Ethical decision-making is a unique aspect of human behavior. When confronted with situations that require careful deliberation over multitude of options that have ethical implications, human behavior tends to resolve...
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ISBN:
(纸本)9781510847651
Ethical decision-making is a unique aspect of human behavior. When confronted with situations that require careful deliberation over multitude of options that have ethical implications, human behavior tends to resolve dilemmas by resorting to a range of heuristics and principles that view the situation from different perspectives. While constraint and utility-driven decision-making strategies are relevant, the incompatibility among these perspectives can invalidate the underlying premises of models of probabilistic utility-based decisions that rely on classic Kolmogorov axioms. In this paper, it is posited that quantum cognition models can provide an alternative and credible representation of human behavior modeling in simulations that involve ethical decision-making.
In a green environment, air quality is among the prominent aspects to be considered to prevent pollution and in turn maintain safe air. Sick Building Syndrome (SBS) and Building Related Illness (BRI) are the problems ...
In a green environment, air quality is among the prominent aspects to be considered to prevent pollution and in turn maintain safe air. Sick Building Syndrome (SBS) and Building Related Illness (BRI) are the problems that must be encountered by building occupants. Existing devices are quite expensive, and more attention is needed on monitoring air quality. Therefore, this paper discusses a software-hardware architecture proposal to overcome the existing IAQ data retrieval performance problem. The objective of this work is to analyse the most recent IAQ sensing device developed by the researcher, to evaluate the performance attribute, and to implement the software-hardware architecture based on the Performance-Driven software Architecture Refactoring (PDSAR) method. In order to assess the overall performance of the architecture proposed, the prototype of the Indoor Air Quality (IAQ) sensing device was developed. The testing was performed during a period of six months. The results demonstrate that the average performance for 540 readings is 76.67%. This shows that the architecture can be accepted as a generic IAQ sensing device development structure. The device act as an alternative, cheaper and safer device which can be employed by all building owners in the future.
The main point of this paper is to provide an affirmative answer through exploiting reinforcement learning (RL) in artificial intelligence (AI) for eliminating herding without any external control in complex resource ...
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The main point of this paper is to provide an affirmative answer through exploiting reinforcement learning (RL) in artificial intelligence (AI) for eliminating herding without any external control in complex resource allocation systems. In particular, we demonstrate that when agents are empowered with RL (e.g., the popular Q-learning algorithm in AI) in that they get familiar with the unknown game environment gradually and attempt to deliver the optimal actions to maximize the payoff, herding can effectively be eliminated. Furthermore, computations reveal the striking phenomenon that, regardless of the initial state, the system evolves persistently and relentlessly toward the optimal state in which all resources are used efficiently. However, the evolution process is not without interruptions: there are large fluctuations that occur but only intermittently in time. The statistical distribution of the time between two successive fluctuating events is found to depend on the parity of the evolution, i.e., whether the number of time steps in between is odd or even. We develop a physical analysis and derive mean-field equations to gain an understanding of these phenomena. Since AI is becoming increasingly widespread, we expect our RL empowered minority game system to have broad applications.
—The visions and ideas of Industry 4.0 require a profound interconnection of machines, plants, and IT systems in industrial production environments. This significantly increases the importance of software, which is c...
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Adolescents with obesity face numerous health risks and encounter barriers that lead to physical inactivity. We developed a virtual reality sports system, named REVERIE (Real-World Exercise and VR-Based Exercise Resea...
Adolescents with obesity face numerous health risks and encounter barriers that lead to physical inactivity. We developed a virtual reality sports system, named REVERIE (Real-World Exercise and VR-Based Exercise Research in Education), which used deep reinforcement learning to train transformer-based virtual coaching agents, offering immersive and effective sports guidance, with biomechanical performance comparable to real-world physical sports. We integrated REVERIE into a randomized controlled trial involving an 8-week intervention in adolescents with excess body weight (n = 227). Participants were randomized (1:1:1:1:1) to physical table tennis, physical soccer, REVERIE table tennis, REVERIE soccer or control. REVERIE sports intervention was effective in reducing primary outcome fat mass (mean -4.28 kg (95% confidence interval (CI) -6.35 to -2.22), relative to control), with no significant difference compared with physical sports (mean -5.06 kg (95% CI -7.13 to -2.98), relative to control). For secondary outcomes, decreases in liver enzymes and low-density lipoprotein cholesterol levels were found in physical and REVERIE sports groups compared to control. Physical and REVERIE sports showed improvements in physical fitness, psychological well-being and sports willingness after an 8-week intervention, which remained at the 6-month follow-up in the REVERIE sports group. REVERIE sports demonstrated superior cognitive enhancements compared to physical sports in exploratory analyses, as evidenced by olfactory tests (total score: mean 2.84 (95% CI 1.15 to 4.53)) and working memory paradigm (2-back accuracy: mean 10.88% (95% CI 1.19% to 20.56%)). Functional magnetic resonance imaging exhibited that REVERIE sports enhanced neural efficiency and neuroplasticity. Multi-omics analyses revealed distinct changes induced by REVERIE sports that were closely associated with cognitive improvement. Minimal injury rates were 7.69% for REVERIE and 13.48% for physical sports, with no
Mobile offloading is a platform that facilitates the distribution of computationally intensive tasks from mobile devices to the cloud or other devices in order to conserve energy and improve performance. The concept i...
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Mobile offloading is a platform that facilitates the distribution of computationally intensive tasks from mobile devices to the cloud or other devices in order to conserve energy and improve performance. The concept is practically based on the idea of exchanging relatively low communication energy for high computation power utilization. Efforts have been channeled towards energy conservation by clusters using Dynamic Power Management (DPM). This paper is a review for green energy sources for reducing energy and using energy consumption to manage sources by stating the latest studies of energy consumption and energy consumptions.
Each nationality has their special culinary practice, which was built by many generations that formed the cultural and historical print of the regional cuisine. Furthermore, nearby regional cuisines tend to learn from...
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ISBN:
(纸本)9781538641538
Each nationality has their special culinary practice, which was built by many generations that formed the cultural and historical print of the regional cuisine. Furthermore, nearby regional cuisines tend to learn from each other either due to communication or migration. The geographical closure for Syria, Lebanon, Palestine and Jordan made their culinary practice and dishes very similar. In this paper, we study the recipes and culinary practice of these four countries and then test the hypotheses of the food pairings that represent the compatibility of every pair of ingredients by finding their shared flavor compounds. Our analysis is considered at cuisines level, recipes, ingredients, and ingredients pair's level. Our study brings up the special features in each cuisine, and explores the similarities and differences between these cuisines by studying their deep culinary details. Comparing the food pairing hypothesis with real life paired ingredients in these cuisines shows the cuisines real fingerprints and whether, or not, they are different from theories. The experimental results showed that the food pairing hypothesis has been confirmed for the cuisines of Jordan, Lebanon, Syria, and Palestine, which suggests that people in this area combine ingredients that have matching flavor compounds.
In this paper, we explore the benefits of teaching heavyweight process life cycle models to young softwareengineering students to better prepare them in the use of agile methods. The benefits of agile methods compare...
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ISBN:
(纸本)9781538611753;9781538611746
In this paper, we explore the benefits of teaching heavyweight process life cycle models to young softwareengineering students to better prepare them in the use of agile methods. The benefits of agile methods compared to process-heavy models include the ability to respond faster to the changing needs of customers and the short feedback loop between customers and developers. Since agile methods depend significantly on the competence of the individual, teaching traditional approaches (e.g. waterfall) can be advantageous to the understanding of students about what the major activities associated with software development are, by providing a well-defined structure that naturally aligns with the novice student. Towards this goal, we conducted a survey with different types of software engineers, ranging from novice undergraduates to softwareengineering professionals. The survey provides data on the exposure of traditional and agile process, the level of experience in using traditional and agile process models, and the perceived most optimal learning sequence. Based on the analysis of the collected data, we argue that teaching traditional softwareengineering process-oriented approaches prior to introducing agile methods, is highly beneficial to students' understanding and optimal use of agile techniques.
With the rapid development of the information technologies in the financial field, extracting meaningful information from a massive amount of data is hugely significant for efficient business decision making. The reco...
With the rapid development of the information technologies in the financial field, extracting meaningful information from a massive amount of data is hugely significant for efficient business decision making. The recommendation system is an intelligent system that applies historical knowledge of users to infer their preferences and make a personalized recommendation. However, it suffers from the problem of time effect of user's behaviour, which means a user's interests may change over time. To overcome this problem, we propose a time effect based collaborative filtering approach to adaptively statistics the change of user preferences. Firstly, Item-based collaborative filtering is used to calculate rating similarity between items. Since an Item-based collaborative filtering algorithm doesn't consider the time effect; next, the time decay function is proposed to statistics the change of user interests. Experimental results show that the proposed scheme retained higher accuracy compare to traditional collaborative filtering method.
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