Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Realize Highly Accurate Computation with Fully Homomorphic Encryption

In recent years, as the number of cloud services increases, leakage of confidential information is a matter of concern. Techniques for processing data while preserving confidentiality of data are called secure computation, and secure computation based on fully homomorphic encryption (FHE for short) is one of the most important ways of realizing secure computation. FHE is a cryptosystem that can perform both arbitrary times of additions and multiplications of data in the encrypted state. Therefore, by using FHE, we can realize arbitrary operations in the encrypted state. However, it is not so easy to realize complex operations using FHE in practice. In particular, there are difficulties in realizing complex operations with high accuracy. Such computation is highly desired in various situations (e.g., in computing medical statistics). Nevertheless, the methodology to compute complex operations given a certain accuracy is not well studied so far. In this research, we propose a method to compute division and a u-th root in the encrypted state using FHE. In the proposed method, the result of an operation can achieve the given accuracy. We employ the n-th order maclaurin approximate polynomial to approximate division and a u-th root by homomorphic addition and multiplication. We evaluate the error of an approximation using a remainder term. Also, we implemented the proposed method and measured execution time for division and a square root.
Low-Cost 3D-Printed Wireless Soil Moisture Sensor

A fully passive, 3D-printed wireless sensor for detecting soil moisture levels is presented in this paper. The sensor comprises a capacitively loaded antenna whose resonant frequency changes in response to soil moisture level. Results show that a variation in soil moisture levels of 20% by weight causes a change in frequency of 16.66 %. A low-cost sensing scheme for large area soil monitoring is proposed in which the sensors are dispersed in the agricultural land and work in combination with unmanned aerial vehicles (U A V s) which record the sensor readings and send the data to a ground station. Calculations show that the sensors can be read by a UAV flying at an altitude of 298 m. Additive manufacturing technique namely 3D-printing has been used for the fabrication of the sensor.
An Adaptive I-V Curve Detecting Method for Photovoltaic Modules

I-V curve tracers are commonly utilized for commissioning, auditing, operation and maintenance of photovoltaic generators. Many approaches have been published to achieve the objective. The performance can be indexed by the accuracy, speed, reliability, and cost-effectiveness. The tracing speed is important for field test since the irradiance changes from time to time. This paper gives the in-depth analysis of power converters used for I-V curve tracers. Based on the result, an adaptive I-V curve trace method is proposed, which aims to achieve better performance and save the energy during test process. The simulation result shows that the proposed method can improve the performance of I-V tracing in speed and accuracy.
Energy Efficient Resource Sharing in Multi-Operator Heterogeneous Cloud RAN

In this paper, we consider a multi-operator heterogeneous cloud radio access network, where operators share their small cells. A formulation for the energy efficiency of the shared network is suggested and an energy-efficient resource allocation algorithm is proposed for the user assignment and power allocation in the multi-operator network. The problem is formulated as a mixed-integer optimization problem and solved using Lagrange Dual Decomposition method. Numerical results proved the benefits of sharing in terms of network energy efficiency, power consumption and users satisfaction. It also showed the efficiency of the proposed algorithm in achieving additional power saving in a multi-operator Heterogeneous Cloud RAN.
High Efficiency Bidirectional DC-DC Converter with Wide Gain Range for Photovoltaic Energy Storage System Utilization

In this paper, a high efficiency bidirectional dc-dc converter with wide dc gain range face to photovoltaic energy storage system (PESS) based on the 48V battery module is proposed. The dc-dc converter uses two-stage topology, which meets the demand of wide gain range in PESS. The characteristics and design rules of the converter was discussed in detail. A 5kW prototype was built and the experimental results were given in the paper.
Analysing Indicator of Compromises for Ransomware: Leveraging IOCs with Machine Learning Techniques

Ransomware is a malware which is spreading largely around the world and imposing serious threats to information assets and victimizes internet users by hijacking and encrypting their files, and then demanding payment to get back access to the files. Seeking system vulnerabilities, ransomware tries to seize control over the victim’s files and system, until the victim agrees to the attacker’s demands. In this paper, we have extended the work by focusing on Indicator of Compromises (IOCs) for ransomware using Cuckoo Sandbox. These IOCs are used to set the base for the analysis and classification of new ransomware into their respective class. Further, working for the implementation of the proposed idea, we have automated the system using machine learning algorithms for the classification of ransomware variants in the real time environment. To the best of our knowledge, this is the first real time, comprehensive and usable methodology to classify the ransomware in their respective classes.
Joint Spatiotemporal Multipath Mitigation in Large-Scale Array Localization

Large-scale antenna arrays not only have been considered as the key technology in future communications systems, but also promise revolutionary impacts on wireless localization. In this paper, we determine the effects of multipath propagation on the localization performance using large-scale antenna arrays. Such effects can be mitigated by joint temporal and spatial separation of the multipath signals, which are determined, respectively, by the signal bandwidth and the array aperture. In particular, we prove the asymptotic spatial orthogonality of large-scale multiple-input multiple-output (MIMO) localization with general non-orthogonal waveforms, showing that the multipath effects will vanish when the number of transmitter or receiver antennas goes large. Then, the Fisher information matrices for the position and orientation are derived to characterize the performance bounds of MIMO localization. Finally, a direct localization algorithm based on the coherent decoupled maximum likelihood criteria is developed for multipath environments. Numerical results validate our theoretical analysis and the performance of the proposed algorithm.
What User Interface to Use for Virtual Reality? 2D, 3D or Speech–A User Study

In virtual reality different demands on the user interface have to be addressed than on classic screen applications. That's why established strategies from other digital media cannot be transferred unreflected and at least adaptation is required. So one of the leading questions is: which form of interface is preferable for virtual reality? Are 2D interfaces—that are mostly used in combination with mouse or touch interactions— the means of choice, although they do not use the medium's full capabilities? What about 3D interfaces that can be naturally integrated into the virtual space? And last but not least: are speech interfaces, the fastest and most natural form of human interaction/communication, which have recently established themselves in other areas (e.g. digital assistants), ready to conquer the world of virtual reality? To answer these question this work compares these three approaches based on a quantitative user study and highlights advantages and disadvantages of the respective interfaces for virtual reality applications.
The Soft-Switching Technique for RB-IGBT based T-Type Three-Level Inverter

In this paper, the reverse-blocking IGBT (RBIGBT) based soft-switching T-type three-level inverter is proposed. With traditional PWM control scheme, zero current switching (ZCS) at turning on and zero voltage switching (ZVS) at turning off are achieved for reducing extra switching loss by passive snubber. The operating principles are given in detail and the parameter design of resonant tank is analyzed based on the state-plane trajectory. Besides, the oscillations caused by device’s parasitic capacitance have been analyzed, and an oscillation suppression measure is also presented using root locus method. Finally, experiments with a single phase prototype are provided to verify the effectiveness of the proposed inverter.
FDQ: Advance Analytics Over Real Scientific Array Datasets

Scientific data is not only rapidly increasing in size, but in complexity of operations performed upon as well. Compared to the prevalent use of ad-hoc approaches, structured operators provide many benefits. In this paper, we introduce FDQ - an Analytical Functions Distributed Querying Engine intended for Array Data. Motivated by needs of climate scientists in terms of both functionality and scalability, we make three major contributions: First, we introduce a new class of analytical querying - querying over windows where the planes that construct these windows are internally ordered. An example of this querying type is the introduced MINUS analytical function, a function that supports querying over accumulative measurements with data resets. Second, we describe in detail memory management optimizations for efficient processing of analytical (and other structured operators) querying over large datasets. Last, we provide efficient methods to execute these queries in parallel, using a sectioned (tiled) approach. We evaluate our methods using real multi-dimensional climate datasets, and show they outperform existing approaches. When running locally (not in a distributed manner), we observed an average performance improvement of 538% compared to other engines for analytical calculations. We also show our methods performance improve linearly with the provided computing resources (scale up and out).
A Computer Vision Approach Based on the Retinal Nerve Fiber Thickness Analysis to Estimate the Risk of Suffering Glaucoma

According to estimations of the World Health Organization (WHO), approximately 4.5 million persons will become blind due to the primary Glaucoma. For these reasons, in this paper, we present a simple approach to estimate the risk of suffering from glaucoma that presents a patient. Our proposal relies on the automatic analysis of Optical Coherence Tomography (OCT) images through the calculus of nerve fiber and ganglionary vessels areas. To this aim, our system separates the two areas mentioned before through computer vision techniques and the Newton Interpolation Method. Once the two areas are separated, the system determines the size of each of them. This proposal was validated through an experiment carried out with OCT 30 images (per eye). The results are encouraging, and the suggestions provided by the system match with medical diagnosis.
Data Quality Best Practices in IoT Environments

The Internet-of-Things (IoT) is a network of physical devices embedded with electronics, sensors, actuators, and connectivity enabling these objects to connect and exchange data. The IoT brings more data than ever before, connecting cyber and physical worlds, which enable people to make better decisions. The very nature of the IoT environment generating giant volumes of data gathered from several heterogeneous sources creates important data quality challenges that need to be addressed. This is because inadequate levels of data quality impact negatively all the working of the IoT network. Despite the fact that data quality has been broadly studied outside the IoT field, and huge standardization efforts are behind the concept, data quality management in the IoT has not been investigated in-depth. This paper presents an approach for managing data quality in 'smart, connected product (SCP)' environments, grounded on the series of international standards ISO/IEC 25000 and ISO 8000. Our approach provides a set of best practices for assessing and improving data quality in such environments.
Integrated Data Acquisition Terminal Used on Board

Based on the Linux system, we design and implement a shipboard terminal that integrates data acquisition, processing, sending and receiving. Furthermore, on this terminal, a video service was set up to transmit offshore operations video to the shore-based command center. Data collected by the sensor are sent to the shore-based data center regularly through Beidou short message module. Based on the analysis and calculation of the original data, the shore-based super computing center pushes the calculated results back to the ship, providing more security for the safe and stable navigation of the scientific survey ship.
An Ontology for Service Semantic Interoperability in the Smartphone-Based Tourist Trip Planning System

This paper presents an ontology-based approach for semantic interoperability tourist trip planning services. The proposed ontology describes a tourist, an attraction route and context information about tourist and his/her environment. This ontology is developed within the Tourist Trip Planning System, which consists of a set of interacting services. All services work accordingly to the proposed ontology which leads to service semantic interoperability and allows to increase interaction speed between them.
Cross-Track Infrared Sounder Spectral Gap Filling Toward Improving Intercalibration Uncertainties

The cross-track infrared sounder (CrIS) is a hyper-spectral infrared sounder with 2211 (full-spectral resolution) channels over three wavelength ranges. Due to its excellent calibration and high spectral resolution, CrlS radiances are also used as an infrared reference to check calibration accuracy of other narrow- or broadband instruments. However, there are spectral gaps between the CrlS bands, which impact the accuracy of intercomparison between CrlS and other instruments. To fill up the spectral gaps, this paper develops a new method to predict the CrlS gap channels. A training data set was first built based on the spectra selected from different seasons to represent different atmospheric and surface conditions. The principal component regression method is then developed to derive the prediction coefficients between the CrlS measured and the gap channel spectra. The prediction accuracies are around 0.005 K ± 0.18 mK, 0.06 K ± 0.45 mK, and 0.05 K ± 0.71 mK for the long-, middle-, and short-wave gap channels, respectively. It should note that the predicted channels are intended to be only used in the intercomparison purposes instead of providing exact information of these gap channels. When comparing the CrlS gap radiances with atmospheric infrared sounder and infrared atmospheric sounding interferometer, consistent results are observed between CrIS and other sounders. The further intercomparison results with visible infrared imaging radiometer suite and advanced baseline imager suggest that the predicted gap radiances are good enough for the intercalibration purposes and this method can be confidently applied in global space-based intercalibration system community.
Study on the Electro-Thermal Characteristics of Three-Level NPC Inverter Based on 60°Discontinuous Space Vector PWM Strategy

The loss of the inverter has a direct impact on its safe and reliable operation. If the loss is too large, the junction temperature of the power device will increase, and on the other hand, the power utilization rate will be reduced. Research shows that DSVPWM strategy can effectively reduce the switching loss of inverter. Based on this, this article first gives a brief introduction to the principle of DSVPWM strategy. Secondly, a closed-loop control method is proposed according to the power factor angle of load side, and the loss and junction temperature of DSVPWM are calculated and analyzed. Finally, the simulation and experimental results verify the effectiveness of the proposed control method.
BlockPGP: A Blockchain-Based Framework for PGP Key Servers

Pretty Good Privacy (PGP) is one of the most prominent cryptographic standards offering end-to-end encryption for email messages and other sensitive information. PGP allows to verify the identity of the correspondent in information exchange as well as the information integrity. PGP implements asymmetric encryption with certificates shared through a network of PGP key servers. Many recent breaches show that certificate infrastructure can be compromised as well as exposed to operational errors. In this paper we propose a new PGP management framework with the key server infrastructure implemented using blockchain technology. Our framework resolves some problems of PGP key servers focusing in particular on fast propagation of certificate revocation among key servers and elimination of man-in-the-middle risk. We also provided user access right control where only the certificate holder can change information related to the certificate. We designed and developed a prototype for key server deployment on permissioned Ethereum blockchain. Permissioned blockchain should allow to control the costs of PGP key server infrastructure maintenance at the present level.
Experience Building IT Infrastructure for Research with Online Youth Mental Health Tools

There is great potential for online tools to be helpful for youth mental health, but equally there are many open research questions requiring field trials. Such research places considerable demands on IT infrastructure to provide appropriate data management, and to be maintainable and scalable through iterations of studies. We report experience building an IT infrastructure for research with online tools for youth mental health. The aim is to create a platform that enables an 'ecosystem' of youth mental health software to be available for field trials and beneficial usage. Key services of the platform include identity management, health assessment storage and reasoning, usage logging, and clinical trial consent and randomisation. This paper reports initial design of the platform, first field tests and ongoing iterative development.
In-Band and Out-Of-Band Distortions Optimization for ATSC 3.0 Transmission: A Novel TR PAPR Reduction Algorithm

This paper presents a novel Tone Reservation (TR) Peak to Average Power Ratio (PAPR) algorithm for the American digital video broadcasting (ATSC 3.0) standard. As any multicarrier communication systems, ATSC 3.0 transmitters suffer from high peaks of the transmitted signal. The high signal fluctuations constitute a major disadvantage of these systems. Indeed, they constraint the high power amplifiers to operate in their linear region which leads to poor spectral efficiency. To reduce the amplitude of the signal peaks, a TR gradient based algorithm has been proposed as an option within the ATSC 3.0 standard. Although TR-based algorithms have been intensively investigated these last years, very few today’s transmitters implement these algorithms as they do not offer a high performance/complexity trade-off. This paper presents a novel TR-based algorithm, named as Grouped Carrier Peak Windowing (GCPW), which offers higher performance than the standard TR gradient-based algorithm while being implementable and compatible with the ATSC 3.0 standard. We also show through simulations that the proposed algorithm highly outperforms the gradient-based standard algorithm in terms of both in-band and out-of-band distortions. Results show that the novel algorithm offers very promising performance in terms of both modulation error rate and shoulder attenuation.
Space Vector Modulation for Multi-Source Inverters

Multi Source Inverters (MSI) as a magnetic-less approach for active control of Hybrid Energy Storage Systems (HESS) in Electric Vehicles (EVs) have been proposed lately. Using such technologies leads to more compact and more efficient HESS in EVs. In this paper, a novel Space Vector Modulation (SVM) technique is surveyed for a recently proposed modular MSI. This method is not limited to the proposed MSI and can be applied to any type of MSIs. Since SVM, in general, requires a heavy calculation burden, this method not only simplifies the mathematical computational steps, but also enhances the implementation speed, and lowers the hardware requirements. Different steps of the method are explained through theory and math. Simulation results are implemented on a recently proposed modular MSI for US06 driving cycle using vector speed control of the induction machines in Matlab/Simulink environment. Finally, the method is implemented on a 1 kW lab prototype of the MSI, which validates the theory and the simulations.
A Novel Tuning Method for PD Control of Robotic Manipulators Based on Minimum Jerk Principle

In this paper we introduce a novel technique for optimal tuning of PD controllers engaged in tracking minimum-jerk (MJ) trajectories. The proposed approach is an attempt to bridge the gap between the MJ principle for trajectory planning, which is based solely on the robot's kinematics, and the optimal estimation of the gains of the joint controllers, which depends on the robot dynamics. For this purpose we define an objective function that combines kinematic and dynamic-based performance indices and is minimized via a genetic algorithm that searches for optimal gains for the joint controllers. The proposed approach is shown to perform consistently better than the standard PD control for tracking MJ trajectories.
Fast Unloading Transient Recovery of Buck Converters Using Series-Inductor Auxiliary Circuit based Sequence Switching Control

This paper presents a sequence switching control (SSC) scheme for buck converters with a series-inductor auxiliary circuit, aiming at improving the load transient response. During an unloading transient, the series inductor is controlled as a small equivalent inductance so as to achieve a fast transient regulation. While in the steady state, the series inductor behaves as a large inductance to reduce the output current ripple. Furthermore, on the basis of the proposed variable inductance circuit, a SSC control scheme is proposed and implemented in a digital form. With the proposed control scheme the unloading transient event is divided inton+ 1 sub-periods, and in each sub-period, the capacitor-charge balance principle is used to determine the switching time sequence. Furthermore, its feasibility is validated in experiment with a 12V-3.3V low-voltage high-current synchronous buck converter. Experimental results demonstrate that the voltage overshoot of the proposed SSC scheme has improved more than 74% compared to that of the time-optimal control (TOC) scheme.
Non-Intrusive Load Monitoring: an Architecture and its evaluation for Power Electronics loads

NILM (Non-Intrusive Load Monitoring) may well become a widespread solution for diagnostic of Electrical Energy consumption available to every end user. Such a diagnostic may identify waste and improper use; it is also an important tool for energy management both by the residential users and by commercial/industrial users. An architecture for a NILM solution is proposed and evaluated. A comparison is performed among common NILM event detection algorithms and the algorithms proposed in this work. Of particular interest in this study is the detection and classification of power electronics loads, as they impose specific challenges in their detection and correct disaggregation (classification). Our proposed algorithm achieved 100% detection of on/off events for the loads in the COOLL dataset.