Cooperative Design, Visualization, and Engineering

The purpose of this study was to discover the relationships among 18 psychological features in a cooperative team in order to analyse work team performance. A Bayesian network (BN) has been built from a dataset of 403 soccer semi-professional players, taking into account prototypical sportive teams with respect to other workteams, regarding its psychological features, such as leadership, cohesion or group roles. The BN shows three conditionally independent features according to the local Markov property: two cohesion dimensions and the cooperative style of management/coaching; and features such as players satisfaction, experience, social integration in the team, and the workplace specificity, i.e., the players’ positions, which were located at the bottom in the BN show a clear dependence. The BN was used to make inferences achieving: (1) The social side of the cohesion has a low likelihood influence on the performance; (2) All psychological leadership styles (positive and/or negative) have some influence on the performance, the years remaining in the same team, and the player’s position; (3) The positive leadership style is not a required condition for the performance or for the player’s satisfaction, but a consequence of the other psychological variables.

Traditionally, the development of systems supporting group work has been considered a complex task because multiple aspects have to be considered. As a consequence, it is necessary to apply methodological processes in order to reach successful and usable systems. CIAM is a methodological approach for developing groupware user interfaces by modeling aspects of collaboration and interaction. CIAM addresses the joint modeling of collaboration and human-computer interaction aspects, guiding the engineers through several modeling stages, starting from the analysis of the context of the group work until obtaining an interactive task model. In its initial proposal, CIAM does not deal directly with evaluation mechanisms and processes of the artifacts produced when this methodology is applied. In addition, CIAM is not primarily focused on the mobile computing paradigm. Thus, the objective of this paper is to describe how CIAM is being improved in order to provide more complete support for modeling and evaluation of collaborative applications based on mobile computing and especially the modeling of applications supporting Mobile Learning (or m-Learning).

In the last years, the increasing use of social networks and applications has significantly changed the business processes in many organizations. These applications provide new cooperative ways of performing these processes by taking advantages of the interactions among users. However, the high number of these applications has lead to a lack of automation in their interactions and, thus, the need of manually connecting to these networks to perform recurrent and repetitive tasks. In order to automate these operations, this paper presents SCPL, a Domain Specific Language (DSL) that enables the connectivity among different social networks and applications and provides a way to automate their management. The main contribution of this paper is showing how SCPL can be used to specify collaborative tasks using social networks in a transparent way.

Developed through many industrial and research partnerships, the software platform Cadral addresses operational needs of organizations by integrating two complementary modules: a collaborative decision support framework and a visual analytics tool suite for knowledge extraction and data processing. It is used to support the designing of innovative applications, facilitates the comparison and selection of up-to-date technologies and the release of specific pieces of software for operational purposes.

Collaboration relies on the flow of information among parties. To make informed decisions, shared knowledge should be managed in a way to be accessible for relevant group members to each of the contents. One of the main factors that contribute to the quality of contents recommendations to the relevant users is the quality of the users and contents identification. A variety of automatic and semi-automatic methods exist for extracting or assigning identity to online resources. Although users’ perception about contents and also their interests might change over time, most current approaches define a fixed identity for the objects and always recommend them to the users based on their fixed, defined identities because they use a source of knowledge that does not evolve. In our approach, we update identities of the users and Web contents dynamically based on the latest collective opinion of the evolving communities of users related to them in a social semantic tagging system.

N-dimensional BIM models integrate many aspects of Architecture, Engineering and Construction (AEC) projects information. These models are well structured and allow users to practically query them, however they are more and more combined with other data sources, provided e.g. by Geographic Information Systems (GIS), Building Automation Systems (BAS) or Facility Management (FM) systems. Construction project managers are facing an important challenge related to making meaningful deduction from these heterogeneous data sets. In this context the current data mining approaches are showing their limitations. Big Data is then gradually getting a reality in the construction industry. This paper characterizes AEC project management data following the conceptual definition of Big Data and proposes a high-level conceptual pipeline aiming at bridging the gap between BIM-based related visualization works and information visualization domain.

Many systems and applications have been developed to help visitors get around the museum and interact with the items on exhibition. However, most of the existing systems are developed to serve as a virtual tour guide and/or provide additional digital information using Augmented Reality techniques. Little attention has been paid to enabling visitors to interact with each other and share their experience with outsiders. In this paper, we describe the design and evaluation of a prototype of a museum touring application called SMART. This system was designed to explore how mobile devices can be used to connect museum visitors and their friends. It is intended to be a smart and novel mobile application that enables groups of museum visitors to select tours by their preferences, display relevant information about their tour and objects, provide interactive activities for tourists and let them mark their favourite exhibits. It also aims to streamline traditional museum tours by providing more interesting, more meaningful and more interactive parts to the tour.

The purpose of this study was to use specially-designed of wall pictures in tunnels to reduce drivers’ negative emotions and enhance positive ones. The three experiments were: investigation of the current driving experience in Hsuehshan Tunnel, the selection of wall pictures, and simulated driving with the designated pictures. The results showed that drivers had more positive emotions and less negative responses in the tunnel with pictures than in the one without pictures. When the pictures changed between each stage, more positive emotions occurred. Pictures with brightness and color changes showed better effects. The length and brightness of the pictures affected drivers’ visual and spatial feelings. Drivers had different speed feelings in stages with different pictures. The rules of pictures’ changes should be able to be recognized by drivers. Pictures lacking a good order will cause negative responses. Brightness changes resemble the change of lightness in the environment. Proper use the design of wall pictures helps ease drivers’ negative emotions and enhance positive ones.

This paper aims to present how hitherto existing aesthetic measure approaches could be enriched by contemporary perception models, which would be useful in computer aided design of architecture. Proposed measure allows designers for collaborative decision making to find an average aesthetic value.

The proper transport of hit sensitive products, such as fish and fruit, is very important because their deterioration may cause the value lost and even the product rejection by the buyer. For this reason, in this paper we present a cooperative monitoring system for the delivery of fresh products. The system consists of fixed wireless nodes and a mobile wireless node that is installed in the packet. This mobile node is able to take data of the internal temperature, external temperature and the 3 axis movement. With the information stored in the network, a vendor can know the optimal conditions of the transport. Finally, we test the maximum distance to the fixed nodes, as well as the data collected by the sensor.

As an increasing number of people use wireless communication to purchase goods and services, we have developed a new micropayment system called M&E-NetPay for mobile electronic commerce. This system has open interoperability and mobility, uses Web services to inter-connect brokers and vendors, and provides secure, flexible, usable, and reliable credit services over the Internet. M&E-NetPay makes use of a secure, cheap, available, and debitbased off-line protocol that allows vendors to interact only with customers after an initial validation of coins. To validate the system, we have conducted an evaluation of the system performance. The results demonstrate that by using fast hashing functions that validate e-coin unspent indexes, M&E-NetPay achieves secure transactions with a high volume per item. It was also confirmed that the .Net framework architecture 4.0 with Web Services used in M&E-NetPay improves client-to-server communications, leading to high system performance. We report on this evaluation in this paper.

In this paper we propose a cloud model of internet of things for logistic supply chains. In the cloud model, the cloud terminals can collect, receive and deliver information by integration of mobile networks, wireless networks, networks of sensors, including data, video and audio information. The data and information are classified and dealt with in the cloud service platform where the communication cluster servers, application servers, middleware servers and database servers are located. In this model the cluster service, resource dispatch and load balance are cooperative for every application group in the cloud in order to serve for the management and monitoring during the logistic supply chain lifecycle. In order to support high performance of cloud service, NIO (Non-blocking Input/Output) and RMI (Remote Method Invocation) are applied for the resource cooperative dispatch.

With the fastidiously ever-increasing complexity of systems, the relentless, massive customisation of products and the mushrooming accumulation of legal documents (standards, policies and laws), we can observe a significant increase in requirements. We consider the tremendous volume of requirements as big data with which companies struggle to make strategic decisions early on. This paper proposes a collaborative requirement mining framework to enable the decision-makers of an Original Equipment Manufacturer (OEM) to gain insight and discover opportunities in a massive set of requirements so as to make early effective strategic decisions. The framework supports OEMs willing to uncover a subset of key requirements by distilling large unstructured and semistructured specifications.

Virtual factory has great influence on the competitiveness of the enterprise production during the design and operation stages, especially on the new factory layout, the factory reconstruction and workshop decision. The paper presents a method of the information modeling for virtual factory based on building information modeling (BIM), including the architectural elements, the integrated digital expressions of the equipment elements and the workshop control elements (geometry, physics and function etc.). It organically combines the solid geometric models, physical properties, rules and some other building and semantic information. This method can realize the modeling, simulation and evaluation (MSE) of manufacturing system. The paper presents a virtual factory integrated method of manufacturing marine product, combined with BIM, and realizes a prototype system to visualize the marine virtual factory based on BIM.

In this paper, an approach based on the Pareto front theory is employed to conduct the multi-objective optimization of the global stiffness and wellconditioned workspace of 3UPU-UPU parallel mechanism. The inverse kinematic and Jacobian matrix of the 3UPU-UPU mechanism are first calculated. Then the stiffness model of the mechanism is derived and the sum of the diagonal elements of the stiffness matrix is used as a criterion to evaluate the global stiffness. Secondly, the Monte Carlo method is used to derive the global condition index of the mechanism which later is used as a criterion to evaluate the wellconditioned workspace of the mechanism. Normally, increasing the workspace of the mechanism will deteriorate the stiffness, here the global stiffness and wellconditioned workspace of the mechanism are optimized simultaneously based on the Pareto front theory, and the optimized results are displayed and compared.

This paper presents the VELaSSCo project (Visualization for Extremely LArge-Scale Scientific Computing). It aims to develop a platform to manipulate scientific data used by FEM (Finite Element Method) and DEM (Discrete Element Method) simulations. The project focuses on the development of a distributed, heterogeneous and high-performance platform, enabling the scientific communities to store, process and visualize huge amounts of data. The platform is compatible with current hardware capabilities, as well as future hardware.

This paper identifies the main criteria used by architecture specialists in the task of clustering alternative floor plan designs. It shows how collective actions of respondents lead to their clustering by carrying out an online exercise. The designs were randomly pre-generated by a hybrid evolutionary algorithm and a questionnaire was posed in the end for the respondents to indicate which similarity criteria they have used. A network of designs was then obtained and it was partitioned into clusters using a modularity optimization algorithm. The results show that the main criterion used was the internal arrangement of spaces, followed by overall shape and by external openings orientation. This work allows the future development of novel algorithms for automatic classification, clustering, and database retrieval of architectural floor plans.

The collaborative architectural design process can be difficult to generate and maintain, especially when consisting of large teams, time constraints and long distance as it requires a higher sense of working together. However, a formal description of collaborative design as a system made of elements, agents, sub-systems and relationships could open a path to potentially improve production efficiency and stream collective intelligence. The CISP is a first attempt methodology to support collaborative design based on the empirical analysis of a single case study involving a multi-disciplinary team competing in an international architectural idea competition. The methodology operates through interdependencies on three layers: organization, planning and shared workspace. By articulating methods, tools, team members and project phases, the CISP fosters an integrated design system and a fluent design process.

The ubiquity of information and communication technologies (ICT) stimulate collaborative shopping and bring together customers with similar interests around the world to perform cooperative and collective online shopping. As a result, various models of collaborative online group buying are emerging. This paper analyses the phases of interaction during the shopping processes and provides a systematic categorization of the online group buying based on the topdown/ bottom-up crowd-shopping models. In addition, this paper discusses recent developments and challenges of group buying in order to contribute to future research directions within the field of collaborative online group buying.

Deep web is growing rapidly with multitude of devices and rendering capability. Despite the richness of deep Web forms, their rendering methodology is very poor in terms of capacity of expression. Hence, user has no indication about the richness of query and query capability when he interprets this interface. In this paper we propose a new rendering approach of deep Web forms which is easy to interpret by user and reflects the exact meaning of query. We have evaluated our algorithm on standard dataset and compared it to a well known state of the art algorithm. Our approach has proved good performances with respect to standard measures.

Design activities associated to the ideation phase of design processes require mutual understanding and clear communication based on artefacts. However, this is often a challenge for remote and multidisciplinary teams due to the lack of ad hoc tools for this purpose. Our approach is to solve these limitations by explicitly connecting pieces of information related to design rationale, feedback, and evolution with the artefacts that are subject of communication. We propose Helaba, a system that creates a shared workspace to support communication revolving around design artefacts and activities within multidisciplinary teams. Helaba supports design communication and rationale, and potentially leads to more satisfying outcomes from the design process.

Simultaneous cultivation of microorganisms in the specially designed experimental laboratory plant with five bioreactors system is a difficult problem. An especially important issue is the realization of the biomass biocoenosis stimulation by controlling the ratio of the dosed substrates. Such control requires a constant attendance by a two-person team of experimenters - the process operator and a measurement and analysis expert. In this paper, the necessity to carefully select the appropriate (well-cooperating) two-person teams for the operation of the process is discussed. An architecture of the “human-in-the-loop” control system is presented in which such control is proposed to be applied. The division of work between the cooperating experimenters has been discussed, taking into account its influence on proper cooperation.

The paper describes the use of the sequence diagrams in the design and analysis of the control software for biotechnological process. The goal was to automate the substrate preparation process. In many situations, a slight change in the substrate preparation procedure may lead to significant changes in the software performing this procedure. Assuming that the substrate can be prepared in two different ways (sequential or concurrent preparation of its components), it is shown that the UML sequence diagrams can be effective in analysis of the possible scenarios. As a result, one can obtain a control software that is suitable for each of the possible scenarios, and that can be easily implemented in the hierarchical distributed control system.

Process control algorithms constitute a specific software model, as they have well-defined and constant sets of inputs and outputs, and perform calculations cyclically in real time. Therefore, the algorithms rarely are implemented otherwise than embedded in the low level control instrumentation. This paper proposes a departure from this well-known approach in order to apply multiagent system directly in the control layer. While this novel approach creates few issues requiring resolving, such as the need to develop an agent-based software operating in real time, it also provides the crucial benefit i.e. the possibility of developing the modules of the control algorithm by experts from different fields, which allows for cooperative dynamic engineering of a control algorithm. The resulting methodology allows to include more modern and advanced solutions from various fields of control science than it is possible in the case of the classical approach.

The advanced control algorithms are often based on a mathematical model of the controlled plant and the performance of the control system largely depends on the accuracy of the plant model. However, simplified phenomenological or linear models are often used in practice. Because, the accuracy of these models may differ and vary over time, it is proposed a model verification system. Its main goal is the on-line verification of the accuracy of two plant models. The system is based on a concept of cooperating agents, which are distributed over several controllers. As a result, the proposed solution can be implemented in already existing industrial control systems, where each of the programmable logic controllers (PLCs) performs its basic tasks. The verification system has been implemented and tested on the several distributed PLCs.

This article sets out the four stages of an analytical approach which enables student - designers at the end of their academic career in the domain of design, to “metareflectively” consider their design and collaboration processes. Inspired by collaborative action research approaches, this analytical approach aims to create a space in which the student can learn and co-construct meaning relative to the activity of collaborative design. It plays a role in enabling the learner/designer/observer to take a step back from their activities, both when considering the activity in isolation and in confronting it to others’ points of view. This article explains the steps and tools (methodological, theoretical and analytical) involved; it also provides feedback on experiences from 7 different contexts. It shows how the system as a whole enables analysis, interpretation, questioning, and critical and collective reflection of the situation.

Due to the fact that majority of web content is provided within collaborative environments such as social media and social networks systems its complexity brings a new strong need for its accurate aggregation and understanding. Sentiment analysis (also known as opinion mining) is one of possibility to understand generated content that may brings an interesting summation in terms of attitudes expressed in texts. The paper proposes a new approach to sentiment analysis of polish language using machine learning approach.

High-speed networks together with visualizations in the highest resolutions enable new level of sharing visual perceptions. They can be used in interactive collaboration in real-time and in specialized training of professionals in many fields. In this paper we will focus on our practical experience in the medical field. We will present several scenarios for live surgery sessions and we will show the role of people who participate in it. The scenarios are different if the session is for a small or large group of attendees and if the session is a one way presentation of surgery techniques of famous surgeons or if it is an interactive session expecting high level of intercommunication including remote drawing into presented screens.

The inherently complex nature of the environmental domain requires that planning efforts become projects of participated, inclusive, multi-agent, multi-source knowledge building processes developed by the community. Knowledge is often hard to be processed, handled, formalized, modeled. Yet cognitive models are useful to avoid the typical unmanageability of domains with high complexity such as the environmental one, and enhance knowledge organization and management. We have investigated on the potentials of cognitivemapping- based tools, particularly on cross impact evaluations, in the case study of Taranto (Italy). The process was aimed at building up future development scenarios in city neighborhoods, and fuzzy cognitive mapping were used to support decision-making by exploring cross impacts of possible policy perspectives. Although substantial results are rather general, the study proves to be interesting in enhancing the potentials of FCM-based approach to support decisionmaking, particularly when dealing with well-focused policy perspectives.

How to discover and rank the scientific research team from the huge amount of literatures is a hard challenge for scientific researchers. Therefore, based on social network analysis with bibliometrics, a comprehensive method to discover and rank collaborative research teams is proposed in this paper. With the data from 2010-2015 in CIMS as the sample, of a Chinese journal of CIMS as the samples, n-clique and snow ball sampling method is used to identify collaborative research teams. Then, the research teams are ranked using indexes which include both scientific research outcomes and the close degree of Co-author networks. Case study shows that the method is more comprehensive than the ranking method which considers bibliometrics or network properties only.

The cross-enterprise business process is different from the common business process. More issues of level interoperability must be defined and differentiated. The enterprise interoperability framework has been proposed by five levels. And a novel method of cross-enterprise process collaboration is presented. In order to enhance the capability of process reengineering and change, the services composition strategy which is based on SCA components have been proposed. An example of cross-enterprise business of cloth-order in textile industry is illustrated and analyzed as well.

As-built modelling has potentials in progress tracking and quality control in industrial plants construction. Although noted work has been conducted, there remain gaps in sophistication of automation and the extent of recognition for semantic information during the process is low. This paper developed a new modelling process for industrial components to fill in these gaps by incorporating 3D object recognition and graph matching techniques. The new process firstly groups the point cloud data of industrial components into geometric primitives. The process is also developed to recognize industrial components by matching connection graph, which is retrieved from geometric primitives, of as-built model with that of as-designed model. Furthermore, the tracking process is able to identify schedule delays by deviation analysis between as-built and as-designed model. A pilot study is carried out and proves that the developed process enables as-built modelling with semantic information and automatic construction progress tracking. Results show that the developed method is promising in saving time and labor cost during construction.

Progress tracking is an essential management function for successful delivery of Liquefied Natural Gas (LNG) projects. It relies on accurate and prompt data collection from construction sites and project participants, which is then used to early detect actual or potential schedule delay. Currently, many Information Technology (IT)-supported methods have been implemented to improve progress tracking. However, none of them has been able to deliver satisfactory and reliable information. This paper aims to develop an integrated approach for construction progress tracking by integrating laser scanning, Building Information Modeling, mobile computing and Radio Frequency Identification. The approach consists of three modules: milestone progress tracking, onsite activity/Task progress tracking, and supply chain tracking. Finally, a pilot LNG project was selected to validate this approach.

With the emergence of cloud computing paradigm, it provides a promising new solution for sophisticated instance intensive applications. However, the reliability and response speed begins to be suffered because of the limitation of the Hadoop’s FIFO scheduling model. It becomes unacceptable to execute the large scale instance intensive tasks under such conditions. In order to enhance the system resource utilization, we propose a solution in this paper. We use a delay scheduling algorithm to determine the scheduling opportunity and reduce the cost. Delay scheduling can ensure that the current scheduled tasks can make full use of the physical resources, raise resource utilization, and reduce the probability of failure scheduling. The experimental evaluation illustrates that the large scale instance intensive tasks can benefit from the Min-cost delay scheduling algorithm presented in the paper.