bluuebunny/crossref_metadata_2025 huggingface dataset:
Aplicação do OpenCV utilizando técnicas de visão computacional e segmentação de imagens para reconhecimento de colônias bacterianas em análises microbiológicas de qualidade de água
Authors: Ribeiro Hebe Morganne Campos , Picanço Ailson Renan Santos , Carr Caroline Nunes , Santos Estêvão Damasceno , Melo Filho Djunio Rosa de , Almeida Tayany Coelho de , Lima Antonio Casanova Junior da Silva , Vieira Andre Fernandes , Oliveira Gustavo Casanova , Dias Isabela Hadassa Fernandes , Correa Junior Ivan de Jesus Coelho , Pacheco Kauan da Silva , Silva Ryan Dias da
Published: June 2024

Ao decorrer deste artigo, exploraremos a aplicação do OpenCV em conjunto com técnicas de visão computacional e segmentação de imagens para o reconhecimento de colônias bacterianas em análises laboratoriais. Investigaremos como o avanço tecnológico, particularmente no campo do reconhecimento visual de imagens, complementa e melhora os estudos e atividades laboratoriais. Discutiremos as ferramentas utilizadas e como desempenham suas funções específicas, visando automatizar tarefas de análise de imagens e potencializar os resultados obtidos. O reconhecimento de colônias bacterianas em análises laboratoriais é uma tarefa importante, mas muitas vezes demorada e suscetível a erros humanos. A detecção de colônias bacterianas em análises laboratoriais é uma tarefa desafiadora, muitas vezes realizada manualmente e sujeita a imprecisões. Para melhorar esse processo, este estudo propõe uma abordagem baseada em recursos visuais, como segmentação de imagens e visão computacional. Utilizando a biblioteca OpenCV, reconhecida por sua eficácia no processamento de imagens, desenvolveu-se uma metodologia para o reconhecimento automático de colônias bacterianas em placas de Petri. Essa abordagem visa aprimorar a eficiência e a precisão das análises laboratoriais, oferecendo uma solução para aplicações biomédicas e de pesquisa. A metodologia inclui o uso de algoritmos e operações para identificar e quantificar com precisão as colônias presentes nas imagens. Os métodos utilizados são discutidos ao decorrer deste artigo, demonstrando uma abordagem promissora para otimizar a análise de amostras bacterianas em ambientes laboratoriais, oferecendo maior eficiência e confiabilidade nos resultados. Ao fornecer uma alternativa mais rápida e precisa para a detecção de colônias bacterianas, essa pesquisa tem o potencial de impactar positivamente a eficiência dos processos laboratoriais, reduzindo erros e tempo de análise. Além disso, abre caminho para futuros estudos que possam aprimorar ainda mais essas técnicas e aplicá-las em diversos contextos científicos e médicos.
Pesquisas pós-críticas em educação e formação docente: aproximações, tensionamentos sobre gênero na escola
Authors: Rabello Karoline Ribeiro , Alves Rozane Alonso
Published: June 2024

Este artigo faz parte de uma pesquisa de dissertação de mestrado, vinculada ao Programa de Pós-Graduação em Ensino de Ciências e Humanidades – PPGECH, junto a Universidade Federal do Amazonas – UFAM. Conta o com financiamento da Fundação de Amparo à Pesquisa do Estado do Amazonas – FAPEAM. Busca tencionar as relações que transitam entre a fronteira e transgressão na formação de professores/as, com ênfase nas discussões de gênero como palco discursivo que se insere no contexto de sala de aula, articulando o campo dos Estudos Culturais e teorias articuladas, tais como Pedagogia Feminista e Teoria Queer, para pensar das dimensões do trabalho docente no que se refere as perspectivas de gênero e sexualidade. O estudo tem como objetivo olhar para as discussões teóricas-metodológicas que buscam desafiar e redesenhar práticas de ensino quanto ao assunto/conteúdo sobre gênero no âmbito da formação de professores. O artigo destaca a importância de considerar a dimensão de gênero na educação, debatendo e problematizando as múltiplas facetas da subjetividade do sujeito aluno/a amplificadas (ou não) a partir da sua relação com a escola. Além disso, tensiona como problematizar o cenário educacional, tornando-o mais perceptível às questões de gênero e, assim, uma educação mais diversificada, voltando-se para a formação de professores e tensionando, de que maneira os professores vem se formando, para debater e problematizar as questões de gênero dentro de sala de aula?. Olhar a partir das narrativas transgressoras ao qual se constituem o campo da pesquisa pós-crítica auxilia na percepção dos modos como a escola e as práticas instituídas nesse espaço, possam produzir novos olhares e discursos sobre as identidades estudantis, bem como estabelece tencionar a fixidez dessas mesmas práticas.
Testamento vital: considerações preliminares
Authors: Tavares Euler Rui Barbosa , Osório Neila Barbosa , Macedo Maria de Lourdes Leoncio , Santos Jocyleia Santana dos , Brito Marlon Santos de Oliveira , Oliveira Núbia Pereira Brito , Noleto Leda Santana de Oliveira , Gomes Glauce Gonçalves da Silva
Published: June 2024

O estudo tem como objetivo analisar os pontos controversos e, muitas vezes, divergentes, sobre as diretivas antecipadas de vontade na velhice a partir de considerações preliminares. Para o desenvolvimento deste trabalho, foram realizados estudos sobre os conceitos, finalidade, relevância e a legislação existente no Brasil sobre o Testamento Vital. Assumpção (2014), o Testamento Vital pode ser o instrumento que melhor se adéqua à expressão dos anseios da pessoa, registrando, de maneira mais segura, as vontades e autonomia de cada indivíduo e afastando eventuais dilemas familiares. Na complexidade do final da vida de uma pessoa, determinadas decisões precisam ser tomadas. Algumas delas envolvem desejos que nem sempre são atendidos. O estudo será norteado pelas concepções dos autores: Husserl (2007; 2008), Heidegger (2012), Merleau-Ponty (1971; 2000) e Sartre (2007), cujas ideias serão o fio condutor desta pesquisa. A relevância do presente estudo parte do pressuposto de que qualquer ser humano tem o direito individual de morrer com dignidade. A construção metodológica foi norteada pela abordagem qualitativa e os dados que instituíram a pesquisa foram obtidos por meio de estudos bibliográficos e documentais.  O estudo indica que o Testamento Vital está presente no ordenamento jurídico brasileiro, amparados pelos princípios da autonomia e dignidade humana. Nesse contexto, as Diretivas Antecipadas de Vontade constituem-se como construção histórica e cultural. A pesquisa qualitativa, bibliografia e análise documental trazem as apreciações sobre o processo de Diretivas Antecipadas de Vontade no fim da vida. Percepções e interpretações que revelam mitos e preconceitos no percurso, mas destacam, também, a importância da conscientização e publicitação do referido Testamento enquanto direito e garantia fundamental em nosso ordenamento jurídico brasileiro.
INTERNATIONAL PROSTATE SYMPTOM SCORE (IPSS) CORRELATION WITH SONOGRAPHIC PROSTATE SIZE
Authors: REHMAN AU , ULLAH S , HAIDER SF , AHMED Y , SAJJAD A
Published: June 2024

The International Prostate Symptom Score (IPSS) is a broadly used questionnaire designed to assess the severity of lower urinary tract symptoms (LUTS) in men, particularly those related to harmless prostatic hyperplasia (BPH). Objectives: The primary aim of this study is to find the International Prostate Symptom Score (IPSS) and its correlation with sonography and prostate size. Methods: This cross-sectional study was conducted at CMH Lahore February 17, 2024, to May 16, 2024. Data were collected from 250 patients. Male patients aged>40 years who presented with LUTS were included in the study. Patients with a history of prostate cancer, bladder dysfunction and prostate surgery were excluded from the study. Data were collected through a systematically designed questionnaire. All the study participants completed the IPSS questionnaire to find the severity and urinary symptoms. Results: Data were collected from 250 patients according to the study's inclusion criteria. The mean age of the patients was 62.4 ± 8.6 years, and the mean BMI was 27.1 ± 3.2 kg/m2. The mean PSA was 6.8 ± 2.5 ng/mL, and the mean IPSS score was 19.5 ± 6.8. there, 140 (56%) patients were smokers, and 125 (50%) also suffering from hypertension. Patients with IPSS scores ranging from 0-7 exhibited a mean PV of 32.5 ± 5.6 mL, with a Pearson correlation coefficient (r) of 0.25 (p = 0.038). As IPSS scores increased to the 22-35 range, the mean PV rose to 54.3 ± 9.2 mL, with a more robust correlation coefficient of 0.75 (p < 0.001). Conclusion: It is concluded that there is a significant positive correlation between the International Prostate Symptom Score (IPSS) and prostate volume (PV) in patients with benign prostatic hyperplasia (BPH).
Peran Kepala Sekolah dalam Meningkatkan Mutu Sumber Daya Manusia
Authors: Munawwarah Faiqatul , Jannah Faridatul , Nurhadi Ali
Published: June 2024

The purpose of this study is to explain and describe the role of the principal in improving the quality of human resources at Al-Ghafur Vocational High School in Sumenep. The research method used is qualitative through a case study. Data collection techniques include interviews, observations, and documentation. The results of the study show that the principal's strategy in improving the quality of human resources includes the design and development of a curriculum that meets the needs of students, with a primary focus on HR management. The goal is for all school members to have a high spirit to advance the educational institution. Other strategic steps include regular performance monitoring and evaluation, as well as staff training and skills development. The principal also strives to build good relationships with the community through meetings with students' guardians, social activities, and school events. As an educational manager, the principal focuses on improving HR quality through regular planning, organizing, directing, coordinating, and supervising. Factors such as effective leadership, a supportive organizational culture, clear policy implementation, technology development, and HR training also play important roles in improving HR quality.
Mental Health Promotion in Children and Adolescents
Authors: Agarwal Vivek , Bansal Teena
Published: June 2024

Mental illnesses among children and adolescents are on the rise and are becoming one of the prime causes of disability across the globe. Untreated or unaddressed mental health issues can extend to adulthood. They can have severe long-term physical, social and economic adverse effects, including low employment rate, lesser wages if employed, interpersonal difficulties and more legal and criminal contacts. However, the focus on preventative and promotive mental health measures has gotten rather less emphasis than the sickness side, including treatment and research on mental illnesses. Resilience and positive well-being are protective against developing mental illnesses and improving courses for those who have developed such issues. Resilience can be enhanced by adopting a healthy lifestyle, music, and other art forms as a recreational activity, limiting screen use and having good social support. Various school-based programs are being developed and tested, targeting positive mental well-being and resilience in children and adolescents. A few of them discussed in this review are life skill education, PAX good behavior games, source of strength, Zippy’s Friends, You Can Do It!, and mindfulness-based stress reduction (MBSR). The responsive advocacy for life and learning in youth (RALLY). Despite these, more investments should be directed towards the prevention of illness and promotion of mental well-being than mere treatment and rehabilitation a ARTICLE INFO fter an illness.
Ensuring Mental Well-being in the Digital World: Challenges and Approaches
Authors: Ahluwalia Yashita , Balhara Yatan Pal Singh
Published: June 2024

In recent years, the integration of digital technology into mental health care has become increasingly prevalent. However, digitalization serves as a dual-force catalyst in the domain of psychological sciences, presenting a spectrum of unparalleled opportunities and significant challenges. The technological growth required for providing mental health interventions transcending geographical and temporal constraints also contributes massively to the emergence of psychological phenomena that can detrimentally impact mental health. This overview explores the intricate relationship shared between digitalization and mental health, investigating the challenges posed by the digital landscape on psychological well-being while highlighting the potential of digital platforms to address mental health concerns and enhance overall well-being
Deep Learning for Localization and Segmentation in Thorax Abdomen CT
Authors: Mamani Gabriel Efrain Humpire
Published: June 2024

The work presented in this thesis is focused on using DL for detecting and segmenting structures in CT scans. In Chapter 2, we present a method for localizing organs in 2D orthogonal views; this method combines the outputs of each orthogonal view to compose a 3D bounding box per organ. In Chapter 3, we apply a state-of-the-art segmentation algorithm using CNN to segment the spleen, achieving performance comparable to that of an independent observer. In an observer experiment, the radiologist rated the segmentation quality as 94% as ready for clinical use. Additionally, we performed an experiment to measure the splenic volume change over time. In Chapter 4, we segment the kidneys and kidney abnormalities, including cysts, lesions, masses, metastases, and tumors. We conducted an ablation study to analyze the performance of five components of the method. In Chapter 5, we explore the use of transfer learning to segment additional structures using a partially annotated dataset (a junction of publicly available datasets and data from public challenges). Finally, Chapter 6, provides the general discussion and summary of this thesis.
The Dilemma and Practice of Anti-monopoly Law Regulation in the Digital Economy Era
Authors: Wang Yiwen
Published: June 2024

The digital economy has emerged as a significant catalyst for worldwide economic expansion. Nevertheless, as the digital economy continues to flourish, the issue of monopoly it brings is becoming more and more important. Certain online platforms engage in predatory pricing and discriminatory practices, undermining fair competition in the market, harming consumer rights and interests, and impeding the healthy growth of the economy. This paper uses the research methods of literature analysis and literature review to explore the theoretical and technical challenges encountered by the anti-monopoly law in the context of the digital economy era, and puts forward proper recommendations for improvement according to its limitations by analyzing the existing anti-monopoly case practices. This study aims to identify effective regulatory measures and recommendations that can offer robust legal protection for the sustainable growth of the digital economy. At the same time, it is anticipated that this study will promote the improvement and development of the anti-monopoly law in the field of digital economy, and contribute wisdom and strength to the construction of a more fair, open and orderly market competition environment.
Research on the Game Behavior of Environmental Protection Strategies Between Government and Enterprises
Authors: Liao Yuxin
Published: June 2024

In recent years, the global environment has been deteriorating. To achieve win-win environmental protection and economic development, the Chinese government has issued various environmental governance policies. However, as an important part of the economy and society, enterprises often ignore the impact on the environment while realizing economic development. Therefore, how the government and enterprises develop appropriate environmental protection strategies to achieve parallel environmental protection and development has become the main problem faced at present. Based on the method theory and practical application of game theory, experts in related fields have studied this problem deeply. According to the different research subjects, this paper starts from five different research objects, such as the mutual influence between government and enterprises under environmental governance, the regulation between governments at all levels, the evolution game of government-enterprise-media, the evolution game of government-enterprise-public, and the game of government-enterprise-media-public, introduces the analysis of the decisions of government and enterprises based on game theory, put forward advice to consider the influence of other factors and explore the connection between various factors, to provide detailed reference for scientific governance environment and realize economic sustainable development.
The Conflict Between Pharmaceutical Patent Right and Life Right and Its Resolution Mechanism: From the Perspective of Legal Philosophy
Authors: Chen Xiaoyu
Published: June 2024

This paper explores the conflict between pharmaceutical patent rights and the right to life and its resolution mechanisms from the perspective of legal philosophy. It begins by discussing how the outbreak of COVID-19 has led to increased global demands for vaccines, temporary medical facilities, and public health controls, which in turn has sparked reflection on the relationship between pharmaceutical patents and the rights to life and health. The paper then analyzes several typical cases, including the Haiqing Ni counterfeit drug case, the Lu Yong case, and the Shanghai fake vaccine case, to illustrate the specific points of conflict between patent rights and the right to life. It also discusses the positive relationship between patent rights and the right to life, as well as the negative impact of the monopolistic nature of patent rights on the protection of the right to life. To resolve these conflicts, the paper proposes some existing measures, such as the application of the principle of proportionality and the compulsory licensing system, and suggests future possible measures, including the re-improvement of existing measures and the establishment of feasible new measures. In conclusion, while existing measures have alleviated the conflict to some extent, there are still difficulties and limitations in their implementation, necessitating further legislative and regulatory improvements.
A Cross-National Examination of Abortion Politics: Contrasting Perspectives in the United States and France
Authors: Zeng Zhijia
Published: June 2024

The debate surrounding abortion laws has been one of great prominence in current politics. While some nations take a strong stance against the accessibility of the practice, others view it as an essential protection of women's autonomy. The main objective of this paper is to perform a comparative analysis of both the historical and contemporary legal landscape of abortion within France and the United States. Throughout this paper, the examination of the evolution of abortion laws in both countries are laid against a backdrop of shifting societal values, cultural influences, and political dynamics. In the United States, the narrative of abortion laws is marked by intense ideological complications and complex legal battles that result from deep rooted societal divisions. In contrast, Frances progression leaned towards growing liberalization, strongly influenced by public health priorities and an emphasis on gender equity. Through delving into key legal decisions, political movements, and public relations, this paper aims to illustrate the shaping legal and cultural frameworks within the two nations shape their respective policies and practices surrounding the topic of abortion. This paper highlights the implications of these divergent approaches towards womens reproductive autonomy, government health outcomes, and overarching societal norms. The comparative analysis of abortion within the two democracies seeks to provide insights into the underlying reasons for the stark differences in their approaches, striving to draw conclusions that may provide insight for future legal and policy initiatives in the realm of reproductive rights.
Research on the prediction of traffic accident by linear regression
Authors: Wang Yuqing
Published: June 2024

Traffic accident is getting increasingly serious. Although previous researchers use a variety of methods to predict the traffic accident, there are numerous demerits that need to be improved. This article demonstrates 12 variables that impact the traffic accident with 679 samples of accidents in UK from 2012 to 2014. This paper first analyses the relevance between dependent and independent variables, and also two independent variables to show the correlation between each factor. By using the multiple linear regression, it is concluded that although some independent variables do not have relationship with the dependent variable urban or rural area, Accident Severity, Number of Casualties, Road Type, Speed limit, Junction Control show significant relationship with the dependent variable. The paper also considers the 95% confidence interval in order to compare the effective density of data. Overall, the prediction of traffic accident is based on a number of factors and a sizable sample of accidents to summarize the impact that traffic accidents bring.
Optimization study of pruning strategy based on KNN trajectory similarity query
Authors: Zhu Jingru , Wang Zhongyu
Published: June 2024

With the development of GPS positioning technology, a large amount of spatiotemporal trajectory data has been generated. Due to the complex structure of trajectory data, which has irregular spatial shapes and continuous temporal sequence attributes, querying massive trajectory data poses certain challenges. The pruning strategy of existing trajectory similarity query methods is not very effective. Even after pruning operations, there are still a large number of trajectories that need to undergo distance calculations to confirm whether they are similar trajectories. This paper proposes multiple local pruning optimization schemes, which maximally reduce the number of trajectories in the candidate set. Specifically, it starts with region pruning in the index space, eliminating index spaces with distances greater than the maximum similarity distance from the query trajectory. Then, it performs distance pruning between trajectories, removing trajectories that do not meet the distance conditions. Finally, it adds a termination condition: when the distance between the current index space and the query trajectory is greater than the maximum similarity distance and the number of trajectories in the result set is K, the loop is exited, and the query process ends. Tests on real datasets demonstrate that the KTSS method outperforms current algorithms of the same type.
Enhancing conversational recommendation systems through the integration of KNN with ConLinUCB contextual bandits
Authors: Zhao Yisen
Published: June 2024

In recommender system research, contextual multi-armed bandits have shown promise in delivering tailored recommendations by utilizing contextual data. However, their effectiveness is often curtailed by the cold start problem, arising from the lack of initial user data. This necessitates extensive exploration to ascertain user preferences, consequently impeding the speed of learning. The advent of conversational recommendation systems offers a solution. Through these systems, the conversational contextual bandit algorithm swiftly learns user preferences for specific key-terms via interactive dialogues, thereby enhancing the learning pace. Despite these advancements, there are limitations in current methodologies. A primary issue is the suboptimal integration of data from key-term-centric dialogues and arm-level recommendations, which could otherwise expedite the learning process. Another crucial aspect is the strategic suggestion of exploratory key phrases. These phrases are essential in quickly uncovering users potential interests in various domains, thus accelerating the convergence of accurate user preference models. Addressing these challenges, the ConLinUCB framework emerges as a groundbreaking solution. It ingeniously combines feedback from both arm-level and key-term-level interactions, significantly optimizing the learning trajectory. Building upon this, the framework integrates a K-nearest neighbour (KNN) approach to refine key-term selection and arm recommendations. This integration hinges on the similarity of user preferences, further hastening the convergence of the parameter vectors.
Strategic insights from multi-armed bandits: Applications in real-time strategy games
Authors: Sun Yuchen
Published: June 2024

In real-time strategy games, players often face uncertainty regarding which strategy will lead to victory. This paper delves into how multi-armed bandit (MAB) algorithms can assist in this context, beginning with an exploration of MAB's theoretical principles, particularly the crucial balance between exploration and exploitation. The study compares the efficacy of the Explore-Then-Commit (ETC), Upper Confidence Bound (UCB), and Thompson Sampling (TS) algorithms through practical experimentation. Beyond gaming, the paper also considers the broader implications of MAB algorithms in healthcare, finance, and dynamic pricing within online retail sectors. A focal point of the research is the application of UCB and TS algorithms in StarCraft, a popular real-time strategy game. The performance of these algorithms is rigorously evaluated by calculating the cumulative regret value, a key metric in assessing strategic effectiveness. The findings suggest that the implementation of UCB and TS algorithms significantly enhances players' winning rates in the game. While the results are promising, the paper acknowledges ongoing challenges and encourages further exploration into this fascinating and valuable area of study. This research not only contributes to the understanding of strategic decision-making in gaming but also signals potential cross-sectoral applications of MAB algorithms.
Advancing decision-making strategies through a comprehensive study of Multi-Armed Bandit algorithms and applications
Authors: Kuang Yang
Published: June 2024

Multi-Armed Bandit (MAB) strategies play a pivotal role in decision-making algorithms by adeptly managing the exploration-exploitation trade-off in environments characterized by multiple options and constrained resources. This paper delves into the core MAB algorithms, including Explore-Then-Commit (ETC), Thompson Sampling, and Upper Confidence Bound (UCB). It provides a detailed examination of their theoretical underpinnings and their application across diverse sectors such as recommender systems, healthcare, and finance. MAB algorithms are celebrated for their efficiency in optimizing decision outcomes; however, they are not without challenges. Significant issues include managing the complexity of exploration and adapting to non-stationary environments where the dynamics of the available options may change over time. A nuanced understanding of these challenges is crucial for effectively implementing MAB strategies in complex decision-making scenarios. This study not only highlights the versatility and potential of MAB algorithms but also underscores the need for ongoing research to refine these techniques and expand their applicability.
Analyzing the strengths and weaknesses of diverse algorithms for solving Multi-Armed Bandit problems using Python
Authors: Zhang Lingxiang
Published: June 2024

With the rapid advancement of science and technology, the internet has become an integral part of daily life, revolutionizing how people access information and make decisions. In this context, algorithms play a pivotal role in helping individuals make informed choices tailored to their preferences across various domains. Utilizing the MovieLens dataset (https://grouplens.org/datasets/movielens/1m/), which contains a rich compilation of movie ratings and metadata, this study conducts a thorough analysis using Python to assess the performance of four distinct algorithms: Explore-then-Commit (ETC), Upper Confidence Bound (UCB), Thompson Sampling (TS), and Epsilon-Greedy. The comparison reveals that the ETC algorithm excels in applications such as online advertising recommendation and autonomous driving. The UCB algorithm proves more advantageous in financial analysis, where risk management is critical. The TS algorithm is particularly effective in short video recommendation systems, while the Epsilon-Greedy algorithm is well-suited for balancing exploration with reward. Overall, the results indicate that the TS algorithm outperforms the others in general efficacy.
Analysis of the realization for emotion recognition based on machine learning
Authors: Shen Fuhong
Published: June 2024

As a matter of fact, music emotion recognition based on machine learning has been a trend in recent years. This study describes the analysis of the realization for emotion recognition based on machine learning. In this paper, the study expresses some methods of analyzing the emotion of the music composition. The paper represents some classifier molds that enable us to determine the emotion of the music. It aims to provide readers with a deeper comprehension of the music and composers feelings and to know more about the background of the music. The study may let more people to improve their own ability to appreciate music, if this process has let great amounts of individuals known. It also allows people to have more awareness and feelings with more voices. In this paper, the research will also show some about the evolution and original of the synthesizer. Moreover, the study will go to illustrate this through scientific, real examples and personal experiences and pictures.
New York city taxi demand forecast based on ARIMA model
Authors: Li Zeheng , Liu Jiaren , Yang Xinyu
Published: June 2024

The competition in the taxi market is becoming increasingly fierce, but there is a gap between the demand and the number of taxis in some time periods, which not only intensifies ineffective competition among taxis but also brings inconvenience to passengers. This study aims to establish a predictive model to predict the demand for taxis in different time periods in the city. The data was collected from New York City yellow taxi data which was from June 1st, 2022 to June 6th, 2022. After processing the raw data, the optimal parameter selection of the model is determined through ADF testing to improve accuracy. Through ACF and PACF calculation, the data and images are analyzed to find the most suitable p and q values. Use ARIMA model to fit the data and obtain a model with robust fitting parameters. The distribution of predicted values is very consistent with actual data. The model was used for 50 periods of prediction, and through analysis of the research results, the fitting effect of the prediction was good. It was found that the accuracy of the model was high, proving its ability to predict short-term taxi demand.
Analysis of the implementation methods for emotion recognition in music based on machine learning
Authors: Zheng Gengyu
Published: June 2024

Music is a carrier of emotions, capable of triggering, expressing, and conveying people's innermost emotional experiences. With the development of digital technology, the recognition of emotions in music has been the subject of extensive research. From the viewpoint of application, MER is of great significance in music personalized recommendation services, psychotherapy, music creation, and music visualization. Currently, MER implementation methods based on machine learning are gradually becoming mainstream. This study starts from the basic knowledge of MER, first introduces the relevant research directions and research background of MER, and then proposes a three-part research framework combining MER and MEC. Based on this research framework, the machine learning algorithms and specific applications involved in the framework are introduced. Finally, the challenges and future paths facing the implementation of MER technology are proposed. Provide a reference for improving the accuracy and quality of using artificial intelligence methods to capture music characteristics and expressiveness.
Synthesis of natural sound based on Nyquist
Authors: Zhang Boya
Published: June 2024

In recent years, sound synthesis has become an important part of daily life with the rapid development of the technology. There are many methods of natural sound synthesis, but each of them has its disadvantages. This paper explored a novel method of natural sound synthesis based on Nyquist. This method has significant advantages in high speed, convenience, flexibility, randomness, and small file size. The research investigates the effectiveness of this method by synthesizing four distinct natural sounds - rain, wind, thunder, and a combination of all three - using unit generators in Nyquist. To further evaluate the result, Mel spectrograms and a questionnaire are applied. The evaluation shows that the synthesized sounds meet expectations and are relatively real and natural. This method can be combined with other technology, such as the large language model, to provide better accessibility. This method can generate natural sounds for many tasks, especially those requiring high speed.
BXCNN: A novel depression detection model
Authors: Xi Haocheng , Zhong Haoyang , Wang Yutong
Published: June 2024

In response to the mounting societal pressures, an increasing number of individuals grappling with mental health challenges are turning to social media platforms to express their feelings. The utilization of deep learning models for analyzing social media data has become increasingly crucial in detecting early signs of depression. Early intervention through depression detection can significantly enhance patients quality of life and even save lives. However, many existing deep learning models suffer from low prediction accuracy, exacerbated by the imbalance between positive and negative samples in the collected data. To address these challenges, we propose a novel depression detection model integrated with BERT, XGBoost, and Convolutional Neural Networks (BXCNN). This model harnesses the advantages of ensemble learning and deep learning technologies by integrating XGBoost for feature extraction to alleviate data imbalance and CNN for classification. We transform depression-related textual data into sentence vectors using BERT to capture semantic information effectively. These features are then fed into a CNN classifier to accurately predict the likelihood of individuals exhibiting depressive symptoms. Through empirical evaluations on relevant datasets, our approach excels across various evaluation metrics, including accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic curve (AUC-ROC).
Evaluasi Pembelajaran Tematik Terpadu menggunakan Model Charlotte Danielson untuk Sekolah Dasar
Authors: Srirahmawati Ija , Hendriani Nunung
Published: June 2024

Penelitian ini bertujuan untuk mengevaluasi pembelajaran tematik terpadu di sekolah dasar, mencakup perencanaan pembelajaran, pelaksanaan, serta evaluasi pembelajaran, menggunakan pendekatan evaluasi dengan metode kuantitatif dan kualitatif. Subjek penelitian adalah guru kelas III yang melaksanakan pembelajaran tematik terpadu. Teknik pengumpulan data meliputi wawancara mendalam (in-depth interview), observasi, dan dokumentasi. Hasil penelitian menunjukkan bahwa pada domain Persiapan dan Perencanaan Pembelajaran, guru kelas III di SDN 06 Pajo berada dalam kategori baik dengan rata-rata persentase 76%. Pada domain Pengelolaan Kelas, guru kelas III berada dalam kategori baik dengan persentase 79%. Pada domain Proses Pembelajaran, guru kelas III berada dalam kategori baik dengan persentase 83%. Pada domain Tanggung Jawab Profesional, guru kelas III berada dalam kategori baik dengan persentase 79%. Berdasarkan hasil penelitian tersebut, dapat disimpulkan bahwa guru kelas III di SDN 06 Pajo telah merencanakan, melaksanakan proses pembelajaran, mengelola kelas, serta memiliki tanggung jawab profesional dengan baik.
Hubungan Kemandirian Belajar dengan Hasil Belajar Siswa Kelas IV Sekolah Dasar
Authors: Afid Ahwam Ahwam , Nuvitalia Duwi , Sanjaya Donis
Published: June 2024

Penelitian ini bertujuan untuk Abstrak ini bertujuan untuk mengevaluasi hubungan antara tingkat kemandirian belajar dan hasil belajar siswa kelas IV B di SDN Sawah Besar 01, Kecamatan Gayamsari, Kota Semarang. Penelitian ini menggunakan pendekatan kuantitatif dengan metode korelasi. Populasi yang diambil terdiri dari 28 siswa kelas IV B di SDN Sawah Besar 01, dengan teknik pengambilan sampel menggunakan metode pengambilan sampel jenuh. Data dikumpulkan melalui penggunaan angket dan dokumentasi. Analisis data dilakukan dengan menggunakan teknik analisis statistik deskriptif, analisis korelasi sederhana, uji signifikansi, dan koefisien determinasi. Hasil penelitian menunjukkan adanya hubungan positif dan signifikan antara tingkat kemandirian belajar dan hasil belajar siswa. Hal ini mengindikasikan bahwa semakin tinggi tingkat kemandirian belajar siswa, semakin baik pula hasil belajarnya. Kontribusi variabel kemandirian belajar terhadap hasil belajar dikategorikan sebagai kuat. Implikasinya, perlu ditingkatkan aspek-aspek kemandirian belajar siswa guna meningkatkan prestasi akademik mereka. Penelitian ini memberikan pemahaman yang lebih mendalam tentang perlunya perhatian dan pengembangan aspek kemandirian belajar siswa di kelas IV B SDN Sawah Besar 01, Kecamatan Gayamsari, Kota Semarang, sebagai upaya meningkatkan hasil belajar secara efektif.
Pengaruh Pay Satisfaction Terhadap Organizational Citizenship Behavior (OCB) Dimediasi Work Engagement
Authors: Arifin Arifin , Ariffin Zakhyadi
Published: June 2024

This study aims to test and analyze the effect of Pay Satisfaction on Organizational Citizenship, the effect of Pay Satisfaction on Work Engagement, the effect of Work Engagement on Organizational Citizenship behavior, and the effect of Pay Satisfaction on Organizational Citizenship Behavior through ASN Work Engagement in Pambalah Batung General Hospital. This study used a quantitative method, with a cross-sectional time dimension. the sample in this study was about 159 people. The data analysis used is descriptive analysis and to test the effect of the model on the PLS-based structure. The results showed that there was an effect of Pay Satisfaction on Organizational Citizenship Behavior, there was an effect of Pay Satisfaction on Work Engagement, there was an effect of Work Engagement on Organizational Citizenship Behavior and there was an effect of Pay Satisfaction on Organizational Citizenship Behavior through ASN Work Engagement at Pambalah Hospital Batung. Suggestions to Pambalah Batung General Hospital need to pay attention to employee Pay Satisfaction because Pay Satisfaction has an impact on Organizational Citizenship Behavior through Work Engagement and Work Engagement also has an impact on Organizational Citizenship Behavior. If these variables can be considered, of course they will have an impact on the services to the community provided by the Pambalah Batung Hospital
Model Penyelesaian Masalah Keputusan Pembelian: Evaluasi Indikator Digital Marketing dan Online Customer Review di Toko Jangkar Kota Serang
Authors: Suhaemi Muhamad
Published: June 2024

This research is related to how the influence of digital marketing on purchasing decisions at the Toko Jangkar Kota Serang. The purpose of this study was to examine the effect of digital marketing on purchasing decisions partially, the effect of online customer reviews on purchasing decisions partially, the effect of digital marketing and online customer reviews on purchasing decisions simultaneously at the Toko Jangkar Kota Serang. Respondents in this study were 130 people. The type of sample in this study is non-probability with purposive sampling technique. The data collection method used is to use questionnaires and explained by quantitative methods. The results of this study indicate that digital marketing has a positive and significant effect on purchasing decisions, then online customer reviews also have a positive and significant effect on purchasing decisions. The two independent variables in this study are also empirically supported and simultaneously influence the dependent variable.
PENINGKATAN KAPASITAS KADER POSYANDU TERKAIT PEMBERIAN MAKANAN BAYI DAN ANAK
Authors: Kapantow Nova , Sanggelorang Yulianty , Rumayar Adisti Aldegonda
Published: June 2024

Asupan makanan yang tidak adekuat merupakan salah satu penyebab malnutrisi pada anak. Sehingga menjadi sangat penting untuk memastikan bahwa anak-anak mendapatkan asupan makanan yang tepat dan sesuai untuk tumbuh kembang yang optimal. Pemberian makanan yang sesuai untuk bayi dan anak (PMBA) sejak lahir hingga usia dua tahun merupakan langkah awal yang krusial dalam upaya mencapai tujuan tersebut. Untuk mendukung upaya tersebut, Program Kemitraan Masyarakat (PKM) ini dirancang dengan tujuan meningkatkan kapasitas kader Posyandu terkait praktik PMBA yang tepat dan sesuai. Melalui metode penyuluhan langsung dan tutorial serta diskusi evaluatif, kegiatan PKM ini berhasil meningkatkan kemampuan kader Posyandu dalam PMBA yang optimal. Dukungan dari berbagai pihak sangat diperlukan untuk keberhasilan upaya kesehatan, termasuk dalam implementasi praktik PMBA yang tepat. Dengan demikian, kegiatan semacam ini dapat menjadi salah satu langkah strategis dalam upaya preventif berbagai masalah gizi
Inadequate food intake is one of the leading causes of malnutrition in children. Hence, it is crucial to ensure that children receive appropriate and sufficient nutrition for optimal growth and development. The provision of proper infant and young child feeding (IYCF) from birth to two years of age is a critical initial step in achieving this goal. To support these efforts, this Community Partnership Program (CPP) was designed with the aim of enhancing the capacity of Posyandu cadres in practicing appropriate and adequate IYCF. Through direct counseling methods, tutorials, and evaluative discussions, this CPP activity successfully improved the ability of Posyandu cadres in optimal IYCF practices. Support from various stakeholders is essential for the success of health initiatives, including the implementation of appropriate IYCF practices. Therefore, activities like this can be seen as a strategic step in preventing various nutritional problems.
Improving the outcome of complex obsessive-compulsive disorder
Authors:   , du Mortier Johanna Adriana Maria
Published: June 2024

The primary objective of this thesis is to improve the treatment outcomes for persons with complex OCD. The thesis examines the heterogeneity of OCD, predictors of intensive treatment and OCD severity after two years, and factors related to insight and motivation for treatment.
The heterogeneity of OCD is studied through two factor analyses of the Y-BOCS symptom checklist and an investigation into how persons with different OCD subtypes reacted to the COVID-19 pandemic. These factor analyses revealed that some factors are consistently identified across various studies and factor-analytical techniques, while others are less stable. Pre-pandemic contamination symptoms were linked to a heightened fear of COVID-19 and more severe contamination symptoms during the pandemic. In contrast, persons without pre-pandemic contamination symptoms reacted similarly to healthy controls.
Two predictive studies identified several factors associated with an increased risk of requiring intensive treatment two years later and more severe OCD. Factors associated with a higher risk for intensive treatment include being single, having more severe comorbid depression, using psychotropic medication, and having a lower quality of life. Low physical activity was associated with higher OCD severity two years later compared to individuals with medium or high levels of physical activity.
The studies on the course of insight and motivation revealed that insight varies during treatment. An improvement in insight was positively associated with a reduction in OCD severity. Lastly, a qualitative study found that videos of compulsions can potentially enhance both insight and motivation for treatment.
The final conclusion of this thesis is that personalised care for OCD is of utmost importance. The specific nature of individual obsessions and compulsions, along with factors such as relationships, comorbid depression, quality of life, and physical activity, should all be considered. Based on this thesis, it is expected that addressing these aspects with evidence-based interventions could enhance the overall functioning of individuals with OCD.
The Integration of Information and Communication Technology Into Classroom Teaching
Authors: Reid Scott
Published: June 2024

This study provides new images of teachers who are pioneers in the use of information and communication technology (ICT) in the classes they teach. This qualitative study looks at teachers in a high school that is a leader in using information technology in the classroom. The findings indicate that most of the teachers participating in this study were enthusiastic about the possibilities ICT holds for classroom use. Examples are given to illustrate how information technology is being used in this school to enhance classroom teaching in several subject areas. Concerns teachers have about the use of technology were identified as issues that could determine the success or failure of the use of ICT in high schools. These concerns include: maintenance, inequalities, the need for training, information overload, the pace of change and stress, plagiarism, business involvement, and teachers' time.
Schools that Don’t Close: Possible Places and Spaces for Progressive Teaching, Learning, and Research
Authors: Harris Carol Elizabeth
Published: June 2024

Small schools and their communities contribute to an important, though threatened, knowledge base. The threat adheres in underlying technologies (conceptual and material) that propel the capitalistic world towards the rationalization of all aspects of human activity. In education, this appears in the consolidation of small schools and ever larger units of organization. From three studies of Newfoundland coastal communities, I describe schools that were deemed to be “necessarily existing.” Because of their isolated location, students from the schools could not be transported to larger centres. While reporting both positive and negative features of actual small, rural schools, I argue against hasty school closures and point, instead, to rural school and community opportunities for “place, voice, and space-based” teaching, learning, and research. Small, rural schools can be pivotal in leading Canadian education from its deeply rooted, market-based ideology to progressive and socially relevant practices that embrace lifelong learning, community involvement, and ecological awareness and action.
Teaching Principals in Small Rural Schools: “My Cup Overfloweth”
Authors: Wallin Dawn C. , Newton Paul
Published: June 2024

This paper presents the results of interviews with 12 Manitoba and Alberta rural teaching principals regarding their leadership practices in small schools. The overwhelming theme mentioned by these teaching principals was the joy and sense of purpose they found in the relationships they cultivated with children, staff, and community members because of the ‘advantages’ they had working in small schools. The paper details the small schools context within which teaching principals are working in these two provinces and outlines the role of reciprocal relationality that is central to their leadership efforts in small rural schools.