Improving quality and quantity of contributions: Two models for promoting knowledge exchange with shared databases

Shared databases are used for knowledge exchange in groups. Whether a person is willing to contribute knowledge to a shared database presents a social dilemma: Each group member saves time and energy by not contributing any information to the database and by using the database only to retrieve information which was contributed by others. But if all people use this strategy, then the database will be empty and, hence, useless for every group member. Based on theoretical approaches, two models for fostering the information-sharing behavior of database users are presented. One for enhancing the quality of database contents, and one for enhancing the quantity of those contents. The models take into account the following factors: the kinds of rewards the participants obtain for contributing information, the individual costs associated with this contribution, the prospective metaknowledge about the importance of one’s own information to the others, and the retrospective metaknowledge about how much others contributed to and retrieved from the database. These factors enhance the quantity of database contents as well as their quality.     

Mothers' attachment status as determined by the Adult Attachment Interview predicts their 6-year-olds' reunion responses: A study conducted in Japan.

Following a 1986 study reporting a predominance of ambivalent attachment among insecure Sapporo infants, the generalizability of attachment theory and methodologies to Japanese samples has been questioned. In this 2nd study of Sapporo mother-child dyads (N=43), the authors examined attachment distributions for both (a) child, based on M. Main and J. Cassidy's (1988) 6th-year reunion, and (b) adult, via the Adult Attachment Interview (AAI). In contrast to the previous Sapporo study, children's 3-way or "organized" distribution did not differ from the global distribution. However, when the disorganized-controlling (D) and cannot classify (CC) categories were applied to the analyses, a high proportion of D/CC children was found. Comparable analyses for Japanese mothers, including the unresolved/disorganized (U) and CC categories, were found to deviate slightly from the global norm. However, turning from global distributions to mothers' AAI classification as related to their child's reunion classification, all matches were surprisingly close to those established worldwide. When, as is customary, mothers' U and CC classifications were combined (U/CC) and compared with the child's D and CC classifications (also customarily combined as D/CC), mothers' U/CC status strongly predicted child D/CC status (r=.60, d=1.50). Additionally, mothers' AAI subclassifications predicted child subclassifications. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

How high growth economies impact global information technology departments

By the very nature of information technology (IT), change and dynamism have always been significant drivers on its path to further development—and it has traditionally been the Western countries leading these. Now the picture is changing. The new high growth economies of the world (also known as BRIC countries) are increasingly pressing forward as active IT development drivers. Internal IT organizations of international companies are experiencing these global shifts firsthand and are facing changes in their traditional roles. This exploratory research is aimed at clarifying the context of the impact of high growth economies on such IT departments of Western-rooted enterprises. Forty-six interviews were conducted with IT managers, HR managers and expatriates emphasizing the importance of intercultural interaction, maturing IT economies, change in IT landscape and entrepreneurship.     

Business process compliance checking – applying and evaluating a generic pattern matching approach for conceptual models in the financial sector

Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.     

MOBSY: Integration of vision and dialogue in service robots

Abstract. This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics. Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level. We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute.     

Detecting zero-day attacks using context-aware anomaly detection at the application-layer

Anomaly detection allows for the identification of unknown and novel attacks in network traffic. However, current approaches for anomaly detection of network packet payloads are limited to the analysis of plain byte sequences. Experiments have shown that application-layer attacks become difficult to detect in the presence of attack obfuscation using payload customization. The ability to incorporate syntactic context into anomaly detection provides valuable information and increases detection accuracy. In this contribution, we address the issue of incorporating protocol context into payload-based anomaly detection. We present a new data representation, called \({c}_n\)-grams, that allows to integrate syntactic and sequential features of payloads in an unified feature space and provides the basis for context-aware detection of network intrusions. We conduct experiments on both text-based and binary application-layer protocols which demonstrate superior accuracy on the detection of various types of attacks over regular anomaly detection methods. Furthermore, we show how \({c}_n\)-grams can be used to interpret detected anomalies and thus, provide explainable decisions in practice.     

Crystal: Integrating Structured Queries into a Tactic Language

We present the language CRStL (Control Rule Strategy Language, pronounce “crystal”) to formulate mathematical reasoning techniques as proof strategies in the context of the proof assistant Ωmega. The language is arranged in two levels, a query language to access mathematical knowledge maintained in development graphs, and a strategy language to annotate the results of these queries with further control information. The two-leveled structure of the language allows the specification of proof techniques in a declarative way. We present the syntax and semantics of CRStL and illustrate its use by examples.