bluuebunny/crossref_metadata_2025 huggingface dataset:
Penerapan Software Inlislite pada Pengolahan Bahan Pustaka di Dinas Perpustakaan dan Kearsipan Provinsi Sulawesi Selatan
Authors: Hidayat Nurul , Iskandar  , Mulyadi Irvan
Published: August 2024

Pokok masalah dalam penelitian ini adalah bagaimana penerapan software inlislite pada pengolahan bahan pustaka di Dinas Perpustakaan dan Kearsipan Provinsi Sulawesi Selatan, dari pokok masalah di atas penulis membagi ke dalam dua sub masalah, yaitu : Pertama bagaimana penerapan software inlislite pada pengolahan bahan pustaka di Dinas Perpustakaan dan Kearsipan Provinsi Sulawesi Selatan. Kedua apa saja kendala yang dihadapi dalam penerapan software Inlislite pada pengolahan bahan pustaka di Dinas Perpustakaan dan Kearsipan Provinsi Sulawesi Selatan. Jenis penelitian yang digunakan adalah penelitian deskriptif kualitatif dengan pendekatan managerial yang bersifat sistematis. Hasil penelitian ini menunjukkan bahwa penerapan aplikasi inlislite di Dinas Perpustakaan dan Kearsipan Provinsi Sulawesi Selatan sudah terlaksana dengan baik. Dalam mengolah bahan pustaka terdapat dua cara, yaitu pengolahan secara manul dan pengolahan secara otomasi. Kendala yang dihadapi pustakawan dalam menerapkan aplikasi diantaranya, aplikasi sering maintenance dan anggaran yang sangat terbatas.
Tinjauan Kriminologis Tindak Pidana Terhadap Putusan Perkara Kejahatan Pembunuhan Berencana Dalam Perspektif Hukum Islam (Studi Kasus Terhadap Putusan Perkara No.523/Pid.B/2017/PN.PLP)
Authors: Mustaming Mustaming , Juniar Mita
Published: August 2024

AbstractCriminological review of the case decision No.523 / Pid.B / 2017 / PN.PLP,an overview leads to the Identity of the Defendant and the scene described in the contents of the accused's indictment, as well as knowing the plot or storyline of the Defendant when committing a murder crime. Islamic criminal law review of the case decision No.523 / Pid.B / 2017 / PN. PLP in Islamic criminal law includes premeditated murder and persecution itself. The actions of the defendant are included in the main punishment was qishash, takzir and diat. If the victim or the victim's family / heir forgives, the defendant must pay a diyat in the form of compensation. Diyat or compensation for its value is left up to the ulil amri decision or the judge. Meanwhile, the defendant can also get an acquittal as long as he gets forgiveness from the victim's family. Thus according to Islamic criminal law, premeditated murder which result in serious injury by the defendant received qishash, takzir and diat laws.Â AbstrakTinjauan kriminologis terhadap putusan perkara No.523/Pid.B/2017/ PN.PLP, suatu tinjauan yang mengarah kepada Identitas si Terdakwa dan tempat kejadian yang dipaparkan pada isi dakwaan Terdakwa, serta mengetahui alur atau jalan cerita Terdakwa pada saat melakukan suatu kejahatan pembunuhan. Tinjauan hukum pidana Islam terhadap putusan perkara No.523/Pid.B/2017/PN. PLP dalam hukum pidana Islam termasuk pembunuhan berencana dan penganiyaan itu sendiri perbuatan terdakwa masuk dalam hukuman pokoknya adalah qishash, takzir dan diat. Apabila korban atau keluarga korban/ahli waris memaafkan maka terdakwa harus membayar diyat berupa ganti rugi. Diyat atau ganti rugi nilainya diserahkan kepada keputusan ulil amri atau hakim. Sedangkan bisa juga hukuman bebas untuk terdakwa asalkan mendapatkan pemaafan dari keluarga korban. Dengan demikian menurut hukum pidana Islam tentang pembunuhan berencana yang mengakibatkan luka berat oleh terdakwa tersebut mendapatkan hukum qishash, takzir dan diat.
Influence of COVID-19 on Taiwan’s manufacturing, procurement, and sales relationship
Authors: Huang Ping-Lung , Cheng Kuo-Hung , Lee Bruce C. Y.
Published: August 2024

Against the backdrop of the COVID-19 pandemic, Taiwan’s economic sectors have experienced a decline in activity. Addressing this situation effectively necessitates Taiwan to strategically align its transnational supply ecosystem with global consumption patterns, positioning itself as a crucial industrial collaborator for co-creation and shared prosperity. This study utilizes a comprehensive framework that encompasses manufacturing, procurement, and sales. Data related to Taiwan’s industries are collected through a questionnaire, and the Structural Equation Modeling (SEM) multivariate statistical method is utilized for factor and path analyses to evaluate the impact of COVID-19 on these industries. Based on the responses from the questionnaire, the dominant sectors in Taiwan’s industries are electronics/electrical machinery, accounting for around 40.84% of the industry, followed by metals/machinery at approximately 20.90%. Notably, specific aspects concerning manufacturing manpower, procurement and delivery processes, sales revenue, and product costs were reported as “somewhat serious” on average during the COVID-19 period. The results of this research indicate that manufacturing does not significantly influence sales. Additionally, there is a significant positive correlation between manufacturing and procurement. Given the unpredictable changes that companies and entire industries are currently facing, it is crucial to implement strategic measures. Because of COVID-19 influence, organizations, companies, and sectors have undergone significant transformation, necessitating the implementation of the necessary protections. In this situation, the concept of organizational resilience becomes crucial.
TONA modell: Elméleti megközelítés a családi vállalkozások fejlődési szakaszainak mérésére, értékelésére
Authors: Tobak Julianna , Krisán László , Tóth Róbert
Published: August 2024

A családi vállalkozások működésének megértése és vizsgálata világszerte fontos, ugyanis ezen vállalkozások jelentős gazdasági hatással bírnak, munkahelyeket teremtenek, és hozzájárulnak a fenntartható, hosszú távú üzleti gyakorlatok kialakításához. Érdemes ezen vállalkozásokat a családi, az üzleti és a tulajdonosi dimenziók alapján megvizsgálni és értékelni. A TONA modell egy olyan módszertan, amely lehetővé teszi a családi vállalkozások fejlődési és érettségi életciklusainak átfogó értékelését. A modell alkalmas egy vagy több vállalat együttes elemzésére. A különböző dimenziók együttes vagy különálló vizsgálata segíthet a családi vállalkozásoknak saját helyzetük felmérésében, de segítségével végezhető nemzetközi vagy ágazatok közötti statisztikai összehasonlító elemzés is. A TONA modell értékes betekintést nyújt a családi vállalkozások piaci helyzetének megértéséhez.
Ukrajna EU-s csatlakozásának lehetséges hatásai
Authors: Pintér Tibor , Dobó Róbert
Published: August 2024

Az Európai Tanács 2023 decemberi döntése értelmében az Európai Unió a csatlakozási tárgyalásokat elkezdhette Ukrajnával és Moldovával is. A tanulmány első részében Ukrajna intézményesített kapcsolatfelvételének és az EU-hoz való közeledésének legfontosabb mérföldkövei kerülnek bemutatásra. Munkánkban azt is vizsgáljuk, hogy milyen jóléti, integrációs értettségi és regionális különbségi folyamatok fémjelzik Ukrajna potenciális EU-s csatlakozását. Ukrajna esetében az igencsak alacsony életszínvonal, valamint a jelentős korrupció és az állandósult társadalmi-gazdasági válság is nehezíti a csatlakozás lehetőségét, nem beszélve a ma is tartó háborús konfliktusról Oroszország és Ukrajna között, valamint a kisebbségek helyzetét sem tarthatjuk megfelelőnek. A tanulmány fő megállapítása, hogy nem tudunk olyan aspektust találni, amely azt támasztaná alá, hogy Ukrajna érettnek mutatkozik az uniós tagságra. A vizsgálat eredményeit diagramokkal és táblázatokkal mutatjuk be.
A magyarországi egyetemi innovációs ökoszisztéma kvalitatív vizsgálata
Authors: Németh Eszter Júlia , Fehérvölgyi Beáta , Birkner Zoltán
Published: August 2024

Az innováció a jelen egy divatos, ám nélkülözhetetlen fogalmává vált, amely ma már a felsőoktatási intézmények keretrendszerében is megjelent, mint jövő orientált igény. A szó értelmét tekintve egy megvalósult újítást értünk alatta, azonban komplexitásának köszönhetően áthatja az egész szervezetet kezdve a meglévő folyamatoktól, az oktatási, kutatási szolgáltatásoktól egészen a szervezet kultúrájáig. Megállapítható, hogy az innováció felsőoktatási intézményekkel megvalósuló kapcsolata szerteágazó, amely egy ökoszisztémában, számos heterogén partner, mint az ipar, a kormányzat vagy a civil társadalom kapcsolatában jön létre, annak érdekében, hogy az innováció adta fejlődési vágyakra és lokális kihívásokra valós megoldások révén reflektáljon, túlmutatva a felsőoktatási intézmények elefántcsonttornyán. Tanulmányozva az innováció és az egyetemek kapcsolatát, a kutatás célja a magyarországi egyetemi innovációs ökoszisztémák átfogó megismerése volt. A kutatás módszertana a témában jártas szakértőkkel kvalitatív félig-strukturált interjúk segítségével vizsgálta meg az egyetemek és az ökoszisztéma adta innovációs lehetőségeket, amely megalapozta az egyetemi innovációs ökoszisztéma létjogosultságának feltételezését és bepillantást adott a rendszer esszenciájába, a résztvevő tagokba és igényeikbe, valamint az egyetemi innovációs ökoszisztéma hazai meghatározásába. A kutatás a megállapításoknak köszönhetően kiindulási alapot ad a továbbiakban megvalósuló részleteket boncolgató vizsgálatokhoz.
SUBJECT INDEX
Authors: INDEX SUBJECT
Published: August 2024

SUBJECT INDEX
Abdominal ultrasound has inconsistent agreement with subsequent surgery or necropsy findings in dogs and cats with septic peritonitis
Authors: Rheingold Curtis G. , Dickens Cody , Tran Anna , Hess Rebecka S. , Buriko Yekaterina
Published: August 2024

OBJECTIVE

To evaluate whether abdominal ultrasound correctly diagnosed septic peritonitis and correctly identified its causative lesion in dogs and cats.

ANIMALS

84 client-owned dogs and 10 cats that underwent an abdominal ultrasound and had confirmation of septic peritonitis via exploratory laparotomy or necropsy.

METHODS

This retrospective case series documented abdominal ultrasound findings, surgical or necropsy findings, and method for initial diagnosis of septic peritonitis, if different from surgery or necropsy. The surgical report and necropsy findings were compared to sonography results to confirm a diagnosis of septic peritonitis. The frequency at which sonography diagnosed septic peritonitis and its causative lesion was calculated for each type of lesion pathology and organ system. Secondary aims included evaluating the effect of patient characteristics (body weight and species) on sonographic results and whether lesion type or location affected mortality.

RESULTS

Most lesions causing septic peritonitis (70.2%) were gastrointestinal in origin and were nonneoplastic ulcerations or perforations (50%). Abdominal ultrasound diagnosed 56.3% of cases of subsequently confirmed septic peritonitis and correctly identified 67% of the causative lesions. Lesions of the gastrointestinal tract and ulcerations/perforations were the most frequent correct sonographic diagnoses and most likely to lead to a correct sonographic diagnosis of septic peritonitis. Lesions located in the hepatobiliary system and lesion types other than neoplasia or ulcerations/perforations were the most frequently missed by abdominal ultrasound.

CLINICAL RELEVANCE

Abdominal ultrasound often fails to diagnose septic peritonitis or the underlying causative lesion, and its accuracy depends on the affected organ and type of lesion.
Electrocardiographic abnormalities are associated with seropositive Trypanosoma cruzi infection status using a simplified cardiac diagnostic evaluation in dogs
Authors: Zelachowski Kendra A. , Collins Stephanie , Henderson Marty , Auckland Lisa D. , Lim Sukjung , Jeffery Nicholas D. , Hamer Sarah A. , Saunders Ashley B.
Published: August 2024

OBJECTIVE

To describe associations between cardiac abnormalities and Trypanosoma cruzi serostatus by use of a simplified diagnostic evaluation in dogs at risk for T cruzi infection.

METHODS

A prospective, cross-sectional study was performed using a simplified diagnostic evaluation including high-sensitivity cardiac troponin I, 30-second ECG, and echocardiogram with 7 variables in 46 client-owned dogs from high-risk environments. Dogs were categorized as serologically positive (SP), negative (SN), or discordant (SD) by use of 2 antibody tests. Functional evaluation of cardiac health scores and blood PCR were obtained.

RESULTS

Dogs were SP (n = 19), SN (17), and SD (10), with 9 PCR positive (7 SP, 1 SN, 1 SD). Troponin was above reference range in 6 of 46 (4 SP, 1 SN, 1 SD), and functional evaluation of cardiac health scores were 0 in all dogs. Conduction system abnormalities (prolonged interval durations, second-degree atrioventricular block, splintered QRS complex) and ventricular arrhythmias were documented in 8 (7 SP, 0 SN, 1 SD). Twenty-six (12 SP, 8 SN, 6 SD) had echocardiographic abnormalities, most often myxomatous mitral valve disease (MMVD) and left ventricular enlargement. Seropositive dogs were significantly older and had a higher likelihood of MMVD. Conduction system abnormalities were associated with positive serostatus.

CONCLUSIONS

Echocardiographic abnormalities were complicated by MMVD and did not distinguish between serostatus. An ECG with assessment and detailed measurement of complexes and cardiac troponin I are simple tests to perform with abnormalities detected in seroreactive dogs.

CLINICAL RELEVANCE

Electrocardiographic abnormalities in high-risk or seroreactive dogs should prompt further evaluation and monitoring of T cruzi infection.
Clot lysis time in patients with end-stage heart failure on mechanical circulatory support: long-term observation
Authors: Kuczaj Agnieszka , Hudzik Bartosz , Skrzypek Michał , Kaczmarski Jacek , Pawlak Szymon , Hrapkowicz Tomasz , Przybyłowski Piotr
Published: August 2024

Introduction

Despite being on antithrombotic therapy patients with left ventricular assist devices (LVAD) are susceptible to thromboembolic events. Therefore, we investigated whether LVAD has an influence on the fibrinolytic capacity of the plasma. The aim of the study was to assess the clot lysis time (CLT) in the course of time in LVAD patients and the connection between CLT and adverse events in this group of patients.

Materials and Methods

We investigated end-stage HF patients scheduled for LVAD (n=85, men 90.6%; age 48.6–63.8 years) at four consecutive time points: prior to LVAD implantation, 3–4 months, 6–12 months, and then every 6 months; the CLT was determined in the first three blood samples and the last, at the end of observation (no longer than 5 years after implantation). Enrolled for further analyses were patients who completed four observations, n=23. MACCE were defined as all-cause mortality, ischemic stroke and TIA, peripheral/pulmonary embolism, and pump thrombosis. NACE included MACCE and bleeding complications.

Results

Patients with HF showed longer CLT median [IQR], when compared to reference values: 111.25 [97–300] vs. 84.8 [75.0–98.5] min, P<0.001. MACCE occurred in 36.5% pts, bleeding events in 25.9% pts and NACE in 62.4% pts. Deaths occurred in 31.8% pts. Patients without NACE during the whole observation period showed shortened CLT in the last long-term observation P=0.025.

Conclusions

This study is the first to show that patients scheduled for LVAD are characterized by prothrombotic fibrin clot properties. The CLT value in long-term observation is lower in patients without NACE.
Assessment of energy balance in nutritional counseling – fact or myth?
Authors: Kiedrowski Mirosław
Published: August 2024

Evaluating energy balance in nutritional counseling is always prone to error. This study explains the reasons for this situation, energy expenditure types and methods of estimation, various categories of energy, the relationship between the caloric content of food and ATP production, the idea of fat balance, the concept of the energy homeostat, and other issues. Awareness of the tools’ limitations draws more attention to simple dietary recommendations and the role of physical activity. It also helps avoid the frustration of putting too much faith in uncertain caloric value and energy balance estimations.
A study of the potential of information technology to improve economic inequality
Authors: Zhang Peili , Li Zhihua
Published: August 2024

The information technology revolution carries a digital dividend and also breeds the mechanism of inequality, and the high-quality development of information technology is of great significance in improving the state of economic inequality. The article utilizes the relative deprivation index and Gini coefficient to quantify the level of economic inequality status and then establishes an evaluation index system combined with the entropy weight TOPSIS method to calculate the level of information technology development. Subsequently, the panel data of 31 provinces and cities in China from 2017 to 2022 are taken as the research object, and the corresponding variables are selected to construct the double-difference model and the threshold regression model. The direct and nonlinear effects of IT application on economic inequality improvement are analyzed through regression. The effect of the level of IT development on the relative deprivation index and Gini coefficient is significantly negative at the 1% level, with regression coefficients of -0.094 and -0.081, respectively, and the relative deprivation index and Gini coefficient have decreased by 187.88% and 117.65%, respectively, over the 13 years after the implementation of IT reform policies. The level of information technology development has two threshold values of 5.412 and 5.634 for the state of economic inequality, and either below the first threshold or above the second threshold significantly reduces the income gap arising from economic inequality. Information technology development can effectively alleviate the state of economic inequality, reduce the economic income gap, and lay the foundation for achieving common prosperity.
Cybersecurity and Risk Prediction Based on Machine Learning Algorithms
Authors: Yang Haoliang , Zhu Jianan , Li Jiaqing
Published: August 2024

This paper focuses on the application of machine learning in cybersecurity and risk prediction. Considering the complexity and dynamics of the cyber environment, the role of plain Bayesian algorithms in improving the accuracy of cybersecurity prediction is explored. First, the limitations of traditional linear regression machine learning algorithms in cybersecurity are analyzed, pointing out that it is difficult for these algorithms to capture complex nonlinear relationships. For this reason, plain Bayes is introduced to improve machine learning for more accurate prediction and assessment of cybersecurity risks by capturing functions and probabilistic agent models. In terms of methodology, this paper combines various technical tools such as statistical analysis, feature extraction, and risk assessment. The research results show that the improved algorithm outperforms the traditional method in simulation experiments, which is reflected in the 10% improvement in risk assessment accuracy and 20% enhancement of detection sensitivity to network intrusion. In addition, through big data analysis, the algorithm successfully identifies key risk points in network security and effectively predicts potential security threats. The improved machine learning algorithm with plain Bayes has significant advantages in network security and risk prediction and can effectively enhance network security protection capability and prediction accuracy.
Study on storage technology of corn wax based ice cream
Authors: Zhao Menglan
Published: August 2024

Ice cream is a complex food colloidal system; saturated fat is an essential element given the taste and texture of ice cream (viscosity, hardness). In recent years, research on fat ice cream has focused on adding fat substitutes. Looking for a suitable source of lipid-based fat substitute instead of fat ice cream, developed more conducive to human health, low in saturated / zero trans fatty ice cream products. The study will use linoleic acid-rich soybean and corn oil gel waxes as a fat source for ice cream, make gel-oil-based ice cream, and study changes in its quality during storage. With an incremental storage time index, we can inspect the effects of different storage times on melting rate, hardness, and fat globule diameter changes. The hardness and melt rates show an increasing trend while the fat globule diameter decreases. We found that the quality of ice cream has reduced over time, but it does not affect the sensory evaluation. By analyzing the acidity, peroxidation value, and F.A. composition changes, we found that the acidity and peroxidation values are low, indicating that the shelf-life of ice cream gel is higher due to using better quality fresh oil. The fatty acid composition did not change during storage, and no trans fatty acids were produced.
Optimization study of computational methods in coordinated integrated carrying capacity assessment of multi-voltage hierarchies
Authors: Wang Huibin , Liu Zhaozheng , Li Chunchao , Wang Yuxi , Zhang Gengxi
Published: August 2024

In this paper, we take a two-level distribution grid as the infrastructure of a multilevel distribution grid and study the comprehensive carrying capacity assessment model in depth. The minimum value of the maximum access capacity under each scenario is used to assess the maximum carrying capacity of the distribution network, and the maximum access volume of the multilevel distribution network is taken as the objective function, and the particle swarm algorithm is improved to establish the maximum carrying capacity assessment model. Using the alternating direction multiplier method, a two-level distribution grid carrying capacity distributed optimization model is established, and the multilevel distribution grid access volume problem is transformed into the maximum access volume subproblem at all levels of the distribution grid. Comparing the whale algorithm and particle swarm algorithm, the model in this paper converges at 7465 kW access capacity and about 12 iterations, respectively, and the weak degree is below 0.4 at different distribution network states, which is a good performance in terms of optimization accuracy and weak degree. We conduct simulation experiments with the modified IEEE33 nodes and find that using this paper’s model to participate in optimal scheduling reduces the total operating cost of the distribution network system by more than 6.24% compared to not using it. Finally, we use the model in this paper to evaluate the comprehensive carrying capacity of the distribution network in Ningxia, China.
Machine Learning Diagnosis of Node Failures Based on Wireless Sensor Networks
Authors: Xia Jun , Zhan Dongzhou , Wang Xin
Published: August 2024

Wireless sensors are widely deployed to harsh environments for information monitoring, as the sensor nodes are highly susceptible to various failures, resulting in erroneous monitoring data. Sensor fault diagnosis is the subject of research work in this paper. Sensor faults are categorized based on their causes and mechanisms. Secondly, the wavelet transform, tuned Q wavelet transform, and LSTM-based neural network model are utilized for equipment fault feature extraction and fault diagnosis. The structure of the LSTM neural network, as well as the parameter settings, are completed with an adaptive moment estimation algorithm for the model training, and simulations are carried out for verification. The diagnostic accuracy of the model in this paper is as high as 97%, and the root mean square error converges to 0.02 after 170 times of training, which shows the high accuracy of the model in this paper. The training time is very short, only 1.226s, which shows that the fault diagnosis model in this paper is very efficient and meets the requirements of practical applications, proving the effectiveness of this paper’s model in wireless sensor network node fault diagnosis.
Mechanisms of data mining in analyzing the effects and trends of news dissemination
Authors: Zhang Lihong
Published: August 2024

Data mining techniques can help news organizations and media practitioners extract valuable information from a large amount of unorganized information, such as by analyzing the effect of news dissemination. In data mining, multiple linear regression is a widely used technical model. In this paper, we utilize the classic “cognition-attitude-behavior” analysis framework to construct a regression analysis model of the news communication effect. We solve the positional parameters according to the principle of least squares, ensuring that the regression value and all observations have the minimum residual square. We then solve the system of linear equations using Clem’s law and the Gaussian elimination method. The constructed models are used to analyze the news dissemination effect of Guangzhou’s city image on traditional news platforms and microblog self-media platforms, respectively. It is found that the news videos of “cultural image” and “ecological image” have a significant positive effect on the news dissemination effect. The longer the duration of the news video, the better the dissemination effect. In terms of the influence of event-related online opinion leaders on news dissemination, the number of comments and likes have a significant positive influence, with coefficients of 0.778 and 0.059, respectively, and both are significant at the 1% level. In addition to the number of comments and likes, the influencing factors on the dissemination of related news are the number of fans, whether there is V authentication, and whether there is microblogging membership. After conducting two empirical data mining analyses, we verified the validity of the multiple linear regression model in this paper by analyzing the effect and trend of news dissemination.
Algorithmic Complexity Research on Foreign-related Tourism English Education and Talent Cultivation Models in the Context of Free Trade Port
Authors: Chen Rulin , Hou Peixu , Huang Cheng
Published: August 2024

In today’s booming development of free trade ports, China, as a big country of inbound and outbound tourism, has put forward higher requirements for the talent cultivation mode of foreign-related tourism English. This paper takes the characteristics of foreign-related tourism English as the entry point and establishes the practical teaching system and the four-in-one talent cultivation mode of foreign-related tourism English. The multi-objective optimization model for cultivating foreign tourism English talents is proposed, with the objective function of enhancing the quality of foreign tourism English talents, and the corresponding constraints are set. The multi-objective optimization model is solved using the DQN model, and a strategy gradient algorithm-based model training optimization strategy is proposed. The test conditions of foreign-related tourism English talent cultivation are set, simulation experiments are carried out, and teaching experiments are compared based on the optimal scheme. The training loss obtained by the DQN model after 1700 iterations fluctuates between [0.015,0.019], and when the training period is set to 2 years, the cumulative return of foreign-related tourism English talent cultivation can reach 623.87%, and the maximum retracement is only - 5.457%. The optimal talent cultivation program’s average score is 14.1 points higher than the ordinary version. Foreign-related tourism English needs to be fully integrated with the actual demand for talent, and the faculty and policy guidelines help to enhance the quality of foreign-related tourism English talent training.
A study of innovative models of community governance under digital social policy
Authors: Bai Jie
Published: August 2024

Intelligent communities are based on the Internet, using vehicles, face recognition, surveillance video structuring, and other technologies to integrate the community’s government services, grid-based management, and convenient services. They also design a grid-based intelligent community service management platform to support all kinds of events closely related to residents’ lives and community management. Through relevant questionnaires, statistics, and generalizations, a comprehensive understanding of security management before and after the digital transformation of a community can be obtained. It has been observed after analysis that the detection rate of criminal cases in the public area monitoring range and the community has reached as high as 98.2% and 99.4%, respectively, following the digital transformation. There is a significant positive correlation between the dimensions of institutional remodeling, convenient services, public affairs, community governance performance, and community governance capacity. Residents are highly satisfied with grid-based community governance after digital transformation, with mean scores exceeding 3.0, according to further analysis. This paper provides a theoretical basis for the government, community, and public to promote the application of digital reform in community governance on the ground.
Three-dimensional model construction of power distribution room and its digital twin physical structure research
Authors: Feng Bin , Wang Yu , Mo Liangyuan , Yang Jing , Luo Hui , Wei Zongchun
Published: August 2024

Aiming at the problem of complex internal structure and difficult monitoring of the distribution room, a new monitoring method for the distribution room based on a digital twin is studied. Firstly, a 3D model design method for the distribution room is proposed by combining visualization technology and 3D Max software to complete the modeling. The 3D laser technology is used to scan the entity to get the texture photos of the 3D laser points and the raw data, then a complete model is obtained by modeling the details, and finally, the texture photos are mapped with the model to get the final model. To enhance the model’s accuracy, the optimal minimum spanning tree model optimization method is proposed, and the power distribution room’s three-dimensional model design is now finished. On the basis of the feature extraction of the sensor data of the distribution room, the digital twin technology is used to realize the matching of the information model architecture from the real entity of the distribution room to the virtual model, digital conversion, correlation of the operating data features and real-time monitoring, and then the monitoring method of the distribution room based on the digital twin is obtained. The experimental analysis yields a 3D Max modeling time of 9.98s and a fineness of 90%, which is more suitable for the construction of complex 3D models of distribution rooms than the other two methods. The accuracy of digital twin wireless communication is kept at 98% or above, and the system operation is disturbed to a small extent. It shows that digital twin technology is suitable for monitoring the complex structure inside the distribution room.
Big Data Analysis Methods for Higher Education Physical Education Teaching Interactive Platform and Its Teaching Effectiveness
Authors: Chen Xiao , Feng Jian
Published: August 2024

The use of big data comprehensively serves physical education, so that students can clarify their learning situation and make reasonable changes in physical education teaching. In this paper, firstly, we do an analysis and investigation on the application of big data in physical education teaching in colleges and universities, apply the tree hierarchy algorithm to collect the key data indexes of physical education teaching classrooms, and use the SMDA aggregation algorithm to aggregate and analyze the collected key data. The weight of each index system of teaching evaluation is calculated using the hierarchical analysis evaluation method. The role and application of analytical methods in physical education teaching are discussed in the context of big data. This paper constructs a system for evaluating teaching effects, which includes 5 primary indicators and 20 secondary indicators. The evaluation results of the 10-factor index system in the teaching process are divided into five grades to obtain the distribution intervals of excellent, good, medium, qualified, and poor students’ learning performance. The results of data analysis of the attributes of this paper show that the percentages of Cluster l, Cluster 2, and Cluster 3 are 22%, 66%, and 12% respectively. The weights of teaching ability, method, content, attitude, and effect in the actual teaching process were 20.97, 24.29, 24.08, 3.89, and 6.31, respectively. This paper elaborates on the effects and roles of four aspects of the interactive platform Big Data application in physical education teaching and learning in the context of Big Data analytics methods. Ideas for the use of big data analysis methods in sports teaching in colleges and universities are presented.
The Effect of Information Entropy Analysis in Computer-Assisted English Translation on Improving Translation Naturalness
Authors: Ke Jun
Published: August 2024

This paper borrows the concept of entropy and refers the information entropy to the computer-aided English translation to build up the information entropy assessment and evaluation model and the information entropy-based English translation optimization model. The information entropy operation formula is used to calculate the fuzziness between the original text and the target translated text, and at the same time, the segmentation function is utilized to find the approximation value of the information entropy value obtained in a sufficiently fine segmentation of the translated text. Obtain the rectangular window function of semantic Gaussian marginalization, project the information entropy data, add the semantic correlation factors of words, identify the features of semantic information, and realize the optimization of English translation. Simulation experiments are carried out to verify the performance of the model. The information entropy evaluation and analysis model in this paper can achieve convergence after 45 iterations. In contrast, the word error rate and the cut-off error rate of the English translation optimization model are both lower than 10%, and the feature recognition and classification are higher than 80%. The fuzzy statements in Chinese writer Lao She’s work “Teahouse” are selected to explore the naturalness of translation. The information entropy value of the translation optimization model in this paper is closer to the original text, and the English translation’s naturalness is better than that of the GLR model.
A Predictive Model of English Vocabulary Teaching Effectiveness Based on Bayesian Networks
Authors: Li Liwei
Published: August 2024

Bayesian networks are a class of probabilistic graphical models used to characterize the relationships between variables, and structure learning is a key step in Bayesian network modeling, which is the basis for network parameter learning and probabilistic inference. In this study, we introduce Bayesian networks and propose a model for tracking vocabulary knowledge based on BKT. In order to test the performance of the model, the vocabulary knowledge tracking model, including the Bayesian network model, is compared with other models by combining the learning structure algorithm and students’ learning characteristics, and the accuracy, recall, and mean square error of the model are explored to study the accuracy of the vocabulary knowledge tracking model in predicting students’ vocabulary mastery is close to 0.9, and the precision is in the interval of (0.5-0.6). In teaching, the model that predicts students’ mastery of English vocabulary in different datasets performs better than other models in practice.
Spatial data analysis model construction for landscape vegetation impact evaluation
Authors: Xue Yi
Published: August 2024

The impact assessment of vegetation ecosystems is inevitably combined with vegetation, soil, hydrothermal conditions, and topographic factors. This paper utilizes a combination of remote sensing imaging, monitoring, on-site data collection, and spatial information visualization to provide data information on landscape vegetation ecosystems and builds a GIS database for the process of landscape vegetation ecological analysis. Define landscape vegetation types and analyze landscape vegetation pattern indices. Combining the evolution of landscape vegetation areas with the change in vegetation type levels, the vegetation cover of landscape vegetation in the study area was calculated. Surface temperature inversion model based on Landsat atmospheric correction algorithm to get the surface temperature of the region from 2014 to 2020. Combined with the soil erosion classification and grading standards, the soil erosion model RUSLE was used to derive the soil erosion class. In 2020, the landscape vegetation of Jiuzhaigou had a high coverage of 62.79%, and the mean surface temperature generally showed a trend of increasing and then decreasing. Mild and moderate soil erosion decreases. The synthesis of vegetation cover, surface temperature, and soil erosion can indicate that the landscape vegetation ecological environment of the study area is good and in ecological balance.
The promotion of mobile Internet to the construction of informationization of ideological and political education in colleges and universities
Authors: Zheng Qiao , Li Mingxi
Published: August 2024

This paper explores the teaching path of the civics class in colleges and universities during the mobile Internet era, and uses a questionnaire survey to analyze the reality of current mobile Internet-based civics class instruction. The changes in the teaching of civics and political science classes under the influence of mobile internet are tracked and systematically analyzed in terms of differences. This study focuses on both the general effective education classroom and the effective education classroom in the mobile environment. It utilizes the Nvivo software to investigate the teaching styles of teachers and the interactions between teachers and students in these two learning modes. The results show that nearly 20% of the students are in schools that have not yet conducted mobile Internet civics instruction, and about 24.5% do not have political theory classes on mobile Internet teaching. In the context of mobile Internet, the habit of reading on a cell phone is increasing by 10% annually, and learners are paying the highest attention to public news sources, reaching 86.4%, which creates favorable conditions for teaching mobile Internet civics and politics. An effective education classroom in the mobile environment tends to be open; the ratio of teachers’ words to students’s words is about 2.09%, and teachers are more willing to use media resources, and network means to check students’ knowledge. And the classroom status is at 0%, and the teaching process is more stable.
A Quantitative Study of Dance Teaching and Students’ Aesthetic Ability Development in the Framework of Aesthetic Education
Authors: Zhu Yuan
Published: August 2024

With the deepening of today’s education reform, the development of students’ aesthetic ability is becoming more and more an important part of the education system, and dance teaching, as an indispensable part of the cultivation of aesthetic ability, is receiving more and more attention. This study takes students majoring in preschool education in colleges and universities as the research object, integrates dance teaching in music courses, conducts a questionnaire survey research, and then conducts research on the characteristics of the dance teaching mode under aesthetic education, studies the relationship of the factors between the survey object and the school dance teaching in terms of the one-way analysis of variance (ANOVA), correlation analysis, and multiple regression analysis, and further analyzes the factors influencing the development of the aesthetic ability of the students. After the analysis, it can be concluded that the place of residence has the main influence on the development of students’ aesthetic abilities, despite the individual differences of students. The integration of art courses and dance courses in schools, the degree of attention of dance teachers to students’ aesthetic ability in dance teaching, the development of dance club activities in schools, students’ participation in club activities, and the cultural atmosphere of dance on campus had high correlations with students’ aesthetic ability, with the highest correlation value of 0.412** for art courses. From the multiple regression analysis to explore the development of art courses and students’ aesthetic ability, it can be seen that the school is the main influencing factor in cultivating the development of students’ aesthetic ability towards dance, so the school should improve the content of art and culture courses and focus on the development of students’ aesthetic ability.
Analysis of value shaping education for college students in the view of ideological education in colleges and universities based on deep learning
Authors: Zhuang Huaijun , Shen Ming
Published: August 2024

This paper proposes a values sentiment analysis model based on RoBERTa-BiLSTM-Attention based on the mechanism and path of values process evaluation under sentiment analysis. After extracting and presenting the values and sentiment features data, we build the values dataset of college students, finish the training of the model, and obtain the classification results of values and sentiment. The college students’ value identity model is established to analyze the value shaping of education at the national, social, and individual levels. The correlation coefficients of the influencing factors of college students’ values were analyzed, and the correlation coefficients of the influencing factors were less than 0.75, and the p-value was less than 0.01. The hypotheses were put forward, and the standardized regression coefficient of the “social role model” was 0.2658, which was significantly higher than that of the other indicators, and the standardized regression coefficient of “emotional satisfaction” was 0.2658. The regression coefficient of “emotional satisfaction” is 0.1987, second only to cognitive identity. In view of the existence of the problem of values, the proposed political education intervention guidance strategy, after the political education intervention, 71.3625% of the students think that the values of guidance have a great help, but there are still some shortcomings, compared with this paper puts forward the optimization of the values of guidance recommendations.
An AI-enhanced teaching model using a novel deep learning approach
Authors: Meng Pan
Published: August 2024

Today’s strategy of vigorously promoting the modernization of education creates conditions for wisdom teaching and promotes the deep application of artificial intelligence technology in education. In this paper, we construct a deep learning smart teaching model that is enhanced by artificial intelligence based on the occurrence mechanism of deep learning and the theory and method of smart teaching. Furthermore, the structural equation modeling method is utilized to conduct further empirical research on the model based on the theoretical model. Among the seven hypothesized paths of the MPERT teaching model, five hypothesized C.R. values were greater than 1.96, and the P-values were all less than 0.05, indicating that the influence relationships among the variables of the hypothesis were statistically significant. It has been verified that the teaching model can effectively promote the occurrence of deep learning, especially in the enhancement of higher-order competencies such as problem creation, situation creation, and value thinking. The M-PERT teaching model constructed in this study and the practice cases designed based on the model can provide theoretical and practical references for teachers to effectively carry out smart classroom teaching and promote students’ deep learning.
Optimization of Machine Learning-based Value Assessment Model in High Value Patent Cultivation in Universities
Authors: Wei Yihang
Published: August 2024

This paper constructs a patent value assessment model for colleges and universities from two perspectives of: value identification and price prediction. Firstly, 10 indicators are selected from 3 dimensions of technology, economy, and law. Then it combines the artificial way of entropy weight TOPSIS model and the machine learning way of gradient boosting tree to realize the identification of the value of university patents and the grading of the economic value of university patents. After analyzing, it can be seen that after pre-processing the data, 10 feature items related to patent value and useful for evaluation are screened out, and the highest weights of the number of homologous patents and the number of citations indicators are 0.1826 and 0.1274, respectively, which have the greatest influence on the economic value of high-value patents of colleges and universities. In the range of 4901-7071 of high-value patents, the assessment results fluctuated in the range of 1.3754-2.8395. The value of invention patents with a gradient range of 1-1400 as well as 6301-7071 fluctuates more dramatically. This paper proposes a patent value assessment model for universities that has a superior assessment and classification effect on high-value patents in universities.
The Application and Innovation of Data Mining Technology in College English Speaking Teaching
Authors: Xia Chunmei
Published: August 2024

College English speaking, as an important part of English teaching, is getting more and more attention from many scholars. Data mining technology has brought new opportunities for teaching spoken English in universities. The article builds a portrait and analyzes students through the data generated in the process of teaching spoken English at university in order to understand their relevant attributes and learning habits. Then, the decision tree model is used to predict several scenarios of students’ oral English performance. Finally, 2 classes of a university majoring in English were selected as the empirical research subjects to be tested. In the analysis of the changes in the oral English scores, the mean score of the pre-test of the control class was 21.43. The mean score of the pre-test of the experimental class was 21.29, which led to a small difference in the mean scores of the pre-tests of the two classes. In contrast, after the experiment, the mean score of the post-test of the control class was 27.51, and the mean score of the post-test of the experimental class was 30.85. The experimental class’s mean score increased by 3.34 points, and the overall English-speaking performance saw a more significant improvement.
Research on Pattern Recognition Technology for Music Teaching and Optimization of Its Teaching Framework
Authors: Yin Na , Li Weiting
Published: August 2024

This paper proposes music rhythm perception technology and music automatic classification technology, respectively, which are pattern recognition technologies for music teaching. The short-time Fourier transform is used to analyze the audio information, transform the acoustic spectrogram into a Mel spectrogram, build the convolutional neural network architecture, and process the spectrogram sequentially to realize the automatic classification of music. The music signal is preprocessed to remove noise using normalization, and a new histogram-based method is proposed to detect music rhythms by analyzing and modeling the music beat sequence. This paper uses S High School in Qujing City, Yunnan Province, China, as the research site to implement pattern recognition technology in teaching practice. The experimental class’s music scores increased from 50.18 before the experiment to 64.52, which was higher than the control class’s, with a 28.58% increase. The experimental class’s mean values in the sentence and paragraph dimensions of music rhythmic sense, the mean values of the experimental class were 0.73 and 0.65 higher than those of the control class, showing significant differences (P<0.05). All dimensions of music core literacy, except opera knowledge and general knowledge of musical instruments, also showed significant differences (P<0.05).