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2024 IEEE Sustainable Smart Lighting World Conference and Expo, LS24 2024

作者： Mahmoudi, Ali Ozcelebi, Tanir Meratnia, Nirvana Eindhoven University of Technology Math. and Computer Science Dept. Eindhoven Netherlands

ISBN: (纸本)9798331540197

Recognizing human activities is necessary to achieve fully context-aware lighting in a smart home. Ambient sensors suit this task as they are ubiquitous, non-intrusive, and non-obstructive. However, each home has a unique floor plan and a unique number and placement of these sensors. This leads to heterogeneity of input data spaces for machine learning models, which hinders their use in different homes. We propose that converting the data into the semantic input space of a language model can not only unify the input space across different houses but also improve the prediction performance thanks to the model's understanding of semantics. We compared a pre-trained BERT model with one trained from scratch to test the proposed semantic conversion on three datasets from CASAS. The results show that the pre-trained model performs better on accuracy and F1-score. © 2024 IEEE.

关键词： Semantics

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Modeling Automatic Emergency Braking System Using Fuzzy Timed Petri Nets Based on the 3-Second Rule

Modeling Automatic Emergency Braking System Using Fuzzy Time...

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2023 IEEE International Conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Serji, A. Mermri, E.B. Blej, M. Mohammed Premier University Dept. of Math. and Computer Science Oujda Morocco

ISBN: (纸本)9798350327816

Automatic Emergency Braking (AEB) systems play a critical role in enhancing road safety by assisting drivers in avoiding or mitigating collisions. This paper proposes a comprehensive method to model AEB systems using Fuzzy Timed Petri Nets tailored for the 3-second rule. The 3-second rule dictates that a vehicle should maintain a safe distance of at least 3 seconds from the advanced vehicle to minimize the risk of forward collisions. It is important to note that this paper's scope is limited to applying the three-second rule under specific conditions. We focus on scenarios where the weather is clear and ideal for driving, the road conditions are standard without any anomalies, and the vehicles involved are in optimal working conditions without mechanical faults. This narrowed focus allows for more in-depth analysis and understanding of the AEB system's performance under these parameters. By incorporating FTPN, which combines the benefits of Timed Petri Nets and fuzzy logic, we can effectively capture timing constraints and uncertainties associated with the AEB system. By integrating Artificial Intelligence (AI) technologies by combining the strengths of Petri Nets and fuzzy logic, FTPN allows us to accurately represent and infer real-time systems while effectively capturing the timing constraints and uncertainties inherent in reliable performance in critical scenarios for our system. Our model aimed at determining the decision of emergency Braking based on rules that consider the vehicle's speed, the distance to the vehicle in front, and the safety distance. An Expert System derives several rules from our database and presents them as Fuzzy Timed Production Rules (FTPR). The conversion from FTPR to FTPN is crucial in building this model since we cannot model this system without the correct formulation of the rules. The based model depicts a real-time system that responds to the surroundings and its speed to determine when it may start braking and to what extent it w

关键词： Artificial Intelligence Automatic Emergency Braking Expert System FTPN FTPR Real-Time System

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A Taxonomic Classification of Insider Threats: Existing Techniques, Future Directions & Recommendations

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Journal of Cyber Security and Mobility 2023年第2期12卷 221-252页

作者： Rauf, Usman Mohsen, Fadi Wei, Zhiyuan Dept. of Math. & Computer Science Mercy College NY United States Information Systems Group Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen9712 CP Netherlands

In the last two decades, the number of rapidly increasing cyber incidents (i.e., data theft and privacy breaches) shows that it is becoming enormously difficult for conventional defense mechanisms and architectures to neutralize modern cyber threats in a real-time situation. Disgruntled and rouge employees/agents and intrusive applications are two notorious classes of such modern threats, referred to as Insider Threats, which lead to data theft and privacy breaches. To counter such state-of-the-art threats, modern defense mechanisms require the incorporation of active threat analytics to proactively detect and mitigate any malicious intent at the employee or application level. Existing solutions to these problems intensively rely on co-relation, distance-based risk metrics, and human judgment. Especially when humans are kept in the loop for access-control policy-related decision-making against advanced persistent threats. As a consequence, the situation can escalate and lead to privacy/data breaches in case of insider threats. To confront such challenges, the security community has been striving to identify anomalous intent for advanced behavioral anomaly detection and auto-resiliency (the ability to deter an ongoing threat by policy tuning). Towards this dimension, we aim to review the literature in this domain and evaluate the effectiveness of existing approaches per our proposed criteria. According to our knowledge, this is one of the first endeavors toward developing evaluation-based standards to assess the effectiveness of relevant approaches in this domain while considering insider employees and intrusive applications simultaneously. There have been efforts in literature towards describing and understanding insider threats in general. However, none have addressed the detection and deterrence element in its entirety, hence making our contribution one of a kind. Towards the end of this article, we enlist and discuss the existing data sets. The data sets can help

关键词： Machine learning

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Studying the Impact of Infrastructure on Cyclist Route Selection: Real-world Data Mining 15

Studying the Impact of Infrastructure on Cyclist Route Selec...

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15th IEEE International Conference on Knowledge Graph, ICKG 2024

作者： Raud, Merlin Hadachi, Amnir Sharma, Rajesh Bertini, Flavio University of Tartu Institute of Computer Science Tartu Estonia University of Parma Dept. of Math. Phys. and Computer Sciences Parma Italy

ISBN: (纸本)9798331508821

Due to urbanisation and increased environmental awareness, many developed countries have put much effort into promoting sustainable mobility modes. Cycling is one option to replace motorised transport in cities. However, this shift often requires the transformation of the urban environment to be more suitable for cyclists. In this paper, we study the spatial and temporal patterns of cyclists and the influence of cycling infrastructure on their route choices using OpenStreetMap street tag information. A dataset of 290,117 unique trips collected over six months in Bologna, Italy, was used to gain insight into cyclist behaviour and preferences in an urban environment. The bicycle in Bologna is used as a means of transportation mainly for short-and medium-distance trips. The analysis of this dataset revealed the routine of cyclists in different periods: peak hours in the workday morning and evening and periods with lower activities during weekends. Generally, cyclists prefer streets with good cycling infrastructure and avoid streets with heavy traffic. In the suburban area, cyclists prefer bigger roads which lead towards the city centre, while in the city centre preference is on roads which avoid narrow streets in the old town. The obtained results may help to grasp the reasons behind specific route preferences, and they can be used to find opportunities to improve cycling infrastructure for a better and safer urban environment. © 2024 IEEE.

关键词： Bicycles

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BERT Goes to SQL School: Improving Automatic Grading of SQL Statements

BERT Goes to SQL School: Improving Automatic Grading of SQL ...

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2023 Congress in computer science, computer Engineering, and Applied Computing, CSCE 2023

作者： Rivas, Pablo Schwartz, Donald R. Quevedo, Ernesto School of Eng. & Computer Science Baylor University Dept. of Computer Science United States School of Computer Science & Math. Marist College Dept. of Computing Technology United States

ISBN: (纸本)9798350327595

Automated grading of SQL queries is a challenging task due to the complexity of the language and the variety of acceptable solutions for a given problem. In this paper, we propose a novel approach that leverages deep learning with a BERT model to understand the syntax and semantics of SQL statements. By training BERT on a dataset of SQL queries and their corresponding grades, we create a model that can automatically grade new questions accurately. Our experiments demonstrate that the proposed methodology achieves high accuracy and consistency in grading SQL queries, outperforming existing state-of-the-art models. Furthermore, we provide an analysis of the model's explainability, revealing a new capability that can be extremely beneficial for understanding the decision-making process. Overall, our work demonstrates the potential of deep learning with BERT for improving the efficiency and accuracy of SQL query grading. © 2023 IEEE.

关键词： bert deep learning machine learning natural language processing sql

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Wireless Security and IoT Device Identification using RF Fingerprinting and Deep Learning 100

Wireless Security and IoT Device Identification using RF Fin...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Quadar, Nordine Chehri, Abdellah Debaque, Benoit Royal Military College of Canada Dept. Math. and Computer Science Kingston Canada Thales-Canada Research and Technology Center QC Canada

ISBN: (纸本)9798331517786

Enhancing the security of wireless networks involves implementing a user authentication method when the fingerprint of a network device is unknown or considered a potential threat. This technique is known as radio frequency (RF) fingerprinting. This paper presents a novel method for RF fingerprinting of Internet of Things (IoT) devices, addressing the challenges of the radio frequency spectrum. The proposed architecture integrates a feature generator module that transforms time-series I/Q samples into a multi-dimensional matrix and a deep learning module inspired by the ResNet-50-1D model. We assess the effectiveness of our approach by analyzing a real-world dataset of BT emissions obtained from 10 commercial IoT devices in two challenging indoor environments. The datasets, made publicly accessible on IEEE Dataport, were gathered using a USRP X300 software-defined radio (SDR) in both line-of-sight (LoS) and rich multipath propagation scenarios. Our method showcases excellent results in the TTS scenario and shows promise in the challenging TTD scenario, considering the complex nature of frequency hopping. The evaluation results emphasize the significance of evaluating RF fingerprinting models in various scenarios and offer valuable insights into the strengths and limitations of our approach in handling radio frequency waveforms. © 2024 IEEE.

关键词： Frequency hopping

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On Vertex-Euclidean Deficiency of Complete Fan Graphs and Complete Wheel Graphs

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Journal of Combinatorial math.matics and Combinatorial Computing 2024年 121卷 41-52页

作者： Gao, Zhen-Bin Guo, Ricky Kwong, Harris Lee, Sin-Min Qiu, Wei College of General Education Guangdong University of Science and Technology Dongguan523000 China Dept. of Computer Science Univ. of Calif. at Los Angeles Los AngelesCA90095 United States Dept. of Math. Sci. SUNY Fredonia FredoniaNY14063 United States 1786 Plan Tree Drive UplandCA91784 United States College of Math. Sci.Harbin Engineering Univ. Harbin150001 China

A simple graph G with p vertices is said to be vertex-Euclidean if there exists a bijection f : V(G) → {1, 2, . . ., p} such that f(v1) + f(v2) > f(v3) for each C3-subgraph with vertex set {v1, v2, v3}, where f(v1) 2) 3). More generally, the vertex-Euclidean deficiency of a graph G is the smallest integer k such that G ∪ Nk is vertex-Euclidean. To illustrate the idea behind this new graph labeling problem, we study the vertex-Euclidean deficiency of two new families of graphs called the complete fan graphs and the complete wheel graphs. We also explore some related problems, and pose several research topics for further study. © 2024 the Author(s)

关键词： Wheels

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Optimal Local Parameters For Hermite Type Cubic Splines 17

Optimal Local Parameters For Hermite Type Cubic Splines

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17th International Conference on Engineering of Modern Electric Systems, EMES 2023

作者： Bica, Alexandru Mihai Laslo, Eugen Crainic, Cristian G. University of Oradea Dept. of Math. and Computer Science Oradea Romania University of Oradea Dept. of Forestry and Forest Eng. Oradea Romania

ISBN: (纸本)9798350310634

The local derivatives of Hermite type cubic splines are optimally determined on each subinterval of a given mesh through a set of five classical interpolation procedures in order to minimize a certain objective function. We construct an iterative method that selects on each subinterval, the adequate algorithm for providing the local derivatives which minimize the objective function such that the values of the local derivatives computed at the previous subinterval are preserved in order to keep the smoothness of the spline. The admissible set of classical interpolation procedures consists of the natural cubic spline, the Catmull-Rom cubic spline, the Akima's cubic spline, and the cubic splines with minimal derivative oscillation and those with minimal deviation by the data polygon. A numerical experiment is presented in order to illustrate the performances of the algorithm. © 2023 IEEE.

关键词： Interpolation

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Towards Low-Code Architecture and Development of Embedded Systems

Towards Low-Code Architecture and Development of Embedded Sy...

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IEEE International Conference on Software Architecture Workshops (ICSAW)

作者： Felipe Xavier Loek Cleophas Michel R. V. Chaudron Dept. of Math. and Computer Science Eindhoven University of Technology Eindhoven Netherlands

ISBN: (数字)9798331533366

ISBN: (纸本)9798331533373

While the interest in low-code platforms grows, these technologies have mostly focused on administrative business applications, and other domains remain relatively untouched. We think much can be gained from introducing low-code concepts and tools to the embedded systems domain, which still suffers from a relatively complex development cycle. This paper presents a roadmap for creating an approach that allows the generalization of embedded software development through a low-code platform. We highlight five main tasks required to accomplish this endeavor, which will be researched in the near future: 1) studying existing low-code development characteristics; 2) defining a reference architecture for embedded systems; 3) identifying prevailing embedded system design patterns; 4) designing a multi-view approach with a consistent visual language; and 5) integrating formal verification into the platform.

关键词： Visualization Embedded systems Software architecture computer architecture Programming Reliability engineering Software reliability DSL Embedded software Guidelines

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Exploring Mixed-Grid Environments for Drone-Based Last-Mile Logistics Optimization 20

Exploring Mixed-Grid Environments for Drone-Based Last-Mile ...

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20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Sorbelli, Francesco Betti Coro, Federico Pinotti, Cristina M. Shende, Anil University of Perugia Dept. of Computer Science and Mathematics Italy University of Padua Dept. of Mathematics Italy Roanoke College Dept. of Math. CS & Physics United States

ISBN: (纸本)9798350324334

In recent years, drone-based delivery systems have gained significant attention for last-mile logistics in various domains. This study focuses on optimizing drone deliveries in mixed-grid environments, which combine urban and rural areas. The objective is to minimize the sum of distances between the delivery locations and the drone's depot. By selecting the optimal depot placement, we aim to improve factors such as expected delivery time, energy consumption, and environmental impacts. To address this optimization problem, we conducted a comprehensive comparison of several state-of-the-art algorithms specifically designed for computing the drone placement in mixed-grid environments. Our evaluation utilized synthetic and quasi-real data and two distinct scenarios were considered: the full-grid scenario, and the partial-grid scenario. Through empirical analyses, we demonstrate the effectiveness of the proposed algorithms and provide valuable insights into their trade-offs in terms of performance and time complexity. © 2023 IEEE.

关键词： Drones

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