Search results for: adjusted network

Authors: Tarek Kandil, Ameen Ali

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Distributed generation (DG) has recently gained a lot of momentum in power industry due to market deregulation and environmental concerns. One of the most technical challenges facing DGs is islanding of distributed generators. The current industry practice is to disconnect all distributed generators immediately after the occurrence of islands within 200 to 350 ms after loss of main supply. To achieve such goal, each DG must be equipped with an islanding detection device. Frequency relays are one of the most commonly used loss of mains detection method. However, distribution utilities may be faced with concerns related to false operation of these frequency relays due to improper settings. The commercially available frequency relays are considering standard tight setting. This paper investigates some factors related to relays internal algorithm that contribute to their different operating responses. Further, the relay operation in the presence of multiple distributed at the same network is analyzed. Finally, the relay setting can be accurately determined based on these investigation and analysis.

Keywords: frequency relay, distributed generation, islanding detection, relay setting

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Authors: Moustafa Osman Mohammed

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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: autopoiesis, nanoparticles, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system

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Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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Authors: Medani Khaled Ben Oualid

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Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

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Authors: Claudiu Mazilu, Ion Robu, Radu Deju

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At the end of 2011 worldwide there were 124 power reactors shut down, from which: 16 fully decommissioned, 50 power reactors in a decommissioning process, 49 reactors in “safe enclosure mode”, 3 reactors “entombed”, for other 6 reactors it was not yet have specified the decommissioning strategy. The concrete radioactive waste that will be generated from dismantled structures of VVR-S nuclear research reactor from Magurele (e.g.: biological shield of the reactor core and hot cells) represents an estimated amount of about 70 tons. Until now the solid low activity radioactive waste (LLW) was pre-placed in containers and cementation with mortar made from cement and natural fine aggregates, providing a fill ratio of the container of approximately 50 vol. % for concrete. In this paper is presented an innovative technology in which radioactive concrete is crushed and the mortar made from recycled radioactive sand, cement, water and superplasticizer agent is poured in container with radioactive rubble (that is pre-placed in container) for cimentation. Is achieved a radioactive waste package in which the degree of filling of radioactive waste increases substantially. The tests were carried out on non-radioactive material because the radioactive concrete was not available in a good time. Waste concrete with maximum size of 350 mm were crushed in the first stage with a Liebhher type jaw crusher, adjusted to nominal size of 50 mm. Crushed concrete less than 50 mm was sieved in order to obtain useful sort for preplacement, 10 to 50 mm. The rest of the screening > 50 mm obtained from primary crushing of concrete was crushed in the second stage, with different working principles crushers at size < 2.5 mm, in order to produce recycled fine aggregate (sand) for the filler mortar and which fulfills the technical specifications proposed: –jaw crusher, Retsch type, model BB 100; –hammer crusher, Buffalo Shuttle model WA-12-H; presented a series of characteristics of recycled concrete aggregates by predefined class (the granulosity, the granule shape, the absorption of water, behavior to the Los Angeles test, the content of attached mortar etc.), most in comparison with characteristics of natural aggregates. Various mortar recipes were used in order to identify those that meet the proposed specification (flow-rate: 16-50s, no bleeding, min. 30N/mm2 compressive strength of the mortar after 28 days, the proportion of recycled sand used in mortar: min. 900kg/m3) and allow obtaining of the highest fill ratio for mortar. In order to optimize the mortars following compositional factors were varied: aggregate nature, water/cement (W/C) ratio, sand/cement (S/C) ratio, nature and proportion of additive. To confirm the results obtained on a small scale, it made an attempt to fill the mortar in a container that simulates the final storage drums. Was measured the mortar fill ratio (98.9%) compared with the results of laboratory tests and targets set out in the proposed specification. Although fill ratio obtained on the mock-up is lower by 0.8 vol. % compared to that obtained in the laboratory tests (99.7%), the result meets the specification criteria.

Keywords: characteristics, radioactive recycled concrete aggregate, mortars, fill ratio

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Authors: Mohammad A. Alia

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With the rapid evolution of the internet applications, cloud computing becomes one of today’s hottest research areas due to its ability to reduce costs associated with computing. Cloud is, therefore, increasing flexibility and scalability for computing services in the internet. Cloud computing is Internet based computing due to shared resources and information which are dynamically delivered to consumers. As cloud computing share resources via the open network, hence cloud outsourcing is vulnerable to attack. Therefore, this paper will explore data security of cloud computing by implementing chaotic cryptography. The proposal scenario develops a problem transformation technique that enables customers to secretly transform their information. This work proposes the chaotic cryptographic algorithms have been applied to enhance the security of the cloud computing accessibility. However, the proposed scenario is secure, easy and straightforward process. The chaotic encryption and digital signature systems ensure the security of the proposed scenario. Though, the choice of the key size becomes crucial to prevent a brute force attack.

Keywords: chaos, cloud computing, security, cryptography

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Authors: Juanling Lin

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The construction of urban parks is an important part of eco-city construction, and the intervention of big data provides a more scientific and rational platform for the assessment of urban parks by identifying and correcting the irrationality of urban park planning from the macroscopic level and then promoting the rational planning of urban parks. The study builds an urban park assessment system based on urban road network data and POI data, taking Futian District of Shenzhen as the research object, and utilizes the GIS geographic information system to assess the park system of Futian District in five aspects: park spatial distribution, accessibility, service capacity, demand, and supply-demand relationship. The urban park assessment system can effectively reflect the current situation of urban park construction and provide a useful exploration for realizing the rationality and fairness of urban park planning.

Keywords: urban parks, assessment system, POI, supply and demand

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Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

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Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

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Authors: Nazila Dehbari, Javad Tavakoli, Yakani Kambu, Youhong Tang

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Superabsorbent hydrogels (SAP), as an enviro-sensitive material have been widely used for industrial and biomedical applications due to their unique structure and capabilities. Poor mechanical properties of SAPs - which is extremely related to their large volume change – count as a great weakness in adopting for high-tech applications. Therefore, improving SAPs’ mechanical properties via toughening methods by mixing different types of cross-linked polymer or introducing energy-dissipating mechanisms is highly focused. In this work, in order to change the intrinsic brittle character of commercialized Poly Acrylic Acid (here as SAP) to be semi-ductile, a commercial available highly branched tree-like dendritic polymers with numerous –OH end groups known as hyper-branched polymer (HB) has been added to PAA-SAP system in a single step, cost effective and environment friendly solvent casting method. Samples were characterized by FTIR, SEM and TEM and their physico-chemical characterization including swelling capabilities, hydraulic permeability, surface tension and thermal properties had been performed. Toughness energy, stiffness, elongation at breaking point, viscoelastic properties and samples extensibility were mechanical properties that had been performed and characterized as a function of samples lateral cracks’ length in different HB concentration. Addition of HB to PAA-SAP significantly improved mechanical and surface properties. Increasing equilibrium swelling ratio by about 25% had been experienced by the SAP-HB samples in comparison with SAPs; however, samples swelling kinetics remained without changes as initial rate of water uptake and equilibrium time haven’t been subjected to any changes. Thermal stability analysis showed that HB is participating in hybrid network formation while improving mechanical properties. Samples characterization by TEM showed that, the aggregated HB polymer binders into nano-spheres with diameter in range of 10–200 nm. So well dispersion in the SAP matrix occurred as it was predictable due to the hydrophilic character of the numerous hydroxyl groups at the end of HB which enhance the compatibility of HB with PAA-SAP. As the profused -OH groups in HB could react with -COOH groups in the PAA-SAP during the curing process, the formation of a 2D structure in the SAP-HB could be attributed to the strong interfacial adhesion between HB and the PAA-SAP matrix which hinders the activity of PAA chains (SEM analysis). FTIR spectra introduced new peaks at 1041 and 1121 cm-1 that attributed to the C–O(–OH) stretching hydroxyl and O–C stretching ester groups of HB polymer binder indicating the incorporation of HB polymer into the SAP structure. SAP-HB polymer has significant effects on the final mechanical properties. The brittleness of PAA hydrogels are decreased by introducing HB as the fracture energies of hydrogels increased from 8.67 to 26.67. PAA-HBs’ stretch ability enhanced about 10 folds while reduced as a function of different notches depth.

Keywords: superabsorbent polymer, toughening, viscoelastic properties, hydrogel network

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Authors: A. K. M. Badrul Alam, Yoshiaki Fujii, Nahid Hasan Dipu, Shakil Ahmed Razo

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Shale rockmasses often include silt layers, impacting slope stability in construction and mining. Analyzing their interaction is crucial for long-term stability. A study used an elastoplastic model, incorporating the stress transfer method and Coulomb's criterion, to assess a shale rock mass with silt layers. It computed stress distribution, assessed failure potential, and identified vulnerable regions where nodal forces were calculated for a comprehensive analysis. A shale rock mass ranging from 14.75 to 16.75 meters thick, with silt layers varying from 0.36 to 0.5 meters, was considered in the model. It examined four silt layer conditions: horizontal (SiHL), vertical (SiVL), inclined against slope (SiIincAGS), and along slope (SilincALO). Mechanical parameters like uniaxial compressive strength (UCS), tensile strength (TS), Young’s modulus (E), Poisson’s ratio, and density were adjusted for varied scenarios: UCS (0.5 to 5 MPa), TS (0.1 to 1 MPa), and E (6 to 60 MPa). In elastic analysis of shale rock masses, stress distributions vary based on layer properties. When shale and silt layers have the same elasticity modulus (E), stress concentrates at corners. If the silt layer has a lower E than shale, marginal changes in maximum stress (σmax) occur for SilHL. A decrease in σmax is evident at SilVL. Slight variations in σmax are observed for SilincAGS and SilincALO. In the elastoplastic analysis, the overall decrease of 20%, 40%, 60%, 80%, and 90% was considered. For SilHL:(i) Same E, UCS, and TS for silt layer and shale, UCS/TS ratio 5: strength decrease led to shear (S), tension then shear (T then S) failure; noticeable failure at 60% decrease, significant at 80%, collapse at 90%. (ii) Lower E for silt layer, same strength as shale: No significant differences. (iii) Lower E and UCS, silt layer strength 1/10: No significant differences. For SilVL: (i) Same E, UCS, and TS for silt layer and shale, UCS/TS ratio 5: Similar effects as SilHL. (ii) Lower E for silt layer, same strength as shale: Slip occurred. (iii) Lower E and UCS, silt layer strength 1/10: Bitension failure also observed with larger slip. For SilincAGS: (i) Same E, UCS, and TS for silt layer and shale, UCS/TS ratio 5: Effects similar to SilHL. (ii) Lower E for silt layer, same strength as shale: Slip occurred. (iii) Lower E and UCS, silt layer strength 1/10: Tension failure also observed with larger slip. For SilincALO: (i) Same E, UCS, and TS for silt layer and shale, UCS/TS ratio 5: Similar to SilHL with tension failure. (ii) Lower E for silt layer, same strength as shale: No significant differences; failure diverged. (iii) Lower E and UCS, silt layer strength 1/10: Bitension failure also observed with larger slip; failure diverged. Toppling failure was observed for lower E cases of SilVL and SilincAGS. The presence of silt interlayers in shale greatly impacts slope stability. Designing slopes requires careful consideration of both the silt and shale's mechanical properties. The temporal degradation of strength in these layers is a major concern. Thus, slope design must comprehensively analyze the immediate and long-term mechanical behavior of interlayer silt and shale to effectively mitigate instability.

Keywords: shale rock masses, silt layers, slope stability, elasto-plastic model, temporal degradation

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Authors: Shahin Zanbaghi, Saeed Samet

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The internet has transformed the way we shop. Previously, most of our purchases came in the form of shopping trips to a nearby store. Now, it’s as easy as clicking a mouse. But with great convenience comes great responsibility. We have to be constantly vigilant about our personal information. In this work, our proposed approach is to encrypt the information printed on the physical packages, which include personal information in plain text, using a symmetric encryption algorithm; then, we store that encrypted information into a Blockchain network rather than storing them in companies or corporations centralized databases. We present, implement and assess a blockchain-based system using Ethereum smart contracts. We present detailed algorithms that explain the details of our smart contract. We present the security, cost, and performance analysis of the proposed method. Our work indicates that the proposed solution is economically attainable and provides data integrity, security, transparency, and data traceability.

Keywords: blockchain, Ethereum, smart contract, commit-reveal scheme

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Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

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The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

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Authors: Pitak Keawbunsong, Sathaporn Promwong

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This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

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Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

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NSGA-II is one of the most well-known and most widely used evolutionary algorithms. In addition to its new versions, such as NSGA-III, there are several modified types of this algorithm in the literature. In this paper, a hybrid NSGA-II algorithm has been suggested for solving the multi-objective flexible job shop scheduling problem. For a better search, new neighborhood-based crossover and mutation operators are defined. To create new generations, the neighbors of the selected individuals by the tournament selection are constructed. Also, at the end of each iteration, before sorting, neighbors of a certain number of good solutions are derived, except for solutions protected by elitism. The neighbors are generated using a constraint-based neural network that uses various constructs. The non-dominated sorting and crowding distance operators are same as the classic NSGA-II. A comparison based on some multi-objective benchmarks from the literature shows the efficiency of the algorithm.

Keywords: flexible job shop scheduling problem, multi-objective optimization, NSGA-II algorithm, neighborhood structures

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Jean-Philippe Amat, Timothée Vergne, Aymeric Hans, Bénédicte Ferry, Pascal Hendrikx, Jackie Tapprest, Barbara Dufour, Agnès Leblond

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The surveillance of infectious diseases is necessary to describe their occurrence and help the planning, implementation and evaluation of risk mitigation activities. However, the exact number of detected cases may remain unknown whether surveillance is based on serological tests because identifying seroconversion may be difficult. Moreover, incomplete detection of cases or outbreaks is a recurrent issue in the field of disease surveillance. This study addresses these two issues. Using a viral animal disease as an example (equine viral arteritis), the goals were to establish suitable rules for identifying seroconversion in order to estimate the number of cases and outbreaks detected by a surveillance system in France between 2006 and 2013, and to assess the sensitivity of this system by estimating the total number of outbreaks that occurred during this period (including unreported outbreaks) using a capture-recapture model. Data from horses which exhibited at least one positive result in serology using viral neutralization test between 2006 and 2013 were used for analysis (n=1,645). Data consisted of the annual antibody titers and the location of the subjects (towns). A consensus among multidisciplinary experts (specialists in the disease and its laboratory diagnosis, epidemiologists) was reached to consider seroconversion as a change in antibody titer from negative to at least 32 or as a three-fold or greater increase. The number of seroconversions was counted for each town and modeled using a unilist zero-truncated binomial (ZTB) capture-recapture model with R software. The binomial denominator was the number of horses tested in each infected town. Using the defined rules, 239 cases located in 177 towns (outbreaks) were identified from 2006 to 2013. Subsequently, the sensitivity of the surveillance system was estimated as the ratio of the number of detected outbreaks to the total number of outbreaks that occurred (including unreported outbreaks) estimated using the ZTB model. The total number of outbreaks was estimated at 215 (95% credible interval CrI95%: 195-249) and the surveillance sensitivity at 82% (CrI95%: 71-91). The rules proposed for identifying seroconversion may serve future research. Such rules, adjusted to the local environment, could conceivably be applied in other countries with surveillance programs dedicated to this disease. More generally, defining ad hoc algorithms for interpreting the antibody titer could be useful regarding other human and animal diseases and zoonosis when there is a lack of accurate information in the literature about the serological response in naturally infected subjects. This study shows how capture-recapture methods may help to estimate the sensitivity of an imperfect surveillance system and to valorize surveillance data. The sensitivity of the surveillance system of equine viral arteritis is relatively high and supports its relevance to prevent the disease spreading.

Keywords: Bayesian inference, capture-recapture, epidemiology, equine viral arteritis, infectious disease, seroconversion, surveillance

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Authors: Irfan Zafar

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Over the years the Telecom Industry in the country has shown a lot of progress in terms of infrastructure development coupled with the availability of telecom services. This has however led to the cut throat completion among various operators thus leading to reduced tariffs to the customers. The profit margins have seen a reduction thus leading the operators to think of other avenues by adopting new models while keeping the quality of service intact. The outsourcing of the network and the resources is one such model which has shown promising benefits which includes lower costs, less risk, higher levels of customer support and engagement, predictable expenses, access to the emerging technologies, benefiting from a highly skilled workforce, adaptability, focus on the core business while reducing capital costs. A lot of research has been done on outsourcing in terms of reasons of outsourcing and its benefits. However this study is an attempt to analyze the effects of the outsourcing on an organizations performance (Telecommunication Sector) considering the variables (1) Cost Reduction (2) Organizational Performance (3) Flexibility (4) Employee Performance (5) Access to Specialized Skills & Technology and the (6) Outsourcing Risks.

Keywords: outsourcing, ICT, telecommunication, IT, networking

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Authors: B. Zerouali, M. Kara, B. Hamaidi, H. Mahdjoub, S. Rouabhia

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In this paper, a safety analysis for crude oil tanks to prevent undesirable events that may cause catastrophic accidents. The estimation of the probability of damage to industrial systems is carried out through a series of steps, and in accordance with a specific methodology. In this context, this work involves developing an assessment tool and risk analysis at the level of crude oil tanks system, based primarily on identification of various potential causes of crude oil tanks fire and explosion by the use of Fault Tree Analysis (FTA), then improved risk modelling by Bayesian Networks (BNs). Bayesian approach in the evaluation of failure and quantification of risks is a dynamic analysis approach. For this reason, have been selected as an analytical tool in this study. Research concludes that the Bayesian networks have a distinct and effective method in the safety analysis because of the flexibility of its structure; it is suitable for a wide variety of accident scenarios.

Keywords: bayesian networks, crude oil tank, fault tree, prediction, safety

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Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Rafael Haag, Elton Rossini

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This work aims to validate and make the projections of solar energy for the Brazilian period from 2025 to 2100. As the plants designed by the HadGEM2-AO (Global Hadley Model 2 - Atmosphere) General Circulation Model UK Met Office Hadley Center, belonging to Phase 5 of the Intercomparison of Coupled Models (CMIP5). The simulation results of the model are compared with monthly data from 2006 to 2013, measured by a network of meteorological sections of the National Institute of Meteorology (INMET). The performance of HadGEM2-AO is evaluated by the efficiency coefficient (CEF) and bias. The results are shown in the table of maps and maps. HadGEM2-AO, in the most pessimistic scenario, RCP 8.5 had a very good accuracy, presenting efficiency coefficients between 0.94 and 0.98, the perfect setting being Solar radiation, which indicates a horizontal trend, is a climatic alternative for some regions of the Brazilian scenario, especially in spring.

Keywords: climate change, projections, solar radiation, scenarios climate change

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Authors: Bhargavi G., Arathi R. Shankar

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Transmitter and receiver closer to every other, which creates the twin benefits of better-nice links and more spatial reuse. In a network with nomadic customers, this inevitably includes deploying greater infrastructure, normally in the form of microcells, hot spots, disbursed antennas, or relays. A less pricey alternative is the recent concept of femtocells, additionally known as domestic base stations that are facts get admission to points installed by means of domestic users to get higher indoor voice and records insurance. Femtocells have the potential to offer excessive exceptional community get entry to indoor customers at low cost, even as concurrently reducing the load. gift femtocells that perform in 4G can also be extended for 5G sub-6 GHz band. Designing the femtocell in mmWave band of 5G may have many blessings in terms of bandwidth availability and coverage. Multiband microstrip patch antennas can be considered as a low value and prominent antennas in designing the femtocells because the single antenna helps multiple frequency.

Keywords: 5G, mmWave, antennas, wireless communications, femtocell

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: Chien-Chun Hung, Chun-Fong Wu

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It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.

Keywords: mini UAV, reconnaissance, wireless transmission, ZigBee modulus

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Authors: Rahaf Mandura, Fatmah Abusharkh, Layan Kurdi, Rahaf Shigdar, Khadijah Alattas

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Introduction: Age-related macular degeneration (AMD) in older individuals are serious health issues that severely impact the quality of life of millions globally. In 2020, the fourth leading cause of blindness worldwide was AMD. The global prevalence of AMD is estimated to be around 8.7%. AMD is a progressive disease involving the macular region of the retina, and it has a complex pathophysiology. RPE cell dysfunction plays a crucial step in the pathway leading to irreversible degeneration of photoreceptors with yellowish lipid-rich, protein-containing drusen deposits accumulating between Bruch's membrane and the RPE. Furthermore, lipofuscinogenesis, drusogenesis, inflammation, and neovascularization are four main processes responsible for the formation of the two types of AMD: the wet (exudative, neovascular) and dry (non-exudative, geographic atrophy) types. We retrospectively evaluated the prevalence of AMD among patients visiting the retina clinic at King Abdulaziz University Hospital (Jeddah, Makkah Province, Saudi Arabia) to identify the commonly associated risk factors of AMD. Methods: The records of 3,067 individuals from 2017 to 2021 were reviewed. Of these, 1,935 satisfied the inclusion criteria and were included in this study. We excluded all patient below 18 years, and those who did not undergo fundus imaging or attend their booked appointments, follow-ups, treatments, and referrals were excluded. Results: The prevalence of AMD among the patients was 4%. The age of patients with AMD was significantly greater than those without AMD (72.4 ± 9.8 years vs. 57.2 ± 15.5 years; p < 0.001). Participants with a family history of AMD tended to have the disease more than those without such a history (85.7% vs. 45%; p = 0.043). Ex- and current smokers were more likely to have AMD than non-smokers (34% and 18.6% vs. 7.2%; p < 0.001). Patients with hypertension and those without type 1 diabetes were at a higher risk of developing AMD than those without hypertension (5.5% vs. 2.8%; p = 0.002) and those with type 1 diabetes (4.2% vs. 0.8%; p = 0.040). In contrast, sex, nationality, type 2 diabetes, and abnormal lipid profile were not significantly associated with AMD. Regarding the clinical characteristics of AMD cases, most cases (70.4%) were of the dry type and affected both eyes (77.2%). The disease duration was ≥5 years in 43.1% of the patients. The most frequent chronic diseases associated with AMD were type 2 diabetes (69.1%), hypertension (61.7%), and dyslipidemia (18.5%). Conclusion: In summary, our single tertiary center study showed that AMD is widely prevalent in Jeddah, Saudi Arabia (4%) and linked to a wide range of risk factors. Some of these are modifiable risk factors that can be adjusted to help reduce AMD occurrence. Furthermore, this study has shown the importance of screening and follow-up of family members of patients with AMD to promote early detection and intervention of AMD. We recommend conducting further research on AMD in Saudi Arabia. Concerning the study design, a community-based cross-sectional study would be more helpful for assessing the disease's prevalence. Finally, recruiting a larger sample size is required for more accurate estimation.

Keywords: age related macular degeneration, prevelence, risk factor, dry AMD

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Authors: Shathya Duobiene, Gediminas Račiukaitis

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Wireless Sensor Networks (WSNs) are an emerging technology that opens up a new field of research. The significant advance in WSN leads to an increasing prevalence of various monitoring applications and real-time assistance in labs and factories. Selective surface activation induced by laser (SSAIL) is a promising technology that adapts to the WSN design freedom of shape, dimensions, and material. This article proposes and implements a WSN-based temperature and humidity monitoring system, and its deployed architectures made for the monitoring task are discussed. Experimental results of newly developed sensor nodes implemented in university campus laboratories are shown. Then, the simulation and the implementation results obtained through monitoring scenarios are displayed. At last, a convenient solution to keep the WSN alive and functional as long as possible is proposed. Unlike other existing models, on success, the node is self-powered and can utilise minimal power consumption for sensing and data transmission to the base station.

Keywords: IoT, network formation, sensor nodes, SSAIL technology

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: A. Mohammadpour, Ebrahim Najafi Kajabad, Ghazale Ipakchi

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Presently, computer networks’ security rise in importance and many studies have also been conducted in this field. By the penetration of the internet networks in different fields, many things need to be done to provide a secure industrial and non-industrial network. Fire walls, appropriate Intrusion Detection Systems (IDS), encryption protocols for information sending and receiving, and use of authentication certificated are among things, which should be considered for system security. The aim of the present study is to use the outcome of several algorithms, which cause decline in IDS errors, in the way that improves system security and prevents additional overload to the system. Finally, regarding the obtained result we can also detect the amount and percentage of more sub attacks. By running the proposed system, which is based on the use of multi-algorithmic outcome and comparing that by the proposed single algorithmic methods, we observed a 78.64% result in attack detection that is improved by 3.14% than the proposed algorithms.

Keywords: intrusion detection systems, clustering, k-means, k-medoids, SV clustering, ensemble

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Authors: Gianmarco Taveri, Ivo Dlouhy

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Geopolymers are well-suited materials to abate CO2 emission coming from the Portland cement production, and then replace them, in the near future, in building and other applications. The cost of production of geopolymers may be seen the only weakness, but the use of wastes as raw materials could provide a valid solution to this problem, as demonstrated by the successful incorporation of fly-ash, a by-product of thermal power plants, and waste glasses. Recycled glass in waste-derived geopolymers was lately employed as a further silica source. In this work we present, for the first time, the introduction of recycled borosilicate glass (BSG). BSG is actually a waste glass, since it derives from dismantled pharmaceutical vials and cannot be reused in the manufacturing of the original articles. Owing to the specific chemical composition (BSG is an ‘alumino-boro-silicate’), it was conceived to provide the key components of zeolitic networks, such as amorphous silica and alumina, as well as boria (B2O3), which may replace Al2O3 and contribute to the polycondensation process. The solid–state MAS NMR spectroscopy was used to assess the extent of boron oxide incorporation in the structure of geopolymers, and to define the degree of networking. FTIR spectroscopy was utilized to define the degree of polymerization and to detect boron bond vibration into the structure. Mechanical performance was tested by means of 3 point bending (flexural strength), chevron notch test (fracture toughness), compression test (compressive strength), micro-indentation test (Vicker’s hardness). Spectroscopy (SEM and Confocal spectroscopy) was performed on the specimens conducted to failure. FTIR showed a characteristic absorption band attributed to the stretching modes of tetrahedral boron ions, whose tetrahedral configuration is compatible to the reaction product of geopolymerization. 27Al NMR and 29Si NMR spectra were instrumental in understanding the extent of the reaction. 11B NMR spectroscopies evidenced a change of the trigonal boron (BO3) inside the BSG in favor of a quasi-total tetrahedral boron configuration (BO4). Thanks to these results, it was inferred that boron is part of the geopolymeric structure, replacing the Si in the network, similarly to the aluminum, and therefore improving the quality of the microstructure, in favor of a more cross-linked network. As expected, the material gained as much as 25% in compressive strength (45 MPa) compared to the literature, whereas no improvements were detected in flexural strength (~ 5 MPa) and superficial hardness (~ 78 HV). The material also exhibited a low fracture toughness (0.35 MPa*m1/2), with a tangible brittleness. SEM micrographies corroborated this behavior, showing a ragged surface, along with several cracks, due to the high presence of porosity and impurities, acting as preferential points for crack initiation. The 3D pattern of the surface fracture, following the confocal spectroscopy, evidenced an irregular crack propagation, whose proclivity was mainly, but not always, to follow the porosity. Hence, the crack initiation and propagation are largely unpredictable.

Keywords: borosilicate glass, characterization, fly-ash, geopolymerization

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Authors: Nattachote Rugthaicharoencheep

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This paper presents a feeder reconfiguration problem in distribution systems. The objective is to minimize the system power loss and to improve bus voltage profile. The optimization problem is subjected to system constraints consisting of load-point voltage limits, radial configuration format, no load-point interruption, and feeder capability limits. A method based on genetic algorithm, a search algorithm based on the mechanics of natural selection and natural genetics, is proposed to determine the optimal pattern of configuration. The developed methodology is demonstrated by a 33-bus radial distribution system with distributed generations and feeder capacitors. The study results show that the optimal on/off patterns of the switches can be identified to give the minimum power loss while respecting all the constraints.

Keywords: network reconfiguration, distributed generation capacitor placement, loss reduction, genetic algorithm

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Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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