bluuebunny/crossref_metadata_2025_split huggingface dataset:
PENINGKATAN DAYA SAING UMKM KULINER DI DESA ADAT PANJER MELALUI PENGEMBANGAN MEDIA PEMASARAN BERBASIS DIGITAL
Authors: Utami Kadek Anggi Dian , Wardani Kadek Devi Kalfika Anggria , Gorda A.A.Ngr.Eddy Supriyadinata 
Published: April 2023

Desa Adat Panjer merupakan desa yang terletak di Kota Denpasar yaitu lebih tepatnya di Kecamatan Denpasar Selatan dengan luas daerah yaitu 3,59 km. Di Desa Adat Panjer sendiri sudah banyak sekali UMKM yang sudah berdiri sejak lama baik itu UMKM kuliner, fashion, jasa dan masih banyak lainnya. Namun, beberapa UMKM kuliner di Desa Adat Panjer masih banyak menggunakan cara pemasaran secara konvensional sangatlah tidak efektif dilakukan, di tengah perkembangan teknologi digital sangat memungkinkan para pelaku UMKM untuk memasarkan produknya secaradigital. Metode kegiatan yang dilakukan pada pengabdian ini adalah dengan melakukan observasi dan wawancara terhadap 2 (dua) UMKM kuliner dan pembuatan akun Instagram dan pelatihan pemasaran melalui sosial media kepada kedua UMKM kuliner. Hasil yang didapat setelah terlaksananya kegiatan ini adalah kedua UMKM kuliner sudah mulai mengerti mengenai manfaat media digital sebagai media promosi yang efektif di era digital saat ini dan setelah dilaksanakanya pengabdian terjadi peningkatan penjualan sebesar 10% yang dirasakan oleh kedua UMKM kuliner.
EDUKASI DAN PENDAMPINGAN PERAJIN DAN PENGUSAHA BATIK DI KABUPATEN GARUT
Authors: Nur Tajudin , Nugraha Tb. Chaeru , Sofyan Agus Nero , Sunarni Nani , Indrayani Lia Maulia , Ismail Nany , Abdul Malik M. Zulfi 
Published: April 2023

Produksi batik Garut yang dikenal dengan batik Garutan mengalami penurunan. Hal ini disebabkan oleh kurangnya minat generasi penerus pada usaha batik tulis, ketidaktersediaan bahan dan modal, serta lemahnya strategi pemasaran dan juga munculnya batik mesin printing. Oleh karena itu, diperlukan upaya edukasi dan pendampingan kepada para perajin batik Garutan. Metode edukasi dan pendampingan yang digunakan adalah metode pemetaan sosial, yaitu rapid appraisal dan participatory appraisal. Pelaksanaan rapid appraisal diawali dengan melakukan wawancara informan kunci, kemudian dilanjutkan dengan diskusi kelompok terarah (focus group discussion/FGD). Adapun pelaksanaanparticipatory appraisaldengan langkah sebagai berikut: pelatihan, pembinaan, pendampingan, dan kaji tindak. Berdasarkan kegiatan edukasi dan pendampingan yang telah dilakukan, terdapat animo dan apresiasi yang besar dari para peserta perajin batik di Kabupaten Garut. Ke depan, kegiatan tersebut dilakukan secara berkesinambungan agar manfaatnya dapat dirasakan oleh para perajin batik di Kabupaten Garut sehingga mereka semangat dalam mengembangkan usahanya.
IRASIONALITAS RASIONAL PERILAKU DAN KEPERCAYAAN MISTIS PEDAGANG PASAR TRADISIONAL: STUDI KASUS DI PASAR REBO DESA CIKEMBANG KABUPATEN BANDUNG, JAWA BARAT
Authors: Rajab Budi , Mulyanto Dede , Wiyanti Dede Tresna , Supangkat Budiawati 
Published: April 2023

Tulisan ini ialah tentang bentuk-bentuk perilaku mistis di antara pedagang Jawa di pasar tradisional. Melalui pendekatan etnografis-kualitatif, perilaku-perilaku seperti melempar koin, pedagang sebagai pembeli pertama, menutup kios pada hari buruk, menepuk-nepukan uang ke barang dagangan, slametan, sukuran, dan solat berjamaah, bisa dianggap perilaku mistis karena di dalamnya ditemukan kepercayaan bahwa jika mereka melakukannya maka keuntungan akan datang dan kemalangan akan pergi. Meski di permukaan tampak irasional, pada dasarnya perilaku-perilaku tersebut ialah manifestasi dari rasionalitas tertentu. Secara teoritis, perilaku mistisnya pedagang bisa ditempatkan dalam situasi ‘irasionalitas rasional’, situasi yang di situ tindakan irasional dilakukan karena dianggap rasional secara instrumental meskipun secara epistemologis irasional. Konteks situasi ini ialah tuntutan kultural dan sosial dari dalam pengalaman sehari-hari pedagang sebagai anggota dari suatu semesta sosial tertentu. This paper is about forms of mysticl behavior among Javanese traders in a traditional marketplace. Through an ethnographic approach, behaviors such as tossing coins, buying their own product, closing kiosk on bad day, tapping money on merchandise, and others can be condidered as mystical behaviors because it is found in the belief that if they do then profit will come and misfortune will go away. Although on the surface they appear irrational, basically these behaviors are manifestation of a certain rationality. Theoritically, the traders’ mystical behavior can be placed in a situation of rational-irrationality, a situation in which irrational actions are carried out because they are considered, instrumentally, rational eventhough epistemologically irrational. The context of this situation is the cultural and social demands of the trader’s daily experience as a member of a particular social universe.
Retrospective analysis of risk and timing of death from right heart failure in United States and Canadian feedlot necropsied cattle
Authors: Johnson Blaine T. , White Brad J. , Dahlman Devin A. , Rademacher Ryan. D. , Amrine David E. , Larson Robert L. 
Published: April 2023

Abstract

OBJECTIVE
To evaluate the risk and timing of right heart failure (RHF) in feedlot cattle.

ANIMALS
Study population consisted of 1,717,356 cattle (5,527 cohorts) in 13 US and Canadian feedlots. There were 1,336 RHF diagnosed at necropsy.

PROCEDURES
Multivariable models were utilized to evaluate risk and timing of RHF death.

RESULTS
Arrival year was associated with RHF and was influenced by arrival quarter on the magnitude of risk of RHF (P < .01), but no linear increase over years was identified. The impact of feedlot elevation on RHF was modified by breed (beef, dairy, or dairy-cross; P < .01) with beef cattle in the highest elevation category having 0.54 times the risk of RHF as dairy cattle in the same elevation category (LCL = 0.31; UCL = 0.962). Cattle that died due to RHF and were treated for bovine respiratory disease died 11 days (LCL = 1.33, UCL = 20.2 days) sooner than cattle never treated for bovine respiratory disease (P = .03). Cattle breed was associated with RHF timing (P = .01), and dairy-cross cattle RHF cases died approximately 37 days earlier (SE = 13.0 days; P = .01) compared to beef cattle.

CLINICAL RELEVANCE
This research showed demographic factors associated with RHF and their respective influence on risk and timing of RHF. Risk rates of RHF were similar to previous research. This could allow for comparisons across different feedlot populations, using different diagnoses at necropsy and RHF risk/rates do not appear to be increasing.
Influence of innovative human capital on economic development of China through the STI model
Authors: Zhang Rongfan 
Published: April 2023

Abstract
With the continuous progress of the times, innovation is the first driving force of development, and human capital is the carrier of innovation ability. Innovative human capital plays an important role in China’s economic development and enhancing its competitiveness. By selecting physical capital, labor input and innovative human capital input, and establishing an RBM-STI function model, the impact of innovative human capital on China’s economic development is calculated. The results show that innovative human capital has a significant role in promoting the contribution rate of economic development. And in the 2021-2022 stage, the growth rate of innovative human capital input and output is the largest, at 81.9%, while the growth rate of physical capital input and output is only 26.3%. It shows that although the role of physical capital in promoting economic development is not as obvious as that of innovative human capital, it is still the backbone of promoting economic development. The lowest contribution rate to economic growth in China’s provinces and cities is the labor input, which accounts for only 9.6% in the 2021-2022 period.
Exploring the Path of Integrating Excellent Traditional Culture into Civic Education in Universities in the Internet+ Era
Authors: Yang Qin 
Published: April 2023

AbstractInternet technology is developing rapidly, and young students, as the subjects of Internet use, are also the objects of college civic education. Based on the Internet+ era, the strategy of integrating traditional culture with the path of college Civic Education has become a necessary issue for reforming this educational direction and the purpose of this paper. Based on the information and culture dissemination mode of the Internet, this paper integrates traditional culture in exploring the path of Civic Education and puts forward an innovative method of college Civic Education. Compared with the original Civic Education method, the average satisfaction of students has increased by 6.6 percentage points, and the comparison has improved by 9.91%. The average satisfaction of teachers increased by 7.6 percentage points and by 9.84% in comparison. The percentage of students who think that the effect of Civic Education is very obvious has increased by 2.7%, the ratio of those who think it is improved has increased by 3.5%, the ratio of those who think it is generally improved has increased by 1.4%, and the ratio of those who think it has almost no improvement effect has decreased by 6.3 percentage points compared to the original. Traditional culture and Civic Education are organically integrated with the support of Internet technology, which optimizes the path of education realization, makes the path play the main role of students, strengthens the interaction in teaching, and refreshes the level of this educational work comprehensively.
Research on network security management monitoring platform based on Internet of things technology
Authors: Yang Qiang , Cheng Chen , Chen Yang , Li Yan , Shi Zhenyu 
Published: April 2023

Abstract
With the rapid development of the times, my country has made good innovation and progress in the Internet of Things technology, which has brought a lot of technical guarantees for computer network security. In the process of computer network security analysis and research, it is necessary to introduce the Internet of Things technology. In this paper, the CNN-GRU-PSO network is used to optimize the information classification control. Compared with the traditional model method, the CNN-GRU-PSO model method improves the accuracy rate from the original 86.4% to the original 95.5%. Nearly 10%; the precision rate increased from 84.3% to the original 91.2%, and the accuracy rate increased to nearly 7%; the recall rate was increased from 86.4% to the original 93.5%, and the accuracy rate increased to nearly 9%. The CNNGRU-PSO model optimizes network security management and formulates strict prevention mechanisms to ensure that computer networks can operate efficiently and safely.
Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things
Authors: Ma Le , Dou Chenchen , Hao Ting 
Published: April 2023

Abstract
With the development of smart grids, power grids have accumulated massive amounts of data in various links such as power generation, transmission, substation, distribution, power consumption, and dispatch. More and more big data applications are beginning to be applied in various professional fields of the power grid. Promote the application and value discovery of smart grid big data through data fusion inside and outside the grid. Grid data has become an important asset for enterprise development, but power grid enterprises lack effective technical means to solve the whole life cycle monitoring and relationship of power grid data assets. Aiming at the relationship between power grid data assets, this paper proposes a set of grid data asset relationship and intelligent classification framework that integrates knowledge graph and Internet of Things. First, the grid knowledge graph extraction relationship is carried out by ProjE algorithm. Then, the relationship between power grid data assets and intelligent classification framework that integrates knowledge graph and Internet is proposed. Finally, the corresponding classification application is proposed by using intelligent classification algorithm. Experimental results show that the intelligent classification accuracy rate can reach 93.12% under the relationship between the knowledge graph and the Internet data assets, which has a new idea for the future development of the relationship between power grid data assets.
Analysis of the application methods of film and television media and images in the era of big data cloud
Authors: Zhang Qing 
Published: April 2023

Abstract
In order to give full play to the application of big data in film and television media and imaging in the cloud era, this study proposes a communication-efficient distributed deep neural network training method based on the DANE algorithm framework. The DANE algorithm is an approximate Newtonian method that has been widely used in communication-efficient distributed machine learning. It has the advantages of fast convergence and no need to calculate the inverse of the Hessian matrix, which can significantly reduce the communication and computational overhead in high-dimensional situations. In order to further improve the computational efficiency, it is necessary to study how to speed up the local optimization of DANE. It is a feasible method to choose to use the most popular adaptive gradient optimization algorithm Adam to replace the commonly used stochastic gradient descent method to solve the local single-machine suboptimization problem of DANE. Experiments show that Adam-based optimization can converge significantly faster than the original SGD-based implementation with little sacrifice in model generalization performance. With the increase of sampling rate, DANE-Adam significantly outperforms the DANE method in terms of convergence speed, and at the same time, the accuracy can be kept almost unchanged, which are 0.96, 0.88 and 0.75, respectively. This shows that Adam-based optimization can converge significantly faster than the original SGD-based implementation with little sacrifice in model generalization performance, with significant potential value.
On the improvement, innovation and inheritance of stage makeup styling in opera under the background of big data
Authors: Zhao Yuqi 
Published: April 2023

Abstract
Character styling design can clearly show the background of story characters and the characteristics of the times in the performance of stage plays. Integrating traditional culture with the art of stage plays is important for developing theatrical communication. In this paper, we analyze the factors that impact theatrical communication in the context of big data. Based on the original innovation diffusion model, it analyzes the limitations of its application, analyzes the innovation characteristics of theatrical stage makeup modeling from a qualitative perspective, finds that its diffusion characteristics do not conform to the prerequisite assumptions of the original innovation diffusion model, and confirms the improvement direction of the innovation diffusion model. Based on the analysis of audience data by the full data analysis method, the main influencing factors affecting the diffusion of opera heritage are identified, and their practical significance in the improved model is analyzed. The original innovation diffusion model is improved quantitatively, and an iterative diffusion model is established. Empirical analysis of the iterative diffusion model was conducted using the actual diffusion data of opera stage makeup styling. The research results show that the initial diffusion rates of the products are, in descending order, Cheese Superman, TikTok, Watermelon Video, and Punchbowl. Among them, the cumulative diffusion of TikTok is the highest at 14, and the diffusion rate of Watermelon Video is 0.68. It indicates that the above products effectively spread opera culture and highlight the charm of opera stage makeup styling.
Multi-featured multi-scale combination of high-resolution remote sensing images for building extraction
Authors: Niu Yuhan 
Published: April 2023

Abstract
As one of the important feature categories in urban geographic data, buildings are the key thematic elements to be represented in large-scale urban mapping with the high speed of urban digital construction. The identification and extraction of buildings are of great significance for feature extraction, feature matching, image interpretation and mapping. However, the great variability of building size, shape, color, orientation, etc., in remote sensing images poses a great challenge to building detection. To this end, this paper proposes an algorithm based on multi-feature multi-scale fusion for the automatic extraction of buildings in remote sensing images are represented in the form of roofs. It is difficult to represent all buildings with a single feature because of the different colors, textures and shapes of building roofs. Effective features to describe buildings are proposed, including edge density and edge distribution, brightness contrast, color contrast and other features to describe building edge brightness. We propose effective features to describe buildings, including edge density and edge distribution, luminance contrast, color contrast and other underlying features to describe the edges, luminance and color of buildings, and adding special structural features such as main direction orthogonality and target integrity and symmetry to describe buildings by multiple features together.
Moreover, the K-value nearest neighbor classification algorithm is used to train a series of samples, and the weights of each feature in the multi-feature model are obtained through iterative learning to obtain the multi-feature linear model and calculate the visual saliency of buildings in the sliding window; finally, the proposed algorithm has experimented with several groups of high-resolution remote sensing images respectively, and the multi-scale multi-feature fusion model algorithm is used as the Erkoff random field model to compare the algorithm. The results of this paper show that the proposed multiscale multi-feature fusion model algorithm improves by 10.82% for building classification accuracy extraction and 13.96% for feature selection extraction accuracy, and finally, the comparison from the shape optimization effect figure concludes that the multiscale multi-feature fusion model can achieve better extraction accuracy and practical effect for buildings in remote sensing images, which has certain practicality and It has certain practicality and superiority. It promotes the in-depth application of multi-feature multi-scale combined high-resolution remote sensing image-building extraction in geographic states, road traffic and other industries.t
The application of ARCS motivation model in college oral English teaching
Authors: Zhu Xuanxuan , Huang Jingwen 
Published: April 2023

Abstract
In order to make spoken English more widely used in college communication, the author proposes the application of ARCS motivation model in college spoken English teaching. The author tries to apply ARCS motivation model in the strategy design of college oral English teaching, the four core factors of attention, relevance, confidence and satisfaction are explained, analyzed and explained in detail respectively, twelve practical teaching methods and strategies are summarized. A total of 109 students in 3 classes were taught for a semester, the teaching strategies and methods mentioned above were used in the weekly oral English teaching classes. After applying several teaching strategies designed by ARCS model to stimulate motivation, a post-test was conducted for all the students in the experimental class, by comparing the data before and after, the anterior and posterior sides of S1 natural consequences completely disagree: 14.67%, 13.75%, less agree: 29.35%, 24.76%, unsure: 11.04%, 1.82%, more agree: 19.26%, 33.07%, strongly agree: 25.68%, 26.6%. We can see that in terms of attention, relevance, confidence and satisfaction, the results show that ARCS motivation model is effective in college oral English teaching.
Research on the evaluation system of tourism management classroom teaching based on multimedia big data analysis
Authors: Yang Zhengquan 
Published: April 2023

Abstract
To improve the quality of tourism management classroom teaching and then improve the quality of undergraduate tourism management professionals, this paper analyzes tourism management classroom teaching evaluation based on big multimedia data. The mean and autocovariance matrix are determined by multivariate statistical analysis, and the effective learning behavior evaluation index and survey data are determined by entropy analysis, and then the evaluation index of tourism management classroom teaching quality is established to explore the improvement of teaching quality after big multimedia data is applied to tourism management classroom. According to the statistics related to the basic tourism education and training statistics of the China Tourism Administration, as of 2017, there were 608 general higher education institutions offering tourism management undergraduate majors with a total enrollment of 59,000; 1086 general higher education institutions offering tourism management higher education majors with a total enrollment of 113,000; 947 secondary vocational The total number of enrollment in 947 secondary vocational schools with tourism-related majors is 103,000, and the scale of tourism talent training has expanded, and the education problem of tourism management majors has gradually come to the fore. Therefore, it is timely and necessary to analyze the evaluation of tourism management classroom teaching based on big multimedia data, and to a certain extent, it can promote the improvement of the education level of tourism management majors in colleges and universities.
An innovative teaching model of automotive manufacturing process based on ADDIE model
Authors: Zhang Zhenzhong , Yue Shifeng , Wang Jie , Yang Pengxin 
Published: April 2023

Abstract
The teaching mode of the innovative automotive manufacturing process is to improve students’ automotive manufacturing technology. In this paper, firstly, the basic principle of the ant colony algorithm is introduced, and the ant colony algorithm is improved and optimized by heuristic function, state transfer probability and pheromone update rule. Then the optimized ant colony algorithm is used as the base algorithm for constructing the ADDIE model. After establishing the ADDIE model, two dimensional indicators of the teaching mode of the automotive manufacturing process, i.e. teaching objectives of the basic course and application course, are mined for the example of the automotive manufacturing process course of L school. The two example indicators proposed are analyzed and illustrated using the example data.
Regarding the basic course teaching objectives, the mean values of A, B, C and D evaluation indicators accounted for 47.73%, 21.46%, 20.17% and 10.65%, respectively. Regarding the teaching objectives of the application courses, the mean values of the four evaluation indexes of A, B, C and D account for 50.24%, 15.75%, 21.05% and 12.96%, respectively. The innovative teaching mode of the automotive manufacturing process based on the ADDIE model is beneficial for students to learn technology in a new way and also for delivering high-quality technical talents to automotive manufacturing enterprises.