bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantification of household electricity consumption for supporting energy efficiency of urban metabolism: Material flow analysis
Authors: Sharif Ali Sharif Shofirun , Kasavan Saraswathy , Razman Muhammad Rizal , Awang Azahan , Zarco-Periñán Pedro J.
Published: August 2024

Despite growing public, academic, and government awareness of the energy consumption issue, there is still little research on the scales and patterns of Household Electricity Consumption (HEC), particularly in developing countries such as Malaysia. Therefore, the present study examines the status of HEC using electricity consumption breakdowns, key performance indicators (KPIs) for electricity consumption and Material Flow Analysis (MFA) by showing potential electricity savings, cost savings, and emission reductions using 5-star energy efficiency appliances. This study used a face-to-face survey of 400 participants in Seremban, the capital city of Negeri Sembilan. The study found that the majority of respondents (49%) consumed about 300-600 kWh/month of electricity with an estimated cost of MYR231.80 per month. Additionally, the study found that households in flats recorded lower average electricity consumption (460.16 kWh/unit) than bungalow households (885.92 kWh/unit) due to respondents’ socio-economic status, the physical size of the houses and the number of appliances owned. The study also revealed that the average energy consumption was higher for refrigerators (9.6 kWh/day) and air conditioners (4.5 kWh/day) due to the use of large amounts of energy to maintain a steady temperature. The material flow analysis shows that energy savings were approximately 22.53%, potential cost savings were MYR12,676.15 per month, and the potential reduction emissions were about 100,759.92 kgCO2e for one month with using EEA compared to non-EEA. The present study empirically discussed the significance of HEC quantification and the opportunity for energy efficiency is critical as a solution for sustainable urban metabolism in a developing country.
Menelisik Usaha Pemerintah Dalam Memajukan Aparatur Sipil Negara Bertaraf Internasional
Authors: Wahyono Agus
Published: August 2024

Latar Belakang: Pola pikir dan paradigma manusia yang berubah akibat perkembangan teknologi berpengaruh pada pengembangan kompetensi pekerja pemerintah. Pekerjaan di pemerintahan mulai berfokus pada digitalisasi, seperti keininan untuk mewujudkan SMART ASN. Pemerintah berupaya mewujudkan tersebut melalui upaya reformasi birokrasi. Penelitian ini bertujuan untuk memahami kondisi birokrasi pemerintahan yang bertujuan memajukan setiap pekerja pemerintahan agar bertaraf Internasional. Metode: Penelitian menggunakan metode pendekatan desk study dengan data sekunder yang berasal dari buku, literatur berupa prosiding dan/atau jurnal, serta laporan laporan terpilih lainnya yang dianalisis melalui pendekatan deskriptif analitis. Data primer penelitian ini adalah hasil pengamatan secara langsung yang nantinya akan dianalisis secara penafsiran dan deskriptif. Temuan: Penelitian yang dilakukan ini bertujuan untuk mewujudkan tata kelola pemerintahan yang baik (good governance) dengan birokrasi pemerintah yang profesional, berintegritas tinggi, pelayanan masyarakat, dan abdi Negara. Langkah yang dilakukan oleh pemerintah ini cukup beragam, seperti usaha e-government dengan tujuan memajukan akses digitalisasi dan komunikasi antar pegawai pemerintah dan masyarakat. Kesimpulan: Pemerintah Indonesia telah memasuki fase usaha memajukan kepemerintahan lokal melalui berbagai pegadaan kebijakan. Kebijakan e-government yang berlanjut dengan  jaringan telekomunikasi, portal pelayanan publik, organisasi untuk mengelola dan mengolah informasi, dan infrastruktur dan aplikasi dasar merupakan pilihan pemerintah Indonesia. Dengan kata lain pemerintah telah berusaha mengembangkan pemerintahan bertaraf Internasional.
Green Logistics Management Practices: A Study on the Hospitality Sector
Authors: Tuan Phan Kim
Published: August 2024

This study aims to assess the effects of the factors on green logistics management practices in the hospitality sector. A quantitative methodology is applied to evaluate a particular population or sample, and research instruments with PLS-SEM are used in this study. Our sample and data were collected via an online survey focusing on managers at hotels in Da Nang city. The results show that GLMP practice in hotels is influenced by the following five factors: government environmental regulations, economic pressure, supply chain collaboration, internal green logistics awareness, and customer pressure. In addition, the result also reveals that government environmental regulations can affect increasing the green logistics management practice through customer pressure, supply chain collaboration, and internal green logistics awareness.
Tri Hita Karana-Oriented Ethnomathematics Learning Resources for Grade Vii Students in Buleleng, Bali-Indonesia: An Ethnographic Study
Authors: Suharta I Gusti Putu , Parwati Ni Nyoman , Astawa I Wayan Puja
Published: August 2024

This study aims to describe the source of THK-oriented ethnomathematics learning for grade VII Elementary Education students in Buleleng Regency-Bali Indonesia. The type of research used is qualitative with an ethnographic approach. The subjects of the study were mathematics teachers who teach in grade VII. Data collection techniques used documentation, open questionnaires, and semi-structured interviews. Data analysis used inductive thematic. The results of the study are ,the sources of THK-oriented ethnomathematics learning that can be used in mathematics learning for grade VII students in Buleleng Regency are determining holy days, menyama braya, megoak-goakan games, Dewa Yadnya ceremonies, Bhuta Yadnya ceremonies, subak systems, traditional Balinese buildings, and tumpek ceremonies. The use of THK-oriented ethnomathematics as a learning source has the potential to increase student interest, as well as foster awareness that many activities or objects related to socio-cultural-religious issues contain mathematical ideas.
Validity of Contracts in the Digital Era in Indonesia
Authors: Irianto Sigit
Published: August 2024

The era of digitalization has brought influence and changes to the contract law order in Indonesia. Contract law is no longer implemented conventionally by meeting the parties face to face in planning or making contracts, but with digital contracts, everything can be realized and legal. Regulations regarding digital contracts have been regulated in Law Number 1 of 2024 concerning Law Number 19 of 2016 and Amendments to I1 of 2008 concerning Information and Electronic Transactions. However, basically digital contracts still cannot leave the conventional Civil Code. The writing method in this article uses a normative juridical method, with a statutory regulatory approach, conceptual approach, philosophical approach, and case approach. This approach method will provide a comprehensive picture from various perspectives and is supported by the Constitutional Court decision Number 20/PUU-XIV/2016. Based on the results of the study, digital and conventional contract law continue to work side by side, and the two contract models can complement each other and can be realized in the implementation of agreements. The validity of the contract basically has similarities with the variations developed in the Information and Electronic Transactions Law, namely the confirmation in Article 47 paragraph (3) with the addition of aspects of price and costs, contract cancellation, hidden defects and legal options in resolving transaction disputes. electronic. However, there are differences in the meaning of hidden defects in the Information and Transaction Law, and it has also regulated several variants regarding electronic contracts and conventional contracts in Article 46 paragraph (1).
The Journey of Emotional Resilience: A Sociopsychological Perspective on Satyavathi in Utkarsh Patel's Novel
Authors: Kumari Shail , Ali Zeeshan
Published: August 2024

Emotions play a profound role in shaping human experiences, influencing personal growth, and fostering resilience in challenging circumstances. This research explores into Utkarsh Patel's novel "Satyavathi," focusing on the central character, Satyavathi, and her transformative journey of emotional resilience. By adopting a socio-psychological lens, the study aims to unravel the complex interplay between social factors and individual psychological processes in Satyavathi's life. The research explores Satyavathi's emotional struggles as she navigates through life, uncovering the sources of resilience that enable her to persevere in the face of adversity. It examines the significance of her emotional support network, self-identity, and inner strength in fostering emotional resilience. The analysis of "Satyavathi" provides valuable insights into emotional resilience, empathy, and emotional intelligence amidst diverse social and cultural factors. It emphasizes the significance of emotional resilience as a coping mechanism and highlights the potential for personal growth and transformative change in challenging circumstances. Utkarsh Patel's novel addresses the complexities of emotional experiences and their impact on personal development and resilience in the face of life's hardships. With its deep weave of the human mind, the story is still immensely relevant today.
The Riddle of Life
Authors: AL-Sarairah Dina Abd Elmahdi Ahmad
Published: August 2024

“The Riddle of Life” is a manifestation of my psychological suffering after I have been separated by internal force till, I find home with myself. I used classical wisdom and aligned them with the characters. Over time I sink deeper into myself to signpost my road to a stable life. My bequeathed is to know yourself.
The Essence of the Implementation of Subsidized Fertilizer Distribution Based on the Regulation of the Minister of Trade in the Jurisdiction of South Sulawesi
Authors: Rahman Sufirman , Mas Bastian , Husen La Ode , Hidjaz Kamal
Published: August 2024

The distribution of subsidized fertilizers in the jurisdiction of South Sulawesi is a strategic effort by the government to increase agricultural productivity and national food security in accordance with the Regulation of the Minister of Trade Number 17/M-DAG/PER/6/2011 Article 2 concerning the Procurement and Distribution of Subsidized Fertilizers for the Agricultural Sector. This research aims to evaluate the implementation of the policy and identify the obstacles faced in the field. Based on the analysis, it was found that the implementation of subsidized fertilizer distribution experienced various problems, including delays and irregularities in distribution, quota deviations by farmers and distributors, and lack of understanding of farmers' procedures. Factors affecting these constraints include ineffective coordination and communication, poor logistics infrastructure, and weak supervision and law enforcement. To overcome this problem, it is suggested that there should be improvements in coordination between parties, improvement of logistics infrastructure, strengthening supervision and law enforcement, as well as intensive socialization and the use of information technology in distribution monitoring. With these steps, it is hoped that the policy goals of subsidized fertilizer distribution can be optimally achieved, support agricultural productivity, and ensure national food security.
Transforming Financial Futures: The Impact of Family Economic Education and Self-Efficacy on Student Economic Behavior Through Economic Literacy
Authors: Kurniawan Riza Yonisa , Kamalia Putri Ulfa , Ghofur Muhammad Abdul , Griselda Putri Elok , Khoo Yin Yin
Published: August 2024

The objective of this study is to examine the influence of family economic education and self-efficacy on economic behavior, while considering economic literacy as a mediating factor. A total of 172 students from three East Java State Universities were included in the study. Questionnaires were given at these universities to collect data. Data analysis was conducted using Warp PLS software, employing Analytic Structural Equation Modelling (SEM). The results demonstrate that providing family economic education has a substantial and beneficial impact on individuals' economic behavior. Similarly, self-efficacy and economic literacy have significant and favorable effects on economic behavior. Furthermore, the effect of learning on the topic of family economics and the belief in one’s ability to apply knowledge of economics also have a positive effect. Indirect effects show that family economic education has a large positive effect on behavioral economising through enhancing economic knowledge. Besides, self-efficacy also exerts a positive impact on economic behavior through economic literacy. These results underlined the potential of family economic education and self-efficacy as the efficient tools to improve economic behavior by increasing the level of economic literacy.
Waste Reduction and Community Empowerment: Assessing the Effectiveness of the Gema Tasamara Program in Takalar Regency
Authors: Pratama Muhammad Fathurahman , . Sangkala , Lambali Suryadi
Published: August 2024

This study aims to analyze the effectiveness of the implementation of the Gema Tasamara program in Takalar Regency. Using a qualitative approach, the researchers conducted in-depth interviews and analyzed archival records to understand the implementation process. The results show that the implementation of the Gema Tasamara program has demonstrated policy accuracy, with the establishment of the Tasamara recycling center contributing to the reduction of waste accumulation along the main roads and temporary disposal sites. However, the management of the recycling center has not been optimal, with issues such as unclear levies affecting its sustainability. The government has also conducted socialization on waste sorting to promote a culture of clean and healthy living among the community.
The Impact of Bonus Mechanisms, Tunneling Incentives, and Good Corporate Governance (GCG) on Transfer Pricing Activities
Authors: Rusydi M.Khoiru , Widya Areta , Larasati Wahyu Kartika
Published: August 2024

This study aims to analyze the transfer pricing used by companies as a technique to save taxes and analyze the effect of bonus mechanisms, tunneling incentives, and good corporate governance on transfer pricing activities in multinational companies listed on the Indonesia Stock Exchange. The data for this study were obtained from multinational companies in Indonesia listed on the Indonesia Stock Exchange from 2015 to 2020, with data collection techniques using database collection techniques. The population of this study were 18 companies so that 90 observations were obtained. The sampling technique in this research is purposive sampling. This study uses secondary data, namely annual reports and financial statements.The results show that the bonus mechanism has no effect on transfer pricing practices, and this study also shows that tunneling incentives have no effect on transfer pricing practices, but this study shows that good corporate governance has a positive effect on transfer pricing aggressiveness activities. This research contributes practically in providing information to company management for consideration in implementing transfer pricing and for the Director General of Taxes to anticipate the implementation of transfer pricing for multinational companies.
Digital Divide and Academic Performance of Students in Educational Institutions in Ilave- Peru
Authors: Hurtado-Arhuata Edwin-Jhonn , Huanca-Rojas Lupe-Marilu , Flores-Mamani Emilio , Paredes René Paz , Yarahuaman-Gonzales Soledad-Consuelo , Quispe-Cansaya Edwin-Abdón , Pedro- Basilio Tapia-Espinoza , Apaza-Chino Julian
Published: August 2024

During the pandemic, governments implemented virtual education to prevent student dropout and the loss of the academic year due to the digital divide in the educational field. The objective of this study was to determine the relationship between digital divides and academic performance under the "Aprendo en Casa" strategy. The research design was non-experimental, cross-sectional and correlational; The representative sample was made up of 476 students to whom a survey was applied. Among the most relevant findings, it was highlighted that most students lack adequate housing for better academic performance, as well as technological equipment with sufficient memory and inefficient connectivity due to low broadband capacity. Therefore, it is concluded that there is a significant association (p value < 0.005) between the digital divide and students' academic performance, reflected in socioeconomic aspects such as inappropriate housing, equipment with capacity limitations and inefficient connectivity, which has a negative impact on academic performance.
Antifungal susceptibility and speciation of Candida isolated from blood at a tertiary care centre
Authors: Prajapati Jagruti , Shah Arpita , Parmar Hemali , Duttaroy Bithika
Published: August 2024

There has been a rise in the incidence and prevalence of fungal infections worldwide, especially by Candida spp. leading to significant morbidity and mortality. Early recognition of Candida bloodstream infection has been associated with improved outcome in patient care. Hence, the present study was carried out to determine the distribution of the Candida species that causes candidemia as well as its antifungal susceptibility pattern in the hospital. A total of 8,087 blood cultures received from various clinical departments of a tertiary care centre were processed via the Automated blood culture system BACTEC FX40 or manually as per standard protocol in the Department of Microbiology from January to December 2022. Isolated Candida spp. were identified using biochemical tests and CHROM agar. Antifungal susceptibility was performed and interpreted as per Clinical and Laboratory Standards Institute guidelines. A total of 2,010 blood cultures showed a positive culture growth of microorganisms, out of which, Candida spp. was isolated in 123 blood cultures (6.11%). The Neonatal Intensive Care Unit accounted for the isolation of 78.8% of Candida spp. C. krusei was found to be the most common isolate 36.5% followed by C. albicans (21.2%), C. glabrata (19.5%), C. parapsilosis (13.8%) and C. tropicalis (9%). Voriconazole was found to be the most effective antifungal agent, with 81.3% of Candida spp. showing susceptibility to it, and was found to be the most effective antifungal agent. Non-albicans Candida spp., C. krusei was found to be the predominant isolate in the present study. The neonatal age group was the most commonly affected age group in candidemia. It is advisable to monitor the changing trend of Candida species in particular, geographical area to get an idea about prevalent species and their antifungal susceptibility pattern for choosing empirical therapy and better patient management
AMELIORATION OF ALUMINIUM FLUORIDE TOXICITY BY ALOE VERA ON BLOOD PARAMETERS IN MALE ALBINO RATS
Authors: Kusum Kushwah  , Akansha Rao  , Dharmendra Pratap Singh
Published: August 2024

It is suspected that drinking water containing fluoride (F) and aluminum (Al) results in negative health effects in the human and animals. Its toxic effect in the especially on blood, brain, liver, and kidney. In this investigation, the effect of AlF3 blood disease was noted. Albino rats were treated either with WHO recommended or slightly higher F and Al levels in drinking water. Treatment solutions contained 0.05–10.0 mg/L of F, and 0.08–10.0 mg/L of Al, and the treatment period was 45 days. Aloe vera gel (Aloes) is a member of the family Liliaceae that is used as herbal or medicine in many cultures for different purposes. The present study was designed to observe the role of Aloe vera gel on blood parameters in rats. The present study was designed to assess the ameliorative effect of Aloe vera gel on aluminium fluoride induced toxic changes in blood parameters of albino rats. The present study was carried out 60 male albino rats that were randomly divided into three groups consisting of 20 rats in each group. Aluminium fluoride was gavages per orally using distill water as vehicle 200mg/kg b. w. to group II and Aloe vera 300mg/kg b. w. in distilled water was given along with AlF3 to group III for 45 days to study of ameliorative effects group I is a control group. Ten rats from each group were sacrificed at sixteenth and forty sixth day night interval. Entire changes were observed in blood cells. The haematological parameters TEC, Hb. Conc., MCV significant decrease treated with AlF3, and TLC, PVC, MCH, MCHC and ESR significant increase after 45 days treated with AlF3 compared with the control group. Treated with AlF3 along with Aloe vera gel all parameters significant increased compared with the control group. These results showed that Aloe vera gel have haematoprotective effects in experimently induced AlF3 rats. This study concluded that Aloe vera gel has haematoprotective effect against aluminium fluoride induced haematotoxicity.
Steering towards the Savvy: Students’ Interpretations of Intercultural Competence and their Intercultural Learning in EFL Classrooms
Authors:   King Mongkut’s University of Technology Thonburi, Rangsarittikun Ronnakrit
Published: August 2024

In the twenty-first century, the teaching and learning of foreign languages (FL) has shifted towards providing English as a foreign language (EFL) learner with the necessary skills in a cross-cultural encounter widely known as intercultural competence. Based on the notion that one's intercultural savvy depends on having a clear conception of what intercultural competence involves, the study aimed to explore Thai students’ interpretations of intercultural competence (IC). The study was carried out through interviews with 20 Thai undergraduate students from two Thai universities in Bangkok. All participants took part in both one-on-one and group interviews. The study used Byram’s (1997) model of intercultural communicative competence (ICC). The findings show that the participants had little understanding of the concepts underlying IC, and how students perceived IC was essentially influenced by their intercultural learning experiences in their classrooms. Overall, the findings of this study offered a wide range of recommendations, specifically regarding classroom practices for intercultural learning.
Efektivitas dan Kontribusi Hasil Pengelolaan Kekayaan Daerah yang Dipisahkan terhadap PAD Kabupaten dan Kota di Jawa Timur
Authors: Barep Setiaji  , Badrus Zaman  , Linawati
Published: August 2024

Abstract : This research is motivated by the problem of Realization of Separated Regional Management Wealth Results (RSRMWR) in East Java which has experienced fluctuations over the last three year period. Because the decline could result from less than optimal management of the business entity, it is estimated that the Regional Owned Enterprises (ROE) sector will become a business entity that always suffers losses and burdens the Regional Revenue and Expenditure Budget (RREB). It is expected to contribute to Regional Original Income (ROI), but in the field more grants flow from the RREB to ROE, while a small share of profits from ROE is set aside for ROI. The research aims to determine and analyze the effectiveness and contribution of RSRMWR to ROI. The research approach uses quantitative causality. The type of data used in this research is secondary data sourced from djpk.kemenkeu.go.id, the analysis method used is multiple linear regression analysis. The results of this research show that partially and simultaneously the effectiveness of RSRMWR and the contribution of RSRMWR do not have a significant effect on the ROI of Regencies and Cities in East Java in 2021-2023. 
Abstrak : Penelitian ini dilatarbelakangi oleh permasalahan realisasi Hasil Kekayaan Pengelolaan Daerah Yang Dipisahkan (HPKDYD) di Jawa Timur yang mengalami fluktuasi selama periode tiga tahun terakhir. Sebab turun bisa dari pengelolaan badan usahanya kurang maksimal, diperkirakan sektor BUMD menjadi badan usaha yang selalu rugi serta membebani APBD. Diharapkan memberikan kontribusi untuk Pendapatan Asli Daerah (PAD) namun di lapangan lebih banyak hibah mengalir dari APBD untuk BUMD, sedangkan sedikit bagian laba dari BUMD yang disisihkan untuk PAD. Penelitian bertujuan untuk mengetahui dan menganalisis efektivitas dan kontribusi HPKDYD terhadap PAD. Pendekatan penelitian menggunakan kuantitatif kausalitas. Jenis data yang digunakan dalam penelitian ini data sekunder bersumber djpk.kemenkeu.go.id, metode analisis yang digunakan adalah analisis regresi linier berganda. Hasil penelitian ini menunjukkan bahwa secara parsial dan simultan efektivitas HPKDYD dan kontribusi HPKDYD tidak berpengaruh signifikan terhadap PAD Kabupaten dan Kota di Jawa Timur tahun 2021-2023.
Svenskundervisning i språkligt heterogena klasser – lärares uppfattningar om språk och social hållbarhet
Authors: Kuksa Katerina , Lyngfelt Anna , Ljung Egeland Birgitta
Published: August 2024

Tidigare forskning visar att lärares uppfattningar om vad, hur och varför något ska läras har betydelse för utformningen av undervisningen och för elevernas lärande. Syftet med artikeln är därför att bidra med kunskap om hur mellanstadielärare ser på sin undervisning i svenska i språkligt heterogena klasser, och hur de motiverar sina val utifrån uppfattningar om inkludering och social hållbarhet. Genom associationsintervjuer har sju lärare erbjudits möjlighet att resonera om sin undervisning utifrån ett antal ord, som kan sättas i förbindelse med varandra. Orden är: andraspråkselev, samarbete, språkundervisning, språkutveckling, ansvar, inkludering och social hållbarhet. Resultaten visar att svensklärarna upplever stora svårigheter att stötta sina elevers språkutveckling på ett professionellt sätt. Att anpassa undervisningen och samtidigt inkludera alla i klassrumsarbetet, innebär en utmaning för lärarna och ställer frågan på sin spets om hur arbete med social hållbarhet kan främjas.
Teaching Swedish in linguistically heterogeneous classes: teachers' beliefs about language and social sustainability
Previous research has shown that teachers' beliefs about what should be learned, how something should be learned, and why, is important for the design of teachers' teaching and students' learning. The purpose of this article is therefore to contribute with knowledge about how teachers in years 4-6 view their teaching of the subject Swedish in linguistically heterogeneous classes, and how they justify their choices based on beliefs about inclusion and social sustainability. With the help of association interviews, seven teachers have been offered opportunities to reason about their teaching based on a number of words, which can be connected to each other and evoke associations with relevance to the teachers' teaching. The words used are the following: second language student, cooperation, language teaching, language development, responsibility, inclusion and social sustainability. The results show that teachers in Swedish experience difficulties in supporting their students in a professional way, i.e. that individual students and student groups are supported based on the language needs they have to be able to follow the classroom teaching. At the same time, adapting the teaching for certain students and groups, and including everyone in the classroom work, means a challenge for the teachers and raises the question of how work with social sustainability can be promoted.
Analysis of Momentum in Tennis Matches Based on Ensemble Learning
Authors: Gong Huanyu , Guo Xuanxuan , Gao Zhuohui
Published: August 2024

In tennis, player performance is often attributed to "momentum," pivotal for game control. We analyzed tennis rules, extracting performance indicators such as point differentials, dynamic scoring, and serving advantages. Utilizing a Random Forest model with player performance as the dependent variable, we mapped features to momentum and determined feature importance, achieving an AUC of 0.8796. We then introduced the Comprehensive Ability Volatility Index (CVI) based on factors like serve win rate and breakpoint success rate, identifying match-turning points. To capture these turning points, we integrated momentum, player fitness, and overall strength into an XGBoost model, which yielded an AUC of 0.8716. The model's feature importance output guided concise recommendations for strategic decision-making. Our research offers comprehensive strategies for athletes and coaches to consider momentum, physical fitness, and other match factors, enhancing guidance for daily training and match adjustments.
Machine Learning-Based Tennis Match Performance Prediction Model
Authors: Zhou Yiyang , Chen Xingyu , Wang Zijin
Published: August 2024

The paper mainly builds a machine learning model for tennis match score prediction and conducts significance analysis on the effects of concomitant conditions using PSM. Firstly, the paper constructed a set of new metrics system, including whether the athlete is on the serve side, his/her personal skill, the level of fatigue, and his/her mentality during the match, tested the significant effect of these metrics on the model prediction by binary logistic regression, and used various machine learning model such as XGBOOST, SVC, LGBM to build the prediction model. Then, the paper trained an LGBM model based on the tennis match data set and improved the metrics system to realize the dynamic evaluation of players’ real-time performance, i.e., “momentum.” Then, in order to prove that players’ fluctuations and successes in the game are not random and that the role of "momentum" in the game really exists, the paper analyzes the concomitant conditions of scoring fluctuations using a counterfactual analysis framework and a propensity score matching algorithm and argues that the essential conditions have a significant effect on players’ performances by comparing the T-stat values of different core explanatory variables, which ultimately proves and further explains the importance of the role of "momentum" in the game’s outcome.
Research on Risk Assessment and Underwriting Decision Making Based on ARIMA Model
Authors: Liu Guanyu
Published: August 2024

Addressing the critical challenge of extreme weather events, this study introduces a comprehensive model for enhancing insurance underwriting strategies through predictive analytics and risk assessment methodologies. Utilizing an integrated approach that combines Autoregressive Integrated Moving Average (ARIMA) for forecasting extreme weather occurrences, Fuzzy Comprehensive Evaluation for assessing regional payment capabilities, and Monte Carlo simulations for detailed risk quantification, the re-search aims to refine the insurance industry's capacity for anticipating and mitigating financial losses. A systematic clustering analysis further segments regions based on their risk profiles, allowing for tailored insurance premium settings and underwriting decisions. Findings from the application of this model across diverse geographical areas underscore the potential for significantly im-proved risk management and economic resilience in the insurance sector. Through detailed statistical analysis and predictive modeling, the study demonstrates the importance of advanced analytical frameworks in adapting to the evolving dynamics of climate risk.
Research on the Impact of Sex Ratio Changes on the Population Dynamics of Lamprey Based on the Lotka-Volterra Algorithm
Authors: Cheng Binglin , Wang Wenchao , Lei Xiaohao , Ma Suien
Published: August 2024

This study employs mathematical modeling to investigate the impact of sex ratio changes on the sea lamprey population dynamics. Utilizing differential equations and specific models for population growth, reproduction success, and resource utilization efficiency, the study examines the effects of sex ratio on population dynamics, reproduction success rates, and resource usage efficiency. Diagrams illustrating variations in sex ratio and population quantities offer insights into their effects on population growth and ecological dynamics. The findings suggest that altering the sex ratio significantly influences reproductive success, resource efficiency, and overall ecosystem dynamics, potentially leading to changes in reproduction rates, population structure, genetic diversity, and predator-prey relationships. By analyzing the boosted Lotka-Volterra model, the study demonstrates that as the sex ratio effect (alpha) increases, significant fluctuations occur in prey populations, contributing to environmental instability. Moreover, predator populations exhibit greater variations and a sharp decline, indicating the intricate interaction between sex ratio, prey stability, and ecosystem dynamics. The conclusion is that changes in sex ratio have a significant impact on the ecosystem. Possible issues that might arise include changes in reproduction rate and population growth rate, changes in population structure, reduced genetic diversity, and changes in predator-prey relations. These results highlight the critical role of sex ratio in population dynamics and ecosystem stability, emphasizing the need for further exploration and management strategies in marine ecosystems.
Research on Machine Learning-Based Forecasting Models for SSE Indexes-Analysis From The Perspective of Quantitative Time-Timing
Authors: Wang Tingyue
Published: August 2024

Quantitative investment is a hot topic in recent years, through machine learning algorithms to deal with a large amount of data, saving investors' time and energy, to provide investors with reliable investment prediction results, the use of machine learning algorithms in quantitative investment has a broad prospect. This paper is based on the machine learning model to predict the rise and fall of the SSE index, using evaluation indicators to measure the model performance, select the best model for further optimisation; and in the backtest to construct a quantitative time-testing trading strategy, to verify that the model is good profitability in the real market, which is of great significance; and finally to analyse the importance of the features, to increase the interpretability of the model. In this paper, the decision tree, random forest and XGBoost models are used to predict the rise and fall of the index respectively, and the sample interval of the historical data of the SSE index is from 19 December 1990 to 6 December 2022, and the training set and test set are divided according to 7 to 3. After a multi-model comparison of the prediction ability by machine learning evaluation metrics such as Accuracy, Precision, Recall, F1 Score and AUC, it is concluded that the XGBoost model has the best performance in upward and downward prediction. Secondly, the paper successfully re-optimises the prediction accuracy of the XGBoost model in the upward and downward prediction of the Shanghai Stock Exchange (SSE) index using an innovative Bayesian optimisation method. Furthermore, the quantitative strategies constructed based on the optimised XGBoost model predictions are backtested and found to have good profitability. Finally, in order to enhance the interpretability of the model, the SHAP interpretable method is used to analyse the important variables that predict the rise and fall of the index.
Vegetable demand forecasting model based on ARIMA
Authors: Li Yongkuan
Published: August 2024

Establishing an accurate vegetable demand forecasting model is crucial for fresh supermarkets to optimize replenishment and maximize profits amidst fluctuating market demand driven by the perishable nature of vegetables and changing consumer purchasing decisions. This study takes a certain fresh supermarket as an example, targeting the strong periodicity and seasonality of the vegetable market demand characteristics, using SPSS for data analysis and ARIMA time series modeling. Through stationary testing and white noise testing, the effectiveness and applicability of the model were verified, and an accurate forecast of the total demand for vegetables in the supermarket for the next week was made. This forecasting model provides a reliable basis for the supermarket to formulate replenishment plans, helping it maximize profits in vegetable supply, cope with market demand fluctuations, ensure timely vegetable supply, and meet the constantly changing purchasing needs of consumers.
Momentum prediction model of the tennis game based on the random forest algorithm
Authors: Zhou Zhisang , Gong Haiwang , Tang Mingyan , Xiao Wenrui , Lou Mengqi
Published: August 2024

Momentum in tennis matches can greatly affect the performance of tennis players, and dynamic monitoring of momentum can help players to achieve better results in the competition. This paper constructs a tennis ball momentum prediction model based on the random forest algorithm. The model selects the nine indicators of the process of winning the competition in the current set, whether to score continuously, whether to serve, gain or lose the point by untouchable shot, relative fatigue, error situation, double fault, rally count, speed of serve, uses the random forest algorithm to predict the momentum. To prevent the model overfitting problem, this paper reduces the index in dimension by PCA. Based on the results of model training, this paper puts forward suggestions on how to improve the score: prepare in advance, good attitude, hold the rhythm, reduce error, play to the score, improve technique. The data of 201910260 ATL of quarter 1 from the game data of the 2019-2020 regular season are trained by a momentum prediction model based on the random forest algorithm, which demonstrate the generalization ability of the model. This model can be used in various sports events to help athletes improve their performance.
Design of Disaster Four-rotor Drone Control System Based on Fuzzy Self-turning PID Control
Authors: Zhou Kairan
Published: August 2024

Disasters often manifest as multifaceted crises that pose significant challenges for emergency responders, particularly when accessing hazardous environments such as fire scenes or chemically contaminated areas. The complexity of these situations necessitates the exploration of innovative solutions to augment the efficacy of rescue operations. In this context, the present study introduces a novel approach through the development of a disaster drone control system, predicated on the principles of fuzzy self-tuning control. This paper delineates the conceptual framework and architectural design of a fuzzy self-tuning Proportional-Integral-Derivative (PID) controller. It leverages fuzzy logic to enhance the precision of control actions by employing fuzzy rules, thereby facilitating a comparative analysis between traditional adaptive controllers and their fuzzy counterparts. Furthermore, this study embarks on a comprehensive examination of the current landscape, practical applications, and prospective advancements in the realm of disaster robotics. The findings underscore the superior accuracy and efficiency of the self-tuning PID control mechanism, which significantly expedites the identification of victims. Consequently, the deployment of disaster drones not only streamlines rescue operations by curtailing time and financial expenditures but also contributes to the broader objective of making rescue missions more manageable and effective.
Fundus Vessel Segmentation Technology Based on Image Recognition
Authors: Zhang Xitan
Published: August 2024

The lower part of the eye is filled with abundant blood vessels, in the normal course of infusion of blood vessels, and the reason for this phenomenon is various eyeground vessels, for example, diabetes retinopathy, retina venous obstruction, hypertension retinopathy, hyperoptic retinopathy, etc. If the bleeding volume is small, people don't need to look for a doctor, but eyeground can be self-relieved. If, however, the hemorrhage in the blood vessel is extensive and hard to heal, it may be necessary to make a new diagnosis and operation. So it is of great importance to treat and recover the entire eyeground. The objective of eyeground image segmentation is to extract the blood vessels from complicated fundusimages. This method can offer non-invasive, high resolution data of retinal blood vessels to assist in the correct and reliable diagnosis of eye diseases. This article gives a brief introduction to some of the technology of segmentation, and discusses the features of them. The purpose of this article is to provide the reader with an insight into how this area develops and to become familiar with the techniques used to segment the vessel.
A Study on Facial Landmark Detection and Image Processing
Authors: Xiong Xiyi
Published: August 2024

This research focuses on developing a robust face alignment system crucial for applications in facial recognition, expression analysis, and augmented reality. Utilizing a dataset of 2811 training images and 554 test images each annotated with 44 facial landmarks, the study explores several models including Convolutional Neural Networks (CNN), Cascade Regression, and Residual Networks (ResNet). Through rigorous experimentation, it was observed that while CNNs and Cascade Regression models provided substantial accuracy, the ResNet model displayed superior performance, especially in complex scenarios involving diverse expressions and occlusions. Additionally, the project also developed a simple algorithm for lip and eye color modification, further broadening the applicability of the system in image processing. Results indicate that while traditional models like CNN and Cascade Regression perform adequately, ResNet offers superior accuracy and robustness, particularly in challenging conditions. This research confirms the effectiveness of ResNet in enhancing face alignment technologies and suggests potential areas for future improvements in the field.
A Research on Machine Learning for Predicting Survival Time in Cancer Patients
Authors: Xi Binghua
Published: August 2024

Cancer remains one of the leading causes of mortality worldwide. Predicting the survival of cancer patients holds immense significance in guiding treatment decisions and enhancing patient quality of life. To provide a comprehensive understanding of the application of machine learning methods and to explore future research directions in survival prediction, this paper reviews the current landscape of machine learning algorithms in this domain. The paper discusses the significance and challenges associated with predicting the survival time of cancer patients. It begins with an introduction highlighting the importance of this prediction task in the medical domain. Traditional methods utilized for survival prediction are then explored, shedding light on their strengths and limitations.  Following this, the paper delves into the application of traditional machine learning approaches for survival prediction.  Subsequently, the focus shifts towards deep learning algorithms and their role in survival prediction.  In conclusion, the paper identifies potential avenues for further research in this field, paving the way for continued advancements in cancer survival prediction.
The Temperature of Feedback Chatbots: an Experiment in Humor Detection
Authors: Cao Yang , Chen Tianle , Wu Qian
Published: August 2024

Humor is one of the measures of human intelligence, and similarly, humor is a major indicator of chatbot intelligence. To make chatbot answers more lively and interesting, thus increasing the interaction and entertainment between users and bots and providing a more interesting user experience. This paper collects a large text dataset and use models such as humor detection and humor scoring to detect the humor ability of chatbots, and improve the future work based on the results obtained from the experiments. It is shown that the CNN model's ability to recognize the humorous elements in the text and score the humorous information in the chat content gradually improves with multiple detections. This experiment implements the detection of humor ability of chatbots. A rating mechanism can assist in enhancing the humor and interactivity of robots, improve the existing computer humor model, enhance computer understanding of natural language, and promote the further development of artificial intelligence.
A Decision model for merchandise replenishment based on logistic regression and ARIMA time series forecasting
Authors: Huang Zenan , Wang Kai
Published: August 2024

In supermarkets or shopping malls that mainly deal with fresh food, vegetable commodities are generally difficult to store for a long time with a short freshness period. And the quality of vegetables and storage time present a certain relationship, the longer the storage time the worse the quality of vegetables, and even the existence of varieties if the day did not sell the next day will not be able to sell. Therefore, supermarkets need to replenish goods on the same day according to the past sales situation and the demand of residents. To address the problem, this paper fits the data to derive a linear equation for sales volume and cost-plus pricing using a logistic regression model and Adam's optimized gradient descent algorithm. Finally, a time series ARIMA forecasting model is used to give daily replenishment and specific pricing for the week ahead based on past daily sales data. In the results, we can adjust the merchandise based on predicted replenishment and pricing strategies. The model reveals the supermarket's replenishment and pricing strategy for fresh food in general, and the supermarket can adjust its replenishment strategy based on its data.
Applications and Prospects of SLAM Technology in Mobile Robot Design
Authors: Chen Baixu
Published: August 2024

This paper studies the application of simultaneous localization and mapping (SLAM) technology in the design of mobile robots. Traditional SLAM research lacks a systematic approach and adaptability to actual work tasks, making it difficult for researchers to choose reasonable architectures for optimized design, thereby limiting the further development of SLAM technology. The paper begins by introducing the definition and development history of SLAM technology, then introduces six kinds of SLAM technologies in the application framework of mobile robots, comparing and analyzing their applicable scenes based on each technology’s characteristics. It proceeds to analyze typical applications of mobile robots with SLAM technology in Autonomous Mobile Robots and three-dimensional (3D) environment exploration, as well as search and rescue operations, rounding off with an analysis and summary of prospects of SLAM technology in mobile robot design. This study offers targeted solutions by employing listing and comparison methods combined with practical application analysis, thus better-assisting researchers in choosing reasonable architectures for optimization. This paper facilitates researchers in choosing reasonable architectures for designing mobile robots under different scenarios. In conclusion, it proposes prospects of SLAM technology in mobile robot design, providing direction for research on SLAM technology in mobile robots.