{"title":"Retracted: Analysis of Brand Communication Influence of Professional Sports Clubs Based on Complex System Discrete Model","authors":"Discrete Dynamics in Nature and Society","doi":"10.1155/2023/9820215","DOIUrl":"https://doi.org/10.1155/2023/9820215","url":null,"abstract":"<jats:p />","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"100 8","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138954227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Retracted: Design of Higher Education System Based on Artificial Intelligence Technology","authors":"Discrete Dynamics in Nature and Society","doi":"10.1155/2023/9786404","DOIUrl":"https://doi.org/10.1155/2023/9786404","url":null,"abstract":"<jats:p />","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"119 12","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138958338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Retracted: Analysis of Psychological and Emotional Tendency Based on Brain Functional Imaging and Deep Learning","authors":"Discrete Dynamics in Nature and Society","doi":"10.1155/2023/9813021","DOIUrl":"https://doi.org/10.1155/2023/9813021","url":null,"abstract":"<jats:p />","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"55 25","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138957111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Retracted: Measurement of Coordination Degree between Economy and Logistics in Hebei Province, China, Based on Fractional Grey Model (1, 1)","authors":"Discrete Dynamics in Nature and Society","doi":"10.1155/2023/9847538","DOIUrl":"https://doi.org/10.1155/2023/9847538","url":null,"abstract":"<jats:p />","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"117 9","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138958476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes an improved whale optimization algorithm with chaotic mapping and adaptive iteration strategy (CMAIS-WOA). This algorithm addresses the issues of the WOA algorithm that is prone to local optimal solutions with low stability. CMAIS-WOA utilizes chaotic mapping to enhance the diversity and coverage of the initial population. Also, it adaptively adjusts the weight values based on the current distribution of whale populations and the fitness of search agents. In addition, CMAIS-WOA uses an improved nonlinear convergence factor to adjust the breadth-first and depth-first search during the optimization process. The performance of the proposed CMAIS-WOA is evaluated by using 13 classical benchmark functions and IEEE CEC2014 test suite. The experimental results show that CMAIS-WOA effectively improves the stability of the optimal solution and helps the algorithm to approach the global optimal solution. The method proposed in this paper contributes to the field of optimization which solves problems more powerfully and efficiently.
{"title":"CMAIS-WOA: An Improved WOA with Chaotic Mapping and Adaptive Iterative Strategy","authors":"Chao-Hsien Hsieh, Qing Zhang, Ya Xu, Ziyi Wang","doi":"10.1155/2023/8160121","DOIUrl":"https://doi.org/10.1155/2023/8160121","url":null,"abstract":"This paper proposes an improved whale optimization algorithm with chaotic mapping and adaptive iteration strategy (CMAIS-WOA). This algorithm addresses the issues of the WOA algorithm that is prone to local optimal solutions with low stability. CMAIS-WOA utilizes chaotic mapping to enhance the diversity and coverage of the initial population. Also, it adaptively adjusts the weight values based on the current distribution of whale populations and the fitness of search agents. In addition, CMAIS-WOA uses an improved nonlinear convergence factor to adjust the breadth-first and depth-first search during the optimization process. The performance of the proposed CMAIS-WOA is evaluated by using 13 classical benchmark functions and IEEE CEC2014 test suite. The experimental results show that CMAIS-WOA effectively improves the stability of the optimal solution and helps the algorithm to approach the global optimal solution. The method proposed in this paper contributes to the field of optimization which solves problems more powerfully and efficiently.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"67 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138743154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The global supply chain has been severely impacted with the outbreak of COVID-19. The continuous supply of essential products in the post-COVID-19 world is a truly effective and strategic contest. The security and useability of inventory management are a main burden for industries along with the pressure from the government to fulfil the targets of net-zero economy in an uncertain circumstance. One of the most potential keys to these issues is an accurate demand forecasting process by blockchain technology. This article addresses a basic outline for blockchain-based supply chain (SC) and reveals how blockchain technology (BCT) can aid policymakers to cut carbon footprint during and postpandemic time in a fuzzy environment. This study fuzzifies all the carbon factors as intuitionistic triangular fuzzy numbers and uses a signed distance method to defuzzify the model. We consider that the retailer can embrace BCT to enhance demand forecasting. The planned scenario is modeled as an optimization problem to maximize the profit with low carbon emissions and suggest a solution method to solve it. A numerical example is also given to validate the model. We compare the optimal decisions of the SC with and without BCT. We discover that the pandemic and BCT have considerable influences on the optimal results. The study also shows that practitioners should exercise caution when developing operational strategies for maximizing profit with the least amount of carbon emissions during and postpandemic time.
{"title":"Blockchain-Based Inventory System considering Uncertain Carbon Footprints and Pandemic Effects","authors":"P. Mala, M. Palanivel, S. Priyan","doi":"10.1155/2023/4403361","DOIUrl":"https://doi.org/10.1155/2023/4403361","url":null,"abstract":"The global supply chain has been severely impacted with the outbreak of COVID-19. The continuous supply of essential products in the post-COVID-19 world is a truly effective and strategic contest. The security and useability of inventory management are a main burden for industries along with the pressure from the government to fulfil the targets of net-zero economy in an uncertain circumstance. One of the most potential keys to these issues is an accurate demand forecasting process by blockchain technology. This article addresses a basic outline for blockchain-based supply chain (SC) and reveals how blockchain technology (BCT) can aid policymakers to cut carbon footprint during and postpandemic time in a fuzzy environment. This study fuzzifies all the carbon factors as intuitionistic triangular fuzzy numbers and uses a signed distance method to defuzzify the model. We consider that the retailer can embrace BCT to enhance demand forecasting. The planned scenario is modeled as an optimization problem to maximize the profit with low carbon emissions and suggest a solution method to solve it. A numerical example is also given to validate the model. We compare the optimal decisions of the SC with and without BCT. We discover that the pandemic and BCT have considerable influences on the optimal results. The study also shows that practitioners should exercise caution when developing operational strategies for maximizing profit with the least amount of carbon emissions during and postpandemic time.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"116 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138716153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Badr Saleh Al-Abdi, Abdallah M. M. Badr, Faisal A. M. Ali, Tawfik M. A. Jabbar, Fahmy Al–Salwi
Over the past decades, Saudi Arabia’s economic development has strongly depended on oil revenues fueled by the rise of oil prices and the strong global market demands for crude oils. However, the country can no longer depend on oil revenues in the face of the dynamic global market, and hence, the Saudi government’s Vision 2030 seeks to reduce this dependence and diversify the economy’s sources of income. Motivated by this, this study aims to investigate the impact of growth factors: financial innovation (FI), nonoil trade openness (TO), nonoil gross capital formation (GCF), and human capital (CH) development on the nonoil economic growth in Saudi Arabia. The goal of this investigation is to examine the dynamic symmetrical and nonsymmetrical impact of these growth factors on nonoil economic growth and policymaking in Saudi Arabia. To achieve this, this study utilizes the distributed lag symmetric and asymmetric (ARDL and NARD) approaches to assess the short- and long-term symmetric relationships among these growth variables with nonoil economic growth as well as the stationarity, cointegration, and directionality among variables with the theory of “ceteris paribus” in the error correction model (ECM), and Granger causality framework to analyze time-series data from 1980 to 2020. The findings of this study revealed that the FI, TO, GCF, and CH have an impact on the nonoil economic growth in the short and long terms. Additionally, in the long term, the NARDL technique showed that the positive adjustments of HC, FI, TO, and GCF boost the development, which have very significant effects on the nonoil GDP. They also indicate that negative movements have more influence than positive movements in FI. Meanwhile, mixed directional causation results were observed in the short-run analyses. Overall, the findings of this study provide significant insights, empirical recommendations, and implications for policymakers striving to achieve sustainable nonoil trade economic growth in Saudi Arabia and the region.
{"title":"Investigating Interaction Dynamics among Nonoil Economic Growth and Its Most Important Determinants: Evidence from Saudi Arabia","authors":"Badr Saleh Al-Abdi, Abdallah M. M. Badr, Faisal A. M. Ali, Tawfik M. A. Jabbar, Fahmy Al–Salwi","doi":"10.1155/2023/6692446","DOIUrl":"https://doi.org/10.1155/2023/6692446","url":null,"abstract":"Over the past decades, Saudi Arabia’s economic development has strongly depended on oil revenues fueled by the rise of oil prices and the strong global market demands for crude oils. However, the country can no longer depend on oil revenues in the face of the dynamic global market, and hence, the Saudi government’s Vision 2030 seeks to reduce this dependence and diversify the economy’s sources of income. Motivated by this, this study aims to investigate the impact of growth factors: financial innovation (FI), nonoil trade openness (TO), nonoil gross capital formation (GCF), and human capital (CH) development on the nonoil economic growth in Saudi Arabia. The goal of this investigation is to examine the dynamic symmetrical and nonsymmetrical impact of these growth factors on nonoil economic growth and policymaking in Saudi Arabia. To achieve this, this study utilizes the distributed lag symmetric and asymmetric (ARDL and NARD) approaches to assess the short- and long-term symmetric relationships among these growth variables with nonoil economic growth as well as the stationarity, cointegration, and directionality among variables with the theory of “ceteris paribus” in the error correction model (ECM), and Granger causality framework to analyze time-series data from 1980 to 2020. The findings of this study revealed that the FI, TO, GCF, and CH have an impact on the nonoil economic growth in the short and long terms. Additionally, in the long term, the NARDL technique showed that the positive adjustments of HC, FI, TO, and GCF boost the development, which have very significant effects on the nonoil GDP. They also indicate that negative movements have more influence than positive movements in FI. Meanwhile, mixed directional causation results were observed in the short-run analyses. Overall, the findings of this study provide significant insights, empirical recommendations, and implications for policymakers striving to achieve sustainable nonoil trade economic growth in Saudi Arabia and the region.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"13 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138682356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Under the background of the rapid development of digital economy, this paper empirically analyzes the impact of digital transformation on enterprise innovation and selects the panel data of China’s Shanghai and Shenzhen A-share listed companies from 2013 to 2021 as the research objective is to study the impact of digital transformation on enterprise innovation from theoretical and empirical perspectives. First, we find that digital transformation accelerates enterprise innovation, a conclusion that has been validated through robustness testing. Second, digital transformation impacts enterprise innovation by enhancing productivity and information transparency. Third, financing constraints and financial redundancy play distinct regulatory roles in the process. Fourth, heterogeneity analysis finds that the role of digital transformation in promoting enterprise innovation has different effects in state-owned and non-state-owned enterprises, high-tech and non-high-tech enterprises, and enterprises with different life cycles. Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. Overall, this study contributes to a deeper understanding of digital transformation and innovation-driven practices and encourages more significant integration of the real and digital economies.
{"title":"Impact of Digital Transformation on Accelerating Enterprise Innovation—Evidence from the Data of Chinese Listed Companies","authors":"Jiqiong Liu, Chunyan Liu, Shuai Feng","doi":"10.1155/2023/2727652","DOIUrl":"https://doi.org/10.1155/2023/2727652","url":null,"abstract":"Under the background of the rapid development of digital economy, this paper empirically analyzes the impact of digital transformation on enterprise innovation and selects the panel data of China’s Shanghai and Shenzhen A-share listed companies from 2013 to 2021 as the research objective is to study the impact of digital transformation on enterprise innovation from theoretical and empirical perspectives. First, we find that digital transformation accelerates enterprise innovation, a conclusion that has been validated through robustness testing. Second, digital transformation impacts enterprise innovation by enhancing productivity and information transparency. Third, financing constraints and financial redundancy play distinct regulatory roles in the process. Fourth, heterogeneity analysis finds that the role of digital transformation in promoting enterprise innovation has different effects in state-owned and non-state-owned enterprises, high-tech and non-high-tech enterprises, and enterprises with different life cycles. Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. Overall, this study contributes to a deeper understanding of digital transformation and innovation-driven practices and encourages more significant integration of the real and digital economies.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"12 7","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138997744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Near-infrared spectrum technology is extensively employed in assessing the quality of tobacco blending modules, which serve as the fundamental units of cigarette production. This technology provides valuable technical support for the scientific evaluation of these modules. In this study, we selected near-infrared spectral data from 238 tobacco blending module samples collected between 2017 and 2019. Combining the power of XGBoost and deep learning, we constructed a flavor prediction model based on feature variables. The XGBoost model was utilized to extract essential information from the high-dimensional near-infrared spectra, while a convolutional neural network with an attention mechanism was employed to predict the flavor type of the modules. The experimental results demonstrate that our model exhibits excellent learning and prediction capabilities, achieving an impressive 95.54% accuracy in flavor category recognition. Therefore, the proposed method of predicting flavor types based on near-infrared spectral features plays a valuable role in facilitating rapid positioning, scientific evaluation, and cigarette formulation design for tobacco blending modules, thereby assisting decision-making processes in the tobacco industry.
{"title":"Evaluation of Flavor Type of Tobacco Blending Module: A Prediction Model Based on Near-Infrared Spectrum","authors":"Lin Wang, Yuhan Guan, Yaohua Zhang","doi":"10.1155/2023/6618009","DOIUrl":"https://doi.org/10.1155/2023/6618009","url":null,"abstract":"Near-infrared spectrum technology is extensively employed in assessing the quality of tobacco blending modules, which serve as the fundamental units of cigarette production. This technology provides valuable technical support for the scientific evaluation of these modules. In this study, we selected near-infrared spectral data from 238 tobacco blending module samples collected between 2017 and 2019. Combining the power of XGBoost and deep learning, we constructed a flavor prediction model based on feature variables. The XGBoost model was utilized to extract essential information from the high-dimensional near-infrared spectra, while a convolutional neural network with an attention mechanism was employed to predict the flavor type of the modules. The experimental results demonstrate that our model exhibits excellent learning and prediction capabilities, achieving an impressive 95.54% accuracy in flavor category recognition. Therefore, the proposed method of predicting flavor types based on near-infrared spectral features plays a valuable role in facilitating rapid positioning, scientific evaluation, and cigarette formulation design for tobacco blending modules, thereby assisting decision-making processes in the tobacco industry.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"18 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138627798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A topological index is a real number derived from the structure of a chemical graph. It helps determine the physicochemical and biological properties of a wide range of drugs, and it better reflects the theoretical properties of organic compounds. This is accomplished using degree-based topological indices. We examined some of the physiochemical characteristics of thirteen HIV therapy medications and created a QSPR model utilizing nine of the medication’s topological indices. The melting point, boiling point, flash point, complexity, surface tension, etc., of HIV medicines are closely related according to this QSPR model. This work can help to design and synthesize new HIV treatments and other disease drugs.
{"title":"Topological Descriptors and QSPR Modelling of HIV/AIDS Disease Treatment Drugs","authors":"Fozia Bashir Farooq, Saima Parveen, Nadeem Ul Hassan Awan, Rakotondrajao Fanja","doi":"10.1155/2023/9963241","DOIUrl":"https://doi.org/10.1155/2023/9963241","url":null,"abstract":"A topological index is a real number derived from the structure of a chemical graph. It helps determine the physicochemical and biological properties of a wide range of drugs, and it better reflects the theoretical properties of organic compounds. This is accomplished using degree-based topological indices. We examined some of the physiochemical characteristics of thirteen HIV therapy medications and created a QSPR model utilizing nine of the medication’s topological indices. The melting point, boiling point, flash point, complexity, surface tension, etc., of HIV medicines are closely related according to this QSPR model. This work can help to design and synthesize new HIV treatments and other disease drugs.","PeriodicalId":55177,"journal":{"name":"Discrete Dynamics in Nature and Society","volume":"25 10","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138520267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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