Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multi-dimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in.

基于CPN的空竭服务单重休假M/G/1型排队系统建模与分析

空竭服务单重休假M/G/1型排队系统是经典排队系统的推广,在许多领域有着广泛的应用.到目前为止对其的处理方法还都是建立在概率论和数理统计的基础上,运用马尔可夫随机过程求解,推导十分复杂,没有直观的模型描述.因此,利用着色Petri网对空竭服务单重休假M/G/1型排队系统进行建模,并对主要性能指标进行仿真分析是迫切以及可行地.仿真软件选用CPNTools[1],仿真结果证明该方法具有较高的精确度以及实用价值.     

Geometric analysis of collaborative optimization

Instead of the past mathematical analyses, an intuitive geometric analysis of the collaborative optimization (CO) algorithm is presented in this paper, which reveals some geometric properties of CO and gives a direct geometric interpretation of the reason for the reported computational difficulties in CO. The analysis shows that if the system-level optimum point at one iteration is outside the feasible region of the original optimization problem, at the next iteration, the system-level optimization problem may be infeasible due to the system-level consistency equality constraints. One way to solve the problem of the infeasibility is to relax the system-level consistency equality constraints using inequality constraints. However it is a delicate job to determine a rational relaxed tolerance because feasibility and consistency have conflicting requirements for the tolerance, that is, the more relaxed the better for feasibility while the stricter the better for consistency. Based on the geometric analysis, a method of variable relaxed tolerance is put forward to solve this problem. In this method, an adaptive adjustment of the tolerance is made at each iteration according to the quantified inconsistency between two subsystems. In the last section, the capabilities and limitations of the proposed method are illustrated by three examples.     

Prediction-based diagnosis and loss prevention using qualitative multi-scale models

A prototype prediction based intelligent diagnostic system that is capable of integrating qualitative and quantitative process models and operational experience in the form of HAZOP result tables is proposed in this paper.The diagnostic system utilizes Gensym’s real time G2 expert system software. Its diagnostic “cause-effect” rules and possible actions (suggestions) are extracted from the results of standard HAZOP analysis. The knowledge base of the system is organized in a hierarchical way following the hierarchy levels of a multi-scale model of the process system. This supports focusing used by fault detection and loss prevention and thus decomposes the otherwise computationally hard problem. Prediction by simplified dynamic models are used to reduce ambiguity in case of multiple possible causes and/or multiple possible mitigating actions.The system is illustrated on the example of a commercial fertilizer granulator circuit using a simulation test bed.     

Pessimists and optimists: Improving collaborative filtering through sentiment analysis

This work presents a novel application of Sentiment Analysis in Recommender Systems by categorizing users according to the average polarity of their comments. These categories are used as attributes in Collaborative Filtering algorithms. To test this solution a new corpus of opinions on movies obtained from the Internet Movie Database (IMDb) has been generated, so both ratings and comments are available. The experiments stress the informative value of comments. By applying Sentiment Analysis approaches some Collaborative Filtering algorithms can be improved in rating prediction tasks. The results indicate that we obtain a more reliable prediction considering only the opinion text (RMSE of 1.868), than when apply similarities over the entire user community (RMSE of 2.134) and sentiment analysis can be advantageous to recommender systems.     

Design and implementation of an agent-based collaborative product design system

The evolution of computer science and technology has brought new opportunities for multidisciplinary designers and engineers to collaborate with each other in a concurrent and coordinated manner. The development of computational agents with unified data structures and software protocols contributes to the establishment of a new way of working in collaborative design, which is increasingly becoming an international practice. In this paper, based on the analysis of the dynamic nature of collaborative design process, a new framework for collaborative design is described. This framework adopts an agent-based approach and relocates designers, managers, systems, and the supporting agents in a unified knowledge representation scheme for product design. In order to model the constantly evolving design process and the rationales resulted from design collaboration, a Collaborative Product Data Model (CPDM) and a constraint-based Collaborative Design Process Model (CDPM) are proposed to facilitate the management and coordination of the collaborative design process as well as design knowledge management. A prototype system of the proposed framework is implemented and its feasibility is evaluated using a real design scenario whose objective is designing a set of dining table and chairs.     

Modelling and control of a class of time-varying continuous flow processes

Models of variable parameter flow processes are derived and their control is discussed. Using a pH reactor with varying flow rate as an example a variable transformation is introduced, which makes the model equations invariant under a new time scale. For a restricted class of flow processes classical analysis and synthesis methods can then be used to design a proper controller to guarantee the system stability and performance in general. The method is illustrated by developing a time-varying PID-controller algorithm as an example. Both simulation results and pilot-plant tests are reported, to verify the performance of the controller.     

On the combination of user-based and item-based collaborative filtering

In this paper, we propose two new filtering algorithms which are a combination of user-based and item-based collaborative filtering schemes. The first one, Hybrid-Ib, identifies a reasonably large neighbourhood of similar users and then uses this subset to derive the item-based recommendation model. The second algorithm, Hybrid-CF, starts by locating items similar to the one for which we want a prediction, and then, based on that neighbourhood, it generates its user-based predictions. We start by describing the execution steps of the algorithms and proceed with extended experiments. We conclude that our algorithms are directly comparable to existing filtering approaches, with Hybrid-CF producing favorable or, in the worst case, similar results in all selected evaluation metrics.     

基于随机灵敏度分析的化工过程裕量设计

对化工过程进行最优设计时,由于过程中参数的不确定性,需要在既满足过程约束又保证经济效益最优的前提下对设计变量增加裕量。本文考虑过程不确定参数的随机分布,结合灵敏度分析,提出一种基于随机灵敏度的化工过程最优裕量设计方法。首先,取不确定参数的标称值,进行化工过程最优设计,得到最优设计点的标称值;其次,假设过程不确定参数服从正态分布,基于灵敏度分析确定约束变量的均值和方差,在保证低概率违反约束的条件下优化求解设计裕量,定量分析不确定参数对设计变量的影响;最后,通过对串联连续搅拌釜式反应器（Continuous stirred tank reactor,CSTR）系统进行仿真实验,说明该裕量设计方法的具体步骤,并得到合理的设计裕量值,验证所提方法的正确性。     

New methods for interaction analysis of complex processes using weighted graphs

The selection of the structure of a controller in large scale industry processes usually requires extensive process knowledge. The aim of this paper is to report new results on recently suggested methods for the analysis of complex processes. These methods aid the designers in comprehending a process by representing structural and functional relationships from actuators and process disturbances to measured or estimated variables. The methods are formulated in a flexible framework based on graph theory, which can also be used for closed-loop analysis. Additionally, the sensitivity of the methods to scaling and time delays are discussed and resolved. It is also proposed how filtering can be used to restrict the analysis to a frequency region of interest.The feasibility of the methods is shown by the use of three case studies. A quadruple tank process is used to exemplify the methods and their use. Then the methods are applied on a real-life process, the stock preparation plant of a pulp and paper mill. The third study case analyzes a previously published example in closed loop.It is shown that the methods can be used to take efficient decisions on decentralized and sparse control structures, as well as assessing the channel interactions in a closed-loop system.     

Coloured Petri Nets and CPN Tools for modelling and validation of concurrent systems

Coloured Petri Nets (CPNs) is a language for the modelling and validation of systems in which concurrency, communication, and synchronisation play a major role. Coloured Petri Nets is a discrete-event modelling language combining Petri nets with the functional programming language Standard ML. Petri nets provide the foundation of the graphical notation and the basic primitives for modelling concurrency, communication, and synchronisation. Standard ML provides the primitives for the definition of data types, describing data manipulation, and for creating compact and parameterisable models. A CPN model of a system is an executable model representing the states of the system and the events (transitions) that can cause the system to change state. The CPN language makes it possible to organise a model as a set of modules, and it includes a time concept for representing the time taken to execute events in the modelled system. CPN Tools is an industrial-strength computer tool for constructing and analysing CPN models. Using CPN Tools, it is possible to investigate the behaviour of the modelled system using simulation, to verify properties by means of state space methods and model checking, and to conduct simulation-based performance analysis. User interaction with CPN Tools is based on direct manipulation of the graphical representation of the CPN model using interaction techniques, such as tool palettes and marking menus. A license for CPN Tools can be obtained free of charge, also for commercial use.     

Relations between task and activity: elements for elaborating a framework for error analysis

The notion of error, when applied to an activity or the result of an activity, implies the notion of task: it expresses the deviation between the activity and the task being considered from an angle which is judged to be relevant. The task and the activity are the object of representations for the analyst (or specialist) and for the driver. Four representations are dealt with in this paper: the task and the activity for the specialist and the task and the activity for the driver. An interpretation is proposed for these tasks, and they are illustrated using some of the work already carried out in this field. The signification of deviations between these representations is then discussed, together with the advantage of studying these deviations in order to clarify error-producing mechanisms. Analysis in terms of task and activity raises methodological and practical problems which are touched upon; it does not exclude referring to psychological theoretical frameworks to which it is worthwhile linking it. This perspective raises questions which make it possible to enhance the study of errors: it could be completed at a later date by extending it to include other representation categories.     

A domain model of Web recommender systems based on usage mining and collaborative filtering

Considering the increasing demand of multi-agent systems, the practice of software reuse is essential to the development of such systems. Multi-agent domain engineering is a process for the construction of domain-specific agent-based reusable software artifacts, like domain models, representing the requirements of a family of multi-agent systems in a domain, and frameworks, implementing reusable agent-based design solutions to those requirements. This article describes the domain modeling tasks of the MADEM methodology and a case study on the application of GRAMO, a MADEM technique, for the construction of the domain model of ONTOWUM, specifying the common and variable requirements of a family of Web recommender systems based on usage mining and collaborative filtering.     

Distributed and collaborative visualization of large data sets using high-speed networks

We describe an architecture for distributed collaborative visualization that integrates video conferencing, distributed data management and grid technologies as well as tangible interaction devices for visualization. High-speed, low-latency optical networks support high-quality collaborative interaction and remote visualization of large data.     

Integrated design and collaborative engineering of fabric structures

The design of fabric structures incorporates specfic aspects due to the tight interdependency between geometric, mechanical and manufacturing data used by the different professional partners. This is highlighted through the analysis of the various steps of the design process. A design approach, that takes into account the various actors, their knowledge and the techniques available within each of the previous fields has been set up.This approach relies on the identification of the flow of information and on the organization of data sets that are compatible with the design process breakdown into tasks in order to preserve their integration. Approximation methods are associated with some of this information to create design phases adapted to each actor through software tools implementing various modelling processes. The form finding process, the mechanical analysis of the structure, the determination of cutting patterns are examples of such modelling processes. The surface model of the fabric structure is one of such sets of data which has been identified and used to preserve the integration of the design process.Associated with the integrated design architecture, a collaborative environment helps to set up communication between some of the actors according to the design process organization. This environment acts as a complementary tool to help seeking compromises among the actors participating in a given phase of the design process. The communication tools work on a distributed architecture in such a manner that dialogue objects are shared among the actors.     

Comparing collaborative drawing tools and whiteboards: An analysis of the group process

Collaborative drawing tools, which are designed to allow multiple users to share an electronic drawing space, have recently become the focus of many researchers' efforts. While advances have been made in the technological implementation of these tools, little is known about the effect these tools have on group processes. This paper discusses a study that was conducted to compare groups using conventional (whiteboard) technology to those using collaborative drawing tools. The results of these two experiments provide evidence that these tools alter the way in, which groups work. For some types of tasks, the amount of interaction among group members using a collaborative drawing tool tends to be less than among groups using conventional technology. Groups using collaborative drawing tools tended to take significantly longer than whiteboard groups. Possible reasons for these results are further explored in this paper.     

A new method for expiration code detection and recognition using gabor features based collaborative representation

Text in images and video contains important information for visual content understanding, indexing, and recognizing. Extraction of this information involves preprocessing, localization and extraction of the text from a given image. In this paper, we propose a novel expiration code detection and recognition algorithm by using Gabor features and collaborative representation based classification. The proposed system consists of four steps: expiration code location, character isolation, Gabor features extraction and characters recognition. For expiration code detection, the Gabor energy (GE) and the maximum energy difference (MED) are extracted. The performance of the recognition algorithm is tested over three Gabor features: GE, magnitude response (MR) and imaginary response (IR). The Gabor features are classified based on collaborative representation based classifier (GCRC). To encompass all frequencies and orientations, downsampling and principal component analysis (PCA) are applied in order to reduce the features space dimensionality. The effectiveness of the proposed localization algorithm is highlighted and compared with other existing methods. Extensive testing shows that the suggested detection scheme outperforms existing methods in terms of detection rate for large image database. Also, GCRC show very competitive results compared with Gabor feature sparse representation based classification (GSRC). Also, the proposed system outperforms the nearest neighbor (NN) classifier and the collaborative representation based classification (CRC).     

Collaborative design and analysis of supply chain network management key processes model

This study focuses on collaboratively designing a structured and comprehensive supply chain (SC) network management key processes model and analyzing the relative importance of these key processes for semiconductor industry. The collaborative design and analysis are performed by a multidisciplinary team consisting of over 20 members from both academia and industry. This research is based on experiences of these team members who joined a successful e-SCM project, used as a case study in this research, between the world's largest semiconductor foundry and the world's largest assembly and testing service provider. This study adopts focus group methodology for collaborative design and fuzzy analytic hierarchy process (FAHP) for collaborative analysis. The result of the design is a structured and comprehensive key processes model consisting of four dimensions: strategy and planning, manufacturing, logistics, and risk management (SMLR) with a total of 15 key processes included in these four dimensions. The resulting weightings from FAHP analysis can identify the most critical one dimension and four key processes since they account for approximately half of the overall weighting in their level. The SMLR model provides a structured and comprehensive reference model for future SC network management project executives, ensuring that all key processes are supported to avoid extremely costly failure. The resulting weightings provide these managers with the relative importance of these key processes and can help them make critical decisions in allocating limited resources to support the most critical processes. To confirm the results and further explore the managerial implications, a second session of focus group meeting was conducted and practices of the top three key processes in the semiconductor manufacturing industry were used to illustrate what actions can be performed to improve these processes and hence benefit the entire SC network. The research results can serve as a foundation for related academic researches.     

Evaluation and selection of group recommendation strategies for collaborative searching of learning objects

Nowadays, there is a wide variety of e-learning repositories that provide digital resources for education in the form of learning objects. Some of these systems provide recommender systems in order to help users in the search for and selection of the learning objects most appropriate to their individual needs. The search for and recommendation of learning objects are usually viewed as a solitary and individual task. However, a collaborative search can be more effective than an individual search in some situations – for example, when developing a digital course between a group of instructors. The problem of recommending learning objects to a group of users or instructors is much more difficult than the traditional problem of recommending to only one individual. To resolve this problem, this paper proposes a collaborative methodology for searching, selecting, rating and recommending learning objects. Additionally, voting aggregation strategies and meta-learning techniques are used in order to automatically obtain the final ratings without having to reach a consensus between all the instructors. A functional model has been implemented within the DELPHOS hybrid recommender system. Finally, various experiments have been carried out using 50 different groups in order to validate the proposed learning object group recommendation approach.