Dual-process action of exercise on appetite control : increase in orexigenic drive but improvement in meal-induced satiety

Background: Exercise could contribute to weight loss by altering the sensitivity of the appetite regulatory system. Objective: The aim of this study was to assess the effects of 12 wk of mandatory exercise on appetite control. Design: Fifty-eight overweight and obese men and women [mean (±SD) body mass index (in kg/m2) = 31.8 ± 4.5, age = 39.6 ± 9.8 y, and maximal oxygen intake = 29.1 ± 5.7 mL · kg–1 · min–1] completed 12 wk of supervised exercise in the laboratory. The exercise sessions were designed to expend 2500 kcal/wk. Subjective appetite sensations and the satiating efficiency of a fixed breakfast were compared at baseline (week 0) and at week 12. An Electronic Appetite Rating System was used to measure subjective appetite sensations immediately before and after the fixed breakfast in the immediate postprandial period and across the whole day. The satiety quotient of the breakfast was determined by calculating the change in appetite scores relative to the breakfast's energy content. Results: Despite large variability, there was a significant reduction in mean body weight (3.2 ± 3.6 kg), fat mass (3.2 ± 2.2 kg), and waist circumference (5.0 ± 3.2 cm) after 12 wk. The analysis showed that a reduction in body weight and body composition was accompanied by an increase in fasting hunger and in average hunger across the day (P < 0.0001). Paradoxically, the immediate and delayed satiety quotient of the breakfast also increased significantly (P < 0.05). Conclusions: These data show that the effect of exercise on appetite regulation involves at least 2 processes: an increase in the overall (orexigenic) drive to eat and a concomitant increase in the satiating efficiency of a fixed meal.

Improvement to Chinese information retrieval by incorporating word segmentation and query expansion

The increasing diversity of the Internet has created a vast number of multilingual resources on the Web. A huge number of these documents are written in various languages other than English. Consequently, the demand for searching in non-English languages is growing exponentially. It is desirable that a search engine can search for information over collections of documents in other languages. This research investigates the techniques for developing high-quality Chinese information retrieval systems. A distinctive feature of Chinese text is that a Chinese document is a sequence of Chinese characters with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose two approaches to deal with the problems. In the first approach, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach. In the second approach, we propose a novel query expansion method which applies text mining techniques in order to find the most relevant words to extend the query. Unlike most existing query expansion methods, which generally select the highly frequent indexing terms from the retrieved documents to expand the query. In our approach, we utilize text mining techniques to find patterns from the retrieved documents that highly correlate with the query term and then use the relevant words in the patterns to expand the original query. This research project develops and implements a Chinese information retrieval system for evaluating the proposed approaches. There are two stages in the experiments. The first stage is to investigate if high accuracy segmentation can make an improvement to Chinese information retrieval. In the second stage, a text mining based query expansion approach is implemented and a further experiment has been done to compare its performance with the standard Rocchio approach with the proposed text mining based query expansion method. The NTCIR5 Chinese collections are used in the experiments. The experiment results show that by incorporating the text mining based query expansion with the hybrid model, significant improvement has been achieved in both precision and recall assessments.

QoS-based web service composition accommodating inter-service dependencies using minimal-conflict , hill-climbing repair genetic algorithm

In the field of semantic grid, QoS-based Web service composition is an important problem. In semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the composition consider not only QoS properties of Web services, but also inter service dependencies and conflicts which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address the Web service composition optimization problem in the presence of domain constraints and inter service dependencies and conflicts. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.

Improvement of stability and load sharing in an autonomous microgrid using supplementary droop control loop

This paper investigates the problem of appropriate load sharing in an autonomous microgrid. High gain angle droop control ensures proper load sharing, especially under weak system conditions. However it has a negative impact on overall stability. Frequency domain modeling, eigenvalue analysis and time domain simulations are used to demonstrate this conflict. A supplementary loop is proposed around a conventional droop control of each DG converter to stabilize the system while using high angle droop gains. Control loops are based on local power measurement and modulation of the d-axis voltage reference of each converter. Coordinated design of supplementary control loops for each DG is formulated as a parameter optimization problem and solved using an evolutionary technique. The sup-plementary droop control loop is shown to stabilize the system for a range of operating conditions while ensuring satisfactory load sharing.

Examining the role of human resource management in continuous improvement

The objective of this paper is to take a first step in developing a theoretical framework describing the role of HRM in successful CI, based on the current literature from both fields. To this end, elements from the CI Maturity Model and a framework depicting the role of HRM in innovation serve as a foundation for examining how specific bundles of HRM practices utilised during different phases of the CI implementation process may contribute to sustained organisational and enhanced operational performance. The primary contribution of this paper is theoretical; however, the framework has practical value in that it suggests important relationships between HRM practices and behaviours necessary for successful CI. A preliminary test of the framework in an empirical setting is summarised at the conclusion of this paper, where a number of possible research avenues are also suggested.

Regulatory approaches to genetic testing in insurance

Rapid advancements in the field of genetic science have engendered considerable debate, speculation, misinformation and legislative action worldwide. While programs such as the Human Genome Project bring the prospect of seemingly miraculous medical advancements within imminent reach, they also create the potential for significant invasions of traditional areas of privacy and human dignity through laying the potential foundation for new forms of discrimination in insurance, employment and immigration regulation. The insurance industry, which has of course, traditionally been premised on discrimination as part of its underwriting process, is proving to be the frontline of this regulatory battle with extensive legislation, guidelines and debate marking its progress.

Performance measurement and continuous improvement : are they linked to manufacturing strategy?

To maintain or achieve competitiveness and profitability, a manufacturing firm or enterprise must respond to a range of challenges, including rapid improvements in technology; declining employment and output; globalisation of markets and environmental requirements. In addition, substantial changes in government policy have had important impacts in many countries, as have the increasing levels of global trade. Manufacturing enterprises need to have a clear understanding of what their customers want and why customers purchase their products rather than purchase from their competitors. They need to fully understand the aims of the business in terms of its customers, market segments, product attributes, geographical markets and performance. Continuous Improvement (CI) methods have become widely adopted and regarded as providing an important component of increased company competitiveness. This article examines the extent to which continuous improvement activities have contributed to the different areas of business performance.

Improved joint control using a genetic algorithm for a humanoid robot

This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.

Contribution of cross-functional teams to the improvement in operational performance

Purpose: The purpose of this paper is to explore the role of cross-functional teams in the alignment between system effectiveness and operational effectiveness after the implementation of enterprise information systems (EIS). In addition, it aims to explore the contribution of cross-functional teams to improvement in operational performance. ---------- Design/methodology/approach: The research uses a combination of qualitative and quantitative methods, in a two-stage methodological approach, to investigate the influence of cross-functional teams on the alignment between system effectiveness and operational effectiveness and the impact of the stated alignment on the improvement in operational performance. ---------- Findings: Initial findings suggest that factors stemming from system effectiveness and the performance objectives stemming from operational effectiveness are important and significantly well correlated factors that promote the alignment between the effectiveness of technological implementation and the effectiveness of operations. In addition, confirmatory factor analysis has been used to find the structural relationships and provide explanations for the stated alignment and the contribution of cross-functional teams to the improvement in operational performance. ---------- Research limitations/implications: The principal limitation of this study is its small sample size. ---------- Practical implications: Cross-functional teams have been used by many organisations as a way of involving expertise from different functional areas in the implementation of innovative technologies. An appropriate use of the dimensions that emerged from this research, in the context of cross-functional teams, will assist organisations to properly utilise cross-functional teams with the aim of improving operational performance. ---------- Originality/value: The paper presents a new approach to measure the effectiveness of EIS implementation by adding new dimensions to measure it.

Improved correlation-based modal strain energy method for global damage detection of truss bridge structures

The previous investigations have shown that the modal strain energy correlation method, MSEC, could successfully identify the damage of truss bridge structures. However, it has to incorporate the sensitivity matrix to estimate damage and is not reliable in certain damage detection cases. This paper presents an improved MSEC method where the prediction of modal strain energy change vector is differently obtained by running the eigensolutions on-line in optimisation iterations. The particular trail damage treatment group maximising the fitness function close to unity is identified as the detected damage location. This improvement is then compared with the original MSEC method along with other typical correlation-based methods on the finite element model of a simple truss bridge. The contributions to damage detection accuracy of each considered mode is also weighed and discussed. The iterative searching process is operated by using genetic algorithm. The results demonstrate that the improved MSEC method suffices the demand in detecting the damage of truss bridge structures, even when noised measurement is considered.

A penalty-based genetic algorithm for the composite SaaS placement problem in the cloud

Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition

Web service composition is an important problem in web service based systems. It is about how to build a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different QoS values. Thus, a significant research problem in web service composition is how to select a web service implementation for each of the web services such that the composite web service gives the best overall performance. This is so-called optimal web service selection problem. There may be mutual constraints between some web service implementations. Sometimes when an implementation is selected for one web service, a particular implementation for another web service must be selected. This is so called dependency constraint. Sometimes when an implementation for one web service is selected, a set of implementations for another web service must be excluded in the web service composition. This is so called conflict constraint. Thus, the optimal web service selection is a typical constrained ombinatorial optimization problem from the computational point of view. This paper proposes a new hybrid genetic algorithm for the optimal web service selection problem. The hybrid genetic algorithm has been implemented and evaluated. The evaluation results have shown that the hybrid genetic algorithm outperforms other two existing genetic algorithms when the number of web services and the number of constraints are large.

Room for improvement : hotel giant resorts to Six Sigma to improve operations

Six Sigma provides a framework for quality improvement and business excellence. Introduced in the 1980s in manufacturing, the concept of Six Sigma has gained popularity in service organizations. After initial success in healthcare and banking, Six Sigma has gradually gained traction in other types of service industries, including hotels and lodging. Starwood Hotels and Resorts was the first hospitality giant to embrace Six Sigma. In 2001, Starwood adopted the method to develop innovative, customer-focused solutions and to transfer these solutions throughout the global organization. To analyze Starwood's use of Six Sigma, the authors collected data from articles, interviews, presentations and speeches published in magazines, newspapers and Web sites. This provided details to corroborate information, and they also made inferences from these sources. Financial metrics can explain the success of Six Sigma in any organization. There was no shortage of examples of Starwood's success resulting from Six Sigma project metrics uncovered during the research.