Future Internet最新文献_第6页

Online Optimization of Pickup and Delivery Problem Considering Feasibility 考虑可行性的取货和送货问题在线优化

Future Internet Pub Date : 2024-02-17 DOI: 10.3390/fi16020064

Ryo Matsuoka, Koichi Kobayashi, Y. Yamashita

{"title":"Online Optimization of Pickup and Delivery Problem Considering Feasibility","authors":"Ryo Matsuoka, Koichi Kobayashi, Y. Yamashita","doi":"10.3390/fi16020064","DOIUrl":"https://doi.org/10.3390/fi16020064","url":null,"abstract":"A pickup and delivery problem by multiple agents has many applications, such as food delivery service and disaster rescue. In this problem, there are cases where fuels must be considered (e.g., the case of using drones as agents). In addition, there are cases where demand forecasting should be considered (e.g., the case where a large number of orders are carried by a small number of agents). In this paper, we consider an online pickup and delivery problem considering fuel and demand forecasting. First, the pickup and delivery problem with fuel constraints is formulated. The information on demand forecasting is included in the cost function. Based on the orders, the agents’ paths (e.g., the paths from stores to customers) are calculated. We suppose that the target area is given by an undirected graph. Using a given graph, several constraints such as the moves and fuels of the agents are introduced. This problem is reduced to a mixed integer linear programming (MILP) problem. Next, in online optimization, the MILP problem is solved depending on the acceptance of orders. Owing to new orders, the calculated future paths may be changed. Finally, by using a numerical example, we present the effectiveness of the proposed method.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140453652","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

Speech Inpainting Based on Multi-Layer Long Short-Term Memory Networks 基于多层长短期记忆网络的语音涂抹技术

Future Internet Pub Date : 2024-02-17 DOI: 10.3390/fi16020063

Haohan Shi, Xiyu Shi, Safak Dogan

{"title":"Speech Inpainting Based on Multi-Layer Long Short-Term Memory Networks","authors":"Haohan Shi, Xiyu Shi, Safak Dogan","doi":"10.3390/fi16020063","DOIUrl":"https://doi.org/10.3390/fi16020063","url":null,"abstract":"Audio inpainting plays an important role in addressing incomplete, damaged, or missing audio signals, contributing to improved quality of service and overall user experience in multimedia communications over the Internet and mobile networks. This paper presents an innovative solution for speech inpainting using Long Short-Term Memory (LSTM) networks, i.e., a restoring task where the missing parts of speech signals are recovered from the previous information in the time domain. The lost or corrupted speech signals are also referred to as gaps. We regard the speech inpainting task as a time-series prediction problem in this research work. To address this problem, we designed multi-layer LSTM networks and trained them on different speech datasets. Our study aims to investigate the inpainting performance of the proposed models on different datasets and with varying LSTM layers and explore the effect of multi-layer LSTM networks on the prediction of speech samples in terms of perceived audio quality. The inpainted speech quality is evaluated through the Mean Opinion Score (MOS) and a frequency analysis of the spectrogram. Our proposed multi-layer LSTM models are able to restore up to 1 s of gaps with high perceptual audio quality using the features captured from the time domain only. Specifically, for gap lengths under 500 ms, the MOS can reach up to 3~4, and for gap lengths ranging between 500 ms and 1 s, the MOS can reach up to 2~3. In the time domain, the proposed models can proficiently restore the envelope and trend of lost speech signals. In the frequency domain, the proposed models can restore spectrogram blocks with higher similarity to the original signals at frequencies less than 2.0 kHz and comparatively lower similarity at frequencies in the range of 2.0 kHz~8.0 kHz.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140453151","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

Enhancing Energy Efficiency in IoT-NDN via Parameter Optimization 通过参数优化提高 IoT-NDN 的能效

Future Internet Pub Date : 2024-02-16 DOI: 10.3390/fi16020061

Dennis Papenfuß, Bennet Gerlach, Stefan Fischer, M. A. Hail

{"title":"Enhancing Energy Efficiency in IoT-NDN via Parameter Optimization","authors":"Dennis Papenfuß, Bennet Gerlach, Stefan Fischer, M. A. Hail","doi":"10.3390/fi16020061","DOIUrl":"https://doi.org/10.3390/fi16020061","url":null,"abstract":"The IoT encompasses objects, sensors, and everyday items not typically considered computers. IoT devices are subject to severe energy, memory, and computation power constraints. Employing NDN for the IoT is a recent approach to accommodate these issues. To gain a deeper insight into how different network parameters affect energy consumption, analyzing a range of parameters using hyperparameter optimization seems reasonable. The experiments from this work’s ndnSIM-based hyperparameter setup indicate that the data packet size has the most significant impact on energy consumption, followed by the caching scheme, caching strategy, and finally, the forwarding strategy. The energy footprint of these parameters is orders of magnitude apart. Surprisingly, the packet request sequence influences the caching parameters’ energy footprint more than the graph size and topology. Regarding energy consumption, the results indicate that data compression may be more relevant than expected, and caching may be more significant than the forwarding strategy. The framework for ndnSIM developed in this work can be used to simulate NDN networks more efficiently. Furthermore, the work presents a valuable basis for further research on the effect of specific parameter combinations not examined before.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139960971","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

Enhancing Smart City Safety and Utilizing AI Expert Systems for Violence Detection 加强智慧城市安全，利用人工智能专家系统进行暴力检测

Future Internet Pub Date : 2024-01-31 DOI: 10.3390/fi16020050

Pradeep Kumar, Guo-Liang Shih, Bo-Lin Guo, Siva Kumar Nagi, Y. C. Manie, C. Yao, Michael Augustine Arockiyadoss, Peng Peng

{"title":"Enhancing Smart City Safety and Utilizing AI Expert Systems for Violence Detection","authors":"Pradeep Kumar, Guo-Liang Shih, Bo-Lin Guo, Siva Kumar Nagi, Y. C. Manie, C. Yao, Michael Augustine Arockiyadoss, Peng Peng","doi":"10.3390/fi16020050","DOIUrl":"https://doi.org/10.3390/fi16020050","url":null,"abstract":"Violent attacks have been one of the hot issues in recent years. In the presence of closed-circuit televisions (CCTVs) in smart cities, there is an emerging challenge in apprehending criminals, leading to a need for innovative solutions. In this paper, the propose a model aimed at enhancing real-time emergency response capabilities and swiftly identifying criminals. This initiative aims to foster a safer environment and better manage criminal activity within smart cities. The proposed architecture combines an image-to-image stable diffusion model with violence detection and pose estimation approaches. The diffusion model generates synthetic data while the object detection approach uses YOLO v7 to identify violent objects like baseball bats, knives, and pistols, complemented by MediaPipe for action detection. Further, a long short-term memory (LSTM) network classifies the action attacks involving violent objects. Subsequently, an ensemble consisting of an edge device and the entire proposed model is deployed onto the edge device for real-time data testing using a dash camera. Thus, this study can handle violent attacks and send alerts in emergencies. As a result, our proposed YOLO model achieves a mean average precision (MAP) of 89.5% for violent attack detection, and the LSTM classifier model achieves an accuracy of 88.33% for violent action classification. The results highlight the model’s enhanced capability to accurately detect violent objects, particularly in effectively identifying violence through the implemented artificial intelligence system.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140475180","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

Efficient Privacy-Aware Forwarding for Enhanced Communication Privacy in Opportunistic Mobile Social Networks 为增强机会性移动社交网络中的通信隐私而进行高效的隐私感知转发

Future Internet Pub Date : 2024-01-31 DOI: 10.3390/fi16020048

Azizah Assiri, Hassen Sallay

{"title":"Efficient Privacy-Aware Forwarding for Enhanced Communication Privacy in Opportunistic Mobile Social Networks","authors":"Azizah Assiri, Hassen Sallay","doi":"10.3390/fi16020048","DOIUrl":"https://doi.org/10.3390/fi16020048","url":null,"abstract":"Opportunistic mobile social networks (OMSNs) have become increasingly popular in recent years due to the rise of social media and smartphones. However, message forwarding and sharing social information through intermediary nodes on OMSNs raises privacy concerns as personal data and activities become more exposed. Therefore, maintaining privacy without limiting efficient social interaction is a challenging task. This paper addresses this specific problem of safeguarding user privacy during message forwarding by integrating a privacy layer on the state-of-the-art OMSN routing decision models that empowers users to control their message dissemination. Mainly, we present three user-centric privacy-aware forwarding modes guiding the selection of the next hop in the forwarding path based on social metrics such as common friends and exchanged messages between OMSN nodes. More specifically, we define different social relationship strengths approximating real-world scenarios (familiar, weak tie, stranger) and trust thresholds to give users choices on trust levels for different social contexts and guide the routing decisions. We evaluate the privacy enhancement and network performance through extensive simulations using ONE simulator for several routing schemes (Epidemic, Prophet, and Spray and Wait) and different movement models (random way, bus, and working day). We demonstrate that our modes can enhance privacy by up to 45% in various network scenarios, as measured by the reduction in the likelihood of unintended message propagation, while keeping the message-delivery process effective and efficient.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140475692","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

A New Dynamic Game-Based Pricing Model for Cloud Environment 基于游戏的新型云环境动态定价模型

Future Internet Pub Date : 2024-01-31 DOI: 10.3390/fi16020049

Hamid Saadatfar, Hamid Gholampour Ahangar, Javad Hassannataj Joloudari

{"title":"A New Dynamic Game-Based Pricing Model for Cloud Environment","authors":"Hamid Saadatfar, Hamid Gholampour Ahangar, Javad Hassannataj Joloudari","doi":"10.3390/fi16020049","DOIUrl":"https://doi.org/10.3390/fi16020049","url":null,"abstract":"Resource pricing in cloud computing has become one of the main challenges for cloud providers. The challenge is determining a fair and appropriate price to satisfy users and resource providers. To establish a justifiable price, it is imperative to take into account the circumstances and requirements of both the provider and the user. This research tries to provide a pricing mechanism for cloud computing based on game theory. The suggested approach considers three aspects: the likelihood of faults, the interplay among virtual machines, and the amount of energy used, in order to determine a justifiable price. In the game that is being proposed, the provider is responsible for determining the price of the virtual machine that can be made available to the user on each physical machine. The user, on the other hand, has the authority to choose between the virtual machines that are offered in order to run their application. The whole game is implemented as a function of the resource broker component. The proposed mechanism is simulated and evaluated using the CloudSim simulator. Its performance is compared with several previous recent mechanisms. The results indicate that the suggested mechanism has successfully identified a more rational price for both the user and the provider, consequently enhancing the overall profitability of the cloud system.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140475113","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

Enhancing Urban Resilience: Smart City Data Analyses, Forecasts, and Digital Twin Techniques at the Neighborhood Level 增强城市复原力：街区层面的智能城市数据分析、预测和数字孪生技术

Future Internet Pub Date : 2024-01-30 DOI: 10.3390/fi16020047

Andreas F. Gkontzis, S. Kotsiantis, G. Feretzakis, V. Verykios

{"title":"Enhancing Urban Resilience: Smart City Data Analyses, Forecasts, and Digital Twin Techniques at the Neighborhood Level","authors":"Andreas F. Gkontzis, S. Kotsiantis, G. Feretzakis, V. Verykios","doi":"10.3390/fi16020047","DOIUrl":"https://doi.org/10.3390/fi16020047","url":null,"abstract":"Smart cities, leveraging advanced data analytics, predictive models, and digital twin techniques, offer a transformative model for sustainable urban development. Predictive analytics is critical to proactive planning, enabling cities to adapt to evolving challenges. Concurrently, digital twin techniques provide a virtual replica of the urban environment, fostering real-time monitoring, simulation, and analysis of urban systems. This study underscores the significance of real-time monitoring, simulation, and analysis of urban systems to support test scenarios that identify bottlenecks and enhance smart city efficiency. This paper delves into the crucial roles of citizen report analytics, prediction, and digital twin technologies at the neighborhood level. The study integrates extract, transform, load (ETL) processes, artificial intelligence (AI) techniques, and a digital twin methodology to process and interpret urban data streams derived from citizen interactions with the city’s coordinate-based problem mapping platform. Using an interactive GeoDataFrame within the digital twin methodology, dynamic entities facilitate simulations based on various scenarios, allowing users to visualize, analyze, and predict the response of the urban system at the neighborhood level. This approach reveals antecedent and predictive patterns, trends, and correlations at the physical level of each city area, leading to improvements in urban functionality, resilience, and resident quality of life.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140483362","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

Context-Aware Behavioral Tips to Improve Sleep Quality via Machine Learning and Large Language Models 通过机器学习和大型语言模型改善睡眠质量的情境感知行为提示

Future Internet Pub Date : 2024-01-30 DOI: 10.3390/fi16020046

Erica Corda, S. M. Massa, Daniele Riboni

{"title":"Context-Aware Behavioral Tips to Improve Sleep Quality via Machine Learning and Large Language Models","authors":"Erica Corda, S. M. Massa, Daniele Riboni","doi":"10.3390/fi16020046","DOIUrl":"https://doi.org/10.3390/fi16020046","url":null,"abstract":"As several studies demonstrate, good sleep quality is essential for individuals’ well-being, as a lack of restoring sleep may disrupt different physical, mental, and social dimensions of health. For this reason, there is increasing interest in tools for the monitoring of sleep based on personal sensors. However, there are currently few context-aware methods to help individuals to improve their sleep quality through behavior change tips. In order to tackle this challenge, in this paper, we propose a system that couples machine learning algorithms and large language models to forecast the next night’s sleep quality, and to provide context-aware behavior change tips to improve sleep. In order to encourage adherence and to increase trust, our system includes the use of large language models to describe the conditions that the machine learning algorithm finds harmful to sleep health, and to explain why the behavior change tips are generated as a consequence. We develop a prototype of our system, including a smartphone application, and perform experiments with a set of users. Results show that our system’s forecast is correlated to the actual sleep quality. Moreover, a preliminary user study suggests that the use of large language models in our system is useful in increasing trust and engagement.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140483400","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

Non-Profiled Unsupervised Horizontal Iterative Attack against Hardware Elliptic Curve Scalar Multiplication Using Machine Learning 利用机器学习对硬件椭圆曲线标量乘法进行非定位无监督水平迭代攻击

Future Internet Pub Date : 2024-01-29 DOI: 10.3390/fi16020045

Marcin Aftowicz, I. Kabin, Z. Dyka, P. Langendörfer

引用次数: 0

Computer Vision and Machine Learning-Based Predictive Analysis for Urban Agricultural Systems 基于计算机视觉和机器学习的城市农业系统预测分析

Future Internet Pub Date : 2024-01-28 DOI: 10.3390/fi16020044

Arturs Kempelis, I. Poļaka, A. Romānovs, Antons Patlins

{"title":"Computer Vision and Machine Learning-Based Predictive Analysis for Urban Agricultural Systems","authors":"Arturs Kempelis, I. Poļaka, A. Romānovs, Antons Patlins","doi":"10.3390/fi16020044","DOIUrl":"https://doi.org/10.3390/fi16020044","url":null,"abstract":"Urban agriculture presents unique challenges, particularly in the context of microclimate monitoring, which is increasingly important in food production. This paper explores the application of convolutional neural networks (CNNs) to forecast key sensor measurements from thermal images within this context. This research focuses on using thermal images to forecast sensor measurements of relative air humidity, soil moisture, and light intensity, which are integral to plant health and productivity in urban farming environments. The results indicate a higher accuracy in forecasting relative air humidity and soil moisture levels, with Mean Absolute Percentage Errors (MAPEs) within the range of 10–12%. These findings correlate with the strong dependency of these parameters on thermal patterns, which are effectively extracted by the CNNs. In contrast, the forecasting of light intensity proved to be more challenging, yielding lower accuracy. The reduced performance is likely due to the more complex and variable factors that affect light in urban environments. The insights gained from the higher predictive accuracy for relative air humidity and soil moisture may inform targeted interventions for urban farming practices, while the lower accuracy in light intensity forecasting highlights the need for further research into the integration of additional data sources or hybrid modeling approaches. The conclusion suggests that the integration of these technologies can significantly enhance the predictive maintenance of plant health, leading to more sustainable and efficient urban farming practices. However, the study also acknowledges the challenges in implementing these technologies in urban agricultural models.","PeriodicalId":509567,"journal":{"name":"Future Internet","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140491126","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