Operation Methods Research Articles

Ray Tracing Meets Terahertz: Challenges and Opportunities

It is very likely that the terahertz (THz) spectrum will be used for the operation of the upcoming 6th-generation (6G) wireless communication systems. This article presents a study for the application of ray tracing (RT) for THz channel modeling. Because of the extremely short wavelengths of THz signals, we argue that signal propagation in the THz spectrum can be precisely modeled by employing RT techniques and thus accurate channel models can be obtained in an efficient manner. We first review recent research and standardization activities related with RT-assisted channel modeling which mainly deal with millimeter-wave (mmWave) applications and to a much lesser extent have been applied the THz spectrum. Then, we present the basic THz wave propagation characteristics, including reflection, scattering, penetration, shadowing as well as signal absorption by atmospheric molecules and tiny particles under different weather conditions. The methodologies for the appropriate construction of target scenarios are presented as well as efficient computational methods for the effective RT operation. Finally, various research and development (R&D) challenges related to RT-based channels for future THz communication systems are identified and possible solutions are highlighted.

Dependability Evaluation of a Smart Poultry House: Addressing Availability Issues Through the Edge, Fog, and Cloud Computing

Internet of Things (IoT) applications equip rural producers with decision support tools and automated solutions that boost agribusiness productivity, quality, and profit. However, most poultry farmers still use conventional methods of operation in which human workers carry out all routines for monitoring and controlling their farms at the expense of greater productivity. One of these human activities is manual weighing, which can be replaced by non-intrusive methods such as computational vision applications that estimate live poultry's weight using video cameras. Since Internet of Things (IoT) devices may have low computing power limiting the ability to process the data locally, they can transfer it to a fog or cloud data center, where they are processed. This paper aims to conduct a dependability study of a poultry house automated with a computer vision-based system for estimating poultry weight considering hierarchical models (e.g., Markov chain, Reliability Block Diagram, and closed-form equation) to represent the whole system and obtain steady-state availability and annual downtime. In addition, our purpose is to consider and compare different architectural solutions, such as edge and fog computing-based solutions. The proposed solution verified that a cloud-based application with no redundancy has a downtime of 34.14% and 9.176% hours when considering a hot-standby redundancy strategy in the office node of a cloud solution.

Digital Twin Learning Ecosystem: A cyber–physical framework to integrate human-machine knowledge in traditional manufacturing

As Industry 4.0 enablers, digital twins of manufacturing systems have led to multiple interaction levels among processes, systems, and workers across the factory. However, open issues still exist when addressing cyber–physical convergence in traditional manufacturing small and medium-sized enterprises. The problem for both traditional operators and the existing infrastructure is how to adapt knowledge to the increasing business needs of manufacturing plants that demand high efficiency, while reducing production costs. In this paper, a framework that implements the novel concept of Digital Twin Learning Ecosystem in traditional manufacturing is presented. The objective is to facilitate the integration of human-machine knowledge in different industrial cyber–physical contexts and eliminate existing technological and workforce barriers. This adaptive approach is particularly important in meeting the requirements to help small and medium-sized enterprises build their own interconnected Digital Twin Learning Ecosystem. The contribution of this work lies in a single digital twin learning framework for different traditional manufacturing scenarios that can work from scratch using a light infrastructure, reusing the knowledge and common condition-based methods well-known by skilled workers to rapidly and flexibly integrate existing legacy resources in a non-intrusive manner. The solution was tested using real data from a milling machine and a currently operating induction furnace with a maximum power of 12 MW in a foundry plant. In both cases, the proposed solution proved its benefits: first, by providing augmented methods for maintenance operations on the milling machine and second, by improving the power efficiency of the induction furnace by approximately 9 percent.

Progress in study on animal models of trigeminal neuralgia.

Trigeminal neuralgia is a manifestation of orofacial neuropathic pain disorder, always deemed to be an insurmountable peak in the field of pain research and treatment. The pain is recurrent, abrupt in onset and termination similar to an electric shock or described as shooting. A poor quality of life has been attributed to trigeminal neuralgia, as the paroxysms of pain may be triggered by innocuous stimuli on the face or inside the oral cavity, such as talking, washing face, chewing and brushing teeth in daily life. The pathogenesis of trigeminal neuralgia has not been fully elucidated, although the microvascular compression in the trigeminal root entry zone is generally considered to be involved in the emergence and progression of the pain disorder. In addition, orofacial neuropathic pain restricted to one or more divisions of the trigeminal nerve might be secondary to peripheral nerve injury. Based on current hypotheses regarding the potential causes, a variety of animal models have been designed to simulate the pathogenesis of trigeminal neuralgia, including models of compression applied to the trigeminal nerve root or trigeminal ganglion, chronic peripheral nerve injury, peripheral inflammatory pain and center-induced pain. However, it has not yet been possible to determine which model can be perfectly employed to explain the mechanisms. The selection of appropriate animal models is of great significance for the study of trigeminal neuralgia. Therefore, it is necessary to discuss the characteristics of the animal models in terms of animal strains, materials, operation methods and behavior observation, in order to gain insight into the research progress in animal models of trigeminal neuralgia. In the future, animal models that closely resemble the features of human trigeminal neuralgia pathogenesis need to be developed, with the aim of making valuable contributions to the relevant basic and translational medical research.

Risk Factors Assessment of Smart Supply Chain in Intelligent Manufacturing Services Using DEMATEL Method With LINGUISTIC q-ROF Information

With the rapid development of technological informatization, competition among enterprises is gradually transitioning from being "production-centered" to being "customer-centric," making service-oriented enterprises increasingly important. In addition to this, as global manufacturing advances in the process of intelligent manufacturing (IM), there is growing attention on the integration of manufacturing and the service industry, which has garnered the interest of numerous experts and scholars in the field of intelligent manufacturing services (IMS). This article combines intelligent manufacturing enterprises, intelligent service nodes, and consumers. Based on the background of intelligent manufacturing services, it collected risk factors within the smart supply chain (SSC) that connect different service nodes. These factors were evaluated by experts using a proposed linguistic q-rung orthopair fuzzy weighted averaging (Lq-ROFWA) operator in combination with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method for aggregation operations. Finally, we obtain the conclusions that the most influential factor affecting other risk factors is the inadequate identification of core customer needs; and the most important risk factor for smart supply chains oriented to intelligent manufacturing services is the leakage of customer information. After analyzing the relevant data, we will provide some theoretical and managerial implications for IM enterprises.

Comprehensive Utilisation and Performance Optimisation of Agro-electricity and Agro-photovoltaic Complementary Systems in Agricultural Production

Agroelectricity agro-photovoltaic (APV) complementary systems are increasingly attracting attention in the field of agricultural production as a way of integrating and utilising renewable energy resources. The aim of this study is to investigate the integrated utilisation and performance optimisation of agro-electricity agro-photovoltaic (AEPV) systems in agricultural production in order to improve the efficiency of agricultural production, conserve energy resources, and protect the environment. The integrated utilisation section explores the application of agroelectricity agro-photovoltaic systems in different types of agricultural production, emphasising the importance of integrated energy utilisation strategies to improve energy and economic efficiency. The Performance Optimisation Methods and Strategies section describes optimisation methods for system operation, equipment performance, energy dispatch and storage to improve system performance and reliability. The section on sustainability and environmental impacts emphasises the environmental friendliness and sustainability of agropower agro-photovoltaic systems, and discusses related environmental protection strategies and social responsibility. The research and application of agro-power agricultural and photovoltaic complementary systems are expected to bring more sustainable and cost-effective solutions to agricultural production.

Novel Operation Mechanism and Multifunctional Applications of Bubble Microrobots.

Microrobots have emerged as powerful tools for manipulating particles, cells, and assembling biological tissue structures at the microscale. However, achieving precise and flexible operation of arbitrary-shaped microstructures in 3D space remains a challenge. In this study, three novel operation methods based on bubble microrobots are proposed to enable delicate and multifunctional manipulation of various microstructures. These methods include 3D turnover, fixed-point rotation, and 3D ejection. By harnessing the combined principles of the effect of the heat flow field and surface tension of an optothermally generated bubble, the bubble microrobot can perform tasks such as flipping an SIA humanoid structure, rotating a bird-like structure, and launching a hollow rocket-like structure. The proposed multi-mode operation of bubble microrobots enables diverse attitude adjustments of microstructures with different sizes and shapes in both 2D and 3D spaces. As a demonstration, a biological microenvironment of brain glioblastoma is constructed by the bubble microrobot. The simplicity, versatility, and flexibility of this proposed method hold great promise for applications in micromanipulation, assembly, and tissue engineering.

Longitudinal Coupling Synthesis in Superconducting Qubits

Longitudinal coupling, which generates entanglement without energy exchange, has extensive applications in quantum computing and quantum simulation. However, achieving available direct and flexible longitudinal couplings between highly coherent superconducting qubits is challenging. In this study, a method is developed to achieve direct and flexible longitudinal couplings between superconducting qubits, including the direct longitudinal coupling between capacitively shunted flux qubits (C‐shunt flux qubits) and that between transmon qubits. Herein, first, a variant of the prototype C‐shunt flux qubit, the concentric C‐shunt flux qubit, is introduced. It is demonstrated that the large mutual inductance between concentric C‐shunt flux qubits produces a longitudinal coupling strength up to 21 MHz. It is also demonstrated that the method can be used to realize a strong longitudinal coupling between two transmon qubits. In the findings, it is demonstrated that it is possible to achieve a flexible and efficient direct longitudinal coupling between superconducting qubits, and open up new possibilities for the development of quantum gate operation methods as well as quantum simulation methods.

Optimal relay performance using advanced fault diagnostic techniques

This paper describes application of Artificial Intelligence (AI) methods in the diagnostic operation of the protective relays in power system with a particular emphasis on neuro-fuzzy method, as a viable enhancement to the existing classical protection technique in use on the Nigeria’s national grid. The proposed method is simulated to showcase its advantages over the existing methods. It will not replace the latter but rather serves as a means of improving its reliability as a protection scheme. This work can also be applied to any other complex power system spread over a wide geographical area like Nigeria’s.

Robot-assisted percutaneous vertebroplasty for osteoporotic vertebral compression fracture treatment and risk factor screening for postoperative refracture.

Osteoporotic vertebral compression fracture (OVCF) is a serious complication of osteoporosis, and percutaneous vertebroplasty (PVP) is a major therapeutic method for OVCF. This study aimed to evaluate the clinical efficacy and postoperative complications of robot-assisted targeted PVP for the treatment of OVCF. The data from 202 OVCF patients were analyzed in this study, including 72 cases received traditional PVP (PVP group), 68 cases received robot-assisted PVP (R-PVP group), and 62 cases underwent robot-assisted PVP combined with targeted plugging (R-PVP + TP group). The fluoroscopic exposure conditions, operative duration, lengths of stay, postoperative bone cement leakage, refracture, Visual Analog Scale (VAS) score, and Oswestry Disability Index (ODI) score were obtained and compared between the three groups. The Kaplan-Meier method and logistic regression model were adopted to screen the risk factors related with postoperative refracture. R-PVP and R-PVP + TP group had significantly reduced fluoroscopic frequency and radiation dose, and reduced cement leakage compared with PVP group. R-PVP + TP not only showed more obvious advantages in these aspects, but also had a lower probability of postoperative refracture. In addition, BMD, fracture vertebral distribution, cement leakage, and surgery methods were independent related with refracture. All the results demonstrated robot assistance could improve the application of PVP in the treatment of OVCF, and robot-assisted PVP combined with targeted plugging showed significantly reduced fluoroscopic exposure, bone cement leakage, and rate of postoperative refracture. BMD, fracture vertebral distribution, cement leakage, and operation methods were identified as four risk factors for the onset of refracture after PVP.

Empirical study on optimization methods of building energy operation for the sustainability of buildings with integrated renewable energy

Owing to the challenges caused by climate change, the spread of green buildings is increasing. Moreover, it is becoming necessary to secure sustainability through the management of new and renewable energy operations. Accordingly, this paper describes the proposal and empirical demonstration of an energy operation optimization method for renewable energy-integrated buildings utilizing photovoltaics (PVs) and energy storage systems (ESSs). The proposed optimization method begins with the calculation of a weather index (WI) based on environmental and climatic data, with particular emphasis on its relevance to PV production. Additionally, we develop the weight-prox algorithm (W-PA) for controlling and optimizing daily building energy operations. The goal of this optimization method is to enhance the performance of three sustainability indicators of green buildings. Simulations are then conducted in a digital transformation environment using real green buildings as targets. The results demonstrate the improved performance of sustainability indicators, including renewable energy efficiency, economic resilience, and eco-friendliness. The output of this study can serve as a set of guidelines that considers the convenience of implementation for building operators. This study is also significant by raising awareness of the need for climate change response and contributing to the use of renewable energy for the sustainability of green buildings.

МЕТОДИКА ОЦЕНКИ РИСКА ПРОЕКТОВ ПО РАЗРАБОТКЕ СИСТЕМ ОБЕСПЕЧЕНИЯ УСТОЙЧИВОСТИ ФУНКЦИОНИРОВАНИЯ ОБЪЕКТОВ С ИСПОЛЬЗОВАНИЕМ НЕЙРОННЫХ СЕТЕЙ

Problem Statement (Relevance).Instrument-making industries need to improve the risk assessment of projects for the design of an automated information system for ensuring the stability of the functioning of a production facility. Objectives.Development of a risk assessment method for the development of an automated information system to ensure the sustainability of the operation of a production facility in order to improve quality.Methods Applied. Methods of operations research.Originality. The method, unlike the existing ones, allows you to assess the risk of a project taking into account the main risk factors inherent in this subject area Result. The method of risk assessment of projects for the creation of AISOU at the stage of the life cycle of the "Design" system is proposed. Practical Relevance.It consists in the ability of users of the EIS OU to more objectively and with less labor to assess the risk of the project of the developed system for assessing the stability of the functioning of the instrument-making facility.

Effectiveness of hybrid workplace and its sustainable impact of determinants of organizational commitment among it companies

Organizational structures have shifted, and new methods of operation have been brought to light, by the recent health crisis. Although many businesses have already started working remotely again, things will not be going back to how they were before the crisis. This is even though remote work seemed to be a vital tool for reducing contamination risks in the workplace. Hybrid work structures, where employees work remotely and in person, will become increasingly common across various IT sectors. Hence, the present study examine the effectiveness of the Hybrid workplace on the organizational commitment in the selected IT companies. The methodology applied here is a stratified sampling method for collecting data from employees working in IT companies around 210 employees participated in the survey. Two factors have been observed for the study one is the effectiveness of the hybrid workplace and the second one is determinants of organizational commitment. The SEM model has been applied to examine the significant impact of is effectiveness of the hybrid workplace on determinants of organizational commitment. Results show there is a significant impact of the effectiveness of the hybrid workplace on determinants of organizational commitment. Thus, it is suggested that for better organizational commitment among employees of IT companies, organizations should develop and propagate a hybrid working model

Deep Retrofitting Study of Government Buildings in the UAE

This report summarizes the findings of a deep retrofitting modelling study of four government buildings across the UAE. Buildings envelope assessment, HVAC, and electrical systems design, installed conditions, maintenance practices and operation methods, and rigorous engineering analysis has been performed for the four buildings to produce calibrated energy models that confirm a good correlation between actual annual energy consumption and advanced simulated energy modeling results. IES-VE software, ASHRAE Guideline 14, and IPMVP were the basis of the energy model calibration based on actual data. Energy retrofitting options were applied to the calibrated energy models of the four government buildings where advanced computational modeling studies have been utilized to analyze different thermal envelope components and external fabric energy efficiency measures in conjunction with the actual HVAC systems. The results have shown that it may be financially challenging to implement a single envelope retrofitting measure on any of the four buildings due to high payback periods. Nevertheless, when conducting an optimization through a holistic building approach targeting the overall envelope enhancements, the financial modeling results provide significantly improved and provide reduced payback periods of the solutions, making them more attractive to investors. Based on the energy modeling results and the cost of the various proposed building envelope solutions provided by Saint-Gobain, the payback period in all cases varies between 15 to 20 years. However, huge savings in terms of carbon emissions are achieved by implementing the deep retrofitting measures, crucial to achieving carbon neutrality within the UAE built environment. Deep retrofitting is a promising segment of the execution roadmap as part of the UAE's decarbonization journey; even though it is capital-intensive upfront, it has a major impact on long-term operational savings. Moreover, it is often more cost-effective than building new and energy-efficient structures from scratch. The findings indicate that deep retrofitting can be a techno-financially viable solution if it is well-planned during major refurbishment or as part of building maintenance. It has significant potential to reduce carbon emissions while also providing a range of benefits such as operational cost savings, improved thermal comfort a feature which has a direct impact on perceived efficiency and productivity at work, indoor air quality, improved asset value, reputational enhancement, and better choice for environmentally-cautious tenants or buyers.

Sustainable Development of Construction Industry in China

The research aims to determine the direction of sustainable development of the construction industry in China and ensure its regular and stable development. A series of data comparisons and methods of the comprehensive analysis showed that the construction industry in China, on the one hand, is a major industry with a huge scale and a significant position on the international market. On the other hand, it is also an industry with low investment in technology, high energy consumption, relatively backward engineering technology, and management. Besides, management and operation methods are relatively traditional and associated with challenges of industry development. The comparison with advanced manufacturing industries and foreign developed countries clarified the shortcomings of China’s construction industry and set the directions for future development. These include (1) active development of green building, (2) promotion of the industrialization process, (3) improvement of the technology application level, and (4) timely improvements of the relevant regulations. China also needs to adjust the industrial form of the construction industry and increase the internationalization level. Based on the methods of data description research and literature review, we identified the conditions for sustainable development of the construction industry and proved the importance of using Integrated Project Delivery [IPD] and BIM (Building Information Modeling) technology in the development of the Chinese construction industry. The research allowed us to understand the important role of technology and organization management in developing the construction industry. When we continue to learn lessons from advanced science and technology, smart organization, and management and implement them in the construction industry, only then it will develop sustainably.

A Systematic Review of Optimal and Practical Methods in Design, Construction, Control, Energy Management and Operation of Smart Greenhouses

A Systematic Review of Optimal and Practical Methods in Design, Construction, Control, Energy Management and Operation of Smart Greenhouses

Innovation and digitalization in construction: new opportunities and challenges for investors and businesses

The article discusses the features of innovation and the possibilities of digitalization, which are extremely important for investors and enterprises. As the authors point out, the construction industry resists technological changes and produces a large amount of useless energy; “green” innovations should compensate for these shortcomings. The emergence of new and powerful digital transformations has provided the construction industry with a lot of opportunities. Along with the industrial revolution and the modernization of technology, all industries are changing their traditional ways of working and managing. However, the developing construction industry is lagging far behind this technological transformation. Traditional methods of design and operation have become obstacles in the process of its transformation. The construction industry has played an indispensable role in the economic growth of countries over the past decades, but now it must keep up with the times. Recently, industrial enterprises have begun to introduce new concepts, such as digital construction and parametric design. However, there is still no assessment of the effectiveness of digital reform at construction enterprises.

DIGITAL BANKING IN THE FINANCIAL SERVICES MARKET OF UKRAINE

In the modern realities of digital transformation, the banking sector faces significant challenges that lead to changes in the methods of traditional banking operations and changes in the way banks interact with clients based on the use of digital technologies. One of the key trends in this area is the development of digital banking as a promising way of banking services. The study aims to study the theoretical and practical aspects of the development of digital banking in Ukraine's financial services market under conditions of digital transformation. The results of the analysis indicated an increase in the amount of attention paid by domestic and foreign scientists to the digital banking development issue. The article examines the theoretical foundations of the implementation of digital technologies in the banking sphere. The concept of digital banking is described. The SWOT analysis determined the main advantages, opportunities, disadvantages, and possible threats associated with using digital banking. The study distinguishes between the concepts of a purely digital bank and a traditional bank that uses digital technologies in its activities. The peculiarities of the activity of digital banks of Ukraine are characterized. The number of digital banking users in the world as a whole and separately in Ukraine was analyzed. The level of development of domestic digital banking was assessed, and the number of cashless transactions using payment cards from 2019 to 2023 was analyzed. The forecast of the number of bank branches and the volume of non-cash payments using payment cards made it possible to determine that in the future the number of bank branches will decrease, and the volume of non-cash transactions will increase. The digital banks of Ukraine are characterized, and the main innovative products of the leading traditional banks are highlighted. Based on the research of the company InMind, it was concluded that the share of digital banking users is growing and the most popular transactions in digital banking among Ukrainians were singled out. An analysis of the ease of use of mobile applications of domestic digital banks was also conducted, among which the most convenient and functional applications were found to be Monobank, Sense Bank, A-Bank, and the least - Raiffeisen Bank and Oschadbank.

МЕТОДЫ ПОВЫШЕНИЯ НАДЕЖНОСТИ И ДОЛГОВЕЧНОСТИ КАБЕЛЬНЫХ ЛИНИЙ В ВЫСОКОВОЛЬТНЫХ ЭНЕРГОСИСТЕМАХ

The article discusses modern methods for increasing the reliability and durability of cable lines in high-voltage power systems. The main factors influencing the performance characteristics of cable lines, including climatic conditions, mechanical loads, electrical overloads and material aging processes, are analyzed. Advanced cable condition monitoring technologies, as well as preventive maintenance methods and innovative solutions aimed at improving the design characteristics of cables are described. In conclusion, recommendations are given for the implementation of the developed methods in practical operation and prospects for their further development.

Design and Implementation of Novel Rotor Side Brushless Controller With Bidirectional Wireless Power Transmission for Doubly-Fed Machine

This paper proposes a novel rotor side brushless controller (RSBC) with bidirectional wireless power transmission (WPT) for a doubly-fed motor (DFM), which can realize the brushless DFM without changing the stator and rotor structures. The WPT-RSBC consists of a grid side converter, a series–series compensated resonant converter, and a rotor side converter. According to the operational characteristics of DFMs, the design requirements of the WPT-RSBC are given in this paper. The systematic selection method for four-quadrant operations of the DFM is introduced, and the variable bus voltage control strategy is proposed to improve its transmission efficiency. The mathematical model and small-signal model of each subsystem in the WPT-RSBC are given, and the stability of the primary and secondary DC bus is analyzed. An experimental platform is implemented to verify the feasibility of the WPT-RSBC. For the prototype, the air-gap length is 1 mm, and the RSBC's transmission efficiency can be up to 92%.