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arXiv 2023年

作者： Augustino, Brandon Leng, Jiaqi Nannicini, Giacomo Terlaky, Tamás Wu, Xiaodi Sloan School of Management Massachusetts Institute of Technology United States Simons Institute for the Theory of Computing Department of Mathematics University of California Berkeley United States Department of Industrial and Systems Engineering University of Southern California United States Department of Industrial and Systems Engineering Lehigh University United States Quantum Computing and Optimization Lab Lehigh University United States Department of Mathematics University of Maryland College Park United States Department of Computer Science University of Maryland College Park United States Joint Center for Quantum Information and Computer Science University of Maryland United States

We propose a novel quantum algorithm for solving linear optimization problems by quantum-mechanical simulation of the central path. While interior point methods follow the central path with an iterative algorithm that works with successive linearizations of the perturbed KKT conditions, we perform a single simulation working directly with the nonlinear complementarity equations. This approach yields an algorithm for solving linear optimization problems involving m constraints and n variables to Ε-optimality using O (√m + n · RΕ1) queries to an oracle that evaluates a potential function, where R1 is an 1-norm upper bound on the size of the optimal solution. In the standard gate model (i.e., without access to quantum RAM) our algorithm can obtain highly-precise solutions to LO problems using at most O (√m + n · nnz(A)RΕ1) elementary gates, where nnz(A) is the total number of non-zero elements found in the constraint matrix. © 2023, CC BY.

关键词： Optimization algorithms

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Brain tumor recognition using an integrated bat algorithm with a convolutional neural network approach

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Measurement: Sensors 2022年 24卷

作者： Chawla, Riddhi Beram, Shehab Mohamed Murthy, C Ravindra Thiruvenkadam, T. Bhavani, N.P.G. Saravanakumar, R. Sathishkumar, P.J. Medical School Akfa University Tashkent Uzbekistan Department of Computing and Information Systems School of Engineering and Technology Sunway University Kuala Lumpur Malaysia Electronics and Instrumentation Engineering Sreevidyanikethan Engineering College Tirupati India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of ECE SIMATS School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Department of Wireless Communication Institute of ECE SIMATS School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Dept of Computer Science and Engineering Panimalar Engineering College India

Tumors are uncontrolled growth of nerve cells that can lead to *** ability to separate malignancies in the brain is critical for better diagnosis. As a result, there are a few research initiatives aimed at improving patient care. The manual method takes time and is only available in a few medical facilities. Treatment choices for brain cancer differ depending on the specific, shape, and position of the tumor, as well as your general health and *** on MRI input images, the system can automatically recognize a type of brain tumor. A Convolutional neural network and Bat algorithm are used in the proposed method to detect brain tumors in MRI images (B–CNN).To eliminate the noise the data is first pre-processed. To extract features from MRI brain pictures, the 2-D Gabor filter is utilized. For better accuracy, feature selection is based on the Bat *** data for this research were obtained from Nanfang Hospital and Tianjing Medical University's General *** proposed BCNN method results in a 99.5% accuracy rate when compared to the existing system. © 2022

关键词： Magnetic resonance imaging

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Analyzing Land Submergence Impact on Temperature Using Random Forest Regression and Explainable AI Techniques

Analyzing Land Submergence Impact on Temperature Using Rando...

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Intelligent Technologies (ACOIT), Asian Conference on

作者： Ujan Pradhan M.N. Aditya R. Raj Kumar Department of Computing Technologies SRM Institute of Science & Technology Kattankulathur Chennai India Department of Electronics & Communication Engineering SRM Institute of Science & Technology Kattankulathur Chennai India Department of Data Science & Business Systems SRM Institute of Science & Technology Kattankulathur Chennai India

ISBN: (数字)9798350374957

ISBN: (纸本)9798350374964

Socio-economic impacts of coastal erosion are serious, more so in Asia. Indeed, there is a greater need for advanced predictive models to be able to manage and reduce risks from increased coastal hazards due to climate change. Most studies provide predictions for shoreline changes using historical data or simple statistical models, which are less accurate and interpretable for proper decision-making. Results show that combining machine learning with explainable AI techniques gives an improvement in predictive accuracy and transparent insight into coastal erosion for informed management decisions. Other methods, such as ensemble techniques, like Random Forest, have been used to improve accuracy and avoid overfitting. In our paper, “Analyzing Land Submergence Impact on Temperature Using Random Forest Regression and Explainable AI Techniques,” we have applied Random Forest Regression for the prediction of the effect of land submergence on temperature change by using the strength of the model. Explainable AI techniques like LIME and SHAP enhance insight into the decision process of the model, but very few studies apply these to coastal erosion. This research fills this gap by using ML models that have explainable AI for more accurate and more interpretable forecasts of temperature variations affecting coastal erosion. A number of explainable AI models are presented in this paper for improving interpretability. Traditionally, black-box ML models are very good at prediction, though often lack transparency, making it hard for stakeholders to understand and build trust in. Explainable models present how each feature contributes to the prediction This transparency enhances trust among coastal managers and policymakers. It aids better decision-making by explaining the drivers of erosion to users. Interpretable models thus help the stakeholders to focus mitigation efforts with directed attention on their part, which helps in ensuring sustainable coastal management.

关键词： Accuracy Temperature Explainable AI Prevention and mitigation Sea measurements Predictive models Land surface temperature Stakeholders Random forests Erosion

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An Improved Driver Safety System based on Drunk and Drive Analyzing Architecture using Internet of Things Assisted Alcohol Identification Sensor

An Improved Driver Safety System based on Drunk and Drive An...

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Advances in computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： M. Swarna G. Saranya A. Vanathi R. Ashwini B. Arunsundar Department of ECE Dr. M.G.R. Educational And Research Institute University Chennai Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Kuniyamuthur Coimbatore Department of ECE Rajalakshmi Institute of Technology Chennai Department of ECE S.A. Engineering College Chennai Department of Data Science and Business Systems School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

The recently survey government is said 80 percentage of road accident is done by drunk and drive and the small cities accident range is 50 percentage to 80 percentage on this survey government declare overall of 100 accident and 30 to 35 deaths occurs on the road due to not wearing the seat belt. The Alcohol Sensor we are implement on the steering and this paper is totally depends on embedded System. This research is IoT and Arduino based system. There has been a dramatic rise in the likelihood of traffic accidents caused by the proliferation of automobiles on the road. Drunk driving is a major contributor to traffic accidents worldwide. The major goal of this research is to develop a system that can detect how much alcohol a driver has consumed. The goal of the proposed system is to decrease the frequency of drunken driving accidents by restricting users from operating motor vehicles while under the influence of alcohol or drugs. A NodeMCU ESP8266 WiFi Modules, an Arduino Controller, an Eye Blink Sensor, and a MQ3 Alcohol Detection Sensors are the main components of the suggested model. To ensure everyone’s safety, when the blood alcohol concentration (BAC) rises beyond a certain threshold, the vehicle’s ignition system will be disabled and the appropriate authorities will be notified via the IoT module; this process has previously been carried out using the GSM module. The proposed work is termed as Improved IoT based Driver Safety Model (IIoTDSM), in which it is cross-validated with the conventional model called GSM based Driver Safety Model (GSMDSM) to evaluate the efficiency of the proposed work.

关键词： Surveys GSM Roads Government Urban areas Safety Automobiles

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Optimal simulation of Deutsch gates and the Fredkin gate

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Physical Review A 2015年第3期91卷 032302-032302页

作者： Nengkun Yu Mingsheng Ying Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada Department of Mathematics & Statistics University of Guelph Guelph Ontario Canada Center for Quantum Computation and Intelligent Systems (QCIS) Faculty of Engineering and Information Technology University of Technology Sydney NSW 2007 Australia State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing 100084 China

In this paper, we study the optimal simulation of the three-qubit unitary using two-qubit gates. First, we completely characterize the two-qubit gate cost of simulating the Deutsch gate (controlled-controlled gate) by generalizing our result on the two-qubit cost of the Toffoli gate. The function of any Deutsch gate is simply a three-qubit controlled-unitary gate and can be intuitively explained as follows: The gate outputs the states of the two control qubits directly, and applies the given one-qubit unitary u on the target qubit only if both the states of the control qubits are |1〉. Previously, it was only known that five two-qubit gates are sufficient for implementing such a gate [Sleator and Weinfurter, Phys. Rev. Lett. 74, 4087 (1995)]. We show that if the determinant of u is 1, four two-qubit gates are optimal. Otherwise, five two-qubit gates are required. For the Fredkin gate (the controlled-swap gate), we prove that five two-qubit gates are necessary and sufficient, which settles the open problem introduced in Smolin and DiVincenzo [Phys. Rev. A 53, 2855 (1996)].

关键词： QUANTUM gates PARTICLE interactions QUBITS QUANTUM information science QUANTUM fluctuations HAMILTONIAN systems QUANTUM states

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Innovative Technologies and Implementation Strategies for Sustainable Irrigation Infrastructure in Nigeria: A Civil engineering Perspective

Innovative Technologies and Implementation Strategies for Su...

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IEEE International Conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Oluwadare Joshua Oyebode Olumayowa Joseph Iyanda Sunday Apeh Sunday Adeniran Afolalu Samuel-Soma M. Ajibade Kazeem Oyeyemi Oyebode Funmilayo Adeola Oyebode Kayode Oluwafemi Olowe Olatunji Peter Folorunso Civil and Environmental Engineering Department Afe Babalola University Ado-Ekiti Nigeria Department of Agricultural Sciences College of Sciences Afe Babalola University Ado-Ekiti Nigeria Mechanical and Mechatronics Engineering Department Afe Babalola University Ado-Ekiti Nigeria Department of Computing and Information Systems School of Engineering and Technology Sunway University Malaysia Department of Computing School of Science and Technology Pan-Atlantic University Lagos Nigeria Ondo State Rural Water Supply and Sanitation Agency Alagbaka Akure Ondo State Nigeria Department of Civil Engineering College of Engineering Afe-Babalola University Ado-Ekiti Department of Civil Engineering Ekiti State University Ado-Ekiti Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Innovative technologies with adequate implementation strategies are essential in Nigeria as Irrigation agriculture accounts for 70% of water use worldwide and irrigation farming in most nations of the World. This paper explores the crucial role of civil engineers in the deployment of innovative strategies and implementation of sustainable irrigation infrastructure in Nigeria. Irrigation systems are currently facing serious challenges due to growing scarcity and competition for water. The methodology includes literature reviews and case studies. Various innovative technologies and implementation strategies were highlighted for sustainable irrigation infrastructure in Nigeria. Remote sensing encompasses satellite imagery, aerial photography, and unmanned aerial vehicles (UAVs) to collect data on crop conditions, soil moisture, and water availability. It was discovered that the implementation of sustainable irrigation infrastructure is of paramount importance for Nigeria’s agricultural development, food security, and overall economic growth. The significance of sustainable irrigation infrastructure, innovative technologies and strategies can be employed by civil engineers and other professionals to address these challenges. Civil engineers possess the expertise, knowledge, and skills to design, implement, and manage sustainable irrigation infrastructure projects. Technological innovations, policy and governance, financing and investment, case studies, and community engagement can be used to achieve sustainable irrigation infrastructure.

关键词： Economics Irrigation Technological innovation Soil moisture Food security Satellite images Stakeholders Water resources Systematic literature review Resilience

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Introducing simulation across the disciplines 05

Introducing simulation across the disciplines

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Simulation Winter Conference

作者： C.R. Standridge M.A. Centeno B. Johansson I. Stahl School of Engineering Padnos College of Engineering and Computing Grand Valley State University Grand Rapids MI USA Industrial and Systems Engineering Florida International University Miami FL USA Department of Product and Production Development Chalmers University of Technology Gothenburg Sweden Department of Managerial Economics Stockholm School of Economics Stockholm Sweden

ISBN: (纸本)9780780395190

How to introduce simulation is a fundamental educational issue in a variety of disciplines including industrial engineering and operations management as well as product design and manufacturing. This panel will discuss, compare, and contrast various perspectives and experiences concerning introducing simulation to undergraduate and graduate students. Topics considered by the panel include the fundamental purposes of a first simulation course, modeling and analysis assignments that are given, examination topics, laboratory content, and term project experiences.

关键词： Modeling Analytical models Computer industry Industrial economics systems engineering and theory Environmental economics Manufacturing industries Laboratories Industrial engineering Distribution functions

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Long Duration Broadcast Authentication for Wireless Sensor Networks

Long Duration Broadcast Authentication for Wireless Sensor N...

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IEEE Vehicular Technology Conference

作者： Yongsheng Liu Jie Li Minyi Guo Graduate School of System and Information Engineering University of Tsukuba Tsukuba Science City 305-8573 Japan Shanghai Key Lab of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai P.R. China

ISBN: (纸本)9781467309899

In the resource constrained Wireless Sensor Networks (WSNs), the broadcast authentication is widely fulfilled by the emerging delayed authentication technique. The one level backward one-way key chain in the delayed authentication technique limits heavily the duration of the broadcast authentication. In this paper, we propose a long duration broadcast authentication scheme for WSNs. The proposed scheme uses a novel hierarchical key chain to extend the duration of broadcast authentication to be as long as the whole lifetime of WSNs. Moreover, the overhead of the proposed scheme is significantly reduced compared to that with one level key chain. Extensive experimental results show that the novel hierarchical key chain fully outperforms the one level key chain in terms of memory and computation.

关键词： Wireless Sensor WSNs chain fully Wireless sensor networks Authentication

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On the Correctness of Speculative Consensus

arXiv

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arXiv 2022年

作者： Hellings, Jelle Rahnama, Sajjad Gupta, Suyash Sadoghi, Mohammad Department of Computing and Software McMaster University HamiltonON Canada Exploratory Systems Lab Department of Computer Science University of California Davis DavisCA United States RISELab Department of Electrical Engineering and Computer Science University of California Berkeley BerkeleyCA United States

The introduction of Bitcoin fueled the development of blockchain-based resilient data management systems that are resilient against failures, enable federated data management, and can support data provenance. The key factor determining the performance of such resilient data management systems is the consensus protocol used by the system to replicate client transactions among all participants. Unfortunately, existing high-throughput consensus protocols are costly and impose significant latencies on transaction processing, which rules out their usage in responsive high-performance data management systems. In this work, we improve on this situation by introducing the Proof-of-Execution consensus protocol (PoE), a consensus protocol designed for high-performance low-latency resilient data management. PoE introduces speculative execution, which minimizes latencies by starting execution before consensus is reached, and PoE introduces proof-of-executions to guarantee successful execution to clients. Furthermore, PoE introduces a single-round check-commit protocol to reduce the overall communication costs of consensus. Hence, we believe that PoE is a promising step towards flexible general-purpose low-latency resilient data management systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Information management

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A Channel-Augmented Multi-Domain Graph Convolutional Network for Fatigue Driving Detection

A Channel-Augmented Multi-Domain Graph Convolutional Network...

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Industrial Automation, Robotics and Control engineering (IARCE), International Conference on

作者： Mingyi Sun Weigang Cui Yang Li Department of Automation Science and Electrical Engineering Beihang University Beijing China School of Engineering Medicine Beihang University Beijing China Department of Automation Science and Electrical Engineering State Key Laboratory of Virtual Reality Technology and Systems The Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9798350380323

ISBN: (纸本)9798350380330

Electroencephalography (EEG) has emerged as a crucial cornerstone within the realm of brain-computer interface (BCI) applications, with its significance notably pronounced in the field of fatigue detection. However, the inherent limitations of EEG acquisition equipment during real driving scenarios have contributed to the constrained robustness of existing models. Moreover, most of recent methods failed to extract robust multi-domain features, leading to a suboptimal performance. To address these challenges, we propose a novel channel-augmented multi-domain graph convolutional network (CA-MDGCNet). Specifically, the initial EEG signals are enriched by incorporating supplementary virtual EEG channels, distinguished as learnable parameters within the network architecture. Then, differential entropy features are extracted from the augmented EEG signals. Following this, a multi-domain graph convolutional network is designed to encode high-level EEG features by means of convolutions in diverse paths, which is beneficial to integrating the characteristics extracted from multiple domains. Finally, the classification block derives the detection outcome from the refined feature maps. To substantiate the potency of the proposed method, the validation was conducted on the publicly accessible SEED-VIG. The proposed CA-MDGCNet not only demonstrates more promising performance compared to state-of-the-art approaches but also underscores the potential viability of our method for the realm of fatigue driving detection.

关键词： Graph convolutional networks Convolution Service robots Neural activity Feature extraction Fatigue Brain modeling Electroencephalography Entropy Robustness

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