Contributions in Merlin

Biometrics is a type of authentication, which recently gained immense importance. It is used in many applications, such as in airports, electronic passport, access control to buildings, etc. The costs involved are very low, when compared to other types of Identification, such as lost key, smartcards and other similar products. This makes Biometrics an ideal type of authentication for long term purposes. It is observed that, there is no standard software to manage different biometric devices. However, this could be accomplished by BioXes-Management software, which could manage different biometric devices centrally. So far this software has managed several fingerprint, iris scanner and a vein scanner. It is clear that this software has the capacity to manage several devices and already has a interface readily available to include more devices. The aim of this bachelor thesis is to program a JBioDC device driver for the 3D Fastpass™ Face Reader. This device is biometric facial recognition, and is a part of the range of devices that can be managed by the BioXes software. The SDK of this Face Reader runs only on Windows computers and unfortunately limits the platform independence of BioXes. To enable the communication between the driver and the SDK of the face reader a Java/-COM bridge had to be used, which operates to the COM interface of the SDK. In that case, Java2COM was chosen as Java/COM bridge.

Deriving products from a software product line is difficult, particularly when there are many constraints in the variability of the product line. Understanding the impact of variability binding decisions (i.e. of selecting or dismissing features) is a particular challenge: (i) the decisions taken must not violate any variability constraint, and (ii) the effects and consequences of every variability decision need to be understood well. This problem can be reduced significantly with good support both for variability specification and decision making. We have developed an extension of the \textsc{Adora} language and tool which is capable of modeling and visualizing both the functionality and the variability of a product line in a single model and provides automated reasoning on the variability space. In this paper we describe how our approach supports stepwise, incremental derivation of a product requirements specification from a product line specification. We visualize what has been derived so far, automatically re-evaluate the variability constraints and propagate the results as restrictions on the remaining product derivation options. We demonstrate our approach by showing a sequence of product derivation steps in an example from the industrial automation domain. We claim that our approach both improves the efficiency and quality of the derivation process.

null

Both biosociological and psychological models, as well as animal research, suggest that testosterone has a key role in social interactions. Evidence from animal studies in rodents shows that testosterone causes aggressive behaviour towards conspecifics. Folk wisdom generalizes and adapts these findings to humans, suggesting that testosterone induces antisocial, egoistic, or even aggressive human behaviours. However, many researchers have questioned this folk hypothesis, arguing that testosterone is primarily involved in status-related behaviours in challenging social interactions, but causal evidence that discriminates between these views is sparse. Here we show that the sublingual administration of a single dose of testosterone in women causes a substantial increase in fair bargaining behaviour, thereby reducing bargaining conflicts and increasing the efficiency of social interactions. However, subjects who believed that they received testosterone-regardless of whether they actually received it or not-behaved much more unfairly than those who believed that they were treated with placebo. Thus, the folk hypothesis seems to generate a strong negative association between subjects' beliefs and the fairness of their offers, even though testosterone administration actually causes a substantial increase in the frequency of fair bargaining offers in our experiment.

null

null

In distributed work systems, individual users perform work for other users. A significant challenge in these systems is to provide proper incentives for users to contribute as much work as they consume, even when monitoring is not possible. We formalize the problem of designing incentive-compatible accounting mechanisms that measure the net contributions of users, despite relying on voluntary reports. We introduce the Drop-Edge Mechanism that removes any incentive for a user to manipulate via misreports about work contributed or consumed. We prove that Drop-Edge provides a good approximation to a user’s net contribution, and is accurate in the limit as the number of users grows. We demonstrate very good welfare properties in simulation compared to an existing, manipulable mechanism. In closing, we discuss our ongoing work, including a real-world implementation and evaluation of the Drop- Edge Mechanism in a BitTorrent client.

In this paper, we empirically evaluate competing approaches for combining inflation density forecasts in terms of Kullback–Leibler divergence. In particular, we apply a similar suite of models to four different datasets and aim at identifying combination methods that perform well throughout different series and variations of the model suite. We pool individual densities using linear and logarithmic combination methods. The suite consists of linear forecasting models with moving estimation windows to account for structural change. We find that combining densities is a much better strategy than selecting a particular model ex ante. While combinations do not always perform better than the best individual model, combinations always yield accurate forecasts and, as we show analytically, provide insurance against selecting inappropriate models. Logarithmic combinations can be advantageous, in particular if symmetric densities are preferred.