با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
Agent negotiation in an IoT-Fog based power distribution system for demand reduction
عامل مذاکره در سیستم توزیع برق مبتنی بر IoT-Fog برای کاهش تقاضا-2020
Growing energy demand is calling for an effective energy management. In smart homes all devices are connected to Internet by means of Internet of Things. There is a possible means of studying the consumer usage pattern and accordingly forecast their energy demand. Multi Agents has been used in computer science for a long time and applied for lot of applications for replicating the job of human. So towards monitoring and controlling the cyber physical systems, these multi agent system has been applied in smart transportation, smart cities, Smart Grid and so. This paper proposes a Multi-agent System (MAS) for smart energy management in an IoT based system. Inspired by the competition in human societies for accepting best proposals: this work proposes an Agent Negotiation system for demand reduction. The Agents in IoT system negotiate with the meter agent for accepting a proposal which will reduce the peak hour usage. The negotiation agent also negotiates with the meter agent for using energy when the availability of renewables are surplus. This negotiation is done with hundreds and thousands of homes thus helping Utilities to meet the supply-demand effectively. Consumers get the best pricing based on the accepted policies.
Keywords: Internet of Things | Multi-agent system | Negotiation | Distribution automation | Smart grid
Explosive, continuous and frustrated synchronization transition in spiking Hodgkin–Huxley neural networks: The role of topology and synaptic interaction
انتقال همزمان ، انفجاری ، مداوم و ناامید کننده در شبکه های عصبی هوچکین-هاکسلی اسپایک: نقش توپولوژی و تعامل سیناپسی-2020
Synchronization is an important collective phenomenon in interacting oscillatory agents. Many functional features of the brain are related to synchronization of neurons. The type of synchronization transition that may occur (explosive vs. continuous) has been the focus of intense attention in recent years, mostly in the context of phase oscillator models for which collective behavior is independent of the mean-value of natural frequency. However, synchronization properties of biologically-motivated neural models depend on the firing frequencies. In this study we report a systematic study of gammaband synchronization in spiking Hodgkin–Huxley neurons which interact via electrical or chemical synapses. We use various network models in order to define the connectivity matrix. We find that the underlying mechanisms and types of synchronization transitions in gamma-band differs from beta-band. In gamma-band, network regularity suppresses transition while randomness promotes a continuous transition. Heterogeneity in the underlying topology does not lead to any change in the order of transition, however, correlation between number of synapses and frequency of a neuron will lead to explosive synchronization in heterogeneous networks with electrical synapses. Furthermore, small-world networks modeling a fine balance between clustering and randomness (as in the cortex), lead to explosive synchronization with electrical synapses, but a smooth transition in the case of chemical synapses. We also find that hierarchical modular networks, such as the connectome, lead to frustrated transitions. We explain our results based on various properties of the network, paying particular attention to the competition between clustering and long-range synapses.
Keywords: Synchronization | Hodgkin–Huxley neuron | Phase transition | Electrical and chemical synapses | Complex networks
Density and speed of sound prediction for binary mixtures of water and ammonium-based ionic liquids using feedforward and cascade forward neural networks
تراکم و سرعت پیش بینی صدا برای مخلوط های باینری مایعات یونی آب و آمونیوم با استفاده از شبکه های عصبی cascade forward-2020
Ionic liquids have attracted a lot of attention in the past years because of some of their properties that distinguish them fromthe classic solvents. Thus, the need for models that can represent their properties without new experimental efforts arises, as experiments are frequently expensive and time-consuming. Neural networks are processing systems capable of simulating biological learning and generalizing the learned functional relations to new cases never seen before. They have been used with success in several areas, like optimization, pattern recognition and function approximation. Therefore, they can be an important asset for properties prediction. This work is focused on designing, training and studying feedforward and cascade forward neural networks for density and speed of sound prediction for binary mixture of water and ammonium-based ionic liquids, using the temperature, mass fraction of ionic liquid and the structural groups of the reagents used to synthesize the ionic liquid as input variables. Besides the synaptic paradigm, some network parameters were also evaluated, namely the hidden neuron number and the number of layers. Also, 13 training algorithms were tested and had their performance evaluated. It was verified a superiority of the Levenberg-Marquardt method and the Bayesian regularization in the training. The proposed neural networks, two 12-10-10-1 cascade forward networks trained with Bayesian regularization, achieved an average absolute relative deviation of 0.0107% for density prediction and 0.1% for speed of sound prediction. The error dispersions showed the networks did not develop trends in prediction.
Keywords: Neural networks | Ionic liquids | Density | Speed of sound | Thermophysical properties
Is itmore effective for national regulators to go directly to the city level to enforce environmental laws?
آیا تنظیم مقررات ملی برای اجرای قوانین محیط زیست مستقیماً به سطح شهر مؤثر است؟-2020
We examine the effectiveness of a new approach of using a direct inspection program on all environmental laws on the firm-level environmental investment in China. The direct inspection programis a response to the continued pollution issues despite the increased effort in the actions of regulatory agencies and their agents. Our findings suggest that firms located in direct inspection cities perform better than those located in non-direct inspection cities in terms of environmental investments. The findings are robust to a battery of robustness checks. Using dynamic analysis, we find that the effect of the direct inspection programlasts at least two years. Our further analysis shows that firms in direct inspection cities respond better to environmental enforcement and nonstated owned firms receive more subsidies than firms in non-direct inspection program cities. The major take away from our analysis is that, in emerging economies, it is more effective to go directly to the city level to enhance the actions of regulatory agencies and their agents. Cutting layers of agencies can enhance firm-level environmental investment.
Keywords: Direct inspection | Environmental actions of regulatory agencies | Layer of regulatory agencies | Environmental investment
Evaluating innovation development among Brazilian micro and small businesses in view of management level: Insights from the local innovation agents program
ارزیابی توسعه نوآوری در بین مشاغل خرد و کوچک برزیل با توجه به سطح مدیریت: بینش از برنامه عوامل محلی نوآوری-2020
This research aims to analyze management and innovation patterns among micro and small businesses (MSBs) that participated during 2015–2016 in the Local Innovation Agents (LIA) Program from the Brazilian Micro and Small Business Support Service (SEBRAE). Complemented by factor analyses, two-step cluster analysis was applied on 6674 MSBs’ management dimensions to identify group patterns and statistical tests explored further cluster differences regarding management and innovation dimensions, besides innovation improvement throughout the program. Results were multifaceted. First, complementary factor analyses showed that management dimensions compose one factor with similar loadings, thus in accordance with their predictive importance found in the cluster analysis. Second, two main clusters were identified in terms of management level, which also presented significant differences regarding innovation levels. Third, considering a before-and-after self-comparison, by and large, innovation was significantly improved by both clusters. Fourth, the highest developed cluster presented higher improvement rates in most innovation dimensions, thus benefiting more from the program, except for two marketing-related innovations, which improved similarly by both clusters. Overall, even though the LIA Program was effective to leverage MSBs innovation, higher efficiency rates would be bounded to fewer participating MSBs, and hence policy planners should be aware of this tradeoff.
Keywords: Micro and small enterprises | Innovation | Support | Program | Innovation radar | Brazilian Micro and Small Business Support | Service (SEBRAE)
Microgrid management system based on a multi-agent approach: An office building pilot
سیستم مدیریت ریز شبکه مبتنی بر رویکرد چند عامل: یک خلبان ساختمان اداری-2020
Microgrids bring advantages to end-users and to the smart grid environment. However, adequate management software, enabling bringing to the field new energy management concepts, is not available yet. Small, single-tasked, software is usually proposed and tested while a clear overall system architecture for microgrid management required to take full advantage of the microgrids’ potential. Previous publications usually focus on energy-related problems and do not provide an efficient and viable solution for players’ representation and microgrid operation. This paper proposes a complete architecture for a microgrid management system based on a multi-agent approach – mGIM – allowing the easy implementation of different energy strategies. The mGIM agents can independently manage local resources while able to collaborate and/or compete with other agents. Designed to run in single-board computers, mGIM agents are light-weighted and easily deployed in buildings. To demonstrate these capabilities, the paper details and presents a microgrid deployment using mGIM solution.
Keywords: Microgrid deployment | Microgrid management | Multi-agent systems | Real-time energy management
A trilevel model for best response in energy demand-side management
مدل سه گانه برای بهترین پاسخ در مدیریت تقاضای انرژی-2020
Demand-side management (DSM) is a powerful tool to efficiently manage the consumption of energy. DSM relies on various techniques and means. In this work, we propose a trilevel energy market model for load shifting induced by time-of-use pricing. Four kinds of actors are involved: electricity suppliers (sell energy), local agents (buy, sell and consume), aggregators (buy and sell) and end users (consume). The interactions among these actors lead to a trilevel multi-leader–multi-follower game. Solving such games is known to be hard, thus we assume that the decision variables of all electricity suppliers but one are known and optimize the decisions of the remaining supplier. This leads to a single-leader–multi-follower game, which aims to compute the leader’s best response to the decisions of his competitors. The trilevel model is first formulated as a bilevel problem using an explicit formula for the lowest optimization level. Solution algorithms are developed in the optimistic case and in a variant named “semi-optimistic” approach leading to more robust solutions. Finally, numerical results highlight the efficiency of the methods and the sensitivity of the solutions with respect to the model parameters.
Keywords : OR in energy | Demand-side management | Bilevel programming | Trilevel programming
Implications of Guideline Updates for the Management of Apparent Treatment Resistant Hypertension in the United States (A NCDR Research to Practice [R2P] Project)
پیامدهای به روز رسانی های راهنما برای مدیریت فشارخون مقاوم به درمان والدین در ایالات متحده (یک تحقیق NCDR برای تمرین [پروژه R2P])-2020
The 2018 resistant hypertension scientific statement offers new treatment recommendations. To determine the implications of these changes, we sought to ascertain the prevalence of apparent treatment resistant hypertension (aTRH) and the therapies used to treat it in an US national ambulatory cardiovascular registry before these recent developments. Using the PINNACLE Registry from 2013 to 2014, we identified all patients receiving treatment for hypertension and then determined the proportion with aTRH as those who met the following criteria over ≥2 consecutive visits: (1) 3 blood pressure medication classes including a diuretic and blood pressure >140/90, OR (2) ≥4 blood pressure medications. Among those with aTRH, we examined past use of therapies now recommended in guidelines including: (1) first-line therapy with an angiotensin-converting enzyme inhibitor or angiotensin-II receptor blocker, calcium channel blocker and a thiazide diuretic, (2) use of chlorthalidone, and (3) use of a mineralocorticoid receptor antagonist (MRA) for those requiring a 4th medication. Of 84,624 patients on treatment for hypertension, 11,147 (13.1%) met criteria for prevalent aTRH. Among these patients: (1) Of those on 3 antihypertensive agents (n = 1,255), 315 (25%) were on the first-line regimen now recommended in guidelines, (2) 520 (6.7%) of the 7,930 patients on thiazides were using chlorthalidone, and (3) 3061 (27%) were using a MRA; another 4,523 (40.6%) were eligible for its addition. In conclusion, our findings of low historic use of therapies now recommended in guidelines suggest opportunities to improve care among patients with aTRH. © 2019 Elsevier Inc. All rights reserved. (Am J Cardiol 2020;125:63−67)
Distributed optimization for structured programs and its application to energy management in a building district
توزیع بهینه برای برنامه های ساخت یافته و کاربرد آن در مدیریت انرژی در یک منطقه ساختمانی-2020
This paper deals with structured multi-agent optimization problems that involve coupled local and global decision variables. We propose an iterative distributed algorithm that explicitly accounts for this struc- ture, and requires the agents to communicate only their tentative solutions for the global variables throughout iterations. Our approach extends to structured multi-agent optimization a proximal-based distributed methodology that has recently appeared in the literature. Privacy of local information is pre- served and communication effort is reduced with respect to alternative distributed solutions where local and global optimization variables are grouped together and treated as a single decision vector. Multi- agent optimization problems with the considered structural properties appear in various contexts. In this paper, we apply our approach to energy management in a district where multiple buildings can commu- nicate over a possibly time-varying network and aim at optimizing the use of shared and local resources. We illustrate the efficacy of the resulting distributed energy management algorithm by means of a de- tailed simulation study on a cooling problem.
Keywords: Distributed optimization | Proximal minimization | Energy management | Building control
No luck for moral luck
بدون شانس برای شانس اخلاقی-2019
Moral philosophers and psychologists often assume that people judge morally lucky and morally unlucky agents differently, an assumption that stands at the heart of the Puzzle of Moral Luck. We examine whether the asymmetry is found for reflective intuitions regarding wrongness, blame, permissibility, and punishment judg- ments, whether people’s concrete, case-based judgments align with their explicit, abstract principles regarding moral luck, and what psychological mechanisms might drive the effect. Our experiments produce three findings: First, in within-subjects experiments favorable to reflective deliberation, the vast majority of people judge a lucky and an unlucky agent as equally blameworthy, and their actions as equally wrong and permissible. The philosophical Puzzle of Moral Luck, and the challenge to the very possibility of systematic ethics it is frequently taken to engender, thus simply do not arise. Second, punishment judgments are significantly more outcome- dependent than wrongness, blame, and permissibility judgments. While this constitutes evidence in favor of current Dual Process Theories of moral judgment, the latter need to be qualified: punishment and blame judgments do not seem to be driven by the same process, as is commonly argued in the literature. Third, in between-subjects experiments, outcome has an effect on all four types of moral judgments. This effect is mediated by negligence ascriptions and can ultimately be explained as due to differing probability ascriptions across cases.
Keywords: Moral luck | Moral judgment | Outcome eﬀect | Dual process theory of moral judgment | Hindsight bias