A web based collaborative testing environment

This paper presents a computer supported collaborative testing system built upon the Siette web-based assessment environment. The application poses the same set of questions to a group of students. Each student in the group should answer the same question twice. An initial response is given individually, without knowing the answers of others. Then the system provides some tools to show the other partners' responses, to support distance collaboration. Finally a second individual answer is requested. In this way assessment and collaboration activities are interlaced. At the end of a collaborative testing session, each student will have two scores: the initial score and the final score. Three sets of experiments have been carried out: (1) a set of experiments designed to evaluate and fine tune the application, improve usability, and to collect users' feelings and opinions about the system; (2) a second set of experiments to analyze the impact of collaboration in test results, comparing individual and group performance, and analyzing the factors that correlate to those results; and (3) a set of experiments designed to measure individual short-term learning directly related to the collaborative testing activity. We study whether the use of the system is associated with actual learning, and whether this learning is directly related to collaboration between students. Our studies confirm previous results and provide the following evidence (1) the performance increase is directly related to the access to other partners' answers; (2) a student tends to reach a common answer in most cases; and (3) the consensus is highly correlated with the correct response. Moreover, we have found evidence indicating that most of the students really do learn from collaborative testing. High-performing students improve by self-reflection, regardless the composition of the group, but low-performing students need to be in a group with higher-performing students in order to improve.     

An algorithm for efficient privacy-preserving item-based collaborative filtering

Collaborative filtering (CF) methods are widely adopted by existing recommender systems, which can analyze and predict user “ratings” or “preferences” of newly generated items based on user historical behaviors. However, privacy issue arises in this process as sensitive user private data are collected by the recommender server. Recently proposed privacy-preserving collaborative filtering (PPCF) methods, using computation-intensive cryptography techniques or data perturbation techniques are not appropriate in real online services. In this paper, an efficient privacy-preserving item-based collaborative filtering algorithm is proposed, which can protect user privacy during online recommendation process without compromising recommendation accuracy and efficiency. The proposed method is evaluated using the Netflix Prize dataset. Experimental results demonstrate that the proposed method outperforms a randomized perturbation based PPCF solution and a homomorphic encryption based PPCF solution by over 14X and 386X, respectively, in recommendation efficiency while achieving similar or even better recommendation accuracy.     

An efficient and secure approach for a cloud collaborative editing

The demand for cloud-based collaborative editing service is rising along with the tremendously increased popularity in cloud computing. In the cloud-based collaborative editing environment, the data are stored in the cloud and able to be accessed from everywhere through every compatible device with the Internet. The information is shared with every accredited user in a group. In other words, multiple authorized users of the group are able to work on the same document and edit the document collaboratively and synchronously online. Meanwhile, during the whole collaborative editing process, the encryption technique is eventually applied to protect and secure the data. The encryption for the collaborative editing, however, could require much time to operate. To elevate the efficiency of the encryption, this study first analyzes the text editing in the collaborative service and presents a framework of the Red–Black tree, named as rbTree-Doc. The rbTree-Doc can reduce the amount of data to be encrypted. Although the trade-off for creating the Red–Black tree introduces extra cost, the experimental results of using rbTree-Doc in text editing operations, such as insertion and removal, show improved efficiency compared with other whole-document encryption strategy. Using rbTree-Doc, the efficiency is improved by 31.04% compared to that 3DES encryption is applied and by 23.94% compared to that AES encryption is applied.     

Computer support for learning in collaborative contexts: prompted hypothesis testing in physics

An enormous amount of work has been carried out into the ways in which computers can support collaboration in the service of learning. Less attention has been paid to computer support for learning when collaboration is non-problematic, yet this is arguably of equal significance. Recognizing this, the present paper reports software which was developed to help collaborating pupils test hypotheses, an activity thought by many to be relevant to conceptual learning. The software addressed hypotheses relating to: (a) the factors which influence the pressure of water; and (b) the factors which influence the formation of shadows. It required collaborating pupils to formulate hypotheses about such factors, decide which factors must be manipulated to check correctness, formulate predictions about outcomes prior to testing, observe the results of tests, and draw conclusions across test series. Pupils were asked to input their decisions at key points as they used the software, and they received prompts to the extent that their decisions were inappropriate. The prompts became increasingly explicit as inappropriate decisions persisted. The paper describes the use of the software by 9–14-year-old pupils, comparing their activity with that of similarly aged pupils who worked with otherwise equivalent software which lacked any prompts. Evidence is presented for the value of prompting, with implications not simply for the use of hypothesis testing as an instructional strategy but also for the design of computer-based support for other complex and co-ordinated activities.     

一种AFDX交换机的高效检测方法

航空电子全双工交换以太网(AFDX)是为航电信息系统之间进行数据通信而专门制定的协议标准,具有确定性、双余度和可靠性等优点,已成功应用于新一代航电网络。分析了ARINC 664 Part7中交换机章节及对应的通信架构等关键技术特点,提出一种高效率适合AFDX交换机的通信测试方法。通过测试与验证,证明该方法对通信功能的测试正确且效率较高。     

An expressive framework and efficient algorithms for the analysis of collaborative tagging

The rise of Web 2.0 is signaled by sites such as Flickr, del.icio.us, and YouTube, and social tagging is essential to their success. A typical tagging action involves three components, user, item (e.g., photos in Flickr), and tags (i.e., words or phrases). Analyzing how tags are assigned by certain users to certain items has important implications in helping users search for desired information. In this paper, we develop a dual mining framework to explore tagging behavior. This framework is centered around two opposing measures, similarity and diversity, applied to one or more tagging components, and therefore enables a wide range of analysis scenarios such as characterizing similar users tagging diverse items with similar tags or diverse users tagging similar items with diverse tags. By adopting different concrete measures for similarity and diversity in the framework, we show that a wide range of concrete analysis problems can be defined and they are NP-Complete in general. We design four sets of efficient algorithms for solving many of those problems and demonstrate, through comprehensive experiments over real data, that our algorithms significantly out-perform the exact brute-force approach without compromising analysis result quality.     

Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets

The deployment of highly interactive, media-rich applications on mobile devices is hindered by the inherent limitations on compute power, memory and battery capacity of these hand-held platforms. The cloudlet concept, opportunistically offloading computation to nearby devices, has proven to be a viable solution in offering resource-intensive applications on mobile devices. In this paper, we propose to extend the cloudlet concept with collaborative scenarios, in which not only hardware resources for processing are shared between all cloudlet users, but also the data computed.In a cloudlet, the resource demand should be spread over all available cloudlet nodes. User mobility and fluctuations in wireless bandwidth will cause the optimal resource allocation to vary over time. The cloudlet middleware must continuously balance the performance gain of reallocating components with the operational costs in terms of user experience and management complexity. In this paper, we formulate this optimization problem based on a theoretical cloudlet model capturing the infrastructure, application structure and user behavior.In order to solve this problem, two heuristic allocation algorithms based on Steepest Descent (SD) and Simulated Annealing (SA) are described. Besides optimality of the found solution, it is also important to limit the number of reallocations at runtime. To evaluate the performance and stability of the algorithms, we propose a discrete-event model for cloudlet simulation. For multiple application scenarios, we observe that SD performs 4 times less reallocations than SA. By introducing hysteresis, the number of reallocations by SA can be nearly halved without any significant degradation of application performance.     

An efficient hybrid multicast transport protocol for collaborative virtual environment with networked haptic

In recent years, we have witnessed a growing interest in the synchronous collaboration based class of applications. Several techniques for collaborative virtual environments (CVE), haptic, audio and visual environments (C-HAVE) have been designed. However, several challenging issues remain to be resolved before CVE and C-HAVE become a common place. In this paper, we focus on applications that are based on closely coupled and highly synchronized haptic tasks that require a high-level of coordination among the participants. Four main protocols have been designed to resolve the synchronization issues in such environments: the synchronous collaboration transport protocol, the selective reliable transmission protocol, the reliable multicast transport protocol and the scalable reliable multicast. While these four protocols have shown good performance for CVE and C-HAVE class of applications, none of these protocols has been able to meet all of the basic CVE requirements, i.e., scalability, reliability, synchronization, and minimum delay. In this paper, we present a hybrid protocol that is able to satisfy all of the CVE and C-HAVE requirements and discuss its implementation and results in two tele-surgery applications. This work is partially supported by Grants from Canada Research Chair Program, NSERC, OIT/Ontario Distinguished Researcher Award, Early Research Award and ORNEC Research Grant.     

CCM‐SLAM: Robust and efficient centralized collaborative monocular simultaneous localization and mapping for robotic teams

Robotic collaboration promises increased robustness and efficiency of missions with great potential in applications, such as search‐and‐rescue and agriculture. Multiagent collaborative simultaneous localization and mapping (SLAM) is right at the core of enabling collaboration, such that each agent can colocalize in and build a map of the workspace. The key challenges at the heart of this problem, however, lie with robust communication, efficient data management, and effective sharing of information among the agents. To this end, here we present CCM‐SLAM, a centralized collaborative SLAM framework for robotic agents, each equipped with a monocular camera, a communication unit, and a small processing board. With each agent able to run visual odometry onboard, CCM‐SLAM ensures their autonomy as individuals, while a central server with potentially bigger computational capacity enables their collaboration by collecting all their experiences, merging and optimizing their maps, or disseminating information back to them, where appropriate. An in‐depth analysis on benchmarking datasets addresses the scalability and the robustness of CCM‐SLAM to information loss and communication delays commonly occurring during real missions. This reveals that in the worst case of communication loss, collaboration is affected, but not the autonomy of the agents. Finally, the practicality of the proposed framework is demonstrated with real flights of three small aircraft equipped with different sensors and computational capabilities onboard and a standard laptop as the server, collaboratively estimating their poses and the scene on the fly.     

Evaluation and comparison of two efficient probabilistic primality testing algorithms

We analyse two recent probabilistic primality testing algorithms; the first one is derived from Miller [6] in a formulation given by Rabin [7], and the second one is from Solovay and Strassen [9]. Both decide whether or not an odd number n is prime in time O(m, lognM(n)) with an error probability less than α^m, for some $\text{0≤a<}\text{1}\text{2}$. Our comparison shows that the first algorithm is always more efficient than the second, both in probabilistic and algorithmic terms.     

IPOG/IPOG‐D: efficient test generation for multi‐way combinatorial testing

This paper presents two strategies for multi‐way testing (i.e. t‐way testing with t>2). The first strategy generalizes an existing strategy, called in‐parameter‐order, from pairwise testing to multi‐way testing. This strategy requires all multi‐way combinations to be explicitly enumerated. When the number of multi‐way combinations is large, however, explicit enumeration can be prohibitive in terms of both the space for storing these combinations and the time needed to enumerate them. To alleviate this problem, the second strategy combines the first strategy with a recursive construction procedure to reduce the number of multi‐way combinations that have to be enumerated. Both strategies are deterministic, i.e. they always produce the same test set for the same system configuration. This paper reports a multi‐way testing tool called FireEye, and provides an analytic and experimental evaluation of the two strategies. Copyright © 2007 John Wiley & Sons, Ltd.     

AICF: Attention-based item collaborative filtering

Item-to-item collaborative filtering (short for ICF) has been widely used in ecommerce websites due to his interpretability and simplicity in real-time personalized recommendation. The focus of ICF is to calculate the similarity between items. With the rapid development of machine learning in recent years, it takes similarity model instead of cosine similarity and Pearson coefficient to calculate the similarity between items in recommendation. However, the existing similarity models can not sufficient to express the preferences of users for different items. In this work, we propose a novel attention-based item collaborative filtering model(AICF) which adopts three different attention mechanisms to estimate the weights of historical items that users have interacted with. Compared with the state-of-the-art recommendation models, the AICF model with simple attention mechanism Self-Attention can better estimate the weight of historical items on non-sparse data sets. Due to depth models can model complex connection between items, our model with the more complex Transformer achieves superior recommendation performance on sparse data. Extensive experiments on ML-1M and Pinterest-20 show that the proposed model greatly outperforms other novel models in recommendation accuracy and provides users with personalized recommendation list more in line with their interests.     

How collaborative technology supports cognitive processes in collaborative process modeling: A capabilities-gains-outcome model

We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling.     

Trust modeling in a distributed collaborative environment: application to a collaborative healthcare system

International Journal of Information Security - The issue of trust is a primary concern for individuals in distributed collaborative environments (DCEs), particularly in emergencies such as the...     

A highly secured and streamlined cloud collaborative editing scheme along with an efficient user revocation in cloud computing

These days with the expanded fame of cloud computing, the interest for cloud-based collaborative editing service is rising. The encryption method is utilized to ensure and secure the data, during the collaborative editing process. In the encryption process, the cloud requires more time to work the collaborative editing. This paper proposes an efficient scheme for reducing the encryption burden over the cooperative users, as the possibilities of cooperative users read and write data by means of any gadget. In the proposed scheme, the encrypted file sent by the data owner is split into smaller segments and stored in the cloud by the cloud service provider (CSP) along with specific tags. Once the cooperative user receives and decrypts the file from the CSP, it modifies and encrypts only the modified segment and resends to the CSP. The CSP after verifying the signature replace the original file segment in the cloud with the modified segment based on the tag information. The scheme that is put forward is performed based on the modified ciphertext-policy hierarchical attribute–based encryption, and the security process is done based on the attribute-based signature schemes. This work employs a proficient attribute updating method to accomplish the dynamic change of users' attributes, consisting granting new attributes, revoking previous attributes, and regranting formerly revoked attributes. A writer's attributes and keys have been revoked, and the stale information cannot be written.     

Enabling collaborative work: Work in progress

Mobile handheld and wearable computer systems to support fieldworkers (e.g. aircraft mechanics) doing a variety of tasks have been designed and studied by Carnegie Mellon University (CMU) researchers since 1991. We developed an initial research agenda and found some important results associated with the design and use of such systems. This article summarises some of the key findings from CMU's research and describes the results from one heuritic usability study about mobile handheld and wearable computer systems. Based on these research results, we put forward a new research agenda addressing important issues still to be resolved.     

CSsCL: the performance of collaborative learning

International Journal of Computer-Supported Collaborative Learning - This article discusses the integration of three concepts central to the enterprise of computer-supported collaborative learning:...     

CFMDA: collaborative filtering-based MiRNA-disease association prediction

Multimedia Tools and Applications - MicroRNAs (miRNAs) are increasingly becoming the focus in a number of researches because abundant studies certify miRNAs play vital roles and have critical...