Handling Capability Research Articles

Configuration-Driven No-Code Data Ingestion Engine with RuleBased Processing

The efficient management of batch processes is critical for modern data-driven organizations, especially within the context of complex data ingestion and processing workflows. This abstract explores the essential components and functionalities required to streamline batch job execution within such environments. Firstly, a robust batch management system is essential, providing capabilities for job scheduling, dependency management, and error handling. Such a system orchestrates the execution of batch jobs, ensuring they run in the appropriate sequence and handle dependencies effectively. Additionally, real-time event-driven triggers enable immediate batch job initiation upon file drops, ensuring timely processing of incoming data and swift response to business needs. Conversely, scheduled batch executions provide predictability and automation, allowing organizations to optimize resource utilization and maintain operational efficiency by running batches at predetermined intervals or specific times. Furthermore, the abstract delves into the necessity of a comprehensive configuration setup to support various data formats, transformation requirements, and validation criteria. A rich configuration engine allows for seamless mapping, transformation, and validation of incoming data, enabling flexibility and adaptability to diverse data sources and requirements. It also emphasizes the importance of containerization for batch job execution, ensuring scalability, resource isolation, and efficient utilization of computing resources. Lastly, the provision of job IDs facilitates seamless invocation of batch jobs by external systems, enabling streamlined interaction and integration across different platforms. Together, these components form a cohesive framework for efficient batch job management, empowering organizations to optimize data processing workflows and derive actionable insights from their data assets.

BSELA: A Blockchain Simulator with Event-Layered Architecture

Blockchain technology has found widespread use in various fields, including finance, healthcare, the Internet of Things, and supply chain management, due to its ability to meet technical and non-technical requirements. Therefore, it is crucial for system designers to evaluate the performance and characteristics of a given blockchain platform before deploying it. One way to achieve this is through the use of blockchain simulators. However, existing simulators have limitations in areas such as model scaling, event scheduling, time control, object model evaluation, and simulation magnitude. To address these limitations, we propose a Blockchain Simulator based on Event-Layered Architecture (BSELA) in this paper. BSELA comprises multiple functional modules with effective model scalability, with the core being our proposed Event-Layered Architecture. This architecture introduces a new event-driven scheduling mechanism for discrete-event simulation, which improves the efficiency, stability, and maintainability of event scheduling during blockchain simulation. Furthermore, we propose a time advancement mechanism for subsequent events based on event rounds, which improves the accuracy of time advancement, simulation complexity, and real-time demand handling capability during the simulation. We begin by validating the efficiency of our simulator by comparing experiments with those of existing blockchain simulators. We then validate the accuracy of BSELA through simulation experiments on blockchain network connectivity, block propagation latency, and the number of INV messages propagated per hour. We validated the accuracy of the experimental results by conducting a comparison with Bitcoin data. Finally, in order to address the research gap in the performance of blockchain systems at the underlying peer-to-peer network level and in other fields, we designed and experimentally validated the node-trust network construction mechanism by adjusting the simulator’s blockchain object model. Our experiments show that this tuning mechanism improves data transfer efficiency by 30%–40%, and also improves security. The design and experiments of the BSELA tuning mechanism validate the scalability and flexibility of our simulator for blockchain research.

Integrating Banking Fundamental Factors with Financial Technology in Reducing Banking Risk

Fintech has been successful in producing new models in financial services, and creating solutions. Fintech is able to improve risk handling capabilities and reduce the possibility of risks. This research is a quantitative research that measures how Fintech can moderate banking fundamental factors in reducing banking risk. This study uses secondary data sourced from the Financial Services Authority and Bank Indonesia from April 2020 to April 2023. This research used Ordinary Least Square (OLS) to determine the magnitude and significance effect of fintech on non performing loan rate. The result showed that Fintech can reduce banking risk and Loan to Deposit Ratio (LDR) can increase banking risk.

An artificial intelligence (AI)-driven method for forecasting cooling and heating loads in office buildings by integrating building thermal load characteristics

Due to the thermal inertia of building envelope and random uncertainty of occupant behaviors, real-time and accurate forecasting for building cooling and heating loads is not easy to implement. It requires not only favorable modeling methods, but also attention to the intrinsic cause analysis of loads. However, most previous studies have focused more on the improvement of forecasting algorithms, lacking the comprehensive analysis and scientific research from the load formation mechanism. To address this, a novel artificial intelligence (AI)-driven forecasting method integrating building thermal load characteristics, is proposed. This modeling approach takes into account both strong reflection ability of resistance-capacitance (RC) for the thermophysical characteristics of building envelope and the superior handling capability of dynamic Bayesian network (DBN) for occupant uncertainties. Therewith, the independent building envelope model and occupant behavior model are established. Coupling the predicted values of these two sub-models, the building total load forecasting model is established using fuzzy radial basis function (RBF) neural network. A case study of an office building in Tianjin is utilized to validate the proposed method, revealing excellent predictive performance for both the sub-models and the total load model. The proposed method can effectively predict thermal load both from the formation mechanism of internal and external disturbances. It was found that the AI-driven model incorporating building thermal load characteristics, achieves significantly higher precision compared to the general data-driven model, with a reduction of 14.74% in coefficient of variation of root mean squared error in summer and 59.78% in winter.

The Application and Research of Translation Studios in the Development of MTI at Polytechnic University

As exchanges with the global community continue to increase, the translation field presents significant challenges that capture the attention of researchers. The new era demands a reform in the traditional approach to cultivating translation talents. Particularly, the form and quality of practical teaching need improvement to adapt to the changing demands of the market. University translation studios can to some extent compensate for the shortcomings of traditional classroom teaching and workshop-style practical training at Polytechnic University. Taking the author's own university as an example, this paper explores the significance, feasibility, and operational model of the university translation studio. The paper concludes that the purpose of the university translation studio is to enhance students' translation skills, application of translation techniques, project management, professional demeanor, task handling, and teamwork capabilities. This kind of studio elevates the ability of both faculty and students to serve the local community and society, thereby making a positive contribution to the comprehensive development of the North China Electric Power University's Master of Translation and Interpreting program.

Electro-Absorption Modulator Thermo-Optical Self-Heating Analysis

In this work a novel methodology is presented for coupled thermo-optical modelling of an electro-absorption modulator (EAM). First, an optical FDTD simulation results in the light absorption map in the EAM waveguide. This absorption is used as a heat source boundary condition in a thermal finite element (FE) simulation in order to calculate the waveguide temperature. The FE model is validated with experimental data. The temperature is averaged over the device length and used as input in a compact, fully coupled thermo-optical model. The model reveals a thermal instability of the device characteristic, which limits the maximum amount of optical power the device can handle. Finally, using the thermal FE model, a self-heating mitigation strategy is proposed. Using process compatible design changes, self-heating can be reduced by up to 40%, greatly increasing the EAM optical power handling capabilities.

RF design of helical long-wire traveling wave antenna for helicon current drive in KSTAR

This paper presents the development, fabrication, and implementation of a state-of-the-art helical long-wire traveling wave antenna (LW-TWA) for the Korea Superconducting Tokamak Advanced Research (KSTAR) helicon wave current drive (HCD). A multi-stage design approach has been employed incorporating schematic and simplified radio frequency (RF) modeling, to fulfill critical antenna performance criteria, such as parallel refractive index, while maintaining low electric field properties and load resilience. The advanced design includes a Faraday shield and a structurally rigid support for mechanical stability and minimal RF performance distortion. The sophisticated design and megawatt (MW)-class RF power handling capability of the LW-TWA hold the potential to improve HCD performance in KSTAR plasma.

Pt-Ni contact engineering in carbon nitride based photocatalysts for hydrogen production

The effect of a binary PtNi co-catalyst supported on graphitic carbon nitride nanosheets is studied in the photo-production of hydrogen from methanol:water mixtures. The physicochemical analysis provides evidence that the carbon nitride support allows the formation of highly dispersed PtNi nanoparticles with an average composition of Pt 85 % Ni 15 %. The binary system outperforms the monometallic Pt and Ni counterparts and renders an extraordinary quantum efficiency of 8.8 % for hydrogen photo-production. The formation of a PtNi alloy, with a Pt-enriched surface and electronic properties influenced by the heterometallic contact, provides high and stable activity, mostly as a consequence of the effects that the co-catalyst exerts on the charge carrier handling capability of the solid.

A New 3D Frequency-Selective Structure for 5G Communication

Background: In this paper, a new frequency-selective structure (FSS) for 3 to 4 GHz frequency band of fifth generation (5G) is proposed as a result of an analytical mode-matching method. Methods: A new periodic structure with stepped rods is designed using a closed-form equation derived by the analytical mode-matching method. Performance of the structure is simulated by different numerical packages. Results: The analytical and simulation results demonstrate that the designed structure transmits incident waves in 3.4 to 3.9 GHz frequency range with return loss lower than 10 dB and insertion loss of about 0.5 dB. The structure reflects the frequencies out of this range, especially wireless local area network (WLAN) 5 GHz, which is adjacent to this band. Furthermore, the performance of the proposed structure is independent of the TE and TM polarization of the incident wave and relative to the angle of the incident wave up to 60 degrees from perpendicular to the FSS surface, it has minor variations of about 8% in the transmitted frequency bandwidth. In addition, the average value of maximum field enhancement factor (MFEF) as the ratio of maximum field magnitude on the FSS surface to the magnitude of the incident field, used for assessing power handling capability of the structure, is about 4.5. Conclusion: Therefore, these features make the proposed structure suitable for 5G communication and high power systems.

Autonomous Catalyst Development for Alkaline Electrolysis

NiFe LDH based materials are promising candidates for cheap, high performance catalysts for alkaline OER. While suffering from degradation effects, the presence of Fe, even in trace amounts, increases their OER activity manifold compared to plain Ni hydroxide. Although discovered in the mid-80s, the exact catalytic mechanism of this “Fe effect” is still not fully understood. Additionally, other doping elements like Co, Cr, Al and others have shown to both further improve OER activity and increase stability. The properties of those materials are often highly dependent on the doping ratio, resulting in an enormous number of possible material combinations. Modern techniques like DFT simulations and machine learning can help to speed up the search for the optimal compositions, but ultimately manual experimentation often limits how fast better materials can be discovered, as the process remains both resource and time-consuming.In this work, we combine an autonomous high-throughput experiment with machine learning assisted optimization of material compositions to a closed-loop system in an attempt to substantially accelerate the search for high performance alkaline OER catalysts. The system screens an eight variable phase space of doped NiFe LDH for compositions that yield optimal OER performance. Its centerpiece is a 4-axis robotic arm from North Robotics with sample, vial and liquid handling capabilities. The samples are prepared by means of a dip-coating process on Ni foam substrates that allows for doping with different metals. Electrochemical investigations are carried out in 1M KOH in an automated test cell, including EIS, CV and CP measurements at current densities of up to 200mA/cm2. From these results, a figure of merit for the OER activity is calculated and fed into a bayesian optimizer (Dragonfly). This algorithm determines the most promising next test candidate based on the principles of exploration and exploitation and initiates the next experiment accordingly. The experimental procedure can be divided into independent sub-steps, allowing for smart scheduling. This can reduce downtime of the robotic arm and therefore increase the throughput significantly, such that up to 1000 experiments per week can be achieved.We present the first results of a screening study conducted with this system and compare it to a manual study in terms of accuracy, reproducibility and throughput. Selected, particularly high performing compositions found in this study are also tested in a flow cell setup under industrially relevant conditions (30 wt. % KOH, 60 °C) for several hundred hours.

Part II: State-of-the-Art Technologies of Solar-Powered DC Microgrid with Hybrid Energy Storage Systems: Converter Topologies

Over the past few years, there have been significant advancements in Microgrid (MG) systems, particularly in the field of power electronics. These advancements aim to address the needs of the grid and loads, while integrating low-voltage, non-linear, and highly sensitive power sources, such as solar PV modules, batteries, and supercapacitors. It is crucial to select the appropriate converter configuration and power converters in MG systems, as they greatly impact their optimal performance. To achieve the best results, numerous architectures and converter configurations have been suggested for integrating different energy sources. As a result, a considerable number of research articles have been published, necessitating a thorough review. This article continues studies of Part I and presents a comprehensive overview of various architectures based on the arrangement of different sources and provides a detailed analysis and discussion of these architectures. This article covers thirty-three different categories of DC-DC converters, both isolated and non-isolated. These converters are divided into subcategories, such as conventional type, switched-capacitor type, soft-switching type, multi-phase type, and multilevel type. The article also evaluates the suitability of these topologies based on factors such as high conversion gain, power decoupling, efficiency, isolation, power handling capabilities, and compact design. The critical examination and comparative study presented in this work can be valuable for industry professionals and academics in selecting the most suitable architectural and power converter topologies for optimal performance.

The effect of eliminating sintering during the synthesis of 3D scaffolds using the gel-casting method on their biological characteristics: in vivo and in vitro evaluations

The possibility of making shapeable three-dimensional scaffolds along with suitable mechanical properties is one of the most challenging points in tissue engineering. This study investigated the effect of the eliminating sintering during the synthesis of Hydroxyapatite/Agarose nanocomposite foam produced by gel-casting method, as bone tissue cellular scaffold, on its biological characteristics. The Hydroxyapatite/Agarose nanocomposite foam was synthesized by gel-casting, and samples were divided into two groups: group S, in which half of the samples were sintered, and group C, which the other half of the samples were left unsintered. To assess in vitro cytotoxicity, the supernatant culture medium was extracted from 100 mg ml−1 foam suspension in complete culture medium after 72 h incubation and diluted into various concentrations. SaOs-II cells were incubated with extracts of each scaffold at different concentrations and analyzed using the MTT assay. Additionally, in vivo characteristics were evaluated by implanting the scaffolds in rat tibia. Overall, the number of living cells was higher in group S than in group C, except for concentrations of 25% and 75% after 24 and 48 h of incubation, respectively. MTT assay results indicated that concentrations below 50% for group S and 25% for group C could be considered non-toxic. All in vivo variables exhibited significant changes over time, with most changes occurring faster in group S than in group C. There was a statistically significant difference between the two groups in terms of inflammation rate, osteocyte, osteoblast, and osteoclast count, as well as remaining biomaterial percentage only on day 30. Despite the delay in the tissue regeneration process observed by eliminating sintering during the gel-casting method, it is recommended as a means of producing reversible polymeric scaffolds with proper handling, cutting, and shaping capabilities that can be easily applied by clinicians during surgery according to the specific defect site.

Performance assessment of a tightly baffled, long-legged divertor configuration in TCV with SOLPS-ITER

Numerical simulations explore a possible tightly baffled, long-legged divertor (TBLLD) concept in a future upgrade of the tokamak à configuration variable (TCV). The SOLPS-ITER code package is used to compare the exhaust performance of several TBLLD configurations with results from unbaffled and baffled TCV configurations. The investigated TBLLDs feature a range of radial gaps between the separatrix and the divertor baffles, with a smaller gap resulting in tighter baffling. All modeled TBLLDs are predicted to lead to a denser and colder plasma in front of the targets and increase the power handling by factors of 2–3 compared to the present, baffled, divertor and by up to a factor of 12 compared to the original, unbaffled, configuration. This improved TBLLD performance is attributed to an increased neutral confinement with more plasma–neutral interactions in the divertor region. Both power handling capability and neutral confinement increase with tighter baffling. The core compatibility of TBLLDs with nitrogen seeding is also evaluated and the detachment window, with acceptable core pollution, for these TBLLDs is explored, showing a reduction of the required upstream impurity concentration to achieve detachment by up to 18% with tighter baffling.

A Sub-GHz CMOS SPDT Antenna Switch Employing Linearity-Enhanced Biasing Strategy for Second-Order Harmonic Reduction

A CMOS single-pole double-throw (SPDT) antenna switch employing linearity-enhanced biasing strategy is proposed for the second-order harmonic (H2) reduction. It was implemented and demonstrated using a 0.28-lm thick-oxide MOSFET in 65-nm CMOS process. The NMOS transistor of the conventional antenna switch is replaced with the CMOS transistor composed of an NMOS and PMOS transistor in parallel to improve second-order harmonic distortion (HD2). The optimum channel width of an NMOS and PMOS transistor is chosen to achieve odd symmetry characteristic of I-V curve with respect to the drain-to-source voltage swing (VDS), and, as a result, enhance HD2 of the antenna switch. In addition, the linearity-enhanced biasing scheme is adopted to the PMOS transistor as a conventional negative biasing method of the NMOS transistor. This prevents the degradation of the power handling capability in adopting the PMOS transistor to the antenna switch. In the measurement, the proposed single-stack SPDT antenna switch shows an insertion loss of less than 0.6 dB and an isolation of greater than 38 dB from 100 MHz to 1 GHz with an input and output return loss of greater than 25 dB. Concerning for H2 and third-order harmonic (H3), it shows H2 of -65 dBm and H3 of -90 dBm at 150 MHz when a single-tone RF signal with a power of +5 dBm is applied. Compared to the conventional NMOS-based antenna switch, the proposed CMOS-based antenna switch improves HD2 by approximately 8 dB, 7 dB, and 1 dB at 150 MHz, 400 MHz, and 1 GHz, respectively, while maintaining the comparable insertion loss, isolation, and third-order harmonic distortion (HD3).

Double-Side Cooled SiC MOSFET Power Modules With Sintered-Silver Interposers for a 100-kW/L Traction Inverter

Low-profile double-side cooled power modules are emerging in electric-drive inverters to achieve higher power density and efficiency. However, the rigid interconnection between the devices and two substrates raises the thermo-mechanical reliability issue of double-side cooled modules. In the prior work, we proposed the use of porous sintered-silver (Ag) interposers in the double-side cooled modules, resulting in reduced thermo-mechanical stresses, better heat extraction, and lower package parasitic inductance. To further improve the power density and demonstrate the benefits of using the sintered-Ag interposers, we proposed a revised half-bridge module layout that further reduced the power-loop parasitic inductance by 23%, improved the power handling capability by 44%, and retained a similar thermo-mechanical stress reduction. After carefully selecting high-temperature packaging materials, we fabricated the improved module layout with a reasonably high yield due to the deformable feature of sintered-Ag interposers. The thermal testing showed that the module had excellent power handling capability with a junction-to-fluid thermal resistance of 0.76°C/W due to the double-sided cooling. The electrical characterization at elevated temperatures up to 250°C and the switching characterization validated the functionalities of the power modules with SiC devices aimed for high-temperature and fast switching. Six of the double-side cooled power modules with sintered-Ag interposers were assembled into a segmented traction inverter, demonstrating a high power density of over 100 kW/L.

On the Design of Regularized Explicit Predictive Controllers From Input–Output Data

On the wave of recent advances in data-driven predictive control, we present an explicit controller that can be constructed from a batch of input/output data only. The proposed explicit law is built upon a regularized data-driven control problem, so as to guarantee the uniqueness of the explicit predictive controller and to endow it with noise handling capabilities. The effectiveness of the retrieved explicit law and the repercussions of regularization on noise handling are analyzed on a benchmark simulation example.

Mechanically Driven Solidly Mounted Resonator‐Based Nanoelectromechanical Systems Magnetoelectric Antennas

The miniaturization of antennas has been a significant challenge in the field of electronics and telecommunications. In recent years, mechanically driven thin‐film bulk acoustic resonator (FBAR) magnetoelectric (ME) antennas have emerged as a promising solution, demonstrating superior miniaturization capabilities compared to conventional state‐of‐the‐art compact antennas. While nanoelectromechanical systems (NEMS) FBAR ME antennas exhibit high miniaturization potential, their suspended thin‐film heterostructures render them fragile and exhibit low power handling capabilities. The findings demonstrate that solidly mounted resonator (SMR) NEMS ME antennas on a Bragg acoustic resonant reflector offer a compelling solution. With a circular resonating disk of 200 μm diameter operating at 1.75 GHz, these SMR‐based antennas display a high antenna gain of −18.8 dBi and a 1 dB compression point (P1dB) of 30.4 dBm. Compared to same‐size FBAR ME antennas with a free‐standing membrane, SMR‐based antennas exhibit significantly higher structural stability and 23.3 dB stronger power handling capability, in addition to easier fabrication processes. The compatibility of the simple fabrication processes with complementary metal–oxide–semiconductor technology, along with the dramatic miniaturization, high power handling, robust mechanical properties, and much higher antenna radiation gain, make these SMR‐based ME antennas a promising candidate for future antenna systems.

Air Cargo Carrier Selection: The Case of Turkey

In this study, 5 companies operating in Turkey and carrying out the most air cargo shipments in 2021 (Turkish Cargo, MNG Airlines and Transportation, ACT Air Cargo, ULS Airlines Cargo Transportation and Sunexpress Cargo Transportation.) were investigated The aim is to evaluate and analyze them according to different criteria. These are 12 different criteria: Breadth of the network, the productivity of employees, adequacy of equipments, flexibility, undamaged delivery, image, cost, customer information systems, handling customer requests and complaints, special cargo handling capabilities, flight frequency, and punctuality. In the research design, using the Multi Criteria Decision Making (MCDM) method, the opinions of 9 different experienced and active experts in the sector were used to evaluate the relevant criteria. A scale of 1 to 5 was used in the evaluation of the companies, with a value of 5 representing the maximum benefit for this criterion. As a result of the research, it was found that the most significant criteria in selecting air cargo companies are undamaged delivery, costs, and on-time delivery. In addition, (1) image, (2) flexibility, and (3) special cargo handling capabilities are among the results of the research, which are the least significant criteria. Another important result of this research is that Turkish Cargo is ranked first and MNG Airlines and Transportation is ranked second.

Optimizing the Functional Properties of Starch-Based Biodegradable Films.

A definitive screening design was used in order to evaluate the effects of starch, glycerol and montmorillonite (MMT) concentrations, as well as the drying temperature, drying tray type and starch species, on packaging film's functional properties. Optimization showed that in order to obtain films with the minimum possible thickness, the maximum elongation at break, the maximum tensile strength, as well as reduced water vapor permeability and low opacity, a combination of factors should be used as follows: 5.5% wt starch concentration, 30% wt glycerol concentration on a dry starch basis, 10.5% wt MMT concentration on a dry starch basis, 45 °C drying temperature, chickpea as the starch species and plexiglass as the drying tray type. Based on these results, starch films were prepared, and fresh minced meat was stored in them for 3 days. It was shown that the incorporation of MMT at 10.5% wt on a dry starch basis in the packaging films led to a decreased mesophilic and psychrotrophic bacteria growth factor compared to commercial packaging. When assessed for their biodegradability, the starch films disintegrated after 10 days of thermophilic incubation under simulated composting conditions. Finally, to prove their handling capability during industrial production, the starch films were rewound in a paper cylinder using an industrial-scale rewinding machine.

Robust femtosecond-written chirped and tilted fiber Bragg gratings for Raman filtering in multi-kW fiber lasers.

We present a robust chirped and tilted fiber Bragg grating (CTFBG) in a large-mode-area double-cladding fiber (LMA-DCF) written by a femtosecond (fs) laser. By implementing the fs-CTFBG into the output end of a high-power fiber laser for Raman filtering, a power handling capability of 4 kW is achieved with a Raman filtering ratio of ∼13 dB. To the best of our knowledge, this is the maximum handling power of a CTFBG for Raman filtering. The signal loss of the fs-CTFBG is 0.03 dB, which has little effect on the output laser beam quality. The air-cooled fs-CTFBG has a minimum temperature slope of 7.8°C/kW due to a self-annealing effect. This work proves the excellent performance of the fs-CTFBG, promoting the development of high-power CTFBGs.