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Driving Activity Classification Using Deep Residual Networks Based on Smart Glasses Sensors

Intelligent Automation & Soft Computing 2023年第11期38卷 139-151页

作者： Narit Hnoohom Sakorn Mekruksavanich Anuchit Jitpattanakul Department of Computer Engineering Image Information and Intelligence LaboratoryFaculty of EngineeringMahidol UniversityNakhon Pathom73170Thailand Department of Computer Engineering School of Information and Communication TechnologyUniversity of PhayaoPhayaoThailand Department of Mathematics Faculty of Applied ScienceKing Mongkut’s University of Technology North BangkokBangkok10800Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Science and Technology Research InstituteKing Mongkut’s University of Technology North BangkokBangkok10800Thailand

Accidents are still an issue in an intelligent transportation system,despite developments in self-driving technology(ITS).Drivers who engage in risky behavior account for more than half of all road *** a result,reckless driving behaviour can cause congestion and *** vision and multimodal sensors have been used to study driving behaviour categorization to lessen this *** research has also collected and analyzed a wide range of data,including electroencephalography(EEG),electrooculography(EOG),and photographs of the driver’s *** the other hand,driving a car is a complicated action that requires a wide range of body *** this work,we proposed a ResNet-SE model,an efﬁcient deep learning classiﬁer for driving activity clas-siﬁcation based on signal data obtained in real-world trafﬁc conditions using smart ***-to-end learning can be achieved by combining residual networks and channel attention approaches into a single learning *** data from 3-point EOG electrodes,tri-axial accelerometer,and tri-axial gyroscope from the Smart Glasses dataset was utilized in this *** performed various experiments and compared the proposed model to base-line deep learning algorithms(CNNs and LSTMs)to demonstrate its *** to the research results,the proposed model outperforms the previous deep learning models in this domain with an accuracy of 99.17%and an F1-score of 98.96%.

关键词： Smart glasses human activity recognition deep learning wearable sensors driving activity

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Forecasting the daily flow of the black water river using soft-computing techniques

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WSEAS Transactions on Information science and Applications 2007年第1期4卷 190-195页

作者： Baareh, Abdel Karim M. Sheta, Alaa F. Al Khnaifes, Khaled Computer Science Department Al-Balqa Applied University Ajlune College Al-Salt Jordan Information Technology Department Al-Balqa Applied University Al-Salt Jordan Mathematics Department Damascus University Damascus Syria

This paper presents a comparative study of three types of the models to solve the river forecasting problem of the daily flow forecast of the Black water river in the USA. They are, the conventional Auto-Regression (AR) model and the two soft-computing models namely the Feed forward neural network (NN) and the fuzzy logic (FL) models. The soft computing models were trained, using the actual daily flow of six water years, and tested, using the actual daily flow of one water year. Data was collected to model the dynamics of the Black River flow models from 01 Oct 1990 to 30 Sept 1996. A comparison of the proposed models and techniques are presented for predicting one water year ahead, from 01 Oct 1996 to 30 Sept 1997. Simulation results indicate that the fuzzy model outperform the neural network and the auto-regression models. Hence, fuzzy logic is recommended as a tool for river flow forecasting.

关键词： Flow of water

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Discretization of the Cir Process Under Volatility Uncertainty Androbust Monte Carlo Simulation: An Application to Pricingguaranteed Equity-Linked Life Insurance Contract

SSRN

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SSRN 2024年

作者： Akhtari, Bahar Payandeh Najafabadi, Amir T. Department of Applied Mathematics and Computer Science Faculty of Mathematics and Statistics University of Isfahan Isfahan81746-73441 Iran Department of Actuarial Science Faculty of Mathematical Sciences Shahid Beheshti University Tehran Iran

The non-negativity property of the CIR process driven by a G-Brownian motion makes it avaluable tool for term structure modeling in the fields of finance and insurance *** paper focuses on two specific types of guaranteed equity-linked contracts that are tiedto a financial asset whose price evolution follows the CIR process driven by G-Brownianmotion. The primary objective of this study is to assess the pricing of these contractsusing a robust expectation framework for the associated payoffs. To achieve this objective,we begin by developing a computationally efficient method to approximate the underlyingprocess while retaining key qualitative aspects of the model. We then demonstrate thenumerical convergence of this method. Subsequently, we introduce a robust Monte Carlotechnique that relies on a nite set of independent sample paths of the guaranteed payoffsat maturity to attain the desired outcome. © 2024, The Authors. All rights reserved.

关键词： Insurance

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BRAIN-TO-TEXT DECODING WITH CONTEXT-AWARE NEURAL REPRESENTATIONS AND LARGE LANGUAGE MODELS

arXiv

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arXiv 2024年

作者： Li, Jingyuan Le, Trung Fan, Chaofei Chen, Mingfei Shlizerman, Eli Department of Electrical and Computer Engineering University of Washington United States Department of Computer Science Stanford University United States Department of Applied Mathematics Department of Electrical and Computer Engineering University of Washington United States

Decoding attempted speech from neural activity offers a promising avenue for restoring communication abilities in individuals with speech impairments. Previous studies have focused on mapping neural activity to text using phonemes as the intermediate target. While successful, decoding neural activity directly to phonemes ignores the context dependent nature of the neural activity-to-phoneme mapping in the brain, leading to suboptimal decoding performance. In this work, we propose the use of diphone - an acoustic representation that captures the transitions between two phonemes - as the context-aware modeling target. We integrate diphones into existing phoneme decoding frameworks through a novel divide-and-conquer strategy in which we model the phoneme distribution by marginalizing over the diphone distribution. Our approach effectively leverages the enhanced context-aware representation of diphones while preserving the manageable class size of phonemes, a key factor in simplifying the subsequent phoneme-to-text conversion task. We demonstrate the effectiveness of our approach on the Brain-to-Text 2024 benchmark, where it achieves state-of-the-art Phoneme Error Rate (PER) of 15.34% compared to 16.62% PER of monophone-based decoding. When coupled with finetuned Large Language Models (LLMs), our method yields a Word Error Rate (WER) of 5.77%, significantly outperforming the 8.93% WER of the leading method in the benchmark. Copyright © 2024, The Authors. All rights reserved.

关键词： Brain mapping

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Towards Dual-Issue Single-Path Code

Towards Dual-Issue Single-Path Code

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International Symposium on Object-Oriented Real-Time Distributed Computing

作者： Emad Jacob Maroun Martin Schoeberl Peter Puschner Institute of Computer Engineering Vienna University of Technology Vienna Austria Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark

ISBN: (数字)9781728169583

ISBN: (纸本)9781728169590

The Patmos instruction-set architecture is designed for real-time systems. As such, it has features that increase the predictability of code running on it. One important feature is its dual-issue pipeline: instructions may be organized in bundles of two that are issued and executed in parallel. This increases the throughput of the processor in a predictable manner, but only if the compiler makes use of ***-path code is a code-generation technique that produces predictable executions by always following the same trace of instructions. The Patmos compiler can already produce single-path code, but it does not use the second issue slot available in the processor. This is less than ideal because the single-path transformation results in code that has a high degree of instruction-level *** this paper, we present a single-path code generator that can produce bundled instructions. It includes generic support for bundling algorithms, such that implementing them is simple and does not require changing other parts of the *** also present one such bundling algorithm plugged into the single-path code generator. With it, we show that we can produce dual-issue instructions to improve performance.

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Open-source verification with Chisel and Scala

arXiv

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arXiv 2021年

作者： Dobis, Andrew Petersen, Tjark Rasmussen, Kasper Juul Hesse Tolotto, Enrico Damsgaard, Hans Jakob Andersen, Simon Thye Lin, Richard Schoeberl, Martin Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark Department of Electrical Engineering and Computer Sciences UC Berkeley BerkeleyCA United States

Performance increase with general-purpose processors has come to a halt. We can no longer depend on Moore’s Law to increase computing performance. The only way to achieve higher performance or lower energy consumption is by building domain-specific hardware accelerators. To efficiently design and verify those domain-specific accelerators, we need agile hardware development. One of the main obstacles when proposing such a modern method is the lack of modern tools to attack it. To be able to verify a design in such a time-constrained development method, one needs to have efficient tools both for design and verification. This paper thus proposes ChiselVerify, an open-source tool for verifying circuits described in any Hardware Description Language. It builds on top of the Chisel hardware construction language and uses Scala to drive the verification using a testing strategy inspired by the Universal Verification Methodology (UVM) and adapted for designs described in Chisel. ChiselVerify is created based on three key ideas. First, our solution highly increases the productivity of the verification engineer, by allowing hardware testing to be done in a modern high-level programming environment. Second, the framework functions with any hardware description language thanks to the flexibility of Chisel blackboxes. Finally, the solution is well integrated into the existing Chisel universe, making it an extension of currently existing testing libraries. We implement ChiselVerify in a way inspired by the functionalities found in SystemVerilog. This allows one to use functional coverage, constrained-random verification, bus functional models, transaction-level modeling and much more during the verification process of a design in a contemporary high-level programming ecosystem. © 2021, CC BY-SA.

关键词： General purpose computers

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A unified weighting framework for evaluating nearest neighbour classification

arXiv

引用

arXiv 2023年

作者： Lenz, Oliver Urs Bollaert, Henri Cornelis, Chris Leiden Institute of Advanced Computer Science Leiden University Leiden2333 CA Netherlands Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent9000 Belgium

We present the first comprehensive and large-scale evaluation of classical (NN), fuzzy (FNN) and fuzzy rough (FRNN) nearest neighbour classification. We standardise existing proposals for nearest neighbour weighting with kernel functions, applied to the distance values and/or ranks of the nearest neighbours of a test instance. In particular, we show that the theoretically optimal Samworth weights converge to a kernel. Kernel functions are closely related to fuzzy negation operators, and we propose a new kernel based on Yager negation. We also consider various distance and scaling measures, which we show can be related to each other. Through a systematic series of experiments on 85 real-life classification datasets, we find that NN, FNN and FRNN all perform best with Boscovich distance, and that NN and FRNN perform best with a combination of Samworth rank- and distance-weights and scaling by the mean absolute deviation around the median (r1), the standard deviation (r2) or the semi-interquartile range (r∞∗ ), while FNN performs best with only Samworth distance-weights and r1- or r2-scaling. However, NN achieves comparable performance with Yager-21 distance-weights, which are simpler to implement than a combination of Samworth distance- and rank-weights. Finally, FRNN generally outperforms NN, which in turn performs systematically better than FNN. © 2023, CC BY-NC-ND.

关键词： Nearest neighbor search

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A quality of service architecture that combines resource reservation and application adaptation

A quality of service architecture that combines resource res...

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International Workshop on Quality of Service

作者： I. Foster A. Roy V. Sander Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA Department of Computer Science University of Chicago Chicago IL USA Central Institute for Applied Mathematics Forschungszentrum Juelich GmbH Julich Germany

Reservation and adaptation are two well-known and effective techniques for enhancing the end-to-end performance of network applications. However, both techniques also have limitations, particularly when dealing with high-bandwidth, dynamic flows: fixed-capability reservations tend to be wasteful of resources and hinder graceful degradation in the face of congestion, while adaptive techniques fail when congestion becomes excessive. We propose an approach to quality of service (QoS) that overcomes these difficulties by combining features of reservations and adaptation. In this approach, a combination of online control interfaces for resource management, a sensor permitting online monitoring, and decision procedures embedded in resources enable a rich variety of dynamic feedback interactions between applications and resources. We describe a QoS architecture, GARA, that has been extended to support these mechanisms, and use three examples of application-level adaptive strategies to show how this framework can permit applications to adapt both their resource requests and behavior in response to online sensor information.

关键词： Quality of service Resource management Degradation Application software mathematics computer science Condition monitoring Feedback Sensor phenomena and characterization Bandwidth

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Sensors Location Problem for Stochastic Non-Linear Discrete-Time Distributed Parameter Systems

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IFAC Proceedings Volumes 1989年第4期22卷 479-484页

作者： J. Korbicz P. Gawłowicz Polytechnical Institute of Zielona Gόra Department of Applied Mathematics and Computer Science ul. Podgόrna 50 65-246 Zielona Gόra Poland

This report deals with the problem of determining the suboptimal measurement scheduling for a stochastic discrete-time distributed parameter systems (DPS) described by a non-linear partial differential equations. The discrete-scanning observations are realized by the suboptimal selection of measurement data from spatially-fixed sensors. The problem statement is in such a form so that the stochastic matrix principle of Pontryagin can be applied to obtain the necessary conditions for optimality. Based on successive approximation of the suboptimal filtering equations, a computationally advantageous approach is developed to obtain the algorithm without solving the non-linear two-point boundary-value problem CTPBVP). An illustrative numerical exemple for a air pollution process is given.

关键词： Distributed parameter systems sensors location state estimation stochastic matrix maximum principle

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Seeking optimal Human/Machine collaborative practice in antisemitic terminology detection

Seeking optimal Human/Machine collaborative practice in anti...

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2024 IEEE Digital Platforms and Societal Harms, DPSH 2024

作者： Melillo, Wendy Emami, Jessica Guarinos, Solene Kikkisetti, Dhanush Klein, Melanie Liubovich, Lisa Mustafa, Raza Ul Japkowicz, Nathalie American University Journalism Division School of Communication United States American University College of Arts and Science Department of Sociology United States American University College of Arts and Science Department of Mathematics United States American University Justice Law and Criminology School of Public Affairs United States American University Data Science for Applied Public Affairs School of Public Affairs United States American University College of Arts and Science Department of Computer Science United States

ISBN: (纸本)9798350351309

This study is concerned with the use of antisemitic language on loosely moderated extremist alt-right social media. It compares, contrasts, and combines human-and machinebased approaches for discovering antisemitic coded or noncoded terminology in such media. Coded terminology refers to the language used in closed-knit communities to communicate beliefs and attitudes without expressing them explicitly. In noncoded discourse, the views of the writer are expressed more explicitly. The detection and analysis of antisemitic terminology in social media is an important problem that can help uncover and monitor the evolution of societal attitudes towards the Jews, and eventually, towards other minority groups once we expand our study. Given the growing prevalence of antisemitic rhetoric in online public spaces, there is a greater need for academic studies to determine its presence and identify strategies to curb its influence. Scholars have noted how intolerant expressions can threaten democratic values. Antisemitic content, like other forms of hate speech, has the potential to radicalize people who may commit violence based on their prejudicial viewpoints. The purpose of this paper is to discuss three different approaches for discovering antisemitic terminology on social media. In particular, it describes an experiment in which three groups-human, software, and mixed-"competed' on the task of retrieving antisemitic terminology over a two-month period (January-February, 2024). The results were manually evaluated for relevance and frequency of occurrence in the next month period (March 2024). The study shows that each group discovered valuable terminology and that neither the human nor the machine group could replace the other. Instead, we advocate that both groups work together using their respective knowledge to optimize the discovery of new terminology on social media. © 2024 IEEE.

关键词： Terminology

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