Miracle-dz/UniFAR-FTUs huggingface dataset:
Software-Defined Low-Complex Visible Light Communication Networks

Today, everything is connected. The Internet transports a massive amount of data every second, and the traffic created by social media, instant messaging, and video streaming is growing day by day. The last step to end user devices, such as mobile phones or laptops, is usually bridged via a wireless connection. Data is transmitted wirelessly using electromagnetic waves with carrier frequencies within the radio spectrum, which is strictly regulated by government organizations. The wireless communication industry tries to keep up with the data growth and regularly releases new standards based on technological improvements to increase the achievable data rates. The communication channel capacity, and thus the maximum possible data rate, depends on the available bandwidth. As only limited spectrum slices are free for commercial and private use, a certain data rate cap will be reached at some point. Fortunately, there is a large piece of the electromagnetic spectrum at hand, also known as Visible Light, that is not regulated and can be exploited for wireless communication. Visible light as communication medium has many promising characteristics. Since the medium can be seen, communication becomes directable and provides visible feedback. Light cannot pass (most) solid objects and can therefore be simply contained within a room, providing a secure communication channel. Furthermore, light sources are available everywhere, enabling the reuse of existing infrastructure to combine illumination and communication. In contrast to other works in the field of Visible Light Communication (VLC), addressing new modulation schemes and data rate improvements, this thesis focuses on a low-complex and software-defined approach and presents inexpensive VLC systems for different scenarios. Basic microcontrollers, off-the-shelf Light Emitting Diodes (LEDs) used as sender and receiver, and softwarebased communication protocols provide a solid basis for VLC
Fast and Robust Asynchronous Rendezvous Scheme for Cognitive Radio Networks

The rendezvous process is considered a key operation that allows a secondary user (SU) to access an unused authorized spectrum in cognitive radio networks (CRNs). Most existing works focused on fast guaranteed rendezvous without considering a sophisticated jamming attack environment. In this paper, I propose a fast and robust asynchronous rendezvous scheme that can improve robustness against jamming attacks under symmetric asynchronous environments in which all SUs have the same available channels. Unfortunately, in CRNs, each SU can have a different number of available channels due to their relative position to primary nodes (PUs). Therefore, I extend my fast and robust asynchronous rendezvous scheme (FRARS) to a general asymmetric scenario while preserving robustness against jamming attacks. I derive the maximum rendezvous time (MTTR) of my new algorithm and the upper bound of the expected TTR (ETTR) and compare it with the state-of-the-art algorithms such as jump-stay (JS) and Enhanced jump-stay (EJS). My numerical results show that the performance of the proposed technique is better than that of JS and EJS in terms of MTTR and ETTR. Also, the performance will be more significant when there are security concerns about a sophisticated jamming attack.
Magneto-visco-hyperelasticity for hard-magnetic soft materials: theory and numerical applications

Soft materials that can deform under external stimuli offer great opportunities for the development of new structural applications such as sensor-actuator systems, soft robots or biomedical devices. Among these materials, soft polymers filled with magnetic particles are experiencing an increasing interest from the scientific community. Apart from magnetorheological elastomers and ferrogels, a new magneto-sensitive material type has been developed recently. These so-called hard-magnetic materials allow for shape-programmability by the addition of magnetically-hard particles within a polymeric matrix. In this regard, constitutive and computational frameworks describing the magneto-mechanics of such materials are needed to provide new avenues in the development of novel applications based on hard-magnetic soft polymers. To this end, this work focuses on the mathematical modelling of the magneto-mechanics of hard-magnetic soft materials and their implementation in finite element (FE) frameworks. The proposed continuum model is formulated for large deformations and within a thermodynamically consistent framework. In addition, the model incorporates viscous contributions to account for relaxation and dissipation effects in the deformation process of these materials when subjected to external magnetic fields and/or mechanical loading. To illustrate the theory, the magneto-mechanical model is implemented within an implicit static FE framework and three numerical examples are provided to explore potential applications as well as to evaluate the influence of the external magnetic field application on the viscoelastic response of the material. Finally, the framework is implemented in an implicit dynamic FE framework to evaluate the role of inertial terms on the dynamic response of these materials.
Practical water animation using physics and image based methods

Dedicated with love to my wife, Jingchao, for her never-ending love, support, and gentle guidance throughout the years. iii PREFACE 'Determinism is the philosophical proposition that every event, including human cognition and behaviour, decision and action, is causally determined by an unbroken chain of prior occurrences. ' The world is as precise as a clock. When I was learning physics for the first time as a kid, I was fascinated by how accurately this world can be predicted by all kinds of physical laws. If you know how fast you throw an apple and where it leaves your hand, you can predict whether it will hit Isaac Newton's head. If you shine a laser pen towards mirrors and lenses, the optics provides you the whole light path so that you may defeat the entire Roman fleet, as Archimedes did. I could not stop imagining that one day everything can be predicted in this world, given all of physical laws. Obviously I was not the first one with this wild idea. Actually, philosophers already had a name for it: determinism. Soon I learned that quantum mechanics is another phenomenon existing in this world, even although I still blindly refuse to accept it just like Albert Einstein did. Luckily this is a thesis for a degree in computer science, not in physics. Thus I turned myself to another question: given a supercomputer that can duplicate everything into a virtual world, can we really distinguish the virtual world from the real world? I was not surprised at all when I saw the movie The Matrix raising the same question that I had. Maybe there is no answer to this question, but at least, computer scientists can make such a scenario real. Moving the real world into the virtual world is not so straightforward as writing down a collection of physical laws. They are far too simplified to cover all of the iv aspects in real world mechanics. The real world is also greatly beyond our imagination in terms of its detail and complexity. Even a pebble has an irregular shape, texture details, and complicated light transport properties. Last but not least, an infinitely powerful supercomputer only exists in scientific fictions. Computational and storage resource of a real-world computer always restricts our choices when simulating the real world. All of these issues come together to make this problem challenging, yet fascinating to me. This dissertation …
Appearance‐based landmark selection for visual localization

Visual localization in outdoor environments is subject to varying appearance conditions rendering it difficult to match current camera images against a previously recorded map. Although it is possible to extend the respective maps to allow precise localization across a wide range of differing appearance conditions, these maps quickly grow in size and become impractical to handle on a mobile robotic platform. To address this problem, we present a landmark selection algorithm that exploits appearance co‐observability for efficient visual localization in outdoor environments. Based on the appearance condition inferred from recently observed landmarks, a small fraction of landmarks useful under the current appearance condition is selected and used for localization. This allows to greatly reduce the bandwidth consumption between the mobile platform and a map backend in a shared‐map scenario, and significantly lowers the demands on the computational resources on said mobile platform. We derive a landmark ranking function that exhibits high performance under vastly changing appearance conditions and is agnostic to the distribution of landmarks across the different map sessions. Furthermore, we relate and compare our proposed appearance‐based landmark ranking function to popular ranking schemes from information retrieval, and validate our results on the challenging University of Michigan North Campus long‐term vision and LIDAR data sets (NCLT), including an evaluation of the localization accuracy using ground‐truth poses. In addition to that, we investigate the computational and bandwidth resource demands. Our results show that by selecting 20–30% of landmarks using our proposed approach, a similar localization performance as the baseline strategy using all landmarks is achieved.
Diagnosis of ICH and SDH Brain Hemorrhage Using Artificial Neural Networks

Medical Image analysis and processing has great significance in the field of medicine, especially in Non-invasive treatment and clinical study. Medical Image Processing has emerged as one of the most important tools to identify as well as diagnose various disorders. Diagnosing brain hemorrhage, which is a condition caused by a brain artery busting and causing bleeding in the surrounded tissues is currently done by medical experts using a CT scan. This paper investigates the possibility of diagnosing brain hemorrhage using an image segmentation of CT scan images using segmentation algorithm and feeding of the appropriate inputs extracted from the brain CT image to an artificial neural network for classification. Aim of this paper is to design, develop and evaluate an easy to use, intelligent and accurate system which enables users like radiologists or medical students as well as doctors to feed brain CT images to diagnose whether there is a hemorrhage and specify the type of hemorrhage using Fuzzy C means along with neural network for hemorrhage classification.
Mueller matrix microscopy

We describe here Mueller matrix microscopy, an imaging technique for investigating the anisotropic properties of the refractive index in biological samples. Tissue properties probed by polarization are the anisotropic real and imaginary parts of the refractive index that modify the polarization. Physical Sciences Inc. has developed a robust polarization microscope that is capable of performing complete Mueller matrix imaging in both transmission and reflection configuration. The system’s capabilities are illustrated on biological samples.
Fault Detection and Identification Scheme for Dual-Inverter Fed OEWIM Drive

Dual-inverter configuration has been attracting increasing attention, especially in motor drives, for its advantages in fault tolerance, multilevel modulation effect, dc voltage utilization, etc. However, its switch fault diagnosis is difficult due to the symmetry of the two sub-inverters. A signal processing approach is proposed in this paper to detect the switch open-circuit fault occurrence and further identify the specific faulty switch, benefiting maintenance and fault-tolerant operation. In this scheme, the faulty phase and the faulty switch pair, consisting of the faulty switch and the switch on its diagonal, are identified using the stator phase currents average values. Following that, the bridge of the faulty phase is forced into a unipolar mode by artificially turning off one switch in the healthy pair continuously. Through properly controlling the duty ratios of the other switches in this bridge, the faulty switch is allowed to be further identified from the faulty pair by analyzing the behavior of the induced current in this phase. This approach is independent of either the speed or the voltage information. The effectiveness is validated through experiments on a sensorless controlled open-end winding induction motor drive.
Study of Dynamic Response Characteristics of the Wind Turbine Based on Measured Power Spectrum in the Eyewall Region of Typhoons

The present research envisages a method for calculating the dynamic responses of the wind turbines under typhoon. The measured power spectrum and inverse Fourier transform are used to generate the fluctuating wind field in the eyewall of the typhoon. Based on the beam theory, the unsteady aerodynamic model and the wind turbine dynamic model are coupled to calculate the dynamic response. Furthermore, using this method, the aeroelastic responses of a 6 MW wind turbine at different yaw angles are studied, and a 2 MW wind turbine are also calculated to verify the applicability of the results for different sizes of wind turbines. The results show that the turbulence characteristics of the fluctuating wind simulated by the proposed method is in good agreement with the actual measurement. Compared with the results simulated by the recommended power spectrum like the Kaimal spectrum, the energy distribution and variation characteristics simulated by the proposed method represent the real typhoon in a superior manner. It is found that the blade vibrates most violently at the inflow yaw angle of 30 degrees under the coupled effect of the aerodynamic, inertial and structural loads. In addition, the load on the tower exceeds the design limit values at the yaw angles of both 30 degrees and 120 degrees.
Enabling resilient wide‐area POD at BESS in Java, Indonesia 500 kV power grid

The future Indonesian power grid will have significant REGs, especially in Java Island. Wind and solar photovoltaic (PV) will be the dominating technologies in future Indonesian grid. Although REG can provide clean and sustainable energy, they also cause undesirable effects on system stability due to the uncertainty in their output and different dynamic characteristics. Battery energy storage system (BESS) has been considered as the promising candidate to manage the intermittency and low inertia associated with wind and PV in many future power systems. In addition to the normal functionality, the resilient wide-area power oscillation damping (POD) can be implemented in the BESS to damp the low-frequency oscillation in the system. This research proposes a method to design a resilient wide-area POD in BESS. A grey wolf optimiser (GWO) has been used to synthesise the resilient wide-area POD. The representative dynamic model of Java-Indonesian power system is used to evaluate the performance of the GWO-based resilient wide area POD. From the results, it is evident that the implementation of the proposed controller at BESS successfully damped the critical mode of the system. It is also observed that the proposed controller is robust against the failure of the input signal.
Discriminating Emotions in the Valence Dimension from Speech Using Timbre Features

The most used and well-known acoustic features of a speech signal, the Mel frequency cepstral coefficients (MFCC), cannot characterize emotions in speech sufficiently when a classification is performed to classify both discrete emotions (i.e., anger, happiness, sadness, and neutral) and emotions in valence dimension (positive and negative). The main reason for this is that some of the discrete emotions, such as anger and happiness, share similar acoustic features in the arousal dimension (high and low) but are different in the valence dimension. Timbre is a sound quality that can discriminate between two sounds even with the same pitch and loudness. In this paper, we analyzed timbre acoustic features to improve the classification performance of discrete emotions as well as emotions in the valence dimension. Sequential forward selection (SFS) was used to find the most relevant acoustic features among timbre acoustic features. The experiments were carried out on the Berlin Emotional Speech Database and the Interactive Emotional Dyadic Motion Capture Database. Support vector machine (SVM) and long short-term memory recurrent neural network (LSTM-RNN) were used to classify emotions. The significant classification performance improvements were achieved using a combination of baseline and the most relevant timbre acoustic features, which were found by applying SFS on a classification of emotions for the Berlin Emotional Speech Database. From extensive experiments, it was found that timbre acoustic features could characterize emotions sufficiently in a speech in the valence dimension.
CLIC e+e- Linear Collider Studies

This document provides input from the CLIC e+e- linear collider studies to the update process of the European Strategy for Particle Physics. It is submitted on behalf of the CLIC/CTF3 collaboration and the CLIC physics and detector study. It describes the exploration of fundamental questions in particle physics at the energy frontier with a future TeV-scale e+e- linear collider based on the Compact Linear Collider (CLIC) two-beam acceleration technique. A high-luminosity high-energy e+e- collider allows for the exploration of Standard Model physics, such as precise measurements of the Higgs, top and gauge sectors, as well as for a multitude of searches for New Physics, either through direct discovery or indirectly, via high-precision observables. Given the current state of knowledge, following the observation of a \sim125 GeV Higgs-like particle at the LHC, and pending further LHC results at 8 TeV and 14 TeV, a linear e+e- collider built and operated in centre-of-mass energy stages from a few-hundred GeV up to a few TeV will be an ideal physics exploration tool, complementing the LHC. Two example scenarios are presented for a CLIC accelerator built in three main stages of 500 GeV, 1.4 (1.5) TeV, and 3 TeV, together with the layout and performance of the experiments and accompanied by cost estimates. The resulting CLIC physics potential and measurement precisions are illustrated through detector simulations under realistic beam conditions.
High Power Density CMOS Compatible Micro-Machined MEMs Energy Harvester

Optimization of piezoelectric energy harvester (PEH) to convert the ambient vibrational energy into maximum electrical energy has been of continued interest. The integration of the proof mass with the optimum cantilever width significantly enhances the output power of PEH. In this paper, we propose an optimized design of PEH that outperforms the existing AlN-based design in terms of power density. We analytically optimize the design of: 1) cantilever-to-harvester length and 2) cantilever-to-harvester width (proof mass width) ratios for the maximum output power. The optimized harvester is fabricated using a novel integration scheme for the bottom electrode with Au as an interlayer. The Au interlayer is used to grow a good quality of AlN film with piezoelectric coefficients, <inline-formula> <tex-math notation="LaTeX">$d_{33} = 12$ </tex-math></inline-formula> pm/V and <inline-formula> <tex-math notation="LaTeX">$d_{31} = -2.37 $ </tex-math></inline-formula> pm/V. It is found that in order to achieve the optimum output from PEH, the fractional length and width occupied by cantilever are 28%–40% and 38%–45%, respectively. The optimized designs are fabricated using a CMOS compatible process. The maximum power density measured from the fabricated PEHs is found to be 9.36 <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>W/mm<sup>3</sup>, which is better than the similar reported data. The optimized and compact low-power PEHs reported in this paper have high potential to be integrated with the system on chip (SOC) and other wireless sensor applications.
Application Layer Multicast Based Services on Hierarchical Peer to Peer Architecture

Application Layer Multicast (ALM) is considered as an attractive approach for implementing wide area multicast services. In ALM, multicast functionality is implemented at the edge instead of the core network (routers). As opposed to network-layer multicast, application layer multicast requires no infrastructure support and can be easily deployed in the Internet. In this paper, we propose a new efficient and scalable model for optimizing application layer multicast using HPM architecture (HPM: A novel hierarchical Peer-to-Peer model for lookup acceleration with provision of physical proximity). This approach benefits from P2P properties and characteristics. In this contribution, we consider our optimized tree construction algorithm simultaneously for each ring of HPM. The global tree construction algorithm is composed of two steps. In the first step, we construct a sub-tree for each ring; the second step is to build a global tree using sub sets of adjacent rings in HPM architecture. The proposed model inherits from main P2P attributes such as: scalability, fault tolerance characterized HPM. Preliminarily performance evaluations show that results are globally satisfactory, the depth of the resulting multicast tree is optimized.
Design and implementation of a novel auxiliary network based ZVS DC/DC converter topology with MPWM: an application to electric vehicle battery charging

The DC/DC converter stage has a significant role in the on-board electric vehicle (EV) battery charger. This study proposes a zero voltage switching (ZVS) full-bridge DC/DC converter (FBDC) for efficient power conversion with minimal power loss. The simplified auxiliary circuit-based FBDC consolidate the modified pulse width modulation (MPWM) gating technique for DC/DC conversion stage according to battery profile of the EV. The proposed MPWM can minimise the conduction and switching losses in comparison to the previously proposed converter configuration using conventional phase shift modulation (PSM) gating technique. The size of auxiliary inductance required is reduced with MPWM in comparison to conventional FBDC auxiliary inductance with PSM gating technique. Design and implementation of proposed ZVS FBDC with MPWM are discussed for a 500 W, 80 kHz laboratory prototype and experimental results are presented to validate the design and performance of the proposed converter.
Evolving Fault and Parallel Switching for SF6 Circuit Breakers

A special stress for circuit breaker is the occurrence of evolving fault or parallel switching condition. These switching cases are not standardized by international standards, but may occur in service and may create problems for the breaker. In the past, it was a problem mainly with oil circuit breakers and some types of air-blast circuit breakers but lesser known with SF6 circuit breakers. In the meantime, with upcoming new switching technologies along with changed operating duties, some doubts exist that these switching cases may become an issue again. This paper explains in detail the background of these stresses and presents a method to evaluate the capability of SF6 circuit breakers for such situations. The theoretical evaluation involves network calculations, gas flow simulations, and dynamic dielectric analysis. It is important to note here that several tests have been done in the past for evolving and parallel switching faults for both puffer as well as self-blast circuit breakers with the knowledge available at that time. These test results are used to validate the outcome of the theoretical evaluation which will help in better prediction of the circuit breaker behavior before performing actual tests. It can be concluded that theoretical simulation may, in majority of the cases, serve as sufficient proof to show feasibility for such cases.