Agent-Oriented Software Engineering Methodologies: Analysis and Future Directions

The Internet of Things (IoT) facilitates in building cyber-physical systems, which are significant for Industry 4.0. Agent-based computing represents effective modeling, programming, and simulation paradigm to develop IoT systems. Agent concepts, techniques, methods, and tools are being used in evolving IoT systems. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever-growing interest in their various implementations. Yet a comprehensive and full-fledged agent approach for developing related projects is still lacking despite the presence of agent-oriented software engineering (AOSE) methodologies. One of the moves towards compensating for this issue is to compile various available methodologies, ones that are comparable to the evolution of the unified modeling language (UML) in the domain of object-oriented analysis and design. These have become de facto standards in software development. In line with this objective, the present research attempts to comprehend the relationship among seven main AOSE methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and limitations of each competing process, structural analysis, and a case study evaluation method. This effort is made to address the significant characteristics of AOSE approaches. The main objective of this study is to conduct a comprehensive analysis of selected AOSE methodologies and provide a proposal of a draft unified approach that drives strengths (best) of these methodologies towards advancement in this area.

Magnetic Resonance Simulation in Education: Quantitative Evaluation of an Actual Classroom Experience

Magnetic resonance is an imaging modality that implies a high complexity for radiographers. Despite some simulators having been developed for training purposes, we are not aware of any attempt to quantitatively measure their educational performance. The present study gives an answer to the question: Does an MRI simulator built on specific functional and non-functional requirements help radiographers learn MRI theoretical and practical concepts better than traditional educational method based on lectures? Our study was carried out in a single day by a total of 60 students of a main hospital in Madrid, Spain. The experiment followed a randomized pre-test post-test design with a control group that used a traditional educational method, and an experimental group that used our simulator. Knowledge level was assessed by means of an instrument with evidence of validity in its format and content, while its reliability was analyzed after the experiment. Statistical differences between both groups were measured. Significant statistical differences were found in favor of the participants who used the simulator for both the post-test score and the gain (difference between post-test and pre-test scores). The effect size turned out to be significant as well. In this work we evaluated a magnetic resonance simulation paradigm as a tool to help in the training of radiographers. The study shows that a simulator built on specific design requirements is a valuable complement to traditional education procedures, backed up with significant quantitative results.

Gaze and pupil size variability predict difficulty-level and safe intersection crosses in a driving simulator

Western populations are ageing. With age comes an increased risk of mild cognitive impairment (MCI) and fragility that leads to higher fatal car crashes. This study develops a driving simulation paradigm that seeks to detect unsafe drivers, particularly among older drivers with MCI. The paradigm includes repeated urban intersection crossings at three difficulty levels while eye movements are tracked. The internal validity of this part of the paradigm was tested with young adults ( N = 7). Results indicated that the simulator tests elicited unsafe driving behaviors that varied across difficulty and avoided ceiling and floor effects. Eye movement metrics associated with cognitive load also varied with difficulty and predicted safe crosses. The strongest predictors were gaze transition entropy, gaze variability, and pupil size entropy. These findings indicate internal validity of the tests. Future research should test the external validity of this paradigm with a larger, more diverse sample.

Simulating semantic change: A methodological note

The current work discusses the Human Diachronic Simulation Paradigm (HUDSPA), a method to experimentally probe into historical meaning change set up to (i) scan for configurations similar to attested alterations of meaning but in (typically, but not necessarily, related) languages or varieties which did not actualize the change(s) under investigations; (ii) measure the reactions of native speakers in order to ascertain the verisimilitude as well as the particular semantic and pragmatic properties of the items scrutinized. Specifically, the present paper discusses the relative propensity of a particularizer (German eben) to be interpreted with comparatively high confidence as a scalar additive particle such as even and of a concessive item like English though to be interpreted similar to a modal particle along the lines of German doch.

Demand Side Simulaton: Architecture And Performance

In this thesis, we describe a simulator of residential power consumption, as the first step towards a comprehensive demand-side simulator in the context of smart grid. The si mulator uses a commercialRelational Database Management System (RDBMS) as its simulation engine, and is thus capable of supporting much larger simulated systems than other existing simulators which are mostly based on a multi-agent simulation paradigm. The RDBMS-based design also leads to much improved performance while requiring less resources than comparable MAS-based system. Moreover, simulator records all the events which exceed a certain threshold and in response controls demand and assures the stability of the system, based on the future and past events. furthermore, simulator can help utility companies to obtain initial data that can lead to the development of more complex solutions to monitor and control energy consumption, and thus identify target operating points for the generation and distribution systems, with the ultimate goal of balancing the demand and supply, and of improving energy efficiency at the utility level.

Demand Side Simulaton: Architecture And Performance

In this thesis, we describe a simulator of residential power consumption, as the first step towards a comprehensive demand-side simulator in the context of smart grid. The si mulator uses a commercialRelational Database Management System (RDBMS) as its simulation engine, and is thus capable of supporting much larger simulated systems than other existing simulators which are mostly based on a multi-agent simulation paradigm. The RDBMS-based design also leads to much improved performance while requiring less resources than comparable MAS-based system. Moreover, simulator records all the events which exceed a certain threshold and in response controls demand and assures the stability of the system, based on the future and past events. furthermore, simulator can help utility companies to obtain initial data that can lead to the development of more complex solutions to monitor and control energy consumption, and thus identify target operating points for the generation and distribution systems, with the ultimate goal of balancing the demand and supply, and of improving energy efficiency at the utility level.

Learning functionals via LSTM neural networks for predicting vessel dynamics in extreme sea states

Predicting motions of vessels in extreme sea states represents one of the most challenging problems in naval hydrodynamics. It involves computing complex nonlinear wave-body interactions, hence taxing heavily computational resources. Here, we put forward a new simulation paradigm by training recurrent type neural networks (RNNs) that take as input the stochastic wave elevation at a certain sea state and output the main vessel motions, e.g. pitch, heave and roll. We first compare the performance of standard RNNs versus GRU and LSTM neural networks (NNs) and show that LSTM NNs lead to the best performance. We then examine the testing error of two representative vessels, a catamaran in sea state 1 and a battleship in sea state 8. We demonstrate that good accuracy is achieved for both cases in predicting the vessel motions for unseen wave elevations. We train the NNs with expensive CFD simulations offline , but upon training, the prediction of the vessel dynamics online can be obtained at a fraction of a second. This work is motivated by the universal approximation theorem for functionals (Chen & Chen, 1993. IEEE Trans. Neural Netw. 4 , 910–918 ( doi:10.1109/72.286886 )), and it is the first implementation of such theory to realistic engineering problems.

Distributed Simulation with Multi-Agents for IoT in a Retail Pharmacy Facility

Nowadays, internet of things (IoT) technology is considered as one of the key future technologies. The adoption of such technology is receiving quick attention from many industries as competitive pressures inspire them to move forward and invest. As technologies continue to advance, such as IoT, there is a vital need for an approach to identify its viability. This research proposes the adoption of IoT technology and the use of a simulation paradigm to capture the complexity of a system, offer reliable and continuous perceptions into its present and likely future state, and evaluate the economic feasibility of such adoption. A case study of one of the largest pharmacy retail chain is presented. IoT devices are suggested to be used to remotely monitor the failures of a geographically distributed system of refrigeration units. Multi-agents distributed system is proposed to simulate the operational behavior of the refrigerators and calculate the return of investment (ROI) of the proposed IoT implementation.