Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequence Modeling for Intelligent Typing Assistant with Bangla and English Keyboard

Typing Assistant is a helping tool that autocompletes writing, both by completing current words and suggesting relevant word sequences. Smart typing assistant is the one that can suggest more than just the current word. Based on the context, it is able to suggest the next few words that are relevant. In this work, we propose such a model using the recent advancement of the recurrent neural network. It is a context-aware model that can predict the next few words conditioning on the context user is writing. This is a general purpose solution to typing assistant system. Our work stands out from other research in two cases. First, rather than using only a temperature variable to introduce randomness in the generation and choosing only one character, we used beam search to generate multiple words suggestion. Second, we used encoder-decoder architecture to generate more than the one-word suggestion. Often more than one word of this suggestion is relevant enough to choose and that makes the typing more efficient. We tried it for both Bangla and English. In both cases, it gave impressive suggestions during typing.
Compensation of the Temperature Measurement Signal in an Experimental Dilatometer by Joule Heating and Controlled Atmosphere

The signal compensation was performed for two temperature sensors, an infrared pyrometer and a K-type thermocouple, which are used to measure and control the temperature in an experimental dilatometer by Joule heating and controlled atmosphere. Sensor signals were corrected by compensation polynomials determined experimentally and encoded in LabVIEW™. The compensation polynomials were validated with the experimental thermal history, correcting the temperature signal of both sensors. Finally, compensation polynomials were implemented in the temperature control system of the experimental dilatometer to exchange the signal sensor from a low to high temperature range.
An Interference Mitigation Technique for FMCW Radar Using Beat-Frequencies Interpolation in the STFT Domain

A frequency-modulated continuous-wave (FMCW) radar interference mitigation technique using the interpolation of beat frequencies in the short-time Fourier transform (STFT) domain, phase matching, and reconfigurable linear prediction coefficients estimation for Coherent Processing Interval processing is proposed. The technique is noniterative and does not rely on algorithm convergence. It allows the usage of the fast Fourier transform (FFT) as the radar’s beat-frequency estimation tool, for reasons such as real-time implementation, noise linearity after the FFT, and compatibility with legacy receiver architectures. Verification is done in range and in range-Doppler using radar experimental data in two ways: first by removing interferences from interference-contaminated data and second by using interference-free data as the reference data, and processing it—as if it had interferences—using the proposed technique, inverse cosine windowing and zeroing for comparison. We found that processing with the proposed technique closely matches the reference-data and outperforms the inverse cosine windowing and zeroing techniques in 2-D cross correlation, amplitude, and phase average errors and phase root-mean-square error. It is expected that the proposed technique will be operationally deployed on the TU Delft simultaneous-polarimetric PARSAX radar.
FMP30 is required for the maintenance of a normal cardiolipin level and mitochondrial morphology in the absence of mitochondrial phosphatidylethanolamine synthesis

Mitochondria of the yeast Saccharomyces cerevisiae contain enzymes Crd1p and Psd1p, which synthesize cardiolipin (CL) and phosphatidylethanolamine respectively. A previous study indicated that crd1Δ is synthetically lethal with psd1Δ. In this study, to identify novel genes involved in CL metabolism, we searched for genes that genetically interact with Psd1p, and found that deletion of FMP30 encoding a mitochondrial inner membrane protein results in a synthetic growth defect with psd1Δ. Although fmp30Δ cells grew normally and exhibited a slightly decreased CL level, fmp30Δpsd1Δ cells exhibited a severe growth defect and an about 20‐fold reduction in the CL level, as compared with the wild‐type control. We found also that deletion of FMP30 caused a defect in mitochondrial morphology. Furthermore, FMP30 genetically interacted with seven mitochondrial morphology genes. These results indicated that Fmp30p is involved in the maintenance of mitochondrial morphology and required for the accumulation of a normal level of CL in the absence of mitochondrial phosphatidylethanolamine synthesis.
Efficient Construction for Full Black-Box Accountable Authority Identity-Based Encryption

Accountable authority identity-based encryption (A-IBE), as an attractive way to guarantee the user privacy security, enables a malicious private key generator (PKG) to be traced if it generates and re-distributes a user private key. Particularly, an A-IBE scheme achieves full black-box security if it can further trace a decoder box and is secure against a malicious PKG who can access the user decryption results. In PKC’11, Sahai and Seyalioglu presented a generic construction for full black-box A-IBE from a primitive called dummy identity-based encryption, which is a hybrid between IBE and attribute-based encryption (ABE). However, as the complexity of ABE, their construction is inefficient and the size of private keys and ciphertexts in their instantiation is linear in the length of user identity. In this paper, we present a new efficient generic construction for full black-box A-IBE from a new primitive called token-based identity-based encryption (TB-IBE), without using ABE. We first formalize the definition and security model for TB-IBE. Subsequently, we show that a TB-IBE scheme satisfying some properties can be converted to a full black-box A-IBE scheme, which is as efficient as the underlying TB-IBE scheme in terms of computational complexity and parameter sizes. Finally, we give an instantiation with the computational complexity as $O(1)$ and the constant size master key pair, private keys, and ciphertexts.
Development of Eddy Current Testing System for Welding Inspection

Non-Destructive Test (NDT) techniques are widely used in several industries since nowadays most of the modern structure are made from steel structures. NDT relates to the examination of materials for flaws without harming the object tested. Eddy Current Testing (ECT) technique is a nondestructive testing method, which is used to detect discontinuities and defects in conductive material. This paper presents a system development with a scanning mechanism for determination of weld defect by using ECT technique. Owing to the low noise of the Anisotropy Magneto resistive (AMR) sensor, the ECT system with the AMR sensor has an advantage of detecting deep and small defects in metal structures. In this study, we developed a magnetic probe using AMR sensor with a sensitivity of 1 nT/sqrtHz that is capable to detect inner defects even at a low frequency. The performances based on characterization of Metal Inert Gas (MIG) welding traces on carbon steel plates. The metal plate is scanned using the XY stage and the detected magnetic signal is utilized to construct 2D image of magnetic distribution map. To improve the sensitivity and operation of the AMR sensor, a small cancellation coil around the AMR sensor is fabricated to cancel the applied magnetic field coupled directly to the sensor. Moreover, the effect of the liftoff between the metal plate and the AMR sensor is studied while the liftoff is lowered from 20 to 4 mm. The results show that a small liftoff could improve the resolution of the constructed distribution map, hence enabling the identification of metal plates and their weld beads. Using the developed ECT systems, the small defects in the samples was successfully detected.
DC-DC q-ZSC with Buck-Boost Converter Gain

In this paper, a DC-DC buck-boost converter (BBC) based on the quasi Z-source converter (q-ZSC) topology is proposed. The converter is classified as buck-boost because their gains are the same. It is also classified as an impedance source converter (ISC) because it is based on q-ZSC topology. These shared properties of the buck-boost and q-ZSC gives it advantages over each of these two converters. The gain curve gives it advantages over a corresponding regular q-ZSC because for a given duty ratio, it has a higher gain, while it's topology edge it over a corresponding BBC thus permitting higher frequency operation, elimination of dead time, shoot-through effects etc. MATLAB/SIMULINK was used to compare its performance and corresponding BBC for a buck mode and boost mode operation. The simulation results show that their responses are very much similar.
Accurately Characterizing the Coupling Effects of Patch Antennas With Complex- and Frequency-Dependent J/K Inverters

This paper proposes an accurate and general method to calculate and characterize the couplings of patch antennas. It is found that the coupling effects of open-/short-circuited patches can be represented by J/K inverters. Unlike traditional ones, these J/K inverters should be with complex- and frequency-dependent values. Three different patch antennas are used to exemplify how to characterize couplings with J/K inverters. Once the values of J/K inverters are successfully extracted, the total equivalent circuits of these patch antennas can be easily given in a unified way. J/K inverters can also help us see how the couplings affect antenna bandwidth. To present advantages of the proposed method, comparison with traditional coupling calculation approach based on characteristic modes is conducted. Technical limitations and potential applications of the proposed method are also discussed.
Essential Role of Sequestosome 1/p62 in Regulating Accumulation of Lys63-ubiquitinated Proteins*

Sequestosome 1 (SQSTM1)/p62 is an interacting partner of the atypical protein kinase C ζ/ι and serves as a scaffold for cell signaling and ubiquitin binding, which is critical for several cell functions in vivo such as osteoclastogenesis, adipogenesis, and T cell activation. Here we report that in neurons of p62–/– mouse brain there is a detectable increase in ubiquitin staining paralleled by accumulation of insoluble ubiquitinated proteins. The absolute amount of each ubiquitin chain linkage measured by quantitative mass spectrometry demonstrated hyperaccumulation of Lys63 chains in the insoluble fraction recovered from the brain of p62–/– mice, which correlated with increased levels of Lys63-ubiquitinated TrkA receptor. The increase in Lys63 chains was attributed in part to diminished activity of the TRAF6-interacting the Lys63-deubiquitinating enzyme (DUB), cylindromatosis tumor suppressor (CYLD). The interaction of CYLD with TRAF6 was dependent upon p62, thus defining a mechanism that accounts for decreased activity of CYLD in the absence of p62. These findings reveal that p62 serves as an adapter for the formation of this complex, thereby regulating the DUB activity of CYLD by TRAF6 interaction. Thus, p62 has a bifunctional role in regulation of an E3 ubiquitin-protein ligase, TRAF6, and a DUB, CYLD, to balance the turnover of Lys63-polyubiquitinated proteins such as TrkA.
A Scalable Multilayer Middleware for Distributed Monitoring and Complex Event Processing for Smart Cities

In this paper, we present a hierarchical, distributed, cloud-based, context-aware architecture for collecting, processing and distributing data in a smart city. The architecture we are proposing has three hierarchical levels, and supports complex event processing (CEP) in several of them. At the lower layer, several mobile objects work as interfaces to sensors and actuators and provide processing capability for local filtering and detection. A second level, consisting of gateways and processing nodes, processes information from its locale and sends the data received from the mobile objects to the storage level using the existing network infrastructure. The highest level provides support for structured storage and queries of the information. Applications outside the platform can collect data through the external interface of the highest level. The system is under development using the InterSCity platform in the upper layer, the ContextNet middleware at the middle layer, and the Mobile-Hub application at the lower layer. It currently collects and processes data on buses running in the City of Rio de Janeiro.
Optimal Multivariable Control for Modified Z-source Based IPT

This paper describes Z-source based inductive power transfer topologies control approaches. The goal of this work is a multi-variable control approach which involves a constant voltage / constant current control along with an optimal frequency control to obtain maximum efficiency. This control is applied to the wireless power transfer system based on a modified Z-source topology. The description of the control method along with simulation results is provided.
Multi-Scale Dense Networks for Deep High Dynamic Range Imaging

Generating a high dynamic range (HDR) image from a set of sequential exposures is a challenging task for dynamic scenes. The most common approaches are aligning the input images to a reference image before merging them into an HDR image, but artifacts often appear in cases of large scene motion. The state-of-the-art method using deep learning can solve this problem effectively. In this paper, we propose a novel deep convolutional neural network to generate HDR, which attempts to produce more vivid images. The key idea of our method is using the coarse-to-fine scheme to gradually reconstruct the HDR image with the multi-scale architecture and residual network. By learning the relative changes of inputs and ground truth, our method can produce not only artificial free image but also restore missing information. Furthermore, we compare to existing methods for HDR reconstruction, and show high-quality results from a set of low dynamic range (LDR) images. We evaluate the results in qualitative and quantitative experiments, our method consistently produces excellent results than existing state-of-the-art approaches in challenging scenes.
The alternative aerobic ribonucleotide reductase of Escherichia coli, NrdEF, is a manganese‐dependent enzyme that enables cell replication during periods of iron starvation

The genome of Escherichia coli encodes two class I ribonucleotide reductases. The first, NrdAB, is a well‐studied iron‐dependent enzyme that is essential for aerobic growth. The second, NrdEF, is not functional under routine conditions, and its role is obscure. Recent studies demonstrated that NrdEF can be activated in vitro by manganese as well as iron. Since iron enzymes are potential targets for hydrogen peroxide, and since the nrdHIEF operon is induced during H2O2 stress, we hypothesized that H2O2 might inactivate NrdAB and that NrdEF might be induced to compensate. This idea was tested using E. coli mutants that are chronically stressed by H2O2. Contrary to expectation, NrdAB remained active. Its resistance to H2O2 depended upon YfaE, which helps to activate NrdB. The induction of NrdEF during H2O2 stress was mediated by the inactivation of Fur, an iron‐dependent repressor. This regulatory arrangement implied that NrdEF has a physiological role during periods of iron starvation. Indeed, NrdEF supported cell replication in iron‐depleted cells. Iron bound to NrdF when it was expressed in iron‐rich cells, but NrdEF was functional only in cells that were both iron‐depleted and manganese‐rich. Thus NrdEF supports DNA replication when iron is unavailable to activate the housekeeping NrdAB enzyme.
Reference Samples Padding for Intra-Frame Coding of Omnidirectional Video

Due to lack of video coding standard tailored specially to spherical or omnidirectional videos, which are important in Virtual Reality applications, omnidirectional video frames have to be projected onto the 2-Dimension(2D) plane, using the EquiRectangular Projection(ERP) for example, to utilize existing video compression techniques. As there is no information available for prediction outside the left or right border after projection, unexpected artefacts that are generated at the right border of frames degrade the subjective visual quality. Utilizing continuity of the content in the omnidirectional video based on ERP, in this work, an efficient intra-coding method is proposed based on adaptively padding the reference samples at the right border for omnidirectional videos. Using the state of art video encoder, the proposed method can reduce the BD-rate by 0.24% in average for the coding tree units (CTUs) at the right border.
Periodic Activity Monitoring Using Radio Frequency Tag Arrays

Periodic activity monitoring, a fateful motive in numerous applications, is regularly costly guided utilizing cameras. Monitoring a massive field effectively by exploring pictures from numerous cameras always remains a testing issue. In this paper, we propose an effective and efficient algorithm for retrieving periodic movement patterns or activities from the frequent region, where RF tag arrays and data mining techniques perform a delicate role. The objects take after similar routes over customary time interims. The RFID has drawn operative intentness late years for its minimal effort, general accessibility and location detecting usefulness. Another favorable position of RFID is that it doesn’t require coordinate contact or observable pathway checking of objects. The feasibility and the efficiencies of this proposal will be verified by our experimental evaluation using both synthetic datasets real RFID datasets.
Canonical Correlation Analysis for Data Fusion in Multimodal Emotion Recognition

Multimodal emotion recognition systems aim at classifying emotion data, usually from different natures, into discrete affective categories. These systems fuse different modalities as each modality classifies the data from its own viewpoint and can compensate the limitations of others when combining with them. Existing approaches for multimodal data fusion either use feature-level or decision-level fusion. The former needs different modalities to be synchronized while the latter has not this limitation. In the current study, audio, visual, and users’ comments are used as modalities for video emotion recognition. Although the first two modalities are synchronized, users’ comments are not synchronized with them and this makes the use of pure feature-level data fusion impossible. In order to exploit the benefits of the feature-level approach, a hybrid method is proposed in the current study which first applies feature-level canonical correlation analysis (CCA) to audio and visual modalities and then combines the outputs with users’ comments using a decision-level fusion. The results of applying this proposed method to DEAP dataset shows that using feature-level CCA not only outperforms the baseline feature-level method but also achieves a higher performance than the decision-level fusion.
9.4 A 145GHz FMCW-Radar Transceiver in 28nm CMOS

Indoor radar applications detecting people, vital signs and minute gestures require a high range resolution. This paper presents a 145GHz FMCW radar transceiver with on-chip antennas in 28nm bulk CMOS. An RF bandwidth of 13GHz yields an 11mm range resolution, and the high RF carrier permits greater velocity and MIMO-angular resolution. An external chirp signal at 16.1GHz is upconverted to 145GHz via a cascade of two frequency triplers in the RX and TX. For MIMO operation, a central chirp signal from a sub-sampling PLL integrated in 28nm CMOS [1] is distributed to multiple TRX chips on a PCB, eliminating mm-wave signal routing. The radar operates over a 0.15-to-10m range using fast sawtooth chirps of 5-to-$50 \mu \mathrm {s}$ duration. The beat frequency at IF fits between 400kHz and 15MHz. The on-chip TX leakage produces a strong beat near DC, suppressed via active highpass filtering. However, group delays of the PA and LNA can shift the beat into the RX passband. This is overcome by delaying the 16.1GHz RX chirp on chip. The chip dissipates 500mW in continuous mode, with the option of a low-power, duty-cycled FM transmission mode (for close ranges) enabled via fast powering built into the transceiver.
Data Augmentation by Adjunct Deletion for Neural Machine Translation

Neural machine translation is shown to be very successful for translation between many language pairs. The experiments have shown that the quality of NMT largely depends on the amount of training data and parallel corpora with large sizes are unavailable for many language pairs. To be able to use this approach for low resource language pairs, generating parallel data for these languages is of great importance. In this paper we introduce an approach for augmenting the size of the parallel corpus. In our work we generate new parallel sentences by deleting the optional constituents from the source and the target sentences in the base parallel corpus. To detect these optional constituents, we consult the Tree Adjoining Grammar (TAG) derivation tree of the source sentence. Adjoined words in these trees are good candidates for deletion. To evaluate the proposed method, we conducted our experiments on English-Persian translation task. The results show that augmenting the parallel corpus with adjunct deletion improves the quality of translation 3.2 and 0.8 BLEU points when using the training sets of 1.6M and 3.2M words respectively.
Environment Detection of 3D LiDAR by Using Neural Networks

Autonomous vehicles and robot are more and more popular, and it is important to sense the environment for autonomous vehicles and robot. LiDAR is a very powerful device, it can capture the distance and contour of object precisely and quickly. And the scanning range is very wide. we use 3D LiDAR and neural network to detection the environment. We get the data packet from LiDAR, and decode the data packet to 3D point cloud coordinate. Then extract the drivable road by neural network and mark the obstacle.
Design of an Archimedes spiral antenna for PD tests under repetitive impulsive voltages with fast rise times

Partial discharge inception voltage measurements under repetitive impulsive voltages play an essential role in evaluating the reliability of inverter-fed low voltage rotating machines. Using impulsive voltages, partial discharge (PD) signals and the disturbance induced by power electronics switches have often similar energy distribution in the frequency domain. Thus, PD test technologies used with sinusoidal voltages are no longer effective. Under repetitive impulsive voltages, ultra-high frequency detection is recommended to couple high-frequency spectral components from the PD and remove the low-frequency disturbance coming from power electronics. However, to obtain high signal to noise (S/N) ratio, the parameters of the antenna used for PD detection should be designed considering the PD and the disturbance energy distributions in the frequency domain. In this paper, we discuss the design and show the properties of an antenna with Archimedes plane spiral structure intended for PD detection under repetitive impulse voltages. The simulation shows that the antenna has low voltage standing wave ratio (<2) and improved directivity in the frequency range from 0.5 to 2 GHz. Moreover, PD tests performed using repetitive square waves with different rise times demonstrate that the designed antenna can receive PD signals efficiently with high S/N.