hard to distinguish which ones are more suitable in the retrieval set, thereby making selection of web services a critical task. In this paper, inspired by the idea that the service composition pattern is significant hint for service selection, a personal profiling mechanism is proposed to improve ranking and recommendation performance. Since service selection is highly dependent on the composition process, personal knowledge is accumulated from previous service composition process and shared via collaborative filtering where a set of users with similar interest will be firstly identified. Afterwards a web service re-ranking mechanism is employed for personalised recommendation. Experimental studies are conduced and analysed to demonstrate the promising potential of this research.

Service bid comparisons by fuzzy ranking in open railway market timetabling

In an open railway access market, the Infrastructure Provider (IP), upon the receipts of service bids from the Train Service Providers (TSPs), assigns track access rights according to its own business objectives and the merits of the bids; and produces the train service timetable through negotiations. In practice, IP chooses to negotiate with the TSPs one by one in such a sequence that IP optimizes its objectives. The TSP bids are usually very complicated, containing a large number of parameters in different natures. It is a difficult task even for an expert to give a priority sequence for negotiations from the contents of the bids. This study proposes the application of fuzzy ranking method to compare and prioritize the TSP bids in order to produce a negotiation sequence. The results of this study allow investigations on the behaviors of the stakeholders in bid preparation and negotiation, as well as evaluation of service quality in the open railway market.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

U.S. Postal Service : diversity in the Postal Career Executive Service : report to the Ranking Minority Member, Subcommittee on the Postal Service, Committee on Government Reform, House of Representatives /

"B-283761"--P. 1.

DOE management : selected information on the workforce at DOE's Livermore laboratory : report to the ranking minority member, Subcommittee on Post Office and Civil Service, Committee on Governmental Affairs, U.S. Senate /

"B-259941"--P. 1.

Strong internal controls at service delivery level will help prevent CETA-type fraud and abuse in Job Training Partnership Act programs : report to Senator Sam Nunn, ranking minority member, Permanent Subcommittee on Investigations, Senate Committee on Governmental Affairs /

"B-215774"--Preliminary p.

Federal personnel management : views on selected NPR human resource recommendations : briefing report to the Ranking Minority Member, Subcommittee on Civil Service, Committee on Government Reform and Oversight, House of Representatives /

"B-265839"--P. 1.

Employee involvement : issues for agencies to consider in designing and implementing programs : report to the Ranking Minority Member, Subcommittee on Federal Services, Post Office, and Civil Service, Committee on Governmental Affairs, U.S. Senate /

"May 1988."

Investigation of sensitivity based load ranking with composite load model in power system

Load modeling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is through parametric sensitivity analysis. Load ranking provides an effective measure of such impact. Traditionally, load ranking is based on either static or dynamic load model alone. In this paper, composite load model based load ranking framework is proposed. It enables comprehensive investigation into load modeling impacts on system stability considering the dynamic interactions between load and system dynamics. The impact of load composition on the overall sensitivity and therefore on ranking of the load is also investigated. Dynamic simulations are performed to further elucidate the results obtained through sensitivity based load ranking approach.

Spam filtering based on preference ranking

When the average number of spam messages received is continually increasing exponentially, both the Internet service provider and the end user suffer. The lack of an efficient solution may threaten the usability of the email as a communication means. In this paper we present a filtering mechanism applying the idea of preference ranking. This filtering mechanism will distinguish spam emails from other email on the Internet. The preference ranking gives the similarity values for nominated emails and spam emails specified by users, so that the ISP/end users can deal with spam emails at filtering points. We designed three filtering points to classify nominated emails into spam email, unsure email and legitimate email. This filtering mechanism can be applied on both middleware and at the client-side. The experiments show that high precision, recall and TCR (total cost ratio) of spam emails can be predicted for the preference based filtering mechanisms.

Synthetic evaluation method for bridge priority ranking

In order to maintain the transportation operation, proper monitoring systems should be established on road structures, especially bridges. Since these systems need enormous investments, only a part of bridges should be equipped. Thus, the priorities of the bridges should be ranked. In this paper, a method based on two-level synthetic evaluation is proposed. First, the importance of each bridge is analyzed through the economic analysis. Six factors are considered for the bridges in a network, including construction cost, service duration, length, location importance coefficient, traffic volume, and reconstruction time. Second, the safety condition of the bridge is evaluated by using improved entropy method (IEM) which combines subjective weight with objective entropy weight. Five indices are incorporated in this step, i.e., design and construction condition, technical condition, level of overloading, hazard of wind and earthquake and environmental factors. Finally, the priorities of all the bridge in one network can be ranked and classified through a judge matrix. To demonstrate the effectiveness of the proposed method, a main highway including 16 bridges is taken as an illustrative example. The results show that the bridges can be ranked and classified quickly by using the proposed method.

Second-year pre-service teachers’ responses to proportional reasoning test items

A recent international study of pre-service teachers identified that proportional reasoning was problematic for pre-service teachers. Proportional reasoning is an important topic in the middle years of schooling and therefore it is critical that teachers understand this topic and can rely on their Mathematical Content Knowledge (MCK) when teaching. The focus of this paper is second-year Australian primary pre-service teachers’ MCK of real number items related to ratio, rate, proportion and proportional reasoning. This paper reports on strengths and weakness of pre-service teachers’ MCK when responding to test items; including a method suitable for analysing responses to five items and ranked by three levels of difficulty. The results revealed insights into their correct methods of solutions and common incorrect responses, identifying difficulty, where multiplication and division were required. The method of coding test items by difficulty ranking may assist with developing an appropriate learning trajectory, which will assist pre-service teachers develop their MCK of this and other difficult topics.