Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency- and Temperature-Dependent Gate Reliability of Schottky-Type ${p}$ -GaN Gate HEMTs

In this paper, we carried out a systematic investigation on gate degradation and the physical mechanism of the Schottky-type <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-GaN gate HEMTs under positive gate voltage stress. The frequency- and temperature-dependent measurements have been conducted. It is found that the time-dependent gate degradation exhibits weak relevance with frequencies ranging from 10 to 100 kHz under dynamic gate stress and is similar to that in static gate stress. Both the gate breakdown voltage (BV) and mean-time-to-failure (MTTF) show positive temperature dependence. Moreover, the current–voltage (<italic>I–V</italic>) characteristics and threshold voltage (<inline-formula> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula>) instability of <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-GaN devices before/after gate degradation are compared and analyzed. The degraded Schottky junction exhibits an ohmic-like gate behavior. It is revealed that under a large gate bias stress, high-energy electrons accelerated in the depletion region of the <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-GaN layer would promote the formation of defect levels near the metal/<inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-GaN interface, leading to the initial <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula>-GaN layer degradation. The subsequent high gate leakage density could cause the final degradation of the AlGaN barrier.
Quijote-mfi: optics characterisation and polarisation measurements of cmb foregrounds

The study of the Cosmic Microwave Background (CMB) anisotropies is one of the key tools of Modern Cosmology. The most important limitations of the experiments aimed at measuring both the intensity and the polarisation of the CMB are the systematics and the foregrounds, i.e. the Milky Way diﬀuse emission. This thesis will be devoted to the characterisation of these two aspects, with particular regard to the Multi-Frequency Instrument (MFI) of the QUIJOTE (Q-U-I JOint TEnerife) experiment. The MFI consists of four horns that can measure intensity and polarisation between 10 and 20 GHz at angular resolutions between 40’ and 57’. It has been operative almost continuously since November 2012, providing data of several calibrators, Galactic sources and extended ﬁelds for cosmological analyses. The ﬁrst part of this thesis consists in the full characterisation of the optics of the MFI. The main beams are obtained through geostationary satellites observations and the results are conﬁrmed with simulations and Cassiopeia A observations. We measure ellipticities > 0.92 and beam eﬃciencies > 0.90 in all horns. We estimate the level of the ﬁrst sidelobe at -40dB at 11GHz, and the far sidelobes are found at a level of -70dB, which is unprecedented for a microwave experiment. The Muller matrices formalism is used to analyse the polarisation response of the instrument. The main contaminant to CMB observation is the intensity-to-polarisation leakage, which is below 1% at 11GHz in the MFI. The major contaminants to the CMB polarisation are the synchrotron radiation and the dust emission of our Galaxy. The MFI is speciﬁcally designed to characterise the former type of emission, which is found mainly along the Galactic plane and in a region around the Galactic centre called Haze but can be found also at higher Galactic latitudes. In the second part of thesis we analyse ≈ 1300 hours of MFI data, covering four ﬁelds: W44, W49, W63 and the Haze. We produce the spectral energy distributions of 13 compact sources and adjust them with physical parameters that model the synchrotron, free-free and thermal dust emission. Also, a phenomenological model is used for the anomalous microwave emission, which has been found in 11 sources. The diﬀuse emission is studied in the Haze region. We found that its main component is free-free at low Galactic latitudes and synchrotron at b ≈ 8o. In polarisation, we measure a spectral index of -2.54 in temperature, which is in agreement with the Haze spectrum measured by Planck.
Fiber-Optic Measurement of Liquid Evaporation Dynamics Using Signal Processing

An evaporation rate measurement method based on multiple reflection interference using a simple fiber optic configuration is proposed in this study. The evaporation rate is a major factor in preventing accidents and is used in various industrial, chemical, biotechnological, and biological fields. The evaporation rate sensor measures the interference signal during evaporation of a liquid. The main frequency of an interferogram is linearly proportional to the evaporation rate and can be obtained by applying a fast Fourier transform to the interferogram. In our study, the time-averaged evaporation rates of deionized (DI) water and ethanol were tested. Ethanol evaporated at a rate approximately a factor four faster than that of DI water. In addition, a Hilbert transform was used to retrieve the phase information of the interferogram over time. Our proposed method is a powerful tool for monitoring the evaporation dynamics of a liquid in time. The sensor requires a tiny amount of liquid as a test sample to determine the rate of evaporation and offers high reliability and reproducibility at low cost.
Ensemble learning for prediction

The goal of this dissertation is to study and develop automatic prediction technology that is accurate, fast and interpretable. The focus here is on decision tree ensembles methods and extensions. Characteristics of popular ensemble methods such as bagging, random forests and boosting are examined and leveraged to create new predictive methodology. The classic ensembles are integrated in an unifying paradigm, the Important Sampled Learning Ensembles. This framework explains some of the properties of these ensembles and suggests modifications that can significantly enhance their accuracy while dramatically improving their computational performance. The ISLES are two-stage algorithms having at the front-end a base learners ensemble generation routine followed by post-processing algorithms that perform a fast gradient directed regularized fit for regression, robust regression and classification. The post-processing algorithms developed here can also serve as a stand-alone toolkit for fitting large linear systems. Decision tree ensembles can generate rules that are fit together with the gradient directed regularized linear algorithms, leading to accurate and interpretable RuleFit models. ISLE and RuleFit are flexible methodologies, able to automatically handle non-linearities and interactions, mixtures of categorical and continuous variables with missing data, as well as feature selection.
Incomplete factorization for preconditioning shifted linear systems arising in wind modelling

The efﬁciency of a mass-consistent model for wind ﬁeld adjustment depends on the stability parameter α . Each simulation with the wind model leads to the resolution of a linear system of equations, the matrix of which depends on a function ε ( α ) , i.e., ( M + εN ) x ε = b ε , where M and N are constant, symmetric and positive deﬁnite. Since each value of ε ( α ) yields a different linear system, we have to solve a set of them. So we could either construct a different preconditioner for each of them and improve the convergence of PCG at the expense of a high computational cost. On the other hand, a single preconditioner constructed with the ﬁrst value of ε may be used for all the systems. Here, an intermediate solution is proposed by using a preconditioner, which is constructed once at ﬁrst and updated for each ε at a low computational cost based on incomplete Cholesky factorization of A ε .
An Axial Compression Planar Lens Antenna Based on Discrete Transformation Electromagnetics Using High-Impedance Surface Cells

A two-dimensional (2-D) convex lens is reshaped and compressed into a 2-D flat lens with a compression ratio of 52.6% by discrete transformation electromagnetics. The single-layer high-impedance surface cells are used to fill with the compressed zone to form a planar flat lens. A parallel-plate waveguide and a 1/4 λ reflector are used to ensure that the electromagnetic energy generated by the monopole flows to the lens. The planar lens antenna, 4.35 λ × 4 λ on the lens plane and 0.375 λ tall, is fabricated and measured in TM mode at 7.5 GHz. The measured data indicate that the proposed planar lens antenna achieves an 11.3 dBi gain, 16.7° half-power beamwidth on H-plane, and almost 260 MHz impedance bandwidth for S11. The joint design of discrete transform electromagnetics and high-impedance surface cells is a new method, which has strong reference value for the miniaturization of other lens antennas.
Konkani SentiWordNet - Resource For Sentiment Analysis Using Supervised Learning Approach

Sentiment Analysis (SA) is the process of analyzing and predicting the hidden attitude/opinion in the given text expressed by an individual. Till now, ample amount of work has been carried out for the English language. But, no work is performed for the language Konkani in the ﬁeld of Sentiment Analysis. Lexicon-based SA is a good beginning for any language, especially if the digital content is limited. Hence, the main motive of this paper is; to present the sentiment lexicon called SentiWordNet for Konkani language.The process of creating Konkani SentiWordNet is under progress using the Supervised Learning Approach. In this approach, the training set is generated using a Synset Projection Approach and Support Vector Machine (SVM) algorithm to classify the data. The reason behind using the Synset Projection Approach for building a training dataset is; English Sentiwordnet is developed using Semi-Supervised Approach where the training dataset is generated using WordNet lexical relations but; in Konkani WordNet, lexical relations are not yet developed. Hence, Synset Projection Approach is preferred. Conducted experimental results for the proposed algorithm are reported in this paper.
IPv6: Features, Current Deployment Scenario, Issues and Migration Status In India

IPv6 was developed to replace and improve the existing Internet Protocol (IP), the IPv4 in many ways. Among the improved areas are addressing space, routing efficiency, header format, auto-configuration, Quality-of-Service (QoS), security and mobility. Although IPv6 promises enhancements to IPv4 standards, its deployment is rather slow in India. This paper examines the IPv6 prominent features in details, discusses on the IPv6 deployment around the world and studies some of the transition mechanisms available today. We will also discusses on some of the contributing factors towards the slow IPv6 deployment phenomenon in India which include lacking of awareness among the public, unclear differentiating benefits to network operators, uncertain risk to the network operators and lacking of IPv6 applications. Finally, we will provide some possible potential solutions to improve the rate of deployment and experimentation of IPv6 in India. KeywordsIPv6 Deployment, Migration Strategy, Dual stack, Translation.
Inner-product based signal processing: Algorithms and VLSI implementation

t l ACKNOWLEDGEMENT First, I would like to give my deep appreciation and thanks to my advisor, Dr. Janusz A. Starzyk, for his advice, support, and patient reviewing of my dissertation. Thanks are also due to the members of my committee: I would also like to acknowledge MOSIS program for the supporting fabrication of the chip. Especially, thanks to Mr. Jen-I Pi, who works for MOSIS, for providing the special frame and technical advice. In addition, I would like to thank Mr. Cheng-Yu Jan, who is my best friend, for his technical advice in building the testingboard. Also, thanks to Mr. Rick Cooper for his patience while correcting my dissertation. This dissertation is particularly dedicated to my parents for their love and support during seven years studying at Ohio University.
Ricci soliton and Ricci almost soliton within the framework of Kenmotsu manifold

First, we prove that if the Reeb vector field $\xi$ of a Kenmotsu manifold $M$ leaves the Ricci operator $Q$ invariant, then $M$ is Einstein. Next, we study Kenmotsu manifold whose metric represents a Ricci soliton and prove that it is expanding. Moreover, the soliton is trivial (Einstein) if either (i) $V$ is a contact vector field, or (ii) the Reeb vector field $\xi$ leaves the scalar curvature invariant. Finally, it is shown that if the metric of a Kenmotsu manifold represents a gradient Ricci almost soliton, then it is $\eta$-Einstein and the soliton is expanding. We also exhibited some examples of Kenmotsu manifold that admit Ricci almost solitons.
Differentially Fed Wideband Filtering Slot Antenna With Endfire Radiation Under Multi-Resonant Modes

In this communication, a differentially fed wideband slot antenna on a single layer with endfire radiation and filtering response under multi-resonant modes is proposed. By using the $\lambda $ /4 slot radiator with its opened terminal at one side, the endfire-radiated fields of the slot antenna is initially formed with compact dimension and endfire radiation. After that, the $\lambda $ /4 slot radiator with two distinctive portions of different slot widths is presented and investigated. The results demonstrate that the resonant frequencies of the first two odd-order modes could be progressively reallocated in proximity to each other as the length and width ratios of these two portions are properly selected. Thus, the bandwidth in input impedance of the entire differentially fed slot antenna could be significantly improved under operation of dual-resonant modes. Next, an extra microstrip-line resonator is introduced in the feeding part so as to produce a third resonant mode and improve its frequency selectivity in the wide operating band. To validate these predicted performances, a filtering slot antenna operating from 3.33 to 4.50 GHz is in final fabricated and tested. The measured results exhibit good impedance matching property, flat radiation gain of about 5 dBi, and improved endfire radiation characteristic with the front-to-back ratio (FBR) better than 9.0 dB in the operating band. Both the simulated and measured results are provided with good agreement.
Stabilisation of a rotary inverted pendulum system with double-PID and LQR control: experimental verification

Rotary inverted pendulum (RIP) system is an under-actuated system. The RIP system consists of a pendulum, which is rotating freely in the vertical plane. A swing-up action using a pivot arm in the horizontal plane would then result in the pendulum to achieve upright equilibrium point. This paper describes the design of double proportional-integral-derivative (PID) controls with a linear quadratic regulator (LQR) controller for the stabilisation control of a RIP system. Besides, the dynamic model of the RIP system is described too. The LQR controller was tuned using Taguchi method of design of experiments (DoE). The double-PID controller was designed using Ziegler-Nichols second method, which the LQR controller is embedded in the RIP system to improve the stabilisation performance. The effectiveness of the double-PID and LQR controller is clarified with a RIP experimentally. The proposed controller has demonstrated succeed stable the pendulum within 0.5 degrees in three seconds and the rotary arm within 22.5 degrees.
PERUMUSAN STRATEGI TELUR PUYUH DI IKHLAS QUAIL FARM MENGGUNAKAN ANALISIS SWOT DAN MATRIKS QSPM

Usaha Kecil Menengah Ikhlas Quail Farm (IQF) terletak di wilayah Padalarang, Kabupaten Bandung Barat merupakan usaha baru dalam bidang budidaya puyuh. Produk yang dihasilkan adalah telur puyuh untuk konsumsi dan bibit puyuh dengan kualitas yang baik sesuai dengan standar Asosiasi Peternak Puyuh Indonesia (APPI). Ikhlas Quail Farm yang baru berdiri selama satu tahun memiliki berbagai kendala yaitu produksi, pemasaran dan menghadapi pesaing yang masuk. Penelitian ini dilakukan dengan tujuan untuk melakukan formulasi dan pemilihan strategi yang paling tepat untuk diterapkan pada Ikhlas Quail Farm, proses formulasi strategi dilakukan dengan melakukan evaluasi kondisi eksternal dan internal yang dimiliki Ikhlas Quail Farm. Metode pengumpulan data dilakukan melalui wawancara, observasi, serta studi literatur. Formulasi strategi yang dilakukan dalam penelitian ini terdiri atas tiga tahap. Tahap pertama yaitu evaluasi ekternal dan internal dengan menggunakan matriks EFE dan IFE menentukan bobot faktor, tahap kedua menggunakan I-E Matrix, dan tahap terakhir menggunakan matrik QSPM. Hasil yang diperoleh dalam penelitian ini menunjukkan letak kordinat Ikhlas Quail Farm berada pada sel ke I dengan kordinat (3,12; 3,28). Strategi yang tepat untuk diterapkan Ikhlas Quail Farm adalah Growt and Build. Hasil analisis matrik QSPM menunjukkan strategi dengan prioritas tertinggi untuk Ikhlas Quail Farm adalah melakukan promosi pemasaran melalui kegiatan penyuluhan di posyandu dengan melibatkan tenaga ahli kesehatan dalam menjelaskan kandungan gizi puyuh (TAS = 16,111). Kata Kunci : UKM (usaha kecil menengah), matriks I-E, SWOT, QSPM (Quantitative Strategic Planning Matrix).
IGBT Neural Network Prediction Method of Radar Transmitter based on Levenberg-Marquard Optimization

Health parameters prediction of radar transmitter needs to complete the electronic components failure characteristics analysis and fault symptom parameters prediction. The article looks the Insulated Gate Bipolar Transistor (IGBT) as the research object, combines the accelerated life experimental data of NASA-ARC, and determines the turn-off voltage spike peak value of collector-emitter as the basis of failure prediction, carries out IGBT health prediction method research based on process neural network. In view of the slow convergence speed and easily trapped in local minimum of back-propagation learning algorithm in the traditional process neural network, develop a kind of learning algorithm based on orthogonal basis function of Levenberg-Marquardt(LM) optimization. The experimental results show that the process neural network algorithm based on LM optimization can better predict the performance degradation trend of IGBT; it has high accuracy and achieves the short-term prediction of IGBT health state.
Photoshop (CS6) intelligent tutoring system

In this paper, we designed and developed an intelligent tutoring system for teaching Photoshop. We designed the lessons, examples, and questions in a way to teach and evaluate student understanding of the material. Through the feedback provided by this tool, you can assess the student's understanding of the material, where there is a minimum overshoot questions stages, and if the student does not pass the level of questions he is asked to return the lesson and read it again. Eventually this administration is a special teacher for the students and can continue with him until he fully understands the lesson without weariness or boredom, regardless of the level of student.
Evaluation of next-generation low-power communication technology to replace GSM in IoT-applications

The large demand for smart metering and control, asset tracking, remote monitoring, and other applications has resulted in the emergence of innovative new internet of things (IoT) low-power wide-area networks (LPWANs) featuring low power consumption, low cost, high scalability and low data rate transmissions. This article compares the performance of LoRaWAN, Sigfox, and NB-IoT as emerging technologies, in terms of power consumption, throughput, scalability, and range. For practical reasons, the comparison also includes cellular GPRS. Although GPRS does not fit the description of LPWAN technologies, it is a legacy method for IoT communications and provides insight into application areas where LPWAN technology can be applied. The study gives a clear comparative overview of the advantages and shortcomings of the various communication networks and highlights the most suitable applications cases for each technology on the basis of the tested metrics.
Estimation in Inverse Weibull Distribution Based on Randomly Censored Data

This article deals with the estimation of the parameters and reliability characteristics in inverse Weibull (IW) distribution based on the random censoring model. The censoring distribution is also taken as an IW distribution. Maximum likelihood estimators of the parameters, survival and failure rate functions are derived. Asymptotic confidence intervals of the parameters based on the Fisher information matrix are constructed. Bayes estimators of the parameters, survival and failure rate functions under squared error loss function using non-informative and gamma informative priors are developed. Furthermore, Bayes estimates are obtained using Tierney-Kadane's approximation method and Markov chain Monte Carlo (MCMC) techniques. Also, highest posterior density (HPD) credible intervals of the parameters based on MCMC techniques are constructed. A simulation study is conducted to compare the performance of various estimates. Finally, a randomly censored real data set supports the estimation procedures developed in this article.
Détermination automatique de fin de réactions à l’aide de méthodes chimiométriques

Grégory Corminboeuf *, Michael Amrhein **, Olivier Naef *, Pascale Voirin *, Ennio Vanoli *, Jean-Nicolas Aebischer *, Simon Crelier*** * Ecole d’ingénieurs et d’architectes de Fribourg, Bd de Pérolles 80, CH-1705 Fribourg (Suisse). Correspondance : olivier.naef@hefr.ch. ** EPFL, STI I2S LA, ME C2 389 (Bâtiment ME), Station 9, CH-1015 Lausanne *** Haute école valaisanne, Rte du Rawyl 47, Case Postale 2134, CH 1950 Sion 2.
N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data

The analysis of hyperspectral data sets requires the determination of certain basis spectra called 'end-members. ' Once these spectra are found, the image cube can be 'unmixed' into the fractional abundance of each material in each pixel. There exist several techniques for accomplishing the determination of the end-members, most of which involve the intervention of a trained geologist. Often these-end-members are assumed to be present in the image, in the form of pure, or unmixed, pixels. In this paper a method based upon the geometry of convex sets is proposed to find a unique set of purest pixels in an image. The technique is based on the fact that in N spectral dimensions, the N-volume contained by a simplex formed of the purest pixels is larger than any other volume formed from any other combination of pixels. The algorithm works by 'inflating' a simplex inside the data, beginning with a random set of pixels. For each pixel and each end-member, the end-member is replaced with the spectrum of the pixel and the volume is recalculated. If it increases, the spectrum of the new pixel replaces that end-member. This procedure is repeated until no more replacements are done. This algorithm successfully derives end-members in a synthetic data set, and appears robust with less than perfect data. Spectral end-members have been extracted for the AVIRIS Cuprite data set which closely match reference spectra, and resulting abundance maps match published mineral maps.