bluuebunny/crossref_metadata_2025 huggingface dataset:
STUNTING: FAKTOR RISIKO, DIAGNOSIS, TATALAKSANA, DAN PROGNOSIS
Authors: Apriastini Ni Komang Tri , Adnyani Ni Putu Tia , Selvyani Putu Onik , Setiawan Komang Hendra
Published: August 2024

Stunting merupakan masalah gizi kronis yang ditandai dengan adanya deviasi pada indeks tinggi badan per umur atau TB/U anak berada di bawah -2 standar deviasi (SD) dari median WHO untuk populasi referensi yang sama dan jenis kelamin yang sama. Stunting masih menjadi permasalahan kesehatan di Indonesia dengan prevalensi mencapai 24,4% pada tahun 2021. Ada beberapa faktor yang mempengaruhi terjadinya stunting, faktor-faktor tersebut, yaitu praktik pemberian ASI eksklusif, pola pemberian makanan pendamping ASI (MP-ASI), riwayat Berat Badan Lahir Rendah (BBLR), riwayat penyakit infeksi kronis, keadaan sanitasi, kondisi sosial dan ekonomi keluarga, serta tingkat pendidikan ibu. Diagnosis stunting ditegakkan dengan anamnesis, pemeriksaan fisik, dan pemeriksaan penunjang. Anak dengan hasil TB/U <-2 SD dapat dinyatakan stunted perlu dievaluasi lebih lanjut mengenai status gizi anak dengan pemeriksaan berat badan, lingkar kepala, kecepatan tumbuh, dan potensi tinggi genetik. Tatalaksana stunting dimulai dengan tindakan pencegahan dan melakukan tindakan kuratif pada anak stunting. Prognosis stunting adalah baik apabila terdeteksi dan mendapat intervensi gizi lebih dini.
DISTRIBUSI KASUS PASIEN BENDA ASING PADA TELINGA, HIDUNG DAN TENGGOROKAN INSTALASI GAWAT DARURAT RSUD KABUPATEN BULELENG
Authors: Aristhagoza I Gede Agustian , Susantini I.G.A Dwi
Published: August 2024

Kasus benda asing yang terjadi di hidung, telinga, dan faring merupakan salah satu insiden yang cukup umum terjadi dalam masyarakat. Diagnosis pada pasien seringkali mengalami keterlambatan karena penyebabnya tidak terlihat secara langsung, gejalanya tidak khas, dan terdapat risiko kesalahan diagnosis diawal. Sehubungan dengan itu, sebuah gambaran distribusi pasien kasus benda asing diperlukan sebagai data epidemiologi suatu penyakit yang nantinya diharapkan berimplikasi terhadap penganggulangan kasus ini di daerah tersebut. Adapun tujuan dari penelitian ini adalah untuk mengetahui distribusi pasien kasus benda asing pada THT IGD RSUD Kabupaten Buleleng periode Januari 2022-Desember 2023. Jenis penelitian ini adalah penelitian deskriptif dengan pendekatan cross-sectional retrospektif menggunakan data sekunder rekam medis. Teknik pengambilan sampel penelitian ini menggunakan total sampling dengan jumlahnya sebanyak 82 sampel. Hasil penelitian menunjukkan kasus benda asing dominan terjadi pada pasien balita (0-5 tahun) dengan jumlah 38 kasus (46,3%) dan berjenis kelamin laki-laki sebanyak 45 kasus (54,9%). Lokasi corpus alienum paling banyak ditemukan pada KAE yaitu 35 kasus (42,7%) yang jenisnya berupa corpus alienum organik sejumlah 46 kasus (56,1%) dengan mayoritasnya merupakan serangga sejumlah 22 kasus (26,8%). Hasil penelitian ini pun sejalan dengan literatur dan mayoritas penelitian sebelumnya sehingga dapat menjadi dasar edukasi kepada orang tua agar lebih mengawasi anaknya ketika bermain.
HUBUNGAN BEBAN KERJA DAN LINGKUNGAN KERJA DENGAN STRES KERJA PADA USAHA DODOL DESA PENGLATAN
Authors: Wijaya I Made Kusuma , Wibowo IP Adi
Published: August 2024

Kesehatan dan keselamatan kerja merupakan salah satu aspek yang perlu diperhatikan pada UMKM dodol karena terdapat berbagai risiko yang dapat menimbulkan kecelakaan/penyakit pada pekerja sehingga menurunkan produktivitas perusahaan. Penelitian ini bertujuan menganalisis hubungan faktor lingkungan dan beban kerja terhadap stress pekerja dodol. Penelitian ini merupakan penelitian analitik observasional dengan pendekatan cross-sectional. Penelitian ini dilaksanakan di desa Penglatan. Sampel penelitian adalah pekerja dodol di desa Penglatan, sebanyak 60 orang yang dipilih secara purposive sampling. Data penelitian dikumpulkan menggunakan angket dan observasi. Analisis data menggunakan model analisis regresi logistik ganda yang disajikan dalam grafik dan tabel. Hasil analisis data menunjukan bahwa tidak terdapat hubungan antara beban kerja dengan stress kerja pekerja dodol di desa Penglatan. Hasil sebaliknya ditemukan pada lingkungan kerja dimana hasil analisis data menunjukan terdapat hubungan yang secara statistik signifikan antara lingkungan kerja dengan stress kerja pekerja dodol di desa Penglatan. Berdasarkan atas hasil tersebut disarankan kepada pengusaha dan pemerintah secara bersama-sama untuk selalu memperhatikan lingkungan kerja pada UMKM sehingga akan meningkatkan kinerja dan produktivitasnya.
Usability, Reliability, Security, and Status: Unpacking the Factors Shaping User Choice between iOS and Android in Saudi Arabia
Authors: Alzahrani Abdullah Abdualrahman H.
Published: August 2024

This investigation delves into user perceptions of iOS and Android operating systems within the Kingdom of Saudi Arabia. A sample of 594 participants was recruited to explore their preferences concerning usability, reliability, security, social influence, and prior experiences with both systems. The study reveals a modest predilection for iOS in terms of user-friendliness and perceived information security. Interestingly, a counterintuitive finding emerged: Android users, particularly females, exhibited high confidence in information security despite encountering a greater number of cyberattacks. Additionally, the research highlights the influence of sociodemographic factors, such as age, education level, and gender, on system selection. A pronounced desire to utilize iOS was observed among younger users, females, and individuals with higher educational attainment. While the study provides a robust foundation for understanding user preferences within the Saudi Arabian context, limitations such as sample size and geographic focus necessitate further research efforts across more heterogeneous populations to achieve a more generalizable depiction.
Introducing Artificial Intelligence (AI), Swarm Intelligence (SI) and Bio-Inspired Algorithms Concepts to Elementary and Secondary (K-12) Education Using Block-Based Programming Environments: A Simplified Simulation Inspired by Artificial Fish Swarm Optimization Algorithm (AFSO)
Authors: Salpasaranis Konstantinos
Published: August 2024

Artificial Intelligence (AI) and Machine Learning (ML) have the potential to revolutionize education, with applications ranging from personalized learning systems to teaching students about AI concepts. Beyond utilizing and integrating these technologies, it is crucial to comprehend the fundamental principles governing the field. Choosing an “attractive” area of AI suitable for students and engaging them is essential to introducing difficult Computer Science concepts. In particular, introducing these concepts in elementary and secondary (K-12) Education is not a simple task, as it involves complex algorithms and theories that could overwhelm young learners. To overcome this challenge, we can rely on nature-inspired or bio-inspired algorithms such as Swarm Intelligence (SI) family, and leverage block-based programming environments (like MIT Scratch or other Logo-like environments) to make AI concepts more accessible and intuitive for students. This article proposes the creation and implementation of simplified simulations inspired by the Artificial Fish Swarm Optimization Algorithm (AFSO)-namely how fish behave collectively in the ocean–as an educational tool for both elementary and secondary school students. The proposed educational methodology combines the integration of Constructionist Learning principles, as the “Creative Thinking Spiral” learning model, with the inquiry-based approach of the 5Es Instructional Model.
Estimating Bedrock Depth Based on Total Magnetic Field Anomaly Data in Medan City Area in the Northern Sumatra Basin Using the Peter Half Slope Method
Authors: Rasimeng Syamsurijal , Sianturi Rizky J. , Surbakti Lucky Dolinta , Kurniawan Yoga , Dani Ilham , Rustadi Rustadi
Published: August 2024

The Peter Half Slope method is valuable for estimating rock depths using total magnetic field anomaly data. It relies on graphical analysis and practical rules to gauge the depths of magnetic sources. This method finds significant utility in magnetic interpretation, measuring half the maximum slope distance on magnetic anomaly curves. The primary objective of this research is to determine anomaly depths within Medan City by applying the Peter Half Slope method. The study employs total magnetic field anomaly data from the Medan city area, a part of the Northern Sumatra Basin. The research methodology includes data preparation, reduction to the pole transformation, profile creation, maximum slope computation, half-slope determination, and identifying tangent points on both minimum and maximum curves. The difference between these tangent points is then calculated to derive the depth of the bedrock. Based on the depth calculations using criteria for very thin, intermediate thickness, and very thick bodies, depths of 401, 301, and 240 meters were obtained, resulting in an average depth of 314 meters. This method plays a pivotal role in characterizing subsurface rock structures and is essential for geophysical analysis and magnetic data interpretation.
Macar Fiğinde (Vicia pannonica Crantz) Ot Verimi ve Kalite Açısından Uygun Hasat Zamanının Belirlenmesi
Authors: Mutlu Ziya , Ünal Sabahaddin , Efe Berna
Published: August 2024

Yarı–kurak bölgelerde ekim nöbetinde ot üretimi amaçlı Macar fiğinin yer alması oldukça önemlidir. Ancak kendinden sonra gelecek tahılların verimini fazla etkilememesi için tarlayı erken terk etmesi gereklidir. Bu çalışmada, Macar fiği 1) çiçeklenme başlangıcı, 2) % 50 çiçeklenme, 3) tam çiçeklenme, 4) alt baklalardaki tanelerin tam şeklini aldığı dönemlerde biçilerek verim, kalite ve ekim nöbeti açısından en uygun biçim zamanının tespit edilmesi amaçlanmıştır. Bu araştırma, Tarla Bitkileri Merkez Araştırma Enstitüsü Gölbaşı/İkizce lokasyonunda 2010-2011, 2011-2012 ve 2012-2013 yetiştirme sezonlarında, Macar fiği Tarm Beyazı-98 (Vicia pannonica Crantz.) çeşidinde tesadüf blokları deneme deseninde dört tekerrürlü olarak yürütülmüştür. Araştırmada gelişme durumu, biçim gün sayısı, ana sap uzunluğu, doğal bitki boyu, ana sap kalınlığı, ana sap sayısı, yeşil ve kuru ot verimi, ham protein oranı, ham protein verimi, asit deterjan lif ve nötr deterjan lif oranı, sindirilebilir kuru madde oranı, nispi yem değeri incelenmiştir. Araştırma sonucunda, biçim zamanlarında en düşük ve en yüksek biçim gün sayısı 210.7- 236.7 gün, ana sap uzunluğu 39.3- 65.6 cm, arasında tespit edilmiştir. En yüksek yeşil ot ve kuru ot verimi 1858.6 kg da-1, 331.2 kg da-1 ile tam çiçeklenme döneminde alınmıştır. Ham protein oranı çiçeklenme başlangıcında %19.2 iken, dönem boyunca azalarak, bakla bağlama döneminde % 15.6 olmuştur. Nisbi yem değerinde de benzeri bir azalış görülmüş, biçim dönemleri içerisinde 116.9’dan 100.7’ e inmiştir. Bu araştırma sonucunda, Macar fiği bitkisinin %50 çiçeklenme döneminde biçilmesinin hem verim ve kalite ve hem de tarlanın erken boşaltılması açısından uygun olduğu sonucuna varılmıştır.
Batı Akdeniz Bölgesi’nde Domates Yetiştiriciliğinin Ana Zararlısı Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae)’nın Popülasyon Takibi ve Bulaşıklık Oranlarının Belirlenmesi
Authors: Topuz Emine , Tekşam İlyas
Published: August 2024

Çalışma, Antalya ilinde açıkta ve örtüaltı domates yetiştiriciliğinde Domates güvesi Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae)’nın popülasyon gelişimi ve bulaşıklık durumunu belirlemek amacıyla yürütülmüştür. Populasyon takibi 2011-2013 yıllarında Açık alanda Korkuteli ilçesi, örtüaltında ise Aksu ilçesinde yapılmıştır. Açık alanda ergin sayılarını belirlemek amacıyla asılan feromon tuzaklarda yakalanan Domates güvesi sayısı, başlangıçta düşük seviyelerdeyken sezon sonuna kadar kademeli bir şekilde artış göstermiştir Açık alanda tuzaklarda yakalanan en yüksek kelebek sayısı 355 iken, örtüaltı domates yetiştiriciliğinde bu sayı 395 olarak belirlenmiştir. Maksimum larva popülasyonu ise açık alan domates yetiştiriciliğinde yaz döneminde bitki başına 29.90 larva iken, örtüaltı domates yetiştiriciliğinde ise en yüksek larva yoğunluğu bahar döneminde bitki başına, 13.30 larva olarak belirlenmiştir. Bulgularımıza göre zararlının Antalya ili örtüaltı domates yetiştiriciliğinde kış aylarında da hayatta kalma ve yumurta bırakma kabiliyetine sahip olduğu belirlenmiştir.
Bolu Ekolojik Koşullarına Uygun Soya (Glycine max L.) Çeşitlerinin Belirlenmesi
Authors: Yılmaz Abdurrahim , Yılmaz İbrahim Hakkı
Published: August 2024

Protein içeriği bakımından zengin bir yağ bitkisi olan soya, insan ve hayvan beslenmesinde önemli bir yere sahiptir. Ham olarak tüketilebilmekle birlikte işlenerek protein ve yağ ürünleri olarak da değerlendirilebilen bu bitkiden günümüzde analitik kimyasallar, bakım yağı, baskı maddesi, dezenfektan, dolgu yağı, farmasötik, ilaç, insektisit, inşaat malzemesi, kauçuk, mayonez, margarin, macun bileşeni, mürekkep, pişirme yağı, yapıştırıcı gibi farklı alanlarda değerlerilen ürünler elde edilebilmektedir. Bu çalışmada bazı soya çeşitlerinin 2021 yılı Bolu ekolojik koşullarında ana ürün olarak değerlendirilmesi ile verim ve kalite özellikleri belirlenmiştir. Tesadüf blokları deneme desenine göre üç tekrarlamalı olarak yürütülen bu denemede; Asya, Sonya, 3616, Agrova, Linda, Ceysoy, Lider, Arısoy, 3546, Planet ve Adel çeşitleri kullanılmıştır. Araştırma sonuçlarına göre, tohum verimi en yüksek çeşitler 3546 (449.2 kg da-1) ve Lider (420.8 kg da-1); yağ verimi en yüksek çeşitler Linda (58.84 kg da-1) ve Lider (57.62 kg da-1); protein verimi en yüksek çeşitler ise 3546 (177.35 kg da-1) ve Arısoy (153.31 kg da-1) olarak belirlenmiştir. Bu değerlere göre hem verim ve hem de kalite parametreleri bakımından 3546 ve Lider soya çeşitlerinin Bolu ekolojik koşullarında diğer çeşitlere göre daha yüksek değerlere sahip olduğu görülmüştür.
Bazı Mısır Çeşitlerinin Yem Kalite Parametrelerinin İncelenmesi
Authors: Bulut Sancar , Öner Fatih
Published: August 2024

2014- 2015 yetiştirme sezonunda Erciyes Üniversitesi Tarımsal Araştırma ve Uygulama Merkezine ait deneme alanında kurulmuştur. Materyal olarak 24 mısır çeşidi kullanılmıştır. İki yıl süresince Kayseri koşullarında ana ürün olarak ekimi yapılan çeşitlerin yem kalitesine ait parametrelerden; ham protein oranı (%), ADF (%), NDF (%), ham kül (%) ve ham selüloz (%), sindirilebilir kuru madde (SKM), sindirilebilir enerji (SE), metabolik enerji (ME), kuru madde tüketimi (KMT) ve nispi yem değerleri sonuçları ile yağ kalite parametre değerleri de incelenmiştir. Yapılan kalite analiz sonuçlarına göre, ham protein oranı bakımından en yüksek çeşit Hido olmuş ve ilk grupta yer almıştır. Pr 31D24 ve Prestige çeşitleri ise istatistiksel olarak en son grupta yer almışlardır. Yıl x çeşit interaksiyonu ham protein oranı, ADF, NDF ve ham kül oranları önemli çıkmıştır. Yıllara göre çeşitlerin kalite performansı değişkenlik göstermiştir. Yıllar arasında istatistiksel olarak sonuçlarda anlamlı farklılıklar bulunmuştur. İlk yıl ham protein oranı ikinci yıldan yüksek çıkarken diğer tüm parametreler açısından ikinci yıl sonuçları ilk yıl sonuçlarından istatistiksel olarak daha yüksek bulunmuş ve ilk grupta yer almıştır. Yetiştiricilikte en önemli unsurların başında doğru çeşit seçimi gelmektedir. Bölge koşullarında 24 farklı çeşit ile sulamalı olarak yapılan denemede yem kalitesi ve yağ asitleri bakımından en iyi performans gösterebilen çeşit ya da çeşitlerin tespiti ve benzer ekolojilerde yapılması planlanan çalışmalara veri oluşturabilmesi amaçlanmıştır.
Study on the Interaction between Media and Chinese Traditional Theater Culture Industry
Authors: Wang Lixue
Published: August 2024

In the information age, the interaction between media and the cultural industry has gradually become a hot spot for academic research. The traditional Chinese theatre culture industry has become a significant area of research on cultural heritage and innovation, seeking development and innovation while considering the impact and opportunities of new media. This study explores how the media influences the development of the Chinese traditional theatre and culture industries and how they mutually promote and deeply integrate. The study systematically analyses the mode and effect of the interaction between the two using a combination of principal component analysis and the DEA evaluation model, combined with a particle swarm algorithm-optimised BP neural network prediction model. We found that during 2018– 2022, the total amount of broadcasting of Huangmei Opera reached 2.97 billion through the media platform, demonstrating the great promotion of the media for disseminating traditional theatre culture. The interaction between the media and the theatre culture industry enhances theatre’s market share and promotes cultural diversification. This paper explores the close relationship between the media and the Chinese traditional theatre culture industry, which is crucial in promoting the development of the culture industry.
Observability analysis of distribution networks based on robust greedy algorithm
Authors: Chong Wang , Hui Zhang , Hongbin Liu , Jian Li , Yougang Ren
Published: August 2024

In this paper, a robust greedy algorithm is applied to select the node with the highest weight value for fault observation in distribution networks. Except for the first observation node, the weights of the remaining nodes are calculated based on the results of the last observation node. The scheduling cycle is divided into several consecutive periods, and the network operation structure is observed for each period, which is gradually merged to finally obtain a set of solution schemes that satisfy the constraints on the number of switching actions for dynamic reconfiguration collaboration. The results show that the line fault system measurability is all in the 81.8%-100% interval. The method in this paper can directly locate 64.3% of the line faults in the 10kV distribution network, which can significantly reduce the number of traveling wave-locating devices, lower the investment cost, and reduce the fault locating error. It has a certain degree of adaptability in the case of the line N-1. Network operation observation can be found that the highest load-interval in a day is from 5:00 to 18:00. Using the method of this paper reduces 1 division period compared with the traditional method, reconfigures the structure to reduce the number of switching actions, and reduces the network loss from 812.06kW·h to 805.69kW·h.
Mutual Influence Mechanism and Optimization Strategy of University Town and Urban Economic Growth Based on Time Series Forecasting Model
Authors: Jiang Yihuo , Lan Fuji
Published: August 2024

University towns and urban economic growth have important interactions, and time series forecasting models can enable urban planners to better clarify the relationship between the two so as to make more scientific and reasonable decisions. Based on the time series forecasting model constructed in this paper, this paper analyzes and forecasts the relationship between university cities and urban economic growth in C. The main conclusions of this paper are that the p-value of ARIMA(0,2,3) and ARIMA(1,1,1) models is lower than 0.05, and the prediction accuracy of ARIMA(1,1,1) model is higher than that of ARIMA(0,2,3) and ARIMA(1,1,1) model in the prediction of the two. ARIMA(0,2,3) with predicted values of 27631.3, 31541.5, and 24412.45, and the error values from the actual values are only 304.98, 1997.49, and 867.95. This paper’s time series prediction model has achieved good results, as evidenced by this. Y1 shows a highly positive correlation with X1, X3, and X4 and a significant positive correlation with X2, which leads to the conclusion that the total amount of investment in urban construction of the university city of C city has a substantial relationship with the economic growth of C city.
Application of IoT technology in cyber security prevention system
Authors: Dong Jiahan , Wang Chao , Guo Guangxin , Ren Tianyu , Sun Hao
Published: August 2024

In the process of gradually expanding the scale of computer networks and the design of network systems becoming more and more complex, people pay more and more attention to the construction of network security protection systems. Starting from the blockchain encryption technology, the article establishes the authentication and access management key based on the elliptic curve encryption algorithm and combines the maximum entropy model with the hidden Markov model to construct the MEMM for intrusion detection of network security. Based on the effective signal-to-noise ratio model of the network channel, an adaptive channel selection strategy based on the UCB algorithm is proposed. The IoT security prevention system is built based on IoT technology, and each functional module of the system is designed. The system’s authentication security, network intrusion detection, adaptive channel selection, and concurrency performance were tested after the design was completed. The encryption operation time of the ECC algorithm was improved by 41.53% compared to the RSA algorithm, the average time of the MEMM network intrusion detection was 41.54ms, and the false alarm rate of the intrusion detection was kept below 16.5%. The average packet collection rate of the nodes in the adaptive channel selection algorithm is 90.98%. The maximum system throughput is up to 62.19MB, and the extreme difference in data volume between different nodes is only 38 entries. Constructing a network security prevention system based on IoT technology and combining multiple encryption techniques can ensure the secure transmission of network data.
Biomimetic Interactive Symbiotic Strategies for Clothing Textiles in the Perspective of Non-Genetic Inheritance
Authors: Chen Chang
Published: August 2024

This paper takes the application techniques of non-heritage paper-cutting elements on modern clothing fabrics as an example, analyzing and outlining the symbiotic trend of non-heritage elements and clothing design, i.e., personalization, ethnicity, and the unity of tradition and popularity. It is proposed to utilize the unique performance of bionic scale knitting structure fabrics in bionic technology, combined with the combination of non-heritage techniques, to innovate the clothing design process of non-heritage and to form a new way of bionic interaction and symbiosis between non-heritage and clothing textile. Simulate the performance of bionic scale knitting structure fabrics and explore the advantages of bionic technology in clothing textiles from the perspective of flexibility. Explore the market operation effect of clothing design works of non-heritage technology from the aspects of consumer demand, market evaluation, and market operation, respectively. From the load-displacement curve of the flexibility test, it can be obtained that when the loading value is 55N, the displacements of the bionic knitted structural fabric and the separate scale layer are all greater than 11mm, and the bionic scale knitted structural fabric possesses good bending deformability. The evaluation results of the enterprise experts show that the clothing works integrating the non-heritage elements have obvious market demand.
Implementation Strategies and Quality Evaluation Systems for Community College Guided Pathways Programs
Authors: Liu Biaosheng , Dong Daohong
Published: August 2024

The “Guided Pathways” program in community colleges can promote the efficient completion of students’ studies without restricting their choices and promote the popularization of education. This paper proposes a specific strategy for the implementation of the Guided Pathway program, and proposes a quality evaluation model for the Guided Pathway program based on the Sparrow Search Algorithm and Deep Neural Networks to construct an evaluation system. In the construction of the quality evaluation model, transient optimization perturbations are added to the SSA to improve the diversity, searchability, and robustness of the population position transformation. DNN cannot retain all the valuable features, so they are optimized to form DRNN, which is the quality evaluation model based on ISSA-DRNN. In terms of overall performance, the ISSA-DRNN algorithm in this paper has a prediction accuracy of more than 98% in different datasets, and the training and testing time required for evaluation is also significantly shorter than that of SVM and DRNN algorithms, resulting in superior overall performance. The quality evaluation of the Guided Pathways program was conducted at a community college in District S, City Q, China. The primary and secondary indicators have mean values between [3.4,3.7] and [3.4,3.6] that fall short of the respondents’ expectation of more than 4 points and cannot meet the demand. The implementation of Guided Pathways in S community college has deficiencies, and it should be improved and optimized by combining them with the implementation strategies proposed in this paper.
Exploration of the Integration and Innovation of Digital Art Elements and Traditional Cultural and Creative Designs
Authors: Shao Yonghong
Published: August 2024

Combined with the modern development form of traditional cultural and creative design, this paper proposes to use digital art elements to assist traditional cultural and creative design. The symbols of cultural and creative design are extracted using digital-assisted design technology, and the grayscale image extraction method is chosen to process the images of cultural and creative design. Then, combined with the YOLO v3 algorithm, CMT algorithm, and spatial mapping to realize three-dimensional tracking of real objects and real-time tracking interactions in mixed reality, adding digitally assisted experience of cultural symbols. With that, the theoretical model of digital art elements and traditional cultural and creative design is designed, and the procedural method of the entire cultural and creative design is analyzed. Online shopping consumer evaluations are selected, high-frequency words are classified, and consumers’ emotional tendencies are analyzed as well. The comprehensive scores of digital art and cultural and creative products are calculated using sense-quality evaluations. Consumers’ positive and negative emotions accounted for 75.72% and 17.49%, respectively, with the general negative emotion field accounting for the highest proportion of 10.54% and the medium and high negative emotion fields accounting for a lower proportion. It can be seen that the response of digital art elements to the cultural and creative design market is better, and its innovative design has a certain consumer market.
A study on the effect of yoga postures on body flexibility based on Fourier transform analysis
Authors: Li Hong , Li Dan , Huang Shiying
Published: August 2024

This paper proposes a method for data acquisition of yoga movements and analyzes it using the Fourier transform. It aims to help residents choose a more scientific and effective exercise method to relieve physical fatigue, reduce body stiffness, and improve body flexibility. Initially, we transform the yoga movements into RGB and optical flow, feeding them into the STF-ResNet network to extract the temporal and spatial features of the movement data. Next, we combine the spatial and temporal flow features with residuals to compensate for the loss of high-level feature information. Finally, we add the convolutional block attention module to further filter the yoga movement features from both channel and spatial dimensions. Next, we introduce the Fourier transform to parse the gathered yoga movement features. We conducted experiments both with and without yoga movements interfering with body soft rhythms to investigate their effects. The experimental group improved the test scores of the forward and backward splitting test and the backward bending body bridge building test, with the mean value of standing forward bending being 5.11 higher after the experiment than before. It shows that yoga intervenes in the flexibility of the human body through auxiliary training, and yoga postures can have a significant beneficial effect on body flexibility.
Strategies for Integrating Civic Education and Traditional Chinese Culture in Colleges and Universities under the ARCS Model for Nurturing People
Authors: Cheng Si , Zhou Qi , Yang Dan , Zheng Sisi
Published: August 2024

The current ideological education in colleges and universities is undergoing a series of changes, and the return of Chinese traditional culture to the system of ideological education in colleges and universities has become the development trend of the current ideological education. The study constructs the ARCS model of college civic education, integrating traditional culture according to the ARCS model, and improves the traditional hierarchical analysis method by introducing triangular fuzzy numbers so as to construct the evaluation index system of college civic education. The evaluation results of the ARCS model of Civic Education in Colleges and Universities, which integrates traditional culture, and its application effects on students’ civic performance and civic literacy are explored. In the three initial indexes of Teaching Content, Teaching Methods, and Teaching Effect, ARCS Civic Teaching in Colleges and Universities has a score of 0.826, 0.809, and 0.854, respectively. The scores of most of the second-level indexes are more than 0.8, and Civic Teaching in Colleges and Universities under ARCS has achieved a better evaluation result. The Civics scores of the experimental group and the control group do not have significant differences at the beginning of the experiment, and the significant p-value is 0.004 after the experiment, which is a significant difference. At the beginning of the experiment, the p-value of each Civic and Political Literacy of the two groups was greater than 0.05, and after the experiment, the p-value of each Civic and Political Literacy of the two groups was less than 0.05. The ARCS model of Civic and Political Education in Colleges and Universities, which integrates traditional culture, significantly improves the civic and political achievements and civic and political literacy of students.
A Cybersecurity Threat Recognition Framework Combining GAN Networks and Semi-Supervised Learning
Authors: Luo Zhuojun
Published: August 2024

This paper delineates the types of threat identification in network security, designs the threat identification model architecture, analyzes the malicious code, and proposes a counter-defense strategy. The talk compares the GAN network model and semi-supervised learning technology, combines them in network security, and proposes a semi-supervised detection model utilizing GAN. Analyze the characteristics of URL network activity and design URL character encoding. Set experimental parameters and selected datasets to analyze the similarity between synthetic URLs based on GAN generators and real URLs and test the effectiveness of a GAN-based semi-supervised detection model for malicious URL recognition using different classifiers. Calculate the detection model’s classification accuracy on a mixed dataset and test its training fit. There is only a 6% difference in how well different classifiers can spot malicious URLs. This shows that the adversarial samples made by the GAN-based generator are similar to real URLs. The GAN-based semi-supervised detection model is capable of recognizing more web threats.
Research on the Teaching Mode and Learning Effectiveness of VR Technology Integration into College English Classroom
Authors: Qi Huimin
Published: August 2024

As an important content of the modern education system, college English teaching plays an important role in cultivating students to conform to the trend of social development and improving college students’ English application ability. In addition, the transformation of English classroom teaching modes is crucial to the impact on students’ learning effectiveness. Based on this, this paper establishes a semantic comprehension model of oral communication based on the teaching mode of English classroom through the BERT model and then builds a simplified model of 3D images using LOD technology to realize a virtual classroom, which can provide targeted oral exercises and competence enhancement for students with different English levels. Students are expected to have an immersive experience of the communication process in the classroom with the help of VR technology. The results of the study show that the application of VR technology in college English teaching makes 82% of the total number of students in the experimental class score above the good level in the pre-test, while only 64% in the control class. The experimental group accounted for 6% of the total among students with poor oral grades. At the same time, the control group accounted for 22% of the total collective. Obviously, the use of VR technology has an extremely significant effect on students with medium to low oral proficiency. To summarize, VR technology-assisted teaching can improve students’ academic performance and stimulate learners’ interest in learning, which can provide insights into college English classroom teaching.
Challenges and Opportunities of Virtual Reality Technology for Innovation and Entrepreneurship Education
Authors: Liu Zhongji , Wang Yike
Published: August 2024

There are still some challenges and opportunities for the cultivation of innovative and entrepreneurial talents in virtual reality technology-related professions, and how to solve these problems is the key to cultivating and incubating innovative and entrepreneurial talents in virtual reality technology. The article first takes Unity3D as the basis for the construction of a virtual teaching classroom scene and utilizes particle system and A* algorithm for technical architecture to build the software platform of a virtual reality simulation teaching platform. Finally, the class of 22 business administration students in a college is used as an empirical research object to test the teaching effect. The results of the study show that virtual reality technology can better enhance students’ interest in learning, and more than 70% of the students are more willing to use virtual reality technology in the innovation and entrepreneurship education classroom. More than 75% of the students think that the use of virtual reality technology helps the conversion of two-dimensional and three-dimensional thinking, and it can improve innovation and entrepreneurship ability. Well, in the VR classroom, the language of the students is improved by 16%, of the teacher’s language is lower by 29%. The use of virtual reality technology is conducive to improving students’ innovation and entrepreneurship abilities, and it is more capable of driving innovation and entrepreneurship education.
Current Transformer Condition Online Monitoring Platform Based on Big Data
Authors: Wang Dan
Published: August 2024

As an important power equipment indispensable to the normal operation of the power grid, the good or bad working condition of the current transformer directly affects the operational efficiency of the whole power grid. In this paper, an online monitoring platform based on big data technology has been developed to monitor the current status of transformers. First of all, for the temperature of the transformer, through the decoupling of the heat generation mode of the transformer, the state monitoring method based on fiber optic temperature measurement technology and optical multiplexing technology is proposed, and the overall scheme of transformer state monitoring is designed. The data signal of the transformer’s status is collected and processed, and a fault state diagnosis model is constructed based on the decision tree algorithm. Finally, according to the data requirements of the current transformer, an online monitoring platform for transformer status has been constructed using big data technology. Through the simulation test, the variation of ratio error of this paper’s monitoring method is less than 0.60%, and the variation of phase error is less than 0.75 percent, which is in line with international requirements. The average loading time of the monitoring platform is between 123.591s~143.911s, the average loading speed is less than 13s, the average throughput is between 241ops/sec ~257ops/sec, and the average latency of the read and upload operations is 24.225ms. The current transformer condition monitoring platform in this paper has good stability, the overall performance is excellent, and it provides a good solution for the research of the current transformer condition monitoring platform provides practical support for the research of current transformer condition monitoring platform.
Research of improving the satisfaction of sports club members and the model of optimizing operation efficiency
Authors: Yang Yan , Huang Xianzhong
Published: August 2024

Understanding members’ psychological needs, improving members’ satisfaction, and enhancing clubs’ operational efficiency are key factors in the development of sports clubs. Taking the customer satisfaction model and the balanced scorecard of operational performance as the starting point, this paper analyzes the factors related to member satisfaction of sports clubs by using multiple linear regression models with provincial sports clubs in 31 provinces (municipalities/autonomous regions) of China as the research objects. After selecting 16 provincial sports clubs, the DEA model was built by utilizing staff salary as the input indicator and club winning rate and operating income as the output indicators. The overall satisfaction of sports club members is 3.94. The regression results show that each independent variable has achieved 75.3% of the explanatory strength of the overall satisfaction of members.4 of the 16 sports clubs reach the optimal operational efficiency in 2023. The comprehensive technical efficiency and scale efficiency of sports clubs were only 0.697 and 0.659, respectively, in 2019. By analyzing the changes in the membership satisfaction and operational efficiency of sports clubs, the DEA model is constructed. The analysis of factors that influence satisfaction and operational efficiency trends can help sports clubs choose inputs rationally and provide new perspectives for improving member satisfaction and operational efficiency.
The value and practical path of promoting the innovative thought of higher education under the background of deep learning
Authors: Zhang Yining
Published: August 2024

The value and practical path of how to promote innovative ideas in higher education in the context of deep learning is a hot issue of concern to many scholars. The article explores the execution steps of this recommendation system through the basic theoretical study of the collaborative filtering recommendation algorithm and further proposes a MapReduce-based collaborative filtering algorithm that utilizes Hadoop to run the ItemCF algorithm's steps in order to complete the Map/Reduce job. The article concludes by systematically testing the algorithm and applying it to evaluate specific innovative ideas in higher education. After the system comparison test, it is found that the recommendation algorithm proposed in this article is better than the KNN collaborative filtering algorithm in the same proportion of the test set, and the memory occupancy, CPU occupancy, and the average response time of the interface are all within the expected value. In the paired-sample t-test analysis of the dimensions of the pre-and post-test data of the values of the students in the experimental class, the P-values of the six dimensions of patriotic sentiment, scientific spirit, humanistic spirit, aesthetic consciousness, ideology and morality, and cooperative spirit are all less than 0.05, which is a significant difference.
Gradual change of vibration characteristics of steel truss structure
Authors: Tang Sicong , Wang Hailong
Published: August 2024

In order to investigate the gradual change law of vibration characteristics of steel truss structures under the influence of fatigue loading and uniform corrosion, this study combines the nonlinear cumulative fatigue damage rule, corrosion depth theory, and structural residual performance theory to establish a multi-level gradually changing performance transfer model. The relationship between structural performance and damage behavior is revealed, and a numerical analysis method for the gradual change phenomenon of vibration characteristics of steel truss structures is provided. A two-dimensional finite element analysis framework for gradual changes in vibration characteristics in steel truss structures has been developed and analyzed for a steel truss girder bridge. The results show that the correlation terms of vibration characteristics gradually decay with the increase of operation time, and the degree of decay is related to the severity of fatigue damage or corrosion damage, with the overall trend exhibiting a three-stage change.
Artificial Intelligence Technology Facilitates the Design of Interactive Platform for English Education in Colleges and Universities
Authors: Li Jing , Liu Yankui , Du Juan
Published: August 2024

In today’s era of rapid scientific and technological advancements, the deep integration of artificial intelligence technology and education is paving the way for intelligent development in English education. This paper designs the architecture of the interactive platform for English education in colleges and universities based on artificial intelligence technology, provides relevant tools for interaction assistance, and establishes an analysis model of students’ online learning interactions. To promote the diversity of English test papers, an improved genetic algorithm is utilised for the intelligent grouping of English test papers. A collaborative filtering algorithm is used to intelligently predict students’ English grades by considering the time sequence of English courses. Performance tests were designed to verify the effectiveness of the application of the interactive platform for English education. The intelligent paper grouping took an average of 1.247 seconds, and the discrepancy between the predicted and actual English course grades did not surpass one grade. The interactive platform for English education had a minimum response time of 1.69 ms, and the application server didn’t use more than 10% of its total CPU. The interactive platform, which combines artificial intelligence technology with English education, provides a new path for innovating teaching methods in English education.
Artificial Intelligence-based Digital Fault Diagnosis and Prediction for Power Grids
Authors: Niu Deling , Lu Tonghe , Wei Changchao , Li Wei , Wang Wenjie
Published: August 2024

When power grid faults occur, especially complex faults, there are many uncertainties such as switch and protection mis-operation, the power system response will be complicated, which causes many difficulties in power grid fault diagnosis. This paper uses the word2vec model vectorization to process the digitized alarm information during grid faults. The processed fault features are input into the DPCNN model to extract global features of the alarm information. Then, the fully connected layer is used to classify grid faults accurately. Subsequently, a convolution module based on the self-attention mechanism is proposed to achieve accurate prediction of grid faults, and the ReLU function and Dropout strategy are used to realize the optimization of the grid fault diagnosis and prediction model. The simulation model test results reveal that the proposed model can effectively diagnose and predict grid faults, with an average accuracy of 97.05% and 95.93%, respectively. The response time for fault diagnosis in this paper’s model for the empirical application of grid diagnosis is reduced from 6.32 minutes to 0.96 seconds, significantly improving diagnosis efficiency compared to the traditional method. This paper provides an effective method for diagnosing and predicting power grid faults and a solution for improving the management of power grids.
Research on Marine Target Detection and Recognition Based on YOLO Algorithm
Authors: Zhang Huayue , Wu Fan , Wang Xuan
Published: August 2024

Marine target detection is a crucial technology for developing and utilizing marine resources, and fast and accurate detection of marine organisms is of great research significance for sustainable development and protection of marine resources. In this paper, we first discuss the convolutional neural network and attention mechanisms in deep learning and then present the YOLO series of algorithms for target detection. Then, we take ResNeXt50 as the backbone network, introduce the global attention mechanism and ASFF module to establish the GA-YOLOv5s model for marine life target detection and recognition, and also design the training strategy of the model through migration learning. Simulation experiments are planned to verify the analysis after considering the feasibility of the GA-YOLOv5s model for marine target detection and recognition. The YOLO algorithm, based on multiple improved strategies, improves the mAP@0.5 of marine target detection and recognition by 5.68%. The detection speed of the model after incorporating the GAM module is 48.51FPS; the model using ASFF mAP@0.5 increased by 3.38%; and the average precision and recall of the model for marine target detection and recognition are 82.79% and 80.17%, respectively. Based on the YOLO algorithm, accurate detection and recognition of marine targets can be achieved, which provides reliable technical support for enhancing the exploitation and protection of marine resources.
Mining the Performance Characteristics of Yao Nationality Musical Instruments under Multivariate Statistical Analysis
Authors: Li Pengpeng
Published: August 2024

In the context of the rapid development of modernization and urbanization, the inheritance and research of music and musical instruments by ethnic minorities are facing great challenges. It is, therefore, of enormous significance to uncover the performance characteristics of ethnic minority musical instruments. This paper focuses on four categories of Yao musical instruments, namely reed instruments, air-pipe instruments, wind instruments, and percussion instruments. We mine the performance features of Yao musical instruments using MFCC feature extraction, perceptual linear prediction parameter extraction, and other methods. The performance of this paper’s algorithm is explored by comparing the detection and recognition accuracy of its algorithm with SVM on four types of musical instruments. The performance characteristics of Yao musical instruments are explored by analyzing the timbre characteristics, auditory characteristics, and beat statistics of the four instruments. This paper’s algorithm significantly outperforms the SVM algorithm in the recognition correct rate of four different types of musical instruments, with differences of 2.1905%, 7.1574%, 5.3758%, and 3.6962%, respectively. The extracted performance features of Yao music instruments reveal that reed instruments and air-pipe instruments have a superior timbral effect than wind instruments and percussion instruments. The sound of pneumatic instruments and wind instruments is the best when it comes to audibility, and the beats of reed instruments and wind instruments are the best among the four instruments.