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Smart public transportation: A future framework for sustainable new cities (Case study Greater Cairo)

IOP Conference Series: Earth and Environmental science 2022年第1期992卷

作者： Hayam M Omayer Assistant Professor Architecture Department Cairo Higher Institute for Engineering Computer Science and Management No.2 Banafseg Center2 first Settlement Cairo Postcode 11477 Egypt.

In the context of the tremendous progress in information technology in all spheres of life, it is necessary to adopt more intelligence solutions to increase the quality of life and achieve sustainable cities. Currently, without a doubt, we have the ability to make all city services accessible to everybody. Transportation and mobility systems are critical components of sustainable city development. Therefore, the scientific literature on the technological systems employed in transportation systems and their primary uses is extensive, outlining their application to improving people's quality of life through promoting a sustainable environment. Recently. There is a new generation of ITS (intelligence transportation system) resulting from the encouragement of related public policy that has been deeply integrated with new infrastructure and new technologies for improving the quality of life. The new generation of ITS technology and urban analysis and planning technology can not only meet the current problems of the coordinated development of the public transportation system and big cities like Cairo, but also meet the needs of the city's future development in advance. This paper will discuss the transformation of intelligent public transportation, the opportunities, and applications, using technologies, and implementation in various urban areas using a case study of China's smart transportation. Additionally, propose a future framework for sustainable transportation in new cities and the feasibility of implementing them in Egypt's new cities. Highlight the actions and outcomes of integrating technologies, as well as their environmental, urban, economic, and social impacts. In order to develop and increase the quality of life in the cities of Egypt and the developing world in order to achieve sustainability goals.

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Paddy rice methane emissions across Monsoon Asia

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Remote Sensing of Environment 2023年 284卷

作者： Ouyang, Zutao Jackson, Robert B. McNicol, Gavin Fluet-Chouinard, Etienne Runkle, Benjamin R.K. Papale, Dario Knox, Sara H. Cooley, Sarah Delwiche, Kyle B. Feron, Sarah Irvin, Jeremy Andrew Malhotra, Avni Muddasir, Muhammad Sabbatini, Simone Alberto, Ma. Carmelita R. Cescatti, Alessandro Chen, Chi-Ling Dong, Jinwei Fong, Bryant N. Guo, Haiqiang Hao, Lu Iwata, Hiroki Jia, Qingyu Ju, Weimin Kang, Minseok Li, Hong Kim, Joon Reba, Michele L. Nayak, Amaresh Kumar Roberti, Debora Regina Ryu, Youngryel Swain, Chinmaya Kumar Tsuang, Benjei Xiao, Xiangming Yuan, Wenping Zhang, Geli Zhang, Yongguang Department of Earth System Science Stanford University StanfordCA United States Woods Institute for the Environment Stanford University StanfordCA United States Precourt Institute for Energy Stanford University StanfordCA United States Department of Earth and Environmental Sciences University of Illinois Chicago ChicagoIL United States Department of Biological and Agricultural Engineering University of Arkansas FayettevilleAR United States University of Tuscia Viterbo Italy IAFES division Viterbo Italy Department of Geography The University of British Columbia VancouverBC Canada Department of Geography University of Oregon EugeneOR United States Department of Environmental Science Policy And Management UC Berkeley BerkeleyCA United States Campus Fryslan University of Groningen Groningen Netherlands Department of Computer Science Stanford University StanfordCA United States Department of Geography University of Zurich Zurich Switzerland International Rice Research Institute Laguna Philippines Ispra Italy Taiwan Agricultural Research Institute Taichung Wufeng Taiwan Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China USDA ARS Delta Water Management Research Unit JonesboroAR United States Fudan University Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering and Coastal Ecosystems Research Station of the Yangtze River Estuary Shanghai China / Jiangsu Key Laboratory of Agricultural Meteorology Nanjing University of Information Science and Technology Nanjing China Department of Environmental Science Shinshu University Matsumoto Japan China Meteorological Administration Institute of Atmospheric Environment Shenyang China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu Nanjing210023 China National Center for AgroM

Although rice cultivation is one of the most important agricultural sources of methane (CH4) and contributes ∼8% of total global anthropogenic emissions, large discrepancies remain among estimates of global CH4 emissions from rice cultivation (ranging from 18 to 115 Tg CH4 yr−1) due to a lack of observational constraints. The spatial distribution of paddy-rice emissions has been assessed at regional-to-global scales by bottom-up inventories and land surface models over coarse spatial resolution (e.g., > 0.5°) or spatial units (e.g., agro-ecological zones). However, high-resolution CH4 flux estimates capable of capturing the effects of local climate and management practices on emissions, as well as replicating in situ data, remain challenging to produce because of the scarcity of high-resolution maps of paddy-rice and insufficient understanding of CH4 predictors. Here, we combine paddy-rice methane-flux data from 23 global eddy covariance sites and MODIS remote sensing data with machine learning to 1) evaluate data-driven model performance and variable importance for predicting rice CH4 fluxes;and 2) produce gridded up-scaling estimates of rice CH4 emissions at 5000-m resolution across Monsoon Asia, where ∼87% of global rice area is cultivated and ∼ 90% of global rice production occurs. Our random-forest model achieved Nash-Sutcliffe Efficiency values of 0.59 and 0.69 for 8-day CH4 fluxes and site mean CH4 fluxes respectively, with land surface temperature, biomass and water-availability-related indices as the most important predictors. We estimate the average annual (winter fallow season excluded) paddy rice CH4 emissions throughout Monsoon Asia to be 20.6 ± 1.1 Tg yr−1 for 2001–2015, which is at the lower range of previous inventory-based estimates (20–32 CH4 Tg yr−1). Our estimates also suggest that CH4 emissions from paddy rice in this region have been declining from 2007 through 2015 following declines in both paddy-rice growing area and emission rates per unit

关键词： Climate change

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Message from the SAIP, NEMI, ECRF, Journal First, and Workshops Track chairs

Proceedings - 2021 IEEE 18th International Conference on Sof...

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Proceedings - 2021 IEEE 18th International Conference on Software architecture Companion, ICSA-C 2021 2021年 x-xi页

作者： Becker, Steffen Camara, Javier Challita, Stephanie Fehling, Christoph Jansen, Anton Kopp, Oliver Koziolek, Heiko Kruchten, Philippe Lewis, Grace A. Lilienthal, Carola Spalazzese, Romina Trubiani, Catia University of Stuttgart Software Quality and Architecture Stuttgart Germany University of York York United Kingdom University of Rennes 1 Rennes France Mercedes-Benz AG Sindelfingen Germany Philips Innovation Services Philips Eindhoven Netherlands ABB Research Ladenburg Germany University of British Columbia Electrical and Computer Engineering Canada Software Engineering Institute Carnegie Mellon University PittsburghPA United States WPS-Workplace Solutions GmbH Hamburg Germany Malmö University Dept. of Computer Science and Media Technology Malmö Sweden Gran Sasso Science Institute L'Aquila Italy

ISBN: (纸本)9781665439107

The 18th IEEE International Conference on Software architecture (ICSA 2021) solicited different types of submissions structured into the following tracks: The main Technical Track (included in the ICSA main proceedings), the Software architecture in Practice (SAIP) track, the New and Emerging Ideas (NEMI) track, the Early Career Researchers Forum (ECRF), the Journal First track, and the Workshop track (included in the companion volume of ICSA 2021 proceedings). Each of these tracks, except for the Technical Track, is presented in the following sections. © 2021 IEEE.

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Collaborating with a Robot Biases Human Spatial Attention

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iscience 2025年

作者： Giulia Scorza Azzarà Joshua Zonca Francesco Rea Joo-Hyun Song Alessandra Sciutti Robotics Brain and Cognitive Sciences Unit Italian Institute of Technology 16152 Genoa GE Italy Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genoa 16145 Genoa GE Italy Cognitive Architecture for Collaborative Technologies (CONTACT) Unit Italian Institute of Technology 16152 Genoa GE Italy Department of Cognitive & Psychological Sciences Brown University 02912 Providence RI USA

Advancements in collaborative technologies have increased the accessibility of Human-Robot Interaction (HRI), yet a gap remains in understanding how HRI affects human systems. This work investigates how HRI influences human visual processing, specifically through the near-hand effect, a phenomenon where the proximity of one’s hand enhances spatial attention. Research has shown that this attentional priority can extend to another person’s hand during collaborative tasks, integrating it into an individual’s body schema. A critical question arises: Can a robot’s anthropomorphic hand similarly bias human attentional priority? Our findings revealed that collaborative HRI facilitates target detection near the robot’s hand, an effect absent before the interaction. Additionally, we examined social and kinematic metrics that enhance this attentional shift by fostering joint body schema formation. These results highlight that HRI can shape human visual processing and body schema integration, offering insight into the interplay between our perceptual and cognitive systems and robotic collaborators.

关键词： Collaborative Human-Robot Interaction Visual Processing Human Spatial Attention Near-Hand Effect Joint Body Schema

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Human-building interaction: Sketches and grounds for a research program

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Interactions 2019年第4期26卷 58-61页

作者： Alavi, Hamed S. Churchill, Elizabeth F. Wiberg, Mikael Lalanne, Denis Dalsgaard, Peter Gen Schieck, Ava Fatah Rogers, Yvonne University College London United Kingdom HumanIST Institute University of Fribourg Switzerland Google United States Umea University Sweden Human-IST Institute Switzerland Centre for Digital Creativity Aarhus University Denmark Bartlett School of Architecture UCL United Kingdom Computer Science Department UCL United Kingdom

Interaction design is increasingly about embedding interactive technologies in our built environment; architecture is increasingly about the use of interactive technologies to reimagine and dynamically repurpose our built environment. This forum focuses on this intersection of interaction and architecture. --- Mikael Wiberg, Editor

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Crossing Roads of Federated Learning and Smart Grids: Overview, Challenges, and Perspectives

arXiv

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arXiv 2023年

作者： Bousbiat, Hafsa Bousselidj, Roumaysa Himeur, Yassine Amira, Abbes Bensaali, Faycal Fadli, Fodil Mansoor, Wathiq Elmenreich, Wilfried University of Applied Sciences Institut für Informatic Wiener Neustadt2700 Austria University of Skikda Department of Computer Science Mezghich Skikda21000 Algeria University of Dubai College of Engineering and Information Technology Dubai United Arab Emirates University of Sharjah College of Computing and Informatics Sharjah United Arab Emirates De Montfort University Leicester Institute of Artificial Intelligence United Kingdom Qatar University Department of Electrical Engineering Doha2713 Qatar Qatar University College of Engineering Department of Architecture and Urban Planning Doha2713 Qatar University of Klagenfurt Smart Grids Research Group Klagenfurt9020 Austria

Consumer’s privacy is a main concern in Smart Grids (SGs) due to the sensitivity of energy data, particularly when used to train machine learning models for different services. These data-driven models often require huge amounts of data to achieve acceptable performance leading in most cases to risks of privacy leakage. By pushing the training to the edge, Federated Learning (FL) offers a good compromise between privacy preservation and the predictive performance of these models. The current paper presents an overview of FL applications in SGs while discussing their advantages and drawbacks, mainly in load forecasting, electric vehicles, fault diagnoses, load disaggregation and renewable energies. In addition, an analysis of main design trends and possible taxonomies is provided considering data partitioning, the communication topology, and security mechanisms. Towards the end, an overview of main challenges facing this technology and potential future directions is presented. © 2023, CC BY-NC-SA.

关键词： Internet of Energy

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A Pareto Dominance Principle for Data-Driven Optimization

arXiv

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arXiv 2020年

作者： Sutter, Tobias Van Parys, Bart P.G. Kuhn, Daniel Department of Computer Science University of Konstanz Germany Sloan School of Management Massachusetts Institute of Technology United States Risk Analytics and Optimization Chair Ecole Polytechnique Fédérale de Lausanne Switzerland

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be expressed as the minimizer of a surrogate optimization model constructed from the data. The quality of a data-driven decision is measured by its out-of-sample risk. An additional quality measure is its out-of-sample disappointment, which we define as the probability that the out-of-sample risk exceeds the optimal value of the surrogate optimization model. The crux of data-driven optimization is that the data-generating probability measure is unknown. An ideal data-driven decision should therefore minimize the out-of-sample risk simultaneously with respect to every conceivable probability measure (and thus in particular with respect to the unknown true measure). Unfortunately, such ideal data-driven decisions are generally unavailable. This prompts us to seek data-driven decisions that minimize the in-sample risk subject to an upper bound on the out-of-sample disappointment-again simultaneously with respect to every conceivable probability measure. We prove that such Pareto dominant data-driven decisions exist under conditions that allow for interesting applications: the unknown data-generating probability measure must belong to a parametric ambiguity set, and the corresponding parameters must admit a sufficient statistic that satisfies a large deviation principle. If these conditions hold, we can further prove that the surrogate optimization model generating the optimal data-driven decision must be a distributionally robust optimization problem constructed from the sufficient statistic and the rate function of its large deviation principle. This shows that the optimal method for mapping data to decisions is, in a rigorous statistical sense, to solve a distributionally robust optimization model. Maybe surprisingly, thi

关键词： Decision making

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Blockchain based Public Auditing Outsourcing for Cloud Storage

Blockchain based Public Auditing Outsourcing for Cloud Stora...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Yangfei Lin Jie Li Shigetomo Kimura Yongbing Zhang Yusheng Ji Yang Yang Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Shanghai Jiao Tong University Shanghai China Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Ibaraki Japan Information Systems Architecture Research Division National Institute of Informatics Tokyo Japan School of Mathematics and Computer Science Fuzhou University Fuzhou China

ISBN: (纸本)9781665408790

Cloud storage services offer flexible, convenient solutions for business and personal users to store data. Traditionally, Third Party Auditors (TPAs) are introduced to ensure data integrity for public auditing. However, TPAs may also be untrusted for forging the auditing results or colluding with cloud storage servers to deceive users. In this paper, we propose a novel Blockchain-based Public Auditing Outsourcing system without TPAs (BPAO), in which the computationally expensive operations in public auditing are outsourced through blockchain to the cloud servers without risking users' privacy. Our security analysis indicates that BPAO achieves soundness and robustness. The experimental results show that BPAO is computationally efficient for cloud storage user.

关键词： Cloud computing Privacy Data integrity Conferences Smart contracts Robustness Outsourcing

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Research on the surface water quality in the Huaihe River Basin and the gensis based on multivariate statistical analysis

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Scientific Reports 2025年第1期15卷 1-12页

作者： Feng, Shuzhen Zhang, Chaokai Yan, Jiaheng Ren, Ke Peng, Ningbo Jiang, Wei Liu, Shouhua Nanjing Vocational Institute of Railway Technology Nanjing 210031 China Faculty of Architecture and Civil Engineering Huaiyin Institute of Technology Huaian 223003 China HYIT-CREC Institute of Science and Technology for Conservation of Cultural Heritage Huaiyin Institute of Technology Huaian 223003 China Key Scientific Research Base of the State Administration of Cultural Heritage for Integrated Technology and Application of Grotto Cultural Heritage Protection Engineering Department Chengdu 610036 China Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huaian 223003 China

The Huaihe River Basin (HRB) is an important water system in eastern China, and its water quality has received widespread attention. This study explored the latest spatial variation patterns of surface water quality in the HRB to cope with the increasingly severe challenges of water resource management. By integrating multidimensional water quality data from surface water monitoring stations, including dissolved oxygen (DO), chemical oxygen demand (CODMn and COD), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3–N), total phosphorus (TP), and total nitrogen (TN), this study utilized a cluster analysis technique to categorize the water quality data and reveal changes in the geographic variability of water quality. Among the 382 monitoring stations in the HRB, 258 stations had TN content lower than Class V, which was the highest among all monitoring indicators. The entropy weight method used to assess the comprehensive water quality showed that there were 157 and 163 monitoring stations belonging to Class III and IV, respectively, and stations with poor water quality were distributed downstream in the river network and estuary area. Correlation and cluster analyses indicated that agricultural and organic matter pollution were the two main factors affecting water quality in the HRB, particularly in the downstream area, and the high loading of nutrient salts such as TP and NH3–N reflected the significant influence of agricultural activities. In addition, the study examined the potential driving role of factors such as topography, geomorphology, and human activities on water quality changes and visualized the relationship between water quality class and cluster categories through spatial distribution maps and Sankey diagrams to clarify the regional patterns of water quality problems.

关键词： Agricultural pollution Cluster analysis Huaihe River Basin Spatial change rules Surface water quality

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Impact of NBTI on Increasing the Susceptibility of FinFET to Radiation

Impact of NBTI on Increasing the Susceptibility of FinFET to...

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Annual International Symposium on Reliability Physics

作者： Frank Sill Torres Hussam Amrouch Jörg Henke Rolf Drechsler Group of Computer Architecture University of Bremen Germany Department of Computer Science Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

This work investigates the interaction between Neg-ative Bias Temperature Instability (NBTI)and radiation effects in 14nm FinFET devices. Due to the complex interaction between traps generated by NBTI and induced charges by strikes of ionizing particles, we opted for a complete physical-based analysis using TCAD mixed-mode simulations. This enables an accurate estimation and then modeling of the duration a circuit requires to recover from a particle strike and, thus, return to correct operation under the effects of NBTI. This a crucial aspect, because the longer the recovery time, the higher the probabilities of a soft-error and that this error remains undetected. Further, our employed setup enables an accurate determination of the critical charge (Q crit ), i. e. the minimum collected charge that results into a faulty transition of a circuit's output node. Our investigation reveals that there is indeed a strong relation between NBTI and the time a circuit remains in faulty state. Consequently, detection schemes must be adapted during circuit's operation to take aging into account in order to avoid that errors remain undetected.

关键词： Negative bias temperature instability Thermal variables control Inverters Ions Circuit faults FinFETs Load modeling

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