Miracle-dz/UniFAR-FTUs huggingface dataset:
ThingNet: A Lightweight Real-time Mirai IoT Variants Hunter through CPU Power Fingerprinting

Internet of Things (IoT) devices have become attractive targets of cyber criminals, whereas attackers have been leveraging these vulnerable devices most notably via the infamous Mirai-based botnets, accounting for nearly 90% of IoT malware attacks in 2020. In this work, we propose a robust, universal and non-invasive Mirai-based malware detection engine employing a compact deep neural network architecture. Our design allows programmatic collection of CPU power footprints with integrated current sensors under various device states, such as idle, service and attack. A lightweight online inference model is deployed in the CPU for on-the-fly classification. Our model is robust against noisy environment with a lucid design of noise reduction function. This work appears to be the first step towards a viable CPU malware detection engine based on power fingerprinting. The extensive simulation study under ARM architecture that is widely used in IoT devices, demonstrates a high detection accuracy of 99.1% at a speed less than 1ms. By analyzing Mirai-based infection under distinguishable phases for power feature extraction, our model has further demonstrated an accuracy of 96.3% on model-unknown variants detection.
A Self-Adaptive Size-Free Method For 3D Point Cloud Completion

The point cloud we obtained from LiDAR or depth camera may usually have some kind of missing part due to the obstacles and the insufficient of resolution. Finding a way to complete these missing parts comes to be essential for the understanding of point cloud. The previous methods tend to have a strict limitation on the input size or output size of point cloud, which leads to some kind of sparsification of the points and can not actually be applied to various scenarios. In this paper, we provide a self-adaptive method where both the input size and output size can be flexible and don’t have any hard limitations on them. We apply the AABB box to convert the problem into 2D image plane and take use of hierarchically depth image painting to complete the task. The experiment shows that our method has a self-adaptive ability to give various output without strict limitations while maintaining the local detail of the point cloud.
Isolated 4- Level DC- DC Converter with Enhanced Soft-Switching Adaptability and Output Voltage Flexibility for High-Power Charger Applications

An isolated 4-level DC-DC converter is proposed to achieve complete zero-voltage-switching (ZVS) adaptability of all active switches while remaining output voltage flexibility of the phase-shifted converters for the high-power universal fast charger applications. A dedicated four-level modulation scheme ensures that the peaks of magnetizing currents of the two H - bridges at primary side are independent of load current and voltage, and phase variations. The magnetizing to leakage inductance ratios of the leading and lagging transformers are improved to be 100 and 25 respectively and the additional series inductors are eliminated. As a result, the circulating current, duty cycle loss and stress on snubber circuit are reduced significantly. The sizing of the output inductor is also decreased because of the 4-level operation. A 30kW isolated DC-DC converter with 7.2kW/L power density (cooling inclusive), 98.5 % peak efficiency, flexible 165V-680V output voltage verifies the features and feasibility of the proposed H8 tonology and four-level modulation scheme.
Heading Control of a Ship Based on Deep Reinforcement Learning (RL)

A deep reinforcement learning (RL) algorithm called Deep Q-Network(DQN) is used for the heading control of a ship in calm water and in waves. Ship’s state space is in continuous space and a set of five rudder angle actions are in discrete space. The optimal rudder action is selected based on maximum Q-value of the rudder actions. The ship positions and velocities serve as input and the Q-values associated with a set of rudder angles are the output of the DQN. Reward functions are designed such that the agent will try to reduce the Cross Track Error (CTE) and Heading Error (HE). The heading control of a KVLCC2 tanker in calm water and waves is investigated. The ship dynamics is represented using a 3DoF numerical model. The CTE and HE are calculated based on Line of Sight (LOS) Algorithm.
In-Situ EV Battery Electrochemical Impedance Spectroscopy with Pack-Level Current Perturbation from a 400V-to-12V Triple-Active-Bridge

A GaN-based, 4-kW, 400V-to-12V triple-active-bridge dc-dc converter is proposed to impose a variable-frequency sinusoidal perturbation between two EV battery half-packs for Electrochemical Impedance Spectroscopy (EIS). The proposed architecture performs EIS on the high-voltage battery at arbitrarily low test frequencies, requiring only a few cycles of operation and no additional means of energy-storage. This allows for fast, opportunistic, in-situ EIS measurements during EV operation. In-situ impedance measurements can help maximize the EV battery performance with respect to its local environment. Full integration into the existing high-voltage to low-voltage dc-dc EV converter results in a compact and low-cost system. A cell-level voltage-response sensor with automatic dc-offset calibration is implemented with integrated signal processing to measure cell-level voltage responses, thereby accurately capturing cell-to-cell impedance variations in the EV battery. Impedance measurements from a fully custom liquid-cooled 350-V lithium-ion EV battery pack are collected between 0.1 Hz and 200 Hz, from 15° C to 25° C, demonstrating simultaneous in-situ pack-level EIS perturbation and cell-level response measurement.
Unifying Temporal and Spatial Locality for Cache Management inside SSDs

To ensure better I/O performance of solid-state drivers (SSDs), a dynamic random access memory (DRAM) is commonly equipped as a cache to absorb overwrites or writes, instead of directly flushing them onto underlying SSD cells. This paper focuses on the management of the small amount cache inside SSDs. First, we propose to unify both factors of temporal and spatial locality of user applications by employing the visibility graph technique, for directing cache management. Next, we propose to support batch adjustment of adjacent or nearby (hot) cached data pages by referring to the connection situations in the visibility graph of all cached pages. At last, we propose to evict the buffered data pages in batches, to maximize the internal flushing parallelism of SSD devices, without worsening I/O congestion. The trace-driven simulation experiments show that our proposal can yield improvements on cache hits by more than 2.8%, and the overall I/O latency by 20.2% on average, in contrast to conventional cache schemes inside SSDs.
Material Calculation Collaborates with Grain Morphology Knowledge Graph for Material Properties Prediction

The study of microstructure of materials is of great significance in the field of materials science. The interdisciplinary cooperation of materials science and computer science makes it more accurate and efficient to explore the relationship between material microstructure and material properties. Machine learning has potential in exploring the relationship between microstructure and properties of materials. This paper proposes adding the morphology features of grains into the construction of grain knowledge graph to enrich the grain information in the graph. First, an autoencoder extracts the grain morphology features and adds them to the grain knowledge graph. Then, the graph convolutional network is used to extract the features of the graph, and the fully connected network is used to predict the properties of the material. Experiments are performed on actual EBSD scanning data. The experimental results show that the proposed method has noticeable improvement over the competing methods.
Acoustics Based Docking for a Coral Reef Monitoring Robot (C-Bot)

Underwater docking plays a vital role in supporting long-term operations by allowing autonomous underwater vehicles (AUVs) to recharge and offload data without the need for launch and recovery operations. Existing vision based docking systems have limitations, such as discrepancies while dealing with bad lighting and visibility conditions, and there is a need for multiple sensors to counteract these constraints. This paper describes a reliable solution to these by using a 2D imaging sonar as the primary sensor. The software proposed in this paper was tested with a hardware-in-the-loop (HIL) simulation of the coral reef monitoring robot (C-Bot) as the target robot and a stationary dock.
Referencing-in-Array Scheme for RRAM-based CIM Architecture

Resistive random access memory (RRAM) based computation-in-memory (CIM) architectures are attracting a lot of attention due to their potential in performing fast and energy-efficient computing. However, the RRAM variability and non-idealities limit the computing accuracy of such architectures, especially for multi-operand logic operations. This paper pro-poses a voltage-based differential referencing-in-array scheme that enables accurate two and multi-operand logic operations for RRAM-based CIM architecture. The scheme makes use of a 2T2R cell configuration to create a complementary bitcell structure that inherently acts also as a reference during the operation execution; this results in a high sensing margin. More-over, the variation-sensitive multi-operand (N)AND operation is implemented using complementary-input (N)OR operation to further improve its accuracy. Simulation results for a post-layout extracted 512x512 (256Kb) RRAM-based CIM array show that up to 56 operand (N)OR/(N)AND operation can be accurately and reliably performed as opposed to a maximum of 4 operands supported by state-of-the-art solutions, while offering up to 11.4X better energy-efficiency.
Simulator-aided Edge-based Acoustic Camera Pose Estimation

In this work, a method to estimate accurate 6 degrees of freedom acoustic camera pose is proposed. Acoustic cameras, also known as 2D forward-looking sonar can generate high resolution 2D images in all water bodies. However, due to the unique imaging principle, techniques such as vision-based localization with acoustic images are still at the early stage. Even we have full 3D information of the scene, it is still difficult to localize the sensor. In this work, we deal with the problem of estimating the accurate relative pose between the camera and a 3D known target which can be applied to tasks like extrinsic calibration. Previous works mainly estimate the camera pose with planar targets; however, the methods are not robust to noise in the image. We propose an accurate pose estimation method with the help of an acoustic image simulator which can deal with 3D targets. We use edge features to match the real images and the synthetic images. A coarse-to-fine strategy is used for global localization and pose refinement. Experiments prove the effectiveness of the method.
Numerical investigation of wave interaction and breaking near a wedge shape submerged reef

Ministry of Earth Science, india successfully implemented a wedge-shaped artificial reef to restore and protect the lost beach at Puducherry coast. The performance of the reef is monitored by measuring the beach profiles and bathymetry periodically near the reef to estimate the quantity of beach formation. Numerical studies are also carried out for the site conditions to investigate the wave interaction and breaking near the reef. Multi-phase numerical models are developed using Computational Fluid Dynamics (CFD) based open source tool OpenFOAM and RANS based multiphase k-ε and Buoyancy modified k-ω SST models are implemented and compared with the default turbulence models for their performance in wave propagation and breaking. Default k-ε model predicts excessive effective dynamic viscosity at interface due to unaccount of density variation in the model and the wave height is reduced while simulation is progressing compared to the other two models.
Six-Zone MVDC Architecture Baseline for Fault Analysis and High Speed Breaker Placement

This paper describes and displays an advanced demonstration model of a medium-voltage dc reduced order system which contains six partial electrical zones of a ship. The model has two anticipated purposes; to assist in the determination of necessary high-speed breaker locations and to be considered a baseline for future medium-voltage dc integrated power systems with pulse loads and energy storage. The model is suited for system analysis and contains the global apparatus for reconfiguration control. The system model was constructed using average-value power electronic components with minimized controls. The impedances between subsystems as well as the internal component impedances were kept intact to assist in the evaluation of high-speed breaker placement, and utilization.
Practical Switching Frequency Control for Improved Efficiency in CCM Boost PFC Converters at Light Load

Existing control methods in continuous conduction mode (CCM) boost PFC topologies employ a fixed switching frequency over the whole range of operation. Besides a simple implementation, retaining the switching frequency unchanged, places front stage converters at a suboptimal level during light load operating conditions. In particular, the dominant switching loss can often lead to an adverse impact on the systems efficiency. This paper proposes a novel control approach to both optimize the light load efficiency and improve input current regulation issues associated with a switching frequency adjustment. The control method is verified using a 3kW bridgeless totem-pole PFC prototype delivering a substantial switching loss reduction enabling 99% power conversion efficiency even with diode rectification.
Jaderná elektrárna Dukovany a její vliv na okolní obce

Předmětem bakalařske prace „Jaderna elektrarna Dukovany a jeji vliv na okolni obce“ je zatim ne zcela probadana oblast působeni JE Dukovany na svoje okoli z některých ekonomických hledisek. Budu se zabývat předevsim obcemi z pasma 5 km od JEDU, kterých je sest. Podrobně rozeberu hlavně dotace od provozovatele JEDU těmto 6 obcim a dale zjistim, na co obce tyto dotace použily. Podobným způsobem, avsak v mensi miře, zhodnotim i vliv na mikroregiony z okoli elektrarny. Dalsi cast prace analyzuje navrhy zakonů týkajicich se kompenzaci obcim v okoli JEDU. Dale zjistim vliv elektrarny na zaměstnanost a podnikatelske prostředi v regionu. V navaznosti na výse zminěne zvažim výhody a nevýhody přitomnosti JEDU v regionu.
MEMS Based Micro Aerial Vehicles

Designing a flapping wing insect robot requires understanding of insect flight mechanisms, wing kinematics and aerodynamic forces. These subsystems are interconnected and their dependence on one another affects the overall performance. Additionally it requires an artificial muscle like actuator and transmission to power the wings. Several kinds of actuators and mechanisms are candidates for this application with their own strengths and weaknesses. This article provides an overview of the insect scaled flight mechanism along with discussion of various methods to achieve the Micro Aerial Vehicle (MAV) flight. Ongoing projects in Chalmers is aimed at developing a low cost and low manufacturing time MAV. The MAV design considerations and design specifications are mentioned. The wings are manufactured using 3D printed carbon fiber and are under experimental study.
Wildlife comeback in Europe: the recovery of selected mammal and bird species

THE ZOOLOGICAL SOCIETY OF LONDON (ZSL), a charity founded in 1826, is a worldrenowned centre of excellence for conservation science and applied conservation. ZSL’s mission is to promote and achieve the worldwide conservation of animals and their habitats. This is realised by carry ing out fi eld conservation and research in over 50 countries across the globe and through education and awareness at our two zoos, ZSL London Zoo and ZSL Whipsnade Zoo, inspiring people to take conservation action. WWW.ZSL. ORG
High Step-up DC-DC Converter with Active Switched Inductor and Voltage Double Based on Three-winding Coupled Inductor

This paper proposes a high step-up dc-dc converter with three-winding coupled inductor, integrating an active switched inductor and voltage double to achieve voltage gain. The main merits of the proposed converter are high voltage gain, reduced voltage stress and current stress on the power switch. In addition, the source energy is transferred through the coupled inductor to the output during the entire switching time and the energy stored in the leakage inductor is recycled directly to the load without intermediate components. The proposed converter can be further derived to two varied converters for higher voltage gain. Finally, a fabricated 270 W with 30 V input voltage, 300 V output voltage is carried out to support the validity of the proposed converter.
A Priority-Based Level Heuristic Approach for Scheduling DAG Applications with Uncertainties

In a typical distributed computing system, as the availability of resources and the precise execution time of different calculations are usually difficult to predict, how to effectively schedule complex calculations composed of interdependent tasks has become a challenge. The priority-based (PB) scheduling scheme, which is designed to maximize the parallelism of ready tasks, has shown better performance than other existing algorithms. However, the PB algorithm has the problem of excessive computing overhead and long running time in some cases. To address this issue, this paper proposes the priority-based level (PBL) algorithm. Experiments results show that the PBL , in comparison with their counterparts, manages to significantly reduce the algorithm running overhead while maintaining the scheduling results.
A High-Power, High-Frequency Matrix Core Transformer Design for Medium Voltage Dual Active Bridge

In this work, the analytical models and optimization procedure for the design of high-power matrix core transformer (MCT) aiming at isolated DC/DC converter applications, especially for dual active bridge (DAB) converters, are proposed. The loss models, leakage inductance and thermal network models of MCT are presented, and a multi-variable, multi-objective optimization methodology of MCT is proposed. A 100 kW/50 kHz MCT design is selected and prototyped based on the optimization results. An additive manufactured bobbin design is also presented to control the leakage inductance and the path of the airflow. The electrical, magnetic, and thermal performance of the prototype are validated using by experimental studies.
Nonlinear System Identification and Motion Control Design for an Unmanned Underwater Vehicle

This paper presents a hierarchical motion control system design for a fully actuated observation class Unmanned Underwater Vehicle (UUV). A Nonlinear Model Predictive Controller (NMPC), which uses the position measurement from an onboard Short Base Line (SBL) acoustical positioning system, is designed to control vehicle. The NMPC uses the measurement model to optimize vehicle trajectories with practical velocity and transponder visibility constraints to generate a reference velocity vector. The dynamics of the underwater vehicle is identified by using a polynomial representation of Nonlinear Auto-Regressive Moving Average with eXogenous input (NARMAX) model and using an onboard Doppler velocity log (DVL) sensor. The structure of the identified model is determined via Orthogonal Forward Regression (OFR) algorithm. The model parameters are selected based on the Error Reduction Ratio (ERR) criterion and are updated using a Recursive Extended Least Squares (RELS) algorithm. To track the reference velocities generated by the kinematics controller, a Control Lyapunov Function (CLF) based inverse optimal control law is synthesized. The proposed control scheme is validated both numerically and experimentally showing that dynamics of vehicle can be captured successfully by the proposed method. It is also shown that the proposed controller can effectively track the desired references.
DWR: Differential Wearing for Read Performance Optimization on High-Density NAND Flash Memory

With the cost reduction and density optimization, the read performance and lifetime of high-density NAND flash memory have been significantly degraded during the last decade. Previous works proposed to optimize lifetime with wear leveling and optimize read performance with reliability improvement. However, with wearing, the reliability and read performance will be degraded along with the life of the device. To solve this problem, a differential wearing scheme (DWR) is proposed to optimize the read performance. The basic idea of DWR is to partition the flash memory into two areas and wear them at different speeds. For the area with low wearing speed, read operations are scheduled for read performance optimization. For the area with high wearing speed, write operations are scheduled but designed to avoid generating bad blocks early. Through careful design and real workloads evaluation on 3D TLC NAND flash, DWR achieves encouraging read performance optimization with negligible impacts to the lifetime.
Vertical greening systems evaporation measurements: does plant species influence cooling performances?

ABSTRACT Vertical greening systems (VGS) can increase the energy performances of building envelopes, while providing several environmental and ecological benefits in dense urban areas. In 10 November 2014, the first vertical greening system in the city of Genoa (Italy) was installed on the south facade of a public institution office building, as pilot project aimed at monitoring environmental effects and energy performances. With the aim to evaluate the cooling performances of some of the different plant species and of the living wall system used 15 for the facade, an experimental site was set-up. It consists of five living wall panels: (1) bare, (2) planted with Cistus Jessami beauty, (3) planted with Phlomis fruticose, (4) planted with Hedera helix, (5) planted with Rhincosperma jasminoides and of four pots (9 cm) planted with the same plant species. Measurements were carried out three times per day in 20 the months of July and September 2015. The data collected, elaborated by means of a statistical analysis, show the amount of water evaporated by the panels and the pots, demonstrating that the living wall panels' behaviour is different compared to the pots' behaviour and that the performances are different when comparing night and day behaviour.
Team Formation and Task Recommendation for Disabled People in Crowdsourcing Systems

The barrier-free map is a new type of map, the demand for which is increasing in modern society, and it is necessary to rely on crowdsourcing platforms to complete the labeling work of barrier-free facilities. Nowadays more people with disabilities are participating in crowdsourcing work. They tend to work with familiar people and hope to maximize their value. However, there is very little research about automatic management of organizations and tasks for the disabled to assist them to complete the work on the crowdsourcing platform. In this paper, we design a new team formation method based on the theory of socially embedded work of the disabled (TFSEW) and a bi-objective task recommendation method (BOTR), in order to ensure the efficiency of task completion and promote the participation of the disabled, thereby realizing their value in the work environment. Our method proves to be superior through experiments. At the same time, through questionnaire, people with disabilities show great anticipation for participating in the tasks in form of team and receive tasks recommended by the system.