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This New Articles Channel contents the latest articles published in Inderscience's distinguished academic, scientific and professional journals.


Innovation management - current trends and future directions
Innovation management as a field has gained ascendancy globally as a way for companies to compete and advance in the global marketplace. Despite the increased interest in innovation management there is still debate about its definition, historical development and future research directions. The aim of this paper is to analyse the literature on innovation management by conducting a bibliometric analysis, which will help researchers ascertain appropriate meanings and usages of the field. The paper analyses the innovation management in three time periods, which includes a discussion and examination of the seminal papers in this area of research. Future suggestions for innovation management researchers are given that highlight the growing complexity but dynamism of this unique field of study.

Customers and service providers in business ecosystem front-end - case study of health and well-being campus
The business ecosystem is a co-evolving, self-organised constellation. By examining the case of a health and well-being campus, we describe how end customers' requirements can be defined based on service preferences. During ecosystem initiation these requirements help to identify a set of core service providers. The research proposes that early customer and service provider involvement during the built environment project's front-end enhances the ecosystem's capability to learn. The resulting five-step model clarifies key customers' profiles and how their preferences help to scope the ecosystem and the project implementing it. The model categorises customers based on their capabilities and motivation. The research provides innovative knowledge on how to orchestrate a built environment project front-end and how to maximise ecosystem value potential. The results emphasise early customer and service provider involvement. The research also indicates a need to increase understanding of an ecosystem's initial value creation. In addition, the findings highlight the central actor's role in ecosystem initiation.

Using QR-Code in a green technology module to foster motivation and independent learning
Green technology education is a process of inculcating awareness and informing people about the interdependency and fragility of life on earth. Exploitation of the earth's resources and abuse of the environment is a significant problem that must be addressed at all levels of society. Thus, the purpose of this research is to develop and test a blended learning module on green technology using QR-Codes to enhance students' motivation and independent learning. The study used an experimental approach designed to investigate the effectiveness of the module, involving 103 students that were divided into two treatment groups and one control group. Students who were taught using the blended learning module showed higher achievement scores with significant improvement in learning motivation and independent learning skills. This study has proven that the blended learning module is user-friendly and makes learning and referencing easy and interesting.

Analysis and formulation of green IT implementation strategy, its driving and inhibiting factors in organisations in Indonesia
Balancing economic and environmental activities is an important issue for organisations. Green IT has emerged as a solution towards the problem. This research attempts to measure the maturity of green IT in organisations in Indonesia based on the G-readiness model and also to identify drivers of and inhibitors to its implementation. Then, it tries to identify strategy for organisation and government to enhance green IT adoption. This was done by conducting a questionnaire survey to IT workers from various companies in Indonesia. The results show the maturity is at medium level and that it focuses on energy consumption efficiency. Furthermore, economic factors, such as improving brand image and reducing operational cost of IT function, are identified as main drivers. In addition, internal factor, namely, lack of leadership was found to be the main inhibitor. Additionally, it is also revealed that government support in the form of incentives and regulations are necessary.

Supporting innovation in technology-enhanced learning: a stakeholder-based open approach
This paper explores the concept of innovation in technology-enhanced learning (TEL) and proposes a model to support innovation in the area of TEL. This model has emerged from the HoTEL project, a support action funded by EU's FP7. The paper first provides a brief summary of innovation models emerging from research and then moves to an analysis of the key elements, dynamics and dimensions that need be considered in order to develop a model supporting innovation specific to the TEL domain. The HoTEL innovation support model is then presented as a new way for supporting innovation adoption and mainstreaming within the field. Such a model is based on the concept of open innovation and advocates the direct involvement of all key stakeholders in the innovation process and their active role in considering all the strategic elements (networking, partnerships, support, user engagement, etc.) necessary for meaningful and effective innovation in TEL.

Development of a blended online and offline learning model with think-pair-share collaborative learning and student team's achievement division competition
Object-oriented analysis and design courses have been considered as the primary paradigms in computer science and information technology curricula, and are traditionally taught face-to-face (F2F). However, the teaching content only comes from the teacher, which may lead to difficulties in following the deep object orientation concept. In this study, a combination of collaborative and blended teaching is presented. In the initial stage, interviews and questionnaires were employed to collect data from experts based on the Delphi research technique, and from this the initial learning model was developed. This initial model was then evaluated by nine experts and the results were used to adjust the learning model. The final model consisted of four main procedures; namely the: 1) preparation stage; 2) introduction; 3) blended on and offline teaching procedure; 4) summary and learning achievement evaluation. Application of the learning model to a sample group resulted in significantly higher learning achievements.

A method study on the value chain optimisation of tourism industry based on big data
The increased demand promotes the development of tourism industry, big data has brought new method for the tourism industry to update value chain and raise industrial development. In this paper, we clarify the definition and characteristics of big data, talking about shaping and upgrading the tourism industry value chain. The internal and external value chain of tourism industry under big data is analysed. Then we put forward the method construction and development countermeasures of tourism industry based on big data.

Gradient vector flow combined saliency analysis for active contours
Image segmentation is one of the key technologies in digital image processing. Gradient vector flow (GVF) active contours model is one of important methods for image segmentation. But GVF method could not deal with complex natural images efficiently. In this paper, a new active contours algorithm is proposed. The proposed algorithm uses the advantage of saliency model in distinguishing objects and background to increasing the ability of GVF method to segment complex images. Experiment results on natural images show the better performances of proposed method compared with the tradition GVF method.

Research on precision marketing data source system based on big data
Under the big data, companies can apply data mining and application to accurately grasp the market changes and customer needs, and then adjust the products and services to enhance the professional and long-term development of enterprises. This paper combined with precision marketing data source system based on big data, research around precision marketing connotation and ideological, and enterprise applications around big data, introducing data standardisation and quality of the model, find a basic method to promote data standardisation, thus to provide reference for constructing data source system based on big data.

A semi-supervised locally linear embedding spectral clustering algorithm
Many practical problems can be attributed to the clustering problem. Spectral clustering algorithm can be clustered in any shape of space, and obtain the global optimal solution. Based on the classical Ng-Jordan-Weiss (NJW) algorithm, utilising the supervision information to guide the clustering process, the result of clustering is more accurate. Meanwhile, combined the manifold learning with semi-supervised spectral clustering algorithm, and the data dimension will reduce based on locally linear embedding (LLE). Based on the heuristic thinking, calculated distance matrix, a reasonable number of nearest neighbours could be funded, thus we achieve the purpose of dimension reduction. Moreover, clustering based on reduced dimension data, the same clustering results as the original data could be obtained. Experimental results have shown that this algorithm could achieve better clustering effect on artificial datasets and real datasets.

Improved adaptive multi-objective particle swarm algorithm under big data
Boundary handling and the global best guiders' selection are of significance to the performance of the multi-objective particle swarm algorithm. Considering the different characteristics of methods of operation, an improved multi-objective adaptive particle swarm optimisation (IMAPSO) was proposed in this paper. When the algorithm falls into local optimum, start crossover and mutation; when the algorithm's convergence stagnates, switch the boundary handling operator between the truncation and the exponential distribution truncation methods; when the diversity of algorithm has not improved in a given duration, switch the two operations of trim boundary handling and exponential distribution and the simulation results of the standard test functions demonstrate the effectiveness of the algorithm proposed in this paper.

Sparsity constrained model for the semantic features selection
Predicting brain activity associated with concrete concepts has been attracted wide attention in brain imaging studies. The main task is to construct a computational model for the link between the stimuli and the brain image. However, the ordinary regression model cannot make the desired selection among the semantic features due to the small sample size problem. In this paper, we propose a sparsity constrained model to automatically choose the relevant semantic features. Specifically, we explicitly constrain the number of semantic features associated with the individual voxels. The motivation is based on the fact that the responses of a voxel to the stimuli can only be explained by a limited number of neuron activity bases. The experimental results on predicting brain images show the effectiveness of the proposed approach, as well as meaningful representation of the concepts.

Structured sparsity model with spatial similarity regularisation for semantic feature selection
In the prediction of brain activity associated with concrete concepts, the main task is to construct a computational model to reveal the neural basis of the concepts. However, the ordinary regression model cannot select desired semantic features and easily over-fitting. To address these problems, in this paper, we propose a structured sparsity model to automatically choose the relevant semantic features by exploiting the sparsity of responses and the spatial relationships between the voxels. Specifically, we require the number of the non-zero responses to be sparse and the responses that two voxels are nearby in the brain to be similar. The constraints do not only regularise the model fitting but also have an interpretation in terms of brain hemodynamics. The experimental results on predicting brain images show the effectiveness of the proposed approach, as well as improved interpretability.

Delay-dependent stability analysis of convection-diffusion equations with delay
This paper is concerned with the delay-dependent stability analysis of the one-dimensional and two-dimensional convection-diffusion equations with time delay. Some sufficient and necessary conditions for the asymptotical stability of the equations are proposed. These results lay the foundation for the numerical stability analysis of such kinds of equations.

Flexible simulations of complex networks in OpenStack clouds
This paper describes a flexible software architecture aimed at performing simulations of complex networks on cloud computing environment based on OpenStack. The kernel of the architecture consists of ComplexSim, a C-based software simulator of complex networks composed of two different layers: the Parallel Simulation Kernel is devoted to manage event-driven simulations on SMP systems through a set of API calls useful to schedule tasks and events; on the other hand, API of the Complex Network Data & Runtime is used to define the complex network in terms of the graph of entities and related user-defined attributes, as well as the runtime behaviour. Two additional components provide the necessary automation to configure, deploy and execute a set of simulations in OpenStack clouds: the Cs-Generator allows to generate any set of user-defined directives, as well as directives for the engine; Cs-CloudRuntime is the component devoted to run the user-defined set of simulations in an OpenStack cloud, i.e. VMs preparation, deployment and execution, as well as collection of results.

A new inter-cloud service-level guarantee protocol applied to space missions
Nowadays, the term cloud computing often falsely assumes the availability of an unlimited pool of resources. On the contrary, if a cloud provider reaches its limits, it may pose the risk of breaking their service level agreement (SLA). Space agencies could start using the cloud computing model within their IT infrastructure with multiple ground control points around the world to reduce the cost. An inter-cloud communication protocol with a guarantee of the service level will significantly reduce the cost if each ground control segment is considered as a cloud provider. This paper outlines a new protocol that was developed to take into consideration the end-to-end service-level guarantee. The protocol defines new structures and functionalities instead of the commonly used BGP as a baseline. The paper presents the results of a performance evaluation study concerning the convergence time and the data overhead as well as the ability of the protocol to support any domain-specific services. The results are highly positive, showing the scalability of the solution. The application of our proposal within the space industry also proved to be a suitable means for experimentation of the protocol.

SLAs for cloud applications: agreement protocol and REST-based implementation
Users with critical data are still reluctant to move apps and data to commercial clouds, showing a substantial lack of trust in providers. Possible risks linked to availability, performance and security may be mitigated by the adoption of Service Level Agreements (SLAs) established among cloud service providers and their customers. This paper presents the design of services for the automatic management of cloud-oriented SLAs by means of a REST-based API. The API is exposed by an SLA Manager component that can be easily integrated into existing cloud applications, platforms and infrastructures, in order to support SLA-based cloud services delivery. Its functionalities have been designed according to an extended version of the agreement protocol state diagram proposed by the WS-Agreement standard, which takes explicitly into account negotiation, remediation and renegotiation issues and is compliant with all the active standards on security.

A study of comparative clustering of EU countries using the DBSCAN and k-means techniques within the theoretical framework of systemic geopolitical analysis
As a geographical method of analysing power redistribution, Systemic Geopolitical Analysis (according to Ioannis Th. Mazis theoretical basis) proposes a multi-dimensional, interdisciplinary research pattern, which embraces economic, cultural, political and defensive facts. The amount of data produced combining these attributes is extremely large and complex. One of the solutions to explore and analyse this data is clustering it. In this work, two clustering algorithms were used, namely DBSCAN and the k-means techniques both of which cluster data according to its characteristics. While DBSCAN groups data based on the minimum size of participating objects per cluster and the minimum required distance between them, k-means clusters the data objects according the pre-desired number of groups. Thus, since the two methods use different roads to group the data objects, they form different clusters but each one has its importance depending on the characteristics of the applied method. As a result, in this work a comparative study is presented.

A smart storage optimisation technique on the cloud
This paper is an extension to a recent work on enhancing load balancing and optimising storage consumption on the cloud. Our methodology, called ssCloud (Smart Storage Cloud), is based on methods designed to enhance the load balancing in concurrent file download techniques on the cloud using a collaborative dual direction technique. In this paper, we show how ssCloud operates in both the upload and download phases for providing Data as a Service (DaaS) on the cloud. Our goal is to reduce the amount of storage consumed on the cloud while providing a fast and efficient download time for the cloud clients. This is done by having two separate cloud interfaces, one for download requests (load balancing module) and another for upload requests, which involves partitioning and saving files on the available cloud servers (FileController). We also provide an analysis of ssCloud performance and compare it to other reviewed storage optimisation techniques on the cloud by simulating the cloud environment and comparing service times.

Cognitive application area networks
Each software application, from e-commerce to a complex machine learning algorithm, is composed of a set of distributed, interacting components that collaborate to accomplish a common goal. While this application goal or the intent is well-defined and decomposed into sub-tasks to be embedded (à la Turing machine) in each composed component, the quality of the application (in terms of performance, responsiveness, availability or robustness) is strongly influenced by how and where the components are executed. This kind of information, including the meta-knowledge of the intent of the algorithm, the association of specific component to a specific machine, the temporal evolution and exception handling when the application deviates from its intent, is outside the application design and expressed in terms of non-functional requirements. In this paper, we describe how it is possible to exploit these non-functional requirements to effectively enforce the application intent while the computation is still in progress.

Combining reputation and QoS measures to improve cloud service composition
In order to provide a wide range of composite Cloud services, providers need to establish mutual agreements on large-scale distributed multi-cloud scenario. In such a way, providers can compose effective and efficient service workflows by taking resources of their own competitors and gain the capability to satisfy unexpected workload peaks. In this paper, we propose a reputation-based model capable to support the composition of complex Cloud services by taking into account both costs and measures of QoS which are collected by measuring both system measures and reputation feedbacks provided by the customers. The proposed model has been validated by a set of experimental results obtained by means of a number of simulations.

Middleware, framework and novel computing models for grid and cloud service orchestration
Highly scalable, resilient commodity hardware along with the availability of huge amounts of data allow consumers and companies to access to a wide range of high-value services through a pay-per-use, pay-as-you-go model. The increasing need for intelligent services at large scale is bringing providers to optimise the use of resources in order to meet the increasing web-scale demand. Programming models are evolving to address the high complexity of service composition, which need resiliency and efficiency. Algorithms and technologies for intelligent orchestration allow multiple owners of cloud and grid infrastructures to satisfy customer requirements and business constraints. We assist in the development of new architectures, frameworks, middlewares and computing models, as well as innovative applications, aimed at supporting scientists and business analysts in the development of unified computing frameworks and data analysis at large scale. This paper summarises a number of contributions given in the area of distributed cloud and grid computing, with particular emphasis on service orchestrations and emergent applications for high-value services.

MAROQ: a resource allocation model driven through quality of experience
The trend of grid computing available on the internet has generated challenges to the allocation of resources provided by this type of environment. Many of these challenges can be solved by the quality of experience paradigm that takes into account several context parameters. In this context, this paper presents the proposal of a new quality of experience-driven model for resource allocation for grids named MAROQ. We detail an experimental evaluation using context information with MAROQ that presents improvements of 7.46% on the average execution time of tasks.

Introducing welding manufacturability in a multidisciplinary platform for the evaluation of conceptual aircraft engine components
Computer simulations play an important role for evaluating designs in an early stages leading to that more informed decisions can be taken and thereby reducing the risk of costly re-design. In this paper, a platform currently in operation at an aeronautical company for doing extensive automated multi-objective design parameter studies on conceptual designs of aircraft engine components is studied. In the paper, an extension of the capability of the platform into making a rule-based evaluation of the welding manufacturability of the conceptual designs is proposed. The extension is tested by a prototype system at the air-craft manufacturer showing the relation between the design parameters and the manufacturability of the components. The results are presented as a manufacturability index showing what trade-offs with other performance criteria of the engine that can be made. It is shown that the manufacturability evaluation can be integrated in the knowledge value stream and supports a set-based concurrent engineering approach in the company.

Framework to automate mechanical-system design using multiple product-models and assembly feature technology
A standard method-of-work, employed by manufacturers of engineering-to-order (ETO) products, involves primarily a knowledge-based engineering (KBE) system and a 3D mechanical CAD system. The KBE system includes technical guidelines, design rules, facts, 'best practices' and even a company's commercial and business rules. Thus, when a client places a new order, the manufacturer's aim is to employ its KBE system and (hopefully) minimal user involvement to more-or-less automatically produce the complete 3D CAD model and technical drawings of the requested product. The present paper proposes a solution method for this KBE-CAD transformation problem by using two product models, the schematic assembly model (SAM) and the intermediate assembly model (IAM), in this manner: KBE-SAM-IAM-CAD. The SAM is designed to fully employ all sorts of information available in the KBE system, and incorporate that either in the list of 'SAM components' or in the related 'SAM connection rules'. Then, the IAM translates this 'SAM model' into 3D part models and assembly features, in a manner that production of the final 3D mechanical-CAD model is automatic. This paper also describes and demonstrates a complete implementation of the above KBE-SAM-IAM-CAD methodology in a major industry.

An approach to improve implementation of PLM solution in food industry - case study of Poult Group
The food industry has a unique role in all countries' economies since it is essential to its people's health. This paper focuses on this important sector. The objective is to identify the main difficulties in the implementation phase of the product lifecycle management (PLM) solution in the design phase. It proposes an approach that could drive and support food companies to make specific and strategic decisions. This work starts with an analysis of the problems associated with the deployment of a PLM solution. Furthermore, this analysis allows the authors to propose an approach to select a PLM solution and to anticipate its deployment in a food company. The purpose of this approach is to increase the level of knowledge of the PLM solution in the food industry and to improve the new product development (NPD) process of the companies operating in the food industry. In this context, a specific industrial case (Poult case study) is described. In conclusion, this study gives a first theoretical framework which can help companies utilise PLM effectively by understanding the context in which they are positioned.

The practical use of inconsistency information in engineering design tasks - first observations
Today's product development projects require collaboration across different engineering domains in order to be successful. For instance, a project may require software engineers to collaborate with electrical engineers and mechanical engineers. Even though engineers of different domains focus on different parts of the system-under-development, these parts typically cannot work in isolation. Therefore, coordination among these engineers is necessary to ensure that the individual parts of a system work together well when combined. The lack of such coordination leads to inconsistencies and hence the inability to integrate individual parts of the system. Even though approaches for finding such inconsistencies have been developed, it has yet to be shown whether the presentation of inconsistencies is of actual value to engineers. In this paper, we present the results of a practical experiment that assessed the effects of the presence of inconsistent information during development. The results indicate that specific feedback about inconsistency (when performing changes) leads to better engineering results than merely presenting general information about system interconnections.

Risk assessment of construction projects by using combined model of analytical network process and DEMATEL method
Many academic and administrative researchers have already done several attempts aiming at risk assessment of big projects. The main risks of construction projects have been identified and classified in this paper by investigating research and studies done in this regard. The risks have then been categorised into several groups and assessment and analysis of project risk have been carried out by using risk breakdown structure and presenting a mixed model of ANP and DEMATEL. Finally, this model application has been explained through a case study. By application of this model and polling experts, it has been proved that financial and external risks are more important than other types of risks.

A comparative evaluation of contemporary models for lean manufacturing practices
Lean manufacturing (LM) is a thought developed in Toyota, thus, there is lack of studies on whether the implementation of LM is appropriate for different enterprises because of differences in organisational and social culture and labour. This paper critically analyses 11 contemporary models for LM in an attempt to find a unified model that can be applied by enterprises. In the literature models have a tendency to focus only on few single components. However, different enterprises use diverse dimensions and models for measuring LM. It aims to review the various LM models prevailing in the contemporary research papers along with presentation of an in-depth analysis exploring the similar and dissimilar aspects. The LM models adopted by different enterprises are quite diverse as revealed through this investigation. The outcome of this study produced a matrix comprising conjoint 98 elements linked with LM 11 models. These represent soft and hard LM elements found in the literature.

Maximising hotel profits with pricing and room allocation strategies
Hotels play an important role in the tourism supply chain by supplying essential accommodations. In today's dynamic and highly competitive market, a hotel's sales strategy significantly influences its profit. This study uses a theoretical modelling approach to help hotel owners make an optimal joint decision of pricing and room allocation strategy to maximise profits when facing new phenomena in the e-tourism era including various distribution channels, promotion programs, and contracts with travel agents. Our study provides optimal solutions for each scenario and discusses the influential factors. Managerial implications are provided.

Innovation development in service firms: a three-model perspective
This paper develops a three-model approach through the dynamic capability view to showcase the forms and dimensionalities service innovation could take. The paper explains that the different resource and capability-base for firms provide the source of variation for innovation. These capabilities allow service firms to create and implement innovation through their service mix that represents basic competitive tools for service engagement, interaction with customers and through the market as a result of external capability activation. The approach recommends the development of innovation with the service mix which is the basic competitive tool for service firms; through the customer-firm interface that enables value co-creation; and the market that allows the firm to capitalise upon its external capabilities. These service innovation dimensions therefore determine how well a service firm performs on the market in both the short and long-term.

The influence of SHRM functions on job satisfaction of employees through organisational support in a man power agency of Chennai International Airport
The growth of successful organisation is determined by the employee's performance and their achievements towards organisation goals. Strategic human resource function plays an important role for organisation performance and individual performance which paves way for job satisfaction. The researcher has identified employee's poor performance due to job dissatisfaction. Need of management support is an essential criteria for employees job satisfaction which pull down labour turn over in the organisation. In this regard, the study is conducted for 100 customer service agents of a manpower agency at Chennai International Airport by distributing well-structured questionnaire. The researchers found that the organisation treats the employees differently based upon the gender, age, designation and working experience. Investigating the results of the findings would trace out the various ways to perform better and suggestions given for the steps to be taken for converting an ordinary employee to sustained and satisfied employee.

Green supplier selection in fuzzy context: a decision-making scenario on application of fuzzy-MULTIMOORA
Green supply chain management has become an important avenue in current business scenario. The concept of GSCM is to integrate environmental thinking into traditional supply chain management. A firm's sustainability performance is greatly influenced by appropriate supplier selection in the green supply chain context. In selecting appropriate green supplier, various green criteria need to be considered along with traditional supplier selection criteria. The decision making in the context of green supplier selection becomes much more complex due to involvement of subjective selection criteria. Subjective human judgment often bears ambiguity and vagueness in the decision making; whilst fuzzy set theory overcomes the challenges of imprecise and inconsistent human judgment in ambiguous decision environment. In this context, a decision making scenario in relation to green supplier selection has been articulated in this paper aiming to investigate the applicability of MULTIMOORA in fuzzy setting (F-MULTIMOORA). The ranking order of candidate suppliers has been compared to that of fuzzy-TOPSIS. Finally, an attempt has been made to determine a unique quantitative performance index for each of the green suppliers; based on which a ranking order has also been arrived.

Analysis, synchronisation and circuit implementation of a novel jerk chaotic system and its application for voice encryption
In this research work, a novel 3D jerk chaotic system with one-quadratic nonlinearity and two-cubic nonlinearities is designed to generate complex chaotic signals. We show that the novel jerk chaotic system has a unique equilibrium at the origin, which is a saddle-focus and unstable. The Lyapunov exponents of the novel jerk chaotic system are obtained as L1 = 0.30899, L2 = 0 and L3 = -4.11304. The Kaplan-Yorke dimension of the novel jerk chaotic system is obtained as DKY = 2.0751. The qualitative properties of the novel jerk chaotic system are described in detail and MATLAB plots are shown. Next, we use backstepping control method to establish global chaos synchronisation of the identical novel jerk chaotic systems with unknown parameters. Next, an electronic circuit realisation of the novel jerk chaotic system is presented using MultiSIM to confirm the feasibility of the theoretical model. Finally, we present an application of the novel jerk chaotic system for voice encryption. The comparison between the MATLAB 2010 and MultiSIM 10.0 simulation results demonstrate the effectiveness of the proposed voice encryption scheme.

A new implementation of an impulsive synchronisation of two discrete-time hyperchaotic systems using Arduino-Uno boards
In this paper, we present experimental results on impulsive synchronisation between two discrete-time hyperchaotic systems. In the first part, we give some sufficient conditions on the asymptotic synchronisation by using varying impulsive distance in order to guarantee the impulsive synchronisation of the two mentioned systems. Numerical simulations are provided to show the effectiveness of the method. Next, an easy experimental implementation is realised using the Arduino-Uno boards. The obtained experiment results validate the proposed approach.

Modelling and simulation: an improved RANSAC algorithm based on the relative angle information of samples
Random sample consensus (RANSAC) algorithm is the most widely used one in the field of computer vision. In order to reduce the high complexity of RANSAC, this paper proposes a novel method which can reject samples before calculating the homography matrix. This algorithm can eliminate random samples that may be wrong through calculating the relative angle information of the random samples, and then, use the correct samples for the next step. The algorithm can ensure the accuracy of the premise while greatly reducing the computational complexity. Not only that, the improved algorithm can also be combined with the existing RANSAC extensions to improve the computational efficiency.

Mechanical analysis of a dual derrick
Dual derrick can greatly improve the efficiency of drilling operations in deep-water area. Analysis of various drilling processes such as single-well drilling, multi-well drilling, collaboration and parallel jobs using dual derrick frame, has been carried out in this research. Meanwhile, static analysis of dual derrick and the analysing of loading cases have been conducted, as well as the suffered stress of dual derrick under severe or normal drilling conditions. Modal analysis of dual derrick has been completed, also, dynamic equilibrium equations and the matrices of corresponding mass and stiffness have already been induced. Concerning the fact that higher modes have a slight impact on vibrations, eight low-level modes of vibration of dual derrick have been put forward, which turn out to match the optimised structure of vibration modes.

An adaptive and selective segmentation model based on local and global image information
This study investigates the application of partial differential equations in image segmentation field. A novel selective segmentation mode is proposed for the existing selective segmentation model which cannot segment the intensity inhomogeneity and fuzzy edge image. In this novel model, a weighting function based on local information is constructed. This weighting function can introduce the global and local information of the image into the novel model which can realise the adaptive segmentation of the image. Compared with the existing selective segmentation model, the novel selective segmentation model proposed in this paper can realise the adaptive segmentation of intensity inhomogeneity and fuzzy edge images. Experimental results show that the novel model is more effective and adaptive to segment images with intensity inhomogeneity or fuzzy edge, and less sensitive to the location of initial contour, without choosing the weighting parameter between global and local information by manual method.

Variational principle for stochastic singular control of mean-field Lévy-forward-backward system driven by orthogonal Teugels martingales with application
We consider stochastic singular control for mean-field forward-backward stochastic differential equations, driven by orthogonal Teugels martingales associated with some Lévy processes having moments of all orders and an independent Brownian motion. Under partial information, necessary and sufficient conditions for optimality in the form of maximum principle for this mean-field system are established by means of convex variation methods and duality techniques. As an illustration, this paper studies a partial information mean-variance portfolio selection problem driven by orthogonal Teugels martingales associated with gamma process as Lévy process of bounded variation.

Controlling a mobile manipulator actuated by DC motors and a single phase H-bridge inverter
In this paper, we treat the dynamic feedback control of a mobile manipulator actuated by DC motors using a digital pulse width modulation (DPWM) and a single phase H-bridge inverter in order to achieve a desired trajectory. Firstly, a fuzzy proportional-derivative (PD) controller is proposed to provide the necessary torques for the motion of the robot and to eliminate the effect of external force on the end-effector. Secondly, we aim to determine the current signal needed to drive the DC motors using an H-bridge inverter. Simulation results are given to show the effectiveness of the proposed controller and to demonstrate the coordination of two subsystems in performing the desired trajectory.

Low voltage ride-through capability improvement of doubly fed induction generator using series connected damping resistances
This paper proposes a control strategy to improve low voltage ride through (LVRT) capability of doubly fed induction generator (DFIG)-based wind turbines in response to grid fault occurrences or grid fault clearances to follow the requirements defined by the grid codes. The proposed scheme involves the use of series connected damping resistances (SCDR) and bypass switching devices coupled with rotor side converter (RSC), by which current peaks at both the rotor side and stator side can be reduced. The steady state behaviour under normal condition and dynamic behaviour of DFIG-based wind turbines during grid faults using the proposed strategy is simulated and assessed, and the results are compared with the scheme using crowbar circuit.

Solutions to fuzzy variational problems: necessary and sufficient conditions
The aim of this study is to investigate the necessary and sufficient conditions for fuzzy variational problems. To this purpose, based on a parametric representation for the α-level set of a fuzzy valued function, the fuzzy variational problems are converted to general variational problems in a parametric form. The Euler-Lagrange equations as necessary optimality conditions are derived, and then the solutions of these equations lead to the construction of the α-level sets of fuzzy extremal solutions for the original problems. Moreover, a sufficient condition under an appropriate convexity assumption is discussed for fuzzy variational problems. Using an example, the effectiveness of the proposed technique is discussed by comparing with the results of the given approaches in Fard et al. (2014) and Farhadinia (2011).

Assessing regional competitiveness in greater China
While China has experienced unprecedented economic growth in the last three decades, regional disparities have become more pronounced as well, paving the way for serious socio-economic challenges that have the potential to hinder China's future growth performance. This has caught the attention of the Chinese policy makers in recent years, which has led to a renewed policy focus on rebalancing regional development across the country. In this context, this paper assesses relative levels of regional development by undertaking a competitiveness analysis for Greater China at the regional level. The analysis confirms the existence of significant regional disparities and identifies the bottlenecks for each region of Greater China along the various dimensions of competitiveness. Our empirical results also have important implications for policy to promote regional rebalancing, which is critical for the sustainability of China's future development.

Problem analysis of 'underdevelopment whirlpools' as an obstacle for economic growth in Asian countries
The purpose of the article is to analyse disproportions of economic growth in Asian countries with the help of methodology of 'underdevelopment whirlpools'. The author analyses the depth and speed of sucking of economies of various Asian countries into 'underdevelopment whirlpools', performs problem analysis of this process, and determines consequences of appearance of 'underdevelopment whirlpools' in Asian countries and perspectives of overcoming them. For the purpose of the research, the author uses proprietary methodology of analysis of 'underdevelopment whirlpools'. As a result of the research, the author comes to the conclusion that Asian countries are peculiar for appearance of 'underdevelopment whirlpools' which hinder their economic growth. The author builds a cluster model of overcoming 'underdevelopment whirlpools' in Asian countries and quickening the rates of economic growth. The performed research contributes into development of the concept of economic growth, which determines its high theoretical value. Practical value of the research consists in a possibility of using the author's conclusions and recommendations during development of state economic policy of Asian countries for overcoming the determined 'underdevelopment whirlpools' and maximisation of rates of economic growth.

Social enterprise for sustainable development: Green Industry approach
Social enterprise is the secular trend for future socio-economic sustainable development. All firms have to consider not only equity value optimisation but also the other stakeholders. Withisuphakorn (2016) has found that higher CSR ratings or CSR implementation associate with higher revenues in the future. The appropriate CSR strategies will lead firm to be more profitable and sustainable in the long run. Therefore, government must seriously set the environment to encourage social enterprise which will simultaneously create mutual benefit to shareholders and all other stakeholders. This research will focus on the literature review on appropriate corporate structure and purposes and develop conceptual model for social enterprise to generate socio-economic sustainable development. Ultimately, we have proposed Green Industry conceptual model. This momentum of Green Industry promotion in Thailand is expanding and will lead to growing future social enterprises and reach long term sustainable of socio-economic and political economy sustainability globally.

How to transform creative ideas into creative products: learning from the success of batik fractal
The existence of the creative industry is one of the characteristics of the knowledge economy where its form may vary between countries. For many developing countries as well as Indonesia, creative industry plays important roles. Bandung, known as emerging creative city, has many factors to promote the creative industry. Many creative ideas that come out of the talented young people can be transformed into creative products such as batik fractal. This research aims to study the batik fractal's road map that has successfully transformed the creative ideas by utilising enabling factors that already exist. The method used was qualitative research method through in depth interview and triangulation of what was presented by the founder of the batik fractal. The results showed that at every phase of its development, the founders were able to integrate internal and external supporting factors to continue to develop to the next stage.

The role of tourist attraction and uniqueness of resources on value creation in the tourist destination
Previous researches on tourist destination in West Java highlighted the decline in revenue from tourism, tourist visits, hospitality and restaurants investment, as well as the number of tourism labour. These symptoms indicate under optimal conditions of value creation in the tourist destination in West Java. The results showed that the tourist attraction in West Java has not been fully adapted and developed several strategic aspects, such as reputation, technology, organisational culture, communication, human resources competence, and adjustment of internal capabilities, so that the relationship among variables and the influencing variable must be tested. The results also revealed that in order to create value, the tourist destinations in West Java should integrate tourist attraction and uniqueness of resources. In other words, the managers of tourist attractions in West Java should have the ability to adjust the value created and their tourist attractions.

Study of Indian exports and imports; sectoral trend analysis for 19 years between 1996-1997 to 2014-2015
Trade is an existential feature of human society. In the era of nation states, the quantum of international trade provides a good indication about the economic progress of a country. Emerging economies thus have very dynamic and expanding contours of international trade. In this research, the authors have collected sectoral trade data of India between the years 1996-1997 to 2014-2015. The authors have carried out trend analysis of the past 19 years data to comprehend the footprints of Indian economy on the world and vice-versa. The authors found the key contributing factors that affected the export and import in different sectors of the Indian economy.

Effect of market orientation on innovation in the footwear industry of Cibaduyut Bandung
This study aims to investigate the perceptions of business operators towards market orientation and innovation, and its influence on the footwear industry centre in Cibaduyut, Bandung. The research methods used are descriptive and verifying research. The technique of data collection is done by employing literature studies and field studies. Field studies are conducted by observation, interviews and questionnaires. Footwear entrepreneurs in Cibaduyut, Bandung, who become respondents are as many as 30. The results show that the implementation of market orientation has been running pretty well. This is due to the dimensions of competitor orientation role being not yet fully understood by businesses. On the other hand, dimensions of customer orientation and coordination between functions are already well underway. Furthermore, based on the dimensions of creativity and risk-taking, the implementation in Cibaduyut footwear industry has been running well. The effect of market orientation on innovation is by 31.43%, while the rest is influenced by other factors outside of this research model.

Partnership pattern of stakeholders in developing centres of small and medium scale flagship industry in Bandung City
This research focused on partnership pattern and used qualitative research method. The site of this research is seven centres of flagship industry (small and medium scale) in Bandung City. The research findings show there are three dimensions in studying partnership pattern namely: attribute, communication behaviour and conflict resolution techniques. The attribute dimension is the lowest in implementation. The poor synergy between entrepreneur program and government program is the biggest problem in the partnership dimension. In communication dimension, there is lack of involvement from entrepreneurs in formulating cooperative plan. The study of conflict resolution technique showed there are no serious problems in technique resolution conflict. Research showed there is low interaction in partnership that cause less potential of conflict. Other results informed that the role of Bandung society is still limited to residents around the industrial centres. The residents role in partnership is only in terms of labour supply.