In this paper we propose an analytical technique for the steady-state dynamic temperature analysis (SSDTA) of multiprocessor systems with periodic applications. The approach is accurate and, moreover, fast, such that it can be included inside an optimization loop for embedded system design. Using the proposed solution, a temperature-aware reliability optimization, based on the thermal cycling failure mechanism, is presented. The experimental results confirm the quality and speed of our SSDTA technique, compared to the state of the art. They also show that the lifetime of an embedded system can significantly be improved, without sacrificing its energy efficiency, by taking into consideration, during the design stage, the steady-state dynamic temperature profile of the system.

In this study, the differences in behavior between two groups of online gamblers were investigated. The first group comprised individuals who played casino games, and the second group comprised those who bet on sports events. The focal point of the study was on problem gambling, and the objective was to identify and quantify both common and distinct traits that are characteristic to casino and sports problem gamblers. To this end, a set of gamblers from the gaming operator LeoVegas was studied. Each gambler was ascribed two binary variables: one separating casino players from sports bettors, and one indicating whether there was an exclusion related to problem gambling. For each of the four combinations of the two variables, 2500 gamblers were randomly selected for a thorough comparison, resulting in a total of 10,000 participants. The comparison was performed by constructing two predictive models, estimating risk scores using these models, and scrutinizing the risk scores by means of a technique originating from collaborative game theory. The number of cash wagers per active day contributed the most to problem-gambling-related exclusion in the case of sports betting, whereas the volume of money spent contributed the most to this exclusion in the case of casino players. The contribution of the volume of losses per active day was noticeable in the case of both casino players and sports bettors. For casino players, gambling via desktop computers contributed positively to problem-gambling-related exclusion. For sports bettors, it was more concerning when the individual used mobile devices. The number of approved deposits per active day contributed to problem-gambling-related exclusion to a larger extent for sports bettors than casino players. The main conclusion is that the studied explanatory variables contribute differently to problem-gambling-related exclusion among casino players and sports bettors.

Electronic system design based on deterministic techniques for power-temperature analysis is, in the context of current and future technologies, both unreliable and inefficient since the presence of uncertainty, in particular, due to process variation, is disregarded. In this paper, we propose a flexible probabilistic framework targeted at the quantification of the transient power and temperature variations of an electronic system. The framework is capable of modeling diverse probability laws of the underlying uncertain parameters and arbitrary dependencies of the system on such parameters. For the considered system, under a given workload, our technique delivers analytical representations of the corresponding stochastic power and temperature profiles. These representations allow for a computationally efficient estimation of the probability distributions and accompanying quantities of the power and temperature characteristics of the system. The approximation accuracy and computational time of our approach are assessed by a range of comparisons with Monte Carlo simulations, which confirm the efficiency of the proposed technique.Index Terms-Power analysis, process variation, system-level design, temperature analysis, uncertainty quantification.

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