Information (Switzerland)最新文献_第3页

Combining Software-Defined Radio Learning Modules and Neural Networks for Teaching Communication Systems Courses 结合软件无线电学习模块和神经网络进行通信系统课程教学

Information (Switzerland) Pub Date : 2023-11-04 DOI: 10.3390/info14110599

Luis A. Camuñas-Mesa, José M. de la Rosa

引用次数: 0

Deep Learning for Time Series Forecasting: Advances and Open Problems 时间序列预测的深度学习:进展和开放问题

Information (Switzerland) Pub Date : 2023-11-04 DOI: 10.3390/info14110598

Angelo Casolaro, Vincenzo Capone, Gennaro Iannuzzo, Francesco Camastra

引用次数: 0

Multi-Agent Reinforcement Learning for Online Food Delivery with Location Privacy Preservation 基于位置隐私保护的在线送餐多智能体强化学习

Information (Switzerland) Pub Date : 2023-11-03 DOI: 10.3390/info14110597

Suleiman Abahussein, Dayong Ye, Congcong Zhu, Zishuo Cheng, Umer Siddique, Sheng Shen

{"title":"Multi-Agent Reinforcement Learning for Online Food Delivery with Location Privacy Preservation","authors":"Suleiman Abahussein, Dayong Ye, Congcong Zhu, Zishuo Cheng, Umer Siddique, Sheng Shen","doi":"10.3390/info14110597","DOIUrl":"https://doi.org/10.3390/info14110597","url":null,"abstract":"Online food delivery services today are considered an essential service that gets significant attention worldwide. Many companies and individuals are involved in this field as it offers good income and numerous jobs to the community. In this research, we consider the problem of online food delivery services and how we can increase the number of received orders by couriers and thereby increase their income. Multi-agent reinforcement learning (MARL) is employed to guide the couriers to areas with high demand for food delivery requests. A map of the city is divided into small grids, and each grid represents a small area of the city that has different demand for online food delivery orders. The MARL agent trains and learns which grid has the highest demand and then selects it. Thus, couriers can get more food delivery orders and thereby increase long-term income. While increasing the number of received orders is important, protecting customer location is also essential. Therefore, the Protect User Location Method (PULM) is proposed in this research in order to protect customer location information. The PULM injects differential privacy (DP) Laplace noise based on two parameters: city area size and customer frequency of online food delivery orders. We use two datasets—Shenzhen, China, and Iowa, USA—to demonstrate the results of our experiments. The results show an increase in the number of received orders in the Shenzhen and Iowa City datasets. We also show the similarity and data utility of courier trajectories after we use our obfuscation (PULM) method.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135775127","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: 1

Temporal Convolutional Networks and BERT-Based Multi-Label Emotion Analysis for Financial Forecasting 基于时间卷积网络和bert的金融预测多标签情绪分析

Information (Switzerland) Pub Date : 2023-11-03 DOI: 10.3390/info14110596

Charalampos M. Liapis, Sotiris Kotsiantis

引用次数: 0

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