System In Recent Years Research Articles

Literature Review on Multi-Criteria Analysis and Application in Education Environment

Due to the increasing complexity of educational data, the use of decision analysis techniques such as Multi-Criteria Decision Making (MCDM) models has become more popular in the education system in recent years. Multi criteria decision making methods provide data analysis methods faster and more efficient for revealing unhidden patterns and other meaningful information from vast educational data those conventional analytics are unable to discover in a reasonable amount of time. Particularly, MCDM techniques have been demonstrated to be effective methods for pattern recognition in educational systems. Motivated by this consideration, the purpose of this paper is to investigate the MCDM approaches applied to education systems through a review of new architectures, applications, and educational trends. The primary objective of this paper is to provide extensive insight into the application of MCDM models to education solutions in order to bridge the gap between MCDM techniques and human-based education interpretability. Then, the application of MCDM to various aspects of education are categorized. Finally, we present the current open challenges and future directions.

Design and Application of Greenhouse Humidity Control System Based on Single-chip Microcomputer

Greenhouse planting is widely used, greenhouse humidity control automation has become people s urgent demand, automatic humidity control can reduce manual operation, improve management efficiency, and reduce operating costs through energy-saving means. In addition, such systems help to achieve a stable production environment, reduce the occurrence of pests and diseases, and improve the sustainability and economic efficiency of agricultural production. Referring to the design of greenhouse humidity control system in recent years, in view of the low degree of automation of greenhouse planting in China, a more reliable greenhouse humidity control system with AT89S51 single-chip microcomputer as the core was designed.

Phase classification and transient effects of the start-up process of multi-functional pump station in pump mode

In the context of achieving the goal of carbon neutrality, multi-functional pump stations (MFPS) have been greatly developed as a new energy system in recent years. The MFPS can operate in forward direction in pump mode to pump water and in turbine mode in reverse direction to generate electricity. At present, the instability of the MFPS during start-up process (SUP) in pump mode has become the key to restricting the operating life and further development of MFPS. In this paper, based on the motion characteristics of the pump and the cut-off facility (COF), the SUP of the MFPS in pump mode is clearly classified. In order to reveal the transient effect during the SUP, the steady-state full characteristic experiment (SFCE) of the pump was carried out. The occurrence phase of the transient effect during the SUP is analyzed, and the deviation between the steady-state external characteristics and the transient characteristics is revealed. In this study, the evaluation formula of the start-up completion degree (SUCD) of the MFPS in pump mode is proposed for the first time, and the evaluation and identification of the start-up progress at different phases are completed. The results show that the water flow in the system is in a reverse flow state in the Phase I. The SUCD of Phase I is 17 %. In the Phase II, The high-speed jet flow in the pump flows to the inlet of the guide vane (GV), which gradually changes the mainstream direction in the GV. A certain vortex structure can be observed at the exit of the flap gate (FG). The SUCD of Phase II is 61 %. In the Phase I and II, the dimensionless head of transient simulation is much larger than that of SFCE. In the Phase III, the flow state in the impeller will gradually stabilize. The transient effect disappears and the pressure fluctuation intensity decreases. The SUCD of Phase III is 93 %. In the Phase IV, the separation vortex that persists from Phase I-III at the tail of the GV blades disappears. The diversion capacity at the gate increases, and significant annular flow can be observed near the FG.

Photophysicochemical properties of pyrazoline substituted ZnII-phthalocyanine-based photosensitizers

Cancer has grown to be a global issue and has put strain on the healthcare system in recent years. Promising alternatives for the treatment of cancer include photodynamic therapy (PDT). For therapeutic purposes, phthalocyanines have been widely employed as sensitizers, especially for photodynamic treatment (PDT). The primary goal of this work is to examine the photophysicochemical properties of newly synthesized and characterized pyrazoline substituted peripherally tetra substituted and non-peripherally tetra substituted ZnII-phthalocyanines. Several techniques were applied during the characterization of the novel compounds, such as mass (MALDI-TOF), nuclear magnetic resonance (NMR), infrared (FT-IR), and UV–Vis spectroscopies. The impact of substituting 3-(5-(4-(dimethylamino)phenyl)-1-phenyl-4,5-dihydro-1H-pyrazole-3-yl)phenol from the peripheral and non-peripheral positions on solubility and aggregation behaviors was examined. The newly synthesized pyrazoline substituted ZnII-phthalocyanines display high solubility in common organic solvents and additionally do not aggregate at concentrations from 1 to 10 μM. The potential use of the pyrazoline substituted ZnII-phthalocyanines as a photosensitizers in photodynamic therapy was investigated by examining their photophysical and photochemical properties. Non-peripheral pyrazoline substituted ZnII-phthalocyanine (HY-ZnPcnp) may be a potential photosensitizer for PDT, owing to an examination of the results.

Right and Duty: Investment Risk Under Different Renewable Energy Support Policies

AbstractRenewable energy projects are subject to risk due to the uncertainty of future electricity prices and the amount of energy produced. Public support usually consists of some form of guarantee, either on the price received per MWh supplied or the return on investment per MW installed. This support reduces the investor’s risk, which is then assumed by the regulator. However, most of these policies do not only grant the investor the right to receive a guaranteed payment but also limit its potential benefits (i.e., impose an obligation). We propose a model with analytical solutions in which, considering the randomness of the market price, as well as that of the energy production, we quantify the risk removed under different types of regulations and assign a value to both the rights and the obligations that each policy entails. Finally, we apply the model to the case of Spain, which has undergone several changes in its green energy support system in recent years. Our results indicate that in the context of low electricity prices, the obligations imposed by most of these policies are negligible compared to the rights received. By contrast, in the context of high electricity prices and increasingly competitive renewable energy sources, the assumed obligations become more notable to the point of the support policy becoming a liability. Nevertheless, a sufficiently risk-averse investor may be incentivized by a policy with negative expected regulatory costs.

Behind the Curtain: Comparing Predictive Models Performance in 2 Publicly Insured Populations.

Predictive models have proliferated in the health system in recent years and have been used to predict both health services utilization and medical outcomes. Less is known, however, on how these models function and how they might adapt to different contexts. The purpose of the current study is to shed light on the inner workings of a large-scale predictive model deployed in 2 distinct populations, with a particular emphasis on adaptability issues. We compared the performance and functioning of a predictive model of avoidable hospitalization in 2 very different populations: Medicaid and Medicare enrollees in Maryland. Specifically, we assessed characteristics of the risk scores from March 2022 for the 2 populations, the predictive ability of the scores, and the driving risk factors behind the scores. In addition, we created and assessed the performance of an "unadapted" model by applying coefficients from the Medicare model to the Medicaid population. The model adapted to, and performed well in, both populations, despite demographic differences in these 2 groups. However, the most salient risk factors and their relative weightings differed, sometimes dramatically, across the 2 populations. The unadapted Medicaid model displayed poor performance relative to the adapted model. Our findings speak to the need to "peek behind the curtain" of predictive models that may be applied to different populations, and we caution that risk prediction is not "one size fits all": for optimal performance, models should be adapted to, and trained on, the target population.

Error analysis and correction of atmospheric disturbance for interferometric imaging radar altimeter

The interferometric imaging radar altimeter (InIRA) is a newly developed microwave remote sensing system in recent years. It is of great significance to analyze the main sources of its height measurement error through simulation, and to develop the corresponding image phase error correction methods. This can provide basis and reference for the subsequent correction of the real images phase error. In this study, according to the interaction principle between atmospheric interference and InIRA radar electromagnetic waves, the influence of background ionosphere and background troposphere on height measurement error is analyzed by introducing ionosphere and troposphere delays into echo signals respectively. The impact of ionospheric scintillation and atmospheric turbulence on the height measurement error is analyzed by building multi-layer phase screen models. Then according to the analysis results, a phase error correction method for InIRA images combined by the improved fruit fly optimization algorithm (IFOA) and the joint minimum entropy criterion (JMEC) is proposed. The image is divided into several sub-images with negligible spatial variation of phase error according to the principle of first range and then azimuth. IFOA is used to search the optimal phase compensation values iteratively to compensate the phase of all sub-images. When the joint entropy of the sub-images reaches the minimum value, the phase error correction of the whole InIRA image is completed. Experimental results show that the proposed method can correct the phase of InIRA images with inconspicuous features and polluted by weak ionospheric scintillation and atmospheric turbulence relatively quickly. After correction, the height measurement error can be reduced from decimeter level to centimeter level. The correction accuracy and efficiency of the proposed method are superior to those of the method combined by particle swarm optimization algorithm and joint minimum entropy criterion (PSO-JMEC), the method combined by genetic algorithm and joint minimum entropy criterion (GA-JMEC), the method combined by phase gradient autofocus and Map Drift (PGA-MD), and improved PGA-MD algorithm.

Construction and Evaluation of Paclitaxel Mn-Doped Dendritic Mesoporous Silica Coated with N-Succinyl Chitosan

Mesoporous silica, as a drug carrier, has become the new research focus in the field of nanodrug delivery system in recent years. In this study, Mn-doped mesoporous silicas are synthesized by template and in-situ doping method and physically characterized. The drug-loading performance of silica and its impact on drug release are studied. The Mn-doped mesoporous silicas show dendritic morphology (MDMS) with a loose wrinkle structure on the surface and a large number of pores. MDMS is used as a carrier to solve the problem of low water solubility of paclitaxel. In order to avoid leakage during drug transportation, the surface of Mn-doped mesoporous silica loaded with paclitaxel is coated with N-succinyl chitosan to construct a new type of nanodrug delivery system (MDMS-PTX-NSC). Compared to MDMS, MDMS-PTX-NSC shows an increase in particle size and smooth surface. The dissolution characteristics of manganese ions and swelling behavior of N-succinyl chitosan make MDMS-PTX-NSC delivery system exhibit a good pH-responsive release. And MDMS-PTX-NSC release curve can be well fitted by Ritger-Peppas equation. The cytotoxicity test shows that the MDMS-PTX-NSC has significant biocompatibility and enhanced cytotoxicity, which reveals that the MDMS-PTX-NSC is a promising nanodrug delivery system.

Improving Patient Flow in the Emergency Rooms using Coloured Petri Nets and the ACO Algorithm

Overcrowding is certainly one of the major problems that have affected the work of the health care system in recent years, especially in the Emergency Department (ED), In addition, overcrowding has a significant impact on the quality of health care in hospitals. In addition to creating issues for patients and staff, overcrowding in the ED can lead to medical errors, longer wait times, and thus causes financial losses to hospitals. Emergency services are considered necessary in society, given the human need for them at any stage of their life. The emergency department is a complex system due to the nature of the resources it contains. Many researchers are interested in proposing many solutions to solve many problems in the emergency department. Researchers rely on many methods and techniques such as simulation, optimization algorithms, data mining, and other methods. In this research, we try to propose an approach based on the ant colony optimization (ACO) algorithms and colored Petri nets, the aim of which is to reduce waiting times and thus reduce the length of the patient’s stay. Simulation models are built utilizing colored Petri nets, and to determine human resources, the ACO algorithms are used. This research helps the administrative staff in the emergency department find appropriate solutions for human resources.

Day-ahead load forecast based on Conv2D-GRU_SC aimed to adapt to steep changes in load

With the significant increase in the proportion of volatile new energy in the power system in recent years, the difficulty of system scheduling has increased. Accurate load forecasting is an important prerequisite for flexible scheduling. The load itself is a highly regular object that is relatively easy to predict. However, steep changes in load can cause significant deviations in load forecasting. In response to this issue, this article first selects input variables that can help the model identify steep changes in load based on Pearson correlation coefficient and the proposed “Steep change impact rate”. Then, Conv2D-Gate Recurrent Unit (Conv2D-GRU) model is built to fully extract steep changes information from inputs and achieve day-ahead load forecasting. Naive persistence, Auto regressive (AR), Gradient boosting decision trees (GBDT), Convolutional neural network (CNN), Long short-term memory (LSTM) and Gate recurrent unit (GRU) are used for comparison. Compared to Naive persistence, the Conv2D-GRU-SC resulted in a decrease of 54.08 % in Mean absolute error (MAE), a decrease of 57.58 % in Root mean square error (RMSE) and an increase of 51.31 % in the R-Square (R2).

How Are Students Learning Patterns Influenced by the CEE

The College Entrance Exam (the CEE) in China has been in operation for several decades. However, there are increasing complaints about this education system in recent years, claiming the CEE can harm students learning patterns. This article aims to review the students affected and changed learning patterns in the context of Chinese College Entrance Exam (CEE) as well as Chinese cultural background. First, this paper introduces the basic information about the CEE and its score-oriented system, in order to better analyse in the following contents. Second, this paper describes how scholars define a learning pattern and what can influence a learning pattern. Then, the paper points out the gap that few researchers have explored how students learning patterns can be influenced by such an exam system. Lastly, after reviewing past papers, the results show that learning patterns of students can be negatively influenced either directly or indirectly in the context of the CEE. This study shows the importance of an education system as well as parenting or teaching styles in affecting the students learning habits and skills like critical thinking. Findings from this study also provide new insights for instructors and learners to optimize the learning patterns.

Strategies of regulating Zn2+ solvation structures toward advanced aqueous zinc-based batteries

Rechargeable aqueous zinc-based batteries not only pave the way for environmentally friendly and safe energy storage devices but also hold great promise for reducing the manufacturing costs of next-generation batteries, positioning them as the most promising energy storage system to replace lithium-ion batteries. However, the commercial application of aqueous zinc-based batteries (AZBs) is severely constrained by issues such as zinc dendrites, hydrogen evolution reaction (HER), and electrode corrosion. While significant efforts have been devoted to exploring electrode materials and their storage mechanisms in this system in recent years, research on the nature of Zn2+ solvation in electrolytes remains insufficient. Therefore, this review primarily provides a comprehensive and in-depth elucidation of the existing issues such as dendrite formation, hydrogen/oxygen evolution, electrode corrosion and passivation interactions. Additionally, from the perspective of electrolyte optimization, this review emphasizes existing strategies to address Zn2+ solvation, including adjusting electrolyte concentration, incorporating functional additives or co-solvents, utilizing ionic liquids, and developing hydrogel electrolytes, and summarizes approaches and mechanisms for improving their relevant performance. Finally, prospects for electrolyte modification and innovation directions of AZBs are proposed, providing guidance for future AZB studies.

Challenges and Breakthroughs in Enhancing Temperature Tolerance of Sodium-Ion Batteries.

Lithium-based batteries (LBBs) have been highly researched and recognized as a mature electrochemical energy storage (EES) system in recent years. However, their stability and effectiveness are primarily confined to room temperature conditions. At temperatures significantly below 0°C or above 60°C, LBBs experience substantial performance degradation. Under such challenging extreme contexts, sodium-ion batteries (SIBs) emerge as a promising complementary technology, distinguished by their fast dynamics at low-temperature regions and superior safety under elevated temperatures. Notably, developing SIBs suitable for wide-temperature usage still presents significant challenges, particularly for specific applications such as electric vehicles, renewable energy storage, and deep-space/polar explorations, which requires a thorough understanding of how SIBs perform under different temperature conditions. By reviewing the development of wide-temperature SIBs, the influence of temperature on the parameters related to battery performance, such as reaction constant, charge transfer resistance, etc., is systematically and comprehensively analyzed. The review emphasizes challenges encountered by SIBs in both low and high temperatures while exploring recent advancements in SIB materials, specifically focusing on strategies to enhance battery performance across diverse temperature ranges. Overall, insights gained from these studies will drive the development of SIBs that can handle the challenges posed by diverse and harsh climates.

Review of Hydraulic Balance and Energy Saving of Cooling Water System

Cooling water system is widely used in industry, transportation and other fields. Reasonable design and optimization of cooling water system is of great significance to reduce energy consumption and realize energy saving and emission reduction. This paper sorted out the articles about the cold water system in recent years, especially the hydraulic balance of pipe network, pointing out that the influence of the hydraulic balance of pipe network on the whole system can not be underestimated. At the same time, the research of cooling water system from the aspects of cooling water system design, hydraulic calculation and balance debugging device.

Navigating Exodus: Understanding the Migration Dynamics of Health Care Professionals from Turkey

Objectives: We aimed to determine the reasons for the emigration of health workers who left Turkey and the difficulties experienced before and after the migration.Methods: This is an exploratory qualitative study of open-text fields focusing on migrant health workers from Turkey. Answers given to five open-ended questions directed to the participants in our survey, with 513 participants between April and June 2022, were used. Data were analyzed following content analysis.Results: A total of 506 responses were analyzed. The mean age of the participants was 39.9 ± 8.8 years (54.2% men, 77.5% medical doctors). Almost all participants reported that the political atmosphere in Turkey forced them to migrate. Some participants were unable to do their jobs due to the increasing violence in the health system in recent years. Most participants saw migration as the only way out, as they did not feel free and safe. Comparatively, they were in a better economic situation in Turkey and had a higher standard of living.Conclusion: Migration creates a sense of security while at the same time accepting a lower standard of living. To organize the sustainable migration of professionals, it is beneficial to ask what framework conditions need to be created and to access the labor market in particular.

Comparison of Educational Development Trends in Ukraine and the World

The article examines the trends in the development of the educational system in recent years in Ukraine and the world in the context of neuropedagogy. Particular attention is paid to the factors that have influenced the strengthening of the role of education in the world, in particular, the strengthening of the state's interest in financing education. The article updates the inextricable connection between the country's economy and the level and quality of education. The author points out the advantages of education support systems in some advanced countries of the world, which can be used as a model experience for domestic educational reform, in particular due to the use of neuropedagogy. The most important trends in the development of education in the world educational space are analyzed. The author notes that the quarter-century experience of the 21st century civilization determines a number of trends according to which it should develop in the future. Among them, for example, the transition of most nations and cultures to market relations is leading in the economy; in politics - to democracy; in social communication - to tolerance; in the general organization of life activities - to an open society and models of sustainable human development, etc. Because education (and science), which prepares a person for independent life, shapes his view on the future development of civilization.

Detection of distributed denial of service attack using enhanced adaptive deep dilated ensemble with hybrid meta‐heuristic approach

AbstractThe biggest firms throughout the world now are the ones that offer services in the cloud. One of the top problems for cloud users (CUs) and cloud service providers (CSPs) is the availability of cloud‐based services whenever needed. A distributed denial of service (DDoS) assault has been a significant threat to the security of the system in recent years. DDoS defense and detection of these attacks have become hot topics of research for academia and business. However, most approaches cannot accomplish efficient detection outcomes with few false alarms. As a result, minimizing the consequences of DDoS attacks allows CSPs to offer CUs high‐quality services. In the cloud sector, a collective deep structured algorithm is suggested to identify DDoS attacks successfully. The recommended method contains several stages: data acquisition, pre‐processing, optimal feature detection, and selection. The first step is the acquisition of data using the help of publicly available sources. Further, the input data undergoes preprocessing. Consequently, the optimal weighted feature selection takes place on the preprocessed data, where the optimization is done with the aid of the Hybrid Border Collie and Dragonfly Algorithm (HBCDA). Finally, DDoS attack detection is achieved via a novel method known as adaptive deep dilated ensemble (ADDE), which includes, one‐dimensional convolutional neural network (1DCNN), deep temporal convolutional neural network (DTCNN), recurrent neural network (RNN), and bidirectional long short‐term memory (Bi‐LSTM). For the attainment of optimal results, the parameter tuning is accomplished by using the HBCDA approach. The detection outcome is computed by using the fuzzy ranking mechanism. The validation is done for the suggested method model, and its corresponding findings are validated with conventional techniques. Hence, the suggested approach outperforms the detection performance and ensures more efficiency than traditional approaches.

Дихотомии евразийства: общественно-географический анализ

Eurasianism is among the traditional and most significant intellectual-political currents for Russia and its geostrategy. The importance of the postulates and approaches cultivated within Eurasianism has notably increased in the context of the sharply manifested conflict in the “Russia-West“ system in recent years and the corresponding reorientation of the Russian Federation’s geoeconomic priorities towards the countries of the “Global Majority.“ The actualization of Eurasianism and its broad entrenchment in Russian academic discourse is combined with its contemporary conceptual “fuzziness,“ variability of interpretations, and the presence of deep contradictions and problematic areas inherent to Eurasian ideological concepts, which the author conceptualizes as “dichotomies of Eurasianism.“ The article emphasizes the essential duality of Eurasianism, combining elements of verifiable scientific knowledge with ideological principles, allowing it to be considered a unique form of geo-ideology. It identifies substantive differences between the positions of classical Eurasianism (works of N. S. Trubetskoy, P. N. Savitsky, G. V. Vernadsky, etc.) and the prevailing directions of Eurasianism in the 21st century (“neo-Eurasianism,“ concepts of “Greater Eurasia,“ “Northern Eurasia“). The simultaneous presence of universalism (on an all-Russian and continental scale) and pronounced “Russia-centricity,“ as well as the combination of geoeconomic and geocultural isolationism with a strong integrative message across nations and countries, inherent in Eurasianism, are demonstrated. The necessity for the further development of Eurasianism, including within the framework of social geography issues, is substantiated.

Entropy Model For Safety Culture and Safety Performance

According to Maslow's Hierarchy of Needs, combined with the political attribute of safety management, the human's demand hierarchy and the development trend of our country's safety production management system in recent years, the realization path of security vision of port enterprises in China is proposed, including that (1) Taking safety vision as the objectives, the process of safety awareness is analyzed from the perspectives of safety perception, safety cognition, and safety decision-making, and the framework model for implementing safety awareness is established.(2) Based on the analytic hierarchy process and logical analysis, the factors with greater weight in safety performance are determined.(3) An entropy model for safety culture and safety performance are established.

New Reference Current Calculation Method of a Hybrid Power Filter Based on Customer Harmonic Emission

This paper presents a novel reference current calculation method for harmonics mitigation and reactive power compensation in power systems. This method was applied to a unique hybrid power filter topology. The motivation for this study comes from the increasing power quality issues, such as harmonic distortion and resonances, caused by the widespread integration of converter-interfaced generation (CIG) and modern nonlinear loads into the power system in recent years. The goal of this study is to propose a cost-effective and practical solution for current harmonics filtering and power factor correction by combining the advantages of passive and active filters into a hybrid solution. The developed reference current calculation method, which is based on customer current harmonic emissions, enables effective reference current calculation. Theoretical analyses along with simulation results obtained from a medium-voltage benchmark model in PSCAD verify the effectiveness of the proposed solution in harmonics filtering and show a substantial reduction in filter current ratings across various harmonic components. In addition, the simulation results were evaluated by comparison with the results obtained from a real-time simulator.