Application Of System Research Articles

Foreign Experience in Ensuring the Security of the Penitentiary System and the Possibility of its Use in Future Practice

The article discusses the foreign experience of penitentiary systems in countries such as Norway, the USA, New Zealand, Australia, Spain, Portugal, Belarus, Great Britain, Canada, Germany and the possibility of its application in the modern penitentiary system of Georgia. Taking into account the analysis of international legal documents, the author of the article positively evaluates the penal practice of foreign countries and formulates a recommendation about its perception in Georgia. The material of the scientific article can later be used in the practical activities of the penitentiary institutions of the penitentiary system, as well as in the educational organizations of the Penitentiary Service of Georgia. Keywords: penitentiary security, penitentiary system, public safety, convicts, differentiation of convicts, correctional institutions.

Case Studies of Battery Energy Storage System Applications in the Brazilian Transmission System

This paper presents the preliminary results of studies aiming to use a battery energy storage system (BESS) in the Brazilian transmission system. The main objective of the BESS is to solve congestion problems caused mainly by the large increase in variable renewable generation in certain system areas. The studies were conducted based on actual forecasted system scenarios using a full representation of the electric grid available from the Brazilian system operator data base. In this work, only the steady-state modeling was considered as this may be the first stage in the assessment of a new technology. A qualitative economic comparison of the BESS application with other possible solutions to the congestion problems is also included.

LightAuth: A Lightweight Sensor Nodes Authentication Framework for Smart Health System

ABSTRACTCounterfeit medical devices pose a threat to patient safety, necessitating a secure device authentication system for medical applications. Resource‐constrained sensory nodes are vulnerable to hacking, prompting the need for robust security measures. Token‐based authentication schemes, such as one‐time passwords (OTPs), smart cards, key fobs, and mobile authentication apps, along with certificate‐based authentication methods, such as client and code‐signing, employ cryptographic frameworks like elliptical curve cryptography (ECC) and physical unclonable functions (PUF). However, these methods face challenges, including block sequence issues and susceptibility to side‐channel attacks. To address these issues, we propose a framework for mutual authentication using private Ethereum. This framework integrates private Ethereum and cryptographic techniques for encrypting and decrypting data using mathematical algorithms to overcome block sequence issues and side‐channel attacks. Similarly, fog nodes are utilised to enhance local computing, storage, and networking capabilities for sensors. The framework is evaluated using metrics such as communication costs, execution costs, and computation costs based on Ethereum gas consumption. The performance of the LightAuth framework is compared with that of the Smart Contracts Against Counterfeit IoMT (SCACIoMT) framework, designed for Internet of Medical Things (IoMT) devices. The effectiveness of LightAuth is verified through formal security analysis using BAN logic.

Multi-Agent Locally Trained Progressive Instance Selected Assisted Federated Learning Architecture for Intrusion Detection in Industrial-IoT

In this work the focus is made on designing and developing a robust federated learning model (FLM) and architecture for multi-type network intrusion detection system (MT-NIDS) for IIoT applications. Unlike traditional intrusion detection systems, where the key focus is made on detecting and classifying single type of intrusion or attack condition, this research targets to perform multi-type network intrusion detection. This as a result can contribute a fit-to-all NIDS solution for IIoT environment.

Iodine Boosted Fluoro-Organic Borate Electrolytes Enabling Fluent Ion-conductive Solid Electrolyte Interphase for High-Performance Magnesium Metal Batteries.

Rechargeable magnesium batteries are regarded as a promising multi-valent battery system for low-cost and sustainable energy storage applications. Boron-based magnesium salts with terminal substituent fluorinated anions (Mg[B(ORF)4]2, RF = fluorinated alkyl) have exhibited impressive electrochemical stability. Nevertheless, their deployment is hindered by the complicated synthesis routes and the surface passivation of Mganode. Herein, we report the design of an advanced electrolyte formulation comprised of B(HFIP)3and I2in 1,2-dimethoxyethane (DME), which eventually convert into a Mg[B(HFIP)4]2/DME-MgI2 electrolyte system upon interacting with Mg anode. The Mg anode reacts with I2 and the electron-accepting B(HFIP)3, leading to the in-situ formation of a solid-electrolyte interphase layer composed of MgF2 and MgI2 species that can facilitate fast and stable Mg plating/stripping. Compared with the pristine Mg[B(HFIP)4]2/DME electrolyte, the Mg[B(HFIP)4]2/DME-MgI2 electrolyte exhibited superior electrochemical performance including an ultra-low overpotential (~80 mV), high Coulombic efficiency and a long-cycling period over 1500 h. In result, the rechargeable magnesium batteries with Mg[B(HFIP)4]2/DME-MgI2 electrolyte and Mo6S8 cathode show outstanding compatibility, rapid kinetics, and stable cyclability for over 1200 cycles, surpassing all previously reported boron-based electrolytes. This work introduces a promising halogen-enhancement strategy for boron-based Mg-ion electrolytes and is pivotal for the advancement and optimization of multi-valent secondary batteries.

Strain Engineered Semiconductor Nanomembranes for Photonic and Optoelectronic Applications

AbstractWhen semiconductor crystals are made into the form of thin sheets, i.e., nanomembranes, their properties and behaviors may be remarkably different from their bulk counterparts. A plethora of fascinating science and important applications arise consequently, some of which are investigated in recent years, and there are still a lot more to be discovered in the future. Nanomembranes (NMs) provide a good platform for strain engineering and offer tremendous research opportunities in photonics and optoelectronics applications. Strain alters energy band line up of a material furthermore influencing its carrier mobility which impacts a wide range of applications. In this article, the strain‐engineered NMs are reviewed using semiconductor materials as a model system for photonics and optoelectronics applications. While many fundamental aspects of NMs are discussed and outlined different methods for strain engineering of NM, the use of semiconductor NMs for photonics and optoelectronics applications is the locus of the present review article.

Analysis of Factors Influencing User Satisfaction with The Benefits of The Information System In The SIPD-SIKD Application of The Special Capital Region of Jakarta

The use of the Regional Government Information System (SIPD) is increasingly important to optimize the performance of local governments, one of which is in regional financial management which is carried out electronically with the implementation of the Regional Financial Information System (SIKD). The success of the implementation of SIPD-SIKD does not only depend on the technical aspect, but also on the level of acceptance and user satisfaction with the benefits of the information system, as measured by the level of user satisfaction and the intensity of using the system. This study aims to analyze the factors that affect user satisfaction with the benefits of information systems. This study integrates the UTAUT and Delone-McLean models, both models describe the relationship between variables and take into account user behavior when using information systems, as well as measure the success of information systems through user satisfaction. This study uses a quantitative approach with data collection techniques using questionnaires distributed online as many as 350 respondents. The analysis technique in this study uses SEM-PLS using SmartPLS software. Based on the results of data processing, it shows that performance expectations, business expectations, facilitation conditions, information quality, and system quality have an influence on user satisfaction. Furthermore, user satisfaction affects the benefits of information systems both at the individual and organizational levels.

Thermally Deposited Pt/InSe/Nb2O5/Ag Stacked Layers Designed as Negative Capacitance Sources and Antennas for 5 G/6 G Networks

Herein, Pt/InSe/Nb2O5/Ag (ISNO) stacked layers are designed as multichannel 5 G/6 G network antennas and negative capacitance (NC) sources. The devices are fabricated using thermal deposition technique to coat Pt/InSe thin films with transparent Nb2O5 dielectric windows. While Pt thin films induce the crystallinity of InSe, the Nb2O5 layer remains amorphous. The impedance spectroscopy studies show that the Pt/InSe/Ag (IS) and (ISNO) antenna channels exhibit resonance–antiresonance peaks at driving frequencies of ≈0.4 and ≈1.1 GHz, respectively. Both the IS and ISNO antenna channels exhibit the NC effect in a wide range of frequency domain. In addition, ISNO antennas show signal transmission above 1.70 GHz with a return loss value of 28 dB and voltage standing wave ratios of 1.20. The range of frequencies over which the antenna performs well (bandwidth) extends from 1.54 to 1.80 GHz. Practical tests of one‐port and two‐port reflection/transmission using a network analyzer operative in the frequency domain of 0.01–6.0 GHz highlight the system's differing isolation and coupling characteristics at 2.43 and 6.0 GHz, respectively. The high levels of isolation at 6.0 GHz assure the suitability of the system for applications requiring minimal reverse transmission and high signal integrity. The NC effect, wide bandwidth, and high signal isolation characteristics are preferable in electronics and 5 G/6 G networks.

Cu(II) removal from aqueous solution in trickle tray adsorber using non-woven fabric modified via radiation-assisted functionalization

An investigation into Cu(II) adsorption from contaminated water utilizing a trickle tray column that has been upscaled from batch-scale adsorption was performed to understand the efficacy of the adsorbent when used in a continuous system—which is more common in actual use in an industry. The size of the functionalized fabric adsorbent selected in a pilot-scale is about four times larger than a batch-scale. The continuous Cu(II) adsorption was analyzed using three parameters: initial Cu(II) concentration in solution; inlet solution flow rate and number of adsorbent sheets in the column to estimate the adsorption process’s breakthrough curve results. The breakthrough curve results were fitted with three mathematical models by Thomas, Yoon-Nelson and Adams-Bohart to comprehend the mechanisms of the adsorption process. All three mathematical models can be used to reliably describe the continuous adsorption process using diverse conditions applied in this study. Overall results showed that PBMEP-g-PE/PP adsorbent using the trickle tray column demonstrated as high as 97% efficiency of Cu(II) adsorption during the first 6 h. Three-cycle reutilization of the adsorbent through a process of adsorption-desorption revealed that Cu(II) removal efficiency surpassed 70% after 6 h of each cycle, confirming the suitability of this system for practical application.

Simulation of Space Charge Effects in Fourier Transform Quadrupole Ion Traps (FT-QITs).

We present ion dynamics simulations regarding the effect of space charge on the performance of Fourier transform quadrupole ion traps (FT-QITs) with special attention to signal stability, mass resolving power, and sensitivity. Ion trajectory simulations within an idealized QIT geometry are performed by applying a dedicated application (QITSim) using an in-house developed open simulation framework (IDSimF). Image current detection transients are generated by the application and are subsequently transformed into frequency spectra of ion secular motion. Such frequency spectra are the basis for the calculation of mass spectra in FT-QIT instruments. The simulation results are used to assess the extent of space charge induced effects regarding the analytical performance of FT-QIT systems. The simulation results for two Cl+ and seven Xe+ isotope ions exhibit diverse space charge induced phenomena. Most prominently, complete isotope signal fusion, quantitative individual signal suppression, and severe signal distortions are observed even at low absolute numbers of trapped ions. Furthermore, significant shifts of the secular oscillation frequencies occur, even when the signal shape appears to be mostly unaffected and when the frequency separation for trapped ions with different masses is large. This significantly limits the applicability of FT-QIT systems for high resolution mass spectrometry. An increase of the RF amplitude of the trapping field as well as increasing the extent of ion excitation partly mitigate these adverse space charge effects; nevertheless, the usable operational range of the simulated FT-QIT system for analytical applications remains rather narrow.

Modeling of Skeletal Development and Diseases Using Human Pluripotent Stem Cells.

Human skeletal elements are formed from distinct origins at distinct positions of the embryo. For example, the neural crest produces the facial bones, the paraxial mesoderm produces the axial skeleton, and the lateral plate mesoderm produces the appendicular skeleton. During skeletal development, different combinations of signaling pathways are coordinated from distinct origins during the sequential developmental stages. Models for human skeletal development have been established using human pluripotent stem cells (hPSCs) and by exploiting our understanding of skeletal development. Stepwise protocols for generating skeletal cells from different origins have been designed to mimic developmental trails. Recently, organoid methods have allowed the multicellular organization of skeletal cell types to recapitulate complicated skeletal development and metabolism. Similarly, several genetic diseases of the skeleton have been modeled using patient-derived induced pluripotent stem cells and genome-editing technologies. Model-based drug screening is a powerful tool for identifying drug candidates. This review briefly summarizes our current understanding of the embryonic development of skeletal tissues and introduces the current state-of-the-art hPSC methods for recapitulating skeletal development, metabolism, and diseases. We also discuss the current limitations and future perspectives for applications of the hPSC-based modeling system in precision medicine in this research field.

Human-Centered Robotic System for Agricultural Applications: Design, Development, and Field Evaluation

This paper introduce advancements in agricultural robotics in response to the increasing demand for automation in agriculture. Our research aims to develop humancentered agricultural robotic systems designed to enhance efficiency, sustainability, and user experience across diverse farming environments. We focus on essential applications where human labor and experience significantly impact performance, addressing four primary robotic systems, i.e., harvesting robots, intelligent spraying robots, autonomous driving robots for greenhouse operations, and multirobot systems, as a method to expand functionality and improve performance. Each system is designed to operate in unstructured agricultural environments, adapting to specific needs. The harvesting robots address the laborintensive demands of crop collection, while intelligent spraying robots improve precision in pesticide application. Autonomous driving robots ensure reliable navigation within controlled environments, and multirobot systems enhance operational efficiency through optimized collaboration. Through these contributions, this study offers insights into the future of agricultural robotics, emphasizing the transformative potential of integrated, experience-driven intelligent solutions that complement and support human labor in digital agriculture.

A supramolecular approach towards the photorelease of encapsulated caged acids in water: 7-diethylaminothio-4-coumarinyl molecules as triggers.

Herein, we establish the release of aliphatic acids in water upon excitation of 7-diethylaminothio-4-coumarinyl derivatives encapsulated within the organic host octa acid (OA). The 7-diethylaminothio-4-coumarinyl skeleton, employed here as the trigger, photoreleases caged molecules from the excited triplet state, in contrast to its carbonyl analogue, where the same reaction is known to occur from the excited singlet state. Encapsulation in OA solubilizes molecules in water that are otherwise water-insoluble, and retains the used trigger within itself following the release of the aliphatic acid. Such supramolecular characteristics usher in new features to the photorelease methodology. The thiocarbonyl chromophore extends the absorption of coumarinyl trigger to visible range while enhancing the intersystem crossing (ISC) to the triplet state, making it the reactive state. Despite the non-polar environment within the OA capsules the photocleavage occurs in a heterolytic fashion to release the conjugate base and the used trigger as triplet carbocation in an adiabatic process. Interestingly, the triplet carbocation crosses to the ground singlet surface (closed shell singlet carbocation) with the help of water molecules, possibly aided by C = S chromophore. Utilizing the known excited state dynamics of related thiocoumarinyl and coumarinyl systems, we have identified a few of the important mechanistic features of the photorelease process of 7-diethylaminothio-4-coumarinyl derivatives. Ultrafast excited state dynamic studies and quantum chemical calculations planned should help us better understand the photorelease process so as to effectively exploit the proposed system for potential applications.

Development of a material selection decision support system for an automotive application

This study presents the development of a material selection decision support system for an automotive rooftop tent. The system uses five parameters of material cost, formability, corrosion resistance, tensile strength and hardness to optimize material choice from a list of aluminium alloy options. This was done before production via the deep drawing process can commence. The parameters were quantified using the average market prices for each alloy, product requirements obtained from the case study and the performance data that was obtained from the uniaxial tensile and hardness tests. These inputs were combined with the developed material selection framework and then programmed into a web-based decision support system for automated, data-driven material selection. The output presents the recommendation for the optimum material that balances cost-effectiveness and performance. The decision support system was successfully used to select the optimum alloy for the rooftop tent. Results show that AA1050 is the optimum material, providing weight reduction at the minimum achievable cost without compromising the product requirements for the rooftop tent. The decision support system is also scalable, and this allows it to be used with larger datasets for different products and processes in the future.

A Well‐Advanced High‐Throughput Test System for Electrocatalytic Screening Applications Under Industrial Relevant Conditions – A Perspective to Accelerate Electrolysis Research and Development

ABSTRACTElectrolysis is a dynamic research area in which both mature and new promising processes, such as alkaline water electrolysis and electrochemical CO2 reduction, are under enormous development pressure due to their high relevance for the energy sector. High‐throughput (HT) technologies are efficient screening platforms that can accelerate research activities and significantly shorten development times. Over the past 25 years, various HT platforms have found their way into electrochemical research. These typically have one or more major disadvantages: they are characterized by abstract experimental conditions, designed for a specific application or process, or generate insufficiently comparable data. In this publication, we present a newly developed HT test system that enables the parallel operation of 16 electrochemical bench‐scale flow cells under industry‐relevant test conditions. The specially developed modular flow cell can be operated variably in the fully automated system and allows research into the most common applications in electrochemistry for many different processes with a focus on all relevant variants of water electrolysis and electrochemical CO2 reduction. Both the HT system and the developed flow cell are designed to accelerate the generation of reliably reproducible data with high comparability in order to strengthen scientific exchange. The fully automated process control, online analysis and programmable feedback loops of the HT test system provide great potential for the design of experiment strategies. The implementation of Design of Experiment strategies will maximize the testing efficiency of this innovative research system.

Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies

Systems for graph processing are a key enabler for insights from large-scale graphs that are critical to many new advanced technologies such as Artificial Intelligence, Internet of Things, and blockchain. In this study, we benchmark another two widely utilized graph processing systems, Apache Spark GraphX and Apache Fink, concerning the key performance criterion by means of response time, scalability, and computational complexity. We demonstrate our results which show the capability of each system for real-world graph applications, and hence, providing a quantitative understanding to select the system for our purpose. GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. These performance characteristics emphasize how the capabilities of graph processing systems can match the requirements for the performance of different emerging technology applications. Our findings ultimately inform practitioners about system efficiencies and limitations, but also the recent advances in hardware accelerators and algorithmic improvements aimed at shaping the new graph processing frontier in diverse technology domains.

Optimization of Cannabinoid Production in Hemp Through Methyl Jasmonate Application in a Vertical Farming System

Optimization of Cannabinoid Production in Hemp Through Methyl Jasmonate Application in a Vertical Farming System

The cosmic ray muons tomography system with wavelength shifting fiber and plastic scintillator plane and vertical borehole detectors and improved 3d image reconstruction algorithm: a simulation study

In this paper, a cosmic ray muon plane detector tomography system based on wavelength shifting fiber and scintillation is built in GEANT4, and the relevant experimental platform is established, then the image reconstruction experiment based on the muon scattering imaging principle is carried out. Finally, based on the research above, a vertical drilling muon detector system is proposed and the simulation studies is completed. The position resolution of the fiber-scintillation detector system is studied in detail, and the chamber position resolution of parallel fiber-optic grid with different parameters is described and compared. Based on the experimental data of the plane detector system, an image reconstruction algorithm and correction method based on muon scattering are proposed, and some engineering applications of the vertical borehole detector system are simulated. The general guiding theory applicable to fiber-scintillation detectors has not been established and detailed simulation studies are required through simulation programs. By using GEANT4, the photon-photon yield of optical light in WLS fiber can be extracted and compared with the existing experiments. The simulation results are in good agreement with the experimental results, indicating that the detector system modeled in the simulation study has high reliability and practical value.

Soft, precision engineered porous, hydrogel scaffolds mechanically tailored toward applications in the central nervous system

Diseases and traumatic injuries to the central nervous system (CNS) demand the development of new biomaterials to improve healing and treatment options. Matching material mechanical properties to specific tissues and optimizing material porous structures are central goals for improving biomaterials. However, biomaterials with both precision-controlled porous structures and brain-matched mechanical properties (low modulus) are still lacking. In this study, we developed soft hydrogel scaffolds with mechanical properties similar to that of CNS tissues, and a uniform 40 µm porous structure—40 µm pores have been shown to be optimal for healing in many tissues. The two characteristics were achieved by a new fabrication process combining phase separation and sphere templating. The resulting scaffolds are non-cytotoxic according to the ISO 10993-5 standard. In addition, the three-dimensional culture of microglial cells within the scaffolds demonstrates cell attachment and maintenance of a rounded, quiescent morphology, potentially due to spatial confinement. These results justify further in vivo studies and suggest broad potential in CNS applications, such as brain-computer interfaces, neural regeneration, and basic neurobiology. Subject classification codes: Neural Interfaces, soft hydrogel, synthetic biomaterials

A Blockchain assisted fog computing for secure distributed storage system for IoT Applications

A Blockchain assisted fog computing for secure distributed storage system for IoT Applications