Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive event-triggered security control for nonlinear CPS under DoS attack

This research studies the co-designing security control and adaptive event-triggered communication for a nonlinear CPS that experiences DoS attacks and actuator faults. First, a new communication scheme that adjusts adaptively to events is developed, and the threshold for triggering this scheme dynamically varies based on the state of the system, resulting in a more efficient utilization of network communication resources. Additionally, utilizing ADETCS as a foundation, a structure for safeguarding nonlinear CPS is constructed. Thirdly, the assistance of Lyapunov theory, time delay system theory and less conservativeness techniques are utilized, a observer is designed to observe the estimation of state and fault in real time, along with a security controller to ensure tolerance against attacks and faults. Finally, the simulation case of the classical quadruple-tank model is adopt to verify the viability and efficiency of the proposed approach.
Index Fund Portfolios Efficiency on the Stock Markets of the Russia, USA, Germany and China for 2012-2022

An analysis of the performance indicators of index investment portfolios of the Russian Federation, the USA, Germany and China stock markets for 2012-2022 was carried out. The most effective methods for optimizing index portfolios have been identified. An analysis and comparison of factors influencing the efficiency of index portfolios of various stock markets was carried out. Recommendations are proposed to improve the efficiency of index investment portfolios of the stock markets under consideration
A Semantic Segmentation Method of Front-View Pavement Distress Based on SegFormer

Pavement distress segmentation and recognition is an important research direction of applying computer vison technology to intelligent traffic inspection. At present, most of the existing studies have used the perspective of overlooking to segment and detect pavement distress, and the types are single, most of them are segmentation and identification of crack distress. In addition, for the semantic segmentation of pavement distress in the front-view, there is a lack of public multi-type distress datasets for experiments. Aiming at the above situations, this study uses Encoder-Decoder to build SegFormer network structure to realize multi-category segmentation and recognition system for front-view pavement distress, and made a self-made front-view pavement distress Chongqing datasets applicable to domestic road traffic situation. Chongqing datasets consists of 1015 images with pixels of 1920x1080, which have been collected from real-word road sections with 11 different distress categories. SegFormer has achieved MIoU of 69.75% and the distress categories segmentation accuracy of 97.72% in the training and testing of the Chongqing data set. The successful application of this study not only provides a new perspective for the research in the field of front-view pavement distress segmentation, but also provides strong support for the application and further exploration in related fields. Chongqing Dataset will be released at: https://gitee.com/orangeYJ/chongqing-pavement-dataset
Sampling Strategies for Compressive Imaging Under Statistical Noise

Most of the compressive sensing literature in signal processing assumes that the noise present in the measurement has an adversarial nature, i.e., it is bounded in a certain norm. At the same time, the randomization introduced in the sampling scheme usually assumes an i.i. d. model where rows are sampled with replacement. In this case, if a sample is measured a second time, it does not add additional information. For many applications, where the statistical noise model is a more accurate one, this is not true anymore since a second noisy sample comes with an independent realization of the noise, so there is a fundamental difference between sampling with and without replacement. Therefore, a more careful analysis must be performed. In this short note, we illustrate how one can mathematically transition between these two noise models. This transition gives rise to a weighted LASSO reconstruction method for sampling without replacement, which numerically improves the solution of high-dimensional compressive imaging problems.
Approaches to Diagnostics of Natural-monopoly Properties of Extra-urban Transport Networks

Model approaches are proposed, and computational procedures for assessing technological characteristics of the network transport subsystems operation and development are elaborated, which make it possible to clarify the influence of the natural monopoly synergy effect. Calculation results are presented for various formulations of the problems of diagnosis on natural monopoly properties concerning extra-urban regional transport networks based on models of natural monopoly normative identification).
The Coordinated Charging Pricing Approach for Charging Stations with Multi-Agent Deep Reinforcement Learning

As the number of electric vehicles on the road increases, there is a corresponding rise in the number of charging facilities available. To entice electric vehicle owners to utilize their services, more operators are entering the market with competitive pricing incentives for charging. However, it is important to implement a pricing mechanism that strikes a balance between supply and demand and avoids the issues of under or over-supply, ultimately leading to rational utilization of resources. An appropriate pricing mechanism can also promote healthy and sustainable growth of the industry. To achieve the desired outcome and develop the synergy of charging facility operators in a competitive environment, we propose a multi-intelligence-based collaborative pricing mechanism for charging facility operators. This mechanism ensures a balance of revenue among multiple operators and prevents harmful price competition between charging facility operators. To learn the coordinated charging pricing strategy, we adopt the multi-agent deep deterministic policy gradient method. This approach incorporates the response pattern of mobility-on-demand vehicles to provide an optimal solution for charging pricing strategies.
On One Approach to the Construction of a Non-Dissipative Kinematic Dynamo on a Non-Compact Manifold

The article discusses models of large-scale objects in which the effect of a non-dissipative kinematic dynamo takes place. A dynamo design is constructed for finite divergence-free vector fields and diffeomorphisms in n— dimensional space. The approach uses the construction of prolonging a vector field from the unit sphere to a divergence-free finite vector field in space.
Automated Test Case Generation for Service Composition from Event Logs

Service compositions, e.g., Internet of Things (IoT) compositions or RESTful service compositions are widely used in the industry to enhance the interoperability and integration of their systems and applications. Testing service compositions is long and difficult activity as each service may be deployed on different servers and often requires specialised testing tools. In order to help developers in this activity, this paper proposes an automated approach to generate test cases for experimenting every service in isolation. These test cases can be later adapted or used for regression testing. This approach is based upon 4 steps that aim to: 1. extract traces from event logs, 2. gather similar behaviours to reduce the final test case number and to extract knowledge that will be used during the test case generation, 3. produce generic test cases given under the form of IOTS (Input Output Transition Systems) that encode the use of mock components and provide test verdicts, 4. generate test scripts and mock components for every testable service. We report experimental results obtained from 4 case studies and show that our algorithms build effective test cases and scale well with the event log size.
Integrated, Language Oriented Cyber Security Glossary

The article describes an integrated, language-oriented glossary of cyber security, created as a result of research and student activity at the Department of Informatics and Cyber Operations of the University of Defense in Brno. Its characteristics and goals to support teaching and learning are given. An important feature of the glossary is its multilingualism. In addition to the current version of the glossary in Czech, it is proposed to create a version in Slovak, with the potential for development by other languages (Polish, Hungarian) of the Visegrad 4 countries. A similar glossary has not yet been created, according to the conclusions of the literature search, it is highly desirable. It will make it possible to get to know the whole area well, the harmonized terms of the glossary will especially support teaching and research when they will be freely accessible from the Internet. The conditions and requirements for the development of the cyber security glossary are given, as well as methodological procedures for adding a Slovak version to the Czech glossary. This is a project – proof of concept, which is supposed to confirm the feasibility of the glossary's intention. The cooperating organization is the Department of Informatics of the Armed Forces Academy of General Milan Rastislav Stefanik, Liptovsky Mikulas, Slovak Republic.
Kinematic Model and Stable Control Law Proposed for Four Mecanum Wheeled Mobile Robot Platform Based on Lyapunov Stability Criterion

Transportation in warehouses and production workshops is a matter of urgency today. Most warehouses arrange routes for circulation along the shelves, transportation vehicles will move on this road to perform the task of exporting or importing goods. Routes will be arranged to move in one direction because vehicles do not have enough space to turn around in cramped warehouses. This causes many difficulties in planning the trajectory for transportation vehicles, especially self-propelled vehicles. In order to have an appropriate transportation plan, it is necessary to solve many problems, including: reasonable transport equipment, sufficient number of devices, optimal route layout, algorithm of operation center for Positioning and Navigation of transportation equipment. This study proposes a method for transportation using an omnidirectional automated guided vehicle (AGV). The AGV's omnidirectional mobility is supported by the mecanum wheels, so vehicles can move in multiple directions on the road without turning, even at a junction or an intersection. This study consists of two parts, the first part focuses on kinematic modeling for mecanum wheels and extends to robot’s platform using four mecanum wheels. Part two proposes a diagram to calculate the errors of the robot compared to a reference tracking line, design a control law based on the Lyapunov stability criterion. The stability of the control law is verified and confirmed by simulation on Matlab environment.
A Hybrid Remaining Useful Life Prognosis Method Integrating Transformer Networks and Wiener process

Remaining useful life (RUL) prediction is the key part in prognostics and health management (PHM) which has proven effective for reliability strengthening, availability improving and cost saving. It is difficult to quantify the level of uncertainty of the RUL prediction model based on deep learning, and the stochastic process based model has some limitations in handing complex and mass data. Therefore, a Wiener process model for RUL prediction integrating Transformer neural network is proposed in this paper. Firstly, the historical data is filtered and smoothed, and the corresponding degradation trend in the processed historical data is extracted by the complete EEMD with adaptive noise (CEEMDAN) method. Based on the obtained degradation trend, the training data set, and test data set have been constructed through moving window skills to train a simplified Transformer neural network. An adaptive identification of the Wiener drift coefficient function is performed using the trained Transformer neural network. Then, the analytical probability density function of RUL based on the first passage time (FPT) has been derived. The proposed method has been illustrated by using the public Lithium-ion batteries capacity degradation data provided by NASA.
Constructing Weighted Host Communication Networks for Intrusion Detection based on Complex Network Theory

As the scope of the Internet continues to broaden, there is an exponential surge in network data, accompanied by a simultaneous escalation of cybersecurity issues. To accurately identify the source of intrusion within a compromised network, this paper proposes an intrusion detection method based on complex network theory. In this method, the network hosts are regarded as nodes, the communication relationships between hosts are seen as edges, and the communication traffic features are mapped as weights to construct weighted host communication networks. Subsequently, complex network metrics that assess the significance of host nodes are extracted. These metrics are then combined with an anomaly detection model to achieve intrusion detection. The proposed method has been verified through testing on two datasets, namely the CIC-IDS-2017 and DAPT2020 datasets. And the experimental results substantiate that the method demonstrate a positive intrusion detection performance, outperform the compared anomaly detection models.
Risk-Aware Intrusion Detection and Prevention System for Automated UAS

This paper designs a proof-of-concept for a Deep Learning-based IDS for UAS. As the drone market grows, safety becomes crucial. Unmanned Aircraft System (UAS) attacks can endanger lives and facilities. With the increasing complexity of attacks, detection has become challenging. Machine Learning-based Intrusion Detection System (IDS), trained on the CSE-CIC-IDS2018 dataset, can handle defined attacks. Combining IDS with an Intrusion Prevention System(IPS), using Threat Analysis and Risk Assessment (TARA) from the automotive domain ensures the system’s safety even after attacks. The implementation involves Raspberry Pi as an attacker and defender. The ISO/SAE 21434 standard serves as the foundation for cybersecurity adaptation.
Value Peripheral Register Values for Fuzzing MCU Firmware

Analyzing the security of MCU firmware is important. Fuzzing with peripheral model emulation is proven successful due to its independence of hardware and practicality. However, prior efforts such as DICE and P2IM expose two issues: insufficient exploration of peripheral states and inadequate handling of abnormal behaviors. Our key insight is that peripheral register values are vital for fuzzing MCU firmware. We present a novel approach called VeRa which introduces several techniques: peripheral state triage, rollback explorative execution, low-frequency-first schedule for control-status register values, and random selection for status register values. We integrated VeRa to a state-of-the-art firmware analyzer DICE and evaluated on 122 firmware covering 11 MCU platforms. Evaluation results show that 1) on modeling peripherals, VeRa passed more 45 out of 99 sample firmware than DICE; 2) VeRa outperforms DICE on fuzzing 23 real-world firmware, with 1.4× basic block coverage and 3.1× path coverage on average (up to 13.2× and 33.7×, respectively); 3) The overhead of VeRa is fairly low, adding 5.6% and 1.2% on average to modeling time and fuzzing time respectively; 4) VeRa discovered 3 unique new bugs that DICE cannot find.
Optimal Battery Swapping and Charging Strategy Considering On-Site Solar Generation

Battery swapping stations (BSSs) are considered as the most promising approach to provide the electric vehicles (EVs) refueling services, due to the process of battery swapping is rapid, taking up less space and aggregating the charging load with uncertainty. Optimizing the charging operation scheduling plays an important role in the operation of BSS, since it can reduce the operation cost and is conducive to the operation of BSS. This paper considers that the on-site solar generation in the BSS which is composed of fully battery inventory, depleted battery inventory and charging area. This paper focuses on the problem of optimizing the charging operation scheduling of BSS, and proposes an operation model of BSS, modeling the charging operation scheduling problem as an integer nonlinear programming problem, which is transformed into an integer linear programming problem through linearization. The case study shows the charging operation scheduling of BSS considering on-site solar generation, and verifies the feasibility of the operation model of BSS.
Adoption of water conservation practices in the society and comparison evaluation study

This paper presents the recent developments in the field of water conservation that have substantial practical implications for water policies, programs, and projects. Water saving and developing water conservation society are the keys to realize both for wise water allocation and the sustainable utilization. In accordance to the scientific, practical, and simple principals, the paper sets up a hierarchy evaluation index system to estimate the advances in constructing water conservation society. Also, a comparing study is carried out in the provinces and cities in China to understand the situation and the impact on the practice of water conservation. The paper suggests that water conservation is a large systematic project that in vovles lots of sectors, industries and departments.
Soil organic carbon in tree-based intercropping systems of Quebec and Ontario, Canada

ABSTRACT M.Sc.Amanda D. BambrickNatural Resource Sciences Tree-based intercropping (TBI) is an agroforestry system where a crop, generally an annual, is planted between established tree rows. TBI systems have a greater potential for carbon storage than conventional cropping systems because carbon is stored in the biomass of growing trees and trees provide additional carbon inputs (leaves, roots) that contribute to the soil organic carbon (SOC) pool. Differences in the litter quality and amount of litter deposited in the tree row versus the intercropped space are expected to generate spatial heterogeneity in the SOC pool. The objectives of this work were to evaluate the spatial variability of the SOC pool in TBI systems, to compare SOC stocks in the TBI system with a nearby conventional agroecosystem, and to describe the SOC dynamics in a TBI system using the ecosys model. Research sites included in this study were 4-year old TBI sites at St. Paulin and St. Edouard (Quebec, Canada), an 8-year old TBI site in St. Remi, Quebec, and a 21 year old TBI site in Guelph, Ontario, Canada. Spatial heterogeneity in SOC pools due to the presence of trees was observed in two of the four sites, but obscured by field variability at one site and even distribution of leaf litter associated with large trees at the oldest TBI site. The SOC pool increased in older TBI sites, relative to the nearby conventional agroecosystem, but the magnitude of SOC change was affected by the land use history. A simulation of changes in SOC using the ecosys environmental model predicted a 5.0% decrease in SOC pools twenty-one years after the site was converted to TBI, while field experiments showed a 12% increase in the SOC pool compared to the conventional agroecosystem. A spatial algorithm that describes the distribution of trees and crops in TBI systems would improve ecosys model predictions. Overall, field results suggest that the trees growing in TBI systems will increase SOC levels after a n%%%%RESUMEM.Sc. Amanda D. BambrickSciences de ResourcesNaturellesUn systeme de culture intercalaire (SCI) est un systeme d’agrosylviculture ou une recolte, generalement annuelle, est etablie entre les rangees d'arbres plantees. Le SCI a un potentiel important pour etre adoptes dans les regions temperees du aux avantages environnementaux lies a ces systemes. Un tel avantage environnemental fourni par SCI est le stockage accru de carbone dans les sols et la biomasse des plantes. Le SCI a un potentiel important pour le stockage de carbone (C) car il contienne de carbone dans la biomasse des arbres croissants, et l’ajout au sol des resides d’arbres (feuilles, racines) contribuent au C organique du sol (SOC). On s'attend a ce que des differences dans la qualite et la quantite des resides organiques deposees dans la rangee d'arbre contre l'espace intercalaire produisent de l'heterogeneite spatiale de SOC. Les objectifs de cette these etaient i) d'evaluer la variabilite spatiale de SOC dans le SCI, ii) comparer des stocks de SOC dans le SCI a un agro-ecosysteme…
The discovery of OIB-type potassic tholeiitic basalts from the Ganjia Area in West Qinling: Implications for the Late Mesozoic continental rift of West Qinling

The Late Mesozoic volcanic rocks of West Qinling Area exposed in the Duofutun Area of Zeku County,Qinghai Province and the Hongqiang and Ganjia areas of Xiahe County,Gansu Province.Preliminary study showed that the Ganjia volcanic rocks belong to potassic tholeiitic basalts.The rocks are enriched in REE,LILE and HFSE,but the fractionation degree of LREE and HREE and the incompatible element contents are slightly lower than those of typical OIB and the Late Mesozoic sodic alkaline basalts of West Qinling.The magma of these basaltic rocks were originated from the lithosphere metasomatized by small-volume,volatiles-enriched,asthenosphere-derived silicate melts and had undergone a large degree of fractional crystallization of mafic minerals.These K-tholeiitic basalts,bearing the typical petrogenetic characteristics of intracontinental OIB,not only differ from the Ganjia seamount basalts suggested by previous authors,but also are not the member of the "Permian Longwuxia-Ganjia ophiolite". These rocks together with the Late Mesozoic sodic alkaline basalts of West Qinling are both the products of the OIB-type magmatism in the Late Mesozoic continental rift system of West Qinling.The Ganjia basalts may have a more complex assemblage of different basaltic rocks,and have a longer time span from the Late Paleozoic to the Late Mesozoic.The Late Mesozoic continental rift of West Qinling died young in the early stage of the lithospheric extension,whose occurrence and the widespread development of the near-SN or NW faults in the studied area,may be the performance of the interaction and reworking of the complexly superimposed Helan-Sichuan-Yunnan N-S trending tectonic belt with the large scale strike-slip fault system.
Digital Halftoning via Mixed-Order Weighted Σ∆ Modulation

In this paper, we propose 1-bit weighted Σ∆ quantization schemes of mixed order as a technique for digital halftoning. These schemes combine weighted Σ∆ schemes of different orders for two-dimensional signals so one can profit both from the better stability properties of low order schemes and the better accuracy properties of higher order schemes. We demonstrate that the resulting mixed-order Σ∆ schemes in combination with a padding strategy yield improved representation quality in digital halftoning as measured in the Feature Similarity Index.These empirical results are complemented by mathematical error bounds for the model of two-dimensional bandlimited signals as motivated by a mathematical model of human visual perception.