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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Precipitation Forecast with an Incorporation of Pollutants: Visual Analytic Approach 8th

Precipitation Forecast with an Incorporation of Pollutants: ...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Govindan, Sudha Sangaiah, Suguna Madurai Kamaraj Univ Dept Comp Sci Madurai Tamil Nadu India Sri Meenakshi Govt Arts Coll Women A PG & Res Dept Comp Sci Madurai Tamil Nadu India

ISBN: (纸本)9789819713196;9789819713202

Weather forecasting is stochastic in nature since the parameters are influenced by several external factors such as pollution. Pollution is raised by human activity and potentially damages the health of all living beings. This research work aimed to reveal the relationship between the parameters of weather, pollution, and perform the medium-term precipitation (rainfall) forecast. The associations among the parameters are identified using intervening variable analysis and the most promising attributes with respect to precipitation are identified. Three forecasting models based on regression, ARIMA, and LSTM are constructed to perform medium-term forecasting. Visual analytics is the technique that enables the binding of visualization with the underlying forecast model, and the performance of the model is evaluated both in quantitative results and visual form. This research work has used weather and pollution observations of 'Chennai' city recorded from 2016 to 2018 are fetched from official websites.

关键词： PM2.5 LSTM Regression ARIMA Modelling and hyperparameter optimization Intervening variable analysis Imputation techniques

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Toward Fair Ride Sharing Platforms: The Role of Regulations and Wait Time 7th

Toward Fair Ride Sharing Platforms: The Role of Regulations ...

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7th International Conference on Logistics Operations Management (GOL)

作者： Malhotra, Ahana Hassini, Elkafi McMaster Univ DeGroote Sch Business Hamilton ON L8S 4L8 Canada

ISBN: (纸本)9783031686337;9783031686344

This paper investigates the impact of the service-time threshold and regulation on minimum hourly wage of driver in the ride-hailing platform. The impact is assessed using a market equilibrium queuing model where passengers' fare and drivers' wages are established by the platform. Numerical analysis and managerial insights are provided which indicated that when a large number of passengers are arriving, the platform should operate with regulations on a low wait-time threshold while prioritizing drivers incentives to incorporate fairness for all the stakeholders of ride hailing platform. Managers, therefore, should strive to attract more passengers and drivers to match supply with demand which mitigates trade-off between objectives of all the stakeholders and also incorporate social welfare.

关键词： fair wages non-linear programming regulations ride-hailing wait-time

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DeepPayAuth: User Authentication in Mobile Payments Using Smartwatch Motion Sensors

DeepPayAuth: User Authentication in Mobile Payments Using Sm...

引用

Computing Conference

作者： Matovu, Richard Ohu, Ikechukwu Gannon Univ Erie PA 16541 USA

ISBN: (纸本)9783031622755;9783031622731;9783031622724

Mobile payment systems have become increasingly prevalent due to notable shift in consumer shopping behaviors and preferences over recent years. Smartwatches have been widely adopted for making payments in such systems due to their convenience and flexibility. However, these devices pose serious inherent security risks, for example, if the smartwatch inadvertently lands in malevolent hands, a malicious actor could make hefty unauthorized transactions on behalf of the legitimate user. In this study, we design and evaluate a deep learning-based biometric authentication system called DeepPayAuth, that implicitly verifies the identity of users based on sensor data collected from smartwatches. The system leverages wrist motion sensor data captured as the user taps their smartwatch onto an NFC-enabled terminal during the payment process. Our experimental results show that DeepPayAuth achieves an overall average authentication performance of 89.43% F-score and error rates as low as 0.03 FAR and 0.08 EER, based on accelerometer and gyroscope sensor data collected from a single tap gesture. The results also show that Deep-PayAuth attains high performance in a wide range of real-world conditions. This paper demonstrates a new deep learning model that can implicitly authenticate users in mobile payments based on natural tap gestures exhibited while tapping their smartwatch on the payment terminal.

关键词： Biometrics Authentication Smartwatch Mobile payments Tap gestures Motion sensors

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Perceptions of Academics on Micro-credentials in Higher Education in Mauritius 9th

Perceptions of Academics on Micro-credentials in Higher Educ...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Rajabalee, Yousra Banoor Santally, Mohammad Issack Halkhoree, Roshan Mauritius Inst Educ Reduit Mauritius Univ Mauritius Reduit Mauritius

ISBN: (纸本)9789819735556;9789819735563

The main driver behind the uptake of micro-credentials, according to the World Economic Forum, is the widening gap between traditional higher education and the skills needed to work in the contemporary digital world. Covid-19 further accelerated this transition to digital learning. This research aims to explore the perceptions of the academic community on micro-credentials in the higher education ecosystem in Mauritius. The research, therefore, seeks to capture the current knowledge and readiness of the academic community, regarding micro-credentials and their perception of its applicability, relevance, and challenges for its adoption in higher education. Using the T-O-E framework as a conceptual model, a survey was carried out with academics from public and private higher education institutions. Preliminary findings suggest that there is generally a positive perception toward micro-credentials within the higher education sector. However, respondents have a limited understanding of this concept and do not have a clear picture of how it can be integrated into the current system. The policy-enabling environment emerges as a crucial factor for a successful implementation. This research contributes to existing literature by providing insights into the perceptions of academics in Mauritius regarding micro-credentials and shedding light on potential challenges and opportunities associated with its adoption.

关键词： Micro-credentials Digital learning Higher education Educational technology

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Implementation of Hybrid ANN-GWO Algorithm for Estimation of the Fundamental Period of RC-Frame Structures 1

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2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI)

作者： Dordevic, Filip Marinkovic, Marko Univ Belgrade Fac Civil Engn Bulevar Kralja Aleksandra 73 Belgrade 11000 Serbia

ISBN: (数字)9783031608407

ISBN: (纸本)9783031608391;9783031608407

The fundamental period (T-FP) of vibration is one of the most important parameters in structural design since it is used to assess the dynamic response of the structures. It is the time taken by a structure or system to vibrate back and forth in its most natural way, without any external forces applied. Simultaneously, T-FP depends on the mass distribution and stiffness of the structure, which is largely influenced by infill walls in RC frame structures, and which is why their careful design is necessary. This study aims to develop a fast, accurate, and efficient machine learning (ML) method for the prediction of the fundamental period of masonry-infilled reinforced concrete (RC) frame structures. Hybridization of the stochastic gradient descent (SGD) based artificial neural network (ANN), and meta-heuristic grey wolf optimization (GWO) algorithm is proposed as an effortless computational method. This approach provided even more reliable solutions than the robust second-order procedure based on single ML models. A total of 2178 samples of infilled RC frames were collected from available literature, where the number of storeys (NoSt), number of spans (NoSp), length of spans (LoSp), opening percentage (OP), and masonry wall stiffness (MWS) were considered as input parameters for predicting the output T-FP results. The accuracy and exploration efficiency of the proposed ANN-GWO paradigm have demonstrated superiority over existing seismic design codes and other conventional ML methods.

关键词： Earthquake engineering Machine learning Artificial neural network Grey wolf optimization Infill frames

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Adversarial Robustness of Multi-bit Convolutional Neural networks 1

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Intelligent systems Conference (IntelliSys)

作者： Frickenstein, Lukas Sampath, Shambhavi Balamuthu Mori, Pierpaolo Vemparala, Manoj-Rohit Fasfous, Nael Frickenstein, Alexander Unger, Christian Passerone, Claudio Stechele, Walter BMW Autonomous Driving Unterschleissheim Germany Tech Univ Munich Munich Germany Politecn Torino Turin Italy

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

Deploying convolutional neural networks (CNNs) on resource-constrained, embedded hardware constitutes challenges in balancing task-related accuracy and resource-efficiency. For safety-critical applications, a third optimization objective is crucial, namely the robustness of CNNs. To address these challenges, this paper investigates the tripartite optimization problem of task-related accuracy, resource-efficiency, and adversarial robustness of CNNs by utilizing multi-bit networks (MBNs). To better navigate the tripartite optimization space, this work thoroughly studies the design space of MBNs by varying the number of weight and activation bases. First, the pro-active defensive model MBN3x1 is identified, by conducting a systematic evaluation of the design space. This model achieves better adversarial accuracy (+10.3pp) against the first-order attack PGD-20 and has 1.3x lower bit-operations, with a slight degradation of natural accuracy (-2.4pp) when compared to a 2-bit fixed-point quantized implementation of ResNet-20 on CIFAR-10. Similar observations hold for deeper and wider ResNets trained on different datasets, such as CIFAR-100 and ImageNet. Second, this work shows that the defensive capability of MBNs can be increased by adopting a state-of-the-art adversarial training (AT) method. This results in an improvement of adversarial accuracy (+13.6pp) for MBN3 x 3, with a slight degradation in natural accuracy (-2.4pp) compared to the costly full-precision ResNet-56 on CIFAR-10, which has 7x more bit-operations. To the best of our knowledge, this is the first paper highlighting the improved robustness of differently configured MBNs and providing an analysis on their gradient flows.

关键词： Adversarial robustness Neural network quantization Multi-bit convolutional neural networks

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Investigation of Conditions of Directed Thermal Influence on Changes of Physical and Mechanical Properties of Diamond Grains in a Grinding Wheels 10th

Investigation of Conditions of Directed Thermal Influence on...

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Lavrinenko, Valerii Ilnytska, Halyna Smokvyna, Volodymyr Dasic, Predrag Fedorovich, Vladimir NAS Ukraine Dept Diamond Abras & Phys Tech Proc V Bakul Inst Superhard Mat Str 2 UA-04074 Kiev Ukraine Engn Acad Serbia IAS Belgrade Serbia Natl Tech Univ Kharkiv Polytech Inst Kharkiv Ukraine

ISBN: (纸本)9783031662676;9783031662683

The article presents information on the features and physical and mechanical characteristics of synthetic diamonds made in Ni-Mn-C and FeSi-C systems, their impurity composition. It is proved that in the Fe-Si-C and Ni-Mn-C systems different contents of inclusions and impurities in diamonds are formed, and therefore different ranges of the value of specific magnetic susceptibility, moreover, diamonds of the Ni-Mn-C system have a range of up to 100 center dot 10(-8) m(3)/kg, but for diamonds of the Fe-Si-C system it is larger - from 100 to 1200 center dot 10(-8) m(3)/kg, and, therefore, potentially have much greater opportunities in the directional change their properties. Using scanning electron microscopy, an elemental analysis of the faces of diamond crystal faces synthesized in both systems was performed after their heat treatment, which showed that the surfaces of diamond faces contain impurities and inclusions that are under the influence of high-temperature heating through cracks and pores came to the surface of the faces of the crystals. The analysis of the obtained data indicates that for synthetic diamond grains made in both systems, the effect of increasing the strength of grains under the action of thermal action is triggered only when there is a sufficient number of inclusions in diamonds, and therefore their increased magnetic susceptibility. That is why magnetic diamonds of the Fe - Si - C system give a noticeable effect in increasing the strength of grains during heat treatment. This is explained by the fact that such diamonds, having a significant (up to 7% wt.) number of inclusions have a significant mass base for moving impurities and inclusions during heat treatment to ensure the effect of "healing" defects of the diamond surface. This indicates that the thermal effect on diamonds of low strength depending on the number, type of impurities and inclusions allows to change the surface elemental composition of diamonds, the value of the specific magn

关键词： grinding grinding tool diamonds specific magnetic susceptibility high-temperature heating strength

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The Need for HPC in AI Solutions 6th

The Need for HPC in AI Solutions

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6th International Conference on Cloud Computing and Artificial Intelligence-Technologies and Applications

作者： Ettifouri, Imane Zbakh, Ivlostapha Tadonki, Claude Mohammed V Univ Natl Sch Comp Sci & Syst Anal Rabat Morocco Mines ParisTech PSL Univ Ctr Rech Informat CRI 35 Rue St Honore F-77305 Fontainebleau France

ISBN: (纸本)9783031786976;9783031786983

High-Performance Computing (HPC) aims at providing the most efficient computing support for problems solving. It is basically a conjunction of three components: methods, programming, and machines. When considered as a support to a given paradigm, the main focus is on the last two components. Artificial Intelligence (AI) is becoming a major topic in the computer science landscape, with a broad range of applications that is continuously increasing. Cutting-edge AI is very ambitious and the required computing power to reach the expected level of efficiency is very high, thus the vital need for HPC support. The aim for this chapter is to illustrate the importance of HPC in AI investigations and solutions through a number of selected applications. For each application or AI-oriented study, we illustrate the critical aspect of the execution time, considering training and inference.

关键词： HPC AI Efficiency Parallelism

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Prediction of Rice Using Random Forest Algorithm with Geographical Information System (GIS) 9th

Prediction of Rice Using Random Forest Algorithm with Geogra...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Suarez, Jane Kristine G. Abamo, Jenny Lyn V. AMA Univ Quezon City Philippines

ISBN: (纸本)9789819735587;9789819735594

Farmers' decision-making processes could change if information technology is used to the agricultural industry. In order to anticipate future yield, the researchers in this study used a GIS-based model, automated learning by machine approaches, and extracting valuable insights from datasets. The training set and test data for yield status were built on information acquired from the provincial agriculture. A spatial map showed where the future yield would be at its highest and lowest levels. A prediction model is created in the first stage. In the second stage, a system that estimates future rice yields will be developed utilizing time series analysis and a GIS-based model for visualization. To effectively complete the data mining process, the proponents employed the cross-industry standard method for data mining. An attribute evaluator was used to process the data after it had been preprocessed using WEKA's attribute selection filtering. The twelve abiotic agricultural parameters are climate, humidity level, time of year, elevation, water supply, growing date, amount of land, output per area, growing method, precipitation, sunlight exposure, and wind velocity. The five biotic agricultural variables are soil, saline, fertilizer, rice variety, and insect/pest diseases. The study offers a structure that can be utilized to improve the application of data mining in agriculture. A computed kappa value for the algorithm used to determine whether rice yield status as "high" or "low" was 0.7327, it is significant to recommend that the set of rules was trustworthy. The Provincial Agriculture Office may establish, incorporate, manage, oversee, and carry out all strategies, programs, initiatives, and actions related to the findings of this study.

关键词： Data mining Provincial Agriculture Random forest Rice Yield prediction

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Physics-Informed Neural networks via Stochastic Hamiltonian Dynamics Learning

Physics-Informed Neural Networks via Stochastic Hamiltonian ...

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Intelligent systems Conference

作者： Bajaj, Chandrajit Minh Nguyen Univ Texas Austin Dept Comp Sci Austin TX 78712 USA Univ Texas Austin Dept Math Austin TX 78712 USA Univ Texas Austin Oden Inst Computat Engn & Sci Austin TX 78712 USA

ISBN: (纸本)9783031664274;9783031664281

In this paper, we propose novel learning frameworks to tackle optimal control problems by applying the Pontryagin maximum principle and then solving for a Hamiltonian dynamical system. Applying the Pontryagin maximum principle to the original optimal control problem shifts the learning focus to reduced Hamiltonian dynamics and corresponding adjoint variables. Then, the reduced Hamiltonian networks can be learned by going backwards in time and then minimizing loss function deduced from the Pontryagin maximum principle's conditions. The learning process is further improved by progressively learning a posterior distribution of the reduced Hamiltonians. This is achieved through utilizing a variational autoencoder which leads to more effective path exploration process. We apply our learning frameworks called NeuralPMP to various control tasks and obtain competitive results.

关键词： Reinforcement learning Pontryagin maximum principle Hamiltonian neural network

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