bluuebunny/crossref_metadata_2025 huggingface dataset:
The application of multiple regression model in interactive English classroom teaching
Authors: Wang Meixiao
Published: August 2023

To verify the effect of the interactive teaching model in English teaching, the author proposes the application of the multiple regression model in the interactive teaching of English classrooms. Authors, by collecting data on each relevant factor, a multiple regression system with regression simulation computing capability was designed and implemented, and the model was solved and analyzed based on Matlab software. Experimental results show that: According to the multiple regression model, the average grade is 1.3732, which shows that the interactive teaching effect is obvious. Conclusion: The application of the multiple regression model in English classroom interactive teaching is of great significance to the reform of college English teaching.
Scheduling Optimization of hotel supply chain based on heterogeneous multipopulation ant colony algorithm
Authors: Yuan Qing
Published: August 2023

A hotel supply chain management system is distributed with considerable computation. In this paper, a multi-colony ant algorithm based on heterogeneous is designed. An optimal scheme based on distributed programming is proposed. A heterogeneous multi-colony ant algorithm is a kind of ant colony with multiple characteristics. Different ant species have other population characteristics and apparent advantages and complementarity. Several heterogeneous ants with optimized performance were studied. In this paper, the collaboration is carried out on several computing nodes. The algorithm of this model can satisfy the characteristics of multiple orders. This algorithm can optimize distributed computing resources in the hotel supply chain to the maximum extent for large and complex suppliers and collaborative time ordering problems. Simulation results show that the proposed method achieves good efficiency, stability and order adaptability.
Dance Emotion Characteristic Parameters Based on Deep Learning Model
Authors: Liu Hongyun
Published: August 2023

In this paper, the emotions of dancers are identified in combination with the integrated deep-learning model. Firstly, four initial value features with important emotional states are extracted from the time, frequency, and time-frequency domains, respectively. It was isolated using a deep belief network enhanced by neuro colloidal chains. Finally, the finite Boltzmann criterion integrates the features of higher abstractions and predicts the emotional states. The results of DEAP data show that the correlation between EEG channels can be discovered and applied by glial chains. The fused deep learning model combines EEG emotional features with temporal, frequency, and expressive qualities.
BIM Model Design of Deep Foundation Pit Engineering Based on BP Network
Authors: Chenghui Wei , Hao Chen , Di Wu
Published: August 2023

It is of great significance to predict the multistage deformation of the foundation pit. A new neural network method is proposed in this paper. The disadvantages of the BP neural network multistage forecast method are discussed. A multistage recursive neural network model for foundation deformation prediction is established. They are taking a deep foundation pit project in the soft soil area as an example. The multistage deformation prediction method is verified in this paper. This new detection technique is feasible. This method can also be used for multistage forecasting.
Construction Cost Control and Management Based on Mapping Model and BIM
Authors: Chenghui Wei , Hao Chen , Bin Wu
Published: August 2023

At present, the information management of highway construction is still at different levels. Poor information coordination ability. Lack of adequate information technology support. BIM technology is used to realize cooperation and information integration among various disciplines. According to the characteristics of highway construction, this paper constructs the decomposition code of the BIM model by the particle swarm method. This model can better reflect the whole process of highway project cost control characteristics. The corresponding relationship between the “three-level list” and the BIM code is constructed. This paper makes a comprehensive analysis and discussion on the mapping between it and the “item list” in the three types of lists. Thus, BIM can be efficiently connected with the three-level list in the construction of bridge projects. It can better adapt to engineering construction and other engineering management requirements.
Strategic Policy Innovation of Regional Development Strategy Transformation in the New Era Based on Progressive Differential Model
Authors: Wang Lingli , Zhao Feng , Zhao Boyu
Published: August 2023

In the new era, the national high-tech industrial development Zone is a powerful platform for implementing the innovation-driven development strategy and promoting China’s high-level development. An empirical study of panel data from 285 county-level cities in China during 2001-2022 was conducted using the binary difference method. The results show that high-tech enterprises have a noticeable promoting effect on improving the quantity of industrial structure. The transformation and upgrading of our industrial design by high-tech enterprises have significant cyclical heterogeneity. It has significantly enhanced the industrial system compared with the “growth type” and “mature type” national high-tech development zones. There is no apparent regional difference in the quality effect of high-tech enterprises on industrial structure upgrading. Still, there is an evident regional difference in the quantity and rationality of industrial structure height.
Construction of network mathematics model for college English mixed teaching
Authors: Chen Siwen , Tian Yanyan
Published: August 2023

To better carry out college English blended teaching and make students adapt better, author Z proposes a method of college English blended teaching model based on the Internet of Things network platform. According to the development of today’s Internet of Things technology, this method combines English learning and the use of cloud computing to develop the Internet network platform, so it is suitable for professionals teaching in college to complete English education., thus improving the quality of education. According to the test results: the average score of 4th grade online students is 523, 78.3% scored above 425; The average score of 4th graders in the non-network course was 394, and 62.4% scored above 425. The 4th-grade score for the online course was 129 points higher than the average score nia average for the offline course and 15.9% higher than the average score of 425. Conclusion: The author’s approach can contribute to the creation of mixed English courses in colleges and universities sad.
Construction of feature extraction model for machine foreign language translation evaluation system
Authors: Hu Honghui
Published: August 2023

To solve the problem that English and Chinese are different in many aspects and often misunderstood in communication, the author proposes a machine foreign language translation evaluation system based on Internet of Things automation technology. By designing an interactive English-Chinese machine translation A system based on the B/S framework can help improve communication between English and Chinese. The system is based on the B/S three-layer architecture, and the system hardware part only focuses on basic language recognition hardware, English-Chinese translation hardware, and production tools; The software produces three main services, which are user access to the application, language recognition, and English-Chinese service. According to the test results: After the translation was evaluated by experts using a system developed for translation, the evaluation score of the book is 3.769 points. The language is 3.5 points, which is above the limit value of the design standard. Conclusion: It is proved that the translation quality of the system is high and meets the demands of the users.
Application of Economic Management System Based on Nonlinear Algebraic Equation
Authors: Lu Xinyao , Pu Ruihui
Published: August 2023

To better construct the economic management system, the author proposes a method based on nonlinear algebraic equations. Using BDS statistics as the test method of data model correctness, it is proved that BDS statistics can be used to test the correctness of a large class of data models. Based on the actual economic data, the validity of the BDS statistical test method and its theory is verified. The experimental results show that the BDS statistics obtained are 5.77 and 7.11. It can be seen that BDS statistics reject AR (2) model. This implies that some part of the sequence has a large variance, which is derived from a different system, and therefore leads to the rejection of the null hypothesis. It is proved that BDS statistics can be used to test the correctness of a large class of data models.
Nonlinear mathematical modeling in the model of village cultural industry
Authors: Zhang Xiaodong , Peng Changrong , Song Nan
Published: August 2023

To solve the problem that the current forecasting methods cannot describe the long-term correlation of traffic, which leads to low prediction accuracy, the author proposes a mathematical modeling, forecasting and analysis method for village nonlinear traffic. The original nonlinear traffic data collected from the village comes from each base station, the information contained is uneven, pre-processing the collected data, eliminating abnormal values and duplicate data, and supplementing the missing data. Nonlinear traffic contains limited information, so a random forest algorithm is used to extract traffic characteristics and reduce data processing dimensions. The nonlinear traffic characteristics of the village are convolved, and the cross entropy function is used as the loss function, the feature vector of the input prediction model is deeply learned, and the communication traffic prediction results are obtained. Taking the traffic data of the communication operation enterprise’s base station as the test data, the experiment results show that, in the test with 1 million pieces of data, the decision coefficient of the mathematical modeling, prediction and analysis method of village nonlinear flow designed by the author is 0.9599, which is 0.1267 and 0.1431 higher than the prediction and analysis method based on genetic algorithm and fuzzy clustering algorithm respectively. In the modeling and prediction of nonlinear flow, the determination coefficient of the method proposed by the author is closer to 1, the fitting degree of this method is better than that of the contrast method, and it is adaptive in the real scene with a large amount of data. It is proved that the mathematical modeling and prediction analysis method designed in this design can reduce NRMSE and MAPE, improve the determination coefficient of prediction results, and provide the basis for village analysis.
Application of Computer Big Data Modeling Based on Lagrangian Mathematical Equation in the Village Cultural Industry Model
Authors: Zhang Xiaodong , Peng Changrong , Liu Qian , Ma Yichu
Published: August 2023

To understand the Lagrangian mathematical equation, the author proposes an application study of big data modeling in the village cultural industry model. The author takes 20 traditional villages in Beijing as the object, and through crawling relevant Internet cultural and tourism big data, using the theory of tourism consumer behavior, from the aspects of consumer motivation behavior, food, housing, shopping, and other experience behavior, consumer evaluation behavior, and consumer space-time behavior, carry out targeted content analysis, aggregation analysis, etc, fully reveal the behavioral portrait of tourists in Beijing’s traditional villages. The results show that the overall tourism experience of Beijing’s traditional villages is good, but the development level is quite different, the cultural and tourism supply pattern of “some have boutiques, some have highlights, and the overall influence is weak” is presented to improve the overall level. At the same time, the computer big data based on tourists’ feedback can reasonably reveal the inherent characteristics and problems of traditional village tourism, which is innovative in the current situation where village tourism data is difficult to obtain.
Analysis of Macro Environment and Development Countermeasures of the Education Industry Based on the PEST Model
Authors: Wang Lihui , Hou Chen
Published: August 2023

To understand the macro environment of the education industry and analyze the development countermeasures, the author proposes a PEST model. The author takes the macro environment analysis of vocational education development in Sichuan Province as the research object. In recent years, the economic development of Sichuan Province has accelerated, and the GDP growth rate has been higher than the national GDP growth rate for many consecutive years. At the same time, the industrial structure has also been continuously optimized and adjusted, which has brought opportunities for the development of vocational education in Sichuan Province, but it also brings many challenges. The author uses the PEST model to analyze the development of vocational education in Sichuan Province, grasp the macro environment faced by the development of vocational education in Sichuan Province, and propose corresponding development strategies.
Characteristic Analysis of Cheerleading Self-selected Action Arrangement Elements Based on BP Neural Network
Authors: Wang Caohui , An Chenwei
Published: August 2023

BP neural network is a typical algorithm in artificial intelligence networks, and it has strong nonlinear mapping ability, solving some nonlinear problems and pattern recognition is its most prominent part. The network topology of the BP neural network is simple, it has high error precision, it is easy to program, and also has strong operability, it is one of the most important algorithms in the field of data mining. Cheerleading is one of the dance cheerleading events, because of its sunshine, fashion and vitality, it has become a new sports event on campus, although cheerleading has developed rapidly in China, its promotion on campus is still at the initial stage, with the increasing number of public contestants, the competition among the participating teams has become increasingly fierce, excellent choreography is the key to victory, by using the methods of literature, video analysis and mathematical statistics, the author made an in-depth analysis of the top eight teams, including 24 teams, who achieved the best in the collective flower ball optional complete set of actions in the three open national cheerleading championships from 2019 to 2021, grasp the current situation and trend of the arrangement of free flower ball movements in the open children’s group, and summarize its rules, it provides a theoretical basis for the arrangement of the set of collective flower ball optional movements of the open university group, improve the overall level of the flower ball cheerleading program of the open university group, and play a role in consolidating the basic learning of flower ball cheerleading.
Application of Deep Learning in Vocal Music Teaching
Authors: Zheng Lili , Cui Lina
Published: August 2023

This paper builds a cloud-oriented speech teaching system based on deep learning mode. A synthetic algorithm for decision-making based on depth and hierarchy knowledge is presented. This algorithm calculates the weight matrix of the user and marks to achieve personalized speech recommendations. The whole process of cloud music teaching has been realized. The identification performance of the recorded database is compared with that of the Berlin database. It is proved that the identification ability of this algorithm is greatly improved.
Design of English pronunciation quality evaluation system based on the deep learning model
Authors: Zhang Fangfang , Zhou Zhihong
Published: August 2023

To explore the design of the English pronunciation quality evaluation system, a design of the English pronunciation quality evaluation system based on a deep learning model is proposed. This method explores the research of English pronunciation quality evaluation by recommending key technical problems and solutions based on information represented by the deep learning model. The research shows that the efficiency of the English pronunciation quality evaluation system based on a deep learning model is about 30% higher than that of traditional methods. Through the experimental verification, the English pronunciation quality evaluation model method is reasonable and reliable. It can give learners timely, accurate, and objective evaluation and feedback guidance, help learners find out the difference between their pronunciation and standard pronunciation, correct pronunciation errors, and improve the efficiency of English spoken language learning.
Curriculum Construction Practice of Ideological and Political Education Based on the IPO Model
Authors: Song Lili
Published: August 2023

This paper establishes the teaching quality evaluation model and index system of ideological and political education with quality products as the core. This method was used to investigate 1140 college students in 10 universities. The results show that college students ignore intrinsic motivation and goals and lack ideal thinking in learning quality. In terms of course quality, there are some problems: the overall level of students’ investment in the course is not high, and their satisfaction with the course teaching is not high. The results of empirical analysis show that the multiple linear regression estimation based on the IPO method can better resist outliers and get a better prediction effect.
Construction of computer-assisted English writing teaching model from the perspective of the Internet of Things
Authors: Liu Fang
Published: August 2023

To solve the problems of the traditional embedded software development teaching platform, such as the heavy load on the server side, resulting in the slow response speed and poor experience of users, this paper proposes a computer-aided English writing teaching model from the perspective of the Internet of things. Based on the cloud platform, the system manages the resources of computers scattered on the server and client, to improve the efficiency of resource retrieval. In addition, based on the fuzzy logic model, the system can evaluate and evaluate students’ knowledge and learning achievements according to students’ preferences for cognition and knowledge acquisition. The experimental results show that motivation (μmot), attitude (μatt), extroversion (μext) and self-esteem (µsel) are positively correlated with students’ performance, and the data are 0.608, 0.533, 0.595 and 0.477 respectively, while introversion (µint) and anxiety (µanx) are negatively correlated with students’ performance, and the data are −0.464, −0.618. Conclusion: from the perspective of the Internet of Things, the computer-assisted English writing teaching model has good performance and can play a positive role in improving students’ grades.
A study on the cognitive model of student management in colleges and universities under the perspective of big data technology
Authors: Wang Enfu
Published: August 2023

The development of big data concepts and technology can not only effectively improve management efficiency but also promote the realization of personalized management. Based on the concept of big data and the management concepts advocated by scientific management theory, goal management theory, and human-oriented management theory, the survey materials were analyzed and organized to understand the current situation of student management in higher education institutions in terms of study management, internship management, merit management, life management, mental health management, and employment management. Combined with the background of big data, we found that there are problems in student management in higher education institutions, such as incomplete information collection, subjective decision-making, low efficiency of resource utilization, delayed management feedback, and lack of personalized management. Therefore, using the concept of big data to promote the optimization of student management in higher education institutions will be the future development trend.
Study on the application of deep learning technology and BIM model in the quality management of bridge design and construction stage
Authors: Huang Rui , Zheng Huan , Lei Jun
Published: August 2023

The development of the transportation industry can effectively accelerate the speed of economic development, in which bridges occupy an important position in transportation. The safety of the bridge design and construction process is a key part of bridge construction, and relying on human resources to investigate safety hazards greatly affects efficiency. In this paper, we combine deep learning technology and the BIM model to explore the synergistic effect of both on the quality management of the bridge construction phase and analyze the measured data. The results show that the application of the BIM model can improve efficiency by 35% compared with the traditional 2D CAD drawings, and the accuracy of data analysis can be improved by 12.51% and 14.26% for DNN and DBN models based on deep learning, respectively. The addition of the GSO algorithm leads to a further 19.19% improvement in the training accuracy of the coupled model. Finally, the optimization model was used to analyze the load factors and force majeure factors that affect the safety of the bridge, and to find the structural factors that affect the safety of the bridge design, which guides to ensure the quality of the bridge during the construction process.
A trajectory prediction method based on graph attention mechanism
Authors: Zhou Hejun , Zhao Ting , Fang Yang , liu Qilie
Published: August 2023

Vehicle trajectory prediction is one of the key technologies to realize autonomous driving, which provides an important guarantee for the safety of vehicles in the process of autonomous driving. In this paper, with this as the starting point, a graph convolutional neural network is introduced through a graph attention mechanism to obtain scene features by modeling the temporal Transformer model of surrounding information. Based on the temporal convolutional model to obtain scene features, new feature vectors are calculated by aggregating the weights for the features of nodes and neighboring nodes. Then the input feature dimensions are transformed into the weight matrix of the output feature dimensions, and the output feature vector corresponding to the attention coefficients is calculated by using weighted summation. Then the effect of multiple training of the model is evaluated by taking the mean value and defining its structural relationship. The experimental results show that the prediction error of the proposed method is significantly smaller than that of the comparison method in scenarios with speeds less than or equal to 5m/s and greater than 5m/s. The prediction error based on target detection is reduced by 58.95%, indicating that the proposed method is more consistent with the operation scenarios of autonomous driving.
Teacher evaluations of open educational resources designed to support dialogic cultural literacy learning in schools
Authors: Zimmermann Maria , Mayweg-Paus Elisabeth , Ruwe Theresa , Maine Fiona
Published: August 2023

For teaching practice to be useful, educational materials must be thoroughly evaluated prior to use. In this study, teachers evaluated open educational resources (OER) created for a European Commission Horizon 2020 project called DIALLS (‘DIalogue and Argumentation for cultural Literacy Learning in Schools’). Considering research on how OER are evaluated, we were interested in learning (1) how teachers perceive their application, content, design, value and sustainability and (2) what other aspects teachers find important when evaluating OER. After analysing quantitative and qualitative data, we found that aspects facilitating self-regulated use were rated most highly and mentioned most often. Teachers additionally valued adaptable materials offering opportunities to reflect their teaching practices. Future research may benefit from evaluating OER based on ‘affordance’ aspects — aspects that allow teachers to adapt the materials in a self-regulated way and reflect on their teaching.
Metamorphic dolomitic marble-hosted talc from the Mulvoj area in the Western Pamir Mountains, Tajikistan
Authors: Moazzen Mohssen , Silmonov Intizor , Elnazarov Sangin
Published: August 2023

Talc is crystallized in the metamorphic dolomitic rocks of the southwest Pamir mountains in the Mulvoj area, Tajikistan. Field studies show that talc is restricted to metamorphic dolomitic marble layers in the garnet-mica schist and gneiss. The layers are parallel to the original sedimentary bedding and schistosity of the metamorphic rocks. Petrography and whole rock geochemistry reveal calcite, tremolite, quartz and dolomite as the main mineral phases in the talc-bearing metamorphosed dolomitic rocks, while calcite is absent in the samples without talc. XRD studies show that talc samples are almost pure, and geochemistry indicates very low Fe and Cr and very high Mg contents. Geochemical features along with field observations clearly shows that Mulvoj talc is not originated from peridotite. Based on phase relations studies in the CaO-MgO-SiO2-H2O-CO2 system, the reaction between dolomite, quartz, and water at pressure greater than 2 kbar and temperature up to ~460°C and XCO2 up to 0.6 was the main talc forming reaction. Talc and calcite consuming reaction produced tremolite, dolomite and binary (CO2-H2O) fluid.
Productive Organisational Energy and Performance in Estonian Football Organisations
Authors: Aidla Anne , Iliushchenkov Georgii
Published: August 2023

Sports governance is a broad domain in which many ambitious goals are expected to be considered by top management. Attending to productive organisational energy may be the key to consolidating and amplifying efforts by members of sports organisations at individual, group and organisational levels in order to achieve those wide-ranging goals. The aim of the article is to discover whether Estonian football organisations with higher results for the dimensions of productive organisational energy also show higher performance. Overall, we reached about 14% of the population of players, coaching staff and management from football organisations in Estonia. Productive organisational energy was measured using affective, cognitive and behavioural dimensions (Cole et al., 2012). Rankings in the league tables for 2020, 2021 and 2022 reflected the performance of the football clubs. The results demonstrated that football clubs that had higher levels of productive organisational energy were mostly placed in the top half of the league table. All three dimensions of productive organisational energy were similarly relevant in regard to performance. The connection between productive organisational energy and performance has so far been analysed only in business organisations and in one health service organisation. We brought the topic to the sports context and distinguished three dimensions of productive organisational energy while comparing the performance of organisations, which has not been done before. We also conducted the first empirical study that considers whether dimensions of productive organisational energy are balanced in better performing clubs.
THE USE OF ROUGH CLASSIFICATION AND TWO THRESHOLD TWO DIVISORS FOR DEDUPLICATION
Authors: B.  Jehlol Hashem , E. George Loay
Published: August 2023

The data deduplication technique efficiently reduces and removes redundant data in big data storage systems. The main issue is that the data deduplication requires expensive computational effort to remove duplicate data due to the vast size of big data. The paper attempts to reduce the time and computation required for data deduplication stages. The chunking and hashing stage often requires a lot of calculations and time. This paper initially proposes an efficient new method to exploit the parallel processing of deduplication systems with the best performance. The proposed system is designed to use multicore computing efficiently. First, The proposed method removes redundant data by making a rough classification for the input into several classes using the histogram similarity and k-mean algorithm. Next, a new method for calculating the divisor list for each class was introduced to improve the chunking method and increase the data deduplication ratio. Finally, the performance of the proposed method was evaluated using three datasets as test examples. The proposed method proves that data deduplication based on classes and a multicore processor is much faster than a single-core processor. Moreover, the experimental results showed that the proposed method significantly improved the performance of Two Threshold Two Divisors (TTTD) and Basic Sliding Window BSW algorithms.
REVIEW ON DETECTION OF RICE PLANT LEAVES DISEASES USING DATA AUGMENTATION AND TRANSFER LEARNING TECHNIQUES
Authors: Alaa Hussein Osama , Salih Mahdi Mohammed
Published: August 2023

The most important cereal crop in the world is rice (Oryza sativa). Over half of the world's population uses it as a staple food and energy source. Abiotic and biotic factors such as precipitation, soil fertility, temperature, pests, bacteria, and viruses, among others, impact the yield production and quality of rice grain. Farmers spend a lot of time and money managing diseases, and they do so using a bankrupt "eye" method that leads to unsanitary farming practices. The development of agricultural technology is greatly conducive to the automatic detection of pathogenic organisms in the leaves of rice plants. Several deep learning algorithms are discussed, and processors for computer vision problems such as image classification, object segmentation, and image analysis are discussed. The paper showed many methods for detecting, characterizing, estimating, and using diseases in a range of crops. The methods of increasing the number of images in the data set were shown. Two methods were presented, the first is traditional reinforcement methods, and the second is generative adversarial networks. And many of the advantages have been demonstrated in the research paper for the work that has been done in the field of deep learning.
Big Data Analytics: A Survey
Authors: Kadhim Jawad Wasnaa , M. Al-Bakry Abbas
Published: August 2023

Internet-based programs and communication techniques have become widely used and respected in the IT industry recently. A persistent source of "big data," or data that is enormous in volume, diverse in type, and has a complicated multidimensional structure, is internet applications and communications. Today, several measures are routinely performed with no assurance that any of them will be helpful in understanding the phenomenon of interest in an era of automatic, large-scale data collection. Online transactions that involve buying, selling, or even investing are all examples of e-commerce. As a result, they generate data that has a complex structure and a high dimension. The usual data storage techniques cannot handle those enormous volumes of data. There is a lot of work being done to find ways to minimize the dimensionality of big data in order to provide analytics reports that are even more accurate and data visualizations that are more interesting. As a result, the purpose of this survey study is to give an overview of big data analytics along with related problems and issues that go beyond technology.
A Survey on Cybercrime Using Social Media
Authors: Khyioon Abdalrdha Zainab , Mohsin Al-Bakry Abbas , K. Farhan Alaa
Published: August 2023

There is growing interest in automating crime detection and prevention for large populations as a result of the increased usage of social media for victimization and criminal activities. This area is frequently researched due to its potential for enabling criminals to reach a large audience. While several studies have investigated specific crimes on social media, a comprehensive review paper that examines all types of social media crimes, their similarities, and detection methods is still lacking. The identification of similarities among crimes and detection methods can facilitate knowledge and data transfer across domains. The goal of this study is to collect a library of social media crimes and establish their connections using a crime taxonomy. The survey also identifies publicly accessible datasets and offers areas for additional study in this area.
Chequeando al fact-checker. Prácticas de verificación política y sesgos partidistas en Newtral (España)
Authors: García-Marín David , Rubio-Jordán Ana Virginia , Salvat-Martinrey Guiomar
Published: August 2023

El periodismo de verificación o fact-checking se ha erigido en los últimos años en una de las estrategias centrales en la lucha contra la desinformación. Para que estas entidades resulten eficaces y logren la confianza de la ciudadanía, resulta fundamental que realicen su labor bajo principios de neutralidad ideológica, sobre todo cuando tratan de verificar el discurso político. Este trabajo, pionero en el contexto español, pretende analizar las prácticas de verificación y los posibles sesgos partidistas del fact-checking en España a través de un estudio específico aplicado a Newtral, el principal fact-checker especializado en política del país. Mediante análisis de contenido de tipo cuantitativo, se estudiaron las prácticas periodísticas utilizadas en los desmentidos políticos de este verificador desde el inicio de su actividad (octubre 2018-octubre 2022). En una segunda fase, se replicó el mismo estudio aplicado solo a los chequeos del discurso de los principales líderes políticos nacionales. El análisis se realizó mediante estadística inferencial (pruebas de chi cuadrado, estudios correlacionales, test de Kruskal-Wallis y U de Mann-Whitney). No se observan diferencias significativas entre partidos políticos en ninguna de las variables analizadas en las fases de ejecución y resolución de los chequeos ni en la muestra general ni en la específica relativa a los líderes políticos. Sin embargo, se aprecia una mayor atención al discurso de los políticos del Partido Popular, que reciben mayor número de verificados, lo que podría implicar un cierto sesgo de selección.
Buenas prácticas en la radio comunitaria. Estudio de caso a través de la aplicación del indicador IRSCOM en Colombia
Authors: Espinar Lara , Peralta García Lidia , Chaparro Escudero Manuel
Published: August 2023

Este trabajo presenta un compendio de buenas prácticas detectadas a partir de la aplicación del Indicador de Rentabilidad Social en Comunicación IRSCOM[1] a una muestra de 12 emisoras comunitarias y de interés público indígena en Colombia durante el año 2022. El IRSCOM-RADCC (Radio Comunitaria Colombia) es una metodología testada que se concreta en 33 indicadores y está diseñada para recoger información cuantitativa y cualitativa sobre el funcionamiento interno de los medios de comunicación en relación con seis categorías de análisis: gestión, capital social, articulación territorial y ciudadana, programación, actividad en Internet e infraestructura. La información recaudada pasa por un proceso de ponderación que resulta en puntuaciones numéricas para cada una de sus variables, permitiendo observar fortalezas y debilidades. La herramienta facilita la recogida de información cualitativa en forma de buenas prácticas para cada una de sus variables, gracias a los resultados de la entrevista semi-estructurada que acompaña a la metodología de implementación de IRSCOM. Los resultados han puesto de manifiesto formas ingeniosas por parte de las emisoras de autogestionarse, así como de fidelizar la participación, tanto en gestión como en la realización de programas. Se detecta además un interés creciente por la diversidad y los aspectos diferenciales en la configuración del capital social y en los contenidos programáticos, así como un alto nivel de vinculación con el tejido social. Todo ello las convierte en eje de vertebración territorial y de puesta en valor de la comunicación de proximidad.
[1] LabCOMandalucía, 2012
Effect of Global Oil Price Volatility and Exchange Rate Policy on Foreign Exchange Reserves in Iraq
Authors: Khudhair Layla Bdaiwi , Ghadeer Yousif Hakim
Published: August 2023

Purpose: This paper offers simulations and forecasts of the ideal currency reserve measure in light of future shocks to the Iraqi economy due to the downturn in the international price of oil and the global economic shutdown triggered by the Corona pandemic.

 

Theoretical framework: The Iraqi foreign exchange reserves have entered a cycle of sustained and accelerated degradation in recent years and hit alarming amounts in 2020, affecting Iraq's financial stability compared to other foreign currency reserves. According to figures from the Iraqi Parliament's Financial Commission, the Iraqi fund in the Central Bank of Iraq decreased, following removing the government's second loan by the end of 2020, to $35 billion. The Fitch Ratings Agency, on the other hand, has found that Iraq's plan to slash public sector wages and pension costs will delay the reduction of currency reserves as part of the attempt to lower financial imbalances and relieve financial pressures. However, it will be difficult to enforce and risk exacerbating social disorders. According to Fitch, by the end of August (15% of projected GDP for 2020), cash funding from the Central Bank of Iraq grew to 28.5 billion Iraqi dinars from 14.1 billion Iraqi dinars at the end of May.

 

Design/methodology/approach: The study uses an analytical approach to show the fluctuations in oil prices and their impact on the fluctuation of oil revenues and the currency-selling window that the Central Bank of Iraq applies to its foreign reserves.

 

Findings: The systemic problem of worldwide petroleum price drops that provide longer-term estimates to estimate the decrease in petroleum prices on global oil markets explains the quick fall in Iraqi exchange reserve magnitude. Iraq's foreign reserves, mostly from oil exports, fulfill international standards. Iraq's exchange rate policy depends on the Central Bank's direct foreign currency sales. This approach reduces foreign money diversion from Iraq, preventing the central bank from maintaining exchange rate stability.

 

Research, Practical & Social implications: The impact of foreign reserves on national financial stability is becoming more obvious as their function evolves from supplying fundamental transaction needs to fulfilling financial security criteria.

 

Originality/value: The Iraqi dinar's value must be protected at all costs, hence the Central Bank of Iraq's foreign reserves are crucial. These reserves are affected by oil revenues, the main financier for it, and the window for selling the currency, which is the outlet for leakage from it.
'Why Don't I Just Create my Main To be a Space That I Could Always Feel That Comfortable?': Negotiating Achievement Imperatives Through Instagram.
Authors:   , Chrystall Rebecca
Published: August 2023

Young people appear to be under extreme pressure to live up to complicated, unrealistic expectations to ‘achieve’ across the domains of their lives. These expectations include achieving academically, gaining employment, volunteering their time, participating in their culture and community, as well as carefully maintaining the self physically and mentally. The pursuit of all these goals together may be a stressful, failure-prone task that can encourage feelings of distress, anxiety, depression, and, in extreme cases suicidality, amongst young people. Instagram is a key pedagogic tool for young people to understand who and how they should be in the world. Importantly, this platform may reflect and reinforce expectations of achievement by, and to, young people. Prefects are considered role models for their peers and as such may be under exacerbated pressure to meet these achievement demands. As such, their experiences may be particularly valuable to understand achievement imperatives. Expectations are gendered; achieving as a young woman, or successful femininity, is defined separately to standards of achievement for young men. As such, this thesis explores how young women negotiate complex and competing gendered achievement expectations through Instagram. Nine young women were recruited from a local, single-sex secondary school in Pōneke, Aotearoa to participate in a three-stage study. The first stage included an initial focus group exploring expectations these young women negotiated in their day-to-day lives. Following this, the participants were followed on Instagram for a period of six weeks during which time the interviewer engaged them in discussion around their posted Instagram content. A final focus group was conducted to explore these young women’s management of Instagram norms. Social constructionist thematic analysis was used to analyse focus group transcripts, online discussions, and Instagram content. Through Instagram, the participants negotiated three key achievement imperatives with their followers: control, authenticity and intimacy. These imperatives are explored through circumstances in which the participants achieve or struggle to achieve these in ways they prefer. At times the platform presented the achievement of these imperatives as a possibility, at other times the platform limited the participants’ capacity to manage these imperatives. The implications for the participants as they negotiate themselves and their lives through Instagram are discussed. This research has implications for the way that Instagram is understood, in research and in the public sphere, to impact young people’s health and wellbeing. Young people are critical, capable users of the Instagram platform, that aim to manage complex achievement imperatives within a constantly evolving social world.
https://www.cijds.calebuniversity.edu.ng/
Authors:   Bursary Department, Michael and Cecilia Ibru University,  Ughelli, Delta State, Nigeria, Akenroye Christopher Taiwo , Adegbie Folajimi Festus ,   Department of Accounting, Babcock University, Ilishan-Remo, Ogun State, Nigeria, Owolabi Sunday  Ajao ,   Department of Accounting, Babcock University, Ilishan-Remo, Ogun State, Nigeria, Ajibade Ayodeji ,   Department of Accounting, Babcock University, Ilishan-Remo, Ogun State, Nigeria, Adelegan Michael Oluyomi ,   Faculty of Management Sciences, University of Benin, Benin, Edo State, Nigeria, Otubor Christopher Osega ,   Department of Banking and Finance, Faculty of Management Sciences, University of Jos, Nigeria
Published: August 2023

In today’s dynamic and competitive business environment, solvency is a critical success factor that strategically enables a firm to structure their resources in meeting their financial obligations on the short, medium and long-term bases. However, the inability of a firm to maintain acceptable level of financial stability threatens its future growth. A company’s inability to sustain robust solvency portends the firm’s sick state that impairs its organic growth rate. Firms’ improper utilization of their unique characteristics as their corporate strategic drivers has given rise to illiquidity causing existential threat among listed firms in Nigeria. This study examines the effect of firms’ characteristics on solvency of selected listed companies in Nigeria. The study adopted ex-post facto research design. The population of the study was 161 listed companies in Nigeria as at 31st December 2020 with a chosen sample size of 111 purposively determined. Secondary data extracted from the published audited financial statements covering a 10-year period (2011–2020) were used for the study. Descriptive and inferential (multiple regression) statistics were employed to analyze the data. Findings revealed that corporate strategic drivers had joint significant effects on short-term solvency and long-term solvency. The study concludes that corporate strategic drivers exert significant influence on solvency of listed firms in Nigeria. The study recommends that firms should continue to utilize their corporate strategic characteristics to drive their short-term and long-term solvency statuses. Keywords: Corporate Strategic Drivers, Financial strategy, Firms’ Characteristics, Long-term solvency, Short-term solvency
Education, human capital development and endogeneous growth in selected African countries
Authors:   Department of Economics, Caleb University, Imota, Lagos, Nigeria, Ifarajimi Gilbert , Salisu Olubowale. O ,   Department of Economics, Caleb University, Imota, Lagos, Nigeria
Published: August 2023

The study examined the effect of education and human capital development on endogenous growth drawing evidence from selected African Countries within the period of 1980-2020. Survey research design was used and secondary data was sourced from world bank statistical bulletin based on tertiary education enrolment rate (TEER) vocational education enrolment rate (VEER), labour force participation rate (LFPR) and endogenous growth (EG). Descriptive analysis using panel covariance, cross-sectional dependence (CD) test, panel unit root tests as well as panel co-integration test were adopted to test the secondary data extracted. It was observed that there is low positive but significant impact of tertiary education enrolment rate (TEER) and vocational education enrolment rate (VEER), on endogenous growth (EG) while the impact of labour force participation rate (LFPR) on endogenous growth (EG) was negative. The study recommends that government should increase not just the amount of expenditure on education and health sector but also the percentage of its total expenditure accorded these sectors. The ten percent benchmark proffered by the current national plan document as contained in National Economic Empowerment and Development Strategy (NEEDS) should be geared up and gravitate towards the UNESCO 26% international recommended standard. Keywords: Education, endogenous growth, human capital development, trade openness.
Asset liability management and performance of deposit money banks in Nigeria and Ghana
Authors:   Babcock University, Ilishan, Ogun State, Nigeria, Achori Emmanuel , Dada Samuel ,   Babcock University, Ilishan, Ogun State, Nigeria, Ogundajo Grace ,   Babcock University, Ilishan, Ogun State, Nigeria
Published: August 2023

This study examines the effect of ALM on the performance Return on Assets (ROA) and Return on Equity (ROE) of DMBs in Nigeria and Ghana. The study used ex-post facto research design. The population comprised 18 DMBs licensed in Nigeria and 22 DMBs licensed in Ghana as at 31st December 2021. Purposive sampling technique was adopted to select a sample of 10 DMBs each with relevant data from Nigeria and Ghana. Validated data were obtained from the annual reports of the banks for the period 2007-2021. The reliability of data was premised on the statutory audit and approval of the Financial Statements by the regulatory agencies in Nigeria and Ghana. Data were analyzed using descriptive and inferential statistics. The findings showed that while ALM had insignificant effect on ROA of DMBs in Nigeria (Adj.R2 = 0.297, W(3, 143) = 3.62, p > 0.05) and Ghana (Adj.R2 = 0.372, W(3, 143) = 3.13, p > 0.05), ALM with control variables exerted significant effect on ROA of DMBs in Nigeria (Adj.R2 = 0.296, W(6, 143) = 29.70, p < 0.05) and Ghana (Adj.R2 = 0.394, W(6, 143) = 33.41, p < 0.05). ALM exerted significant effect on ROE of DMBs in Nigeria (Adj.R2 = 0.327, W(3, 146) = 4.17, p < 0.05) and Ghana (Adj.R2 = 0.351, W(3, 146) = 3.68, p < 0.05). ALM with control variables had significant effect on ROE of DMBs in Nigeria (Adj.R2 = 0.293, W(6, 143) = 6.38, p < 0.05) but an insignificant effect on ROE in Ghana (Adj.R2 = 0.337, W(6, 143) = 1.94, p > 0.05).The study concludes that ALM affected performance of DMBs in Nigeria and Ghana. The study recommended that the management of DMBs in both countries should continuously adopt ALM to improve performance. Keywords: Asset liability management, Deposit money banks, Loan deposit ratio, Net interest margin, Return on assets, and Return on equity