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Applying “modularity” principles in services is gaining in popularity. The purpose of this paper is to enrich existing service modularity theory and practice by exploring how services are being decomposed and how the modularization aim and the routineness of the service(s) involved may link to different decomposition logics. The authors argue that these are fundamental questions that have barely been addressed.

The authors first built a theoretical framework of decomposition steps and the design choices involved that distinguished six decomposition logics. The authors conducted a systematic literature search that generated 18 empirical articles describing 16 service modularity cases. The authors analysed these cases in terms of decomposition logic and two main contingencies: modularization aim and service routineness.

Only three of the 18 articles explicitly addressed the service decomposition by reflecting on the underlying design choices. By unravelling the decomposition in each case, the authors were able to identify the decomposition logic and found four of the six theoretically derived logics: single-level process oriented; single-level outcome oriented; multilevel outcome oriented; and multilevel combined orientation. Although the authors did not find a direct relationship between the modularization aim and the decomposition logic, the authors did find that single-level decomposition logics seem to be mainly applied in non-routine service offerings whereas the multilevel ones are mainly applied in routine service offerings.

By contributing to a common understanding of modular service decomposition and proposing a framework that explicates the design choices involved, the authors enable an enhanced application of the modularity concept in services.

New approaches for non‐classical neural‐based computing are introduced. The developed approaches utilize new concepts in three‐dimensionality, invertibility and reversibility to perform the required neural computing. The various implementations of the new neural circuits using the introduced paradigms and architectures are presented, several applications are shown, and the extension for the utilization in neural‐systolic computing is also introduced.

The new neural paradigms utilize new findings in computational intelligence and advanced logic synthesis to perform the functionality of the basic neural network (NN). This includes the techniques of three‐dimensionality, invertibility and reversibility. The extension of implementation to neural‐systolic computing using the introduced reversible neural‐systolic architecture is also presented.

Novel NN paradigms are introduced in this paper. New 3D paradigm of NL circuits called three‐dimensional inverted neural logic (3DINL) circuits is introduced. The new 3D architecture inverts the inputs and weights in the standard neural architecture: inputs become bases on internal interconnects, and weights become leaves of the network. New reversible neural network (RevNN) architecture is also introduced, and a RevNN paradigm using supervised learning is presented. The applications of RevNN to multiple‐output feedforward discrete plant control and to reversible neural‐systolic computing are also shown. Reversible neural paradigm that includes reversible neural architecture utilizing the extended mapping technique with an application to the reversible solution of the maze problem using the reversible counterpropagation NN is introduced, and new neural paradigm of reversibility in both architecture and training using reversibility in independent component analysis is also presented.

Since the new 3D NNs can be useful as a possible optimal design choice for compacting a learning (trainable) circuit in 3D space, and because reversibility is essential in the minimal‐power computing as the reduction of power consumption is a main requirement for the circuit synthesis of several emerging technologies, the introduced methods for non‐classical neural computation are new and interesting for the design of several future technologies that require optimal design specifications such as three‐dimensionality, regularity, super‐high speed, minimum power consumption and minimum size such as in low‐power control, adiabatic signal processing, quantum computing, and nanotechnology.

Modified reconstructability analysis (MRA), a novel decomposition technique within the framework of set‐theoretic (crisp possibilistic) reconstructability analysis, is applied to three‐variable NPN‐classified Boolean functions. MRA is superior to conventional reconstructability analysis, i.e. it decomposes more NPN functions. MRA is compared to Ashenhurst‐Curtis (AC) decomposition using two different complexity measures: log‐functionality, a measure suitable for machine learning, and the count of the total number of two‐input gates, a measure suitable for circuit design. MRA is superior to AC using the first of these measures, and is comparable to, but different from AC, using the second.

A novel many‐valued decomposition within the framework of lossless reconstructability analysis (RA) is presented. In previous work, modified reconstructability analysis (MRA) was applied to Boolean functions, where it was shown that most Boolean functions not decomposable using conventional reconstructability analysis (CRA) are decomposable using MRA. Also, it was previously shown that whenever decomposition exists in both MRA and CRA, MRA yields simpler or equal complexity decompositions. In this paper, MRA is extended to many‐valued logic functions, and logic structures that correspond to such decomposition are developed. It is shown that many‐valued MRA can decompose many‐valued functions when CRA fails to do so. Since real‐life data are often many‐valued, this new decomposition can be useful for machine learning and data mining. Many‐valued MRA can also be applied for the decomposition of relations.

The objective of this paper is to provide a brief review of recent developments in the area of applications of ANN, Fuzzy Logic, and Wavelet Transform in fault diagnosis. The purpose of this work is to provide an approach for maintenance engineers for online fault diagnosis through the development of a machine condition‐monitoring system.

A detailed review of previous work carried out by several researchers and maintenance engineers in the area of machine‐fault signature‐analysis is performed. A hybrid expert system is developed using ANN, Fuzzy Logic and Wavelet Transform. A Knowledge Base (KB) is created with the help of fuzzy membership function. The triangular membership function is used for the generation of the knowledge base. The fuzzy‐BP approach is used successfully by using LR‐type fuzzy numbers of wavelet‐packet decomposition features.

The development of a hybrid system, with the use of LR‐type fuzzy numbers, ANN, Wavelets decomposition, and fuzzy logic is found. Results show that this approach can successfully diagnose the bearing condition and that accuracy is good compared with conventionally EBPNN‐based fault diagnosis.

The work presents a laboratory investigation carried out through an experimental set‐up for the study of mechanical faults, mainly related to the rolling element bearings.

The main contribution of the work has been the development of an expert system, which identifies the fault accurately online. The approaches can now be extended to the development of a fault diagnostics system for other mechanical faults such as gear fault, coupling fault, misalignment, looseness, and unbalance, etc.

This paper aims to explore the role of customer engagement during the production of services in a modular innovation. Modularity can be used to explain the structure and relationship in services innovation.

The authors explore the theory of modularity focussing on the context of consumer engagements. They adopted ideas from product modularity and approach services using modular principle.

Contrary to the extant literature, the authors are content that the transactions between the participants were mainly conducted at thick crossing points. By focusing on thin crossing point, the service provider will achieve better overall service structure.

There is a need to focus on specifying interface to define how service modules and service providers interact with the customer within the service.

By engaging customer, modular principle can help firms achieve cost efficiency, higher product and process variety, as well as better response to individual customer needs.

This paper scrutinises the engagement of customer and conceptualises the role of customer in modular innovations that have been previously neglected.

Modified reconstructability analysis (MRA) can be realized reversibly by utilizing Boolean reversible (3,3) logic gates that are universal in two arguments. The quantum computation of the reversible MRA circuits is also introduced. The reversible MRA transformations are given a quantum form by using the normal matrix representation of such gates. The MRA‐based quantum decomposition may play an important role in the synthesis of logic structures using future technologies that consume less power and occupy less space.

To develop a novel approach for encapsulating high level business knowledge and logic of a given application domain in patterns and frameworks, which can be reused and be applied to improve a process for a given business in the domain and to develop an application to support such process.

Formal and explicit business process patterns (BPP) have been developed that synthesize best practices found in hundreds of real projects of process redesign. From these, software business objects (BO) frameworks that encapsulate business logic have been derived.

Good characterization of the processes and associated decisions by means of formal BPP allows including complex generalized business decisions logic in BO frameworks. Such logic is built upon the best current knowledge of analytical methods, such as business intelligence, optimization and heuristics.

This approach provides a very flexible way, based on reusable components, to develop solutions and software for complex business decisions, which is an alternative to packaged products. The approach is exemplified by using a specific application domain and applied to a real case in the domain.

As it is shown in the literature review in the paper, patterns and frameworks up to now have only marginally included high‐level decision logic.

Purpose – Our purpose in this chapter is to argue for the importance of integrating reading and writing in classrooms and to provide examples of what integration of this nature looks like in classrooms across content areas and grade levels.Design/methodology/approach – In this chapter we provide an overview of the argument for reading–writing integration, highlight four common tools (skill decomposition, skill decontextualization, scaffolding, and authenticity) that teachers use to cope with complexity in literacy classrooms, and describe four classrooms in which teachers strive to integrate reading and writing in support of learning.Findings – We provide detailed examples and analyses of what the integration of reading and writing in the service of learning looks like in four different classroom contexts and focus particularly on how the four teachers use scaffolding and authenticity to cope with complexity and support their students’ literacy learning.Research limitations/implications – We intentionally highlight four noteworthy approaches to literacy instruction, but our examples are relevant to specific contexts and are not meant to encompass the range of promising practices in which teachers and students engage on a daily basis.Practical implications – In this chapter we provide classroom teachers with four concrete tools for coping with the complexities of literacy instruction in classroom settings and highlight what instruction of this nature – with an emphasis on scaffolding and authenticity – looks like in four different classroom contexts.Originality/value of chapter – Teachers and other educational stakeholders must acknowledge and embrace the complexities of learning to read and write, so that students have opportunities to engage in rich and authentic literacy practices in their classrooms.