bluuebunny/crossref_metadata_2025 huggingface dataset:
PENERAPAN PEMBELAJARAN TEMATIK KELAS RENDAH SD NEGERI 7 WONOGIRI
Authors: Maryati Maryati
Published: February 2024

Penelitian ini bertujuan untuk penerapan pembelajaran tematik kelas rendah serta upaya guru dalam mengatasi kendala yang dihadapi dalam penerapan pembelajaran tematik di SDN 7 Wonogiri. Penelitian ini menggunakan pendekatan kualitatif dengan jenis penelitian deskriptif. Penelitian ini dilaksanakan di SDN 7 Wonogiri. Subjek dalam penelitian ini adalah tiga guru kelas rendah di SDN 7 Wnogiri. Pengumpulan data menggunakan wawancara dan analisis dokumen. Proses analisis data dimulai dari menelaah seluruh data hasil wawancara dengan perangkat pembelajaran tematik. Setelah itu dilanjutkan dengan mengadakan reduksi data ke dalam tabel dan verifikasi untuk mengambil kesimpulan. Hasil penelitian menunjukkan bahwa guru telah menerapkan pembelajaran tematik Kendala yang dialami oleh guru saat membuat rencana pelaksanaan pembelajaran yakni guru kesulitan dalam memadukan mata pelajaran kompetensi dasar yang tidak berkaitan dengan kompetensi dasar lain. Upaya guru dalam mengatasi permasalahan tersebut adalah guru tetap menerapkan pembelajaran tematik kepada peserta didik walaupun mata pelajarannya masih terlihat.
Penggunaan Media Video & Gambar Dalam Pembelajaraan IPAS Pada Siswa Kelas 4 SDN 1 Wonoboyo
Authors: Wahyu Dwi
Published: February 2024

This research aims to explore the use of video and image media in learning Natural Sciences (IPAs) for grade 4 students at SDN 1 Wonoboyo. Visual media has become an important component in modern education, and this research investigates how the use of this media can influence students' understanding and motivation in learning sciences.

The research results show that the use of video and image media in science learning positively influences students' understanding of the concepts being taught. Students also show higher interest and motivation to learn when visual media is used. Even though it requires more intensive preparation for teachers, the use of visual media is considered effective in explaining complex science concepts.

This research provides insight into the importance of using visual media in improving the quality of science learning at the elementary level and suggests that teachers and schools continue to develop their skills in integrating this media in the curriculum. Video and image media have great potential in motivating students and facilitating better understanding of science material, so they can be effective tools in improving education at the elementary level.
ANALISIS PROBLEMATIKA PADA KETRAMPILAN MENULIS DAN MENGGAMBAR SISWA KELAS II SEKOLAH DASAR NEGERI 1 WONOGIRI
Authors: Ayu Ardani Ines
Published: February 2024

Early writing skills are a critical aspect in a child's language development. This article provides an overview of early writing skills and identifies several challenges often encountered in developing writing abilities among children. The importance of early writing skills as the foundation for language learning and communication is the main focus. This stage involves introducing letter forms, fine motor training, and the ability to connect simple letters into meaningful words. Proficient writing skills serve as the basis for more complex language abilities in the future. However, there are several challenges faced in developing early writing skills in children. One of them is the lack of attention from parents and educators regarding the importance of these writing skills. Insufficient support and appropriate stimulation during the initial learning stage can hinder a child's writing development. Additionally, another challenge is the difficulty experienced by some children in overcoming fine motor obstacles. Their untrained hand-eye coordination makes it challenging to form letters clearly and neatly koordinasi tangan dan mata yang belum terlatih membuat mereka kesulitan dalam membentuk huruf-huruf dengan jelas dan teratur.
ՎԱՐԴԱՆ ԱՐԵՒԵԼՑՈՒ ՆԵՐԲՈՂՆԵՐԻ ԲԱՌԱՅԻՆ ԱՐՎԵՍՏԸ/ THE WORD ART OF VARDAN AREVELTSI'S ODES/ СЛОВЕСНОЕ ИСКУССТВО ОД ВАРДАНА АРЕВЕЛЦИ
Authors: Grigoryan Susanna
Published: February 2024

The given article is dedicated to the linguistic features of Vardan Areveltsi’s odes. Vardan Areveltsi is one of the prominent figures of the Armenian medieval culture, a national-public figure, philosopher, historian, chronicler, literary man, translator, geographer.

The author's honest patriotism, sympathy for the pain and care of the motherland is manifested in the comments.

Vardan Areveltsi’s dialects stand out for their unique linguistic structures and stylistic features. They are rich in epithets, comparisons, repetitions, contrasts. The use of these stylistic means provides the odes with unique expressiveness and sensitivity.

The wealth and beauty of Vardan Areveltsi’s odes is also manifested in the system of imagery, that is created by the appropriate linguistic and stylistic means, by the nature of the selection and application of which the degree of artistry of his work is determined.

With the help of imagery and expressive means, not only does the writer make the object of thought real and tangible, bringing up relevant images in the reader's imagination and influencing his imagination, but he also makes the described phenomenon bright and impressive (Qyoseyan, p. 5).
ՀԱՐՑՈՒՊԱՏԱՍԽԱՆ ԱՐՏԱՀԱՅՏՈՂ ԽՈՍՔԱՅԻՆ ԱԿՏԵՐԻ ԼԵԶՎԱԳՈՐԾԱԲԱՆԱԿԱՆ ԱՌԱՆՁՆԱՀԱՏԿՈՒԹՅՈՒՆՆԵՐԸ ԳՈՐԾԱՐԱՐ ՀԱՐՑԱԶՐՈՒՅՑԻ ՀԱՂՈՐԴԱԿՑԱԿԱՆ ԿԱՂԱՊԱՐՈՒՄ/ PRAGMALINGUISTIC PECULIARITIES OF SPEECH ACTS EXPRESSING QUESTION-ANSWER IN THE COMMUNICATIVE MODEL OF BUSINESS INTERVIEWS/ ПРАГМАЛИНГВИСТИЧЕСКИЕ ОСОБЕННОСТИ РЕЧЕВЫХ АКТОВ ВЫРАЖАЮЩИХ ВОПРОС-ОТВЕТ В КОММУНИКАТИВНОЙ МОДЕЛИ БИЗНЕС-ИНТЕРВЬЮ
Authors: Grigoryan Syuzanna
Published: February 2024

The given article studies speech acts expressing questions and answers in business interviews in the English language. A business interview is considered as a combination of locutionary, illocutionary, perlocutionary acts, which emphasize the communicative purpose and intention of the interlocutors, as well as the influence of businessmen on the further choice and actions of the audience. The thorough analysis of speech acts shows that perlocution is of key importance in the question-answer speech sequence in business interviews. Our study identifies the most common speech acts in the discourse of a business interview, which are used as a means of achieving the desired perlocutionary effect. The perlocutionary effect refers to consumers’ thoughts, emotions, opinions, choices, and post-communicative behavior resulting from a businessman’s discourse.
Pengaruh Kompensasi, Karakteristik Individu Dan Lingkungan Kerja Terhadap Kinerja Karyawan Di PT. Bank Sumut Cabang SEI Rampah
Authors: Safina Wan Dian , Fadhilah Nur , Samosir Suhaila Husna
Published: February 2024

Tujuan penelitian ini adalah untuk mengetahui pengaruh Pengaruh Kompensasi, Karakteristik Individu Dan Lingkungan Kerja Terhadap Kinerja Karyawan Di PT. Bank Sumut Cabang Sei Rampah baik secara parsial maupun simultan. Jenis penelitian ini menggunakan data primer dan data skunder. Sedangkan teknik pengumpulan data menggunakan observasi, angket dan wawancara. Sampel pada Karyawan PT. Bank Sumut Cabang Sei Rampah sebanyak 43 Karyawan. Teknik analisis data menggunakan analisis regresi linear berganda, pengujian hipotesis (Uji t dan Uji F), dan koefisien determinasi. Hasil penelitian ini membuktikan bahwa secara parsial diketahui t-hitung Kompensasi (X1) sebesar 2.704 > 1.682, Karakteristik Individu (X2) sebesar 2.309 > 1.682, dan Lingkungan Kerja (X3) sebesar 2.158 > 1.622, maka H0 ditolak dan Ha diterima yang berarti berpengaruh terhadap Kinerja Karyawan, dan secara simultan diketahui nilai F-hitung 20.706 > F-tabel 2.85 maka ada Pengaruh Kompensasi, Karakteristik Individu Dan Lingkungan Kerja Terhadap Kinerja Karyawan Di PT. Bank Sumut Cabang Sei Rampah.
Determinan Kepatuhan UMKM Dalam Membayar Pajak Penghasilan Pada UMKM Kabupaten Deli Serdang
Authors: Noviani Sri , Harahap Wilda Sri Munawaroh
Published: February 2024

Penelitian ini bertujuan untuk mengetahui determinan kepatuhan umkm dalam membayar pajak penghasilan pada umkm kabupaten deli serdang. Penelitian ini lebih menekankan pada suatu proses dalam menyelesaikan masalah dengan peneliti ikut terlibat langsung dalam objek yang diteliti. Data yang dikumpulkan dapat berupa hasil wawancara dengan informan yang diuraikan dalam sebuah pertanyaan, observasi dan studi pustaka. Hasil pengumpulan data tersebut dianalisis dan ditarik kesimpulan. Lokasi yang dilakukan dalam penelitian ini adalah di UMKM Kabupaten Deli Serdang yang menjadi Objek penelitian yang tersebar di daerah, Jl. Karya Utama No.4, Perbarakan, Kec. Lubuk Pakam, Penelitian bertujuan untuk mendeskripsikan pelaksanaan dari awal penelitian sampai selesai pengumpulan data. Analisis data merupakan proses mencari dan menyusun data secara sistematis, data yang diperoleh dari hasil wawancara, catatan lapangan dan bahn-bahan lainnya sehingga dapat mudah di pahami dan temuannya dapat di informasikan kepada orang lain.  Rata-rata Tarif PPh yang terlihat pada tabel adalah 6,50%. Namun, perlu diperhatikan bahwa rata-rata tersebut tidak terkait langsung dengan data yang diberikan pada tahun-tahun spesifik dalam tabel. Hal  ini  membuktikan  bahwa semakin tinggi  informasi perpajakan  yang diberikan dan diterima  oleh  pelaku  UMKM,maka  akan  semakin  tinggi  pula  tingkat  kesadaran  akan kepatuhan pajak UMKM.
In front of bars: the occurrence of burnout syndrome in female police officers
Authors: Silva Nayla Cristina Santiago da , Cury Elenir Rose Jardim
Published: February 2024

Burnout results from chronic workplace stress that has not been successfully managed. The objective of this study was to investigate the presence of Burnout Syndrome (BS) in female criminal police officers who work in the prison system of Mato Grosso do Sul, in order to understand its triggering factors and levels of manifestation. A quantitative exploratory research was carried out, with a cross-sectional design. The data demonstrated the presence of BS in 14.7% (IC95%: 7.6% to 24.7%) of the participants, especially in younger women, those without children and those who work in the care sector. Among others, there was an association between a high level of emotional exhaustion and working in the care sector, drinking alcohol and not practicing physical activity; the results highlighted the need for attention to the mental health of these professionals and the development of strategies that minimize the harmful effects of prison work.
Repercussions of admission in hospitals of custody and psychiatric treatment on subjectivity: integrative review of the literature
Authors: Shimada Beatriz Yokimi Shimada , Raphaloski Giovanna Lyssa Ferreira Raphaloski , Colleti Mayara , Scorsolini-Comin Fabio Scorsolini-Comin
Published: February 2024

This study aimed to synthesize the scientific literature produced regarding the process of suppression of human subjectivity in people with mental disorders who have broken the law and are subject to hospitalization in custody and psychiatric treatment hospitals. An integrative review without temporal delimitation was carried out. The searches were carried out by two independent judges in the databases/libraries VHL (Virtual Health Library), LILACS, SciELO and ReP (USP Production Repository). After applying the eligibility criteria, 13 productions were recovered. The literature emphasizes the history of madness and crime, its impacts on society and the consequent social exclusion of individuals institutionalized in custodial hospitals. Even with the Psychiatric Reform, these institutions still employ a protective and hygienist discourse, suppressing the subjectivity of these subjects. The literature asserts the need to strengthen an intersectoral policy, thus promoting comprehensive care for people with mental disorders in conflict with the law.
The importance of experimentation in physics teaching in the education of young people and adults
Authors: Barrelo Junior Nelson , Costa Isa , Martins Thayna Dias
Published: February 2024

The use of experimentation in the classroom provides a practical approach to learning scientific concepts, allowing students to establish a direct relationship between theory and practice. Critical thinking is stimulated and promotes exploration and discovery, making it an interesting methodology for youth and adult education (EJA). In this context, this research project aims to investigate the importance of using experiments in teaching physics at EJA. The study seeks to analyze how the incorporation of experiments can facilitate the understanding of physical phenomena and promote meaningful learning for these individuals. The main difficulties encountered by EJA students in learning physics will be presented and the way in which experiments can collaborate to overcome these challenges will be evaluated. Through this research, it is expected to obtain results that contribute to the implementation of effective physics teaching strategies in EJA, valuing experimentation as a pedagogical tool capable of promoting more relevant learning for these students.
Academic Procrastination and its Association with Academic Achievement among Undergraduate Health Sciences’ Students
Authors: Hussain Khalid , Baloch Zafar Iqbal , Fayyaz Muhammad , Rahimoon Ubedullah , Ahmed Tanseer
Published: February 2024

Background: Academic procrastination is the postponement of educational activities. Most university students try to keep themselves away from academic activities which might lead to procrastination and unsatisfactory performance.
Objective: To assess the level of academic procrastination and its association with academic performance and the demographic characteristics of undergraduate students.
Methods: This cross-sectional analytical study using a convenient sampling technique was conducted on 250 health sciences undergraduate students at Sohail University, Karachi, Pakistan from August to October 2022. Ethical approval and data collection permission were obtained. The Procrastination Assessment Scale for Students was used to gather data. The SPSS version-24 was used for statistical analysis. Simple descriptive statistics, spearman’s rank order correlation coefficient tests and independent sample t-test was applied.
Results: Mostly participants (53.6%) were female, 93.2% were single, and 46 % in the generic nursing program and 54% were in 3rd & 4th year. Students’ academic performance was insignificant with all the domains except writing a term (p-value 0.22, 0.5, 0.26, 0.37, 0.31 and 0.041 respectively). A significant relationship of students’ gender, education level and study program with academic procrastination was found (p-value 0.004, 0.021 and 0.002 respectively). Bachelor of Science in Nursing (BSN) and Pharm-D programs did not show as much procrastination as compared to Doctor of Physical Therapy (DPT) program (p-value 0.021).
Conclusion: This study showed the considerable behaviour of procrastination among undergraduates. There was a significant association between writing a paper and academic achievement. In addition, academic procrastination was significantly associated with gender and the enrolled program of the participants.
Nurses in Politics: An Emergent Need
Authors: Tariq Ali  , Khan Kashif
Published: February 2024

Nurses are recognized for their vigorous role in healthcare, own untapped potential in politics. Their advocacy skills, honed through patient care, could be harnessed to make policies for improved healthcare access and health equity. The representation of nurses in politics is unreasonably low, in U.S., only 10 out of 535 Congress members are nurses, despite being the largest group of healthcare professionals. Similarly, there is absence of nursing representation in Pakistan's parliament. To tie this gap, nurses should be inspired to enter politics, provided with mentorship, policy training, and financial support.
Macassa Mine Geology
Authors: Cater D. F.
Published: February 2024

The Macassa Mine, a division of LAC Minerals Ltd. is situated immediately west of the town of Kirkland Lake, Ontario. It is the only active producer of seven (7) mines located along the famed Mile of Gold in the Kirkland Lake Gold Camp. Production from all seven mines in the camp from inception to the end of 1989 amounted to 52.6 million tons generating 23.4 million ounces at an average grade of 0. 446 ounce/ton (source: MNDM resident geologists office pers. comm. ). Production at the Macassa Mine commenced in late 1933 at a rate of 200 tons per day. The mine has produced gold continuously for the past 58 years. In May 1990, the Macassa Mine produced its 3 millionth ounce. Total mine production to the end of 1990 amounts to 6,835,110 tons mined yielding 3,070,502 million ounces of gold at an average grade of 0. 45 ounce/ton. The cut-off grade at the mine is 0.25 ounce/ton. Current proven and probable ore reserves are estimated as of January 1991 to be 1. 67 million tons at a grade of 0. 53 ounce/ton. Current underground production is on the order of 550 tons per day.

The Kirkland Lake Gold Camp is situated on the southwestern portion of the Abitibi greenstone belt (Fig. 1). On a smaller scale, the Kirkland Lake area can be considered as a series of volcanic, sedimentary and intrusive litho-units which strike N 60–80 E and dip steeply to the- south. These litho units which lie within the Timiskaming group are wrapped around both the Lebel Stock and Round Lake Batholith situated to the south.
Study of the effectiveness of teaching cultural geography in a school’s geography course
Authors: Satybaldieva Ayzhan , Kaimuldinova Kulyash , Laiskhanov Shakhislam , Shakirova Nurzhanat , Muzdybayeva Karlygash
Published: February 2024

The experience of countries with developed education and the work of scientists who have conducted research in this area indicate that cultural geography is the most important factor in the formation of the worldview of students.  However, an analysis of the state of teaching cultural geography in secondary schools in Kazakhstan has shown that it is insufficiently studied. The cultural geography components of geography are included in school geography textbooks, although they are not specifically taught as an independent subject or course.  Therefore, an elective course on Cultural Geography was developed to fill this gap, and its effectiveness was studied through experimental research. The general secondary education school in Almaty City was chosen as the base of the experiment. The experiment, in which a total of 50 students voluntarily participated, was conducted from September 2021 to the end of May 2022.  In order to determine the educational levels of students after the course, three stages of monitoring were conducted and 15 tasks of different levels were given. The experiment's findings demonstrated the significance of the elective "Cultural Geography" course in helping students develop their subject competencies and the value of implementing it in regular secondary schools.
Leg het uit
Authors: Van ’t Klooster Maryse
Published: February 2024

Martine van Zandvoort is op 1 juli 2021 benoemd als hoogleraar Translationele Neuropsychologie aan de Universiteit Utrecht, bij zowel de faculteit Sociale Wetenschappen als bij de faculteit Geneeskunde. Op 23 juni 2023 sprak zij haar oratie uit getiteld ‘Leg het Uit’. In deze bijdrage een verkorte weergave van haar oratietekst, met als belangrijkste boodschap: verbindt onderzoek en onderwijs met zorg voor de patiënt vanuit het neuropsychologische perspectief.
Poliklinisch instellen van een ketogeen dieettherapie, de voors en tegens
Authors: Van der Louw Elles
Published: February 2024

Ketogeen dieettherapie, een zeer vetrijk, streng koolhydraat beperkt dieet met voldoende eiwit en energie, is een bewezen effectieve behandeling voor therapieresistente epilepsie. Vanwege het risico op bijwerkingen wordt een dergelijke therapie veelal tijdens een ziekenhuisopname gestart. Het ‘ketoteam’ van het Sophia Kinderziekenhuis biedt sinds 2008 poliklinisch een ketogeen dieettherapie aan, die effectief is en veilig maar ook zorgkosten kan besparen.
Evaluatie van slaap- en ademhaling bij kinderen met CDKL5-deficiëntiestoornis: lange termijn beloop
Authors: Hagebeuk Eveline , Smits Annelies , De Weerd Al
Published: February 2024

CDKL5-deficiëntiestoornis is een genetische epileptische encefalopathie. Het is aangetoond dat kinderen met deze stoornis veelal forse slaapproblemen en ademhalingsstoornissen (in waak) hebben. Vooral slaapstoornissen kunnen een aanzienlijke invloed hebben op het emotionele welzijn en de levenskwaliteit van verzorgers van kinderen met een CDKL5-deficiëntiestoornis. Hopelijk draagt de lange termijn studie1 die hier wordt besproken bij tot het vinden van een optimale behandeling van de epilepsie en slaap bij deze kinderen.
Analyzing sentiment and its application in deep learning: Consistent behavior across multiple occasions
Authors: Xiang Yanxiong
Published: February 2024

This article offers a systematic review of the evolution in sentiment analysis techniques, moving from unimodal to multimodal to multi-occasion methodologies, with an emphasis on the integration and application of deep learning in sentiment analysis. Firstly, the paper presents the theoretical foundation of sentiment analysis, including the definition and classification of affect and emotion. It then delves into the pivotal technologies used in unimodal sentiment analysis, specifically within the domains of text, speech, and image analysis, examining feature extraction, representation, and classification models. Subsequently, the focus shifts to multimodal sentiment analysis. The paper offers a survey of widely utilized multimodal sentiment datasets, feature representation and fusion techniques, as well as deep learning-based multimodal sentiment analysis models such as attention networks and graph neural networks. It further addresses the application of these multimodal sentiment analysis techniques in social media, product reviews, and public opinion monitoring. Lastly, the paper underscores that challenges persist in the area of multimodal sentiment fusion, including data imbalance and disparities in feature expression. It calls for further research into cross-modal feature expression, dataset augmentation, and explainable modeling to enhance the performance of complex sentiment analysis across multiple occasions.
Implementing the AlphaZero algorithm for Connect Four: A deep reinforcement learning approach
Authors: Guo Yubo
Published: February 2024

The realm of board games presents a challenging domain for the application of artificial intelligence (AI), given their vast state-action space and inherent complexity. This paper explores the development of a proficient AI for Connect Four using DeepMind's AlphaZero algorithm. The algorithm employs a policy-value network for concurrent prediction of action probabilities and state values, and Monte Carlo Tree Search (MCTS) for decision-making, guided by the policy-value network. Through extensive self-play and data augmentation, our AI learns without the need for explicit prior knowledge. Our experiment demonstrated that the AI player showed significant capability in playing Connect Four, exhibiting strategic decision-making that sometimes-surpassed human performance. These results underline the potential of deep reinforcement learning in advancing AI performance in complex board games.
A review on current progress of semantic segmentation
Authors: Liu Jinqi
Published: February 2024

Semantic segmentation, as an important task in the field of computer vision, has wide applications in image analysis and scene analysis. These application domains include autonomous driving, medical image analysis, image identification, and intelligent video surveillance. However, it faces many challenges due to the complex image structures and some confusing relationships between objects. This paper aims to provide an overview of key concepts in the field of semantic segmentation, including datasets and annotations, data augmentation, some relevant algorithms and models, and loss functions. By introducing and analyzing these concepts, we can gain a comprehensive understanding of the research progress and future directions in semantic segmentation. This paper also provides research advancements in the field of semantic segmentation. Through the introduction and analysis of these different concepts, we gain a deeper understanding of the current state and challenges of semantic segmentation. With the continuous development of deep learning techniques, we can expect semantic segmentation to have broader applications in the fields of computer vision and artificial intelligence.
Harnessing the power of AutoML: A comparative study of image recognition techniques for smoking detection
Authors: Wang Anbang , Yu Jianing
Published: February 2024

As infrastructure continues to evolve, the significance of fire protection escalates. Many fires are caused by smoking in smoke-free areas, underscoring the necessity to promptly detect smoking activities in hazardous zones. In this scenario, image recognition emerges as a pivotal tool. The accuracy and efficiency of image recognition bear substantial implications for both academic and industrial sectors, and these aspects form the crux of our investigation. This study aims to compare the performance of image recognition techniques based on automatic machine learning with those of traditional methods such as YOLO. Our findings indicate that image recognition powered by automatic machine learning outperforms YOLO recognition in terms of efficiency and accuracy.
Research and application analysis of typical recommendation methods
Authors: Zhang Mingyang
Published: February 2024

Recommendation systems are vital tools in the modern digital landscape for handling vast amounts of online data and are now employed across a variety of sectors. This manuscript underlines the importance of video recommendation algorithms and delves into the three main types: content-based, collaborative filtering, and hybrid algorithms. Content-based algorithms offer suggestions by assessing and matching the descriptive attributes of videos. These attributes could range from the genre, the actors involved, the director, or any other related metadata. On the other hand, collaborative filtering algorithms provide recommendations by comparing the user's historical data with that of others. They function on the principle that individuals who have agreed in the past are likely to agree again in the future. Hybrid recommendation algorithms, as the name suggests, are a combination of both content-based and collaborative filtering algorithms. They aim to harness the strengths of the two while mitigating their individual weaknesses, providing more balanced and accurate recommendations. This detailed exploration of these algorithms not only underscores their significance but also paves the way for the future, heralding the potential advancements and adaptations these systems could undergo. Continued innovation in this realm has the potential to revolutionize how information is processed and shared, ultimately enriching the user experience across the digital platform landscape.
Modified A* algorithm for path smoothing and obstacle avoidance
Authors: Geng Hui
Published: February 2024

With the rapid development of robotics technology, path planning is a crucial aspect of autonomous robot systems. Among them, planning paths involves using the A* algorithm, which is a common method. However, traditional A* algorithm has several limitations in path planning, such as poor real-time performance, large amount of computation per node, long computation time, low algorithmic search efficiency. Based on this, two improved approaches for the A* algorithm are proposed. The first is expanding the obstacles in the map by increasing their expansion radius. The second is the Hybrid A* algorithm, which optimizes the A* algorithm by modifying its heuristic function. Specifically, the Hybrid A* algorithm combines two heuristic functions: one based on non-holonomic constraints and the other based on dynamic programming. Experimental tests are conducted under various map expansions and branching parameters to compare the performance of these two algorithms in terms of path length, execution time, and path smoothness at corners. The results demonstrate that, with smaller branching parameters, the Hybrid A* algorithm generates shorter paths. However, in highly complex mazes, the path length of the Hybrid A* algorithm may be longer, but it exhibits smoother movements at corners.
Sentiment analysis and implementation in film evaluation utilizing BERT
Authors: Zhou Fangbing
Published: February 2024

This study explores the use of the dmsc_v2 dataset, which is a rich collection of over 2 million ratings and commentary data from over 700,000 users on 28 films, to train the BERT model for sentiment analysis. This expansive dataset, drawn from the popular Chinese movie-rating website, Douban, has been meticulously curated for this research. In the context of the methodology, it is comprehensive and involves multiple stages. Initially, data preprocessing is conducted to refine and format the dataset suitably for model training. Subsequently, the BERT model is trained using the prepared data. Following the training process, the model's performance is critically evaluated to validate its efficacy and accuracy. The resulting model is adept at performing sentiment classification on comments pertaining to films across various social media platforms such as Weibo, Xiaohongshu, and more. This is particularly beneficial as it enables a nuanced analysis of user opinions and trending topics, offering invaluable insights for businesses, movie producers, or marketers. The findings of this study demonstrate that the BERT sentiment analysis model, developed with the dmsc_v2 dataset, exhibits impressive performance and has expansive potential for application within the sphere of social media commentary analysis. The successful development and validation of this model underscore its potential to transform the way sentiment analysis is conducted, especially in the context of entertainment and social media discussions.
Model and algorithm analysis of MPC control in aerospace engineering
Authors: Wang Wenxi
Published: February 2024

With the continuous development of time and technology, the control system has thus evolved in the direction of great complexity. In the field of path control, once control algorithms cannot absolutely meet the requirements of all people, so this paper introduces an alternative algorithm-MPC. This article focuses on the development of MPC from when it is invented and its application in aerospace today with specified examples, and then lists and analyses the mainstream MPC algorithms, namely LTI, LTV, LPV, PWA and nonlinear systems. Article below also illustrates the derivation of sample of non-parametric model-based algorithms (Dynamic matrix control) and parametric model-based algorithms (Generalized Predictive Control) and the elaboration of mainstream systems and their applications in the form of an overview. Eventually gives a conclusion to the current situation of MPC and relationships among various algorithms. Note that this article is mainly aimed at scholars who are new to MPC algorithms.
Improving machine translation and post-editing for Chinese tourism texts using transformer-based models
Authors: Feng Yuan , Hu Qiwei , Yang Siran
Published: February 2024

As the digital age and globalization continue to evolve, the demand for accurate machine translation of tourism texts has increased substantially. This paper investigates how to improve the quality of machine translation (MT) and machine translation post-editing (MTPE) of Chinese tourism texts for non-native speakers. A review of the machine translation literature reveals a significant progression in translation methods from rule-based to corpus-based, statistical, and finally to the current neural machine translation (NMT) models. Despite its advanced capabilities, NMT requires large amounts of parallel data for training, which often presents challenges. This study proposes the use of Transformer-based models for MT and MTPE to improve translation quality. A dataset was curated from online sources, mainly Chinese tourism websites. The methodology involved pre-processing the data, performing machine translation using the Transformer model, and post-editing the results. The experiment demonstrated an increase in the BLEU score, suggesting an improvement in translation quality. However, challenges such as the handling of synonyms and geographical nouns were encountered, indicating the need for further research and model optimization.
Research on the application of computer in drug design
Authors: Shi Peiyang
Published: February 2024

Virtual screening by computer is of great scientific significance for drug research and development. In recent years, a large number of computer simulation methods have been developed and applied to drug development for a variety of diseases. This paper summarized and prospected the application progress of computer aided drug design (CADD) in the research and development of new drugs, focusing on the working principle of CADD, related algorithms, and the advantages and disadvantages of existing methods. Although CADD has been successfully applied to a number of drug development projects, the accuracy of auxiliary drug structure optimization is still not high. Therefore, it is urgent to develop more accurate and efficient CADD models and algorithms to promote the process of new drug discovery.
Adaptive simulation of digital signal transmission
Authors: Ye Diwen
Published: February 2024

High-order modulated signals have lower anti-interference ability than low-order modulated signals with the same modulation method and conditions. In situations with low signal-to-noise ratios, the quality of high-order signals can degrade significantly. An algorithm capable of intelligently switching the modulation order based on the current signal-to-noise ratio can effectively address this issue. This paper presents an adaptive signal transmission algorithm that intelligently selects different orders of Phase shift keying (PSK) modulation depending on varying signal noise ratio (SNR) conditions, while ensuring the user-specified upper limit of bit error rate (BER). This approach guarantees signal transmission quality. The algorithm is implemented in Python and involves simulating the relationship curve between SNR and BER for different PSK orders. This simulation is combined with theoretical transmission rate analysis, resulting in an adaptive algorithm that intelligently switches modulation methods under complex conditions to meet transmission requirements. The proposed algorithm dynamically adapts to diverse user requirements for signal-to-noise ratios in various environments. It achieves this by adjusting the modulation order, calculating theoretical transmission times based on the given signal frequency, and ultimately verifying the actual bit error rate through transmission and testing. Upon testing, this design successfully achieved its intended goals.
Analyzing correlation with BER: Constellation diagrams across various modulation modes and FDM/OFDM
Authors: Yang Xiao
Published: February 2024

Over the last two decades, owing to rapid advancements in digital signal processing and integrated circuit technology, Frequency Division Multiplexing (FDM) and Orthogonal Frequency Division Multiplexing (OFDM) have emerged as pivotal technologies for wireless multimedia communication. Research reveals that coupling OFDM with diverse modulation modes aids in mitigating the Bit Error Rate (BER) during transmission. Nonetheless, a comprehensive elucidation remains absent regarding the interplay between constellation diagrams and BER, as well as the correlation between FDM and BER. Thus, the primary focus of this research is to dissect the correlation between BER and constellation diagrams for distinct modulation methodologies, while also scrutinizing the impact of FDM on BER. The research methodology adopted herein entails two main steps: First, gathering papers pertinent to constellation diagrams, BER, FDM, and OFDM technology. Second, leveraging survey and literature analysis methodologies for thorough examination. The findings highlight that diverse constellation diagram designs yield disparate BER outcomes post demodulation. Foremost among the influential factors on FDM and OFDM technology BER are distinct Inter-Carrier Interference (ICI) patterns and the quantity of subcarriers stemming from signal wave side lobes. To address the BER challenge, a prospective avenue involves refining the selection of constellation diagram styles for demodulation, leveraging an understanding of constellation diagram traits. Furthermore, future research endeavors should delve deeply into co-channel interference and adjacent channel interference to contribute effectively towards BER reduction and augmenting channel reliability.
Achieving stable trajectory tracking in complex environments using an adaptive PID control strategy-based quadcopter drone
Authors: Yuan Xinran
Published: February 2024

Stable trajectory tracking of unmanned aerial vehicles (UAVs) in complex environments is of paramount importance for achieving high precision and robustness in flight missions. In this paper, we address the attitude control problem of quadrotor UAVs and propose an optimization method based on adaptive PID control strategy. This text first presents an overview of the current status of UAVs both domestically and internationally, followed by the establishment of a mathematical model for quadrotor UAVs. Next, analysing the application of the traditional PID algorithm in UAV attitude control and provide a detailed description of the principles behind genetic algorithms and simulated annealing algorithms, along with their application in optimizing PID parameters. Through simulation experiments conducted in strong wind conditions, we compare the performance of the traditional PID algorithm with the optimization algorithm in stable trajectory tracking tasks. The experimental results demonstrate that the optimization algorithm significantly enhances the flight stability and accuracy of UAVs. Finally, this text summarizes the research findings and provide an outlook on future development directions.
A research of the impact of ChatGPT on education
Authors: Fu Yu
Published: February 2024

The integration of AI language models, particularly ChatGPT, into higher education has sparked concerns about academic integrity and its impact on student learning experiences. This research aims to explore the applications, benefits, challenges, and future implications of ChatGPT in education, striving to achieve a balanced and beneficial integration of AI in higher education. The study reviews related works on ChatGPT, investigating its development, capabilities, and potential applications in education. Firstly, the paper emphasizes that ChatGPT changes teaching methods, enabling teachers to adopt more flexible and interactive approaches to education. Secondly, the paper highlights that ChatGPT can provide personalized learning experiences for students by generating customized teaching content based on their needs and offering real-time assistance and guidance, thereby enhancing learning effectiveness. However, the paper also acknowledges some potential challenges and issues, including concerns regarding plagiarism and privacy, as well as the possibility of biases and the generation of erroneous information. Addressing these issues requires technological improvements and the development of sound usage policies. The paper concludes by summarizing the findings and prospects of the research.
The applications and prospects of intelligent services robots in medicine
Authors: Xinyi Wang
Published: February 2024

With the rapid growth of the ageing population and the increasing demand for medical services, the medical market is facing great challenges and opportunities. Intelligent service robots can provide various medical services, such as patient monitoring, drug distribution, medical record management, etc., which can improve medical efficiency, reduce the burden of medical staff, and have the advantage of 24-hour uninterrupted service. However, the application of intelligent service robots in the medical field still faces some challenges, such as technical limitations, legal and ethical issues. In addition, there are also differences in patient acceptance and demand for intelligent service robots. Based on the summary of intelligent medical treatment, this paper will introduce the application of intelligent service robots, study the application and prospect of intelligent service robots in medical treatment and the innovation of intelligent service robots in business models. Through literature review, SWOT analysis and data, the paper explains the wide application of intelligent service robots and their future opportunities and challenges.
A comprehensive investigation for ChatGPTs applications in education
Authors: Bao Yifei
Published: February 2024

With the surge in popularity of Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence technology, on a global scale, numerous industries have started to take notice of its potential applications in their specific sectors, including the field of education. This document presents a thorough examination of how ChatGPT is being used in the realm of education. The following piece outlines the approaches to integrating ChatGPT into education, viewed from three angles: Educational Assessment, Exercise Generation, and Personalized Learning. It also provides comprehensive guidelines aimed at both teachers and students. Utilizing ChatGPT in education allows for personalized one-on-one assistance to students, addressing challenges posed by uneven distribution of educational resources and individual differences among students. Current research on applying ChatGPT in education mostly revolves around designing prompts to elicit specific responses or using generated content for evaluating its subject-specific capabilities. Given that ChatGPT is a more versatile form of artificial intelligence not limited to any particular domain, the article suggests that future research should focus more on integrating ChatGPT into existing educational systems, ensuring its consistent performance in specific tasks. Furthermore, considering ChatGPT's possibility of generating imprecise information, it is necessary to explore how to fine-tune ChatGPT using specialized databases, enabling it to generate reliable content in professional subject areas.
ChatGPT - A new milestone in the field of education
Authors: Liu Zeyu
Published: February 2024

With the rapid development of artificial intelligence, natural language processing models like ChatGPT hold creative potential for applications in education. This study focuses on ChatGPT and explores its applications in the field of education. This research employs literature review and case analysis methods to systematically investigate the applications of ChatGPT in instructional assistance, personalized education, and writing support. By analyzing three cases involving ChatGPT's professional competence in medical exams, the construction of personalized learning systems, and writing support, the paper emphasizes ChatGPT's advantages in education, future development directions, as well as ethical and privacy concerns. The study finds that ChatGPT possesses strong semantic understanding and analytical capabilities. Within the context of general applicability, it can provide accurate answers to questions posed by users with certain specialized backgrounds. The paper not only addresses ChatGPT's role as a student's auxiliary tool but also explores collaborative models between ChatGPT and teachers. However, it's important to note that ChatGPT currently has limitations in terms of limited knowledge and inadequate emotional understanding. Additionally, in terms of ethics and privacy, considerations regarding information protection and moral aspects within the educational application of ChatGPT are crucial. In the future, it's worth further exploring specialized models for ChatGPT's tasks in both teacher and student roles, along with enhancing ChatGPT's emotional support capabilities.
A comparative analysis of convolutional coding and block coding techniques over satellite communication
Authors: Hou Yuchen
Published: February 2024

Reliable data transmission is crucial in the field of satellite communication, and many coding schemes are used to improve this reliability. Two popular coding techniques: convolutional codes and block codes were investigated and compared in this paper. Utilizing a simulated environment, the author investigates the bit error rate (BER) performance of both coding strategies along with a baseline case of no coding. The analysis reveals distinct characteristics and performance attributes of the two coding techniques across a range of signal-to-noise rate (SNR) values. Convolutional codes, with their inherent memory, offer error protection across sequences, while block codes, particularly a Hamming-like 7,3 implementation, provide localized protection for individual blocks. The findings of this study contribute to the understanding of error control strategies in satellite communication, guiding the selection and design of coding methods suitable for various operational scenarios and requirements.
Design of lower limb rehabilitation exoskeleton with self-adaptive knee optimal force
Authors: Shi Hongyu , Tao Yuchen , Wang Hanyu
Published: February 2024

With the increasingly serious trend of population aging in China, various diseases of the elderly are emerging in an endless stream, including hemiplegia, half limb disorder, limb numbness, hemianopia, and aphasia, with a high disability rate. The available auxiliary device cannot make a clear assistance for the patient, so that this design plans to make an exoskeleton for the patients who need effective rehabilitation alternatives and improve the rehabilitation efficiency. In this design, we would create Solid works model with some joint to fit human knees and then select sensors which are suitable to collect signs to depict kinematics features. The model, which has self-adaptation for receiving force signs from calf and knee joint, depends on the different force points of the calf lift affecting the stress state of the knee joint. Because the different stress points of the calf lift directly affect the stress state of the knee, so to find the best stress point of the calf is the research direction of this paper. In order to find the best and the most suitable force point of the human lower limb, we two methods, step-by-step process and dichotomy process, were discussed and compared in this study. Reasonable material may decide the robotic features.
Comparison and analysis of the number of convolutional layers in CNN-based breast cancer detection
Authors: Zhang Jiayu
Published: February 2024

Breast cancer is becoming more and more common, and the mortality rate is increasing, which is indeed a serious problem. To alleviate this problem, this study applies a convolutional neural network (CNN) model to analyze breast cancer images formed by mammography. The CNN model has the property of automatically learning hierarchical feature representations from the original image data. The structure of the CNN enables it to capture spatially hierarchical features at multiple scales, including edges, textures, and objects. Specifically, this study explores the performance of CNN models on prediction tasks by varying the number of convolutional layers. This study is conducted on the DDSM mammography dataset. The experimental results demonstrate that CNN models are effective for detecting breast cancer, both in terms of accuracy and loss rate, and that more convolutional layers improve performance. In particular, the model saturates at four convolutional layers to reach the highest performance. Thus, this study helps to accelerate the efficiency of breast cancer detection and paves the way for more efficient methods in the future.