Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a Novel Low-Cost Consequent-Pole Permanent Magnet Synchronous Machine

This article proposes a novel low-cost consequent-pole permanent magnet (CPM) synchronous machine structure, considering the reluctance torque utilization. First, a novel CPM machine with doubled salient ferromagnetic iron poles (ICP-PMSM) is proposed, featuring an N pole – iron – S pole – iron sequence to maximize the reluctance torque utilization and reduce cost. Flux barriers are integrated into the rotor structure to maintain the same magnetic rotor pole number as the conventional CPM synchronous machine (CP-PMSM). Second, for a low torque ripple, soft ferrite is used to replace part of the iron pole in the ICP-PMSM (ISCP-PMSM) to improve the air-gap flux density distribution. Furthermore, the CP-PMSM, ICP-SPMSM, and ISCP-PMSM rotors are optimized for a fair comparison. The electromagnetic performances of all the optimized machines are compared with those of a conventional surface permanent magnet synchronous machine (SPMSM). It is demonstrated that the ISCP-PMSM can obtain an almost equivalent torque and torque ripple, but with reduced PM (NdFeB) usage and cost when compared to the SPMSM.
Analytical Model of Band-to-Band Tunneling in ATLAS-TFET

The Atomically Thin and Layered Semiconducting-channel Tunnel Field Effect Transistor (ATLAS-TFET) is a recent development from the conventional TFET that shows a sharp transition from off to on and has an exceedingly low subthreshold swing (SS) with minimum recorded value of 3.9 millivolts per decade. In this paper, a semiclassical analytical model of the tunneling current of this device is derived. The electric field and charge concentration is calculated by solving Poisson's equation. The generation current is then obtained using Kane's generation model for band-to-band tunneling (BTBT) along with maximum electric field approximation (MEFA). Quantum mechanical factors are incorporated in our model using necessary correction factors. The values obtained from this model are plotted along with the experimental data and the results are found to be very similar.
A Modeling Study on Performance of a CNOT Gate Devices based on Electrode-driven Si DQD Structures

Behaviors of quantum bits (qubits) encoded to electron spins in silicon double quantum dot (Si DQD) systems are examined with a multi-scale modeling approach that combines electronic structure simulations and Thoas-Fermi calculations. Covering the full-stack functionality of Si DQD devices from electrode-driven charge controls to logic operations, we investigate the sensitivity of exchange interaction between two initialized qubits and its effect on the fidelity of controlled-NOT gate operations to understand the experimental reported feature. This preliminary work not only presents a theoretical clue for understanding the major control factors for the gate fidelity, but opens the possibility for further exploration of the engineering details of qubit logic gate devices that is hard to be uncovered with experiments due to the time and the expense.
Dead-Zone Free Control Scheme for H-Bridge Buck–Boost Converter

The H-bridge buck–boost converter shows better efficiency compared to all other buck–boost converter variants due to the ability to work in buck and boost modes. The existence of dead-zone in voltage gain during mode transition due to the maximum and minimum duty limitations results in instability and oscillations in output voltage. This dead-zone is eliminated by overlapping the buck and boost gate signals, which results in efficiency decrement due to high switching loss. Using a common compensator in all the modes in the H-bridge buck–boost converter results in poor dynamic performance. In this article, dead-zone free control (DZFC) scheme with increased efficiency and improved dynamic performance is proposed to mitigate the dead-zone during mode transition. In the proposed DZFC scheme, dead-zone elimination is independent of the values of mode boundaries, which reduce the transition mode duration. The proposed DZFC scheme improves the efficiency during transition modes by reducing the switching loss, a generalized small-signal model valid for the buck, boost, and transition modes and a control design is proposed for improved dynamic performance. The proposed DZFC scheme is verified experimentally on a hardware H-bridge buck–boost converter prototype.
Predictive Modeling on MEG Signal to Classify Hand and Wrist Movement using UNEQ and KNN

The domain of Brain-Computer Interface (BCI) explores how humans can interact with the computer without giving direct instruction. Recognizing the activity from brain signals affiliated with an electronic device might (i.e. MEG) provide a stepping stone in the field of BCI. The intended algorithm in the paper aimed at presenting a statistical strategy to classify the brain signal from the MEG signal data, provided by BCI competition IV dataset III. The algorithm is compartmentalized in three levels: preprocessing, feature extraction, and classification. Autoregressive features have been extracted from the signals to classify using UNEQ, KNN and SIMCA, discuss the data distribution and asses how well the algorithm performs on unknown yet similar distribution. The proposed algorithm has obtained 64% prediction accuracy and 67% validation accuracy, which exceeds the current highest result reported on the same dataset.
Multi-zone engine combustion model calibration using genetic algorithms

The more severe emission regulations are forcing the engine builders to refine the design of combustion chamber and port geometry together with integration of new electronically controlled strategies. In order to make engine models trustworthy they are usually calibrated to fit the measurement data collected on test engine, research cylinder or already measured data from a similar engine. The model calibration is high effort and durable process if high model quality wants to be achieved. In this paper the model calibration was performed using genetic algorithm for parameterization of Multi-zone combustion model. The method showed to be time efficient and with high output quality. From the genetic algorithm search space, the points where chosen that have entered into the error tolerance space to determine the combustion model parameters range for two stroke low speed marine diesel engines. The combustion model parameters range allows to speed up the calibration process on a different large two stroke low speed marine diesel engine when using genetic algorithms or some other optimization method. The combustion model parameters range is also useful in early design phase when no measurement data is available to determine the design boundaries. The detected parameter range was tested on a new larger two stroke diesel marine engine and mean integrated squared error had showed high matching between in-cylinder measured and simulated pressure traces.
LVTTL and SSTL IO Standards Based Energy Efficient FSM Design on 16nm Ultrascale Plus FPGA

Reducing power dissipation of any device at design stage leads to saving of power consumption in the lifetime of the device that eventually results in saving of energy and resources. With the emergence of Green Computing, energy efficiency has become an important criterion in designing any device. In this work, we are going to design an LVTTL and SSTL IO Standards based energy efficient FSM on a 16nm Ultrascale Plus FPGA. Manufacturer of Ultrascale Plus FPGA claims that it consumes half power in comparison to 7 Series (28nm) FPGA. Here, the power consumption of design of FSM for two different IO standards, LVTTL and SSTL is observed at different output loads: 0,100 and 10000. We compare the power consumptions of the design for LVTTL and SSTL IO standards to find the most energy efficient architecture for our design among the two. At output load 0, there is 36.51% saving in total on chip power consumption, 84.29% saving in dynamic power consumption and 0.59% saving in static power consumption when we migrate our design from LVTTL to SSTL12. At output load 0, there is 36.06% saving in total on chip power consumption, 83.24% saving in dynamic power consumption and 0.59% saving in static power consumption when we migrate our design from LVTTL to SSTL15. In comparison to LVTTL, there is a significantly less power consumption at different output loads when using SSTL12 and SSTL15 IO standards. The designed FSM will be helpful in reducing heat dissipation, overcoming power management challenges and enhancing the energy efficiency of any device.
ÉTUDE ET ÉLABORATION DE REVÊTEMENTS MULTICOUCHES POUR L'OPTIQUE EXTRÊME UV DANS LA GAMME SPECTRALE 30-50 NM

L'elaboration de nouveaux revetements interferentiels multicouches est motivee par la demande de l'astrophysique solaire et par le developpement de nouvelles sources de rayons EUV (source a generation d'harmoniques d'ordre eleve, laser X, rayonnement synchrotron). Nous avons etudie et developpe differents systemes multicouches possedant a la fois des proprietes optiques optimisees (reflectivite et/ou bande passante) et une bonne stabilite temporelle et thermique pour la gamme de longueurs d'onde comprise entre l=30 nm et l=50 nm. Des multicouches destinees a la selection d'harmonique ont ete optimisees et utilisees pour la realisation d'un interferometre EUV. Une augmentation significative de la reflectivite des multicouches dans la gamme spectrale de 30 a 40 nm a ete obtenue par l'addition d'un troisieme materiau dans l'empilement. Une etude comparative des courbes de reflectivites theorique et experimentale en fonction de la longueur d'onde a ete menee. Les differences observees ont pu etre expliquees notamment a l'aide de l'analyse des proprietes physique des differents materiaux en couche mince. Nous montrons egalement que l'utilisation de ces multicouches a trois materiaux par periode permet le developpement d'empilements repondant a des demandes specifiques (miroirs a large bande passante, miroirs a double bande). Pour les longueurs d'ondes comprises entre 35 nm et 50 nm nous avons developpe des multicouches a base de scandium. Cette etude a permis d'obtenir des multicouches avec de forts pouvoirs reflecteurs et une bonne stabilite temporelle. La stabilite de ces empilements a pu etre ameliorer a l'aide de l'insertion aux interfaces de couches barrieres
Efficient Sliding Window Decoding of Spatially Coupled LDPC Codes for Broadcasting

Spatially-coupled low-density parity-check (SCLDPC) codes, which are capable of universally achieving capacity over different channels, could be a potential candidate of error control channel codes employed in flexible transmission schemes for future broadcasting systems. Sliding window decoding is believed the preferred decoding method for SC-LDPC codes, due to its lower decoding latency and complexity compared to conventional full belief propagation (BP) decoding, and is studied in this paper for SC-LDPC codes under broadcasting scenario. More specially, the optimal window size for sliding window decoding is investigated in this paper to improve the decoding performance under practical constraints of decoding complexity and latency in broadcasting systems. The early termination strategies are also considered to further reduce the decoding complexity. Finally, simulation results are presented, which demonstrate that the proposed sliding window decoding method has decoding complexity comparable to conventional LDPC decoding and shows consistent excellent decoding performance.
Distributed Boosting Variational Inference Algorithm Over Multi-Agent Networks

Distributed Bayesian estimation over multi-agent networks has received much attention due to its broad applications, where each agent has its private data that is unavailable to other agents. For efficient inference over multi-agent networks, we develop a distributed boosting variational inference (DBVI) algorithm with limited communication. We first decompose the global cost function into a sum-of-costs form, where each local cost only relates to its own dataset. Then, the global posterior distribution is approximated by a gradient decent at each boosting step, followed by a consensus protocol for cooperation with the neighbors. Moreover, we derive DBVI with Gaussian mixture model (DBVI-GMM) in detail. Finally, simulations on the synthetic and real datasets illustrate the effectiveness of the proposed algorithm.
Dual Band Monopole Antenna with Concentric Square Electromagnetic Band Gap (EBG) Structure

In this Paper, a Dual Band Monopole Antenna has been presented for GSM 900 and Wi-Fi band. To improve the performance parameters of the antenna, concentric square shaped electromagnetic band gap (EBG) structure has been incorporated. FR4 substrate is used and the proposed antenna is fed by line feed technique. The outer cell of $6.8533^{\ast}6.8533\text{mm}^{2}$ has been designed for GSM 900 band and inner cell of $2.557^{\ast}2.557\text{mm}^{2}$ is tuned to Wi-Fi band. The structure without EBG, reported a gain of 6.1928dB and 5.72499dB for GSM 900 band and Wi-Fi band respectively. The return loss of - 16.36116dB and -14.12084dB was obtained for GSM 900 and Wi-Fi band correspondingly. Introducing a concentric square EBG cells, the gain of 6.3391dB and 7.1013dB is obtained for GSM 900 and Wi-Fi bands individually. Return loss of the antenna is also improved for both the bands which makes the proposed antenna suitable for GSM and Wi-Fi applications.
A Compact Grounded Asymmetric Coplanar Strip-Fed Flexible Multiband Reconfigurable Antenna for Wireless Applications

A compact grounded asymmetric coplanar strip (GACS)-fed flexible multiband frequency reconfigurable antenna with two PIN diodes is proposed. The investigated antenna is backed by a flexible polyamide substrate with compact dimensions of 24 mm $\times19$ mm and a thickness of 1.53 mm. The investigated antenna structure contains a monopole patch that facilitates operation for wireless LAN applications, whereas inverted L-shaped and F-shaped monopoles facilitate operation for Bluetooth and 5G NR applications. The investigated antenna operates at 2.4, 3.8, and 5.6 GHz with measured impedance bandwidths of 5.8%, 6.3%, and 6.6%, respectively, over the three frequency bands, thus facilitating coverage for Bluetooth, 5G NR, and WLAN standards. The two PIN diodes are employed to tune the investigated antenna among four modes, including a single band mode (WLAN 5.5 GHz), two dual-band modes (5G NR 3.8/5.6 GHz, and Bluetooth 2.48/5.6 GHz), and one multiband mode with Bluetooth (2.4 GHz), 5G New Radio (NR) N77 band (3.8 GHz), and WLAN (5.6 GHz) modes. The investigated antenna radiates unidirectionally with a peak gain of 3.73 dBi at 5.6 GHz. Measurements are carried out on the human body to investigate the behaviour of the wearable antenna. The simulated SAR values are in a safe limit of 1.6 W/kg for 1 g of tissue, according to the FCC. Moreover, the investigated antenna shows extremely low vulnerability to degradation in performance as a result of bending effects concerning impedance matching with acceptable acquiescence between measurements and simulations.
Detecting outliers and anomalies to prevent failures and accidents in Industry 4.0

Due to the rapid development of IT and sensorial technologies in the previous decade, the fourth industrial revolution, Industry 4.0 has become a reality. Many new terminologies and approaches were introduced in this concept. Combined with the new technologies and advantages of the 5G telecommunication networks it is possible to gain much faster response times over a reliable infrastructure which paves the way towards efficient industrial control. Based on historical datasets and using the knowledge of the domain specific experts it is possible to label those records with the corresponding key performance indicators which stand out as anomalies or outliers from the normal operation behavior. This paper is concerned with developing new algorithms for fast identification of outliers, which ensure high operational reliability. Our approach is statistical driven, once the usually high dimensional data is mapped into a low dimension for tractable analysis, outliers are captured by statistical decision techniques. As the corresponding numerical analysis performed on industrial data has demonstrated, the method has a reliable performance. Thus, the new methods can prove to be appropriate tools for industrial control in Industry 4.0 environment.
Comparative Run Time Analysis of LiDAR Point Cloud Processing with GPU and CPU

The Light detection and ranging (LiDAR) sensor is well known for its application in the field of surveying and autonomous vehicles. It is used for capturing the three-dimensional view of a scene. The output of the LiDAR sensor, known as point cloud, contains a large number of spatial points leading to bulky data. Any algorithm developed for this data consumes too much time, making it impractical to be used for real-time applications. Recently, Graphics Processing Units (GPUs) have been extensively used for performing the parallel operation. In this paper, we have quantitatively verified the usefulness of GPU for faster LiDAR point cloud data processing as compared to CPU. Algebraic operations were performed on LiDAR point cloud data on GPU, and the run time was found to decrease up to one-sixth as compared to Central Processing Unit (CPU).
A True Power Allocation Constraint for Non-Orthogonal Multiple Access with M-QAM Signalling

Non-orthogonal multiple access (NOMA) scheme is seen as a strong candidate for future wireless networks thanks to its spectral efficiency. Thus, NOMA has attracted a great recent attention and the power allocation (PA) in NOMA has been analyzed in terms of various perspectives. However, all these studies analyze only the Shannon limit and the detection at the users have not been considered in detail. In this paper, we propose a true PA constraint for a detectable NOMA signal design in multi-user NOMA schemes with arbitrary M-QAM signalling. With the proposed PA constraint, the successful detection at the receivers are guaranteed. We evaluate the proposed PA with computer simulations. We also compare with other PA strategies in the literature and present that if the provided PA constraint is not satisfied, none of the users can detect it symbols and all users have the worst bit error rate (BER) performance (i.e., 0.5). Finally, we demonstrated that for a reliable communication, the number of users and/or the modulation orders of the users should be limited.
SAR-based Localization of UHF-RFID Tags in Smart Warehouses

This paper presents the application of the SAR- based localization for UHF-RFID tags in smart warehouses, when readings are acquired along multiple apertures. The reader antenna motion is achieved through a robot typically employed for item inventory. Two different estimation methods are investigated. The first one foresees an average operation among consecutive estimated tag positions when the SAR-based method is applied to single trajectories. Indeed, the second one adopts the SAR-based method jointly to the phase data collected along multiple trajectories. The method applicability is discussed by considering different trajectory configurations and different sources of error through both numerical simulations and an experimental analysis.
Molecular Dynamics Modeling of the Radial Heat Transfer from Silicon Nanowires

Thermal transport in radial direction in Si nanowires embedded into amorphous silicon dioxide has been studied using nonequilibrium molecular dynamics simulations. For comparison, we also considered the axial heat transfer. For Si nanowires with a radius of 2.6 nm, both radial and axial thermal conductivities were found to be about independent of the SiO2 thickness ranging from 1 nm to 3 nm. The radial thermal conductivity of the Si core and of the covering SiO2 material are similar and nearly equal to 1 $W\cdot K^{-1}\cdot m^{-1}$. Thermal resistances for the heat transfer from uniformly heated nanowires in radial direction are by a factor of 3 to 4 lower than those for the heat transfer in axial direction.
Detecting Malware Injection with Program-DNS Behavior

Analyzing the DNS traffic of Internet hosts has been a successful technique to counter cyberattacks and identify connections to malicious domains. However, recent stealthy attacks hide malicious activities within seemingly legitimate connections to popular web services made by benign programs. Traditional DNS monitoring and signature-based detection techniques are ineffective against such attacks. To tackle this challenge, we present a new program-level approach that can effectively detect such stealthy attacks. Our method builds a fine-grained Program-DNS profile for each benign program that characterizes what should be the “expected” DNS behavior. We find that malware-injected processes have DNS activities which significantly deviate from the Program-DNS profile of the benign program. We then develop six novel features based on the Program-DNS profile, and evaluate the features on a dataset of over 130 million DNS requests collected from a real-world enterprise and 8 million requests from malware-samples executed in a sandbox environment. We compare our detection results with that of previously-proposed features and demonstrate that our new features successfully detect 190 malware-injected processes which fail to be detected by previously-proposed features. Overall, our study demonstrates that fine-grained Program-DNS profiles can provide meaningful and effective features in building detectors for attack campaigns that bypass existing detection systems.
Impact of Interface Traps on Negative Capacitance Transistor: Device and Circuit Reliability

In this work, we investigate the impact of Si-SiO2 interface traps on the performance of negative capacitance transistor, which is a promising emerging technology that aims at achieving a steep sub-threshold slope. Interface traps induced degradation is well known to be one of the major concerns when it comes to reliability. We focus on investigating the impact of different interface trap concentrations on the figures of merit of both the devices and circuits. Our investigation is performed using TCAD models, which are well calibrated against 14nm production quality FinFETs. This allows accurate analysis and modeling of the impact of NC on the electric field across the SiO2 layer. Then, the industry compact model of FinFET (BSIM-CMG) is fully calibrated to reproduce TCAD data. In addition, a physics-based NC model is integrated and solved self-consistently within the BSIM-CMG model in which TCAD data of NC-pFinFETs and NC-nFinFETs are also well matched. This allows studying how interface traps induced degradation can impact circuits. Our results demonstrate that the amplified electric field across the SiO2 layer within NC-pFinFET due to NC effect leads to a higher interface trap concentration. This, in turn, results in a larger degradation in the NC-pFinFET compared to its pFinFET counterpart – when both of these devices are operated at the same nominal supply voltage of the 14nm node. However, at the same interface trap concentration, the NC-pFinFET always exhibits less degradation than the baseline pFinFET due to the former’s better electrostatic integrity on account of voltage amplification effect. With respect to circuits, we study both Ring Oscillator (RO) and 6-T SRAM cell circuits. We show how the frequency of RO in the case of NC-FinFET is always less impacted by interface trap induced degradations compared to its counterpart FinFET-based RO. For 6-T SRAM cell, we demonstrate how the key reliability metrics such as hold noise margin, read noise margin, and write noise margin are also less impacted by the induced degradations in NC-FinFET SRAMs compared to the baseline FinFET SRAMs. This is because of the much better electrostatic integrity that NC provides.