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One of the biggest problems in gaming AI is related to how we can optimize and adapt a deep reinforcement learning (DRL) model, especially when it is running inside complex, dynamic environments like "PacMan". The existing research has concentrated more or less on basic DRL approaches though the utilization of advanced optimization methods. This paper tries to fill these gaps by proposing an innovative methodology that combines DRL with high-level metaheuristic optimization methods. The work presented in this paper specifically refactors DRL models on the "PacMan" domain with Energy Serpent Optimizer (ESO) for hyperparameter search. These novel adaptations give a major performance boost to the AI agent, as these are where its adaptability, response time, and efficiency gains start actually showing in the more complex game space. This work innovatively incorporates the metaheuristic optimization algorithm into another field—DRL—for Atari gaming AI. This integration is essential for the improvement of DRL models in general and allows for more efficient and real-time game play. This work delivers a comprehensive empirical study for these algorithms that not only verifies their capabilities in practice but also sets a state of the art through the prism of AI-driven game development. More than simply improving gaming AI, the developments could eventually apply to more sophisticated gaming environments, ongoing improvement of algorithms during execution, real-time adaptation regarding learning, and likely even robotics/autonomous systems. This study further illustrates the necessity for even-handed and conscientious application of AI in gaming—specifically regarding questions of fairness and addiction. [ABSTRACT FROM AUTHOR]

Despite the increase in the efficiency of energy consumption in information and communication technology, software execution and its constraints are responsible for how energy is consumed in hardware hosts. Consequently, researchers have promoted the development of sustainable software with new development methods and tools to lessen its hardware demands. However, the approaches developed so far lack cohesiveness along the stages of the software development life cycle (SDLC) and exist outside of a holistic method for green software development (GSD). In addition, there is a severe lack of approaches that target the analysis and design stages of the SDLC, leaving software architects and designers unsupported. In this article, we introduce our behavior-based consumption profile (BBCP) external Domain-Specific Language (DSL), aimed at assisting software architects and designers in modeling the behavior of software. The models generated with our external DSL contain multiple sets of properties that characterize features of the software's behavior. In contrast to other modeling languages, our BBCP emphasizes how time and probability are involved in software execution and its evolution over time, helping its users to gather an expectation of software usage and hardware consumption from the initial stages of software development. To illustrate the feasibility and benefits of our proposal, we conclude with an analysis of the model of a software service created using the BBCP, which is simulated using Insight Maker to obtain an estimation of hardware consumption and later translated to energy consumption. [ABSTRACT FROM AUTHOR]

One of the biggest problems in gaming AI is related to how we can optimize and adapt a deep reinforcement learning (DRL) model, especially when it is running inside complex, dynamic environments like “PacMan”. The existing research has concentrated more or less on basic DRL approaches though the utilization of advanced optimization methods. This paper tries to fill these gaps by proposing an innovative methodology that combines DRL with high-level metaheuristic optimization methods. The work presented in this paper specifically refactors DRL models on the “PacMan” domain with Energy Serpent Optimizer (ESO) for hyperparameter search. These novel adaptations give a major performance boost to the AI agent, as these are where its adaptability, response time, and efficiency gains start actually showing in the more complex game space. This work innovatively incorporates the metaheuristic optimization algorithm into another field—DRL—for Atari gaming AI. This integration is essential for the improvement of DRL models in general and allows for more efficient and real-time game play. This work delivers a comprehensive empirical study for these algorithms that not only verifies their capabilities in practice but also sets a state of the art through the prism of AI-driven game development. More than simply improving gaming AI, the developments could eventually apply to more sophisticated gaming environments, ongoing improvement of algorithms during execution, real-time adaptation regarding learning, and likely even robotics/autonomous systems. This study further illustrates the necessity for even-handed and conscientious application of AI in gaming—specifically regarding questions of fairness and addiction.

This paper focuses on the monitoring and prediction of the energy consumption of IT equipment to make informed decisions in terms of energy efficiency. The challenge with current monitoring systems lies in their specialization, scalability and integration complexities. To overcome these challenges, we propose a monitoring and prediction system for energy consumption of IT equipment. The proposed solution combines an adaptable, cost-effiective and energy-Efficient embedded device with open source software and a service-oriented architecture (SOA), which offers flexibility and integration capabilities, facilitating the easy inclusion of several workstation working from different environments. Several traditional Linear Regression (LR) models were evaluated prediction models using a temporal window of hour taking into account several features. As a result of the LR models evaluation, it is established that the Bayesian Ridge model was the best model since it presented the lowest error and the highest coefficient of determination. Finally, two approaches were evaluated to predict energy consumption: a Kernel Density Estimation (KDE)-based mechanism proposed to generate predictor variables in order to predict future energy using the best LR model, and a KDE-based energy model. Numerical results show that the energy prediction using KDE for the energy measurements provides lower time response than the LR based mechanism for the available dataset. [ABSTRACT FROM AUTHOR]

With the increase in voltage level and current capacity of the insulated gate bipolar transistor (IGBT), the avalanche effect has become an important factor limiting the safe operating area (SOA) of the device. The hole injection into the p/n junction on the backside of the IGBT after avalanche is the main feature that distinguishes the avalanche effect from other devices. In this paper, the avalanche breakdown characteristics of IGBT and the nature of current filament are investigated using theoretical analysis and numerical simulation, and the underlying physical mechanism controlling the nature of current filaments is revealed. The results show that the hole injection on the backside of the IGBT leads to an additional negative differential resistance (NDR) branch on the avalanche breakdown curve. The device's common-base current gain, αpnp, is a crucial factor in determining the current filament. As αpnp increases, the avalanche-induced current filament becomes stronger and slower, resulting in weaker avalanche robustness of the device. [ABSTRACT FROM AUTHOR]

Organonitrates (ON) and nitroxy-organosulfates (NOS) are important components of secondary organic aerosols (SOAs). Gas-phase reactions of α-pinene (C10H16), a primary precursor for several ON compounds, are fairly well understood although formation pathways for NOS largely remain unknown. NOS formation may occur via reactions of ON and organic peroxides with sulfates as well as through radical-initiated photochemical processes. Despite the fact that organosulfates (OS) represent a significant portion of the organic aerosol mass, ON and NOS formation from OS is less understood, especially through nighttime heterogeneous and multiphase chemistry pathways. In the current study, surface reactions of adsorbed α-pinene-derived OS with nitrogen oxides on hematite and kaolinite surfaces, common components of mineral dust, have been investigated. α-Pinene reacts with sulfated mineral surfaces, forming a range of OS compounds on the surface. These OS compounds when adsorbed on mineral surfaces can further react with HNO3 and NO2, producing several ON and NOS compounds as well as several oxidation products. Overall, this study reveals the complexity of reactions of prevalent organic compounds leading to the formation of OS, ON, and NOS via heterogeneous and multiphase reaction pathways on mineral surfaces. It is also shown that this chemistry is mineralogy-specific.

Smart factories are focusing on bridging the gap between physical and cyber-physical systems through software applications. This article proposed an efficient and sufficient data acquisition, storing and processing real-time monitoring information, response, and feedback in milling process monitoring. A methodology to enable integration between service-oriented IoT-based monitoring with interpreted information for open architecture CNC system was presented. The proposed system comprises four main layers: the perception layer, communication layer, application layer, and CNC machine. The developed system was validated through two case studies. First, the developed system successfully enabled data flow through the validation, from CNC machine back to CNC machine. Secondly, the reading of temperature, vibration, and electric current monitoring is higher for the worn cutting tool than the new cutting tool. Third, the percentage difference between new and worn cutting tools for temperature monitoring is up to 3.38%, and for vibration monitoring, it is up to 78.93%. Fourth, the electric current reading is proportional to cutting force as the reading of electric current on cutting insert is higher than reading before cutting tool insert with percentage differences more than 8.33% up to 20%. Based on the findings, it was summarized that the developed integrated monitoring system is feasible enough based on the performance and highly sensitive to any changes that occurred during the machining process, specifically on the cutting tool condition. In the future, this integrated monitoring system could be applied to other open CNC machine-based plug and play. [ABSTRACT FROM AUTHOR]

Electricity is becoming the most important resource for environmental development. Hence, Global warming has led to the acceptance of electric vehicles as the most efficient alter- native to internal combustion engines. The growing number of electric vehicles on the road cannot be charged by conventional fossil fuel power grids because they are neither economical nor efficient. Hybrid power systems for charging stations are the main source of charge for electric vehicles. Here hybrid involves two energy sources, namely wind and solar. Therefore, this paper aims to optimize the cost and reliability of the Hybrid Wind-Solar Power Charging Station for Electric Vehicles (HWSCSEV). Solar energy is converted into electric power by solar panels, and wind energy is converted into electric power by wind turbines with optimum reliability and minimum cost. A few recent metaheuristics techniques, such as the Osprey Optimization Algorithm (OOA), Pelican Optimization Algorithm (POA), Skill Optimization Algorithm (SOA), Velocity Pausing Particle Swarm Optimization (VPPSO) are successfully used for the cost and reliability calculation of the proposed model. Furthermore, the obtained results of these techniques are contrasted with each other outcomes for the best reliability and cost of the HWSCSEV. Finally, algorithms are effectively analyzed based on convergence rate, computational time, Friedman ranking test, and statistical results. [ABSTRACT FROM AUTHOR]

This document is a special issue of the journal Nonlinear Studies, featuring interdisciplinary perspectives in applied mathematics. It includes articles on consumer behavior, diffusion of innovation, numerical methods, game theory, and optimization, covering domains such as engineering, management, and physics. The papers have undergone peer review and offer original and high-quality research. The document compiles research contributions on reliability analysis, mathematical modeling, differential equations, and optimization problems, with references for further exploration. The authors express gratitude to the contributors and reviewers for their valuable contributions. [Extracted from the article]

Naphthalene is the most abundant polycyclic aromatic hydrocarbon (PAH) in vehicle emissions and polluted urban areas. Its atmospheric oxidation products oxygenated compounds potentially harmful for health and/or contributing to secondary organic aerosol (SOA) formation. Despite its impact on air quality, its complex structure and lack of data mean that no detailed scheme of naphthalene gaseous oxidation for SOA formation and speciation has yet been established. This study presents the construction of the first near-explicit chemical scheme for naphthalene oxidation by OH including kinetic and mechanistic data. The scheme redundantly represents all the classical steps of atmospheric organic chemistry (i.e. oxidation of stable species, peroxy radical formation and reaction and alkoxy radical evolution) integrating therefore fragmentation or functionalization pathways and the influence of NOx on secondary compound formation. Missing kinetic and mechanistic data were estimated using structure-activity relationships (SARs) or by analogy with existing experimental or theoretical data. The proposed chemical scheme involves 392 species (237 stable species, including 93% of the major molar masses observed in previous experimental studies) and 503 reactions with products. A first simulation reproducing experimental oxidation in oxidation flow reactor under high NOx conditions shows a simulated SOA mass in the same order of magnitude as experimentally observed, with an error of -12%. [ABSTRACT FROM AUTHOR]

In the context of Industry 4.0, this paper explores the vital role of advanced technologies, including Cyber–Physical Systems (CPS), Big Data, Internet of Things (IoT), digital twins, and Artificial Intelligence (AI), in enhancing data valorization and management within industries. These technologies are integral to addressing the challenges of producing highly customized products in mass, necessitating the complete digitization and integration of information technology (IT) and operational technology (OT) for flexible and automated manufacturing processes. The paper emphasizes the importance of interoperability through Service-Oriented Architectures (SOA), Manufacturing-as-a-Service (MaaS), and Resource-as-a-Service (RaaS) to achieve seamless integration across systems, which is critical for the Industry 4.0 vision of a fully interconnected, autonomous industry. Furthermore, it discusses the evolution towards Supply Chain 4.0, highlighting the need for Transportation Management Systems (TMS) enhanced by GPS and real-time data for efficient logistics. A guideline for implementing CPS within Industry 4.0 environments is provided, focusing on a case study of real-time data acquisition from logistics vehicles using CPS devices. The study proposes a CPS architecture and a generic platform for asset tracking to address integration challenges efficiently and facilitate the easy incorporation of new components and applications. Preliminary tests indicate the platform's real-time performance is satisfactory, with negligible delay under test conditions, showcasing its potential for logistics applications and beyond. [ABSTRACT FROM AUTHOR]

—Hospital information system, as an integrated system consists of complex, diverse, and heterogeneous information systems, which supports all clinical, administrative, and financial activities of patients; therefore, it faces interoperability problems, which is a critical feature of data sharing and integration. In this regard, a reference architecture will be presented for the integration of different systems in the hospital which comprises system, information and software architecture. This architecture emphasizes interoperability with eight layers of user interface and application, services, data collection and storage, integration, external application systems, communication and information infrastructure, management, and security/privacy, based on service orientation. It will be evaluated by ATAM method, based on ten scenarios. It shows the presented architecture will satisfy all functional and non-functional requirements such as interoperability between different information systems, reduction of information redundancy and development cost and time, scalability and accessibility.

Meta-heuristic approaches evaluate the optimum size and position of flexible alternative current transmission systems power systems. The seeker optimization algorithm (SOA) technique was used to solve power engineering optimization problems with better performance than traditional approaches. This article shows the application of SOA for optimal setting and allocation of thyristor-controlled series compensators (TCSCs) in a transmission line. TCSC devices are used to improve transmission systems’ capacity and voltage profile by controlling the transmission line reactance. The IEEE 30 bus system, as well as the Iraqi Super Grid 400 kV system, is used as a test system to illustrate the technique used. Results showed that the installation of TCSC unites the aims to reduce the voltage deviation, reduce the losses of active/reactive power, and increase transmission line reserves over thermal limits. TCSC devices are very effective for the better use of existing installations without sacrificing the stability margin. SOA is intended to identify the best location and size of TCSC devices that resolve the technological difficulties of reducing the TCSC devices’ costs.

The purpose of this research is to propose a System Architecture to facilitate the IT Talent ecosystem using a service-oriented approach. The need for this is important to support digital transformation in the IT Talent ecosystem. Human resources in the IT field are one of the key factors in implementing IT in organizations. However, the availability of IT human resources has not been able to meet the needs and challenges of the organization in synergizing IT and business. Meanwhile, on the other hand, the qualifications of IT human resources do not meet the existing competency standards. In this research, we use a service-oriented system development method. It consists of three stages, such as (1). Analysis and Observation, (2). Analysis from an in-depth interview, and (3) System Architecture Design, which includes Analysis Features of the Systems, Service Analysis and Identification, Specification of Architecture, and Layering. The novelty and findings of this research are a system architecture, which is called a middleware architecture, that can bridge entities in the IT Talent ecosystem to provide and use services to each other for support collaboration. In this study, we proposed a system architecture that acts as middleware to support collaboration and integration in the IT Talent ecosystem. We proposed TALENT-IT, which acts as a service bus mechanism. We used a service-oriented approach to develop this platform. The results of this study are: list of features, list of services, SOA layer, SOA architecture, and monetization feasibility and challenges. Doi: 10.28991/HIJ-2023-04-04-03 Full Text: PDF

The popularity of microservice architecture abbreviated MSA has attracted researchers and practitioners in recent years. MSA aims to divide the complex monolithic system from the service to the database into several autonomous blocks called microservices. In this way, updates and deployment of each service can be managed independently. The dissociation of data storage for each microservice is one of the particularities of this architecture. However, the manual implementation of certain tasks in the design and development of the MSA is time-consuming particularly with regard to data management. The objective of this article is therefore to automatically generate the data structure of a microservice from ReLEL in order to systematically derive the MSA databases. Our approach is based on the Praxeme methodology. It is realized in two stages. First, the semantic aspect is derived. Then, we develop ATL derivation rules to design the data structure. [ABSTRACT FROM AUTHOR]

Hospital information system, as an integrated system consists of complex, diverse, and heterogeneous information systems, which supports all clinical, administrative, and financial activities of patients; therefore, it faces interoperability problems, which is a critical feature of data sharing and integration. In this regard, a reference architecture will be presented for the integration of different systems in the hospital which comprises system, information and software architecture. This architecture emphasizes interoperability with eight layers of user interface and application, services, data collection and storage, integration, external application systems, communication and information infrastructure, management, and security/privacy, based on service orientation. It will be evaluated by ATAM method, based on ten scenarios. It shows the presented architecture will satisfy all functional and non-functional requirements such as interoperability between different information systems, reduction of information redundancy and development cost and time, scalability and accessibility. [ABSTRACT FROM AUTHOR]

The impact of relative humidity (RH) on organic new particle formation (NPF) from the ozonolysis of biogenic volatile organic compounds (BVOCs) remains an area of active debate. Previous reports provide contradictory results, indicating both the depression and enhancement of NPF under conditions of high RH. Herein, we report on the impact of RH on NPF from the dark ozonolysis of cis-3-hexenyl acetate (CHA), a green-leaf volatile (GLV) emitted by vegetation. We show that RH inhibits NPF by this BVOC, essentially shutting it down at RH levels > 1%. While the mechanism for the inhibition of NPF remains unclear, we demonstrate that it is likely not due to increased losses of CHA to the humid chamber walls. New oxidation products dominant under humid conditions are proposed that, based on estimated vapor pressures (VPs), should enhance NPF; however, it is possible that the vapor phase concentration of these low-volatility products is not sufficient to initiate NPF. Furthermore, the reaction of C3-excited state Criegee intermediates (CIs) with water may lead to the formation of small carboxylic acids that do not contribute to NPF. This hypothesis is supported by experiments with quaternary O3 + CHA + α-pinene + RH systems, which showed decreases in total α-pinene-derived NPF at ~0% RH and subsequent recovery at elevated RH. [ABSTRACT FROM AUTHOR]

Despite the increase in the efficiency of energy consumption in information and communication technology, software execution and its constraints are responsible for how energy is consumed in hardware hosts. Consequently, researchers have promoted the development of sustainable software with new development methods and tools to lessen its hardware demands. However, the approaches developed so far lack cohesiveness along the stages of the software development life cycle (SDLC) and exist outside of a holistic method for green software development (GSD). In addition, there is a severe lack of approaches that target the analysis and design stages of the SDLC, leaving software architects and designers unsupported. In this article, we introduce our behavior-based consumption profile (BBCP) external Domain-Specific Language (DSL), aimed at assisting software architects and designers in modeling the behavior of software. The models generated with our external DSL contain multiple sets of properties that characterize features of the software’s behavior. In contrast to other modeling languages, our BBCP emphasizes how time and probability are involved in software execution and its evolution over time, helping its users to gather an expectation of software usage and hardware consumption from the initial stages of software development. To illustrate the feasibility and benefits of our proposal, we conclude with an analysis of the model of a software service created using the BBCP, which is simulated using Insight Maker to obtain an estimation of hardware consumption and later translated to energy consumption.

1,2-Dihydroxy isoprene (1,2-DHI), a product of isoprene oxidation from multiple chemical pathways, is produced in the atmosphere in large quantities; however, its chemical fate has not been comprehensively studied. Here, we perform chamber experiments to investigate its gas-phase reactions. We find that the reactions of 1,2-DHI with OH radicals and ozone are rapid (kOH = 8.0 (±1.3) × 10-11 cm3 molecule-1 s-1; kO3 = 7.2 (±1.1) × 10-18 cm3 molecule-1 s-1). Reaction with OH, which dominates 1,2-DHI loss, leads primarily to fragmentation and radical recycling; major products under both high- and low-NO conditions include hydroxyacetone, glycolaldehyde, and 2,3-dihydroxy-2-methyl-propanal (DHMP). Radical-terminating hydroperoxide formation from the peroxy radical (RO2) reaction with HO2 and organonitrate formation from RO2 + NO are not observed in the gas phase, possibly due to low volatility; constraints for their branching ratios are instead derived by mass balance. We also measure secondary organic aerosol mass yields from 1,2-DHI (0-23%) and show that oxidation in the presence of aqueous particles leads to formic and acetic acid production. Finally, we incorporate results into GEOS-Chem, a global chemical transport model, to compute the global production (25.3 Tg a-1) and gas-phase loss (20.2 Tg a-1) of 1,2-DHI and show that its oxidation provides non-negligible contributions to the atmospheric budgets of hydroxyacetone, glycolaldehyde, hydroxymethyl hydroperoxide, formic acid, and DHMP.

The accurate calculation of the height of fractured water-conducting zone (FWCZ) is of great significance for mine optimization design, water disaster prevention, and safety production of the coal mines. In this article, a height-prediction model of FWCZ based on extreme learning machine (ELM) is proposed. To address the issues of low prediction accuracy and challenging parameter optimization, we optimized the ELM model using the gray-wolf optimization algorithm (GOA), whale optimization algorithm (WOA), and salp optimization algorithm (SOA). These optimization algorithms mitigate the issues of slow convergence, poor stability, and local optimality associated with traditional neural networks. The mining depth, mining height, overburden strata structure, working face length, and coal seam dip angle are selected as the main controlling factors for the height of FWCZ. A total of 42 fields-measured samples are collected and divided into 2 subsets for training and validating with a ratio of 36/6. The prediction capability of GOA-ELM, WOA-ELM, and SOA-ELM models are evaluated and compared, and the results show that the calculation results of the three models are optimized compared with the ELM model. The prediction capability of GOA and WOA are similar, while the prediction results of SOA-ELM are better than the other two models, and the relative errors of the test sets are all less than 10%. Therefore, the SOA-ELM model is finally applied to predict the height of FWCZ formed after the mining of No.15 coal seam in Xinjian Coal Mine. Finally, we verified the prediction results using measured data from the borehole television detection instrument, which showed good consistency. This provides further evidence of the effectiveness of the swarm intelligence optimization algorithm in predicting the height of FWCZ. [ABSTRACT FROM AUTHOR]

Atmospheric ammonia (NH3) can affect nitrogen deposition, particle acidity, and gas-particle partitioning. Although the inorganic chemistry of NH3 in fine particulate (PM2.5) formation are well-constrained, the understanding of interactions between NH3 and secondary organic aerosol (SOA) are rather insufficient until recently. Laboratory studies indicate that NH3 molecule can react with SOA then forms nitrogen-containing organic compounds (NOCs), which can further react to form heterocyclic organic compounds. In this study, we use a modified version of the CMAQ model to simulate the potential importance of the SOA-ammonia uptake mechanism on air quality over China in summer and winter 2017, considering a range of assumed NH3 uptake coefficients (10−3–10−5). Our results show that uptake of NH3 by SOA leads to a decrease in gas-phase NH3 mixing ratio, by as much as 27.5% and 19.0% for the highest uptake coefficient scenario (10−3) in summer and winter, respectively. The largest reduction of ammonia occurs over the Sichuan Basin and the North China Plain. The reduction of gas-phase NH3 engenders a decrease of ammonium nitrate, by up to 30%, but has little impact on the ammonium sulfate concentration. Uptake of NH3 does not significantly affect SOA concentrations owing to overall moderate changes in aerosol acidity, and thus small effects on SOA formation from isoprene. Altogether, NH3 uptake led to a reduction in the average PM2.5 concentration up to 8.9% and 8.7% for the highest uptake coefficient (10−3) in summer and winter, respectively. These results highlight the need for better constraints on the NH3-SOA interactions.

In the context of Industry 4.0, this paper explores the vital role of advanced technologies, including Cyber–Physical Systems (CPS), Big Data, Internet of Things (IoT), digital twins, and Artificial Intelligence (AI), in enhancing data valorization and management within industries. These technologies are integral to addressing the challenges of producing highly customized products in mass, necessitating the complete digitization and integration of information technology (IT) and operational technology (OT) for flexible and automated manufacturing processes. The paper emphasizes the importance of interoperability through Service-Oriented Architectures (SOA), Manufacturing-as-a-Service (MaaS), and Resource-as-a-Service (RaaS) to achieve seamless integration across systems, which is critical for the Industry 4.0 vision of a fully interconnected, autonomous industry. Furthermore, it discusses the evolution towards Supply Chain 4.0, highlighting the need for Transportation Management Systems (TMS) enhanced by GPS and real-time data for efficient logistics. A guideline for implementing CPS within Industry 4.0 environments is provided, focusing on a case study of real-time data acquisition from logistics vehicles using CPS devices. The study proposes a CPS architecture and a generic platform for asset tracking to address integration challenges efficiently and facilitate the easy incorporation of new components and applications. Preliminary tests indicate the platform’s real-time performance is satisfactory, with negligible delay under test conditions, showcasing its potential for logistics applications and beyond.

Tunable multiwavelength fiber lasers based on semiconductor optical amplifiers (SOA) have received attracting interest due to their wide prospective applications in dense division multiplexing (DWDM) systems and optical sensing. Using an SOA in a nonlinear optical loop mirror (NOLM), we demonstrate up to 13 lasing peaks by controlling the pump current and the polarization controller. At maximum pump current (450 mA), the emitted multiwavelength is between 1550 nm and 1572 nm with a wavelength spacing of 1.87 nm and 3 dB output linewidth of 0.8 nm with an output power of −7 dBm and 27 dB optical signal-to-noise ratio (OSNR). The multiwavelength output power and multiwavelength peak stability are investigated, and it was found that the power fluctuation of each multiwavelength line is less than 0.2 dB. In addition, by adjusting the polarization controllers (PCs) and SOA temperature, we obtained a tunable multiwavelength emission. The proposed fiber laser offers advantages such as simple structure, low loss, and long-time stable and multiwavelength emission. [ABSTRACT FROM AUTHOR]

SOA is an architectural style that enables providing applications as services. Following the authentication procedure, most Web services-based applications use application-specific access control mechanisms to make authorization decisions. Services can interact with one another, sometimes relying on a trust-based relationship. However, if unauthorized access is gained to a particular service, it could potentially jeopardize the whole security system. REST, likewise, is an architectural style defined by a set of principles for creating network-based software structures. These concepts come together to form a coherent metaphor for the Web's processes and interactions. In RESTful services, authentication and authorization play a tremendous role in terms of security, so services are constantly charged with authenticating users. Security as an essential aspect of services affects those servers necessarily containing the authentication mechanism, and they must authenticate each service for each of its requests. This study presents the mechanisms of authentication and authorization in RESTful services. A RESTful service's authorization management framework is proposed and the possibility to manage service access authorization to specific services (resources) is described and implemented. The paper is concluded with the presentation of experimental results derived from the implementation of the REST services based on the proposed framework. [ABSTRACT FROM AUTHOR]

Manufacturing companies across multiple industries face an increasingly dynamic and unpredictable environment. This development can be seen on both the market and supply side. To respond to these challenges, manufacturing companies must implement smart manufacturing systems and become more flexible and agile. The flexibility in operational planning regarding the scheduling and sequencing of customer orders needs to be increased and new structures must be implemented in manufacturing systems' fundamental design as they constitute much of the operational flexibility available. To this end, smart and more flexible solutions for production planning and control (PPC) are developed. However, scheduling or sequencing is often only considered isolated in a predefined stable environment. Moreover, their orientation on the fundamental logic of the existing IT solutions and their applicability in a dynamic environment is limited. This paper presents a conceptual model for a task-based description logic that can be applied to factory planning, technology planning, and operational control. By using service-oriented architectures, the goal is to generate smart manufacturing systems. The logic is designed to allow for easy and automated maintenance. It is compatible with the existing resource and process allocation logic across operational and strategic factory and production planning. [ABSTRACT FROM AUTHOR]

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Aromatic hydrocarbons represent a large fraction of anthropogenic volatile organic compounds and significantly contribute to tropospheric ozone and secondary organic aerosol (SOA) formation. Toluene photooxidation experiments were carried out in an oxidation flow reactor (OFR). We identified and quantified the gaseous and particulate reaction products at 280, 285 and 295 K using a proton-transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) coupled to a CHemical Analysis of aeRosol ONline (CHARON) inlet. The reaction products accounted for both ring-retaining compounds such as cresols, benzaldehyde, nitrophenols, nitrotoluene, bicyclic intermediate compounds, as well as ring-scission products such as dicarbonyls, cyclic anhydrides, small aldehydes and acids. The chemical system exhibited a volatility distribution mostly in the semi-volatile (SVOCs – semi-volatile organic compounds) regime. The saturation concentration (Ci*) values of the identified compounds were mapped onto the two-dimensional volatility basis set (2D-VBS). Temperature decrease caused a shift of Ci* towards lower values while there was no clear relationship between Ci* and oxidation state. The CHARON PTR-ToF-MS instrument identified and quantified approximately 70–80 % of the total organic mass measured by an aerosol mass spectrometer (AMS). The experiments were reproduced by simulating SOA formation with the SSH-aerosol box model. A semi-detailed mechanism for toluene gaseous oxidation was developed. It is based on the MCM and GECKO-A deterministic mechanisms modified following the literature in particular to update cresols and ring-scission chemistry. The new mechanism improved secondary species representation with an increment of the major identified species (+35 % in number). Light compounds formation (i.e. m/z < 100) is enhanced and accumulation of heavy compounds (i.e. m/z ≥ 100) is reduced, especially in the gas phase. Additional tests on (i) partitioning processes such as condensation into aqueous phase, (ii) interactions of organic compounds between themselves and with inorganics and (iii) wall losses were also performed. When all these processes were taken into account the simulated SOA mass concentration showed a much better agreement with the experimental results. Finally, an irreversible partitioning pathway for methylglyoxal was introduced and considerably improved the model results, opening a way to further developments of partitioning in models. Our results underline that the volatility itself is not sufficient to explain the partitioning between gas and particle phase: the organic and the aqueous phases need to be taken into account as well as interactions between compounds in the particle phase. [ABSTRACT FROM AUTHOR]

Integration test order generation is an important problem in software integration testing research.Reasonable test order can improve the efficiency of integration test and reduce the cost of test.Service oriented architecture(SOA) is a kind of distributed architecture widely used in enterprises in recent years.At present,there are few researches on integration test order generation in SOA architecture.Due to the polymorphism of service composition in SOA architecture,it is impossible to get the integration test sequence between service software in SOA architecture by using the traditional top-down and bottom-up integration test strategies.However,the current research on the generation of integration test sequence based on class cluster in object-oriented system is difficult to apply to the complex coupling relationship between services in SOA architecture.Therefore,an integration test order generation method based on genetic algorithm is proposed to solve the integration test problem between service software in SOA architecture.In this method,the concept of service feature group is used to represent the influence factors of integration testing,and the concept of integration testing priority is used to represent the importance of integration testing of service software.At the same time,the test dependency graph is constructed to describe the complex coupling relationship between ser-vice software in SOA Architecture.In order to reduce the cost of test,a genetic algorithm is designed to generate integrated test sequence.Finally,an example is given to verify the feasibility and correctness of the method.The example results show that the proposed method can generate service software integration test orders with relatively high test priority and low test cost.

A novel snapback-free superjunction reverse-conducting insulated gate bipolar transistor (SJ-RC-IGBT) is proposed and verified by simulation. In the SJ-RC-IGBT, the parasitic P/N/P/N structure as thyristor or Shockley diode demonstrates large conductivity due to an overabundance of carriers for reverse conduction. By preventing electrons from leaking across the N+ region at the collector side, the extra electron-blocking (EB) layer introduced in the SJ-RC-IGBT can dramatically enhance electron–hole pairs in the N/P-pillars. Hence, the SJ-RC-IGBT demonstrates a low on-state voltage (Von). In addition, snapback-free characteristics and a large safe operating area (SOA) are also achieved in the SJ-RC-IGBT. During the turn-off process, a significant amount of electrons are extracted by parasitic MOS across the EB layer at the collector side to decrease the turn-off loss (Eoff). According to the optimized results, the SJ-RC-IGBT with EB layer obtains an ultralow Eoff of 3.9 mJ/cm2 at Von = 1.38 V with 88% and 81% decreases, respectively, compared with the conventional reverse-conducting IGBT (CRC-IGBT) and superjunction IGBT (SJ-IGBT). [ABSTRACT FROM AUTHOR]

Atmospheric ozone (O3) concentration is impacted by a number of factors, such as the amount of solar radiation, the composition of nitrogen oxides (NOx) and hydrocarbons, the transport of pollutants and the amount of particulate matter in the atmosphere. The oxidative potential of the atmosphere and the formation of secondary organic aerosols (SOAs) as a result of atmospheric oxidation are influenced by the prevalent O3 concentration. The formation of secondary aerosols from O3 depends on several meteorological, environmental and chemical factors. The relationship between PM2.5 and O3 in different urban environmental regimes of India is investigated in this study during the summer and winter seasons. A relationship between PM2.5 and O3 has been established for many meteorological and chemical variables, such as RH, WS, T and NOx, for the selected study locations. During the winter season, the correlation between PM2.5 and O3 was found to be negative for Delhi and Bengaluru, whereas it was positive in Ahmedabad. The city of Bengaluru was seen to have a positive correlation between PM2.5 and O3 during summer, coinciding with the transport of marine air masses with high RH and low wind speed (as evident from FLEXPART simulations), leading to the formation of SOAs. Further, O3 concentrations are predicted using a Recurrent Neural Network (RNN) model based on the relation obtained between PM2.5 and O3 for the summer season using NOx, T, RH, WS and PM2.5 as inputs. [ABSTRACT FROM AUTHOR]

The problem of user authentication and authorization is usually being solved in a single system. Federated environment assumes heterogeneity of systems, which brings the problem of mutual users and services authentication and authorization. In this article the authors presented security requirements for cross domain information exchange in federated environments and a method of secure access to information resources on the basis of web services. Special attentionwas paid to authentication and authorization of users and services. As opportunities, there were presented solutions verified in multinational experimentations and exercises.

In many tasks humans can trade speed against accuracy. This variation of strategy has different consequences for congruency effects in different conflict tasks. Recently, Mittelstädt et al. (2022) suggested that these differences are related to the dynamics of congruency effects as assessed by delta plots. With increasing delta plots in the Eriksen flanker task congruency effects were larger under accuracy set, and with decreasing delta plots in the Simon task they were smaller. Here we tested the hypothesis for a single task, making use of the observation that for the Simon task delta plots decline when the irrelevant feature is presented first, but increase when the relevant feature leads. The differences between congruency effects under speed and accuracy instructions confirmed the hypothesized relation to the slope of delta plots. In fact, for similar delta plots in the compared speed-accuracy conditions, the relation should be a straightforward consequence of the shorter and longer reaction times with speed and accuracy set, respectively. However, when relevant and irrelevant features were presented simultaneously, congruency effects were stronger under speed set at all reaction times. For this condition, a supplementary model-based analysis with an extended leaky, competing accumulator model suggested a stronger and longerlasting influence of the irrelevant stimulus feature. The congruency effects for reaction times were accompanied by congruency effects for error rates when delta plots were decreasing, but not when they were increasing. [ABSTRACT FROM AUTHOR]

Vehicular Ad hoc Network (VANET) is the cutting edge technology for smart transportation. VANET becomes an important aspect of the Intelligent Transport System (ITS). Different safety and non-safety applications have been developed for VANET. The inspiration behind VANET is to provide safe, and pleasant journeys to the drivers and passengers. Although the quality of software depends upon its architecture, most of them do not give proper attention to the consideration of Software-Oriented Architecture (SOA) for providing safety and non-safety ITS services in VANET. To address this issue, we proposed an efficient software architecture by highlighting the important operations and services of the system. The performance of the proposed architecture is evaluated by several design metrics and the results are compared with a state-of-the-art solution. The results showed that our proposed architecture has low coupling and high cohesion factors. Furthermore, the results reveal that our architecture is less complex and more reusable. From the results, we conclude that the proposed architecture is suitable for providing safety and non-safety ITS services and will pave the way for the implementation of the futuristic vision of the ITS. [ABSTRACT FROM AUTHOR]

A faulty situation occurred in Service Oriented Architecture (SOA) based systems can affect its functionality. It is challenging to guarantee the reliability of service utilization in a distributed, concurrent and dynamic composition of web services. This paper aims to present a fault detection approach of SOA using dependency analysis. Data and control dependencies are identified and a fault diagnosis approach based on these dependencies is proposed in this paper. The presented approach extends discrete state space techniques to simulate the concurrent and distributed behavior through Colored Petri Nets (CPNs) for the SOA-based systems in case of the faulty situation. Concrete translation from SOA based system to a CPN model is presented. Model-based technique is used and some heuristics are presented for dependency analysis and fault detection purpose. The experimental performance analysis shows the feasibility of our proposed approach.

This paper demonstrates a C-band 25G colorless passive optical network (PON) based on semiconductor optical amplifier (SOA) and 10G electro-absorption modulator (EAM). The experimental results show that the SOA in the optical network unit (ONU) can erase the downlink signal by taking advantage of the gain saturation feature, realizing the reuse of downstream wavelength. Meanwhile, the SOA gain can compensate for the EAM loss by optimizing the current and injection power. Apart from this, equalization algorithms at the optical line terminal are investigated for linear and nonlinear impairments compensation. Besides, the system robustness to the ASE and the maximum transmission speed are also evaluated. Finally, the system capacity can reach up to 25 Gbps with NRZ format at a bit-error ratio threshold of 2 × 10−2, proving that this system is a promising technology for future high-speed colorless 2 × 25G or 4 × 25G Wavelength division Multiplexing (WDM) PON system.

Novel events catch our attention, which can influence performance of a task. Whether this attentional capture by novelty benefits or impairs performance depends on several factors, such as the relevance of the stimulus, task requirements, and the timing of the event. Additionally, it has been argued that novel stimuli can hold intrinsic reward value, which may directly affect approach motivation, similar to positive valence stimuli. This link between novelty and approach/avoid behaviour has not been investigated directly. Here, we investigated whether stimulus novelty interacts with response behaviour in an approach/avoidance task, and whether these effects depend on the task relevance of novelty and stimulus timing. In experiment 1, participants gave an approach or avoid response dependent on a shape (diamond or square) presented at different stimulus onset asynchronies (SOA) following a novel or familiar scene (target-irrelevant novelty). In experiment 2, participants had to approach or avoid a novel or familiar image depending on the content (indoor/outdoor; target-related novelty). A shape was presented at different SOA. Results of a linear mixed model showed novelty-induced performance costs as demonstrated by longer RT and lower accuracy when novelty was target-relevant, likely due to attentional lingering at novel images. When images were target-irrelevant, approach but not avoid responses were faster for familiar versus novel images at 200 ms SOA only. Thus, novelty had a differentially pronounced detrimental effect on performance. These observations confirm that processing of novel stimuli generally depends on stimulus relevance, and tentatively suggests that differential processing of novel and familiar images is intensified by motivated approach behaviour.

The need of generating new paradigms in software engineering requires the development of models and methodologies used properly innovations, personalized services and software to integrate different models that facilitate interactivity and access to vital information for organizations technologies. This paper bring to account a proposition for the integration of technologies for implementing semantic web applications. An exhaustive study of the different possible technological paradigms to integrate, as well as tools and standards that support it is performed. The converging points of these areas in creating web applications can assist a strategy to ensure the permanence of the principles of each paradigm for which they were created. The results of this research confirm that such integration is possible in a single web site for the knowledge, information and processes management of an organization or business unit. It is possible to establish a technological guideline to implement a website, where the central core is built with ontological models and business process modeling, which share information and web services, described by the first one and invoked by the latter.

High loads of fine particulate matter (PM2.5) and ozone (O3) pollution occurred frequently since early spring and led to an increasing contribution of secondary organic aerosols (SOA) in organic aerosols. However, the characteristics of precursor volatile organic compounds (VOCs) have rarely been studied. In this study, the continuous observation of VOCs was performed by an offline VOC monitoring system and gas chromatography-mass/flame ionization detector from 1 April 2020 to 31 July 2020; the characterization of VOCs and their contribution to SOA was explored. The results showed that during the observation period, the average mixing ratio of TVOCs was 42.6 ± 11.2 ppbv, and the major VOCs species were OVOCs, followed by alkanes, halocarbons, aromatics, alkenes and acetylene. When the west circulation pattern functioned, the value of aromatics increased, and the relation between PM2.5, O3 and VOCs increased when the high-pressure system controlled by anticyclone functioned. In combination with the results of positive matrix factorization, the main emission sources of ambient VOCs were complex, and the fuel combustion, industry-related emission, vehicle emission, biogenic emission and solvent volatilization accounted for 27.1%, 24.4%, 24.3%, 12.1% and 12.0%, respectively. Moreover, the industry-related emission contributed the greatest to the generation of SOA. This result indicated that the restrictions on aromatics during the industrial process are vital to reducing SOA formation. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are of vital importance in the formation of secondary organic aerosol (SOA). Understanding SOA formation remains challenging, requiring further investigation of both oxygenated VOCs (OVOCs) and SOA composition with novel measurement techniques. In this work, we deployed a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS) to measure VOCs and their oxidation products in urban Zurich in summer 2016. The positive matrix factorization (PMF) source apportionment method identified five sources, including two primary sources (traffic and local), and three OVOC sources associated with different oxidation processes in the atmosphere. Together with the deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF-MS), this enabled a detailed understanding of the SOA components which were dominated by biogenic SOA and distinguished by daytime and nighttime chemistry. The combination of the two instruments provided new insights in the understanding of atmospheric processes by comparison of molecular-level secondary components between gas phase and particle phase. In the gas phase, two OVOC factors (32.1% and 16.7%) showed strong influence from the oxidation of aromatic compounds, exhibiting low atomic H to C ratios, and were distinguished by daytime and night-time chemistry. The third OVOC factor (19.3%) was characterized by strong biogenic influence. Similar temporal variations were found for the gas and aerosol phase, indicating co-evolution of OVOCs and SOA in summer. Besides, comparisons of OVOC compounds and SOA composition exhibited similar H to C ratio distributions for both the gas phase and particle phase., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

In many tasks humans can trade speed against accuracy. This variation of strategy has different consequences for congruency effects in different conflict tasks. Recently, Mittelstädt et al. (2022) suggested that these differences are related to the dynamics of congruency effects as assessed by delta plots. With increasing delta plots in the Eriksen flanker task congruency effects were larger under accuracy set, and with decreasing delta plots in the Simon task they were smaller. Here we tested the hypothesis for a single task, making use of the observation that for the Simon task delta plots decline when the irrelevant feature is presented first, but increase when the relevant feature leads. The differences between congruency effects under speed and accuracy instructions confirmed the hypothesized relation to the slope of delta plots. In fact, for similar delta plots in the compared speed-accuracy conditions, the relation should be a straightforward consequence of the shorter and longer reaction times with speed and accuracy set, respectively. However, when relevant and irrelevant features were presented simultaneously, congruency effects were stronger under speed set at all reaction times. For this condition, a supplementary model-based analysis with an extended leaky, competing accumulator model suggested a stronger and longer-lasting influence of the irrelevant stimulus feature. The congruency effects for reaction times were accompanied by congruency effects for error rates when delta plots were decreasing, but not when they were increasing.

Manufacturing companies across multiple industries face an increasingly dynamic and unpredictable environment. This development can be seen on both the market and supply side. To respond to these challenges, manufacturing companies must implement smart manufacturing systems and become more flexible and agile. The flexibility in operational planning regarding the scheduling and sequencing of customer orders needs to be increased and new structures must be implemented in manufacturing systems’ fundamental design as they constitute much of the operational flexibility available. To this end, smart and more flexible solutions for production planning and control (PPC) are developed. However, scheduling or sequencing is often only considered isolated in a predefined stable environment. Moreover, their orientation on the fundamental logic of the existing IT solutions and their applicability in a dynamic environment is limited. This paper presents a conceptual model for a task-based description logic that can be applied to factory planning, technology planning, and operational control. By using service-oriented architectures, the goal is to generate smart manufacturing systems. The logic is designed to allow for easy and automated maintenance. It is compatible with the existing resource and process allocation logic across operational and strategic factory and production planning.

This paper deals with improving transmission properties of a DWDM system based on amplification techniques. Parameter values change due to a change in the type of optical amplifier or an adjustment of the parameters of the optical amplifiers. Optimization summarizes the knowledge of the systems and software that are used. These assumptions are verified by a set of simulations and the obtained numerical values are compared with the values given in the relevant articles. The proposed design, which uses a larger number of EDFA amplifiers over long distances, has been found to perform better than single amplifier systems. In addition, the proposed solution is better in transmission characteristics than other approaches with a similar purpose. [ABSTRACT FROM AUTHOR]

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Present-day intelligent healthcare applications offer digital healthcare services to users in a distributed manner. The Internet of Healthcare Things (IoHT) is the mechanism of the Internet of Things (IoT) found in different healthcare applications, with devices that are attached to external fog cloud networks. Using different mobile applications connecting to cloud computing, the applications of the IoHT are remote healthcare monitoring systems, high blood pressure monitoring, online medical counseling, and others. These applications are designed based on a client–server architecture based on various standards such as the common object request broker (CORBA), a service-oriented architecture (SOA), remote method invocation (RMI), and others. However, these applications do not directly support the many healthcare nodes and blockchain technology in the current standard. Thus, this study devises a potent blockchain-enabled socket RPC IoHT framework for medical enterprises (e.g., healthcare applications). The goal is to minimize service costs, blockchain security costs, and data storage costs in distributed mobile cloud networks. Simulation results show that the proposed blockchain-enabled socket RPC minimized the service cost by 40%, the blockchain cost by 49%, and the storage cost by 23% for healthcare applications. [ABSTRACT FROM AUTHOR]

This paper demonstrates a C-band 25G colorless passive optical network (PON) based on semiconductor optical amplifier (SOA) and 10G electro-absorption modulator (EAM). The experimental results show that the SOA in the optical network unit (ONU) can erase the downlink signal by taking advantage of the gain saturation feature, realizing the reuse of downstream wavelength. Meanwhile, the SOA gain can compensate for the EAM loss by optimizing the current and injection power. Apart from this, equalization algorithms at the optical line terminal are investigated for linear and nonlinear impairments compensation. Besides, the system robustness to the ASE and the maximum transmission speed are also evaluated. Finally, the system capacity can reach up to 25 Gbps with NRZ format at a bit-error ratio threshold of 2 × 10−2, proving that this system is a promising technology for future high-speed colorless 2 × 25G or 4 × 25G Wavelength division Multiplexing (WDM) PON system. [ABSTRACT FROM AUTHOR]

With the tremendous growth of Internet and its related technologies, the Service Oriented Architecture (SOA) became a dominant paradigm shift for enterprise computing. In SOA, business functionalities are offered by many different Service Providers as services. In order to get served by different service providers, the client has to authenticate with those service providers at multiple times. Single Sign On (SSO) mechanism provides the client to login only one time so that access to different services is made possible without needing to re-authenticate. Here, the identity of the logged-in client is federated among the enterprise computing nodes. This is one of the simplest forms of federated identity. The goal of identity federation is to benefit ease of use, flexibility, productivity and reduced cost of the authentication process, but trust and security is a major concern in this situation. Major threats on federated identity management are due to identity misuse, identity theft, and trust deficit between identity providers and services providers. As of now, the Security Assertion Markup Language (SAML), Open Authorization (OAuth) and OpenID are the three important federated identity management standards in the industry. However, none of them is equipped by itself to provide comprehensive security protection for identity federation even within a single enterprise computing environment. In fact, these federated solutions result in additional security vulnerabilities due to their openness of identity federation. The security threats are becoming severe when federated identity is spanned into the inter-organizational and intra-organizational computing environment. This paper analyses the vulnerabilities and security gaps in the existing federated identity solutions. To overcome these gaps, an adaptive security architectural model is proposed for identity federation at inter and intra-organizational level using public key infrastructure that adheres to the SOA security standards and specifications. The proposed architecture is implemented and tested in a large-scale federated identity enterprise computing environment with security-centric financial data to acquire the desired results. A cross-sectional comparative analysis is done between existing and proposed solutions to validate the improvement in the protection of identity federation environment.