Demand System Research Articles

Applicability of HEC-RAS and Geospatial Tools for Inland Waterways Transportation Corridor: Case Study of Ganga Basin, Bihar, India

Bihar has the largest networks of Rivers and drainage systems and most of them are perineal. Previously, north Bihar had active inland waterways transportation networks but these days the networks are not in use. Due to rapid urbanization and a hike in fuel prices, the transportation cost within the state has risen in the past few years. The demand for cheaper transportation systems is highly needed in these areas for goods transportation. Recently, the inland waterways authority of India has started a new shipping service in River Ganga only but a few more river networks can also be used for these kinds of activities. A study was conducted to find the inland waterways' potential for the development of a state river transportation corridor for North Bihar India. Various mathematical modeling tools such as HEC-RAS, HEC-HMS along with geospatial tools have been used for this study. The result obtained by the study indicates that the six more rivers of the states have the potential for inland waterways transportation along with suitable vessels for transportation. The methodology developed in the study is suitable for the development of waterways transportation corridors at various places. The study also emphasizes selecting the proper places for making the jetties which may be helpful for various activities such as disaster management, industrial fright services, logistic supply, etc.

Using 5G Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System

ABSTRACTThe introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing resource usage, managing mobility, ensuring cost‐efficiency, managing interference, and maximizing spectral efficiency. The fast advancement of artificial intelligence (AI) in several domains yields improved performance in contrast to traditional methods. Hence, including AI in 5G standards would enhance performance by catering to diverse end‐user applications. Initially, we provide an overview of concepts such as Industry 4.0, the 5G standard, and recent developments in the sphere of wireless communications in the future. The goal is to use 5G technology to look at current research problems. We present a new architecture for Industry 4.0 and 5G‐compliant smart healthcare systems. We develop and run the proposed model to investigate the current 5G methods using the Network Simulator (NS2). The results of the simulation show that 5G resource management and interference management approaches already in use face challenges including performance trade‐offs.

Stochastic optimization of a hybrid photovoltaic/fuel cell/parking lot system incorporating cloud model

The interaction and optimization of electric parking lots (EPLs) with hybrid renewable energy to exchange power and improve the system load reliability has been welcomed systems in energy industry, but it is accompanied by challenges such as uncertain parameters, and also implementing the optimal energy management. This paper proposes a novel stochastic optimization framework for a hybrid energy system including photovoltaic resources, hydrogen storage based-fuel cell integrated with an EPL (PV/FC/EPL) aiming for minimization of the total net present cost (TNPC) while ensuring the maximum probability of power shortage (PPSHmax) to meet a commercial load in Tianjin, China using the real meteorological data. A new improved kepler optimization algorithm (IKOA) utilizing the golden sine strategy is applied to optimize system component sizes and EPL charge/discharge. In a deterministic scenario, the optimal system configuration ensures cost-efficiency and reliability for load supply. Also, a new stochastic modeling framework is proposed using the Cloud Model (CM) to evaluate the effect of uncertainties in irradiance, temperature, and system demand on TNPC and PPSH. Deterministic findings reveal enhanced reliability and reduced TNPC through FC and EPL overlap during power shortages, compared to systems lacking EPL. Specifically, TNPC and PPSH are $8,632,643 and 1.45 %, respectively, for PPSHmax = 2 % over 20 years of operation. However, stochastic optimization demonstrates a 10.82 % increase in TNPC and an 8.67 % decrease in PPSH compared to the deterministic model under PPSHmax = 2 %, indicating heightened cost and reduced reliability when uncertainties are considered. This underscores the efficacy of the cloud model-based stochastic approach in addressing uncertainty in hybrid system optimization. Also, it reveals fluctuations in optimal cost and reliability values with changes in cloud droplet distribution around the expected value, emphasizing the significance of stochastic modeling for robust decision-making in hybrid energy systems. Moreover, evaluating the incorporating the penalty for the system's inability to supply the load, changing the storage investment cost, and interest rate variations on the system optimization cleared considerable effect of the system cost and reliability.

Rail Detection Research Status of Multi -Sensing Technology

Traditional rail inspection methods, primarily relying on manual inspection and basic equipment, face significant challenges including low efficiency, poor accuracy, and susceptibility to human error. This paper presents a comprehensive review of the current research status and future trends in multi-sensor rail transit inspection vehicles. The focus is on the integrated application of various sensing technologies, particularly inertial systems and visual sensing, to achieve high-precision and efficient measurement of rail geometrical parameters. An in-depth analysis of key technologies and challenges in railway track inspection is provided, exploring how advanced sensing methods can overcome the limitations of traditional approaches. The paper also examines the market prospects for rail transit inspection, highlighting the growing demand for more sophisticated and reliable inspection systems. Furthermore, potential future research directions in this field are outlined, including the development of AI-powered data analysis, real-time defect detection algorithms, and the integration of emerging technologies such as LiDAR and thermal imaging. This review aims to provide valuable insights for researchers, engineers, and industry professionals working on advancing rail inspection technologies.

Institutional Discrimination in Health Security Policies against Immigrants in South Korea

Abstract Background South Korea is poised to become Asia’s first mult-iethnic society with over 5% of its population, totaling more than 2.5 million, being immigrants. This demographic shift presents significant public health challenges linked to widespread, and even intensifying, institutional discrimination in healthcare services. Methods This study reviews discriminatory practices across ten essential health security programs, including National Health Insurance (NHI) system, disability assistance, occupational health services, maternal and child care services, national immunization program, health screening program, and assistance for catastrophic medical expenses. Government data and personal narratives were also reviewed to identify the discriminatory elements that can have significant consequences, including increased disease prevalence, higher incidence of occupational injuries, and broader socio-economic instability among migrants. Results Discriminatory elements were found in most programs, with the exception of emergency medical services. These programs commonly provide fewer benefits or impose stricter eligibility criteria for migrants compared to nationals. In particular, the Korean NHI system demands migrants to pay higher premiums and more rigorous maintenance requirements. Conclusions The findings emphasize the need for urgent reforms to equalize health insurance costs, simplify eligibility criteria for migrants, and broaden the scope of benefits to encompass all residency statuses. Implementing these changes will enhance public health infrastructure, improve occupational safety, and foster better integration of the diverse population, ultimately promoting social cohesion and a fairer health system for all. Key messages • A number of discriminatory elements against migrants have been identified in South Korea’s social security policies that can exacerbate health disparities. • Reforms are needed to expand benefits and relax eligibility criteria for migrants in key healthcare policies, including the National Health Insurance system.

A novel taxonomy for facilitating in-depth comparison of continuing engineering education practices

IntroductionThis study addresses the urgent need for standardized frameworks in Continuing Engineering Education (CEE) to support lifelong learning in the rapidly evolving global workforce. Significant events, such as the Digital Transformation and the rise of artificial intelligence, have highlighted the demand for adaptable and diverse learning systems, especially in engineering education. On the one hand, the World Economic Forum's, 2023 Future of Jobs Report predicts a transformation in 44% of workers’ core skills within 5 years, with engineering facing substantial labor shortages. On the other hand, the Paris Agreement’s call for sustainable development necessitates a workforce with skills aligned with the green transition.MethodsThe research introduces an innovative framework taxonomy that categorizes and organizes CEE programs by integrating standardized terminologies. It focuses on critical elements such as resourcing, organizational models, and program development strategies to provide a comprehensive structure that supports consistency and comparability across diverse educational contexts.ResultsUnlike existing models, the proposed framework enhances cross-institutional learning and dissemination of best practices. It identifies key components required for effective CEE management, filling a critical gap in the literature. The study’s output is a taxonomy for discussing and comparing CEE institutional approaches and practices to advance the field and foster a global CEE community committed to excellence in engineering education.DiscussionsThis study equips educators, policymakers, and industry leaders with a practical tool to design, implement, and scale CEE programs. It ultimately fosters a skilled workforce prepared to meet the challenges of future technological and sustainable transitions, supporting the development of a standardized approach to CEE.

Multidisciplinary Optimization of Gyroid Topologies for a Cold Plate Heat Exchanger Design

Abstract The strive to reduce the environmental impact of aviation has led to electrification and increasing demand for powerful on-board power electronic systems. These high-performance electrical components are bound to produce significant amounts of low-quality heat waste that, if not dissipated properly, will lead to malfunctioning and even permanent damage. For this reason, high-performance heat exchangers (HX) represent a key enabler for future advances in aircraft systems electrification and are vital to meet net zero goals and reduce the aviation's carbon footprint. For a given volume of the exchanger, the heat flow rate can be increased by adopting more sophisticated fluid domains. However, excessive geometrical complexity will lead to an increase in pressure losses, often resulting in inhomogeneous temperature distributions. In this paper, a novel optimization procedure is employed to maximize the efficiency of a high-performance heat exchanger, while minimizing overall pressure loss and temperature gradients. The optimization is performed with full three-dimensional high-fidelity computational flow simulations. The geometry of the fluid domain is constituted by triply periodic minimal surfaces (TPMS), with a parametrization based on thickness and aspect ratios, done by using the ntopology suite. To assess the performance gain, the topology-optimized design is compared against the datum case and a conventional serpentine design.

Dynamic Lock-And-Release Mechanism Enables Reduced ΔG at Low Temperatures for High-Performance Polyanionic Cathode in Sodium-Ion Batteries.

Low-temperature synthesis of polyanionic cathodes for sodium-ion batteries is highly desirable but often plagued by prolonged reaction times and suboptimal crystallinity. To address these challenges, a novel self-adaptive coordination field regulation (SACFR) strategy based on a dynamic lock-and-release (DLR) mechanism is introduced. Specifically, urea is used as a DLR carrier during synthesis, which dynamically "locks" and "releases" vanadium ions for controlled release, simultaneously "locking" H+ ions to enhance phosphate group release, thereby creating a self-adaptive coordination field that can intelligently respond to real-time demands of the reaction system. This dynamic coordination behavior contributes to both an improvement in reaction kinetics and a significant reduction in Gibbs free energy change (ΔG). As a result, the kinetic efficiency and thermodynamic spontaneity of the reaction are greatly enhanced, enabling the efficient synthesis of high-crystalline Na3V2O2(PO4)2F (NVOPF) at 90 °C within just 3 hours. The as-prepared NVOPF cathode exhibits exceptional rate performance and ultra-stable cycling stability across a broad temperature range. Furthermore, the successful kilogram-scale synthesis underscores the practical potential of the innovative strategy. This work pioneers the regulation of coordination field chemistry for polyanionic cathode synthesis, providing transformative insights into material design.

Optimization of combustion chamber geometry for a two-stroke spark-ignited direct-injection opposed-piston rod-less aviation kerosene engine

Spark-ignited direct-injection opposed-piston rod-less kerosene engines are highly suitable for small and medium-size unmanned aerial vehicles (UAVs) because of the high power-to-weight ratio, self-balancing ability, and safety of such engines. The design and optimization of combustion systems are crucial for power, fuel economy, and knock control. To meet the increasing demand for UAV power systems and fill the research void in this area, reported here for the first time are the design and optimization of a swirl-wall-guided combustion system including the spray pattern and pit structure on the top surface of the piston, with the dynamic, fuel economy, and knock intensity as the evaluation indicators. The results indicate that the spray pattern mainly affects the fuel escape rate and inhomogeneity. After it is injected into the pit, the fuel is guided to the combustion chamber by the steering role of the guide arc. If the spray drop point is located away from the pit, it leads to increased fuel escape rate and inhomogeneity. The turbulent kinetic energy in the spark-plug zone decreases as the pit diameter decreases, fluctuating by 48 %, while the average value remains relatively constant. The distribution is influenced primarily by the enveloping effect of the pit structure on the airflow. Under low-speed conditions, as the pit diameter decreases, the ignition delay period increases and then decreases, and the combustion duration decreases monotonically. The fluctuation of indicated power is relatively small (2.64 %), and the fuel escape rate decreases monotonically, resulting in the same variation pattern of indicated specific fuel consumption (ISFC). When the pit diameter is 43 mm, the fuel escape rate and ISFC reach their lowest values. Knock combustion near the wall is influenced mainly by two factors: the temperature rise rate and the flame propagation speed. The temperature rise rate increases significantly with decreasing pit diameter. When the pit diameter is less than 50 mm, knock combustion begins to occur. Under high-speed equivalent combustion conditions, as the pit diameter decreases, the indicated power changes by 5.21 %, and the ISFC decreases monotonically.

Система государственного управления как актор политики по обеспечению жизнеустойчивости страны (на материалах РФ и стран Запада)

This study draws conclusions from the analysis of the activities of governmental bodies and the public administration system in ensuring the resilience of the country. Resilience is understood as the state and capacity of society to counteract both external and internal threats without significant losses to the vitality and integrity of the nation. The viability of a country depends on a variety of conditions and factors that affect its existence and position at a particular time. The study reveals the management subjects and the mechanisms for implementing state policy. Systemic errors in the implementation of state policies aimed at ensuring national resilience are identified. Furthermore, ways for improving the public administration system as a mechanism that fosters the achievement of this goal are proposed. The main task of public policy for ensuring national resilience is the development of society and the overcoming of uncertainty and chaos in the relationships among individuals, society, and the state under the influence of both internal and external threats. “Freedom” as a systemic category characterizes the quantity and quality of connections among the elements of the system. It can be stated that the greater the freedom afforded to social systems – characterized by fewer moral, ethical, spiritual, legal, and other ties – the lower the level of security within such a society. In addressing the challenge of ensuring the resilience of the country, enhancing the effectiveness of the public administration system demands firm political decisions and operational management.

Advancing SWAT Model Calibration: A U-NSGA-III-Based Framework for Multi-Objective Optimization

In recent years, remote sensing data have revealed considerable potential in unraveling crucial information regarding water balance dynamics due to their unique spatiotemporal distribution characteristics, thereby advancing multi-objective optimization algorithms in hydrological model parameter calibration. However, existing optimization frameworks based on the Soil and Water Assessment Tool (SWAT) primarily focus on single-objective or multiple-objective (i.e., two or three objective functions), lacking an open, efficient, and flexible framework to integrate many-objective (i.e., four or more objective functions) optimization algorithms to satisfy the growing demands of complex hydrological systems. This study addresses this gap by designing and implementing a multi-objective optimization framework, Py-SWAT-U-NSGA-III, which integrates the Unified Non-dominated Sorting Genetic Algorithm III (U-NSGA-III). Built on the SWAT model, this framework supports a broad range of optimization problems, from single- to many-objective. Developed within a Python environment, the SWAT model modules are integrated with the Pymoo library to construct a U-NSGA-III algorithm-based optimization framework. This framework accommodates various calibration schemes, including multi-site, multi-variable, and multi-objective functions. Additionally, it incorporates sensitivity analysis and post-processing modules to shed insights into model behavior and evaluate optimization results. The framework supports multi-core parallel processing to enhance efficiency. The framework was tested in the Meijiang River Basin in southern China, using daily streamflow data and Penman–Monteith–Leuning Version 2 (PML-V2(China)) remote sensing evapotranspiration (ET) data for sensitivity analysis and parallel efficiency evaluation. Three case studies demonstrated its effectiveness in optimizing complex hydrological models, with multi-core processing achieving a speedup of up to 8.95 despite I/O bottlenecks. Py-SWAT-U-NSGA-III provides an open, efficient, and flexible tool for the hydrological community that strives to facilitate the application and advancement of multi-objective optimization in hydrological modeling.

Advanced Venturini control for PMSM with modular multilevel matrix converter

This paper provides a comprehensive analysis of control strategies for modular multilevel matrix converters (MMMC) utilizing advanced second-order sliding mode control (ASOSMC) within the context of permanent magnet synchronous motor (PMSM) applications. The research introduces a novel control framework based on the Venturini method, which, when integrated with ASOSMC, achieves a unity input power factor while generating sinusoidal phase current waveforms with markedly reduced harmonic distortion. These advancements not only enhance overall system performance but also significantly improve power quality, addressing critical requirements in contemporary electrical engineering. Additionally, the study conducts a rigorous comparative analysis between classical Proportional Integral (PI) control and ASOSMC, elucidating the substantial limitations of PI control in nonlinear environments where dynamic adaptability is paramount. In contrast, ASOSMC demonstrates superior capability in managing disturbances and nonlinearities, thereby offering enhanced reliability and efficiency for MMMC systems. The findings illustrate that ASOSMC not only addresses the challenges posed by traditional control techniques but also contributes to the development of more robust control methodologies within power electronics. By establishing a clear superiority of ASOSMC over conventional methods, this research paves the way for future innovations in control strategies specifically tailored for high-performance applications that require resilience under varying operational conditions. Ultimately, this work underscores the necessity of integrating advanced control techniques to optimize the operational capabilities of modular multilevel converters, facilitating the creation of sophisticated solutions that meet the evolving demands of electrical systems and power quality enhancement in diverse applications. The implications of these findings are significant, offering foundational insights for both theoretical exploration and practical implementation in the field.

Consumer Psychology in the Digital Age: How Online Environments Shape Purchasing Habits

The advent of the digital age has profoundly changed consumers’ mindsets and habits. The rapid development of e-commerce and the widespread use of mobile applications have created enormous demand for individual recommendation systems based on mass data. This system not only increases the convenience of purchases and conversions but also alters the purchasing behavior of consumers, leading them to make choices subconsciously. Potential risks associated with large-scale data sharing and usage have heightened consumer concerns regarding privacy, thereby weakening the foundational trust in platforms and deterring them from shopping. Additionally, the rapid growth of e-commerce in the digital age, coupled with changing market circumstances, has intensified psychological pressure on consumers, making their decision-making processes more complex and difficult. Furthermore, the program will explore issues related to improving customer experience, developing individual marketing strategies, and designing customer loyalty plans. It will also address questions of privacy in a digital environment, the dilemmas of excessive or disruptive consumption behavior, and the complexity and diversity of consumer behavior in the face of digital change. The objective of this study is to develop a fear study that will enable a better understanding of the impact of online shopping on consumer behavior and provide a strategic guide for retailers to meet the challenges and opportunities presented by the digital age.

Experimental study on thermal performance of a novel serpentine-looped flat microchannel heat pipe

The pulsating heat pipe is an efficient heat transfer element widely used in a variety of applications due to the simple wickless structure and no external power requirements. Increasing the number of pipe turns can enhance the pulsation, but reduce the structural compactness. A new type of serpentine-looped flat microchannel heat pipe (SLFMHP) is proposed with numerous turns by series connection of flow channels and good thermal contact by large flat surface. The thermal performance of SLFMHP is experimentally investigated and compared with that of the copper pulsating heat pipe. Results show that the minimum thermal resistance of SLFMHP is 0.036 K/W, 80 % smaller than 0.19 K/W of the copper pulsating heat pipe. The maximum effective thermal conductivity of SLFMHP reaches 37400 W/(m·K), five times of 7233 W/(m·K) of the copper pulsating heat pipe. The sensitivity to inclination angle has also been reduced with thermal resistance at 0° improved by over 90 %. As the inclination angle increases, the thermal resistance decreases first sharply and then slowly, and the turning point is defined as the critical pulsation angle, about 15° and 8° with the filling ratio of 20 % and 40 %, respectively. The SLFMHP can provide a possible solution for the demand of the thermal control systems with miniaturization, light weight and high heat transfer capability.

Optimal Flexibility Dispatching of Multi-Pumped Hydro Storage Stations Considering the Uncertainty of Renewable Energy

With the continuous increase in the penetration rate of renewable energy, the randomness and flexibility demand in the power system continues to increase. The main grid side of the power system vigorously develops pumped hydro storage (PHS) resources. However, the current PHS station scheduling method of a fixed time period and fixed power has lost a certain flexibility supply. In this paper, an optimal dispatching model of multi-pumped hydro storage stations is proposed to supply flexibility for different regions of the state grid in east China. Firstly, the credible predictable power (CPP) of renewable energy is calculated and the definition of flexibility demand of a power system is given. The calculation model for flexibility demand is established. Secondly, considering the regional allocation constraint in the state grid in east China, a non-centralized model of multi-PHS within the dispatch scope is established. In the model, the constraints of storage capacity of different hydropower conversion coefficients of each PHS station is considered. The flexibility supply model of PHS stations to each region of the state grid in east China is established to realize reasonable flexibility allocation. Then, by combining the PHS station models and the flexibility demand calculation model, the optimal dispatching model for the flexibility supply of multi-PHS stations is established. Finally, based on the network dispatching example, the effectiveness and superiority of the proposed strategy are verified by a case study.

α-MnO2 with a cryptomelane structure for the non-enzymatic glucose electrooxidation in a neutral medium

A high demand for non-enzymatic glucose sensors and continuous glucose monitoring systems encourages the development of stable and active catalysts for the enzymeless anodic oxidation of glucose in the neutral medium. In regard to this reaction, we analyze the prospects of alpha manganese dioxide with a cryptomelane structure synthesized via an aqueous chemical route. To provide various specific surface area, the hydrated α-MnO2 oxide is annealed in a wide temperature range from 60 to 700 °C. Furthermore, we investigate the influence of the oxide annealing temperature on the amount of crystal water, chemical composition, morphology, electrochemical recharging behavior, electrocatalytic activity and stability in the glucose oxidation carried out in an isotonic NaCl-based phosphate-buffered saline (pH 7.40). To solidly determine potentials of the irreversible cathodic dissolution of α-MnO2 as well as O2/Cl2 evolution on α-MnO2, a rotating ring-disk electrode is applied. For the most active α-MnO2 sample with the 100 μg cm−2geo loading the glucose oxidation current of ca. 40 μA cm−2geo after 1 h at +0.8 V (SCE) for 7 mM of glucose is achieved. The linear concentration dependence in a physiological glucose range (1–30 mM) with the sensitivity of ca. 17.8 μA mM−0.5 cm−2geo at 25 °C is observed. Finally, glucose selectivity of α-MnO2 in relation to fructose, galactose, xylose, ribose, urea, lactic acid, acetone, ascorbic acid and paracetamol is revealed.

Experimental performance investigation on a desiccant-assisted two-stage evaporative cooling system in hot and humid areas

The escalating demand for energy-efficient and eco-friendly air conditioning systems in buildings has spurred the development of comfortable, efficient, and cost-effective air handling system configurations. Desiccant cooling has shown a higher coefficient of performance (COP) compared to traditional vapor compression refrigeration (MVCR) systems. However, current desiccant cooling facilities struggle to decouple and efficiently handle indoor heat and moisture loads. The complexity of these facilities has kept intricate cooling systems remaining theoretical, requiring simplification and experimental investigation. This paper presents an experimental study on a compact, two-stage evaporative cooling system assisted by a liquid desiccant. A key innovation of this system is the inclusion of a two-stage heat exchanger that adeptly manages the decoupling of indoor heat and moisture loads under challenging high-temperature and high-humidity conditions. Performance analysis was conducted experimentally under three hot and humid climatic conditions using an optimized operating parameter scheme. Starting from an initial condition of 36.22 °C and a humidity ratio of 0.028 kg/kg, the proposed system achieves COP values ranging from 11.3 to 18.4 without compromising indoor comfort or facility compactness. Under high heat and high humidity conditions, the optimized system extracts 20 % of the product air as the secondary air source. It can reach a minimum supply air temperature of 18.44 °C, achieved under optimized conditions of low wind speed (1.0 m/s), high desiccant concentration (35 %), and substantial desiccant flow (0.09 kg/s). Experimental studies of this new system provide the possibility of achieving high efficiency in air handling over a wide range of temperatures and humidity.

Demand for milk and milk products in the rural household of Bangladesh: A panel data analysis

Milk is considered an essential source of protein for people of all ages. However, Bangladeshi people, particularly those living in rural areas, tend to consume less milk and milk products than necessary. Therefore, this study aims to investigate the demand for milk and milk products among rural consumers and the factors affecting their consumption habits. The study utilizes balanced panel data from three waves of the Bangladesh Integrated Household Survey: 2011–12, 2015, and 2018–19, collected by the International Food Policy Research Institute. Both the Almost Ideal Demand System (AIDS) and Fixed Effects Model were employed. The expenditure elasticity for liquid milk, powdered milk, and condensed milk was found to be 1.013, 1.856, and 1.060, respectively, indicating that these products are considered luxury goods in rural Bangladesh. Additionally, powdered milk is more price-sensitive than liquid or condensed milk in these areas. Milk and milk products exhibit a substitutable relationship based on the Slutsky and Cournot cross-price elasticities matrix. Consumption of liquid milk is significantly influenced, either positively or negatively, by several factors, including age, education, family size, ownership of dairy animals, income, expense of food, and year. Furthermore, while the consumption of powdered milk is increasing over time, factors such as family size and livestock ownership negatively impact its consumption. Similarly, the consumption of condensed milk is negatively affected by education and ownership of dairy animals. Based on our study results, we recommend increasing household income through on and off-farm job creation, promoting educational campaigns on the benefits of milk, and supporting livestock ownership to reduce reliance on processed milk products.

Development of a Cloud Computing-Based Collaboration Information System

The rapid advancement of information and communication technology has created a demand for efficient and effective information systems to facilitate collaboration among institutions. This study develops a cloud computing-based collaboration information system designed to enhance real-time communication, data management, and collaboration among users. The system comprises key modules, including collaboration management, document management, and integrated collaboration features. Testing involved various scenarios with 10 to 100 active users simultaneously, revealing that the system maintained stable performance with response times under 3 seconds for each user request. Furthermore, security assessments utilizing encryption protocols and two-factor authentication confirmed that the managed data is protected from external threats. The findings underscore the system's potential to improve collaborative efficiency while ensuring data security, making it a valuable solution for future collaborative initiatives.

Research on a cloud model intelligent computing platform for water resource management

ABSTRACT As the demand for water management information systems continues to increase, addressing issues such as poor generalizability, low reusability, and difficulties in updating and maintaining water resource planning cloud model service platforms becomes crucial. To achieve goals like business-oriented functionality, high availability, and reliability, this study proposes constructing a cloud model service platform for basin water resource planning based on cloud computing technology and business workflows. This study couples water cycle models with multi-objective optimization models for water resource allocation, using digital topological water networks to achieve dynamic regional water resource allocation. The cloud service platform adopts a business-oriented modeling method based on B/S development architecture. This paper takes the Weihe River Basin as an example to simulate and analyze the evolution of the water cycle pattern and optimize the annual water resources allocation plan. Results show that: (1) the water cycle model of the cloud model service platform can better describe the runoff change process in the verification period; (2) through the cloud platform service model, the water shortage rate of the Weihe River Basin in 2025 is 7.95%. The research findings provide technical references for intelligent water management and refined allocation of water resources in the Weihe River Basin.