Miracle-dz/UniFAR-FTUs huggingface dataset:
A nonlinear control scheme for independent stabilization of a parallel multi-phase boost converter by blocking pure zero-sequence current

We propose a nonlinear controller, developed in a synchronous frame, for a parallel three-phase boost converter consisting of two modules. The basic idea, however, can be extended to a system with N modules. Each of the closed-loop power-converter modules operates asynchronously without any communication with the other module. The controller stabilizes the currents on the dq axes by blocking the flow of the pure-zero sequence current. The dynamic performance of the converter using the proposed nonlinear controller is much superior compared to that obtained using a linear controller. The steady-state performances of the two controllers are comparable.
Performance implications of rapid load changes in carbonate fuel cell systems

There are several key performance objectives of molten carbonate fuel cell systems operating under load perturbations. Among these include: regulation of stack temperature, regulation of differential pressure between anode and cathode, maintaining acceptable fuel utilization and steam-carbon ratio, and electrical load tracking. Utilities are interested in rapid load cycling of carbonate fuel cell systems while the military is interested in the response of carbonate fuel cell systems under sudden application and removal of electrical load. An integrated fuel cell system may endure these types of disturbances while satisfying performance goals, depending largely on the control system. In this paper, the authors examine two important performance variables: fuel utilization and steam-carbon ratio, under both ramping operation and sudden increase in load. Setpoint control laws are proposed for determining the proper steam and natural gas flows corresponding to steady state or transient conditions. In the case of a sudden load increase, they illustrate a trade-off between good load tracking and good utilization/steam-carbon ratio when considering rate constraints on valves.
Differentiable time-gated rendering

The continued advancements of time-of-flight imaging devices have enabled new imaging pipelines with numerous applications. Consequently, several forward rendering techniques capable of accurately and efficiently simulating these devices have been introduced. However, general-purpose differentiable rendering techniques that estimate derivatives of time-of-flight images are still lacking. In this paper, we introduce a new theory of differentiable time-gated rendering that enjoys the generality of differentiating with respect to arbitrary scene parameters. Our theory also allows the design of advanced Monte Carlo estimators capable of handling cameras with near-delta or discontinuous time gates. We validate our theory by comparing derivatives generated with our technique and finite differences. Further, we demonstrate the usefulness of our technique using a few proof-of-concept inverse-rendering examples that simulate several time-of-flight imaging scenarios.
Designing Games for Internal Training Is Not Child’s Play Guidelines for Designing Games at Ericsson Packet Core

The aim of this project was to investigate how games can be designed for training purposes at Ericsson Packet Core. A set of 37 guidelines, three game concepts and a prototype were created to investigate how games could be used and implemented. The project was carried out in an iterative manner and feedback was received throughout the project. The guidelines are based on an extensive research study performed in the beginning of the project. To test and evaluate the guidelines, game concepts were created. The guidelines and game concepts were developed in parallel during four iterations. A prototype was developed for one of the games to get hands-on experience and to perform tests with learners from the target group. The guidelines, the game concepts and the prototype have been developed and tested in close collaboration with Ericsson Packet Core and Ericsson Global Services. Even though they are still in the early stages of development, they could be used for further development of internal training games at Ericsson.
Optically controlled frequency reconfigurable band stop filter with multifrequency switching

A novel technique of optically switching the notch frequency of a band stop filter using photoconductive switch is presented. The effect of finite switch photoconductance on the frequency response and the design limitations is analyzed using transmission line model. The proposed design is generalized for multifrequency switching and multipole filter responses. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:1204–1211, 2014
z-OTS: a one-time hash-based digital signaturescheme with fast verification

—Hash-based signature schemes are a class of post-quantum algorithms usually built upon one-time signature (OTS) solutions via hash-trees. The beneﬁts of such schemes include small key sizes, efﬁcient processing and the fact that they are simple to implement using a regular hash algorithm. In addition, their security properties are quite well understood, since they rely basically on the pre-image or collision resistance of the underlying hash function. Among the existing OTS schemes, W-OTS+ is among the most popular. One reason for such popularity is that the OTS public key can be recovered from the signature itself, which facilitates the construction of a multi-time signature scheme using Merkle trees. On the other hand, signature generation and veriﬁcation in W-OTS+ take roughly the same time, which is not ideal for applications where each signature is expected to be veriﬁed several times, as in software stores, PKI certiﬁcate validation, and secure boot. It is also inconvenient when the devices that verify signatures have lower computational power than the signers. In such scenarios, it is desirable to design signature schemes enabling faster veriﬁcation, even if such speed-ups come at the expense of a slower signature generation procedure. With this goal in mind, we hereby present and evaluate a novel OTS scheme, called z -OTS. The main interest of z -OTS is that it preserves all beneﬁts of W-OTS+, but provides faster signature veriﬁcation at the cost of a (not much) slower signature generation procedure. For example, for signature sizes equivalent to W-OTS+ with Winternitz parameter w = 4 , our simulations show that veriﬁcation can be 30.3% faster with z -OTS, while key and signature generation become, respectively, 53.7% and 137.5% slower. Larger w leads to even more expressive gains in the veriﬁcation procedure, besides providing lower overheads when generating keys and signatures.
Diversity issues in the engineering curriculum

Teaching engineering studies students about diversity issues as part of the curriculum in engineering programs is an essential part of preparing the students for their professional life. By teaching them what this is and what it means for their (professional) lives sensitises them towards more responsibility. The idea is to connect diversity issues with technical subjects. Topics like technical development, human–machine communication or power management and other topics relevant to society are very suitable for this purpose.
Lower Extremity Exoskeleton Simulation Model with Variable Stiffness Actuation for Vertical Locomotion

This paper proposes a lower extremity exoskeleton simulation model for more effective control in vertical locomotion when patients need to move from static seating configuration to walking-ready configuration. Variable impedance actuators (VIA) or variable stiffness actuators (VSA) are considered as the primary source of generating and translating controlled torque values with elastic compliance properties to movement elements of a discussed system using PID control with dynamic compensation. The model-applied torque can be divided into two torques, one about gravity compensation and another about acceleration. The simulink environment with simscape library was used to create a simulation process of the working mechanism. Data on angles, torques, and velocities were obtained and considered for correctness in natural human locomotion. Calculations provide upper limit for the required torque to stand up, which can be used as a basis to select a proper actuator.
Multi - Task Assignment Strategy for Vehicular Crowdsensing with Clustering Characteristic

Recently, with a large number of on-board sensors, vehicles have been widely used for Vehicular Crowdsensing (VCS). Appropriate multi-task assignment strategy is crucial for V CS. However, sensing efficiency and benefit of the system of the existing works need to be improved due to the following challenges. On one hand, many sensing tasks have clustering characteristics in terms of their geographic distribution and sensing requirements, but current works are often ignored. On the other hand, existing multi-task assignment strategies often only design optimization problem for the benefit of one of the platform or participants, and fail to maximize the overall benefit of the system. To remedy that, this paper proposes a multitask assignment for tasks with clustering characteristics. First, we propose a task combination algorithm, which can greatly improve the task assignment efficiency and reduce the sensing cost. Next, we design a two-stage task assignment scheme, in which the benefits of the platform and participants are optimized respectively in two stages to maximize the benefit of the system. Finally, we carry out extensive simulations, and the simulation results verify the effectiveness of our proposal from clustering validity and sensing cost.
Spatial-Temporal Graph Convolutional Networks for Parking Space Prediction in Smart Cities

In smart cities, on-street parking space prediction is the key yet difficult point in smart parking system. However, conventional prediction methods generally neglect spatial and temporal dependencies and cannot predict long-term parking events accurately. To this end, we propose a parking space prediction scheme based on the spatial-temporal graph convolution networks (STGCN). We first consider the instantaneous status of the parking to calculate the on-street parking occupancy rate (POR). Then, based on the POR, we exploit a time convolution module and a graph convolution module to extract spatial and temporal dependencies of the parking spaces, respectively. Next, we design the parameters of the STGCN to predict the POR of all the parking spaces based on the spatial and temporal dependencies. Finally, based on the real-world data sets, we compare the proposed scheme with the benchmark models. The experimental results show that the proposed scheme has the best performance in predicting the POR.
Gait and balance patterns related to Free-Walking and TUG tests in Parkinson’s Disease based on plantar pressure data

Continuous monitoring of patients with Parkinson’s Disease (PD) is critical for their effective management, as early detection of improvement or degradation signs play an important role on pharmaceutical and/or interventional plans. Within this work, a group of seven PD patients and a group of ten controls performed a set of exercises related to the evaluation of PD gait. Plantar pressure signals were collected and used to derive a set of analytics. Statistical tests and feature selection approaches revealed that the spatial distribution of the Center of Pressure during a static balance exercise is the most discriminative analytic and may be used for every-day monitoring of the patients. Results have revealed that out of the 28 features extracted from the collected signals, 10 were statistically significant (p < 0.05) and can be used to machine learning algorithms and/or similar approaches.
Near Wellbore Salt Precipitation in Gas Reservoirs

Production wells in gas reservoirs often experience rapid production decline towards the late production stage. In many cases, this behavior can be attributed to salt precipitation in the near wellbore region. Water evaporates in the vicinity of the well bore with pressure drop, leading to an increase in the dissolved salt concentration, causing salt precipitation when the solubility limit is exceeded. Salt deposition causes the blockage of gas flow in the vicinity of the wellbore and increases towards the end of lifetime of a gas field, thus becoming problematic for most North Sea assets. Regular downhole fresh water treatments are required to restore the production back to normal. However, these water treatments are expensive and are required quite frequently. Thus, a better understanding of this phenomenon and the conditions under which it takes place is necessary. Additionally, the question arises whether there exists a better reservoir management strategy that can can improve control over well productivity. The model used to model salt precipitation in this work is a compositional two-phase N- component porous media flow model under isothermal conditions(2pNcmin) developed in the numerical simulator DuMuX. A sensitivity analysis was carried out to measure the sensitivity of the model to certain critical parameters and to understand the phenomenon better. The concept of a drying-transport balance was then developed, which can help understand the salt precipitation trends occurring under differing conditions. A study of the variables controlling the productivity of wells plagued by salt precipitation shows that there does exist an optimized reservoir management strategy which can better the cash flow from such wells. Based on these results, a simplified analytical model was developed to show the scope for optimization. Furthermore, an optimization problem was formulated to maximize the Net Present Value (NPV) of wells undergoing cyclic production and water washing.
Separability of Input Features and the Resulting Accuracy in Classifying Target Poses for Active Transhumeral Prosthetic Interfaces

In active prostheses, it is desired to achieve target poses for a given family of tasks, for example, in the task of forward reaching using a transhumeral prosthesis with coordinated joint movements. To do so, it is necessary to distinguish these target poses accurately using the input features (e.g. kinematic and sEMG) obtained from the human users. However, the input features have conventionally been selected through human observations and influenced heavily by the availability of sensors in this context, which may not always yield the most relevant information to differentiate the target poses in the given task. In order to better select from a pool of available input features, those most appropriate for a given set of target poses, a measure that correlates well with the resulting classification accuracy is required so that it can inform the interface design process. In this paper, a scatter-matrix based class separability measure is adopted to quantitatively evaluate the separability of the target poses from their corresponding input features. A human experiment was performed on ten able-bodied subjects. Subjects were asked to perform forward-reaching movements with their arms on nine target poses in a virtual reality (VR) platform and the corresponding kinematic information of their arm movement and muscle activities were recorded. The accuracy of the prosthetic interface in determining the intended target poses of the human user during forward reaching is evaluated for different combinations of input features, selected from the kinematic and sEMG sensors worn by the users. The results demonstrate that employing input features that yield a high separability measure between target poses results in a high accuracy in identifying the intended target poses in the execution of the task.
Effective system spectral efficiency applied to a multiple high-altitude platform system

An innovative performance measure, effective system spectral efficiency (ESSE), is proposed. This new performance measure takes into account both the spectral reuse efficiency of an entire system and the spectral efficiency of an individual channel, in order to represent the efficiency of spectrum utilisation in a comprehensive way. The application of this new measure in a multiple high-altitude platform (HAP) system is presented as an example to show its superiority. It is shown that the number of HAPs can be optimised in terms of ESSE, to provide maximum capacity gains for users with a given type of antenna. It is also shown how ESSE can be effectively used to evaluate radio resource management (RRM) schemes that have contradictory performance, which is difficult to evaluate using conventional performance measures.
Joint multi-channel multi-step spectrum prediction algorithm

As wireless communication technology is applied to various fields and the non-renewable nature of spectrum resources, spectrum resources become more and more scarce. Spectrum sensing proposed to improve spectrum efficiency requires a lot of time and energy, therefore, people pay attention to spectrum prediction, but most of existing algorithms are only used for single-step prediction. Thus, we use LSTM, Seq-to-Seq modelling and attention mechanism to design a joint multi-channel multi-step spectrum prediction algorithm. The simulation results show that the prediction performance of the algorithm is better than that of single-channel prediction algorithm.
GTO controlled series capacitors: multi-module and multi-pulse arrangements

This paper describes the GTO controlled series capacitor-G4CSC, an equipment for controlled series compensation of transmission systems. The principles of operation of the GCSC are reviewed and harmonic analysis is performed, showing how much of voltage harmonics are produced by the GCSC. Novel configurations using multi-module and multi-pulse GCSCs are proposed in order to reduce the voltage harmonics. Digital simulations using the EMTP are presented to validate the proposed configurations.
Comprehensive CNN-Based Approach for Helmet Use Detection of Tracked Motor Cycles

Precautionary measures for safety on road and traffic have become key roles played by the new Traffic Regulations and Management, especially for two-wheeler riders. It has been made mandatory for the two-wheeler vehicle riders to wear helmets, which is, unfortunately not being followed by a few riders. In such a scenario, several aspects have been taken into account, resulting in the current project, that consists of the technique where, any two-wheeler rider without wearing helmet, can be detected in places it must be worn compulsorily. In this project, helmet detection and recognition have been deployed mainly using algorithms such as YOLOv2 (You Only Look Once version 2) and LeNet. Any kind of helmet can be detected and recognised under several conditions and cases. Whenever a rider is detected without a helmet from the source file in the format of either image or video, the instance of such malpractice is considered and the output is built by analysing the data. The trained model gives an accurate result at the rate of95% under multiple cases and marks to 1 FPS using CPU.
Research on Computer Modeling of Human Movement

Human body is a complex life forms.A lot of complexity means that affect motor function of factor structure. Human movement is a dynamic feedback process control, need to be coordinated through the visual, vestibular, proprioceptive feedback, not only by the physical laws of gravity, inertia force of domination, but also by the emotional impact of individual factors such as hobbies. Computer modeling of human actions including key frame method, kinematics, dynamics, motion capture method and process control methods. These methods have their own advantages, there are also their limitations. The different methods to combine the use of their complementary strengths will be the focus of future research and development direction.
Design and Error Estimates of Cut Tobacco Feeding by Wind System

The cut tobacco transporting is the absolutely necessarily important tache, whether the transportation process stability is a direct impact on production quality and manufacturing standards. The wind system is adopted by most tobacco companies because of it caused least disruptive of the cut tobacco structure and the pipe network layout of system is flexible, but the wind system is greater influence by itself, different control methods are caused greater difference of process indicators, for example essence and spice ingredients, moisture proportion and smoke flavor. Based on the above reasons, so we need to design the control method of wind system necessarily, in addition we must checkout the control accuracy opportunely, so that it is satisfied by the actual working conditions.
Uncertainty-Aware Recurrent Encoder-Decoder Networks for Vessel Trajectory Prediction

In this paper, we propose a deep learning framework for sequence-to-sequence vessel trajectory prediction based on encoder-decoder recurrent neural networks to learn the predictive distribution of maritime patterns from historical Automatic Identification System data and sequentially generate future trajectory estimates given previous observations. Special focus is given on modeling the predictive uncertainty of future estimates arising from the inherent non-deterministic nature of maritime traffic. An attention-based aggregation layer connects the encoder and decoder networks and captures space-time dependencies in sequential data. Experimental results on trajectories from the Danish Maritime Authority dataset demonstrate the effectiveness of the proposed attention-based deep learning model for vessel prediction and show how uncertainty estimates can prove to be extremely informative of the prediction error.
V2X-based Vehicle Speeding Enforcement System

In this paper, we suggest a vehicle speeding enforcement system based on V2X (Vehicle-to-Everything). Existing camera-based enforcement, which can measure in one direction, has a narrow measurement range and it is difficult to analyze vehicle speed in real time. To overcome these shortcomings, we measure vehicle speed in real time by extracting speed data from the GPS (Global Positioning System) and the IVN (In-Vehicle Network). Also, we aim to expand the scope of enforcement by using a V2X-based system. Under the V2X-based system, we show a wider enforcement range and the instantaneous/average speed of the vehicle in real time. We also analyze the difference in performance between DSRC (Dedicated Short Range Communication) and C-V2X (Cellular-V2X) in the proposed V2X-based system.
Delay Reduction for Liner-Search Based Packet Filters

In general, a packet filter handles incoming pack- ets according to a set of rules. This paper show that the order of rules is critical to the performance of filters that use the linear search algorithm to handle packets. To reduce the fil- tering delay, a rule-order optimization problem is formulated. A simple algorithm to solve this problem is also proposed.
In the Making: The ‘Power to the People’ Workshop Track at Crafting the Future

ABSTRACT Over the last decade several projects and exhibitions have explored how crafts can play a central role for empowerment through social development, innovation and entrepreneurship. In order to facilitate this, there is a need to explore how craft practices can act as tools for empowerment, both in research and practice. The ‘Power to the People’ track at the European Academy of Design Conference in Gothenburg 2013 tried to answer on this challenge with a series craft-based seminars, each centred on a participant's proposed craft or ‘Paper of Practice’. This formed a series of practice-based seminars that mixed hands-on activities and discussion, centred on and emerging from the very act of doing.