bluuebunny/crossref_metadata_2025 huggingface dataset:
THE SYSTEM OF GOAL-SETTING IN THE STATE POLICY OF ELECTORAL INNOVATION MANAGEMENT: THE ASPECT OF ENSURING ELECTORAL SOVEREIGNTY OF THE STATE
Authors:   St. Petersburg State University, Antyushin N.A.
Published: November 2024

The process of innovation management is of major importance for the realization of political modernization and development goals. The ability of a sovereign State to implement the policy of managing innovations in the electoral sphere, as well as to implement the principle of electoral sovereignty, which is an integral part of state and national sovereignty, deter-mines the legitimacy of political power and political regime, and the trust of civil society and a wide range of external actors (first and foremost, other sovereign States and international organizations) in the political system. The disruption to interstate communication between Russia and Western countries, including the issues of electoral cooperation, as well as the drive to reinforce Russia’s electoral autonomy, has led to a significant requirement for academic research and expert- analytical support in the domain of innovation management. The purpose of the article is to identify and systematize the reasons (innovation goals) that the sovereign state faces when carrying out innovation activities in the electoral space, and the conformi-ty of such activities with the category of ‘electoral sovereignty’. The research methodology is based on the theory of political development and modernization, the theory of diffusion of innovation, and the legal theory of sovereignty. As one of the results of the study, an ex-plicative model of innovation activity in the electoral space is proposed, according to which innovations can be divided into three orders of goals. These goals are complementary and oriented not only towards the modernization and development of the electoral system, but also towards the implementation of the principle of electoral sovereignty. The author notes that an innovation is not necessarily a newly created or imported institution or technology; rather, it can also be a recreated process that was previously institutionalized in its entirety, or fragmented, in the electoral history of a state. The author suggests reformulating Russia’s electoral traditions to make them relevant and innovative. This would strengthen the domestic electoral sovereignty.
SUSTAINABLE DEVELOPMENT AND TOURISM OF URBAN HERITAGE: AN IMPERATIVE FOR THE FUTURE. CASE OF DACHRA HAMRA IN EL KANTARA, BISKRA, ALGERIA
Authors: Souad Belhannachi  , Meriem Benmechiche  , Imene Bensid  , Oualid Meddour
Published: November 2024

In Algeria, as in the rest of the world, urban heritage, specifically historical centers, attracts many visitors due to their heritage significance. However, the growth of tourist flows and the attractiveness of these cities are dependent on the conservation, enhancement, and sustainable preservation of this heritage.
The original core of the city of El Kantara in Biskra, Algeria, Dachra El Hamra, remains inhabited and is distinguished by its unique architecture and urban organization. This village is regarded as a cultural model of great value. From a tourist perspective, Dachra El Hamra holds particular interest as both tangible and intangible heritage. This interest is heightened by its integration within lush landscapes, characterized by date palm orchards thriving at the foot of its majestic cliffs and impressive gorges.
The village of Dachra El Hamra remains at the center of concerns for local authorities and communities. The objective of this study revolves around this urban heritage, considering the criteria of sustainable development while promoting local and international tourism. To achieve this, we developed an evaluation using the RST02 grid, supplemented by a direct questionnaire conducted with the stakeholders involved in its management.
Miliolide-rich assemblages in the Paratethys: Paleoenvironmental implications for Serravallian (Badenian–Sarmatian) sediments
Authors: Babejová-Kmecová Jaroslava , Hudáčková Natália , Király Edit , Báldi Katalin , Preto Nereo , Bielich Márius , Golej Marián
Published: November 2024

The presented multiproxy study sheds light on the intricate interplay between the biological and environmental factors which shaped the middle Miocene landscapes of the Paratethys region. Moreover, they highlight the diverse and dynamic nature of these ancient ecosystems. Here, we study the reasons for the predominance of nine miliolids in the Badenian and Sarmatian sediments, validate systematic and morphogroup approaches using geochemical methods, and finally reveal the bio stratigraphic potential of miliolid horizons during the Serravallian (late Badenian–Sarmatian). Trace elements (Mg/Ca, Ba/Ca, Mn/Ca) from the MZ 102 borehole and isotopic (δ18O, δ13C) analyses from ŠVM 1 and MZ 102 were measured. On the basis of the morphogroup division, an autecological comparison, and geochemical analyses, three main (MG 1, 2, 3) and two small (SG 1, 2) miliolid groups representing distinct microhabitats were characterised. Specific faunal communities (MG 1) document the environment of arborescent algae, such as Cutleria and Fucus in detritus-rich water substrates, which can lead to suboxia or anoxia in muddy-sandy sediment layers. Other associations (MG 2) correspond to shallow marine environments of hypo/hypersaline lagoons overgrown by short-stemmed arborescent algae, such as Padina, Halopteris, and Pseudolithophyllum, as well as notable salinity fluctuations. Host faunal communities (MG 3) inhabiting the inner shelf are characterized by motile epiphytic foraminifera on algae and Posidonia rhizomes. The observable changes to the paleoenvironment can be characterized by fluctuations in salinity and the occasional depletion of oxygen at the bottom.
Extraglottic airway devices: essential uses as a new generation
Authors: Prasad T Krishna
Published: November 2024

The second most frequent postoperative complication following wound infection is postoperative nausea and vomiting. Retching and vomiting can cause a wound to dehisce, extending hospital stays and increasing costs. Numerous clinical studies have revealed that propofol is equally efficient at lowering the incidence of nausea and vomiting after intrathecal morphine administration as it is at reducing pruritus.
Aim:
The aim of the study was to analyse the antiemetic effects of sub hypnotic dose of propofol in various surgical conditions.
Methods:
An extensive research of all materials related to the topic was carried out in the PubMed and Google scholar search engine .relevant research articles focusing on sub hypnotic doses of Propofol for nausea and vomiting published since 2019 were included in the review .several review articles were excluded, and studies related to anaesthesia were included from 241articles, narrowing it down to a total of 7 studies which implies the subhypnotic doses of the drug in various anaesthesia related clinical scenarios. A total of 7 studies similar to the current study objectives were included in the study and analyzed. keywords used in the searches included Propofol, sub hypnotic, nausea, vomiting.
Conclusion:
Sub hypnotic dose of Propofol (0.5mg-1.0mg/kg/hr) given pre operatively effectively reduce post-operative nausea and vomiting in various surgical operation. But the duration of its anti-emetic effect seems to be lower than other anti-emetic drugs in the market. Still it can be effectively used in reducing post op and intra op nausea and vomiting.
Golden Smiles: Ensuring Oral Health in the Elderly
Authors: Boczko Faerella
Published: November 2024

Poor oral care correlates with an increase in systemic diseases such as aspiration pneumonia. Lack of education and oral care knowledge in caregivers raises the risk of poor oral care among elderly patients residing in long-term care facilities. A study investigated the results of an education program provided by speech-language pathologists for certified nursing assistants (CNA). Data pre and post oral healthcare knowledge education program was collected on 54 CNAs. Data on oral health of their patients prior to and subsequent to the education was also collected.
Levobupivacaine -Safe and Effective Drug in Daycare Ophthalmic Surgery
Authors: Prasad T Krishna
Published: November 2024

A new local anesthetic, levobupivacaine, is the levorotatory isomer of bupivacaine and therefore meets all safety requirements. Out of 120 articles, ten articles similar to the current study objectives were included in the study and analyzed. Keywords used in the search include medical education and geriatrics. : in view of the above studies reviewed, we conclude levobupivacaine given in ophthalmic blocks is effective and safe for daycare surgeries. Levobupivacaine's lower risk of adverse effects may be especially helpful for the elderly cataract extraction, useful in daycare with the benefits of good preservation of sensory and motor block postoperatively. Less pain compared to lignocaine in the intraoperative and postoperative periods. We suggest drugs and agents which are appropriately suitable for clinical use in peribulbar anesthesia for cataract surgery.
Nanotechnology as a New Revolution for Cancer Therapy
Authors: Fathy Abd-E llatef Gamal Eldein
Published: November 2024

Since cancer is one of the leading causes of death worldwide, research into cancer treatments is currently representing a top priority. Researchers from all over the world are looking for an effective treatment that will specifically target cancer while causing minimal morbidity. Nanotechnology can improve the potency and selectivity of biological, chemical, and physical methods for inducing the death of cancer cells while lowering collateral damage to non-cancerous cells. Many nanoparticle delivery systems as inorganic and organic materials have been used in the development of cancer therapy. In this review, the function of nanoparticles in cancer therapy among various cancer drug delivery techniques will be discussed as well as how it works to overcome cancer drug resistance. We provide an up-to-date discussion of the recent progress that has been made in the use of nanotechnology in cancer therapy.
Analysis of Fluid Flow Characteristics for Stress-Sensitivity Dual-Porosity Reservoir considering Elastic Outer Boundary
Authors: Chol Kim Song
Published: November 2024

Previous researchers have considered the influence of stress sensitivity and elastic outer boundary on the flow characteristics of fluids in reservoir, and solved the problem by considering stress sensitivity and elastic outer boundary conditions when analyzing the flow characteristics, but the stress sensitivity and elastic outer boundary conditions are not taken into account at the same time, the error still arises in the well test analysis.

In order to simplify the complex problem in solving the model, we obtained analytical solutions in Laplace space by applying inverse transformation and obtained the pressure and pressure derivative curve, and analyzed the sensitivity of the characteristic values for pressure and pressure derivative curve.

In order to simplify the complex problem in solving the model, Pedrosa’s transformation and perturbation’s transformation were applied.

Using these transformations, the nonlinear partial differential equation was linearly transformed. By Laplace transformation, we obtained analytical solutions in Laplace space and applied inverse transformation to obtain solutions in real space, and plotted the pressure and pressure derivative curves.

The model accuracy was verified by comparison with previous studies and sensitivity analysis of the characteristics for pressure and pressure derivative curves was performed.

This study is of great significance in improving the accuracy of the parameters of the well and reservoir determined by well test analysis.
Exploring Prevalence and Predictors of Clinically Suspected Dialysis Disequilibrium Syndrome in End-Stage Kidney Disease Patients Initiating Hemodialysis
Authors: Nookaew Budsarawadee
Published: November 2024

Objective: This study aimed to examine the prevalence and predictors of clinically suspected dialysis disequilibrium syndrome (DDS) in end-stage kidney disease (ESKD) patients starting their first hemodialysis session.Material and Methods: Data was retrospectively collected from a university hospital; from december 2020 to july 2023. It included adult patients receiving their first session of hemodialysis. Patient demographics, comorbidities, medications, and laboratory results were analyzed. The primary objective was to identify clinically suspected DDS using predefined criteria. Multivariate logistic regression was used to identify independent risk factors for clinically suspected DDS.Results: A total of 106 patients were enrolled. Among these, 18.8% had clinically suspected DDS, with nausea being the most prevalent symptom. The onset of symptoms varied, with a median of 240 minutes. Multivariate analysis revealed higher pre-hemodialysis serum creatinine as a risk factor for DDS (adjusted OR: 1.13; 95% CI: 1.02–1.25), while lower pre-hemodialysis serum sodium (adjusted OR: 0.90; 95% CI: 0.84–0.98) and capillary blood glucose levels (adjusted OR: 0.99; 95% CI: 0.97–1.0) were associated with increased risk. Notably, elevated blood glucose levels were protective against DDS.Conclusion: Higher pre-dialysis serum creatinine, coupled with lower sodium and glucose levels significantly predicts DDS. These findings emphasize the necessity of tailored hemodialysis prescriptions and vigilant monitoring of patients likely to develop DDS.
Cultura de compliance Corporativo. Retos para los procesos de educación empresarial
Authors: Vaudo Godina Liliana
Published: November 2024

Introducción: El artículo busca explorar el impacto de la instrucción por competencias en el incremento de habilidades profesionales durante el desempeño en el ámbito corporativo, para lograr un verdadero vínculo comunicacional que permita alinear el desempeño empresarial con el logro de un intercambio comercial identificado con la correcta gestión de riesgos y las buenas prácticas empresariales. Metodología: Se emplea el análisis documental, analítico y exploratorio de textos, normas, datos derivados de estudiantes vinculados con el ámbito de formación superior empresarial, utilizando para ello un enfoque cualitativo. Resultados: Las instituciones de educación superior que preparan a los futuros profesionales para el ámbito corporativo, deben incluir actividades y recursos educativos que les permita desarrollar competencias profesionales que los haga capaces de implementar sistemas de gestión organizacional sostenibles y que impacten de modo positivo en el entorno y en la sociedad.  Discusión: Del análisis de resultados surge la necesidad de formar en valores y principios a los futuros profesionales del ámbito empresarial para que se conviertan en edificadores de una cultura de cumplimiento. Conclusiones: La profesionlización empresarial presenta como retos la adquisición de competencias signadas por la sostenibilidad y la cultura de cumplimiento normativo para el logro de empresas socialmente responsables.
Connections and contradictions
Authors: Pusceddu Antonio Maria
Published: November 2024

Eric Wolf is conventionally credited with reframing the term “political ecology” through the lens of political economy in the early 1970s. However, he never engaged with what by the 1980s was already a growing transdisciplinary field. An inspiring book in the genealogy of political ecology, Europe and the people without history said little about the emerging approach. Nevertheless, I argue that despite its limited focus on ecological issues, the book's vision and method can still provide insights for envisioning an anthropologically minded political ecology of value that combines the heuristic skills of ethnographic research with the systemic analysis of global capitalist-driven environmental change. To this end, the article brings Wolf's strategic use of Marxian frameworks into conversation with the Marxian ecological critique of value.
Ablaut, Stress, Internal Derivation and Law of Accent Shift on the Right in the Indo-European Languages
Authors: Krasukhin K. G.
Published: November 2024

Abstract. The article treats the mobility of Proto-Indo-European accent, its function and role in nominal derivation. Some researchers argue the existence of noun with several types of accent movement (accent-ablaut paradigms) and formulate the concept of internal derivation – i. e. the change of accent type of noun, transition in other class. Author means that there was one type of mobile accent in declension (unitary ablaut-accent-paradigm), and proposes a basic rule of derivation – the law of accent movement onto right: the position of accent is more right, the meaning of noun is more concrete.
“The Proletarian Episode” in the Literary Process of the 1920-s: the Case of Saratov
Authors: Khroustaleva A. V. , Moskovskaya D. S.
Published: November 2024

Abstract. The peculiarity of Saratov literary process in the New Economy Policy Period was underlied by a small regional budget, slow speed of documentation circulation and the absence of distinct political guidance from the Party and censorship organs towards literature up to the mid-1920s, as the themes of cultural agenda were often chosen by trade unions. The regional Proletkult became a foundation for Saratov Association of Proletarian Writers (SAPW). Until the moment SAPW was supported by the central organs, it had no sufficient energy for its creative and propaganda activities, which were left to Proletkult. Getting the support, the organisation became dependent on the guiding Moscow organs. The renewal of the life of the Proletarian Association is connected with the appearance of G. Lelevich in Saratov. Together with the appearance of Lelevich in Saratov, the influence of the Proletkult weakened, and the SAPW began a flourishing period. A significant contribution to this was made by G. Lelevich.
The Phenomenon of the Character of Chekhovʼs Fiction
Authors: Afanasyev E. S.
Published: November 2024

Abstract. The topic raised in this article reflects the specificity of Chekhovʼs artistic and aesthetic system. The research literature on this topic is extensive; however, its scholarly significance is not fully appreciated due to the insufficient attention of scholars to the methodology of literary studies, which puts stock into addressing a writerʼs work as an artistic and aesthetic system considered in the context of the historical and literary process. For this reason, taking a Chekhov’s character as a single person all by himself (A.P. Chudakov, V.B. Kataev, V.Y. Linkov) has not brought clarity to the problem of the specificity of the Chekhov’s personage, its ontological and aesthetic status. We proceed from the specificity of Chekhovʼs postclassical realism, in which the artistic world is referential to the real world, and the character is a real ‘single person’, which allows us to illuminate, the above mentioned and related problems of Chekhovʼs aesthetic conception of man. In our conclusion, we summarize our observations in the form of a methodological algorithm, which would facilitate approaching and scholarly interpreting of Chekhovʼs literary texts.
The Motive of Childlessness in the Myth of the Ancestors of the Buryats
Authors: Dampilova L. S.
Published: November 2024

Abstract. On the base of the numerous variants of the myth of the origin of the ancestors of the Buryats, the author analyzes episodes concerning the motive for punishing a childless shaman (two shamanesses), and the rituals associated with receiving a child. The composition of folklore discourse reveals the semantic and semiotic specificity of variable texts. Methods of comparative, semantic-hermeneutic and semiotic analysis to identify the features of the text structure and definition of transformations of text and context at different times and in different ethnic traditions are used. As a result of the study, it was revealed that the original plot outline and characters remain unchanged in the structure of the text: the shaman as a mother, the bull as a father and the children – the first ancestors of the Buryat tribes. The motive of punishment and description of the rite for obtaining a child is present in all versions of the myth, except for the brief Selenga version. In the invariant of the motive of punishment, variants of the motive of exile, mortification, and strangulation are revealed. In different versions of the myth, recoding, transformation and refinement relate to images, motifs and mnemonic symbols. In the composition of the analyzed episodes, the author reveals the transcoding of mnemonic symbols, which are deciphered in the context of traditional stories and legends related to ritual events. From a semiotic point of view, it has been established that sparks from a flame / embers from a fire, a bone and an arrow in this case are the receptacle of the souls of future children.
The Textology of I. A. Bunin’s Short Story “Silence”: Elegy in Prose
Authors: Shchavlinskiy M. S.
Published: November 2024

Abstract. In 1901, after returning from his first trip abroad, I.A. Bunin wrote a short story based on a trip to Switzerland in the company of V.P. Kurovsky, “On Lake Geneva” (later “Silence”). This text is the only prose work of the writer that contains a dedication. The figure of Kurovsky (a romantic character) fascinated the young Bunin, and he later dedicated poetry to him.
The article shows through a textual prism how the writer’s elegiac story was transformed from edition to edition (the text was reprinted 7 times). Bunin retained the original principles of the poetics of romanticism, but diligently retouched the excessive emotionality of the text, got rid of romantic clichés, reduced the amount of intertextual connections, and also carried out the stylistic text editing characteristic of the mature Bunin of the mid-1910s.
Analysis of Results of Scaling Digital Images by Interpolation Algorithms
Authors: Balovsyak Serhiy , Hnatiuk Yurii
Published: November 2024

Scaling of digital bitmap images is often used in modern computer and telecommunications systems. Among image scaling algorithms, the most common are interpolation algorithms, namely nearest neighbor, Lanczos, bilinear and bicubic interpolations. However, in the process of scaling images by interpolation algorithms, characteristic distortions appear on them. Therefore, in this work, software implementation and research of image interpolation algorithms was performed in order to identify their advantages and disadvantages, areas of use and ways of improvement. In order to study the interpolation algorithms, a scaled fRGBs image was calculated based on the initial image fRGB, and then a scaled image fRGBs2 with the dimensions of the original image was calculated based on fRGBs. The scaling accuracy is evaluated using the Root Mean Square Error between the pixel values of the original and scaled images. The software for scaling images is developed in the Python language. Calculation of scaled images is performed by the cv2.resize() function of the OpenCV library. Using the developed program, scaling of a series of 100 images was carried out, the accuracy and speed of digital image scaling by interpolation algorithms were investigated. For each interpolation method, the average scaling error AR and the limits of its confidence interval ARmin and ARmax with a specified reliability γ are calculated. The average scaling time AT of a series of 100 images by different algorithms was determined. The research results showed that in most cases the smallest scaling error is provided by the bicubic interpolation algorithm, which is slightly inferior in speed to the nearest neighbor and bilinear interpolation algorithms. Recommendations for the application of interpolation algorithms have been developed. It is shown that the use of convolutional neural networks is promising for the highest quality image scaling.
Intelligent Monitoring and Fault Diagnosis in Automatic Production
Authors: Yang Dejun
Published: November 2024

In order to analyze the faults of equipment in the process of operation in time and feed them back to the information system synchronously, and provide decision-making information for the setting of maintenance scheme, the method of intelligent monitoring and fault diagnosis in textile automatic production is put forward. The condition monitoring system of textile machinery can monitor the signal parameters of textile equipment in operation, and then analyze the failure problems faced by textile equipment in the current control mode by comparing the system reference parameters. Based on this, taking vibration signal analysis as the breakthrough point, this paper expounds the condition monitoring signal analysis and fault diagnosis of textile machinery. The results show that the monitoring times are 8 times, and then the actual efficiency of fault diagnosis is obtained by analyzing the data, and the false alarm rate is less than 0.5%. Conclusion: The monitoring system based on vibration signal analysis has higher monitoring accuracy, which can accurately identify the fault problems and provide basic guarantee for the subsequent operation and maintenance work.
Optimized Design of New Automobile Frame Light Weighting Under Deep Learning Algorithm
Authors: Cai Yu
Published: November 2024

In order to solve the problems of long time, high cost and low efficiency in the lightweight design and optimization process of new automobile frame, the lightweight optimization design method of new automobile frame based on deep learning algorithm was proposed. According to the load and length of the target frame, a mathematical model is established with the minimum weight of the longitudinal beam as the objective function and the boundary conditions, strength, stiffness and stability of the longitudinal beam as the constraints. In MATLAB, the radial basis function neural network algorithm is used to optimize the cross section of the frame longitudinal beam, and the optimal cross section size of the target longitudinal beam is obtained. The finite element models of the new frame 1 obtained from the optimization design and the new frame 2 obtained from the experience design are established respectively, and the working conditions of the two are compared and analyzed by using ANSYS. The experimental results show that frame 1 is 19.5% lighter than frame 2 on the premise of meeting the requirements of frame design and use. Conclusion: The lightweight optimization design idea is feasible.
Evaluation and Analysis of the Economic Efficiency of the Tobacco Industry Based on the Factor Analysis Method
Authors: Yang Lei , He Xuefeng
Published: November 2024

In order to broaden the application of factor analysis, the economic benefit evaluation analysis of tobacco industry based on factor analysis was proposed. Using factor analysis and SPSS statistical software correctly, the economic benefits of 7 cigarette industrial enterprises in a certain place were evaluated quantitatively and qualitatively. The results showed that: using Euclidean distance and class average method, the threshold value was 1.6, and seven cigarette enterprises were divided into four categories: the first category: the second cigarette factory in A city. Category II: Cigarette Factory in City B, Cigarette Factory in City C and Cigarette Factory in City D. Category III: No. 1 Cigarette Factory in City A, and No. 1 Cigarette Factory in City E. Category IV: F City Cigarette Factory. The first cigarette factory in city A has a big difference in comprehensive rankingF_(Summarize) Only ranked 5th; Cigarette Factory in City B, Cigarette Factory in City C, and Cigarette Factory in City D, where comprehensive F is ranked higher in turn, due to asset operation factorsF_“1 ”, capital preservation and enhancement factorsF_“3 ” It is better than No. 1 Cigarette Factory in City A, so it ranks before No. 1 Cigarette Factory in City A. Conclusion: The determination of the number of factors and the naming of factors reflect the actual data, and the evaluation is more objective.
Research on the Application of Power System Cryptography Based on Quantum Key
Authors: Dong Wu , Liu Xu , Peng Linyu , Liu Kang , Peng Dili , Wang Tao , Shi Ji , Zuo Jun
Published: November 2024

The research and test of the security protection technology of distribution network quantum encryption information based on 5G multi access edge computing applies the communication technology and quantum encryption technology of 5G power private network to the terminal environment of distribution network. Through the integration of quantum key and power service master station, terminal and quantum key, 5G communication and quantum encryption equipment, It enables safe communication between the distribution terminal equipment and the distribution master station, and the system response time is controllable. The results show that in the 5G deployment environment, the maximum delay in 1000 tests is 121.23 ms, while in the 5G+quantum environment, the maximum delay is 200.23 ms.
Design and Optimization of an Intelligent Recommendation System for Instant Retail Services Based on Machine Learning
Authors: Zhou Xingyao , Wan Fujun , Zhang Yuchen , Qiu Shuohan
Published: November 2024

In order to realize the desire of all parties involved in instant retail, it can better understand the behavior of users, discover the hidden interests of users and the behavior rules of group users, and an intelligent recommendation system for instant retail services based on machine learning is proposed. Analyze and process the relevant data of e-commerce websites, use the improved rough set attribute reduction algorithm and Apriori improved algorithm for data mining, use the two improved algorithms together as a scheme to apply to the recommendation system, and then compare the recommendation efficiency of the system through empirical analysis of relevant data. The experimental results show that the time to generate frequent item sets based on the improved Apriori algorithm is significantly less than that based on the Apriori algorithm when the minimum support is fixed. In terms of the efficiency of generating frequent item sets, the Apriori improved algorithm is more efficient. With the minimum support getting smaller and smaller, the comparison becomes more obvious. When the number of transactions is fixed, the time used by the recommendation system to apply Scheme II is obviously less than that used by Scheme I. Moreover, with the continuous increase of the number of transactions in the transaction database, the difference in the time used to apply the two schemes increases significantly. In terms of recommendation efficiency of instant retail intelligent recommendation system, Scheme II is better than Scheme I. Conclusion: The system effectively improves the recommendation efficiency of the recommendation system.
A Study on the Correlation Between Brand Image and Customer Satisfaction Using Big Data Analytic
Authors: Hua Chunxiang , Wu Fang , Zhou Xingyao , Duan Qi , Zhang Ning
Published: November 2024

Social media provide new opportunities to publicize the image of a brand, and the study of the correlation between brand image and customer satisfaction using big data analysis technology is proposed. This paper focuses on the impact of brand image matching strategy on consumer satisfaction in social media, and explores the four oriented features of social media, namely personality-oriented, fun-oriented, interaction-oriented and interest-oriented, and discusses the different brand images that should be paid attention to in social media, including brand value image, emotional image and specialized image, and then verifies the matching effect between them. The results show that personality-oriented social media promote brand values, fun and interaction-oriented social media promote emotional image, and interest-oriented social media promote professional image, all of which promote consumers’ satisfaction with the brand.
Integrating Computer-Mediated Communication Tools to Improve Collaborative English Writing in Higher Education
Authors: Zhang Yingting
Published: November 2024

This study examines the integration of computer-mediated communication tools in collaborative English writing within higher education. It addresses enhancing student engagement, writing quality, and digital literacy skills in an increasingly digital academic landscape. Through a comprehensive literature review and analysis of empirical studies, the research explores the effectiveness of both synchronous and asynchronous CMC tools in facilitating collaborative writing processes. The study reveals that strategically implementing these tools can significantly improve peer interaction, feedback processes, and writing outcomes. The findings suggest that CMC tools offer viable solutions for enhancing collaborative writing in higher education, provided institutions address technological infrastructure needs and provide adequate training for educators and students.
A Study on the Requirements of a Smart Security Product for Solitary Women’s Night Travel Based on the KANO Model
Authors: Yu Ping , Zhuang Yingfeng
Published: November 2024

The acceleration of social development and urbanization has led to an increase in the number of women living alone in cities. Due to their physiological and psychological characteristics, these women face heightened safety risks when travelling at night. This study aims to design and evaluate the functions of intelligent security products tailored for women living alone during nighttime travel. Initially, the Customer journey map (CJM) method was employed to identify the pain points and opportunities experienced by users while walking at night. Subsequently, the KJ method was employed to explore, refine, and integrate deeper user needs into a comprehensive list of requirements. The Kano model questionnaire was then designed to subjectively evaluate the positive and negative aspects of the same functional characteristics, classifying them according to the KANO attribute classification comparison table. This allowed for the prioritization of demand items by excluding indifference attributes and focusing on the essential, expected, and attractive attributes. The results indicate that women living alone have significant concerns regarding the safety of nighttime travel. It is therefore crucial to optimize the design of real-time monitoring, alarm, and emotional interaction functions in the products in order to enhance their practicality and user satisfaction.
The Application of Big Data Analytics in the Planning and Placement of Rural Charging Infrastructure
Authors: Zhao Guan , Liu Yongchao , Zhang Tao
Published: November 2024

This paper discusses the application of big data analysis in rural electric vehicle charging infrastructure planning, aiming to promote the development of rural tourism industry and improve the satisfaction of electric vehicle users. By analyzing the travel pattern and charging demand characteristics of rural tourism, a charging station location model considering user experience is established. The study shows that the sparse road network in the countryside needs more charging stations to meet the charging demand of different mileage, and verifies the validity and applicability of the model in the site selection decision.
A Study of Extended Interaction and Reliability of Distribution Networks with Multiple Demand-Side Resources
Authors: Liu Yuanhong , Liu Yongmei , Yu Hui
Published: November 2024

This study aims to improve the reliability and economy of distribution networks, and proposes a multi demand side resource distribution network expansion interaction study. By analyzing the characteristics of energy supply and demand in industrial clusters, a bilevel programming model of distribution network expansion with high permeability DG is constructed. The results show that the absorption capacity of new energy is significantly improved by optimizing the absorption capacity of photovoltaic resources. Finally, the effectiveness of the method is verified by an actual distribution network, and the reliability index of the distribution network is evaluated. This study provides an important reference for distribution network planning and active distribution network, especially in demand response and reliability.
Novel Power System Design and Optimization Based on Renewable Energy Integration
Authors: Li Tao , Wang Bo , Su Yongbin , Li Cheng
Published: November 2024

This study introduces an optimized power system design that integrates renewable energy, focusing on sustainable development and economic efficiency. Using particle swarm optimization, the capacity allocation model shows that optimizing wind turbine models can increase resource utilization and reduce costs. The final system includes 500 wind turbines (750MW), PV modules (300MW), and generators (1050MW total) with 3500MWh storage, achieving a total capacity of 1550MW. The results confirm the method’s effectiveness in reducing emissions and enhancing system performance.
Research on Deep Learning Based Fault Diagnosis and Prediction Methods for Power Systems
Authors: Liu Guangyu , Qum Xinying , Qu Dongzhe
Published: November 2024

The deep learning-based power system fault diagnosis and prediction method combines efficient data acquisition techniques and advanced machine learning algorithms, aiming to improve the accuracy and response speed of fault prediction. By analyzing a large amount of historical and real-time data, the study is able to effectively identify potential fault risks and pinpoint the causes of faults. Experimental results show that the accuracy reaches 98.9% during normal operation. The method shows high efficiency and stability under various environments and conditions, which verifies its feasibility and effectiveness in practical applications. This study is of great value to improve the reliability and efficiency of power systems, and has a positive impact on the development of smart grids.
The Construction and Evaluation of a Labor Education System Based on a Multimodal Model
Authors: Xu Guorong , Zhang Wei
Published: November 2024

This paper proposes the construction and evaluation method of the evaluation system of labor education courses based on the multimodal model. The study analyzes the advantages of unimodal and multimodal models, and explores the effectiveness of multimodal data in identifying the learning input status. The experimental results show that the early fusion model performs well in various evaluation indexes, which proves its effectiveness in improving the accuracy of learning input evaluation. The method of this paper can help improve the evaluation system of labor education courses in colleges and universities, promote the overall development of students, and provide a guarantee for the realization of talent cultivation goals in colleges and universities.
An Innovative Exploration of the Intelligent Management Mode of Electric Power Enterprises in the Era of Big Data
Authors: Qu Dongzhe , Qu Xinying , Liu Guangyu
Published: November 2024

This article proposes an innovative intelligent management model for power enterprises in the big data era, aiming to solve the problem of insufficient analysis and utilization of power operation data. Through text cleaning, continuous bag of words (CBOW) model vectorization and Apriori-LSTM algorithm, efficient classification of power operation texts is achieved. Experimental results show that the algorithm achieves an average accuracy of 93.6% in power operation text classification, which is significantly better than traditional methods. In addition, the LSTM algorithm using mini-batch gradient descent (MBGD) not only improves the accuracy, but also significantly shortens the model training time.
Based on Multimodal Compensatory Virtual Model Room
Authors: Zhang Dongyang , Li Honghai
Published: November 2024

Currently, virtual office model rooms only provide visual experiences. The perception of walls and floors, the spatial distribution of office facility layouts, and the display of the overall effect are poorly understood, resulting in deviations between the virtual experience scene and the final decorated physical objects, increasing the risk of rework. This study aims to explore the impact of tactile-auditory proxy devices on the user experience of virtual office model rooms from a multimodal perspective. By designing tactile-visual proxy devices and virtual prototypes, the conclusion that tactile-auditory proxies can enhance the user experience of virtual space roaming is verified. Based on the sensory compensation interaction theory, an intelligent device design strategy is constructed. Through multimodal synergy, the virtual experience of users is enhanced to provide a more realistic experience for virtual offices and virtual space walking systems.
Research on Group Learning Product Design Based on Hierarchical Analysis Approach
Authors: Guo Rui , Li Honghai
Published: November 2024

With the advancement of educational models and technologies, group learning has received increasing attention. This study is dedicated to developing group learning products that can promote students’ communication and cooperation and enhance multiple skills. Through hierarchical analysis, this study evaluated the key design elements, established a comprehensive evaluation framework, and found six key design elements through questionnaires and in-depth interviews. The weights were further calculated through AHP to optimize the core indicators in the product design. The study proposes a design for an intelligent teaching robot equipped with an interactive interface, automatic recognition, and adjustment functions, aiming to improve the efficiency and quality of group learning, while taking into account the safety and environmental friendliness of the product. Looking forward, the product design will pursue higher intelligence and portability, and utilize new technologies to enhance the customized learning experience.
Research on Digital Protection and Inheritance Strategy of Non-Heritage Culture Based on Artificial Intelligence
Authors: Li Wenjun , Wang Xiaojiao
Published: November 2024

In order to solve the current problems of single form and poor interactivity of intangible cultural heritage protection, research on digital protection and inheritance strategies of intangible cultural heritage based on artificial intelligence is proposed. Taking the protection of clay sculpture intangible cultural heritage as an example, this paper designs the main functional modules of the system cloud and mobile terminals, proposes a rapid modeling method based on a combination of three-dimensional scanning and grid iterative simplification, and uses ORB-FV and optical flow tracking algorithms to achieve online recognition of images. and tracking registration, complete system development based on Unity3D, and conduct experimental verification. The experimental results show that the total time taken by the system to complete image recognition, tracking registration and three-dimensional rendering is 36.5ms, which can meet the real-time system requirements of mobile augmented reality. Conclusion: This system not only meets the requirements of realism and fluency for the enhanced display of intangible cultural heritage products on the mobile terminal, but also realizes the real-time interactive coloring display function after the enhanced display of the model, which enhances the fun and interactivity of the protection and dissemination of intangible cultural heritage.
An Assisted Decision-Making Method for Microgrid Optimal Dispatch Based on Deep Bidirectional Long- and Short-Term Memory Networks
Authors: Jiang Yicheng , Kong Piaohong , Gu Dongjian , Zhu Nan , Zhu Jianping
Published: November 2024

This paper proposes an auxiliary decision-making method for microgrid optimal scheduling based on deep bi-directional long and short-term memory network to solve the problem that the existing microgrid scheduling optimization methods cannot effectively accumulate and mine the learned scheduling knowledge. Firstly, the mathematical planning model of microgrid optimal operation is introduced, and its limitations are analyzed. Subsequently, the day-ahead optimal scheduling model based on deep learning and its correction and processing principles are described in detail, and the effectiveness and accuracy of the method are verified through case studies. The experimental results show that the method in this paper has only 1.42% average error in the total system operating cost compared with the traditional model-driven method, which proves its potential in improving the model solving accuracy.
A Study of Machine Learning-Based Models for Assessing the Quality of Financial Statements
Authors: Zhang Chongyan
Published: November 2024

A machine learning-based financial statement quality assessment model is proposed, which aims to provide a reliable reference for the value assessment of new energy enterprises and guide the decision-making of the market and investors. The model improves the free cash flow model and applies the gray time series combination model to predict the future operating income of the enterprise. The study shows that the accuracy of the gray time series combination model in predicting the future income of the enterprise is better than that of a single model, effectively integrates the information and data of multiple models, and enriches the system of enterprise value assessment methods.
Research on the Correlation Between Virtual Scene Interaction Methods and Experience Based on Emotional Measurement Methods
Authors: Feng Zichong , An Cong
Published: November 2024

In virtual scene interaction, different interaction methods affect user emotions and experience. This study uses the PAD emotional scale and eye tracking technology to quantitatively analyze user emotional responses and experience, aiming to propose and apply a user emotional experience evaluation method based on the PAD emotional model and eye tracking. At the same time, the paper takes the digital exhibition hall of traditional Chinese medicine science popularization as an example to verify the method of combining the PAD emotional scale with eye tracking. By recording the emotional state of users when experiencing different interaction modes, it simulates and compares the display interaction method with the experience interaction method to evaluate the effectiveness of virtual scene interaction experience. The research results show that display interaction has advantages in ease of use, but experience interaction can significantly enhance immersion, and users generally prefer the latter.
Intelligent Storage Method of Student Education Management Data and Information in Colleges and Universities Under Network Communication Platform
Authors: Xu Zihan , Wang Ziyue , Wang Hangyu
Published: November 2024

In order to solve the problem of low storage efficiency in existing educational resource management technology, an intelligent storage method for college student education management data information under the network communication platform was proposed. This paper proposes an optimized educational resource management technology that improves storage efficiency through Hadoop cloud storage architecture, digital information management and big data mining methods. Experimental results show that the storage efficiency of this technology is 35.7% higher than the existing technology.
A Study of Artificial Intelligence-Assisted Art Creation and Style Migration Techniques
Authors: Xing Yadan
Published: November 2024

This study addresses detail loss and authenticity issues in image style transfer by using AI-assisted art creation and style transfer technologies. It proposes replacing the original ResNet network model with a U-Net network structure, which better preserves image details and structure through its encoder-decoder design and jumping connections. These features enhance the capture of multi-scale information, leading to improved detail recovery. Experiments validate the effectiveness of the proposed method, showing that the improved CycleGAN algorithm with a U-Net generator and self-attention mechanism outperforms the benchmark algorithm in PSNR and SSIM scores. The results demonstrate significant improvements in detail retention and visual realism in style-transferred images.