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SSRN 2023年

作者： Zhao, Na Tian, Yongshang Lu, Yuwen Zhai, Guofang School of Architecture and Urban Planning Nanjing University 210093 China Department of Computer Science and Technology Nanjing University 210023 China

As a typical ICT-based transportation infrastructure in smart cities, ride-sharing platforms significantly enhance the efficiency of urban public transportation. However, they face severe cybersecurity risks. Cities like Moscow have experienced incidents where hackers infiltrated ride-sharing platforms to maliciously dispatch vehicles, leading to extensive traffic congestion. Existing literature has paid much attention to road network vulnerability against natural disasters. Yet, less focus has been put on disturbances due to such cyber attacks. In this study, we assess the vulnerability of the downtown road network in Nanjing during the morning peak hours when subjected to ride-hailing malicious dispatch attacks. We begin by adopting the perspective of attackers, leveraging relevant theories from graph theory to devise an optimized malicious vehicle dispatch scheme under the real-time road conditions. Subsequently, we conduct simulated attacks against the target network in five major commuting directions. Results show that this attack can significantly decrease the road traffic capacity in some critical directions with just a dispatch of tens of vehicles. Additionally, there is a noticeable disparity in vulnerability across different directions. In response, we further identify the primary factors contributing to these variations, which aims to enhance the resilience of urban road network in the information age. © 2023, The Authors. All rights reserved.

关键词： Traffic congestion

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The differential fault analysis on block cipher FeW

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Cybersecurity 2023年第2期6卷 62-74页

作者： Haiyan Xiao Lifang Wang Jinyong Chang School of Computer Science Northwestern Polytechnical UniversityXiAn 710055People's Republic of China Engineering University of PAP XiAn 710055People's Republic of China School of Information and Control Engineering XiAn University of Architecture and TechnologyXi'An 710055People's Republic of China State Key Laboratory of Information Security(SKLOIS) Institute of Information EngineeringChinese Academy of SciencesBeijing 100089People's Republic of China

Feather weight(FeW)cipher is a lightweight block cipher proposed by Kumar et *** 2019,which takes 64 bits plaintext as input and produces 64 bits *** Kumar et ***,FeW is a software oriented design with the aim of achieving high efficiency in software based *** seems that FeW is immune to many cryptographic attacks,like linear,impossible differential,differential and zero correlation ***,in recent work,Xie et *** the security of *** precisely,they proved that under the differential fault analysis(DFA)on the encryption states,an attacker can completely recover the master secret *** this paper,we revisit the block cipher FeW and consider the DFA on its key schedule algorithm,which is rather popular cryptanalysis for kinds of block *** particular,by respectively injected faults into the 30th and 29th round subkeys,one can recover about 55/80~69%bits of master *** the brute force searching remaining bits,one can obtain the full master secret *** simulations and experiment results show that our analysis is practical.

关键词： Differential fault analysis Block cipher FeW Side channel attack

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Smartphone-based colorimetric detection of formaldehyde in the air

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Building Simulation 2024年第11期17卷 2007-2015页

作者： Meng Yang Jin Ye Tao Yu Ying Song Hua Qian Tianyi Liu Yang Chen Junqi Wang Shi-jie Cao Cong Liu School of Energy and Environment Southeast UniversityNanjing210096China School of Energy and Power Jiangsu University of Science and TechnologyZhenjiangJiangsu212100China Wuhan Second Ship Design and Research Institute Wuhan430205China Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test Hubei Provincial Institute for Food Supervision and TestWuhan430075China Laboratory of Image Science and Technology the School of Computer Science and EngineeringSoutheast UniversityNanjingChina Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast UniversityNanjingChina School of Cyber Science and Engineering Southeast UniversityNanjingChina Key Laboratory of Computer Network and Information Integration Southeast UniversityMinistry of EducationNanjingChina School of Architecture Southeast UniversityNanjingChina Jiangsu Province Engineering Research Center of Urban Heat and Pollution Control Southeast UniversityNanjingChina Global Centre for Clean Air Research(GCARE) University of SurreyGuildfordUK

Adverse impacts of exposure to formaldehyde on human health significantly increases attention in monitoring formaldehyde concentrations in the *** formaldehyde detection methods typically rely on large and costly instruments and requires high skills of expertise,preventing it from being widely accessible to *** study introduced a novel approach utilizing smartphone-based colorimetric *** of green channel signals of digital images by a smartphone successfully capture variation of purple color of 4-amino-3-hydrazino-5-mercapto-1,2,4-triazol solution,which is proportional to formaldehyde *** is because that green and purple are complimentary color pairs.A calibration curve was established between green channel signals and formaldehyde concentrations,with a correlation coefficient of *** limit of the smartphone-based method is 0.008 mg/m^(3).Measurement errors decrease as formaldehyde concentrations increase,with median relative errors of 34%,17%,and 6%for concentration ranges of 0–0.06 mg/m^(3),0.06–0.12 mg/m^(3),and 0.12–0.35 mg/m^(3),*** method replaced scientific instrumentation with ordinary items,greatly reducing cost and operation *** would provide an opportunity to realize onsite measurements for formaldehyde by occupants themselves and increase awareness of air quality for better health protection.

关键词： indoor air quality VOC RGB color identification machine vision

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CDP: Selective Influential Nodes Based on Cliques in the Diffusion Process in Social Networks 9

CDP: Selective Influential Nodes Based on Cliques in the Dif...

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9th International Conference on Web Research, ICWR 2023

作者： Yazdanifar, Fatemeh Beni, Hamid Ahmadi Salimi, Nikoo Bouyer, Asgarali Amirkabir University of Technology Dept. of Mathematics and Computer Science Tehran Iran Madani University Dept. Software Engineering Azarbijan Shahid Tabriz Iran University of Genoa Dept. of the Elec. Electronics Electronics and Telecommunication Eng. and Naval Architecture Genoa Italy Azarbaijan Shahid Madani University Dept. of Computer Engineering Tabriz Iran

ISBN: (纸本)9798350399691

Influence maximization techniques emphasize selecting a set of influential nodes in order to maximize influence. Because the algorithms presented in this field ignore the topology of cliques for diffusion, there are two major challenges in influence maximization algorithms: optimal diffusion and computational overhead reduction. As a result, the CDP algorithm is presented in this article to address these issues. This algorithm first selects suitable cliques for diffusion based on their position and strategy in social networks. Furthermore, for each clique, a score is calculated based on the topological criteria of the clique, and suitable cliques are selected for diffusion by applying a threshold limit. The seed nodes are chosen from the cliques in the second step. To avoid the rich club phenomenon, only a few nodes from each clique are chosen as seed candidate nodes. Finally, the seed nodes are chosen based on the node's topology and the strength of the node's level one neighbor. In the experiment section, the CDP algorithm significantly outperforms the best algorithms presented in recent years in terms of influence spread rate and execution time. © 2023 IEEE.

关键词： Diffusion

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A Review on the need of Clustering Techniques Used for Wireless Sensor Networks 2

A Review on the need of Clustering Techniques Used for Wirel...

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2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Bharany, Salil Rehman, Ateeq Ur Tariq Sadiq, M. Farrukh, Muhammad Alharbi, Meshal Hussain, Amjad Issa, Ghassan F. CET and Technology Department Amritsar India Government College University Department of Electrical Engineering Lahore Pakistan University of Brighton School of Architecture & Engineering United Kingdom Minhaj University Department of Computer Science Lahore Pakistan Prince Sattam Bin Abdulaziz University College of Computer Engineering and Sciences Department of Computer Science Alkharj11942 Saudi Arabia School of Computer Science NCBA&E Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan Skyline University College School of Information Technology Sharjah United Arab Emirates

ISBN: (纸本)9798350335644

Wireless sensor networks have been implemented in various software to help gather and analyze data from the physical world. Wireless sensor networks are networks of multiple tiny sensors powered by low-energy batteries (WSNs). WSN lifetime is a critical factor. This is because, after WSNs have been deployed in a given application, the inaccessibility of the sensing nodes makes it impossible to recharge or replace the power source that is limited in energy. Until recently, WSNs were thought to be the same. All the network nodes have the same power, processing speed, and operational capacity. However, scientists have developed heterogeneous WSNs, in which the properties of individual nodes may vary, to extend the lifespan of networks. In order to extend a network's helpful life, energy-efficient protocols must be designed. Even though WSN has its own problems, it has brought a fresh perspective to studying real-time intelligent systems. WSN (Wireless Sensor Network) has gained significant popularity in the recent years, owing to its vast applications in real-time scenarios, such as disaster management, pollution monitoring, temperature monitoring, traffic monitoring, transport monitoring, healthcare monitoring, battlefield monitoring, and border security surveillance, to name a few. Numerous sensor nodes are employed in these applications. They are typically placed in the sensing field, where they automatically transfer data to the base station (BS) through energy transmission (i.e., battery in the sensor). In WSN, clustering is one method for optimizing power consumption at the sensor node. The sensor nodes are grouped and given a leader when they undergo clustering. This study overviews various WSN clustering algorithms, each categorized according to various clustering properties. © 2023 IEEE.

关键词： Sensor nodes

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Wearable and interactive multicolored photochromic fiber display

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Light(Science & Applications) 2024年第3期13卷 454-465页

作者： Pan Li Yuwei Wang Xiaoxian He Yuyang Cui Jingyu Ouyang Ju Ouyang Zicheng He Jiayu Hu Xiaojuan Liu Hang Wei Yu Wang Xiaoling Lu Qian Ji Xinyuan Cai Li Liu Chong Hou Ning Zhou Shaowu Pan Xiangru Wang Huamin Zhou Cheng-Wei Qiu Yan-Qing Lu Guangming Tao State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and Engineering and Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Vascular Aging(HUST) Ministry of EducationWuhan 430030China School of Optoelectronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China School of Performing Arts Wuhan Conservatory of MusicWuhan 430060China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Architecture and Urban Planning Huazhong University of Science and TechnologyWuhan 430074China School of Fashion Beijing Institute of Fashion TechnologyBeijing 100029China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Tongji Medical College Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent,wearable interactive ***,significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight ***,we introduce a mass-produced,wearable,and interactive photochromic fiber that provides uniform multicolored light *** designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the *** impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission *** addition,we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single *** prepared fibers on mass-produced kilometer-long using the thermal drawing *** fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as *** work provides a new perspective and inspiration to the existing field of fiber display interaction,paving the way for future human–machine integration.

关键词： fiber interactive colored

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Balancing accuracy and interpretability: AI-driven predictive modeling of construction schedule performance in India

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Asian Journal of Civil Engineering 2025年第7期26卷 3083-3098页

作者： Maurya, Sudhanshu Lakkimsetty, Nageswara Rao Manjunath, T.C. Shukla, Anoop Kumar Sethy, Barada Prasad Behera, Rashmi Rekha Symbiosis Institute of Technology Symbiosis International (Deemed University) Nagpur Campus Nagpur India Department of Chemical and Petroleum Engineering School of Engineering American University of Ras Al Khaimah (AURAK) Ras al Khaimah United Arab Emirates Ras al Khaimah United Arab Emirates Department of Computer Science & Engineering Cyber Security & Blockchain Technology Rajarajeswari College of Engineering Bengaluru India Manipal School of Architecture and Planning Manipal Academy of Higher Education Manipal India NIST University Berhampur India Centurion University of Technology and Management Gajapati India

Construction schedule delays are a persistent challenge in India’s infrastructure sector, leading to significant cost overruns, stakeholder dissatisfaction, and inefficient resource utilization. In this context, the integration of Artificial Intelligence (AI) into project forecasting offers a promising solution. This study presents an AI-driven predictive modeling framework aimed at estimating construction schedule adherence, with a dual focus on predictive accuracy and model interpretability. Three machine learning models—multiple linear regression (MLR), artificial neural networks (ANN), and gradient boosting machine (GBM)—were developed and evaluated using real-world data from 150 construction projects across India. The models were assessed based on standard performance metrics (MAE, RMSE, R²), computational efficiency, and transparency. While MLR offered high interpretability, it lacked accuracy in handling nonlinear interactions. ANN showed high accuracy but limited explainability. GBM outperformed both, achieving the best predictive performance (R² = 0.94) and a favorable trade-off between accuracy and interpretability. Feature importance and sensitivity analyses identified equipment utilization, material availability, and labor productivity as key influencers. Case study validation further reinforced the practical value of GBM in diverse project settings. The findings advocate for the strategic adoption of interpretable AI tools like GBM in construction management to enhance scheduling precision and decision-making efficiency. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Artificial intelligence Construction schedule prediction Gradient boosting machine (GBM) Interpretability in machine learning Project performance analytics

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Distributed Voltage Regulation of Distribution Network Based on Partition Control

Distributed Voltage Regulation of Distribution Network Based...

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Cyber-Energy Systems and Intelligent Energy (ICCSIE), International Conference on

作者： Wang Jine Chen Hui Zhao Liying Zhang Guangxin School of Electrical Information Changchun University of Architecture and Civil Engineering Changchun City School of Computer Technology and Engineering Changchun Institute of Technology Changchun City School of Information and Engineering College of Science & Technology Ningbo University Ningbo City

ISBN: (数字)9798350373318

ISBN: (纸本)9798350373325

As China's social economy progresses, the amount of equipment in distribution networks continues to grow, leading to increasingly complex system operations. In this environment, traditional centralized control methods consume excessive computing resources and fail to achieve the processing speeds required by modern intelligent distribution networks. To address these challenges, this article introduces the concept of electrical distance to segment the distribution network and proposes voltage regulation algorithms based on the alternating direction multiplier method and dual ascent method for efficient distributed voltage regulation.

关键词： Reactive power Network topology Electricity Process control Distribution networks Power grids Partitioning algorithms Topology Voltage control Convergence

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Study of an OPTO-ASIC for a Functionally Safe Speed Sensor Using the Spatial Frequency Filter Method

Study of an OPTO-ASIC for a Functionally Safe Speed Sensor U...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Frank Wasinski Werner Bonath Ubbo Ricklefs Michael Schwarz Josef Börcsök Dept. of Electrical Engineering and Information Technology THM University of Applied Sciences Giessen Germany ICAS Institute for Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (数字)9798331528010

ISBN: (纸本)9798331528027

For decades, speed sensors based on the spatial frequency filter method have successfully proven themselves in a wide range of applications. This makes the sensor concept particularly suitable for the area of functional safety. New filter variants extend the previous measuring range to very low speeds up to standstill detection. By combining the sensor with a safety system on chip for recording and analysing measured values, a functionally safe measuring chain can be established. In order to demonstrate the variability and performance of the new filters, an optical application-specific integrated circuit was designed, which forms the basis for further extensive tests. The core components are a large number of freely configurable photodiode channels, which were realised via a redundant structure, as well as two different transimpedance amplifier concepts. In the further course of the project, the ASIC will be analysed with regard to its desired performance parameters and its robustness.

关键词： Optical filters Semiconductor device measurement Optical design Stimulated emission Safety Topology System-on-chip Optical sensors Optical amplifiers Velocity measurement

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TensorMD: Scalable Tensor-Diagram based Machine Learning Interatomic Potential on Heterogeneous Many-Core Processors

arXiv

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arXiv 2023年

作者： Chen, Xin Ouyang, Yucheng Chen, Xin Chen, Zhenchuan Lin, Rongfen Gao, Xingyu Wang, Lifang Li, Fang Liu, Yin Shang, Honghui Song, Haifeng Institute of Applied Physics and Computational Mathematics Beijing China SKL of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China National Research Center of Parallel Computer Engineering and Technology Beijing China

Molecular dynamics simulations have emerged as a potent tool for investigating the physical properties and kinetic behaviors of materials at the atomic scale, particularly in extreme conditions. Ab initio accuracy is now achievable with machine learning based interatomic potentials. With recent advancements in high-performance computing, highly accurate and large-scale simulations become feasible. This study introduces TensorMD, a new machine learning interatomic potential (MLIP) model that integrates physical principles and tensor diagrams. The tensor formalism provides a more efficient computation and greater flexibility for use with other scientific codes. Additionally, we proposed several portable optimization strategies and developed a highly optimized version for the new Sunway supercomputer. Our optimized TensorMD can achieve unprecedented performance on the new Sunway, enabling simulations of up to 52 billion atoms with a time-to-solution of 31 ps/step/atom, setting new records for HPC + AI + MD. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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