Data Science and Management最新文献_第7页

Network science approach for identifying disruptive elements of an airline 识别航空公司干扰因素的网络科学方法

Data Science and Management Pub Date : 2023-06-01 DOI: 10.1016/j.dsm.2023.04.001

Vinod Kumar Chauhan , Anna Ledwoch , Alexandra Brintrup , Manuel Herrera , Vaggelis Giannikas , Goran Stojkovic , Duncan Mcfarlane

{"title":"Network science approach for identifying disruptive elements of an airline","authors":"Vinod Kumar Chauhan , Anna Ledwoch , Alexandra Brintrup , Manuel Herrera , Vaggelis Giannikas , Goran Stojkovic , Duncan Mcfarlane","doi":"10.1016/j.dsm.2023.04.001","DOIUrl":"https://doi.org/10.1016/j.dsm.2023.04.001","url":null,"abstract":"<div><p>Currently, flight delays are common and they propagate from an originating flight to connecting flights, leading to large disruptions in the overall schedule. These disruptions cause massive economic losses, affect airlines’ reputations, waste passengers’ time and money, and directly impact the environment. This study adopts a network science approach for solving the delay propagation problem by modeling and analyzing the flight schedules and historical operational data of an airline. We aim to determine the most disruptive airports, flights, flight-connections, and connection types in an airline network. Disruptive elements are influential or critical entities in an airline network. They are the elements that can either cause (airline schedules) or have caused (historical data) the largest disturbances in the network. An airline can improve its operations by avoiding delays caused by the most disruptive elements. The proposed network science approach for disruptive element analysis was validated using a case study of an operating airline. The analysis indicates that potential disruptive elements in a schedule of an airline are also actual disruptive elements in the historical data and they should be considered to improve operations. The airline network exhibits small-world effects and delays can propagate to any part of the network with a minimum of four delayed flights. Finally, we observed that passenger connections between flights are the most disruptive connection type. Therefore, the proposed methodology provides a tool for airlines to build robust flight schedules that reduce delays and propagation.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49749482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forecasting hourly PM2.5 concentrations based on decomposition-ensemble-reconstruction framework incorporating deep learning algorithms 基于结合深度学习算法的分解-集成-重建框架的每小时PM2.5浓度预测

Data Science and Management Pub Date : 2023-03-01 DOI: 10.1016/j.dsm.2023.02.002

Peilei Cai, Chengyuan Zhang, Jian Chai

{"title":"Forecasting hourly PM2.5 concentrations based on decomposition-ensemble-reconstruction framework incorporating deep learning algorithms","authors":"Peilei Cai, Chengyuan Zhang, Jian Chai","doi":"10.1016/j.dsm.2023.02.002","DOIUrl":"https://doi.org/10.1016/j.dsm.2023.02.002","url":null,"abstract":"<div><p>Accurate predictions of hourly PM<sub>2.5</sub> concentrations are crucial for preventing the harmful effects of air pollution. In this study, a new decomposition-ensemble framework incorporating the variational mode decomposition method (VMD), econometric forecasting method (autoregressive integrated moving average model, ARIMA), and deep learning techniques (convolutional neural networks (CNN) and temporal convolutional network (TCN)) was developed to model the data characteristics of hourly PM<sub>2.5</sub> concentrations. Taking the PM<sub>2.5</sub> concentration of Lanzhou, Gansu Province, China as the sample, the empirical results demonstrated that the developed decomposition-ensemble framework is significantly superior to the benchmarks with the econometric model, machine learning models, basic deep learning models, and traditional decomposition-ensemble models, within one-, two-, or three-step-ahead. This study verified the effectiveness of the new prediction framework to capture the data patterns of PM<sub>2.5</sub> concentration and can be employed as a meaningful PM<sub>2.5</sub> concentrations prediction tool.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49749479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Cross-border electronic commerce’s new path: from literature review to AI text generation 跨境电子商务的新路径：从文献综述到人工智能文本生成

Data Science and Management Pub Date : 2023-03-01 DOI: 10.1016/j.dsm.2022.12.001

Qing Zhu , Yinglin Ruan , Shan Liu , Sung-Byung Yang , Lin Wang , Jianhua Che

引用次数: 0

Application of support vector machine algorithm for early differential diagnosis of prostate cancer 支持向量机算法在前列腺癌早期鉴别诊断中的应用

Data Science and Management Pub Date : 2023-03-01 DOI: 10.1016/j.dsm.2022.10.001

Boluwaji A. Akinnuwesi , Kehinde A. Olayanju , Benjamin S. Aribisala , Stephen G. Fashoto , Elliot Mbunge , Moses Okpeku , Patrick Owate

{"title":"Application of support vector machine algorithm for early differential diagnosis of prostate cancer","authors":"Boluwaji A. Akinnuwesi , Kehinde A. Olayanju , Benjamin S. Aribisala , Stephen G. Fashoto , Elliot Mbunge , Moses Okpeku , Patrick Owate","doi":"10.1016/j.dsm.2022.10.001","DOIUrl":"https://doi.org/10.1016/j.dsm.2022.10.001","url":null,"abstract":"<div><p>Prostate cancer (PCa) symptoms are commonly confused with benign prostate hyperplasia (BPH), particularly in the early stages due to similarities between symptoms, and in some instances, underdiagnoses. Clinical methods have been utilized to diagnose PCa; however, at the full-blown stage, clinical methods usually present high risks of complicated side effects. Therefore, we proposed the use of support vector machine for early differential diagnosis of PCa (SVM-PCa-EDD). SVM was used to classify persons with and without PCa. We used the PCa dataset from the Kaggle Healthcare repository to develop and validate SVM model for classification. The PCa dataset consisted of 250 features and one class of features. Attributes considered in this study were age, body mass index (BMI), race, family history, obesity, trouble urinating, urine stream force, blood in semen, bone pain, and erectile dysfunction. The SVM-PCa-EDD was used for preprocessing the PCa dataset, specifically dealing with class imbalance, and for dimensionality reduction. After eliminating class imbalance, the area under the receiver operating characteristic (ROC) curve (AUC) of the logistic regression (LR) model trained with the downsampled dataset was 58.4%, whereas that of the AUC-ROC of LR trained with the class imbalance dataset was 54.3%. The SVM-PCa-EDD achieved 90% accuracy, 80% sensitivity, and 80% specificity. The validation of SVM-PCa-EDD using random forest and LR showed that SVM-PCa-EDD performed better in early differential diagnosis of PCa. The proposed model can assist medical experts in early diagnosis of PCa, particularly in resource-constrained healthcare settings and making further recommendations for PCa testing and treatment.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49765234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

The influence of e-commerce live streaming affordance on consumer’s gift-giving and purchase intention 电商直播对消费者送礼和购买意愿的影响

Data Science and Management Pub Date : 2023-03-01 DOI: 10.1016/j.dsm.2022.10.002

Yunfan Lu, Yucheng He, Yifei Ke

引用次数: 5

Comparison of administrative and regulatory green technologies development between China and the U.S. based on patent analysis 基于专利分析的中美绿色技术发展行政与监管比较

Data Science and Management Pub Date : 2023-03-01 DOI: 10.1016/j.dsm.2023.01.001

Mengshu Liu, Ju’e Guo, Dan Bi

{"title":"Comparison of administrative and regulatory green technologies development between China and the U.S. based on patent analysis","authors":"Mengshu Liu, Ju’e Guo, Dan Bi","doi":"10.1016/j.dsm.2023.01.001","DOIUrl":"https://doi.org/10.1016/j.dsm.2023.01.001","url":null,"abstract":"<div><p>With the increasing importance of computer intelligence in the new round of the industrial revolution, administrative, regulatory, or design (ARD) green technology contributes to improving national technological competitiveness and promoting the transformation of green technology, which is becoming an important field under sustainable development goals. The U.S. and China ranked top two in terms of paper influence and patent applications in the field of ARD green technology. However, few comparative studies have been conducted in these two countries. This study presents the evolution and landscapes of ARD green technology between China and the U.S., focusing on comparing development priorities and technical layouts in each five-year plan period. According to the “International Patent Classification (IPC) Green Inventory” launched by the World Intellectual Property Organization (WIPO), we retrieved 69,412 patents published between 2001 and 2020 from the PatSnap database. Descriptive, content, and thematic network analyses were conducted using latent dirichlet allocation (LDA) and community detection algorithms. The results show that both China and the U.S. strategically focus on ARD green technology development. The technical topics in this field can be divided into three themes: data processing systems, traffic control systems, and building designs. The emphasis on technology research and development (R&D) differs between China and the U.S. There is also evidence that the U.S. has advantages in terms of technological innovation and capabilities. However, China has an advantage in terms of data volume, and the gap between China and the U.S. is gradually narrowing. We also highlight the contributions and limitations of this study.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49758594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Two-phase tabu search algorithm for solving Chinese high school timetabling problems under the new college entrance examination reform 两阶段禁忌搜索算法在新高考改革下的应用

Data Science and Management Pub Date : 2023-03-01 DOI: 10.1016/j.dsm.2023.02.001

Zhe Sun, Qinghua Wu

{"title":"Two-phase tabu search algorithm for solving Chinese high school timetabling problems under the new college entrance examination reform","authors":"Zhe Sun, Qinghua Wu","doi":"10.1016/j.dsm.2023.02.001","DOIUrl":"https://doi.org/10.1016/j.dsm.2023.02.001","url":null,"abstract":"<div><p>Upon the latest reform to the college entrance examination in China (i.e., Gaokao), high schools began implementing an optional class system. Under this scheme, students’ time slots become complex, thereby increasing the difficulty in formulating a suitable timetable from the available ones. To address this problem, the course-scheduling model was improved. On the basis of the original hard constraints, the “concurrent group” was considered, and the softer constraints were regarded as optimization goals, such as “teaching plans synchronously”, “no idle periods in the timetables of teachers”, and “evenly distributed lessons”. Given these soft constraints, the model becomes more practical. In this study, a two-phase tabu search algorithm was proposed to solve the problem. The proposed algorithm uses the characteristics of the graph coloring model to eliminate redundant calculations in the neighborhood search process, thereby effectively improving computational efficiency. Fifteen practical instances of different scales were selected for testing to verify the effectiveness of the algorithm. The proposed algorithm can formulate high-quality available timetables (The average satisfaction rate of soft constraints is more than 71%) in a short period.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49749484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VERS UN FILTRE ÉTHIQUE POUR LES IA CHARGÉES DE LA VENTE ? 对负责销售的人工智能进行道德过滤?

Data Science and Management Pub Date : 2023-01-01 DOI: 10.36863/mds.a.25456

Thomas Michaud

引用次数: 0

L’IMPACT DE LA TRANSFORMATION NUMÉRIQUE DANS LES ADMINISTRATIONS PUBLIQUES AFRICAINES 数字转型对非洲公共行政的影响

Data Science and Management Pub Date : 2023-01-01 DOI: 10.36863/mds.a.25559

Jean Babei, MOYO NZOLOLO

引用次数: 0

COMMENT RENDRE LE MANAGEMENT ALGORITHMIQUE CAPACITANT ? 如何使算法管理授权?

Data Science and Management Pub Date : 2023-01-01 DOI: 10.36863/mds.a.25594

SOPHIA GALIÈRE

引用次数: 0