Information (Switzerland)最新文献_第3页

Enhancing Walking Accessibility in Urban Transportation: A Comprehensive Analysis of Influencing Factors and Mechanisms 提高城市交通步行可达性:影响因素与机制综合分析

Information (Switzerland) Pub Date : 2023-11-02 DOI: 10.3390/info14110595

Yong Liu, Xueqi Ding, Yanjie Ji

{"title":"Enhancing Walking Accessibility in Urban Transportation: A Comprehensive Analysis of Influencing Factors and Mechanisms","authors":"Yong Liu, Xueqi Ding, Yanjie Ji","doi":"10.3390/info14110595","DOIUrl":"https://doi.org/10.3390/info14110595","url":null,"abstract":"The rise in “urban diseases” like population density, traffic congestion, and environmental pollution has renewed attention to urban livability. Walkability, a critical measure of pedestrian friendliness, has gained prominence in urban and transportation planning. This research delves into a comprehensive analysis of walking accessibility, examining both subjective and objective aspects. This study aims to identify the influencing factors and explore the underlying mechanisms driving walkability within a specific area. Through a questionnaire survey, residents’ subjective perceptions were gathered concerning various factors such as traffic operations, walking facilities, and the living environment. Structural equation modeling was employed to analyze the collected data, revealing that travel experience significantly impacts perceived accessibility, followed by facility condition, traffic condition, and safety perception. In the objective analysis, various types of POI data served as explanatory variables, dividing the study area into grids using ArcGIS, with the Walk Score® as the dependent variable. Comparisons of OLS, GWR and MGWR demonstrated that MGWR yielded the most accurate fitting results. Mixed land use, shopping, hotels, residential, government, financial, and medical public services exhibited positive correlations with local walkability, while corporate enterprises and street greening showed negative correlations. These findings were attributed to the level of development, regional functions, population distribution, and supporting facility deployment, collectively influencing the walking accessibility of the area. In conclusion, this research presents crucial insights into enhancing walkability, with implications for urban planning and management, thereby enriching residents’ walking travel experience and promoting sustainable transportation practices. Finally, the limitations of the thesis are discussed.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"17 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135973727","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

Range-Free Localization Approaches Based on Intelligent Swarm Optimization for Internet of Things 基于智能群优化的物联网无距离定位方法

Information (Switzerland) Pub Date : 2023-11-01 DOI: 10.3390/info14110592

Abdelali Hadir, Naima Kaabouch, Mohammed-Alamine El Houssaini, Jamal El Kafi

{"title":"Range-Free Localization Approaches Based on Intelligent Swarm Optimization for Internet of Things","authors":"Abdelali Hadir, Naima Kaabouch, Mohammed-Alamine El Houssaini, Jamal El Kafi","doi":"10.3390/info14110592","DOIUrl":"https://doi.org/10.3390/info14110592","url":null,"abstract":"Recently, the precise location of sensor nodes has emerged as a significant challenge in the realm of Internet of Things (IoT) applications, including Wireless Sensor Networks (WSNs). The accurate determination of geographical coordinates for detected events holds pivotal importance in these applications. Despite DV-Hop gaining popularity due to its cost-effectiveness, feasibility, and lack of additional hardware requirements, it remains hindered by a relatively notable localization error. To overcome this limitation, our study introduces three new localization approaches that combine DV-Hop with Chicken Swarm Optimization (CSO). The primary objective is to improve the precision of DV-Hop-based approaches. In this paper, we compare the efficiency of the proposed localization algorithms with other existing approaches, including several algorithms based on Particle Swarm Optimization (PSO), while considering random network topologies. The simulation results validate the efficiency of our proposed algorithms. The proposed HW-DV-HopCSO algorithm achieves a considerable improvement in positioning accuracy compared to those of existing models.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135221111","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

CoDiS: Community Detection via Distributed Seed Set Expansion on Graph Streams CoDiS:基于图流上分布式种子集展开的社区检测

Information (Switzerland) Pub Date : 2023-11-01 DOI: 10.3390/info14110594

Austin Anderson, Petros Potikas, Katerina Potika

{"title":"CoDiS: Community Detection via Distributed Seed Set Expansion on Graph Streams","authors":"Austin Anderson, Petros Potikas, Katerina Potika","doi":"10.3390/info14110594","DOIUrl":"https://doi.org/10.3390/info14110594","url":null,"abstract":"Community detection has been (and remains) a very important topic in several fields. From marketing and social networking to biological studies, community detection plays a key role in advancing research in many different fields. Research on this topic originally looked at classifying nodes into discrete communities (non-overlapping communities) but eventually moved forward to placing nodes in multiple communities (overlapping communities). Unfortunately, community detection has always been a time-inefficient process, and datasets are too large to realistically process them using traditional methods. Because of this, recent methods have turned to parallelism and graph stream models, where the edge list is accessed one edge at a time. However, all these methods, while offering a significant decrease in processing time, still have several shortcomings. We propose a new parallel algorithm called community detection with seed sets (CoDiS), which solves the overlapping community detection problem in graph streams. Initially, some nodes (seed sets) have known community structures, and the aim is to expand these communities by processing one edge at a time. The innovation of our approach is that it splits communities among the parallel computation workers so that each worker is only updating a subset of all the communities. By doing so, we decrease the edge processing throughput and decrease the amount of time each worker spends on each edge. Crucially, we remove the need for every worker to have access to every community. Experimental results show that we are able to gain a significant improvement in running time with no loss of accuracy.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135371364","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

Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation 机器学习在异质植被场地二氧化碳流量分析中的应用

Information (Switzerland) Pub Date : 2023-11-01 DOI: 10.3390/info14110591

Ekaterina Kulakova, Elena Muravyova

{"title":"Machine Learning in the Analysis of Carbon Dioxide Flow on a Site with Heterogeneous Vegetation","authors":"Ekaterina Kulakova, Elena Muravyova","doi":"10.3390/info14110591","DOIUrl":"https://doi.org/10.3390/info14110591","url":null,"abstract":"The article presents the results of studies of carbon dioxide flow in the territory of section No. 5 of the Eurasian Carbon Polygon (Russia, Republic of Bashkortostan). The gas analyzer Sniffer4D V2.0 (manufactured in Shenzhen, China) with an installed CO2 sensor, quadrocopter DJI MATRICE 300 RTK (manufactured in Shenzhen, China) were used as control devices. The studies were carried out on a clear autumn day in conditions of green vegetation and on a frosty November day with snow cover. Statistical characteristics of experimental data arrays are calculated. Studies of the influence of temperature, humidity of atmospheric air on the current value of CO2 have been carried out. Graphs of the distribution of carbon dioxide concentration in the atmospheric air of section No. 5 on autumn and winter days were obtained. It has been established that when building a model of CO2 in the air, the parameters of the process of deposition by green vegetation should be considered. It was found that in winter, an increase in air humidity contributes to a decrease in gas concentration. At an ambient temperature of 21 °C, an increase in humidity leads to an increase in the concentration of carbon dioxide.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"74 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135221107","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

Multiple Information-Aware Recurrent Reasoning Network for Joint Dialogue Act Recognition and Sentiment Classification 联合对话行为识别与情感分类的多信息感知循环推理网络

Information (Switzerland) Pub Date : 2023-11-01 DOI: 10.3390/info14110593

Shi Li, Xiaoting Chen

{"title":"Multiple Information-Aware Recurrent Reasoning Network for Joint Dialogue Act Recognition and Sentiment Classification","authors":"Shi Li, Xiaoting Chen","doi":"10.3390/info14110593","DOIUrl":"https://doi.org/10.3390/info14110593","url":null,"abstract":"The task of joint dialogue act recognition (DAR) and sentiment classification (DSC) aims to predict both the act and sentiment labels of each utterance in a dialogue. Existing methods mainly focus on local or global semantic features of the dialogue from a single perspective, disregarding the impact of the other part. Therefore, we propose a multiple information-aware recurrent reasoning network (MIRER). Firstly, the sequence information is smoothly sent to multiple local information layers for fine-grained feature extraction through a BiLSTM-connected hybrid CNN group method. Secondly, to obtain global semantic features that are speaker-, context-, and temporal-sensitive, we design a speaker-aware temporal reasoning heterogeneous graph to characterize interactions between utterances spoken by different speakers, incorporating different types of nodes and meta-relations with node-edge-type-dependent parameters. We also design a dual-task temporal reasoning heterogeneous graph to realize the semantic-level and prediction-level self-interaction and interaction, and we constantly revise and improve the label in the process of dual-task recurrent reasoning. MIRER fully integrates context-level features, fine-grained features, and global semantic features, including speaker, context, and temporal sensitivity, to better simulate conversation scenarios. We validated the method on two public dialogue datasets, Mastodon and DailyDialog, and the experimental results show that MIRER outperforms various existing baseline models.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135325932","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

Predicting COVID-19 Hospital Stays with Kolmogorov–Gabor Polynomials: Charting the Future of Care 用Kolmogorov-Gabor多项式预测COVID-19住院时间:描绘护理的未来

Information (Switzerland) Pub Date : 2023-10-31 DOI: 10.3390/info14110590

Hamidreza Marateb, Mina Norouzirad, Kouhyar Tavakolian, Faezeh Aminorroaya, Mohammadreza Mohebbian, Miguel Ángel Mañanas, Sergio Romero Lafuente, Ramin Sami, Marjan Mansourian

{"title":"Predicting COVID-19 Hospital Stays with Kolmogorov–Gabor Polynomials: Charting the Future of Care","authors":"Hamidreza Marateb, Mina Norouzirad, Kouhyar Tavakolian, Faezeh Aminorroaya, Mohammadreza Mohebbian, Miguel Ángel Mañanas, Sergio Romero Lafuente, Ramin Sami, Marjan Mansourian","doi":"10.3390/info14110590","DOIUrl":"https://doi.org/10.3390/info14110590","url":null,"abstract":"Optimal allocation of ward beds is crucial given the respiratory nature of COVID-19, which necessitates urgent hospitalization for certain patients. Several governments have leveraged technology to mitigate the pandemic’s adverse impacts. Based on clinical and demographic variables assessed upon admission, this study predicts the length of stay (LOS) for COVID-19 patients in hospitals. The Kolmogorov–Gabor polynomial (a.k.a., Volterra functional series) was trained using regularized least squares and validated on a dataset of 1600 COVID-19 patients admitted to Khorshid Hospital in the central province of Iran, and the five-fold internal cross-validated results were presented. The Volterra method provides flexibility, interactions among variables, and robustness. The most important features of the LOS prediction system were inflammatory markers, bicarbonate (HCO3), and fever—the adj. R2 and Concordance Correlation Coefficients were 0.81 [95% CI: 0.79–0.84] and 0.94 [0.93–0.95], respectively. The estimation bias was not statistically significant (p-value = 0.777; paired-sample t-test). The system was further analyzed to predict “normal” LOS ≤ 7 days versus “prolonged” LOS > 7 days groups. It showed excellent balanced diagnostic accuracy and agreement rate. However, temporal and spatial validation must be considered to generalize the model. This contribution is hoped to pave the way for hospitals and healthcare providers to manage their resources better.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"94 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809334","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

Security Analysis and Enhancement of INTERBUS Protocol in ICS Based on Colored Petri Net 基于有色Petri网的ICS中INTERBUS协议的安全性分析与改进

Information (Switzerland) Pub Date : 2023-10-29 DOI: 10.3390/info14110589

Tao Feng, Chengfan Liu, Xiang Gong, Ye Lu

引用次数: 1

Large-Scale Group Decision-Making Method Using Hesitant Fuzzy Rule-Based Network for Asset Allocation 基于犹豫模糊规则网络的大规模群体资产配置决策方法

Information (Switzerland) Pub Date : 2023-10-26 DOI: 10.3390/info14110588

Abdul Malek Yaakob, Shahira Shafie, Alexander Gegov, Siti Fatimah Abdul Rahman, Ku Muhammad Naim Ku Khalif

引用次数: 0

Securing the Network: A Red and Blue Cybersecurity Competition Case Study 网络安全:红蓝网络安全竞争案例研究

Information (Switzerland) Pub Date : 2023-10-26 DOI: 10.3390/info14110587

Cristian Chindrus, Constantin-Florin Caruntu

{"title":"Securing the Network: A Red and Blue Cybersecurity Competition Case Study","authors":"Cristian Chindrus, Constantin-Florin Caruntu","doi":"10.3390/info14110587","DOIUrl":"https://doi.org/10.3390/info14110587","url":null,"abstract":"In today’s dynamic and evolving digital landscape, safeguarding network infrastructure against cyber threats has become a paramount concern for organizations worldwide. This paper presents a novel and practical approach to enhancing cybersecurity readiness. The competition, designed as a simulated cyber battleground, involves a Red Team emulating attackers and a Blue Team defending against their orchestrated assaults. Over two days, multiple teams engage in strategic maneuvers to breach and fortify digital defenses. The core objective of this study is to assess the efficacy of the Red and Blue cybersecurity competition in fostering real-world incident response capabilities and honing the skills of cybersecurity practitioners. This paper delves into the competition’s structural framework, including the intricate network architecture and the roles of the participating teams. This study gauges the competition’s impact on enhancing teamwork and incident response strategies by analyzing participant performance data and outcomes. The findings underscore the significance of immersive training experiences in cultivating proactive cybersecurity mindsets. Participants not only showcase heightened proficiency in countering cyber threats but also develop a profound understanding of attacker methodologies. Furthermore, the competition fosters an environment of continuous learning and knowledge exchange, propelling participants toward heightened cyber resilience.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"68 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134905830","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

Deep Learning Approaches for Big Data-Driven Metadata Extraction in Online Job Postings 基于深度学习的大数据驱动元数据提取方法

Information (Switzerland) Pub Date : 2023-10-25 DOI: 10.3390/info14110585

Panagiotis Skondras, Nikos Zotos, Dimitris Lagios, Panagiotis Zervas, Konstantinos C. Giotopoulos, Giannis Tzimas

{"title":"Deep Learning Approaches for Big Data-Driven Metadata Extraction in Online Job Postings","authors":"Panagiotis Skondras, Nikos Zotos, Dimitris Lagios, Panagiotis Zervas, Konstantinos C. Giotopoulos, Giannis Tzimas","doi":"10.3390/info14110585","DOIUrl":"https://doi.org/10.3390/info14110585","url":null,"abstract":"This article presents a study on the multi-class classification of job postings using machine learning algorithms. With the growth of online job platforms, there has been an influx of labor market data. Machine learning, particularly NLP, is increasingly used to analyze and classify job postings. However, the effectiveness of these algorithms largely hinges on the quality and volume of the training data. In our study, we propose a multi-class classification methodology for job postings, drawing on AI models such as text-davinci-003 and the quantized versions of Falcon 7b (Falcon), Wizardlm 7B (Wizardlm), and Vicuna 7B (Vicuna) to generate synthetic datasets. These synthetic data are employed in two use-case scenarios: (a) exclusively as training datasets composed of synthetic job postings (situations where no real data is available) and (b) as an augmentation method to bolster underrepresented job title categories. To evaluate our proposed method, we relied on two well-established approaches: the feedforward neural network (FFNN) and the BERT model. Both the use cases and training methods were assessed against a genuine job posting dataset to gauge classification accuracy. Our experiments substantiated the benefits of using synthetic data to enhance job posting classification. In the first scenario, the models’ performance matched, and occasionally exceeded, that of the real data. In the second scenario, the augmented classes consistently outperformed in most instances. This research confirms that AI-generated datasets can enhance the efficacy of NLP algorithms, especially in the domain of multi-class classification job postings. While data augmentation can boost model generalization, its impact varies. It is especially beneficial for simpler models like FNN. BERT, due to its context-aware architecture, also benefits from augmentation but sees limited improvement. Selecting the right type and amount of augmentation is essential.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"61 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135113706","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