bluuebunny/crossref_metadata_2025 huggingface dataset:
Ardanuç-Gevhernik Kalesi Kazı Çalışmaları
Authors: AYTEKİN Osman
Published: November 2023

Ardanuç, one of the districts of Artvin province and located at the easternmost edge of the Eastern Black Sea Region, was conquered in 1551, during the reign of Suleiman the Magnificent, and joined the Ottoman lands. Until 1878, many Turkish- Islamic works were built and put into service of the society in today’s Adakale campus under Ottoman rule. The first mosque structure all across the province of Artvin was built in 1553 by Erzurum Governor Çerkez İskender Pasha, who conquered Ardanuç Castle and as it can be understood from the foundation certificate-charter dated 1565, continuation of the service was provided by donating commercial buildings, such as dye-house and arasta (shops), for the execution of mosque services. In 2012, Adakale was registered as an urban archaeological site, and Gevhernik Castle (İçkale) was registered as a first degree archaeological site. The inner castle attracts attentions with the remains of buildings such as medieval walls and churches, in Adakale; mosques, graveyards, madrasahs, tombs, baths, fountains, mansions and many civil architectural works have survived to the present day. Having adopted the conservation plan including Adakale and the Gevhernik Castle in 2023, it has been documented as having a distinct historical significance. ”Ardanuç-Gevhernik Castle Archaeological Excavations”, initiated by the scientific team headed by Dr. Lecturer Osman Aytekin on behalf of Van Yuzuncu Yil University and with the permission and support of the Ministry of Culture and Tourism in 2021, continues without interruption and is planned to continue for many years. In the 2021 excavation season, the interior and exterior excavations of the tombs located in the graveyard of the İskender Pasha Mosque were carried out, and important scientific data was obtained about for whom the tombs were built. It is understood that all three tombs belong to Meskhetian pashas and their family members in the 17th century. Since there are no inscriptions belonging to the graves in the burial ground, a definite definition could not be made. As for 2022, the city church, located at the lowest part of the Adakale, was studied. It has become clear that the church building, which has survived only at its foundation level, was probably built in the 9th century during the time of the Bagratlı Christian administration, which was dominant in the region. Contrary to what is said, the vaulted space in the southeast corner of the church, below the floor level, was found to be a cistern rather than a tomb structure. Apart from these, cleaning works have also been started in the city bath and fountain, which are now privately owned. Adakale; with restorations of immovable cultural assets after archaeological excavations, Artvin is expected to be one of the most important cultural and tourism areas. For more detailed information, please refer to the Extended Abstract at the end of the text
TRABZON İÇ KALE KAZISI
Authors: YAVUZ Mehmet , ALNIAK Levent
Published: November 2023

Historically, the city of Trabzon consisted of three separate sections, namely the Lower Fortress, the Middle Fortress and the Upper Fortress (Inner Fortress) sections. Considering its strategic location and its status fit for an administrative center, it is highly probable that the first walled city construction was made in the Inner Fortress (Upper Fortress) section. The structural features of the walls both at the north-western and north-eastern parts of the Inner Fortress (Upper Fortress) section and the first archaeological findings confirmed this view. The first observer to mention the existence of Trabzon as Trapezus in ancient written sources was Xenophon, who returned to Greece with “tens of thousands” of soldiers in 400 BC from Persia. Based on this source Trabzon was a city intact around 400 BC, and therefore its known history dates back to 2500 years. However, the German historian Jakob Fallmerayer Pausanias, known for his work “History of the Empire of Trabzon”, argued that the core inhabited area of Trapezus was Trabzon, which still exists today, and that its foundation dated back 4500 years ago. Considering that the transition to a sedentary agricultural life was during the Neolithic period around 2000 BC, this view is likely to be accurate. Until February and August 2021, no scientific archaeological excavation or drilling work had been carried out either inside or outside the city walls of old Trabzon, which has been inhabited since ancient times. With the permission of the General Directorate of Cultural Heritage and Museums of the Ministry of Culture and Tourism, in 2021 archaeological drilling was carried out for a month in the northeastern part of the Lower Hisar in Trabzon for the first time in history, and important architectural remains from the Roman Period were found in addition to minor Hellenistic finds. Following this significant discovery, at the end of August of the same year, long-term, planned and systematic archaeological excavations were initiated at the Inner Fortress section under the presidency of Trabzon Museum and under the coordination and academic supervision of Prof. Mehmet Yavuz from Karadeniz Technical University. The third phase of these archaeological studies was carried out at the bottom of the city wall behind the Women’s Groceries Market in the Lower Hisar section, and the works that began in December 2021 continued until the end of July 2022. During the rescue excavations, the ancient harbor structure uncovered during the excavation of the construction foundation was fully unearthed. The first archaeological excavations in these three different places yielded a large number of ceramic artifacts, coins, glass, metal and bone artifacts belonging to the Roman, Byzantine, Komnenos and Ottoman Periods, starting from the Hellenistic Period. For more detailed information, please refer to the Extended Abstract at the end of the text
Inhibitors to Earth-based Materials Adoption in Urban Housing Construction: The View of Design Experts
Authors: Nwaki William , Sofolahan Onyinye , Eze Emmanuel
Published: November 2023

Earth-based materials are eco-friendly and harmless to the environment but have been neglected and relegated, and preference is given to non-sustainable and expensive conventional materials owing to certain factors. Existing studies in the Nigerian context did not consider the factors hindering the use of earthen materials in urban low-cost housing production. This study presents the outcome of examining the inhibitors to the adoption of earth-based materials in urban housing construction from the perspective of design experts in a developing country like Nigeria. Thus, it fills the critical literature gap in the Nigerian context. A well-structured quantitative questionnaire was utilised to collect data from construction design experts using the snowball sampling technique via electronic means. With a reliability index of 0.899, The gathered data were analysed using frequencies, percentages, Mean score, normalisation value technique, Mann-Whitney U test, overlap analysis, and exploratory factor analysis (EFA). It was found that the major barriers to the use of earth materials in urban housing production are (i) image and aesthetic barriers, (ii) Knowledge and resistance barriers, (iii) technology and data barriers, (iv) strength and maintenance barriers, and (v) demand and demographic barriers. More training and workshops were advocated to increase knowledge of the environmental and economic benefits of these materials among stakeholders to influence their interest and the market for earthen materials' acceptability and usage in housing production in urban areas.
IoT-based Heart Signal Processing System for Driver Drowsiness Detection
Authors: Yunidar Yunidar , Melinda Melinda , Khairani Khairani , Irhamsyah Muhammad , Basir Nurlida
Published: November 2023

Traffic accidents often result in loss of life and significant economic losses. Indonesia's high number of traffic accidents indicates the need for effective solutions to overcome this problem. Developing a drowsiness detection device is one effort that can be made to reduce accidents caused by drowsy drivers. The data obtained in this study used driver heart rate data. The drowsiness detection tool was developed using the Wemos D1 Pro Esp8266 microcontroller and MAX30102 sensor. Testing was carried out on 25 subjects under two conditions: 'Drowsy' and 'Normal.' The driver's level of drowsiness is determined based on the heart rate measured by the detection device. The Blynk application is used as a visual interface to provide notifications via smartphone if the driver is drowsy. The accuracy of the drowsiness detection tool was compared with the results obtained from the Pulse Oximeter. This research shows that the drowsiness detection tool using the Wemos D1 Pro Esp8266 microcontroller and MAX30102 sensor has an accuracy of around 98% when compared with the pulse oximeter. The Blynk application successfully sends notifications precisely when the driver is drowsy. This study highlights the potential of drowsiness detection devices to improve traffic safety and reduce accidents caused by drowsy drivers.
Enhanced IoT Solution System for Smart Agriculture in Indonesia
Authors: Hugeng Hugeng , Trisnawarman Dedi , Huntarso Axel Irving Yoshua
Published: November 2023

This innovative solution encompasses an IoT-based smart agricultural system. The system includes a solar panel power supply, a weather station (monitoring temperature, humidity, air pressure, wind speed and direction, raindrop), an air quality monitoring module (measuring NH4, CO2, and PM2.5 levels), a soil quality measurement module, a microcontroller, a GSM cellular module for internet connectivity, and an automated relay actuator for a water pump. The water pump's operation is contingent upon the soil moisture levels, ensuring efficient irrigation. The utilization of an IoT-driven smart agricultural system enables real-time monitoring of weather conditions, air quality, and agricultural soil conditions. Additionally, it facilitates the remote control of automated water pumps via smartphones—an aspect that remains unattainable within the confines of traditional Indonesian agriculture. Leveraging an Android application on smartphones, this system delivers detailed insights. To present the collected sensor data in accordance with prevailing environmental and soil states, a dedicated Android application has been developed. Moreover, this application facilitates the control of the water pump to irrigate arid soil as required. The data is transmitted via the internet to a cloud server, serving as the intermediary that receives data from the IoT system's sensors positioned at the farm.
HUBUNGAN BODY SHAMING DENGAN HARGA DIRI PADA MAHASISWA NERS DI STIKES SANTA ELISABETH MEDAN TAHUN 2022
Authors: Derang Imelda , Lilis Novitarum  , Yanti Lestari Hasibuan
Published: November 2023

Harga diri merupakan persepsi seseorang tentang bagaimana memandang dirinya sendiri, menilai diri sendiri baik secara positif maupun negatif. Orang yang memiliki harga diri tinggi (positif) cenderung percaya diri, kompeten, dan mampu mengatasi masalah hidupnya, sebaliknya jika harga diri rendah (negatif) lebih cenderung menampilkan perilaku kurang aktif, kurang percaya diri, dan tidak mampu mengekspresikan diri. Hal ini dipengaruhi oleh pengalaman hidup diantaranya tentang body shaming yang dapat mempengaruhi mental seseorang. Penelitian ini bertujuan untuk mengetahui hubungan body shaming dengan harga diri pada mahasiswa ners STIKes Santa Elisabeth Medan tahun 2022. Jenis penelitian yang digunakan adalah pendekatan cross sectional. Teknik pengambilan sampel menggunakan Simple Random Sampling, Jumlah sampel 163 orang, Analisa data menggunakan uji spearman rank. Hasil yang diperoleh body shaming tinggi sebanyak 2 orang (1,2%), sedang 129 orang (79,1%), dan rendah 32 orang (19,6%), sedangkan pada harga diri : harga diri tinggi sebanyak 11 orang (6,7%), sedang 149 (91,4%), dan rendah 3 orang (1,8%), Hasil uji statistik spearman rank diperoleh r = (0,050) dan p (value) = 0,525 (p>0,05) sehingga dapat disimpulkan bahwa tidak terdapat hubungan antara body shaming dengan harga diri pada mahasiswa, diharapkan peneliti selanjutnya dapat dikembangkan dengan menambahkan variabel yang lain untuk mencari tahu solusi untuk mengatasi harga diri yang rendah.
The Use of Allusion in Tonga Work Songs: Its Social and Economic Implication
Authors:   Kwame Nkrumah University, Lubbungu Jive
Published: November 2023

This article sets out to examine the use of allusion in selected Tonga work songs. Whereas there is extensive and impressive documentation about the Tonga people and their culture, their history, and even their literature, by authors like Elizabeth Colson, there is hardly any documentation on the use of allusion and its social implications in Tonga work songs. Therefore, this study gives utter attention to one poetic element – the allusion, in the Tonga work songs and argues that allusion reflects the Tonga people’s social and economic activities through work songs. The study mainly used the qualitative method to collect data from respondents. This article is a brain child of research work which was conducted in two ways namely, through desk research and field research in three districts of Southern Province in Zambia. A total of 35 work songs were collected through interview guide, questionnaires, and Focus Group Discussions. The study revealed that Tonga work songs help lighten the work, comment on perpetual unpalatable social tendencies, communicate values of hard work, social cohesion, and objectives and share memories of the past other than culture transmission to the young generation. The study also revealed that Tonga Work songs are rich in Poetic elements such as allusion that inculcate a sense of self-responsibility among others. The study further reveals that allusion in Tonga work songs reflects Tonga people’s past and their agricultural inclination, a reflection of Tonga’s main economic activity. What comes out of this study also is that there are hardly any allusions to Tonga’s paramountcy of chiefs like in other tribes in southern Africa.
Growth and Yields of Upland Rice (Oryza sativa L.) Applied by Synthetic Zeolite and Catfish Liquid Organic Fertilizer
Authors: Putri Mutiara , Nelvia Nelvia
Published: November 2023

The average productivity of upland rice in Indonesia is around 4.4 tons per ha, significantly lower than its potential yield of 8.5 Mg per ha. The utilization of synthetic zeolite as a soil amendment and liquid organic fertilizer (LOF) is one of the technologies that can be applied to increase the growth and yield of upland rice. This study was carried out by factorial experiment with 2 factors: synthetic zeolite application at 4 levels (0, 100, 150, and 200 kg per ha), and catfish LOF application at 3 levels (0, 200, and 400 ml per clump), and each combina- tion was repeated three times. The results showed that applying synthetic zeolite and catfish LOF at each dose had no significant effect on plant height, maximum number of tillers and productive tillers, panicle exit age, harvest age, and weight of milled dry grain per clump. The interaction of synthetic zeolite at a dose of 100 kg per ha with catfish LOF at a dose of 400 ml per clump increased the number of pithy grains per panicle by 70%, the weight of milled dry grain per clump by 68%, and the harvest index 37.5% significantly compared to control (no treatment).
Analysis of Fatigue Performance and Parameter Optimization of Single-turn Crankshaft of Submersible Diaphragm Pump
Authors: Pei Menglong , Sun Boying , Yang Ruixuan , Liu Ao
Published: November 2023

In order to improve and optimize the structure and performance of the submersible diaphragm pump, make the pump work more efficient and stable, and reduce the energy loss and noise, take the single-turn crankshaft of the submersible diaphragm pump as the research object, analyze the force of the single-turn crankshaft, establish a three-dimensional model of the single-turn crankshaft, and parameterize the key design dimensions, find the force change of the single-turn crankshaft by changing the size, and bring the changed value into the software for further analysis, and obtain the influence relationship between the key size parameters of the single-turn crankshaft on performance and stability. Finally, the single-turn crankshaft is optimized by finite element software. The results show that the force of the single-turn crankshaft can be changed through parameter optimization, which can reduce the maximum stress of the single-turn crankshaft and improve the overall safety factor, and the maximum stress of the optimized single-turn crankshaft is reduced by 16.28%, the total deformation is reduced by 15.81%, and the optimized state is more stable, and the bearing capacity and life are improved. It is believed that the parameter optimization of finite elements is obviously helpful for the improvement of single-turn crankshaft.
Research on the Application of Low Carbon and Energy Saving in Green Buildings
Authors: Dai Yahui
Published: November 2023

This article discusses the principles and recommendations for green and energy-efficient architectural design. Firstly, it is suggested to optimize architectural design and orientation to fully utilize natural resources and lighting. Secondly, using environmentally friendly and energy-efficient materials can effectively reduce energy consumption. Thirdly, by incorporating smart controls and renewable energy applications, the energy efficiency of buildings can be further improved. Additionally, strengthening organizational leadership and establishing sound mechanisms for energy-saving in construction projects, as well as enhancing energy-saving supervision throughout the entire construction process, are also necessary. Lastly, the application of low-carbon energy-saving technologies in the architectural design phase is explored. By implementing the above principles and recommendations, the development of green and energy-efficient buildings can be promoted, contributing to sustainable development.
Research on Measurement of Multi-beam Transducer Based on Analytic Geometry Method
Authors: Xu Haoxuan , Zhu Fangyan , Dai Chenghang
Published: November 2023

The ocean is inseparable from the survival and development of human beings. It not only provides rich resources for human beings, but also provides a large number of samples for human scientific research. For the efficient development of the ocean, detailed and accurate seabed topography and geomorphology information is needed as a prerequisite. In this paper, aiming at the problem of multi-beam detection system detecting full coverage water depth strip in waterway, the measurement model of multi-beam transducer under different survey lines is established. Based on the combination of numbers and shapes, firstly, this paper considering the special situation that the survey line is perpendicular to the horizontal component of the normal of the seabed slope, it is concluded that the depth of seawater is positively correlated with the width of the survey line. Secondly, when the angle of the survey line is arbitrary, and the spatial rectangular coordinate system model is established, this paper considering the law of the width of the survey line at different angles and distances. Finally, through analytic geometry method, the measuring line equations at different positions and angles are expressed in this paper, and the measuring line width is quantified according to the distance formula between two points. The results show that the coverage width is unchanged at the center of the sea area or when the direction of the survey line is perpendicular to the horizontal component of the normal of the submarine slope. The coverage width is symmetrically distributed at the survey line angle. The results show that the multi-beam transducer measurement model is effective.
Research on the Influence of Heavy Pollution Environment on Hydrophobic Substances in Silicone Rubber Materials
Authors: Yu Shumin , Xu Mingshen , Xu Ruixin , Zhang Jingzhong , Wang Shijie , Tian Jingjia
Published: November 2023

Power load forecasting is very important for power dispatching. Accurate load forecasting is of great significance for saving energy, reducing generating costs, and improving social and economic benefits. In order to accurately predict the power load, based on BP neural network theory, combined with the advantages of Clementine in dealing with big data and preventing overfitting, a neural network prediction model for large data is constructed.
Problems of Building Energy Consumption in Rural Schools in Linzhi, Tibet
Authors: Zhou Liqing , Liu Chengpeng , Wan Li , SUOLANGQUZONG  , Wang Wei , Wen Qiqi
Published: November 2023

The energy-saving research of school buildings in villages and towns in the severe cold areas of Linzhi Township has not yet been widely carried out. The energy consumption of schools in villages and towns in the severe cold areas of Linzhi is generally high, and the heating energy consumption in winter accounts for a large proportion of the energy consumption of school buildings. With the promulgation and implementation of energy-saving design standards for public buildings in schools in large and medium-sized cities, energy-saving activities have been carried out. In the severe cold area of Linzhi, there are a large number of buildings in villages and towns, with primary schools in each village, secondary schools and central primary schools in each township. The total energy consumption of village and town school buildings accounts for the majority of the total energy consumption of village and town public buildings. From this, it can be seen that studying the characteristics of village and town school buildings in the severe cold area of Linzhi and researching energy-saving design strategies suitable for their own characteristics based on the characteristics of village and town school buildings in the severe cold area are of great significance for the promotion and application of clean energy in schools in the Linzhi area.
Discussion on the Landscape Design of Urban Parks Under the Background of ' Double Carbon '
Authors: Zhang Qi , Hua Huiting , Ou Liqin
Published: November 2023

In view of the landscape design under the background of ' double carbon ', the requirements and principles of practicing ' double carbon ' action are put forward in the planning stage. Based on the existing problems of urban parks and the design idea of ' low carbon ', this study puts forward some design ideas such as carbon emission reduction, carbon substitution, carbon storage and carbon cycle, in order to provide reference value for landscape designers in urban park landscape design.
"TGT-Lcarbon" - A Non-Profit Third-party Carbon Fund Platform
Authors: Yin Siyi , Zhang Wenjing , Gao Wei , Tang Mengmeng
Published: November 2023

In the context of "carbon neutrality" and "carbon peak", energy conservation, environmental protection, and low-carbon life have become the mainstream of society. As a new force in the development of green economy, carbon trading has become an indispensable part of the financial market. There are unlimited business opportunities in the carbon market, and the good development of carbon funds is of great significance to promoting the development of China's CDM projects and enhancing the international competitiveness of the low-carbon economy. At present, government-led public welfare carbon funds are the main driving force in China's carbon financial market. Narrow financing channels have caused China's carbon financial market to face a funding gap, and there is an urgent need for social funds to participate in the carbon financial market. Therefore, this article first analyzes carbon funds and their operating methods; secondly, sorts out the existing domestic and foreign carbon fund transaction types, focusing on domestic carbon funds; and finally, in order to better serve the real economy’s low-carbon emission reduction Develop and better develop China's carbon financial market, and study the role and significance of carbon funds as media investors and financing parties in the financial system.
Preface: 2023 International Conference on Mathematical Modeling, Electronic Information and Algorithm Analysis (ICMEA 2023)
Authors: Bartholomew Pamela , Xu Hui
Published: November 2023

The 2023 International Conference on Mathematical Modeling, Electronic Information and Algorithm Analysis (ICMEA 2023) is a scientific conference, which was held on September 23-24, 2023 in Berlin, Germany. The conference is an international forum for the presentation of technological advances and research results in the fields of mathematical modeling, optoelectronic technology, signal processing, electronic information, algorithm analysis, and computer simulation. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world.

ICMEA 2023 is an opportunity for PhD students in this area to moot their dissertation works to a global audience. The key intention of this seminar is to provide opportunity for the global participants to share their ideas and experience in person with their peers expected to join from different parts of the world. This event also provides an opportunity for researchers in related fields to explore the research conducted by their colleagues in other places and to present their research findings.

Best regards,

ICMEA Conference Committees

Berlin, Germany
Research on the Development of Wordle Based on Multi-Model Analysis
Authors: Zhang Ziyue
Published: November 2023

Wordle is becoming more and more popular around the world, so it is of great significance to study its healthy development. This paper predicts the number of Wordle 's report results and predicts the percentage of attempts for different words. Firstly, this paper establishes a prediction model of the number of ARIMA report results, and analyzes the relationship between word attributes and the percentage of players in difficult mode. This article collects data on the number of Wordle 's daily reporting results from January 7 to December 31, 2022, and predicts that the number of reporting results in 2023 will be: 10220-10637. This paper constructs three indicators to measure word attributes: the number of vowel letters, the number of affixes and the number of repeated letters. Using Pearson correlation coefficient method and AIC information criterion, according to the correlation coefficient of the three indicators, it is analyzed that there is no relationship between word attributes and the percentage of players in difficult mode. Then, this paper establishes a prediction model of the distribution of the number of attempts, and accurately predicts the percentage of attempts of EERTE words. This paper constructs the data into a lexicon and quantifies the letters. Multiple linear regression equation and multiple nonlinear regression equation were established by using the number of vowel letters, the number of affixes and the number of repeated letters corresponding to each letter in the word. The average number of guessing words and variance were fitted. It was found that the fitting effect of multiple nonlinear regression was better, was 0.805 and 0.821. Finally, the related attributes of “EERIE” were counted, and its distribution percentage was obtained. The results were 0, 1 %, 16 %, 49 %, 29 % and 3 %. The model constructed in this paper can provide some theoretical support for the good development of Wordle.
Research on Express Demand Problem Based on Analytic Hierarchy Process, Entropy Weight Method and ARIMA Time Series
Authors: Yang Kecheng , Cheng Zhoukai , Tao Tao
Published: November 2023

Under the background of rapid development of express industry, this article establishes the evaluation model of station city importance and the forecast model of express transport volume by means of analytic hierarchy process, entropy weight method and ARIMA time series model, which has strong practical significance. Firstly, this article preprocess the data to get the daily receipt and shipment of each city. Then, seven indexes are selected as the comprehensive evaluation indexes of each station city, a comprehensive evaluation system based on analytic hierarchy process and entropy weight method is constructed, and the evaluation model of the importance degree of each station city is established. Considering that the number of express delivery varies greatly and irregularly, this article chooses the ARIMA time series analysis model, and determine the coefficient of the ARIMA time series analysis model through the ACF diagram and the PACF diagram, and plug the data into the prediction model to obtain the prediction result of the number of express transportation between stations and cities.
A Multi-Strategy Integrated Optimized Salp Swarm Algorithm and Its Application for Engineering Problems.
Authors: Huang Shiyi
Published: November 2023

Salp Swarm Algorithm has the advantages of few adjustment parameters and easy implementation, which has been applied in many fields, such as data mining, image processing, and engineering calculation. However, this algorithm is easy to fall into local optimization and sometimes the accuracy of optimization is not high. To solve the above problems in SSA, this paper proposes an orthogonal opposition-based adaptive slap swarm algorithm OOASSA. First, an orthogonal opposition learning strategy was introduced when updating the leader position to enhance the adequacy of global search and improve the algorithm's ability to get out of the local extreme value. Then, it was introduced adaptive inertia weight when updating the follower position and introduced an adaptive adjustment strategy in the ratio of a leader-follower number to ensure that the algorithm had a good global development ability in the early stage of iteration. Good local exploration ability in late iteration. In this paper, 10 test functions and 3 engineering optimization problems in CEC2017 are used for simulation experiments, and the proposed algorithm's global exploration, local mining, and local optimization capabilities are significantly better than many of the most advanced SSA variants.
Application Analysis of Security Technology in Computer Software Development
Authors: Lyu Sirui , Guo Haiyang , Zhang Kairui
Published: November 2023

At present, citizens benefit from the facilities provided by information network technology in all aspects of daily life. However, the particularity of the computer network environment also causes many unfavorable factors in the application of network technology. If these negative factors are not restricted, they will have a direct impact on the development of information technology industry. Therefore, creating a good business environment for this network has become a key issue in the field of computer software development. Facts have proved that computer security not only affects the economic development of enterprises, but also affects the security of information provided to users. In order to cope with these shortcomings, designers have developed many computer security tools to solve the problems of computer network operation caused by security risks.
SVM Model Against Telecom Card Fraud Using GA Optimised Ten-Fold Cross-Testing
Authors: Wei Peng
Published: November 2023

The increased number of payment methods also makes it easier for personal information to be stolen by criminals, and for criminals to take over financial payment accounts and steal money. With trillions of bank card transactions occurring every day, Credit Card Fraud Detection (CCFD) is a serious challenge, so this paper predicts "whether or not fraud occurs" by using six types of machine learning models. For problem 1, firstly, "mean, maximum, minimum, median, variance, standard deviation, quartile" are calculated for each indicator; secondly, data cleaning is carried out, and the data set is found to be free of missing values and outliers. Then the data preprocessing work was carried out, min_max normalisation and z-score standardisation were performed on the data. After that, correlation analysis was carried out, and the first four indicators were classified as negative indicators and the last three as positive indicators according to the characteristics of the indicators themselves. It can be found by calculating the Pearson correlation coefficient value after two data processing. Using the coefficient of variation method to calculate the weight of the seven "influence whether fraud" indicators. Finally, BP neural network model, decision tree model, random forest classification model, ELM model, SVM model, logistic regression model are established. For Problem 2, the four models constructed in Problem 1 are solved; to solve the BP neural network model: the data set is divided into training set and testing set according to the ratio of 6:4, and the sigmod function is used as the activation function. For BP neural network, "output >0.5" is recorded as 1, i.e. fraudulent behaviour; "output <0.5" is recorded as 0, i.e. non-fraudulent behaviour. Adjusting the learning rate and the number of iterations, the optimal average mean square error after optimal gradient descent is smaller. To solve the SVM model, the data set is divided into ten groups using the improved ten-fold cross-test, with one group as the training set and nine groups as the validation set, so as to obtain the model with the highest accuracy and the corresponding training data, and then the genetic algorithm is used to search for the optimisation of the kernel parameters in the SVM model on this basis. To solve the decision tree model, the training set and prediction set are divided into 7:3 and solved, and the number of leaf nodes is optimised. Solve the random forest classification model, divided into training set and prediction set according to 7:3 and solved, for similar accuracy choose the random forest classifier when the decision tree is less.
Stability Study of Event Dynamic Systems Based on Discrete Mathematical Random Variable Modeling
Authors: Yang Xueji
Published: November 2023

This project intends to consider the stability of a nonlinear control system with unknown dynamics. The system is controlled systematically by using the reverse step method based on Lyapunov's stability principle. This paper also gives the conclusion that when the control law is in a steady state, the output signal in this state will reach uniform boundedness or asymptotic convergence. Finally, a numerical simulation is carried out through an example, and the results show that the algorithm is effective.
A Technical Study of Sdgs-Based Prioritization and Network Construction
Authors: Luo Weiqi
Published: November 2023

The 17 Sustainable Development Goals are a blueprint for a better and sustainable future for all. In order to achieve these 17 SDGs faster and to explore the relationship between these SDGs, this study prioritizes among the SDGs and develops several models to address these issues. First, this study identifies priorities based on the SDGs and the network structure that effectively drives the work of the United Nations. Based on this, each SDG was prioritized using the DEMATEL-ISM model. Second, to more clearly demonstrate the interrelationships among the 17 SDGs, this study combines GRA (gray relational analysis) and ISM (explanatory structural model) to propose a coupled GRA-ISM model to construct a relational network of the 17 SDGs. Then, this study assumes that one of the SDGs has been achieved, and using the above model, the remaining 16 SDGs are re-networked and given a new priority order. Finally, the model developed in this study is useful for the United Nations in making decisions on the path to achieve the SDGs.
Prediction of Wordle Puzzles Based on Neural Networks and K-Means Improved Models
Authors: Qiu Zihong , Duan Chengbin
Published: November 2023

Wordle is an online word puzzle game that gained viral popularity in January 2022. The goal is to guess a hidden five letter word. In order to study the distribution of the reported results and the difficulty of the words, based on BP neural network theory, combined with the advantages of Genetic Algorithm in Stability and speed, a neural network prediction model is constructed and the model can be used to predict the percentage distribution of the number of player guesses for a given word on a given number of days. In addition, a Canopy-Kmeans-based word difficulty classification model was further developed. It can be combined with the previous neural network model to determine whether the difficulty of guessing a given word is easy, normal or hard.
Development of an automatic tracking model for seismic stratigraphic correlation based on information entropy theory
Authors: Du Zhongsheng , Guo Zhiyu , Liu Yixuan , Chen Yilin , Li Yuxin , Li Haojin
Published: November 2023

Accurate stratigraphic information is the basis of seismic data interpretation and reserve prediction. Based on this, this paper firstly establishes a grey model based on information entropy, uses particle swarm optimization technology of neural network to analyze and track the influence of each factor on the degree of seismic hazards, and gets the weight of each factor on the degree of occurrence of geologic hazards through the model by using the matlab software, and secondly, uses the theory of information entropy to determine the evaluation system and its grading standard, and finally evaluates the comprehensive evaluation of fuzzy through the grey clustering model. bp neural network. The development and research of automatic tracking model of seismic stratigraphic correlation based on information entropy theory can greatly improve the efficiency and accuracy of seismic data interpretation, which is of practical value and significance for seismic data interpretation.
Research on Outcome Prediction Model Based on LSTM Neural Network Model: An Example of Wordle Game
Authors: Feng Yuan , Song Xinjie
Published: November 2023

Wordle is popular worldwide, and predicting the results of the game has attracted many people's attention. Based on this, this article uses the LSTM neural network model, information entropy theory to predict and analyze the number of gamers and word difficulty of Wordle's daily words. The results indicate that: (1) The number of players in the Wordle game shows a daily decreasing trend; (2) The information entropy of words with two or more duplicate letters is lower than words without duplicate letters; (3) There is no significant correlation between the information entropy and the pass rate in the Wordle difficult mode.
Research on Automatic Pricing and Replenishment Strategy of Vegetable Commodities Based on Fourier Series Fitting and Linear Programming
Authors: Zhang He , Tian Shaokai , Liu Liguo , Zhao Yufan
Published: November 2023

Vegetable goods are a common category of goods sold in superstores. In order to determine the relationship between commodity price and sales quantity, and develop a reasonable replenishment and pricing strategy, this paper firstly uses the curve fitter linear regression in the MATLAB toolbox to analyse the relationship between total sales volume of different categories and cost plus pricing, and secondly, uses the curve fitter Fourier series in the MATLAB toolbox to fit the sales volume curve in June and calculates the degree of fit for validation to predict the sales volume of each vegetable category in the first week of July, calculate the daily replenishment volume, and determine the pricing of each category using the results of linear regression. Vegetable category sales, calculating daily replenishment, and using linear regression results to determine pricing for each category. Then, we consider the pricing and replenishment strategy when the total number of single items is restricted, and construct a linear programming decision optimisation model with single items as the main body, taking the replenishment quantity of single items as the decision variable, the restriction of the total number of single items, the minimum display quantity and the satisfaction of category demand as the constraints, and the maximum revenue of the superstore as the objective function, and then we construct the linear programming decision optimisation model, and find out the pricing and replenishment quantities for a total of 28 individual items as well as for each single item.
Research on Predicting Wordle Results
Authors: Zhong Qiuping , He Mingfei
Published: November 2023

Worldle is a very popular puzzle game, but the number of players is decreasing. In order to reduce this phenomenon, this paper intends to solve it through relevant methods,such as ARIMA model, Credibility, Multicollinearity model; Ridge regression algorithm; Fuzzy synthetic evaluation method. First, the data in the game is cleaned up, mainly including the modification of the number of letters, the number and percentage of special letters in the word competition result report, etc. Secondly, the use of the establishment of the relevant model, and to be analyzed related factors and circumstances, to obtain clear results. It is worth noting that the model itself has certain advantages and disadvantages. Finally, based on the above steps, put forward four feasible suggestions, hope that the game can be adopted, the game complement.
Research on Forecasting Short-term Passenger Flow of Subway Based on Deep Neural Network
Authors: Ha Jinbing , Zhao Zhengguang
Published: November 2023

With the rapid development of urbanization, a large number of people have poured into cities, which makes the traffic congestion problem increasingly serious. As a stable, efficient, safe and environmentally friendly public transport, subway has gradually become the first choice for residents to travel by bus. The rapid increase in the number of passengers has caused great pressure on the quality of subway operation and service. Therefore, how to accurately predict the passenger flow of the station at a certain time in the future and let the subway operation department make the corresponding operation plan in advance according to the predicted passenger flow is of great significance to improve the service quality of subway operation. Under this background, this paper summarizes the existing short-term passenger flow forecasting methods at home and abroad, and puts forward the application of deep neural network method in the field of short-term passenger flow forecasting of urban rail transit according to the advantages and disadvantages of different forecasting methods. Taking the short-term passenger flow forecast of Nanjing subway as an example, the original credit card data is preprocessed to obtain passenger flow data, and the temporal and spatial distribution law of historical passenger flow is studied, and the LSTM prediction model and CNN-LSTM combined prediction model are established, which improves the prediction accuracy of short-term inbound passenger flow of rail transit.
Analysis of the Design of Wearable Wireless Biosensors
Authors: Liu Zhenxiao
Published: November 2023

With the increasing health awareness and diversification of lifestyle, wearable biosensor systems have gradually become an effective tool for monitoring individual physiological parameters. This study introduces an innovative design to address this need, which aims to monitor important physiological indicators such as heart rate, body temperature and exercise status. The system integrates a heart rate sensor (MAX30101), a body temperature sensor (DS18B20), an acceleration sensor (MPU6050), a microcontroller (ESP32) and a Bluetooth low energy module (HC-06), and is powered by a rechargeable lithium battery (18650 battery). This study adopted a system design and hardware development approach, focusing on sensor performance optimization, power consumption control. The hardware connection method of the system is described in detail, and the experimental verification is carried out. Based on the experiments, a wearable biosensor system that can accurately monitor the user's heart rate, body temperature and motion state has been successfully designed. The low-power design of the system ensures prolonged wear with potential medical, sports health and quality of life monitoring applications. These results provide a powerful tool for individualized health management, providing users with real-time knowledge of their physiological state, offering a useful reference and enlightenment for the development and application of wearable biosensor technology.
Analysis of Modeling Methods for Different Types of Channels
Authors: Tang Ao
Published: November 2023

Contemporarily, channels are widely used in various fields. This study aimed at introducing different advanced modeling methods for different types of channels. It mainly introduces the method of modeling wireless channels, compositing channels and AWGN channels and the characteristics of each are summarized and compared. The development of channel modeling has gone through an evolutionary process from empirical models to statistical models, physical models, and evolutionary models. As communication technology continues to advance and application requirements continue to change, channel modeling will continue to develop, providing more accurate and practical model tools for the design and optimization of communication systems. This study analyzes the modeling methods for three different channels according to background introduction, theoretical research, result analysis, and performance comparison. For these three different channel modeling methods, this study obtained a very satisfactory fit, but there are still some errors, which proves more advanced algorithms for different channels are still waiting to be developed.
The Characteristics of Early Childhood Education in Spain
Authors: Zhang Ruzhen
Published: November 2023

Spain is a key member of the European Union, which stands out with its high enrollment rates and comprehensive early childhood education system among EU countries. Early childhood education (Educación Infantil, 0-6 years old) in Spain is a non-compulsory stage in the country’s education system. Over 95% of Spanish children start school at the age of 3, and the enrollment rate of children aged 3 to 5 is close to 100%. The study explores the unique features of early childhood education in Spain, emphasizing its internationalized educational framework, comprehensive educational objectives and content, relatively well-developed welfare system, as well as the emphasis on children’s foreign language proficiency and digital literacy, provide valuable insights for the development of early childhood education in other countries.