Report from CSCWID 97

TheSecondInternationalWorkshoponCSCW(Computer-SupportCooperativeWork)inDesign(CSCWID'97),jointlyorganizedbytheInstituteofComputingTechnology(ICT),ChineseAcademyofSciences,washeldonNovember26-28,l997inBangkok,Thailand,atNationalElectronicsandComputerTechnologyCenter(NECTEC).Inadditionto1otechnicalsessionswith62paPerspresented,therewerealsoatutorialsessionandexhibitions,providingattendeeswithaviewofemergingtechnologiesfromboththeresearchandengineeringperspectives.overviewoftheSes…     

Green Charm from Green Design

1 Introduction As the fast development of the world economy, energies are employed on great scale but poor effectiveness. A great deal of waste is produced and almost two thirds of cities in China are surrounded by rubbish which deteriorates the environment and threatens the people’s health and even lives [1]. The overuse and serious pollution of the underground water will lead to no water for civilian use in 50 years. Saving water has become an urgent task under the pressure of water shorta…     

Surface reconstruction from stereoscopy and “shape from shading” in SEM images

The computational reconstruction of surface topographies from scanning electron microscope (SEM) images has been extensively investigated in the past, but fundamental image processing problems still exist. Since conventional approaches adapted from general-purpose image processing have not sufficiently met the requirements in terms of resolution and reliability, we have explored combining different methods to obtain better results.This paper presents a least-squares combination of conventional stereoscopy with shape from shading and a way of obtaining self-consistent surface profiles from stereoscopy and stereo-intrinsic shape from shading using dynamic programming techniques. Results are presented showing how this combined analysis of multi-sensorial data yields improvements of the reconstructed surface topography that cannot be obtained from individual sensor signals alone.     

Who benefits from virtuality?

For educational software to take advantage of contemporary views of learning, instructional designers need to employ design models that incorporate the variety of ideas that are based on constructivist frameworks for developing learning environments. These environments, if well designed, can support learner construction of knowledge, however, such frameworks are based upon arguments that learners should be placed in authentic environments that incorporate sophisticated representations of context through such constructs as “virtual worlds”. Within these environments the learner is supported by visual metaphors constructed to represent the information structure and how the “world” operates. This paper will discuss the framework employed in the development of several virtual solutions and the process by which they were constructed.     

Ordinal depth information from accommodation?

The ability to judge egocentric distance was assessed in two groups of six observers using a manual pointing task. The purpose of the study was to determine the extent to which blur-driven accommodation can provide information on target distance in the absence of any retinal cues to distance. Observers were extremely accurate when carrying out the pointing task in a 'full-cue' condition. In contrast, observers were extremely poor at carrying out the task when accommodation was the only distance cue available. Responses on individual trials bore little relationship to the actual target distance in any of the observers. On the other hand, accommodation weakly biased the mean responses in some observers. This bias appears to be due to the observers' effective use of accommodation to determine whether the target presented in one trial was nearer or further away than the target presented in the previous trial. Accommodation therefore appears to provide ordinal information, although the distance signal may actually arise from accommodation-driven vergence. The poverty of accommodation as a source of metric information was highlighted in a second group of observers who all demonstrated a strong bias when perceiving distance in the presence of an initially ambiguous retinal cue. It is concluded that accommodation can act as a source of ordinal distance information in the absence of other cues to distance but the contribution of accommodation to normal distance perception in full-cue conditions is questioned.     

Clustering： from Clusters to Knowledge

Data analysis and automatic processing is often interpreted as knowledge acquisition. In many cases it is necessary to somehow classify data or find regularities in them. Results obtained in the search of regularities in intelligent data analyzing applications are mostly represented with the help of IF-THEN rules. With the help of these rules the following tasks are solved： prediction, classification, pattern recognition and others. Using different approaches---clustering algorithms, neural network methods, fuzzy rule processing methods--we can extract rules that in an understandable language characterize the data. This allows interpreting the data, finding relationships in the data and extracting new rules that characterize them. Knowledge acquisition in this paper is defined as the process of extracting knowledge from numerical data in the form of rules. Extraction of rules in this context is based on clustering methods K-means and fuzzy C-means. With the assistance of K-means, clustering algorithm rules are derived from trained neural networks. Fuzzy C-means is used in fuzzy rule based design method. Rule extraction methodology is demonstrated in the Fisher＇s Iris flower data set samples. The effectiveness of the extracted rules is evaluated. Clustering and rule extraction methodology can be widely used in evaluating and analyzing various economic and financial processes.     

Where do requirements come from?

What should a product do? What qualities should it have? How do we determine these requirements for new generations of products? Requirements engineering is an activity in which a wide variety of stakeholders work together to answer these questions. The answers do not arrive by themselves, there is a need to-ask, observe, discover, and increasingly create requirements. If we want to build competitive and imaginative products that avoid re-implementing the obvious, we must make creativity part of the requirements process. Indeed, the importance of creative thinking is expected to increase over the next decade. Unfortunately, most RE research and practice does not recognize this important trend. We highlight some important information sources for creativity and innovation and present some useful examples of creative RE as references to guide and inspire readers     

Extracting Schema from an OEM Database

While the schema-less feature of the OEM(Object Exchange Modl)gives flexibility in representing semi-structured data,it brings difficulty in formulating database queries. Extracting schema from an OEM database then becomes an important research topic.This paper presents a new approach to this topic with th following reatures.(1)In addition to representing th nested label structure of an OEM database,the proposed OEM schema keeps up-tp-date information about instance objects of the database,The object-level information is useful in speeding up query evaluation.(2)The OEM schema is explicitly represented as a label-set,which is easy to construct and update.(3)The OEM schema of a database is statically built and dynamically updated.The time complexity of building the OEM schems is linear in the size of the OEM database.(4)The approach is applicable to a wide range of areas where the underlying schema is much smaller than the database itself(e.g.data warehouses that are made from a set of heterogeneous databases).     

Extractors from Reed–Muller codes

Finding explicit extractors is an important derandomization goal that has received a lot of attention in the past decade. Previous research has focused on two approaches, one related to hashing and the other to pseudorandom generators. A third view, regarding extractors as good error correcting codes, was noticed before. Yet, researchers had failed to build extractors directly from a good code without using other tools from pseudorandomness. We succeed in constructing an extractor directly from a Reed–Muller code. To do this, we develop a novel proof technique.Furthermore, our construction is the first to achieve degree close to linear. In contrast, the best previous constructions brought the log of the degree within a constant of optimal, which gives polynomial degree. This improvement is important for certain applications. For example, it was used [E. Mossel, C. Umans, On the complexity of approximating the VC dimension, J. Comput. System Sci. 65 (2002) 660–671] to show that approximating VC dimension to within a factor of $N^{1-\delta }$ is AM-hard for any positive δ.     

Three-Dimensional Volume Datafield Reconstruction from Physical Model

1IntroductionVisualizationinscientificcomputingisarapidlygrowingapplicationofcom-putergraphicsandhasmadeanirreplaceablecontributiontothepresentationofscientificdata.Inthepastfewyears,mostoftheresearchesofvisuaJizationfocusedontherenderingofdatasets.Manysurface-basedrenderingandvolumerenderingaPproacheshavebeenputforward[1-8].Intheseapplications,thedatafieldsweresimplydescribedasthree-dimensionalregularorirregulardatameshesandtheobjectsinthedatafieldwerereconstructedbyisosurfacesinelemellts.H…     

Extracting and Sharing Knowledge from Medical Texts

In recent years,we have been developing a new framework for acquiring medical knowledge from Encyclopedic texts.This framework consists of three major parts.The first part is an extended high-level conceptual language (called HLCL 1.1)for use by knowledge engineers to formalize knowledge texts in an encyclopedia.The other part is an HLCL 1.1 compiler for parsing and analyzing the formalized texts into knowledge models. The third part is a set of domain-specific ontologies for sharing knowledge.     

Eliminating “converse” from converse PDL

In this paper we show that it is possible to eliminate the converse operator from the propositional dynamic logic CPDL (Converse PDL), without compromising the soundness and completeness of inference for it. Specifically we present an encoding of CPDL formulae into PDL that eliminates the converse programs from a CPDL formula, but adds enough information so as not to destroy its original meaning with respect to satisfiability, validity, and logical implication. Notably, the resulting PDL formula is polynomially related to the original one. This fact allows one to build inference procedures for CPDL, by encoding CPDL formulae into PDL, and then running an inference procedure for PDL.     

Lessons from molecular modeling human α-l-iduronidase

Human α-l-iduronidase (IDUA) is a member of glycoside hydrolase family and is involved in the catabolism of glycosaminoglycans (GAGs), heparan sulfate (HS) and dermatan sulfate (DS). Mutations in this enzyme are responsible for mucopolysaccharidosis I (MPS I), an inherited lysosomal storage disorder. Despite great interest in determining and studying this enzyme structure, the lack of a high identity to templates and other technical issues have challenged both bioinformaticians and crystallographers, until the recent publication of an IDUA crystal structure (PDB: 4JXP). In the present work, four alternative IDUA models, generated and evaluated prior to crystallographic determination, were compared to the 4JXP structure. A combined analysis using several viability assessment tools and molecular dynamics simulations highlights the strengths and limitations of different comparative modeling protocols, all of which are based on the same low identity template (only 22%). Incorrect alignment between the target and template was confirmed to be a major bottleneck in homology modeling, regardless of the modeling software used. Moreover, secondary structure analysis during a 50 ns simulation seems to be useful for indicating alignment errors and structural instabilities. The best model was achieved through the combined use of Phyre 2 and Modeller, suggesting the use of this protocol for the modeling of other proteins that still lack high identity templates.     

How cooperation arises from rational players？

In classical control systems, the plant to be controlled does not have intention to gain its payoff or benefit, which is obviously not the case in various aspects of social and economic systems（or subsystems）. In the latter case, competition and cooperation between players who will optimize their own payoffs turn out to be an important feature, and a fundamental problem is how to achieve cooperation from these rational players. In this paper, we present a neat way to lead to cooperation in dynamical Prisoner＇s Dilemma game. In our scenario, the two players are heterogenous with hierarchical roles as the ＇leader＇ and the ＇follower＇ respectively. It is shown that the system will co-evolve into and stay at the cooperation state if and only if the leader is restricted not to take the dominating strategies. For the special case of 1-step-memory, the optimal strategies for the leader and follower are ＇Tit for Tat＇ and ＇ALL C＇ respectively. In this framework, both the heterogeneity of the players＇ roles and the multiplicity of time-scales are crucial for cooperation, which are quite natural settings from the view point of control theory. Besides, the boundary for cooperation also turns out to depend on the relative payoffs of the players.     

Modeling Computer Forensics Process from Workflow Perspective

Similar with software process, computer forensics process is also a complex process. There have been a lot of modeling technologies for planning, analyzing and documentation of computer forensics activities. Different from software process, the step order of forensics process is very important. Skipping any step or interchanging one step may lead to the illegality of the whole forensics process, so a precise process is critical. In this paper, Petri net is used to model the computer forensics process.     

Craving for internet games? Withdrawal symptoms from an 84-h abstinence from Massively Multiplayer Online gaming

This qualitative study examined the psychological consequences of an 84-h Internet gaming abstinence period for young adults with and without Internet gaming disorder. Using a repeated-measures online survey methodology, participants were asked to abstain and then describe their craving for Internet games, including any coping strategies used to manage craving, and to reflect on the positive and negative aspects of gaming abstinence. A total of 155 written responses were gathered from 24 participants (M_age = 24.6 years, SD = 5.8), including 9 who met the criteria for Internet gaming disorder, recruited from online gaming communities. Participants completed a series of seven online surveys containing open-ended questions before, during, and after abstaining from Massively Multiplayer Online games. The results revealed several key themes, including: (1) internal and external cues that elicit craving for Internet games; (2) beliefs and assumptions about Internet gaming experiences; (3) negative affect related to abstinence; (4) coping strategies for managing craving; (5) beneficial outcomes in behavioral and cognitive domains, including adjustments to gaming-specific activities; and (6) negative outcomes such as unwanted emotional and cognitive states, and social isolation. Notably, participants' reactions to gaming abstinence could be broadly characterized as boredom and a drive for mental stimulation, which seemed somewhat inconsistent with the DSM-5 criterion of withdrawal. These data provide new insights to guide clinical conceptualization and interventions for problematic patterns of Internet gaming behavior.     

Mobile recommendations based on interest prediction from consumer's installed apps–insights from a large-scale field study

Recommender systems are essential in mobile commerce to benefit both companies and individuals by offering highly personalized products and services. One key pre-requirement of applying such systems is to gain decent knowledge about each individual consumer through user profiling. However, most existing profiling approaches on mobile suffer problems such as non-real-time, intrusive, cold-start, and non-scalable, which prevents them from being adopted in reality. To tackle the problems, this work developed real-time machine-learning models to predict user profiles of smartphone users from openly accessible data, i.e. app installation logs. Results from a study with 904 participants showed that the models are able to predict interests on average 48.81% better than a random guess in terms of precision and 13.80% better in terms of recall. Since the effectiveness of such predictive models is unknown in practice, the predictive models were evaluated in a large-scale field experiment with 73,244 participants. Results showed that by leveraging our models, personalized mobile recommendations can be enabled and the corresponding click-through-rate can be improved by up to 228.30%. Supplementary information, study data, and software can be found at https://www.autoidlabs.ch/mobile-analytics.