21 research outputs found

    A novel population-based local search for nurse rostering problem

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    Population-based approaches regularly are better than single based (local search) approaches in exploring the search space. However, the drawback of population-based approaches is in exploiting the search space. Several hybrid approaches have proven their efficiency through different domains of optimization problems by incorporating and integrating the strength of population and local search approaches. Meanwhile, hybrid methods have a drawback of increasing the parameter tuning. Recently, population-based local search was proposed for a university course-timetabling problem with fewer parameters than existing approaches, the proposed approach proves its effectiveness. The proposed approach employs two operators to intensify and diversify the search space. The first operator is applied to a single solution, while the second is applied for all solutions. This paper aims to investigate the performance of population-based local search for the nurse rostering problem. The INRC2010 database with a dataset composed of 69 instances is used to test the performance of PB-LS. A comparison was made between the performance of PB-LS and other existing approaches in the literature. Results show good performances of proposed approach compared to other approaches, where population-based local search provided best results in 55 cases over 69 instances used in experiments

    THE INCIDENCE AND NATURE OF NON-CONTACT INJURIES IN U.S. WOMEN’S RUGBY-7S

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    The aim of this study was to prospectively determine non-contact injury incidence and mechanisms among U.S. amateur women’s Rugby-7s. Non-contact injuries occurred frequently among the U.S. women population (26.5/1000ph; 29% of all injuries; n=167). The incidence of non-contact injuries occurred at similar rates among backs (58%, 23.9/1000ph, CI:19.1-29.6) and forwards (42%, 19.3/1000ph, CI:14.4-25.3; RR:1.04, p=0.816). Non-contact injuries resulted in 58.4 mean days absence from play. This study demonstrates a greater proportion of match injuries among U.S. amateur women Rugby-7 participants were related to non-contact mechanism when compared to International women participants. Therefore, U.S. women Rugby-7 players would benefit from prevention programs to minimize non-contact injury risks

    THE PREVALENCE AND CAUSE OF NON-CONTACT INJURY MECHANISMS IN U.S. MEN’S RUGBY-7S

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    The aim of this study was to prospectively report non-contact injury incidence and causes in U.S. men’s Rugby-7s players (n=446) over 2010-2015, using the Rugby Injury Survey & Evaluation (RISE) methodology. Non-contact injuries (time-loss 25%; medical attention 75%) had higher rates among backs (62%; 28.4/1000ph) than forwards (38%; 23.2/1000ph; RR:1.22; p=0.05). Non-contact injuries resulted in an average of 48.7days (d) absence from sport (classic non-contact 48.1d; other non-contact 77.0d). Acute injuries (85%) were most common during attempts to elude a tackle (31%) and in running/open play (48% overall; from 35% in 2010, 41% in 2011, 52% in 2012, 43% in 2013, 46% in 2014, 70% in 2015). Most non-contact injuries (44%) occurred during the first two tournament matches. These results provide much needed data on Rugby-7s, impacting emerging countries

    Techno-economical study of solar water pumping system: optimum design, evaluation, and comparison

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    Solar water pumping systems are fundamental entities for water transmission and storage purposes whether it is has been used in irrigation or residential applications. The use of photovoltaic (PV) panels to support the electrical requirements of these pumping systems has been executed globally for a long time. However, introducing optimization sizing techniques to such systems can benefit the end-user by saving money, energy, and time. This paper proposed solar water pumping systems optimum design for Oman. The design, and evaluation have been carried out through intuitive, and numerical methods. Based on hourly meteorological data, the simulation used both HOMER software and numerical method using MATLAB code to find the optimum design. The selected location ambient temperature variance from 12.8 °C to 44.5 °C over the year and maximum insolation is 7.45 kWh/m2/day, respectively. The simulation results found the average energy generated, annual yield factor, and a capacity factor of the proposed system is 2.9 kWh, 2016.66 kWh/kWp, and 22.97%, respectively, for a 0.81 kW water pump, which is encouraging compared with similar studied systems. The capital cost of the system is worth it, and the cost of energy has compared with other systems in the literature. The comparison shows the cost of energy to be in favor of the MATLAB simulation results with around 0.24 USD/kWh. The results show successful operation and performance parameters, along with cost evaluation, which proves that PV water pumping systems are promising in Oman

    A Feature Selection Technique for Hand Gesture Recognition in Music Display System

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    A novel trust measurement method based on certified belief in strength for a multi-agent classifier system

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    A novel trust measurement method, namely, certified belief in strength (CBS), for a multi-agent classifier system (MACS) is proposed in this paper. The CBS method aims to improve the performance of the constituent agents of the MACS, viz., the fuzzy min-max (FMM) neural network classifier. Trust measurement is accomplished using reputation and strength of the constituent agents. Trust is built from strong elements that are associated with the FMM agents, allowing the CBS method to improve the performance of the MACS. An auction procedure based on the sealed bid, namely, the first price method, is adopted for the MACS in determining the winning agent. The effectiveness of the CBS method and the bond (based on trust) is verified by using a number of benchmark data sets. The results demonstrate that the proposed MACS-CBS model is able to produce better accuracy and stability as compared with those from other existing methods. © 2012 Springer-Verlag London

    Application of the Fuzzy Min-Max Neural Networks to Medical Diagnosis

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    A Multiple Classification Method Based on the D-S Evidence Theory

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