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Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the composition and verification is also correspondingly high. In this paper, the authors aim to propose a logic-based clustering approach to solve this problem by separating the original repository of WS into clusters. Moreover, they also propose a so-called quality-controlled clustering approach to ensure the quality of generated clusters in a reasonable execution time.

The approach represents WSs as logical formulas on which the authors conduct the clustering task. They also combine two most popular clustering approaches of hierarchical agglomerative clustering (HAC) and k-means to ensure the quality of generated clusters.

This logic-based clustering approach really helps to increase the performance of the WS composition and verification significantly. Furthermore, the logic-based approach helps us to maintain the soundness and completeness of the composition solution. Eventually, the quality-controlled strategy can ensure the quality of generated clusters in low complexity time.

The work discussed in this paper is just implemented as a research tool known as WSCOVER. More work is needed to make it a practical and usable system for real life applications.

In this paper, the authors propose a logic-based paradigm to represent and cluster WSs. Moreover, they also propose an approach of quality-controlled clustering which combines and takes advantages of two most popular clustering approaches of HAC and k-means.

A rotary kiln is a pyro processing device that is used to raise the temperature of materials in cement factories. Temperature monitoring is an essential process in the rotary kiln to yield high quality clinker. Temperature measurement is a challenging task in clinkering process and it is difficult to apply automation techniques. As the pyrometer gives unreliable readings, it is necessary to apply various image processing techniques on the camera images to measure the temperature inside the kiln at different zones.

In this paper, a fuzzy logic rule-based analysis is proposed to measure temperature using a burning flame image in which it considers red, green, blue (RGB) magnitude planes. The proposed method uses Mamdani fuzzy inference system for decision-making. The system takes RGB magnitude as an input fuzzified variable and generates temperature as fuzzified output.

This paper focuses on the temperature measurement obtained from the images of the camera system. The commands to the valves and actuators are controlled using the center of gravity of the control regime. The fuzzy logic controller detects the temperature of flame zones using color features of burning flame images.

Precise temperature mapping of flame images helps to control the temperature inside the rotating kiln to produce high quality clinker. The process can be viewed remotely and controlled using various control loops from anywhere.

The purpose of this paper is to develop a deeper understanding of the new service development (NSD) research field. It addresses its scientific production, social and intellectual structures, and maturity.

This study uses a bibliometric-based literature review. Quantitative and qualitative analyses are performed on a sample of 277 NSD articles (published from 1984 to 2014). These articles are organized into four periods to improve the analyses from an evolutionary perspective: Early Writings (1984-1995), Advancing of Literature (1996-2001), Progressive Literature (2002-2008), and Recent Works (2009-2014).

The scientific production in the NSD field has grown significantly over these four periods, and the entry of new authors has extended the social structure. However, collaboration networks seem disconnected from one another. Nonetheless, the intellectual structure has shown great progress, making NSD an independent area of research and discovery from the new product development domain, with its own foundations and expansions into new topics. Although the NSD research field has not yet reached maturity, it is consistently moving toward it.

This study delivers a multiperspective view of research on NSD using a mixed quantitative and qualitative approach. It provides new insights into the discussion of the field’s maturity and can be used as a roadmap for academics and practitioners who would like to understand the state of existing knowledge and are looking for research opportunities.

The purpose of this paper is to address the Internet of Things (IoT) service discovery problem and investigate the existing solutions to tackle this problem in many aspects.

This paper presents an overview of IoT services aiming at providing a clear understanding about their features because this term is still ambiguous for the IoT service discovery approaches. Besides, a full comparison study of the most representative service discovery approaches in the literature is presented over four perspectives: the IoT information model, the mechanism of IoT service discovery, the adopted architecture and the context awareness. These perspectives allow classifying, comparing and giving a deeper understanding of the existing IoT service discovery solutions.

This paper presents a new definition and a new classification of IoT services and citation of their features comparing with the traditional Web services. This paper discusses the existing solutions, as well as the main challenges, that face the service discovery issue in the IoT domain. Besides, two classifications of the approaches are adopted on the basis of their service description model and their mechanism of discovery, and a set of requirements that need to be considered when defining an IoT service are proposed.

There are few number works that survey the service discovery approaches in the IoT domain, but none of these surveys discuss the service description models in the IoT or the impact of the context awareness aspect in the service discovery solution. There are also few works that give a comprehensive overview of IoT services to understand their nature to facilitate their description and discovery. This paper fills this gap by performing a full comparison study of multi-category and recent approaches for service discovery in the IoT over many aspects and also by performing a comprehensive study of the IoT service features.

This paper aims to serve two main purposes. In the first instance it aims to it provide an overview addressing the state‐of‐the‐art in the area of activity recognition, in particular, in the area of object‐based activity recognition. This will provide the necessary material to inform relevant research communities of the latest developments in this area in addition to providing a reference for researchers and system developers who ware working towards the design and development of activity‐based context aware applications. In the second instance this paper introduces a novel approach to activity recognition based on the use of ontological modeling, representation and reasoning, aiming to consolidate and improve existing approaches in terms of scalability, applicability and easy‐of‐use.

The paper initially reviews the existing approaches and algorithms, which have been used for activity recognition in a number of related areas. From each of these, their strengths and weaknesses are discussed with particular emphasis being placed on the application domain of sensor enabled intelligent pervasive environments. Based on an analysis of existing solutions, the paper then proposes an integrated ontology‐based approach to activity recognition. The proposed approach adopts ontologies for modeling sensors, objects and activities, and exploits logical semantic reasoning for the purposes of activity recognition. This enables incremental progressive activity recognition at both coarse‐grained and fine‐grained levels. The approach has been considered within the realms of a real world activity recognition scenario in the context of assisted living within Smart Home environments.

Existing activity recognition methods are mainly based on probabilistic reasoning, which inherently suffer from a number of limitations such as ad hoc static models, data scarcity and scalability. Analysis of the state‐of‐the‐art has helped to identify a major gap between existing approaches and the need for novel recognition approaches posed by the emerging multimodal sensor technologies and context‐aware personalised activity‐based applications in intelligent pervasive environments. The proposed ontology based approach to activity recognition is believed to be the first of its kind, which provides an integrated framework‐based on the unified conceptual backbone, i.e. activity ontologies, addressing the lifecycle of activity recognition. The approach allows easy incorporation of domain knowledge and machine understandability, which facilitates interoperability, reusability and intelligent processing at a higher level of automation.

The comprehensive overview and critiques on existing work on activity recognition provide a valuable reference for researchers and system developers in related research communities. The proposed ontology‐based approach to activity recognition, in particular the recognition algorithm has been built on description logic based semantic reasoning and offers a promising alternative to traditional probabilistic methods. In addition, activities of daily living (ADL) activity ontologies in the context of smart homes have not been, to the best of one's knowledge, been produced elsewhere.

This paper aims to evaluate the user satisfaction criterion for qualitative assessment of timeliness and efficacy of digital libraries based on the multivariate fuzzy logic technique.

In this paper, the performance of digital library services using fuzzy logic modeling are evaluated. This model based on fuzzy logic control is used to compute the dynamic response of users by using multiple independent variables. These parameters with inherent uncertainties in practical scenarios are characterized by fuzzy linguistic information.

Several parameters determining the user satisfaction metric in the deployment of digital library exhibit implicit uncertainties which can be intelligently modeled by means of fuzzy control systems. Given the sample data set for the proposed fuzzy multi-attribute decision-making framework, the simulation results are used to compute various error performance measures in the estimation of the fuzzy output variables.

The size of the considered sample data set is considerably small. Scalable real-world data sets can be used to reinforce the statistical efficiency and accuracy of the proposed model. Moreover, other techniques such as evolutionary multi-objective optimization and the Markovian process can be implemented to explore the efficient correlation between different parameters influencing the users’ behavior and facilitate the general application of the proposed technique.

The paper applied a fuzzy design methodology in which several attributes related to the service of digital library and the affiliated online resource provisions are used to assess their synchronous impact on user convenience in accessing and manipulating the library information. End-users’ satisfaction is crucial for quality-based valuation of compliance with the time limitations and proficiency of digital libraries.

This paper aims to propose an extensible, service-oriented framework for context-aware data acquisition, description, interpretation and reasoning, which facilitates the development of mobile applications that provide a context-awareness service.

First, the authors propose the context data reasoning framework (CDRFM) for generating service-oriented contextual information. Then they used this framework to composite mobile sensor data into low-level contextual information. Finally, the authors exploited some high-level contextual information that can be inferred from the formatted low-level contextual information using particular inference rules.

The authors take “user behavior patterns” as an exemplary context information generation schema in their experimental study. The results reveal that the optimization of service can be guided by the implicit, high-level context information inside user behavior logs. They also prove the validity of the authors’ framework.

Further research will add more variety of sensor data. Furthermore, to validate the effectiveness of our framework, more reasoning rules need to be performed. Therefore, the authors may implement more algorithms in the framework to acquire more comprehensive context information.

CDRFM expands the context-awareness framework of previous research and unifies the procedures of acquiring, describing, modeling, reasoning and discovering implicit context information for mobile service providers.

Support the service-oriented context-awareness function in application design and related development in commercial mobile software industry.

Extant researches on context awareness rarely considered the generation contextual information for service providers. The CDRFM can be used to generate valuable contextual information by implementing more reasoning rules.

More and more organizations make parts of their information systems available to their business partners and often face integration and interoperability issues. To counter these problems, web services appeared as a promising technology to bridge the gap between organizations and their partners. While web services generally focus on the implementation of functional concerns (FC) such as ordering of goods, the reservation of flights, etc. also non‐functional concerns (NFC) such as security, reliable messaging, performance, and availability have to be addressed appropriately. The purpose of this paper is to identify web services' requirements.

In this paper the authors provide a survey on works in the area of NFCs in web services. After presenting a common terminology, the most important requirements in that context are presented. Further, the authors assess these works against the requirements.

The evaluation reveals that there is no approach that supports the requirements to a satisfying degree. Based on that, the authors motivate the need for a novel holistic approach to NFCs in web services.

The paper presents an extended version of one of the papers presented at iiWAS2010.

Extends the concept of e‐service to the whole phase of manufacturing. Develops an e‐service platform prototype based on this concept with Java Web solution including the mobile agent broking technologies and application service provider (ASP) principle. The key point to implement the platform is to enable an open Web information service infrastructure for the whole product manufacturing chain. Inside this infrastructure, product‐specific online manufacturing system can be created by means of using a kind of bidding model. All users participating in the manufacturing process are able to cooperatively finish manufacturing tasks in real time through sharing the same platform. With the help of BOM flow, the global information service flow can be controlled easily. In addition, the legacy hardware/software can also be encapsulated with aglets that are Java mobile agents. As to new ASP software packages, they can be configured simply via the plug and play mode to the e‐service platform. In this way, the on‐line networked manufacturing can be tested.

This study aims to propose a service quality evaluation model for health-care services.

In this study, a service quality evaluation model is proposed based on the service quality measurement (SERVQUAL) scale and machine learning algorithm. Primarily, items that affect the quality of service are determined based on the SERVQUAL scale. Subsequently, a service quality assessment model is generated to manage the resources that are allocated to improve the activities efficiently. Following this phase, a sample of classification model is conducted. Machine learning algorithms are used to establish the classification model.

The proposed evaluation model addresses the following questions: What are the potential impact levels of service quality dimensions on the quality of service practically? What should be prioritization among the service quality dimensions and Which dimensions of service quality should be improved primarily? A real-life case study in a public hospital is carried out to reveal how the proposed model works. The results that have been obtained from the case study show that the proposed model can be conducted easily in practice. It is also found that there is a remarkably high-service gap in the public hospital, in which the case study has been conducted, regarding the general physical conditions and food services.

The primary contribution of this study is threefold. The proposed evaluation model determines the impact levels of service quality dimensions on the service quality in practice. The proposed evaluation model prioritizes service quality dimensions in terms of their significance. The proposed evaluation model finds out the answer to the question of which service quality dimensions should be improved primarily?