Hybrid sampling on mutual information entropy-based clustering ensembles for optimizations

In this paper, we focus on the design of bivariate EDAs for discrete optimization problems and propose a new approach named HSMIEC. While the current EDAs require much time in the statistical learning process as the relationships among the variables are too complicated, we employ the Selfish gene theory (SG) in this approach, as well as a Mutual Information and Entropy based Cluster (MIEC) model is also set to optimize the probability distribution of the virtual population. This model uses a hybrid sampling method by considering both the clustering accuracy and clustering diversity and an incremental learning and resample scheme is also set to optimize the parameters of the correlations of the variables. Compared with several benchmark problems, our experimental results demonstrate that HSMIEC often performs better than some other EDAs, such as BMDA, COMIT, MIMIC and ECGA. © 2009 Elsevier B.V. All rights reserved.

A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty

Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty. © 2009 Springer Berlin Heidelberg.

Modelling e-business processes:a component-based simulation approach

With new and emerging e-business technologies to transform business processes, it is important to understand how those technologies will affect the performance of a business. Will the overall business process be cheaper, faster and more accurate or will a sub-optimal change have been implemented? The use of simulation to model the behaviour of business processes is well established, and it has been applied to e-business processes to understand their performance in terms of measures such as lead-time, cost and responsiveness. This paper introduces the concept of simulation components that enable simulation models of e-business processes to be built quickly from generic e-business templates. The paper demonstrates how these components were devised, as well as the results from their application through case studies.

Some clarifications on the DEA clustering approach

This paper clarifies the role of alternative optimal solutions in the clustering of multidimensional observations using data envelopment analysis (DEA). The paper shows that alternative optimal solutions corresponding to several units produce different groups with different sizes and different decision making units (DMUs) at each class. This implies that a specific DMU may be grouped into different clusters when the corresponding DEA model has multiple optimal solutions. © 2011 Elsevier B.V. All rights reserved.

An operational research-based integrated approach for mass evacuation planning of a city

Large-scale disasters are constantly occurring around the world, and in many cases evacuation of regions of city is needed. ‘Operational Research/Management Science’ (OR/MS) has been widely used in emergency planning for over five decades. Warning dissemination, evacuee transportation and shelter management are three ‘Evacuation Support Functions’ (ESF) generic to many hazards. This thesis has adopted a case study approach to illustrate the importance of integrated approach of evacuation planning and particularly the role of OR/MS models. In the warning dissemination phase, uncertainty in the household’s behaviour as ‘warning informants’ has been investigated along with uncertainties in the warning system. An agentbased model (ABM) was developed for ESF-1 with households as agents and ‘warning informants’ behaviour as the agent behaviour. The model was used to study warning dissemination effectiveness under various conditions of the official channel. In the transportation phase, uncertainties in the household’s behaviour such as departure time (a function of ESF-1), means of transport and destination have been. Households could evacuate as pedestrians, using car or evacuation buses. An ABM was developed to study the evacuation performance (measured in evacuation travel time). In this thesis, a holistic approach for planning the public evacuation shelters called ‘Shelter Information Management System’ (SIMS) has been developed. A generic allocation framework of was developed to available shelter capacity to the shelter demand by considering the evacuation travel time. This was formulated using integer programming. In the sheltering phase, the uncertainty in household shelter choices (either nearest/allocated/convenient) has been studied for its impact on allocation policies using sensitivity analyses. Using analyses from the models and detailed examination of household states from ‘warning to safety’, it was found that the three ESFs though sequential in time, however have lot of interdependencies from the perspective of evacuation planning. This thesis has illustrated an OR/MS based integrated approach including and beyond single ESF preparedness. The developed approach will help in understanding the inter-linkages of the three evacuation phases and preparing a multi-agency-based evacuation planning evacuation

A paradigm sensitive perspective on the ranking of accounting journals:a web-based survey approach

This paper reports the results of a web-based study of the perceptions of accounting journals in Australasia. Journal ranking studies have generally adopted citation techniques or used academics’ perceptions as the basis for assessing journal quality. Our research contributes to the existing literature by conducting a survey of academics in Australasia using a web-based instrument. The analysis indicates that the perceptions of the so-called “elite” accounting journals have become unsettled. The research highlights the emergence of more recent, alternative paradigm journals (CPA and AAAJ) as both highly ranking.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.

A three-level RFID-based automation approach to enhance network competitiveness

Today, the question of how to successfully reduce supply chain costs whilst increasing customer satisfaction continues to be the focus of many firms. It is noted in the literature that supply chain automation can increase flexibility whilst reducing inefficiencies. However, in the dynamic and process driven environment of distribution, there is the absence of a cohesive automation approach to guide companies in improving network competitiveness. This paper aims to address the gap in the literature by developing a three-level framework automation application approach with the assistance of radio frequency identification (RFID) technology and returnable transport equipment (RTE). The first level considers the automation of data retrieval and highlights the benefits of RFID. The second level consists of automating distribution processes such as unloading and assembling orders. As the labour is reduced with the introduction of RFID enabled robots, the balance between automation and labour is discussed. Finally, the third level is an analysis of the decision-making process at network points and the application of cognitive automation to objects. A distribution network scenario is formed and used to illustrate network reconfiguration at each level. The research pinpoints that RFID enabled RTE offers a viable tool to assist supply chain automation. Further research is proposed in particular, the area of cognitive automation to aide with decision-making.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

A rule-based approach to implicit emotion detection in text

Most research in the area of emotion detection in written text focused on detecting explicit expressions of emotions in text. In this paper, we present a rule-based pipeline approach for detecting implicit emotions in written text without emotion-bearing words based on the OCC Model. We have evaluated our approach on three different datasets with five emotion categories. Our results show that the proposed approach outperforms the lexicon matching method consistently across all the three datasets by a large margin of 17–30% in F-measure and gives competitive performance compared to a supervised classifier. In particular, when dealing with formal text which follows grammatical rules strictly, our approach gives an average F-measure of 82.7% on “Happy”, “Angry-Disgust” and “Sad”, even outperforming the supervised baseline by nearly 17% in F-measure. Our preliminary results show the feasibility of the approach for the task of implicit emotion detection in written text.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

Exploring the effectiveness of similarity-based visualisations for colour-based image retrieval

In April 2009, Google Images added a filter for narrowing search results by colour. Several other systems for searching image databases by colour were also released around this time. These colour-based image retrieval systems enable users to search image databases either by selecting colours from a graphical palette (i.e., query-by-colour), by drawing a representation of the colour layout sought (i.e., query-by-sketch), or both. It was comments left by readers of online articles describing these colour-based image retrieval systems that provided us with the inspiration for this research. We were surprised to learn that the underlying query-based technology used in colour-based image retrieval systems today remains remarkably similar to that of systems developed nearly two decades ago. Discovering this ageing retrieval approach, as well as uncovering a large user demographic requiring image search by colour, made us eager to research more effective approaches for colour-based image retrieval. In this thesis, we detail two user studies designed to compare the effectiveness of systems adopting similarity-based visualisations, query-based approaches, or a combination of both, for colour-based image retrieval. In contrast to query-based approaches, similarity-based visualisations display and arrange database images so that images with similar content are located closer together on screen than images with dissimilar content. This removes the need for queries, as users can instead visually explore the database using interactive navigation tools to retrieve images from the database. As we found existing evaluation approaches to be unreliable, we describe how we assessed and compared systems adopting similarity-based visualisations, query-based approaches, or both, meaningfully and systematically using our Mosaic Test - a user-based evaluation approach in which evaluation study participants complete an image mosaic of a predetermined target image using the colour-based image retrieval system under evaluation.

The mosaic test:measuring the effectiveness of colour-based image retrieval

A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants. © 2012 Springer Science+Business Media, LLC.

Statistical model of OFDMA cellular networks uplink interference using lognormal distribution

In this letter, we propose an analytical approach to model uplink intercell interference (ICI) in hexagonal grid based orthogonal frequency division multiple access (OFMDA) cellular networks. The key idea is that the uplink ICI from individual cells is approximated with a lognormal distribution with statistical parameters being determined analytically. Accordingly, the aggregated uplink ICI is approximated with another lognormal distribution and its statistical parameters can be determined from those of individual cells using Fenton-Wilkson method. Analytic expressions of uplink ICI are derived with two traditional frequency reuse schemes, namely integer frequency reuse schemes with factor 1 (IFR-1) and factor 3 (IFR-3). Uplink fractional power control and lognormal shadowing are modeled. System performances in terms of signal to interference plus noise ratio (SINR) and spectrum efficiency are also derived. The proposed model has been validated by simulations. © 2013 IEEE.

Managing enterprise resource planning and multi-organisational enterprise governance:a new contingency framework for the enterprisation of operations

This research has been undertaken to determine how successful multi-organisational enterprise strategy is reliant on the correct type of Enterprise Resource Planning (ERP) information systems being used. However there appears to be a dearth of research as regards strategic alignment between ERP systems development and multi-organisational enterprise governance as guidelines and frameworks to assist practitioners in making decision for multi-organisational collaboration supported by different types of ERP systems are still missing from theoretical and empirical perspectives. This calls for this research which investigates ERP systems development and emerging practices in the management of multi-organisational enterprises (i.e. parts of companies working with parts of other companies to deliver complex product-service systems) and identify how different ERP systems fit into different multi-organisational enterprise structures, in order to achieve sustainable competitive success. An empirical inductive study was conducted using the Grounded Theory-based methodological approach based on successful manufacturing and service companies in the UK and China. This involved an initial pre-study literature review, data collection via 48 semi-structured interviews with 8 companies delivering complex products and services across organisational boundaries whilst adopting ERP systems to support their collaborative business strategies – 4 cases cover printing, semiconductor manufacturing, and parcel distribution industries in the UK and 4 cases cover crane manufacturing, concrete production, and banking industries in China in order to form a set of 29 tentative propositions that have been validated via a questionnaire receiving 116 responses from 16 companies. The research has resulted in the consolidation of the validated propositions into a novel concept referred to as the ‘Dynamic Enterprise Reference Grid for ERP’ (DERG-ERP) which draws from multiple theoretical perspectives. The core of the DERG-ERP concept is a contingency management framework which indicates that different multi-organisational enterprise paradigms and the supporting ERP information systems are not the result of different strategies, but are best considered part of a strategic continuum with the same overall business purpose of multi-organisational cooperation. At different times and circumstances in a partnership lifecycle firms may prefer particular multi-organisational enterprise structures and the use of different types of ERP systems to satisfy business requirements. Thus the DERG-ERP concept helps decision makers in selecting, managing and co-developing the most appropriate multi-organistional enterprise strategy and its corresponding ERP systems by drawing on core competence, expected competitiveness, and information systems strategic capabilities as the main contingency factors. Specifically, this research suggests that traditional ERP(I) systems are associated with Vertically Integrated Enterprise (VIE); whilst ERPIIsystems can be correlated to Extended Enterprise (EE) requirements and ERPIII systems can best support the operations of Virtual Enterprise (VE). The contribution of this thesis is threefold. Firstly, this work contributes to a gap in the extant literature about the best fit between ERP system types and multi-organisational enterprise structure types; and proposes a new contingency framework – the DERG-ERP, which can be used to explain how and why enterprise managers need to change and adapt their ERP information systems in response to changing business and operational requirements. Secondly, with respect to a priori theoretical models, the new DERG-ERP has furthered multi-organisational enterprise management thinking by incorporating information system strategy, rather than purely focusing on strategy, structural, and operational aspects of enterprise design and management. Simultaneously, the DERG-ERP makes theoretical contributions to the current IS Strategy Formulation Model which does not explicitly address multi-organisational enterprise governance. Thirdly, this research clarifies and emphasises the new concept and ideas of future ERP systems (referred to as ERPIII) that are inadequately covered in the extant literature. The novel DERG-ERP concept and its elements have also been applied to 8 empirical cases to serve as a practical guide for ERP vendors, information systems management, and operations managers hoping to grow and sustain their competitive advantage with respect to effective enterprise strategy, enterprise structures, and ERP systems use; referred to in this thesis as the “enterprisation of operations”.