bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive modeling for coiled tubing fatigue using advanced machine learning techniques
Authors: Brahim Khalil Moulay , Saad Aissa Abidi , Saad Elfakeur Abidi , Hadjadj Ahmed , Horra Hichem
Published: October 2024

Coiled tubing CT plays Pivotal role in oil and gas well intervention operations due to its advantages such as flexibility, fast mobilization, safe, low cost and wide range of applications, including: well intervention, cleaning, stimulation, fluid displacement, cementing, and drilling. However, CT is subject of fatigue and mechanical damage caused by repeated bending cycles, internal pressure and environmental factors which can lead to a premature failure, high operational cost and production downtime. With the development of CT proprieties and application traditional fatigue life prediction methods based on analytical models integrated in tracking process showed in some cases an underestimate or overestimate of the actual fatigue life of CT particularly when complex factor like welding type, corrosive environment, and high-pressure variation are involved. This study addresses this limitation by introducing a comprehensive machine learning-based approach to improve the accuracy of CT fatigue life prediction, using a data set derived from over 350 tests both lab scale and full-scale fatigue test. The study has incorporated the impact of different parameters such as CT, grades, wall, thickness, CT diameter, internal pressure and welding types. By using advanced machine learning techniques such as artificial network (ANN), Gradient boosting regressor we got a more precise estimation of the number of cycles to failure than traditional models. The results of this study shown the importance of integration of machine learning for CT fatigue life analysis and demonstrating its capacity to enhance the prediction accuracy and reduce the uncertainty.  A detailed machine Learning models is presented, emphasizing their capability to handle complex data and improve prediction under diverse operational conditions. This study contributes to more reliable, CT management and safer more cost-efficient well intervention operations.
Use of a multi-criteria approach to analyze the degradation of reinforced concrete beam bridges. Three case studies in the north west of Algeria
Authors: Debbal Mohammed Zakaria , Boumechra Nadir , Lallam Faiza
Published: October 2024

The main motivation for this research is to develop assessment and estimation tools for the degradation state of existing civil engineering structures. The longevity of a structure is influenced by a complex set of interconnected phenomena and parameters. Therefore, we adopt a multicriteria approach aimed at better identifying these elements, particularly the most influential ones. This study focuses on assessing the degradation of reinforced concrete beam bridges by developing a digital tool based on the Analytic Hierarchy Process (AHP). We have identified 30 factors impacting degradation, categorized as internal factors, such as the condition of structural elements, and external factors, such as age and environment. From these factors, we calculate a Global Bridge Degradation Index (GBDI) that reflects the overall condition of the bridge. This index allows us to establish a classification of the bridges, ranging from no danger to a critical state requiring immediate intervention. The innovation of our model lies in its ability to provide a quantified estimation of the degradation state while incorporating an unlimited number of factors and criteria. After applying this model to three bridges in Algeria, we observed satisfactory results. The ultimate goal is to provide managers with tools for reflection and comparison to assess the condition of bridges and consider the necessary actions for their maintenance, repair, or replacement, thereby contributing to the improvement of the management and safety of road infrastructures.
Intelligent solar light electric vehicle moving in hot regions under a hybrid power source strategy
Authors: Abderrahmani Abdesselam , Gasbaoui Brahim , Nasri Abdelfatah
Published: October 2024

Solar Light Electric Vehicles (ISLEV) have recently gained increasing attention as a promising solution for sustainable transportation. In hot regions, such as the BECHAR region in southwest Algeria, where temperatures can exceed 50 °C, the challenge of maintaining high performance standards while coping with challenging environmental conditions is critical. To address this challenge, this study proposes an intelligent hybrid power source strategy comprising SUN Power solar PV and lithium-ion battery supercapacitors. To optimize the vehicle's performance, a feedforward neural network FF-NN is employed, which regulates the power flow between the hybrid sources. The proposed system's efficiency and effectiveness are assessed through simulations, which reveal its robustness in coping with challenging environmental conditions while maintaining high performance standards. The results show that the proposed system holds con-siderable potential for sustainable and efficient transportation in hot regions and can have broad applications in diverse sectors. Future industrial vehicle designs must incorporate the choice of hybrid power management into their planning process to ensure the efficient use of energy and optimize the vehicle's performance.
Development of decision support methods for efficient maintenance of urban wastewater systems
Authors: Bedjou Abdelhamid , Mezhoud Cherifa , Berreksi Ali , Sahnoune Rachid , Benzerra Abbas , Igroufa Meriem
Published: October 2024

The sanitation network is a vital urban infrastructure that requires systematic and co-ordinated activities and practices to realize lowest life cycle cost. The sustainable management of this asset is based on the efficient acquisition of diagnostic data from the sanitation network in order to analyze the defects of each section, then to assess their condition to prioritize and consider the effective mode of maintenance of sections deemed failing. In this perspective, knowledge of the sanitation networks is essential for reliable classification of defects and effective maintenance. A numerical model based on weighted criticality is developed to evaluate and prioritize the defects in an urban sanitation network. It is based on the combination of two methods: Fuzzy Analytic Hierarchy Process (F-AHP) and Weighted Product Model (WPM). A case study of a real sanitation network in Bejaia city (Algeria), consisting mainly of non-visitable pipes evaluated from television inspections, is used to illustrate and validate the proposed model. The results show that the weighting of criticality parameters has a considerable influence on the classification of defects in a sanitation network. The weighted criticality results obtained in the present case are significantly better than those obtained using a method based on the notion of classical criticality. This clearly indicates the relevance of the proposed numerical model.
Laplacian edge detection method based on a new approximation of the second-order fractional derivative in the Caputo-Fabrizio sense
Authors: Bellabaci Safia , Dehda Bachir
Published: October 2024

Edge detection is an important issue in image processing and computer vision problems. It includes all mathematical methods that aim to identify  the discontinuous points  in the image. This process leads to construct curves that indicate the boundaries of an object and therefore extract feature information. In recent years, this task has received great attention from researchers and scientists, as we find  in the literature many methods with their different algorithms. Up to now, there are two methods, the gradient and Laplacian methods. The first depends on the first derivative,  where pixels with a high gradient are considered edges, whereas the second depends on the second derivative, such as the pixel whose second derivative is zero, it is marked as an edge point. Although these methods have achieved remarkable success, they are sensitive to noise and sometimes produce false edges. For this reason, in this paper, we propose an efficient edge detection method based on the fractional Laplacian operator in the Caputo-Fabrizio sense. In this method we develop a new approximation formula to the second-order with the Caputo-Fabrizio fractional derivative. Then, we construct a new   fractional mask to compute the Laplacian convolution. To check the effectiveness of our proposed method, we have provided some test images that are affected by a Gaussian noise. The numerical results and visual observation show that our proposed edge detection method gives better performance compared to the classical Laplacian method in terms of the peak signal to noise ratio (psnr) and fine details extraction.
High dynamic performance based by sliding mod control of quadrotor MAV
Authors: Bouchaib Ali , Taleb Rachid , Benbouali Abderrahmen , Bessaad Taieb , Saidi Hemza
Published: October 2024

The paper focuses on strong control of high dynamic performance based on the sliding mode in order to control the quadrotor MAV. The model used in the simulation is the Newton-Euler model, and also choose the Mambo Parrot quadrotor parameters, to improve the latter's performance in terms of accuracy and robustness in case the impedance control chosen by the manufacturer needs to be changed. The results of which gave effectiveness and efficiency compared to classical controls PID and sliding mode.  High dynamic performance control (HDP) is a type of control system designed to provide the highest level of performance over a wide range of operating conditions. This control is not a regulator but an organizing technique. It uses a prediction-based approach to anticipate rapid variations in system states and disturbances and to generate real-time commands to correct tracking errors and maintain system stability. This approach allows HDP control to achieve high performance while maintaining system stability, even under harsh operating conditions.
Mechanical properties of a mortar with aluminum fibers waste of drink cans
Authors: Moufida Gherdaoui , Abdelkrim Maanser , Ali Mehamdia , Fatiha Boudjedra , Wafa Djebabla
Published: October 2024

The aim of this study is to utilize drink cans as fibers to reinforce mortars production. for this purpose, we cut the cans into various sizes to investigate how the width and length of the fibers affect the mechanical properties of the mortar (2x10, 4x10 and 2x20)mm, as well as using different percentages 0,5%,1%, 1,5%, 2%, and 2,5% by the weight of the cement. The results of this study showed improvement of mechanical strength of the mortar especially the flexural strength. The comperessive strength increased by 14% compared to the control mortar, whereas the flexural strength increased by 14% and 20% compared to the control mortar of the fiber MF1 and MF2, while the addition of 2% of aluminium in  fiber MF3 incresed the flexural strength by more than 39% compered to mortar not reinforced. The addition of alimunium fiber have helped in reducing the cracking of the mortar . Consequently, incorporating aluminum fibers from drink cans into the mortar mix will significantly impact the indirect tensile strength, flexural strength, ductility, and post-cracking behavior.
Research on the Impact of Disclosure of Key Audit Matters on Corporate Financing Constraints
Authors: Fang Yihan
Published: October 2024

This paper studies the impact of key audit disclosures on corporate financing constraints through empirical analysis. Although the disclosure of key audit matters can help to reduce the information differences between management and investors and improve the audit quality, such disclosure may also be regarded as a risk signal, and the warning function to investors may cause the difficulty of corporate financing to increase. This study concludes that the increase in the number of key audit disclosures will make corporate financing more difficult. When an enterprise announces more key audit matters, the market may regard them as a stronger risk signal, causing investors to be more cautious in making investment decisions, thus increasing the financing difficulty of the enterprise. However, in companies with large board sizes, the disclosure of key audit matters can alleviate the financing constraints. Larger boards are more likely to make the right decisions and therefore may disclose fewer risky aspects of key audit matters. This study provides a new understanding of key audit issues in financing activities and a useful reference for the possible impact of macro-policy adjustments on corporate profitability. In addition, the research also provides useful information support for enterprises to understand and adapt to the new auditing standards.
Problems And Solutions of Real Estate Industry in China
Authors: Lai Junhong
Published: October 2024

Since real estate industry is one of the national pillar industries in China, therefore, it has great contributions to China’s economy and society. for example, promoting the Chinese economic growth in the long-run, and it provide financial support to government and benefits for cities development. Secondly, real estate also helping the development of relevant business, creating large amount of job opportunities to society, for residents, they can enjoy higher living standard. However, at same time of rapid development of real estate industry and economic boost, they exist series of problems that harmful to society like real estate bubble, unfinished buildings and cooperates financing difficulties. aiming at these problems, this paper suggest that government can through promulgate some new policies, laws, and establish the compete financing channel mechanism to solve these kinds of problems. The target of this study is to help real estate industry in China keep healthy development.
The Effectiveness of Asset Pricing Models Under Special Conditions: Evidence from the COVID-19 Pandemic, Emerging Markets, and Financial Crises
Authors: Liu Rui
Published: October 2024

Asset pricing models are important tools in finance. However, special market conditions can make them highly ineffective. This paper evaluates the performance of classical asset pricing models (that is, CAPM and Fama-French models) under three specific scenarios: the COVID-19 pandemic, emerging markets, and financial crises. Recent research and market data are reviewed to conclude that these models have very low efficiency in times of extreme occurrences for capturing proper asset valuations. Our findings reveal that standard models lose a substantial part of their explanatory power in periods of crises while new context-specific risk factors come into existence in other exceptional conditions. This work argues for the inclusion of liquidity and tail risk considerations, especially during market stress, as we also observe a greater need for more dynamic and adaptive modeling approaches that capture time-varying risk premia and factor loadings. The findings drive home the point that standard asset pricing models cannot be applied across the board in all market conditions and stress the need for developing more flexible and situation-specific valuation tools. Therefore, this research lies in its dual contribution, both in academic terms and practical finance, by providing an understanding of the behavior of asset pricing models in extreme markets and giving indications for future model development.
Officials' Social Networks and Local Indebtedness - A Study Based on Provincial Data
Authors: Lyu Yinming
Published: October 2024

This paper takes the average annual growth of indebtedness of provincial party secretaries and the places where they serve from 2006 to 2017, and aims to investigate whether the social network of officials significantly affects the indebtedness of places. This paper adopts the linear regression method and establishes a unique evaluation system of officials' social networks. It is finally found that officials' social networks have a significant impact on the indebtedness of local governments. At the same time, the provincial officials' tenure, during which the growth of the indebtedness of other provincial governments also significantly affects the indebtedness of that provincial government.
Research Progress of Three-dimensional Geological Modeling and Multi-field Coupling of Fractured Oil and Gas Reservoirs
Authors: Han Zhaoxu , Jin Xinru , Li Wenzhi , Fu Zhengxing
Published: October 2024

Fractured oil and gas reservoirs play an important role in oil and gas exploration and development due to their complex fracture network structure. As the main fluid channel in the reservoir, fractures have a significant impact on the migration, accumulation and exploitation efficiency of oil and gas. This paper summarizes the key geological characteristics of fractured reservoirs, including fracture types, distribution rules and main controlling factors of fracture development, and discusses the influence of fractures on reservoir physical properties. Furthermore, the deterministic and stochastic modeling methods of three-dimensional geological modeling of fractured reservoirs and the latest progress of discrete fracture network modeling technology are introduced in detail. In addition, this paper also discusses in detail the application of multi-field coupling model in the numerical simulation of fluid flow in fractured reservoirs, including continuous medium model and discrete medium model, and their advantages and disadvantages in simulating fluid flow in fractured reservoirs. Finally, this paper summarizes the research progress of multi-physics coupling model of fractured reservoirs, and points out the direction and challenges of future research. Through these studies, it can provide theoretical support and technical guidance for oil and gas exploration and development, in order to achieve more effective development and management of fractured reservoirs.
Exploring The Celebrity Effect on Live-Streaming E-Commerce: A Comprehensive SWOT Analysis of Influencer Marketing Strategies
Authors: Fang Ziyue
Published: October 2024

In recent years, with the rapid development of the Internet and mobile technology, the landscape of business and marketing has changed dramatically, and particularly notable is the rise of live-streaming e-commerce. This new e-commerce model combines e-commerce with live video streaming to enhance the shopping experience through product display, promotion and sales by anchors. In this model, the celebrity effect, which takes advantage of celebrities' large fan bases and strong influence, plays an important role in driving consumer behaviour. This paper explores the impact of the celebrity effect on live-streaming e-commerce and analyses its strengths, weaknesses, opportunities and threats through SWOT analysis with typical case studies in China. The findings highlight the key role of celebrity endorsement in increasing consumer engagement and purchase intention, while also exploring the potential risks and challenges. The paper concludes with suggestions for optimisation and development to maximise the role of the celebrity effects in live-streaming e-commerce.
Analysis of the Laws of Planar Composition in Interior Design
Authors: Jiang Daowei
Published: October 2024

The purpose of this paper is to discuss the laws of planar composition in interior design, analyze the role and use of basic elements such as points, lines and surfaces in interior design, as well as the analysis of the laws of composition such as contrast and symmetry, proportion and balance, rhythm and repetition. Firstly, the thesis introduces the importance of points, lines and surfaces as constituent elements in interior design, and discusses their influence on spatial atmosphere, visual effect and overall sense. Secondly, through the analysis of the compositional laws of contrast and symmetry, proportion and balance, rhythm and repetition, the paper elaborates on the principles and effects of the application of these laws in interior design. Then, the thesis discusses the application of planar composition in different styles, including modern minimalist style, European classical style, Chinese traditional style, etc., showing the characteristics and design techniques of planar composition in different styles. Finally, the paper discusses the optimal use of interior space from the perspective of plane composition, emphasizing the importance of the unity of functionality and aesthetics, spatial layout and flow design, and the collocation of materials and colors. Through in-depth analysis of the laws of plane composition in interior design, this paper aims to provide designers with certain theoretical guidance and practical reference, with a view to achieving better design effects and space utilization.
Research on the Impact of Enterprise Digital Transformation on High-Quality Development and Countermeasures
Authors: Dong Haoran
Published: October 2024

With the rapid development of the digital economy, enterprises face the important task of digital transformation. This paper, based on the analysis of literature, discusses the positive impacts of digital transformation on the high-quality development of enterprises, reveals the main mechanisms of digital transformation, and proposes corresponding countermeasures for the challenges encountered by enterprises during the digital transformation process. The study finds that digital transformation can optimize the talent structure of enterprises, improve organizational governance, nurture new market environments, and thereby promote the high-quality development of enterprises. This paper suggests that enterprises should strengthen the training of digital talents, optimize organizational structures, and innovate business models using digital technologies to adapt to the needs of the digital age.
Combat Effectiveness Evaluation of UAV Intelligent Swarm Based on AHP-Fuzzy Comprehensive Evaluation
Authors: Li Yuan
Published: October 2024

In order to evaluate the combat effectiveness of UAV intelligent swarm, this paper puts forward the establishment of UAV intelligent swarm combat effectiveness evaluation index system based on availability, credibility and combat ability, analyzes the factors affecting the combat effectiveness of UAV intelligent swarm, establishes the effectiveness evaluation model, determines the weight of each factor by AHP, and evaluates the effectiveness index by fuzzy evaluation matrix. Using this method to evaluate the combat effectiveness of UAV intelligent swarm, the evaluation result is objective and reasonable, which provides theoretical reference for the optimal design and use of UAV intelligent swarm system.
Does the Imbalance of ESG Activities Affect Company Performance? -- Evidence from Chinese A-share Listed Companies from 2018-2022
Authors: Wang Yujie , Liang Yuyan , Zhang Kaichao
Published: October 2024

In recent years, the concept of sustainable development has progressively gained traction among the populace, with the performance of enterprises in environmental, social, and corporate governance (ESG) aspects attracting widespread attention from various sectors of society. The weighting of E, S, and G components varies across domestic and international ESG rating agencies, often resulting in significantly divergent weighted ESG scores. Leveraging the theory of organizational ambidexterity, this paper empirically investigates the impact of discrepancies between institutional ESG scores and equally weighted ESG scores on company performance, utilizing a sample of Chinese A-share listed companies spanning the years 2018 to 2022. Our findings reveal that equally weighted ESG scores exhibit a correlation with company performance, and a higher positive percentage difference between a company's rating agency ESG scores and its equally weighted ESG scores is associated with lower performance. This suggests that the rating agency weighting method may inadvertently encourage companies to engage in "greenwashing." This conclusion remains consistent after conducting robustness tests. Heterogeneity analysis further indicates that the negative impact of this difference on company performance is more pronounced among non-state-owned companies, manufacturing companies, and small companies. The mechanism of action test reveals that this difference negatively affects company performance by exacerbating financing constraints and reducing operating efficiency.
Research on Ancient Academy Inscriptions and Documents in Zhejiang Province
Authors: Zhou Jia , Sun Jiaying
Published: October 2024

This paper takes the inscriptions on ancient academies in Zhejiang as the main research object, tracing the cultural lineage of ancient academy culture from the inscriptions and creating a new pattern for the development of academy culture in Zhejiang. At the same time, the author examined ancient academy inscriptions around Zhejiang, delved into the collection, organization, and protection status of academy inscriptions, rescued abandoned inscriptions in the wilderness, and created a database and distribution map of inscriptions using new media technology, laying a solid foundation for the protection and development of academy inscriptions in the future.
Analysis Of Current Situation, Risk Causes and Countermeasures of Real Estate Finance--Taking Jiangsu Province as An Example
Authors: Tong Tong
Published: October 2024

The real estate industry is not only an important engine of economic growth, but also a cornerstone of social stability and personal life. As a major economic province in China, Jiangsu Province is rich in natural resources and has a strong economic base. It is an important demonstration area for China's modernization and comprehensive development and plays an important role in promoting China's economic growth, scientific and technological innovation and social progress. In the economic structure of Jiangsu Province, the real estate market occupies a pivotal position, which not only contributes greatly to the local financial income, but also has a far-reaching impact on employment, consumption, investment and other aspects. The development of the real estate market in Jiangsu Province has an important impact on the national real estate market, thus this paper takes Jiangsu Province as the research object, discusses the credit risk of the real estate industry in Jiangsu Province from the perspectives of its status quo, risk causes, etc., and then puts forward policy recommendations to promote the sustainable development of the real estate market in Jiangsu Province.
Exploration of the Upgrading Path of China's Gas Meter Industry in the Digital Economy Era
Authors: Liu Qinghua , Huang Jie
Published: October 2024

Gas supply is a fundamental public good that affects millions of households. The online hot search event in April 2024 regarding the "fast running" of gas meters in multiple cities such as Chongqing and Chengdu indicates that there is still a long way to go in improving the quality and upgrading of the gas service industry and gas meter manufacturing industry. Based on the background of the digital economy era, this paper analyzes the role of gas meter manufacturers in the multilateral market of the smart gas management platform and the role of the gas meter industry value chain, explores the basic path and countermeasures for the upgrading of the gas meter industry, with a view to providing valuable reference for the digital transformation of the traditional gas meter industry in the industrial Internet era.
The Impact of Intelligent Transportation Technology on The Operational Efficiency of Public Transportation Enterprises
Authors: Zhai Yachao
Published: October 2024

With the acceleration of urbanization, the public transport system is facing increasingly severe challenges. How to improve the operational efficiency of public transport enterprises has become an urgent problem to be solved. Intelligent transportation technology, with its advanced information technology means, provides a new solution for the operation management of public transportation enterprises. The purpose of this study is to explore the impact of intelligent transportation technology on the operational efficiency of public transportation enterprises. Through the field investigation and data analysis of a number of public transportation enterprises, the application of intelligent transportation technology in bus scheduling, vehicle tracking, passenger information service and other aspects is studied. The results show that the application of intelligent transportation technology significantly improves the operating efficiency of public transportation enterprises, which is reflected in shortening the driving time, reducing the empty driving distance, and improving passenger satisfaction. In addition, the study also found that smart transportation technology can help reduce operating costs and reduce environmental pollution. Future research will further explore the application of smart transportation technology in a wider range, and put forward corresponding policy recommendations, with a view to providing technical support for the sustainable development of public transportation enterprises.
Research on the Evaluation of Competitiveness of Steel Industry Enterprises
Authors: Guo Xiaoqing , Huang Huan
Published: October 2024

The steel industry, as a fundamental industry in the organic development framework of China's economy, has been facing the long-standing problems of production exceeding consumption, high asset liability ratio, severe product homogenization competition, and high pollution and carbon emissions in the production process in recent times. At the same time, due to the impact of the sluggish demand caused by the COVID-19, the rapid rise in the cost of raw materials such as iron ore, and the gradual disappearance of a series of policy dividends such as supply side reform, the financial situation of steel enterprises is becoming more and more pessimistic. How to cope with the increasing financial risks and gain competitive advantages through strengthening financial competitiveness in the fierce market competition has become a major issue that China's steel enterprises urgently need to solve. This article selects steel industry enterprises as the research object for analysis. By reviewing relevant literature on enterprise competitiveness, the relevant concepts of enterprise competitiveness are extracted, and the research results and evaluation system are organized. Based on factor analysis, 16 targeted indicators are selected based on scale, efficiency, growth, operational capacity, debt paying capacity, and research and development capacity. An analysis model is constructed and analysis conclusions are drawn. In the analysis results, problems are identified regarding the poor competitiveness of steel industry enterprises. The following research results were obtained: 1) The overall competitiveness score of enterprises in the industry is not high, all less than 1. Among them, operational capability has the greatest impact on the competitiveness of steel industry enterprises, followed by scale, debt paying ability, efficiency, research and development ability, and growth. 2) The worst scoring indicators among the six enterprise competitiveness indicators are the scale indicator and the growth indicator. There is a significant gap in industry scale, with 12 companies scoring positive in the scale factor, accounting for 34.29% of the industry; The scale factor score of 23 enterprises is negative, with an industry proportion of 65.71%. In addition, there are growth indicators, with 12 companies in the industry having positive growth factor scores and 23 companies having negative growth factor scores, indicating a significant head effect on overall growth capacity.
Neologismi per la prevenzione neurale. Parole nuove per nuovi diritti? Attestazioni nei giornali e in rete
Authors: Mondani Paola
Published: October 2024

Nel contributo si dà conto dell’origine e della diffusione in contesti divulgativi delle espressioni che denotano i nuovi diritti della sfera neurale (la parola neurodiritti e le polirematiche continuità psicologica, integrità mentale, libertà cognitiva, potenziamento neurale, pregiudizio algoritmico e privacy mentale) e se ne offre una definizione lessicografica. L’analisi linguistica è svolta secondo i metodi e con gli strumenti della lessicografia neologica.
INTERRELATION OF YIELD AND ITS COMPONENTS IN COTTON (Gossypium hirsutum L.) GENOTYPES
Authors: SAJID MA , JATOI WA , KALERI AA , MANZOOR D , ULLAH N , AFZAL A , SHAHZADI I , AHMED M , AHMED F , ASGHAR S
Published: October 2024

Cotton is regarded as a profitable crop that gives people fiber and shelter. Research focuses on how yield, its components, and related attributes work together to enhance cotton. During the Kharif season of 2022, the present study was completed, implementing a randomized complete block design with ten genotypes and three replications. The study took place at the Nuclear Institute of Agriculture (NIA), located in Tandojam. This work aimed to examine the correlation and regression between upland cotton genotypes and heritability estimates for traits associated with yield. The outcomes showed that all of the parameters in the mean square of the ANOVA were significant. In contrast to the remaining genotypes, genotype FH-142 displayed the most favorable performance; it had the tallest plants, more sympodial branches, more bolls per plant, an improved seed index, and the longest staple length. The genotype CRIS-342 came in second, exhibiting good plant height, sympodial branches, a good number of bolls per plant, a ginning outturn, and the highest boll weight among the other genotypes. The findings of the correlation and regression indicated that the number of bolls per plant-1 had a highly significant and positive relationship with monopodial branches plant-1 (r = 0.73*) and (b = 2.45) and that the number of bolls per plant had a strong relationship with seed cotton yield plant-1 (r = 0.83**) and (b = 3.29). Staple length and seed cotton yield plant-1 had a negative correlation (-0.77*) with regression (b = -4.58). The highest heritability estimates in the broad sense are for monopodial branch plants (84.61), ginning outturn% (97.03), bolls plant-1 (93.96), plant height (90.70), staple length (79.31), and seed index (71.42). However, the boll's weight showed a low heritability (23.71). Further breeding programs can utilize genotype FH-142 to increase the number of sympodial branches, increase the number of boll plants, and improve the staple length. Genotype CRIS-342 can be utilized for medium-stature plant height, boll weight, and better ginning outturn. However, genotype NIA-BT-40 can be utilized for short-strategy plants with the highest ginning output.
Emerging Research Topics in Social Learning
Authors: Klamma Ralf
Published: October 2024

Despite the fact, that an uncountable crowd of technology affine learners has entered the Internet with fast connections lines, little support exists for scalable learning support technologies. In this paper, we explore research topics which address the new needs of long tail learning and technologies which may help to overcome the current situation. Especially, we investigated the concepts of connectivism. Key theorists state that (a) learning is a process of connecting entities, (b) nurturing and maintaining connections is needed to continual learning, (c) learners need the ability to see connections between fields, ideas, and concepts, (d) the capacity to know more is more critical than what is currently known, and (e) decision-making is itself a learning process. Drawing on these concepts, we have combined social network analysis (SNA), visualization and recommendation technologies supporting social navigation, positioning and reflection in learning networks. We demonstrate first results from recent research in case studies. In the PROLEARN Academy we studied the co-authorship relations of PhD students having attended the summer schools and found some impact. In the eTwinning database we applied SNA on a large dataset about collaboration among European schools and demonstrated the need for gaining competences in reading network data. In a digital database we identified research communities based on co-authorship relations and recommended events for young scientists. Longitudinal SNA studies with small but self-created network datasets help to facilitate the understanding of dynamic aspects of learning networks on a very coarse level. However, creating and maintaining network datasets in extremely expensive and needs financial support, e .g. from a network of excellence. Analyzing existing datasets from digital libraries or learning networks can be done very effectively and efficiently by experts using a handful of good analysis and visualization tools. However, when non-experts and stakeholders (like school teachers for example) need support, we have to design special environments for doing so. If not only understanding of historical data is aimed at but also forecasting future behaviour of learning networks some general laws about complex networks can be applied. Still, if the domain knowledge can be modeled into game theoretic payoff functions, multi agent simulation is a way to predict at least trends in the future. In the future we will add game theoretic multi agent simulation. So, there is a big need for supporting the learners in their communities and domains and not only expert data analysts.
Design for Learning in a Social Network
Authors: Levinsen Karin , Nielsen Janni
Published: October 2024

The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of tension between time resources and the demand for educational quality. Our approach is based on constructivist and social constructivist traditions but we are required to measure students according to a list of learning goals. The size of curriculum is growing while the time available for learning is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students´ acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3) The Operationalization that direct the students' performance in practice when the design model is applied. Moving from conceptual modelling and orchestration to operationalization is a move from the generic theoretical modelling into a specific description of an application of the model in a specific context. The context for the experiment is MIL´s course on Interaction Design. The orchestration is operationalized as a 4-hour script that builds on classic role-play designed as an open ended explorative task. The script of the teams' tasks is designed to facilitate the teams' ongoing negotiation and structuring of their collaboration and students are required to document their choices, deselections, decisions and arguments and reflect on their learning process during the role-play. In the final paragraph we discuss our experimental work with the Design for Learning Model. We argue that our model gives birth to scaffolding which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning.
Where does the learning take place?
Authors: Peters Sue
Published: October 2024

This paper presents the concept of learning spaces to demonstrate where and how learning takes place within a networked learning programme. The focus of the study is a ten month leadership and development programme, called LEAD, for owner managers of small to medium sized enterprise (SMEs). The programme incorporates different types of learning interventions including experiential sessions, masterclasses, coaching, action learning and business shadowing and exchanges which are brought together with an online virtual learning environment. The paper draws upon data from an ethnographic study including a virtual ethnography of one cohort of 25 delegates on LEAD. The data is supported by interviews and observations from six previous cohorts.
LEAD is based on a social theory of learning and the SMEs learn about management and leadership predominantly through peer-to-peer learning. The paper conceptualises five learning spaces; (1) LEAD, (2) reflective, (3) social, (4) peer-to-peer and (5) future. These spaces are relational and the paper explores what they mean in terms of the SMEs’ learning. Drawing on situated learning theory the paper shows how participants engage in these spaces through Lave and Wenger’s (1991) reading of legitimate peripheral participation . Building on this the concept of the situated curriculum (Gherardi et al., 1998) is used to show how the delegates learn to ‘behave’ in these spaces and how their identity shifts according to which learning space they occupy. Finally, building on Ponti and Hodgson’s (2006) networked learning principles for SME managers the paper will present some learning principles for designing networked learning programmes for SMEs. This paper will be of interest to academics and practitioners alike who have an interest in learning technologies, SMEs and debates surrounding communities of practice. Additionally the paper has relevance to government policy in the area of higher education and knowledge transfer through networked learning and SMEs.
Coalition Formation in Networked Innovation
Authors: Sie Rory L. L. , Bitter-Rijpkema Marlies , Sloep Peter B.
Published: October 2024

During the last several decades, we see a tendency towards openly distributed knowledge. Whereas we experienced an open source movement in the 80's, we now see that open learning and open innovation have become popular. Akin to open source code encouraging transformational creativity (Boden, 2004), open or networked innovation may lead to more effective organisational learning (Sloep, 2009a). This process of open knowledge exchange involves short time commitments, similar to those in Ad-Hoc Transient Communities (AHTC). We would like to pose a new view on the interpersonal ties in networked innovation, that is, the view of interpersonal ties as coalitions.Networked innovation occurs on three levels: the micro level, the meso level, and the macro level. Micro level coalitions are formed on the personal level. Meso level coalitions are formed by units of people within organisations. Organisations form coalitions or alliances with other parties on the macro level of networked innovation. Each of these levels has their own problems that hinder the process of networked innovation. Examples are self-interest (micro), negative ties between units (meso) and so-called logrolling. People need to be informed of the value of their candidate coalitions so as to develop intrinsic motivation for co-operation.We propose the view of interpersonal ties within networked innovation as coalitions. We compare characteristics of Granovetter’s characteristics of interpersonal ties (Granovetter, 1973)with the characteristics that were identified by Begley et al. (2008)to underscore this view. Afterwards, we propose an initial model of the antecedents of coalitions. These antecedents were described earlier by Brass et al. (2004)and we suggest an extension of this list of antecedents. Besides, we provide an initial model that visualises the relations between the antecedents and coalitions. As this is part of ongoing research, we provide a methodology for further investigation of the process of coalition formation within networked innovation. This includes an extensive literature review, model development, simulation and verification through an online experiment. This will hopefully answer our questions on how coalitions are formed within networked innovation, what the structure of these coalitions is, how they are sustained and how the payoff is divided.
Dialogue design - transformation of identity and local practice
Authors: Wentzer Helle , Dirckinck-Holmfeld Lone , Coto Mayela
Published: October 2024

This paper reflects the experiences with Dialogue Design for cross-cultural collaboration and product development in relation to local transformation of practice(s). The paper presents a methodology for transnational learning using Dialogue design on deliberate ideals and continuously evaluation as principle for guiding the process. Dialogue design is based on experiential phenomenology taking the point of departure for design and evaluation processes in the experienced practitioners themselves. The methodology has been developed in relation to the research and development project Making Online Path to Enter new Markets- MOPEM. It is an EU-research project with partners from different Educational Institutions of Technology and Business in five European Countries. The results of this transnational project suggest that in the development of net-worked learning environments, infrastructure cannot be reduced to technical solutions, as the cultural aspects of the educational infrastructure, teaching traditions and student expectation also play their role.
Symposium 6: Problem-oriented project studies – the role of the teacher as supervising / facilitating the study group in its learning processes
Authors: Danielsen Oluf , Nielsen Jørgen Lerche
Published: October 2024

This contribution focuses on 'problem based learning' (however we prefer the notion of ‘problem-oriented project studies’) and the role of the teacher in such a context. The classic traditional role as an expert deciding the curriculum, providing lectures and seminars, giving assignments and marking papers / essays is complemented and in some way overruled by a new role as supervisor and facilitator for the group of students working with a research problem, they themselves have picked. However different dimensions of this new teacher role can be seen – from expert in an academic field (result-oriented focusing on how the final product demonstrates the students’ ‘correct’ way to handle the academic aspects of the subject in mind) to a role more focusing on processes, methodological dimensions and stressing the importance of a reflexive approach. Some teachers may even tend to take on a role of a ‘therapist’, questioning and assisting the members of the group in the complex task of acting together with fellow students in an uncertain and volatile context and environment.