Articles

In recent years, the exploration and utilisation of the environment has become in full swing with the advancement of technology. However, the environment has also suffered a certain degree of damage in the process. As a result of the increasingly serious environmental problems, various environmental issues have become hot spots in society. Among them, marine environmental problems have undoubtedly become one of the focuses of attention. Therefore, the robot design for underwater water quality detection has become an important issue. This paper will mainly focus on the design and research of the hardware circuit system of the underwater detection robot, and give the relevant design scheme. The underwater robot will achieve the following functions: floating suspension at a certain depth in the ocean; synchronously detecting the radiation intensity of x-rays and γ-rays underwater and transmitting the data to the ground to achieve real-time monitoring; maintaining the dynamic balance in the water. Therefore, this paper analyses the pressure sensor circuit, the inertial sensor circuit, the underwater x-ray and γ-ray detection probe circuit and the DC motor drive circuit, determines the interface relationship of each part, and at the same time, uses the Arduino mega 2560 as the control panel, and provide the appropriate voltage according to the needs of each circuit to achieve the hardware circuit design of the robot.

The study of sediment movement in a stably stratified (each layer is less dense than the one below it) fluid is important for applications such as airborne virus transport, contaminant transport, and sediment settling in river inlets. This project will quantify the effect of sediment-driven instability on the horizontal motion of sediment in a stably stratified fluid. Experiments are designed to analyze this process by adding sediment-rich brine-free water to sediment-free brine, where salinity differences are used to construct stably stratified fluids. The experiments are done with salinity same as salty water with concentration of sediments derived from linear stability analysis. This work provide baseline experiments for sediment settling in a stably stratified fluids for numerical validations in the future.

The temperature distribution of flames has long been a fascinating topic of study. To quantitatively analyze the temperature field of flames, traditional methods include infrared devices, thermocouples and thermometer. However, these conventional techniques provide only cross-sectional snapshots while lacking the capability to offer real-time 3D temperature field visualization. This paper proposed a different approach to measure the 3D temperature field with accurate data and details by applying the digital holography. First, based on digital holography and the equations of thermodynamics, we derived the equation between the phase difference and temperature. Then we built a transmission off-axis digital holographic microscopy in the experimental section to perform static and dynamic flame measurements. To calibrate the actual temperatures and test our theory’s accuracy, we also took photographs of the flames as a standard reference using an infrared thermal imager. Finally, we obtained a quantitative 3D distribution of the temperature field and a qualitative dynamic process of 3D temperature field. Our results show that the temperature decreases from the center of the flame and follows a general pattern. The comparison with infrared imaging shows that digital holography offers an accurate measurement of the temperature.

This paper presents an in-depth exploration of the integration of Artificial Intelligence (AI) in theatre, with a focus on the creation of AI-generated stage plays. Utilizing ChatGPT's language model and deep learning algorithms, the research investigates AI's capability to generate compelling scripts, characters, and narratives for theatrical productions. The study employs a mixed-methods approach, analyzing existing AI-generated theatrical works and conducting experimental script creation using AI. The findings highlight both the potential and limitations of AI in theatre, emphasizing the need to balance AI-generated content with the intrinsic human qualities of theatrical performances. The paper contributes to the understanding of AI's impact on theatre and raises questions about audience engagement and authenticity in AI-generated content.

Illuminance is a measurement proportional to the intensity of light. When light is incident on a surface, the angle it makes with the normal vector of the surface plane is the angle of incidence. This paper focuses on an investigation of the relationship between the illuminance of reflected light from a glass block and the angle of incidence of the light on the block. By applying Fresnel’s coefficients, an expression for the illuminance of reflected light is derived in terms of the angle of incidence. The controlled measurements, including the illuminance of s-polarized and p-polarized light of a green laser (532nm), are directly measured to arrive at a set of calculated reflected illuminance at 10 different angles of incidence. The reflected illuminance is also experimentally measured with a light sensor at these angles. Upon the comparison between the two sets of data in this paper, a close resemblance of the shape of their curves is observed, both revealing an increasing reflected illuminance with a growing rate with respect to the increase of the angle of incidence. However, due to some expected systematic errors in the experiment, the calculated data has a generally higher reflected illuminance than the theoretical data at each angle of incidence. Overall, it is confirmed that as the angle of incidence increases, the illuminance of the reflected light increases with a growing rate.

In the contemporary digital landscape, architectural firms are increasingly reliant on sophisticated websites to showcase their portfolios and engage with clients. This paper delves into creating a user-centered website, emphasizing the critical role of front-end development in marrying aesthetics with functionality. Through a detailed examination, the study highlights prevailing trends in user interaction, visual design, and technological integration specific to architectural web platforms. In this paper, a prototype website was designed and implemented, utilizing HTML5, CSS3, and JavaScript, coupled with responsive design principles and interactive features. The development process involved using interactive keywords, a dynamic project gallery, and a responsive navigation menu, all facilitated by Java Server Pages (JSP) for back-end integration. This approach underscored the importance of user-centered design in web development for architectural firms. This study successfully integrated an intuitive user interface with advanced functionality, resulting in a web design that not only aesthetically aligns with the architectural firm’s brand identity but also enhances user engagement. Key results include an innovative scrolling gallery showcasing architectural projects, seamless integration of JSP for dynamic content management, and a notable improvement in website navigability and responsiveness, leading to a more interactive and satisfying user experience.

As society becomes more and more competitive, the pressure of exams faced by students is also increasing. For example, high school students are about to face the college entrance examination, college students face the graduate school examination, graduates face the job, and many other problems. The pressure on students is increasing, which may lead to psychological problems that may jeopardize their physical and mental health. To prevent students from having psychological issues, this project researched a Java web that analyzed students’ heart problems and provided corresponding solutions according to the problems. In this Java web, a heart questionnaire evaluation is provided, which is divided into selective questions and scored according to the user’s filling in the situation. According to the user’s scores combined with the big data, the user’s existing heart problems was analyzed. The user’s score is combined with big data to analyze the user’s heart problems, and finally feedback to the user’s heart problem suggestions. This mental health assessment helps students to face the stress of life’s difficulties positively and to maintain a positive attitude to deal with any difficulties.

Freelancing is a type of labor arrangement in which independent freelancers use their discretionary time to perform ad hoc tasks, usually of a single nature, with the aim of getting paid. This study proposes an augmented method for predicting the amount of freelance transactions using textual sentiment analysis. First, a unique feature labeled “Freelancer Sentiment” was selected to summarize the positive or negative sentiment orientation of freelancers. Subsequently, Naive Bayes algorithm is applied to process the text data from the freelancer’s platform to finally develop a “Model for Computing Word Sentiment Values”. The model helps to accurately calculate the sentiment values associated with emotional words. Finally, the Word Frequency-Inverse Document Frequency (TF-IDF) algorithm is used to construct the Text Sentiment Value Calculation Model, so as to accurately calculate the sentiment values of freelancers. The results of the comparison experiments of the five commonly used prediction models show that the mean squared error (MSE) of the model that includes the “freelancer sentiment” feature is significantly reduced by 6%-11% compared with the model that does not include the “freelancer sentiment” feature. This study contains theoretical explorations and practical implications. First, the proposed approach of extracting features from textual data to build predictive models provides a valuable reference for future enhancement of predictive modeling on freelance platforms, especially those that rely on unstructured data. Second, incorporating textual sentiment value features relevant to freelancers can significantly improve the accuracy of predicting transaction amounts. Third, the calculation of word and text sentiment values employs a series of algorithms that target specific features of the freelancer platform’s text data. This approach is important for improving the accuracy of feature value calculation.

This paper proposes a fault-tolerant frequent itemset mining algorithm (FT_HTlist) based on the linear table when the fault-tolerance is 1. The algorithm uses the method of concatenating 1 in the highest bit of the binary number of the known fault-tolerant frequent patterns to generate the candidate fault_tolerant patterns, called FT_Candidate. The algorithm is based on the data structure of the linear table for fault-tolerant frequent itemset mining. This method does not need recursion, so it reduces the consumption of mining space. At the same time, the paper proposed a deduplication algorithm to remove the support for repeat calculations. So the algorithm has a strong advantage in spatial performance. In addition, the algorithm only needs to mine two horizontal chains of the FT_Candidate, thus reducing the consumption of mining time. Finally, the paper shows the time performance and space performance of the proposed algorithm under sparse datasets and dense datasets. The results show that our algorithm has better mining time than other algorithms, and the horizontal chain reduces the memory occupation of the algorithm.

Due to the rapid development of the Internet, online shopping is also developing, in which the construction of online shopping platforms is becoming more and more important. However, existing shopping website page designs often lack consideration for user needs, resulting in some negative user experiences for users. This paper aims to research the design and implementation of Java for commercial shopping pages and points out that Java design pages can greatly help enterprises and users. This study achieved a user-friendly improvement of key design elements such as logos, typography, language style, colors, and icons. This design provides diverse user options and improves user satisfaction. The research in this paper can help designers better satisfy the needs of users when designing pages and bring the greatest benefits to themselves or enterprises. The results of this study provide a new path for website page design for related research, which significantly improves user experience and shopping enthusiasm.

The purpose of this study is to investigate how the Wix platform and JavaScript collaborate to create user interfaces (UI) for educational blogs that are robust and simple to operate. The purpose of this study is to investigate the extent to which Java technologies, particularly Spring and Hibernate, might enhance user interface designs on the Wix platform. The study also focuses on the significance of striking a balance between design and technology. Through the incorporation of tools for online lesson preparation and time management, the project intends to improve the overall quality of the user experience. This is because educational applications have challenges that are unique and need to be eliminated. Using Java technologies like Spring, Hibernate, and Jakarta Faces, the research project involves the creation of an instructive blog. The research makes use of the Design Thinking methodology and takes a human-centered approach to its methodology. To facilitate user comfort, aesthetic appeal, and efficient interaction, the design makes use of visual harmony, simplicity, and refinement at various points throughout. In the context of this research, the use of wireframing, high-fidelity mockups, and prototype assembly on the Wix platform helps the growth of the internet as well as the development of instructional resources. One of the objectives of this project is to develop a design for an educational blog that is consistent and visually appealing.

As the need for efficient and user-friendly web applications in the field of psychological assessment continues to grow, traditional web development approaches are challenged to provide a dynamic and adaptive user experience. This study focuses on addressing these challenges through a comprehensive study that provides insight into the current state of psychological assessment web development, highlighting the shortcomings of traditional approaches, including the static limitations of Hyper Text Markup Language (HTML) and limited client-side scripting. The result is a user experience that lacks the responsiveness and flexibility that modern users expect. To tackle these problems, the intended solution suggested in this work combines a strong and scalable database design with a dynamic switching mechanism for psychological exam questions. Features-rich, aesthetically pleasing, and functioning client-server Web applications are created using technologies such as Servlets and Java Server Pages (JSP). The research contains practical case studies that demonstrate how Java-based user interface design can be successfully applied in real-world scenarios. The advantages of modularity, code reusability, and maintainability are demonstrated in these case studies. The study examines how selected technologies affect the performance, security, and accessibility of web UI, while also addressing load times, data integrity, and user inclusion issues. To summarize, this investigation underscores the crucial role of dynamic and scalable databases and Java-based technologies in enhancing the design of psychological assessment Web UIs.Developers can create web applications that exceed user expectations and provide superior user experience in the evolving digital landscape by using the proposed framework’s comprehensive toolkit.

The shock tube is a crucial experimental apparatus in the field of explosive impact. Limited research has been conducted on the visualization of the internal flow field in shock tubes under blockage conditions, and there is a lack of comprehensive understanding of the mechanisms behind blockage effects. This paper presents experimental and numerical investigations into the propagation of shock waves inside a shock tube and their interaction with obstructive elements. Blockage effect experiments were conducted on a shock tube test platform, where pressure data were obtained through a pressure monitoring system. Additionally, schlieren imaging technology was employed to visualize the evolution of shock wave fronts. A two-dimensional numerical model of the shock tube was established using Fluent software, and the computed results exhibited excellent agreement with the experimental data, confirming the accuracy of the numerical model. The mechanism of the blockage effect was revealed through analysis of pressure-time curves and images depicting the evolution of shock wave fronts. Furthermore, adjustments to parameters on the validated numerical model allowed for analysis and comparison of different blockage ratios. The results indicate that the disturbance to the flow field caused by the blockage effect is primarily due to the reflection of shock waves between the front surface of the obstructive element and the shock tube wall. This reflection leads to differences in pressure curves compared to free-field conditions, and such differences increase with higher blockage ratios.

Due to the different divergence angles in two perpendicular directions and the presence of astigmatism in edge-emitting semiconductor lasers, the communication distance and efficiency of underwater communication are seriously affected. Therefore, based on the fact that the semiconductor laser beam belongs to Gaussian beam, satisfying Gaussian characteristics and collimating and expanding characteristics, a system composed of fast-axis collimation mirror and variable magnification beam expander is designed. Simulation is performed, and the final divergence angle is calculated. Experimental results show that the divergence angles of the fast axis and the slow axis have been compressed from 49° and 9°, respectively, to 0.315 mrad and 0.180 mrad. Simulation demonstrates that the system can achieve propagation over a distance of 100m underwater and solve the alignment difficulty of APT. The designed structure is compact, easy for processing and adjustment, with high practical value, which helps to solve the problems of optical energy loss and low coupling efficiency in underwater long-distance communication.

In the actual financial market, the classical Black-Scholes (B-S) model can’t perfectly describe the process of stock price. Besides, memory effect is an important phenomenon in financial systems. Thus, in this paper, we establish a fractional order stochastic differential equations (FSDE) which is driven by fractional Brownian motion (fBm) to describe the effect of noise memory and trend memory in financial pricing. Finally, we derive a European option pricing formula based on the established model. After conducting an empirical analysis based on the SSE 50ETF, we find that the established model performs better than the traditional one.

With the development of 5G technology, communication networks have become increasingly complex, leading to a continuous growth in the number of base stations. While this has resulted in faster speeds, lower latency, and greater capacity, it has also presented a pressing issue: weak coverage points, areas with weak signal radiation from base stations. To address this challenge, this paper proposes a layout optimization scheme for the coexistence of base stations with multiple coverage capabilities, based on a genetic algorithm. The scheme considers the rational deployment of various types of base stations (represented as macro base stations and micro base stations in the paper) to improve the situation of weak coverage points. The specific steps of the optimization layout scheme include initializing existing base station coverage, calculating distances to weak coverage points, selecting new base station locations, updating data, and analyzing calculations. The final output includes the coordinates and types of new base stations needed. Through model simulation, the proposed optimization layout scheme can consider cost, coverage effectiveness, and threshold constraints while accommodating various requirements. Additionally, the scheme is highly applicable and can be integrated with computer analysis software. Finally, a dialectical analysis of the model is conducted, recognizing the flexibility and practicality advantages of the layout optimization scheme based on genetic algorithms, while acknowledging potential limitations such as overly idealistic assumptions.

This paper delves into the application of generative artificial intelligence and large language models in the field of education, with a particular focus on the rising trend of large language models. Large language models play a crucial role in intelligent tutoring systems by accurately understanding student queries through deep learning and providing personalized responses. Case studies showcase the exemplary utilization of natural language processing techniques and reasoning engines, albeit facing challenges related to real-time processing and privacy concerns. The latter part of the paper concentrates on the application of generative artificial intelligence and large language models in curiosity-driven learning and the integration of multimodal educational systems, emphasizing the technical frameworks and challenges associated with multimodal integration. Finally, the paper provides insights into future developments, highlighting research on the potential benefits in the field of education, while emphasizing concerns related to ethics and privacy.

Since various means of transportation and entertainment activities are restricted by objective conditions, the number of tickets is always limited, so ticket scalpers continue to be a companion product to this day. In the current Internet environment, the web application of the ticketing system faces challenges from ticket-grabbing robots controlled by ticket dealers. The current security procedures have significantly increased the workload and time consumption of effective users. The question now is whether ticket-grabbing bots can be stopped without increasing the workload of legitimate users and being as unnoticed by users as possible. In response to this problem, this article proposes a ticket booking system model integrated with a form-based honeypot, which can achieve the function of deceiving robots without being noticed by ordinary users. This model provides a feasible method for implementing network applications that are both secure and efficient, ensuring that users have a more seamless and protected experience.

As a core component in deepening reforms and expanding the strategy of dual circulation development, the importance of developing sub-centers for the economic growth of provincial capitals is self-evident. This paper, based on panel data from 300 prefecture-level cities in China from 1998 to 2020, constructs a progressive double-difference (DID) model to assess the impact of sub-central development on the economic growth of provincial capitals. The research reveals that the development of sub-centers at the provincial level significantly promotes the economic growth of provincial capitals. Moreover, the policies of sub-center cities have a more pronounced stimulating effect on the economic growth of provincial capitals in the central and western regions. Additionally, the more sub-center cities there are, the more apparent the effect on promoting the economic growth of provincial capitals. Subsequently, this paper employs the Particle Swarm Optimization - Random Forest (PSO-RF) model through machine learning to validate the above conclusions, confirming the validity of the findings.

Dark matter and dark energy are used as two important concepts in cosmology to explain some of the observed phenomena in the universe. Dark matter is one of the most dominant constituents of the Universe, and it influences the structural formation of the Universe through gravity, including the formation and evolution of galaxies, clusters, and the large-scale structure of the Universe. Dark energy is believed to be one of the causes of the accelerated expansion of the Universe, and its presence explains the observed phenomenon of the accelerating rate of expansion of the Universe. Although their existence has not been directly observed, people understand through the study of the structure and evolution of the universe that they play an important role in the universe. This paper first introduces the background knowledge of dark matter and its related properties and explains the reasons why three types of models, namely WIMP, axion, and sterile neutrino, are candidates for dark matter in the light of existing observations. The paper then discusses the relevant properties of dark energy and analyses the mainstream dark energy models. For the cosmological constant Λ mode, the fine-tuning problem and cosmic coincidence problem it faces are analysed in detail. The evolution of the dark energy equation of state ω from the past ω>-1 to the present ω<-1 is then explained, and this is used to introduce the scalar field model involving dynamic, the Chaplygin gas model, the holographic dark energy model, and the interacting dark energy model.