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关键词： Anomaly detection   Logistics   Databases   Transportation   Computer science   Postal services   Classification algorithms   Aggregation   anomaly detection   Choquet integral   classification   transportation system  

摘要： Anomaly detection is one of the most important problems of modern data science due to the threat to the security of information systems as well as their users. This applies in particular to logistic data, which is used to predict costs, times, and organization of travel routes. Data anomalies may endanger the welfare and safety of transport users, goods, handling companies, and consumers. Moreover, they contribute to the overexploitation of the natural environment. Therefore, it is extremely important to find methods that are responsible for their effective detection. The desired approach may be the Choquet integral and its extensions, which in various applications have proven that with their help it is possible to efficiently increase the quality of the classification measured, for example, with the help of the accuracy. Due to the fact that the Choquet integral is resistant to data fluctuations and takes into account the quality (significance) of the information source, it appears to be an effective proposition for the final determination of what data, or more precisely, which records can be considered anomalous. The innovative approach to analyze transport data has not been used before. This article considers four publicly available databases covering different fields of application of transport systems. In a series of comprehensive numerical experiments, the Choquet integral-based approach has proven high efficiency for each of them. Moreover, we made a comparative analysis of the solutions before applying the Choquet integral and the results after its application.

关键词： Saliency detection   Task analysis   Training   Visualization   Visual systems   Object detection   Computer science   Audio-visual fusion   video saliency detection   semantical consistency  

摘要： Video saliency detection (VSD) aims at fast locating the most attractive objects/things/patterns in a given video clip. Existing VSD-related works have mainly relied on the visual system but paid less attention to the audio aspect. In contrast, our audio system is the most vital complementary part of our visual system. Also, audio-visual saliency detection (AVSD), one of the most representative research topics for mimicking human perceptual mechanisms, is currently in its infancy, and none of the existing survey papers have touched on it, especially from the perspective of saliency detection. Thus, the ultimate goal of this paper is to provide an extensive review to bridge the gap between audio-visual fusion and saliency detection. In addition, as another highlight of this review, we have provided a deep insight into key factors that could directly determine AVSD deep models' performances. We claim that the audio-visual consistency degree (AVC) - a long-overlooked issue, can directly influence the effectiveness of using audio to benefit its visual counterpart when performing saliency detection. Moreover, to make the AVC issue more practical and valuable for future followers, we have newly equipped almost all existing publicly available AVSD datasets with additional frame-wise AVC labels. Based on these upgraded datasets, we have conducted extensive quantitative evaluations to ground our claim on the importance of AVC in the AVSD task. In a word, our ideas and new sets serve as a convenient platform with preliminaries and guidelines, all of which can potentially facilitate future works in further promoting state-of-the-art (SOTA) performance.

关键词： Implementation   Computation   Computer science   Levels of abstraction  

摘要： In chapter eleven of "On The Foundation of Computing," Primiero takes on the implementation debate in computer science. He contrasts his theory with two other views-the Semantic and the specification-artifact. In this paper, I argue that there is a way to fine-tune the implementation concept further. Firstly, contrary to Primiero, I claim it is problematic to separate the implementation relationship from the conditions which make it correct. Secondly, by taking a pluralistic approach to implementation, I claim it is a mistake to try and provide a general theory of implementation for the entire production cycle of computational systems.

关键词： Computer science   Industries   Costs   Virtual assistants   Technological innovation   Statistical analysis   Reactive power   Gender gap   computer science   university graduates by gender  

摘要： This study focuses on the numerical gap in CS from different angles, whether it presents a similar behavior in all countries or not, and how it evolves over time. We have analyzed OECD statistics from 1998 to 2016 in twenty-nine countries and present results that show that this is a global problem. The average of women who graduated in CS is lower in 2016 than it was in 1998 and the tendency is to continue to diminish, although the situation is very different from some groups of countries to others. We have made statistical analysis that has allowed to present a country classification. This analysis has shown that there is a wide difference between countries such as Mexico, Italy and Belgium for example. We have also carried out statistical analysis of possible relations between economic and social variables for the countries studied along the almost 19 years' span and have found no statistically significant correlation in global terms, which shows that the problem is complex and that the solutions adopted are only partial.

关键词： Data mining   Time factors   Heuristic algorithms   Computer science   Computational modeling   Software   Prediction algorithms   Bitmap   negative sequential patterns (NSPs)   nonoccurring behavior (NOB) analysis   prefixspan   sequential patterns  

摘要： Nonoccurring behavior (NOB) studies have attracted the growing attention of scholars as a crucial part of behavioral science. As an effective method to discover both NOB and occurring behaviors (OB), negative sequential pattern (NSP) mining is successfully used in analyzing medical treatment and abnormal behavior patterns. At this time, NSP mining is still an active and challenging research domain. Most of the algorithms are inefficient in practice. Briefly, the key weaknesses of NSP mining are: 1) an inefficient positive sequential pattern (PSP) mining process, 2) a strict constraint of negative containment, and 3) the lack of an effective Negative Sequential Candidate (NSC) generation method. To address these weaknesses, we propose a highly efficient algorithm with improved techniques, named sc-NSP, to mine NSP efficiently. We first propose an improved PrefixSpan algorithm in the PSP mining process, which connects to a bitmap storage structure instead of the original structure. Second, sc-NSP loosens the frequency constraint and exploits the NSC generation method of positive and negative sequential patterns mining (PNSP) (a classic NSP mining method). Furthermore, a novel pruning strategy is designed to reduce the computational complexity of sc-NSP. Finally, sc-NSP obtains the support of NSC by using the most efficient bitwise-based calculation operation. Theoretical analyses show that sc-NSP performs particularly well on data sets with a large number of elements and items in sequence. Comparison and extensive experiments along with case studies on health data show that sc-NSP is 10 times more efficient than other state-of-the-art methods, and the number of NSPs obtained is 5 times greater than other methods.

关键词： affectivity   affective punishment   capital punishment   intra-activity   modern disenchantment   new materialism   onto-epistemology   vibrant matter  

摘要： This paper re-reads American Appellate and Supreme Court rulings about the constitutionality of execution by electrocution from the perspective of new materialism. Using the case of Provenzano v. Moore, this paper highlights how the existing jurisprudence develops a notion of cruelty that deliberately avoids the sensual and affective dimensions of punishment. Given the profoundly corporeal nature of punishment and even more so capital punishment, any consideration of the ethics of punitive practice must meaningfully engage with the body, its situatedness, and its material networks, all of which enact punishment as a social phenomenon. Employing Jane Bennett's ethics of affective enchantment, grounded in the ethico-onto-epistemology of new materialist thinkers, this paper critiques the majority opinion in Provenzano by demonstrating how it feeds into modern disenchantment. It then draws on Provenzano's landmark dissent to show how ethical practice stems from deliberately opening oneself up to the wonderment of an entangled world produced through the acknowledgement of nonhuman selves and plastic bodies. This has the potential to generate an understanding of 'humane' punishment that better, and more meaningfully accounts for how human beings relate to and engage with the world around them.

关键词： Technology   Gestalt   Education  

摘要： The use of information technology in the academic environment has grown. Building different didactic techniques to help students learn and practice with Information Technology (IT) resources is common. However, applying these techniques does not necessarily mean that students may acquire knowledge. The differential idea of this work is to create an approach in which students are protagonists and not just absorbers of IT. Based on this perspective, we applied a Gestalt approach to assist students in practicing these technological resources. They produce new hardware and software tools during classes based on their personal needs and worldviews. We analyzed applications of this novel way of computer science teaching in three different schools. It was possible to observe greater motivation from the students to experience new knowledge from technological resources. The common aspect was that solutions were conceived and developed from students' needs. The development followed a Gestalt approach, which combines the idea of form and imagination. Thus, with this approach, reactivity towards IT was reduced. It helped construct technological tools to acquire propaedeutic knowledge.

关键词： Games   Nash equilibrium   Learning automata   Convergence   Markov processes   Computer science   Benchmark testing   Games with incomplete information   learning automata (LA)   LA with artificial barriers  

摘要： Learning automata (LA) with artificially absorbing barriers was a completely new horizon of research in the 1980s (Oommen, 1986). These new machines yielded properties that were previously unknown. More recently, absorbing barriers have been introduced in continuous estimator algorithms so that the proofs could follow a martingale property, as opposed to monotonicity (Zhang et al., 2014), (Zhang et al., 2015). However, the applications of LA with artificial barriers are almost nonexistent. In that regard, this article is pioneering in that it provides effective and accurate solutions to an extremely complex application domain, namely that of solving two-person zero-sum stochastic games that are provided with incomplete information. LA have been previously used (Sastry et al., 1994) to design algorithms capable of converging to the game's Nash equilibrium under limited information. Those algorithms have focused on the case where the saddle point of the game exists in a pure strategy. However, the majority of the LA algorithms used for games are absorbing in the probability simplex space, and thus, they converge to an exclusive choice of a single action. These LA are thus unable to converge to other mixed Nash equilibria when the game possesses no saddle point for a pure strategy. The pioneering contribution of this article is that we propose an LA solution that is able to converge to an optimal mixed Nash equilibrium even though there may be no saddle point when a pure strategy is invoked. The scheme, being of the linear reward-inaction ( $L_{R-I}$ ) paradigm, is in and of itself, absorbing. However, by incorporating artificial barriers, we prevent it from being ``stuck'' or getting absorbed in pure strategies. Unlike the linear reward-epsilon penalty ( $L_{R-epsilon P}$ ) scheme proposed by Lakshmivarahan and Narendra almost four decades ago, our new scheme achieves the same goal with much less parameter tuning and in a more elegant manner. This article includes the

关键词： AI teaching competency   Computer science teachers   Teacher professional development   TPACK   In-service teachers  

摘要： With the rapid development of artificial intelligence (AI), the demand for K-12 computer science (CS) education continues to grow. However, there has long been a lack of trained CS teachers. To promote the AI teaching competency of CS teachers, a professional development (PD) program based on the technological pedagogical content knowledge (TPACK) framework was intentionally designed in this research. A quasi-experimental design with a 25-day (75-h) intervention was conducted among 40 in-service CS teachers to examine its impact on AI teaching competency, including AI knowledge, AI teaching skills, and AI teaching self-efficacy. The quantitative data were collected via a pretest and posttest, and qualitative data were collected via artifact analysis and semistructured interviews. The results indicated that the TPACK-based PD program a) significantly improved CS teachers' AI knowledge, especially in representation and reasoning, interaction, and social impact;b) developed CS teachers' AI teaching skills, including their AI lesson plan ability and AI programming skills;and c) significantly improved CS teachers' AI teaching self-efficacy, both in AI teaching efficacy beliefs and AI teaching outcome expectancy. These findings revealed the effectiveness of the TPACK-based PD program in improving the AI teaching competency of K-12 CS teachers and could help to expand the design of effective PD for CS teachers.

关键词： Building Energy System   HVAC   Heating   Cooling   Reinforcement learning   Machine learning   RL   ML  

摘要： Energy efficient control of energy systems in buildings is a widely recognized challenge due to the use of low temperature heating, renewable electricity sources, and the incorporation of thermal storage. Reinforcement Learning (RL) has been shown to be effective at minimizing the energy usage in buildings with maintained thermal comfort despite the high system complexity. However, RL has certain disadvantages that make it challenging to apply in engineering practices. In this review, we take a computer science approach to identifying three main categories of challenges of using RL for control of Building Energy Systems (BES). The three categories are the following: RL in single buildings, RL in building clusters, and multi-agent aspects. For each topic, we analyse the main challenges, and the state-of-the-art approaches to alleviate them. We also identify several future research directions on subjects such as sample efficiency, transfer learning, and the theoretical properties of RL in building energy systems. In conclusion, our review shows that the work on RL for BES control is still in its initial stages. Although significant progress has been made, more research is needed to realize the goal of RL-based control of BES at scale.