An Effective Memetic Algorithm for the Distributed Integrated Scheduling of Tree-Structured Products

Aiming at the distributed integrated scheduling of complex products with tree structure, a memetic algorithm-based distributed integrated scheduling algorithm is proposed. Based on the framework of the memetic algorithm, the algorithm uses a distributed estimation algorithm for global search and performs a local search strategy based on the critical operation set for the current optimal solution obtained in each evolutionary generation. A bi-chain-based individual representation method is presented and a simple greedy insertion-based decoding method is given; two position-based probability models are built, which are used to describe the distribution of the operation priority and factory assignment, respectively. Based on the designed probability models, two learning-based updating mechanisms and an improved sampling method are given, which ensures that the population evolves towards a promising region. In order to enhance the searchability for the superior solutions, nine disturbance operators based on the critical operation set are presented. The parameters are determined by the design-of-experiment (DOE) test, and the effectiveness of the proposed algorithm is verified by comparative experiments.

Assessing Process Attribute Visualization and Interaction Approaches Based on a Controlled Experiment

Ensuring the smooth and efficient execution of business processes requires a continuous process quality assessment and optimization. Process optimization exploits process attributes and their values, e.g. cost or duration of a process task, in order to derive, for example, control flow adaptations. The complexity of the analysis can range from a few to a plethora of attributes, e.g. machining times and sensor parameters in the manufacturing domain. Hence, it is crucial to support single and multiple users (e.g. process analysts) in visually exploring process attributes and their values. Specifically, comparing and assessing different visualization and interaction approaches with respect to their efficiency is required in order to offer the most suitable approach to users for a specific analysis task. However, such assessments are currently missing. To close this gap, this paper assesses three visualization and interaction approaches, i.e. 2D, 3D, and 3D with virtual reality (VR) support, based on a controlled experiment. We choose the process modeling standard Business Process Modeling and Notation (BPMN) as 2D approach. 3DViz is introduced as 3D approach with focus on attribute representation, and additionally augmented with VR. A statistically significant difference between the approaches can be observed with respect to their efficiency.

A Cross-Domain Comparative Study of Big Data Architectures

Nowadays, a variety of Big Data architectures are emerging to organize the Big Data life cycle. While some of these architectures are proposed for general usage, many of them are proposed in a specific application domain such as smart cities, transportation, healthcare, and agriculture. There is, however, a lack of understanding of how and why Big Data architectures vary in different domains and how the Big Data architecture strategy in one domain may possibly advance other domains. Therefore, this paper surveys and compares the Big Data architectures in different application domains. It also chooses a representative architecture of each researched application domain to indicate which Big Data architecture from a given domain the researchers and practitioners may possibly start from. Next, a pairwise cross-domain comparison among the Big Data architectures is presented to outline the similarities and differences between the domain-specific architectures. Finally, the paper provides a set of practical guidelines for Big Data researchers and practitioners to build and improve Big Data architectures based on the knowledge gathered in this study.

Governance Mechanism and Structural Power Fit: Evidence from an Information System Development Project

This study identifies how relational and contractual governance mechanisms differently influence the distinct output of information systems development (ISD) performance at the project level. This study also reveals how the consequence of two modes of inter-organizational relationships (IOR) governance mechanism is affected by the gap of a dyadic partner’s centrality within the network — the client’s structural power (CSP). We collected dyadic samples of clients and vendors for 107 ISD projects and explored their governance mechanisms and project performances, all of which were evaluated by both parties. Our results first reveal a positive relationship between relational (or contractual) governance and qualitative (or quantitative) performance, respectively, but not vice versa. Second, the results incorporating a structural position within the network reveal that CSP facilitates the efficacy of relational governance to lead the quantitative performance, but surprisingly, CSP also mitigates the efficacy of contractual governance.

Web Accessibility Assessment Through Multi-Agent Support for Visually Impaired Users

In general, users who access Web sites do not necessarily have the same abilities in terms of cognitive, sensory and physical conditions. An accessible Web site is one whose content can be used by as many users as possible; and to improve accessibility, the use of evaluation tools has been incorporated among other resources. However, from the point of view of the end user, the evaluation obtained by most of these tools does not fit to the individual needs and abilities of the users. On the other hand, there is a greater understanding of the need to automate the support to reach higher levels of accessibility. Promoting this type of support on both the developer and the end-user sides is a complex procedure that can be done by incorporating intelligent features, such as the collaborative participation of intelligent agents. In this paper, we introduce a multi-agent system based on visually impaired user’s profiles to improve Web Accessibility assessment. The proposal is validated through a proof of concept, by contrasting results against 10 wide-known assessment tools. Our results show that evaluations are more focused, and therefore, unnecessary assessments are avoided improving efficiency.

MVPP-Based Materialized View Selection in Data Warehouses Using Simulated Annealing

The process of extracting data from different heterogeneous data sources, transforming them into an integrated, unified and cleaned repository, and storing the result as a single entity leads to the construction of a data warehouse (DW), which facilitates access to data for the users of information systems and decision support systems. Due to their enormous volumes of data, processing of analytical queries of decision support systems need to scan very large amounts of data, which has a negative effect on the systems’ response time. Because of the special importance of online analytical processing (OLAP) in these systems, to enhance the performance and improve the query response time of the system, an appropriate number of views of the DW are selected for materialization and will be utilized for responding to the analytical queries, instead of direct access to the base relations. Memory constraint and views maintenance overhead are two main limitations that make it impossible, in most cases, to materialize all views of the DW. Selecting a proper set of views of DW for materialization, called materialized view selection (MVS) problem, is an important research issue that has been focused in various papers. In this paper, we have proposed a method, called P-SA, to select an appropriate set of views using an improved version of simulated annealing (SA) algorithm that utilizes a proper neighborhood selection strategy. P-SA uses the multiple view processing plan (MVPP) structure for selecting the views. Data and queries of a benchmark DW have been used in experimental results for evaluating the introduced method. The experimental results show better performance of the P-SA compared to other SA-based MVS methods for increasing the number of queries, in terms of the total cost of view maintenance and query processing. Moreover, the total cost of queries in the P-SA is also better than the other important SA-based MVS methods of the literature when the size of the DW is increased.

Research on Optimized Online Allocation of Scope Spatial Crowdsourcing Tasks

Task allocation of spatial crowdsourcing tasks is an important branch of crowdsourcing. Spatial crowdsourcing tasks not only require workers to complete a specific task at a specified time, but also require users to go to the designated location to complete the corresponding tasks. In this paper, Scope spatial crowdsourcing task whose work position is a region rather than a location is a kind of spatial crowdsourcing task. Mobile crowdsourced sensing (MCS) is one of the most important platforms to publish spatial crowdsourcing tasks, based on which MCS workers can use smartphones to complete the collections of related sensing data. When assigning tasks for scoped crowdsourcing tasks, there is a scope overlap between tasks and one or more tasks due to the association of task scope between tasks, which causes a waste of manpower. The focus of this paper is to study the redundancy of the task scope that occurs when using MCS to collect scoping data in the case of fewer workers and more tasks. Optimizing scope spatial crowdsourcing tasks allocation algorithm (OSSA) can eliminate the redundancy of the task area by integrating and decomposing tasks and achieve the improvement of the assignable number of tasks. In the Windows platform, experiments are made to compare the efficiency of the OSSA algorithm with the greedy algorithm and the two-phase-based global online allocation (TGOA) algorithm to further prove the correctness and feasibility of the algorithm for task scope optimization.

Information System Services Generation of Business Services Specification and Based on a System-of-Services Logical Architecture Pattern

The generation and design of the service architecture of an information system is complex. It depends more on the vision of the service than on the vision of the service inside an information system. An information system is indeed a system of services that can contain thousands of services. The lack of consideration of constraints imposed by the information system makes it difficult to reuse these services. Another strong constraint is that an information system service must support a business service. The proposed approach allows information system services to be generated in accordance with the business services specification and their logical architecture to be automatically designed by respecting a logical architecture pattern of the system-of-services. An information system services generation algorithm allows being consistent with the logical architecture pattern during this generation. The definition of coherence and coupling properties makes it possible to evaluate the relevancy of the system-of-services. A use case shows the value of these properties in making the logical architecture of the service system more relevant to business services.

A Graph-Based Tag Recommendation for Just Abstracted Scientific Articles Tagging

Tags, when properly assigned to limited access papers, help users to estimate their relevance. This paper introduces a new approach for the selection of relevant tags as well as a recommendation for scientific papers tagging. The approach defines the relatedness between the tags attributed by users and the concepts extracted from the available sections of scientific papers based on statistical, structural and semantic aspects. Two different term-based graphs ([Formula: see text]-graph and [Formula: see text]-graph) were generated whose vertices indicate the terms and the edges represent the relatedness score between these terms. In addition, two algorithms were implemented to select and recommend the relevant tags: the neighbor-algorithm and the best-path-algorithm. The results of the experiments performed on a CiteULike collection of tagged papers show significant improvements only for the tagging of abstracted scientific articles. The approach was evaluated by referring to the full text of the papers with expert evaluation and comparing the tags generated by CiteULike users. Using the neighbor-algorithm, 80% of the top 10 recommended tags based on [Formula: see text]-graph and 76% of the top 10 recommended tags based on the [Formula: see text]-graph were relevant. While only 62% of those recommended by CiteULike users were relevant. The best-path-algorithm gave the best results in the top 20 and top 30 recommended tags and this in comparison with the tags recommended by the neighbor-algorithm and the tags assigned by CiteULike users.