Miracle-dz/UniFAR-FTUs huggingface dataset:
An indoor mobile robot navigation technique using odometry and electronic compass

A novel method of indoor mobile robot navigation is presented. The proposed approach fuses the data of odometry and electronic compass for navigation. It includes two calibration methods and a fusion algorithm. First of all, calibration method of systematic odometry error is used to reduce the error of navigation and provide the reliable estimate of pose of mobile robot for adaptive extended Kalman filter fusion algorithm later. Secondly, calibration method of electronic compass using an adaptive neural fuzzy inference system provides direction angle of mobile robot as observation for adaptive extended Kalman filter algorithm later. Finally, a fusion algorithm using adaptive extended Kalman filter algorithm fuses data of odometry and electronic compass that provides the position and orientation of mobile robot. In addition, the value of the parameter k of adaptive extended Kalman filter algorithm which is related to the process noise covariance is decided by fuzzy algorithm. In order to illustrate the feasibility of the proposed approach, two types of experiments are done: the first-type experiment is that the mobile robot runs along default path only with odometry, and the mobile robot with odometry and electronic compass in the second-type experiment utilizes the proposed approach for navigation. The results of experiments show that the error of localization and navigation in the first-type experiment is larger than one in the second-type experiment. They prove the good performance of the proposed approach.
Generalized Halpern-type forward–backward splitting methods for convex minimization problems with application to image restoration problems

ABSTRACT In this work, our interest is to investigate the monotone inclusion problem in the framework of real Hilbert spaces. For solving the inclusion problem, we propose a composite iteration for approximating a zero of sum of two operators. We prove its strong convergence under some mild conditions. Finally, we provide a number of applications to convex minimization and image restoration problems including numerical experiments to support our main theorem.
Evaluation of the Exact Spraying Time of Chemicals for Management of Bruchus Pisorum Under Field Condition's

Ethiopia have highly potential to produce field pea, this crops produce in Ethiopia from ancient time still now and the societies use it for different purpose such as to prepare cultural food, in household consumption and as a source of income. It is substantial crop and substitute meat nutritional value, as a source of protein. Field pea production has different constraints such as weed, disease and insect pest problems, and bruchuspisorum is major insect pest which is decline quantity of production in Ethiopia. The experiment was done at Holleta Agriculture Research center in the field condition with four replication in Completed Randomized Block Design. The objective of this study was to distinguish the exact chemical spraying time in the field to control bruchuspisorum. The variety was Adi, Wolemera, Markos and Burkitue, the chemical treatment were spraying during, early flowering, flat and full podded as recommended level, three times in every week. As a result there was significance difference between pre flowering chemical spraying time, flat podded spraying and full podded spraying time, on the number of larvae per pod (F13,18 at 0.005=11.13, p<0.0001). There was least recorded of number of larvae on per pod in full and flat pod spraying time. Even if there was no significance difference among the flat and full podded spraying time, in full podded spraying time, there was no larvae recorded totally. So in order to manage field pea bruchuspisorum in the field condition, the chemical spraying must be started from flat podded and will continued until to full podded.
Short text similarity algorithm based on the edit distance and thesaurus

S t r e s z c z e n i e Artykuł przedstawia propozycję metody porównywania krótkich fragmentów tekstów bazującą na algorytmie odległości Levenshteina i słowniku wyrazów bliskoznacznych. Porównywane teksty zawierają odmienione terminy oraz celowe błędy ortograficzne i gramatyczne. Opisany mechanizm zestawiony został z popularnymi metodami porównywania tekstów, takimi jak: odległości Kosinusowa, Dice’a i Jaccard’a, dla których wartości wektorów obliczane są metodą częstości terminów. Zastosowanie w mechanizmie słownika wyrazów bliskoznacznych jest alternatywą wobec znanych algorytmów określania rdzenia terminu i lematyzacji w analizie danych tekstowych. Słowa kluczowe: odległość Levenshteina, odległość edycyjna, słownik wyrazów bliskoznacznych, miara podobieństwa tekstów, detekcja plagiatu, analiza danych tekstowych, przetwarzanie języka naturalnego, stemming, lematyzacja DOI: 10.4467/2353737XCT.16. 149.5760
High Performance ${\beta}$ -Ga2O3 Nano-Membrane Field Effect Transistors on a High Thermal Conductivity Diamond Substrate

To suppress severe self-heating under high power density, we herein demonstrate top-gate nano-membrane <inline-formula> <tex-math notation="LaTeX">${\beta }$ </tex-math></inline-formula>-gallium oxide (<inline-formula> <tex-math notation="LaTeX">${\beta }$ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub>) field effect transistors on a high thermal conductivity diamond substrate. The devices exhibit enhanced performance, with a record high maximum drain current of 980 mA/mm for top-gate <inline-formula> <tex-math notation="LaTeX">${\beta }$ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> field effect transistors and 60% less temperature increase from reduced self-heating, compared to the device on a sapphire substrate operating under identical power density. With improved heat dissipation, <inline-formula> <tex-math notation="LaTeX">${\beta }$ </tex-math></inline-formula>-Ga<sub>2</sub>O<sub>3</sub> field effect transistors on a diamond substrate are validated using an ultrafast high-resolution thermoreflectance imaging technique, Raman thermography, and thermal simulations.
Analytical Modeling of an Isotope Separation Column by Second-Order Quasi-Linear Equations with Two Independent Variables Sas

The presented process is an isotope separation column for , which represents a space propagation process modeled by the proposed method. Cohen's equation was approached by a second-order differential equation in relation to time t and also second-order in relation to the spatial variable s. This second order partial derivative equation was developed at an initial stage for which the variables and have been limited to two time constants ( ), or space ( ), resulting a family of curves of the concentration.
An Active Deep Learning Approach for Minimally Supervised PolSAR Image Classification

Recently, deep neural networks have received intense interests in polarimetric synthetic aperture radar (PolSAR) image classification. However, its success is subject to the availability of large amounts of annotated data which require great efforts of experienced human annotators. Aiming at improving the classification performance with greatly reduced annotation cost, this paper presents an active deep learning approach for minimally supervised PolSAR image classification, which integrates active learning and fine-tuned convolutional neural network (CNN) into a principled framework. Starting from a CNN trained using a very limited number of labeled pixels, we iteratively and actively select the most informative candidates for annotation, and incrementally fine-tune the CNN by incorporating the newly annotated pixels. Moreover, to boost the performance and robustness of the proposed method, we employ Markov random field (MRF) to enforce class label smoothness, and data augmentation technique to enlarge the training set. We conducted extensive experiments on four real benchmark PolSAR images, and experiments demonstrated that our approach achieved state-of-the-art classification results with significantly reduced annotation cost.
Deep cycle autoencoder for unsupervised domain adaptation with generative adversarial networks

Deep learning is a powerful tool for domain adaptation by learning robust high-level domain invariant representations. Recently, adversarial domain adaptation models are applied to learn representations with adversarial training manners in feature space. However, existing models often ignore the generation process for domain adaptation. To tackle this problem, deep cycle autoencoder (DCA) is proposed that integrates a generation procedure into the adversarial adaptation methods. The proposed DCA consists of four parts, a shared encoder, two separated decoders, a discriminator and a linear classifier. With the labelled source images and unlabelled target images as inputs, the encoder extracts high-level representations for both source and target domains, and the two decoders reconstruct the inputs with the latent representations separately. The shared encoder is pitted against the discriminator; the encoder tries to confuse the discriminator while discriminator aims at distinguishing which domain the latent representations come from. DCA adopts both adversarial loss and maximum mean discrepancy loss in the latent space for distribution alignment. The classifier is trained with both the source original and reconstructed image representations. Extensive experimental results have demonstrated the effectiveness and the reliability of the proposed methods.
Device for source position stabilization and beam parameter monitoring at inverse Compton X-ray sources

An X-ray beam monitor operating in parallel to experiments and adapted to the moderate flux density as well as rather large beam diameter of inverse Compton sources is presented. In conjunction with this device a closed-loop feedback system was developed counteracting the recorded source position drifts and thereby significantly improving the X-ray source position stability.
Investigating the electromigration limits of Cu nano-interconnects using a novel hybrid physics-based model

To predict the impact of technological variables such as materials, dimensions, interfaces, and operating conditions on Cu electromigration, in this study a hybrid modeling framework is developed by coupling a global Korhonen-type electromigration modeling module with a cellular automaton-based void dynamics module. The modeling framework is corroborated and benchmarked using experiments on Cu interconnects and is used to predict the impact of scaling on Cu electromigration induced stress evolution. The simulations shed light on the impact of dimensional scaling on stress kinetics, void nucleation, and growth phases, where the nucleation phase is found to become longer than the growth phase and voids are found to grow relatively more rapidly upon nucleation in highly scaled linewidth. In addition, the simulations predict 22% lower median time to failure and a higher variability of time to failure for downstream vs upstream electromigration modes due to the more critical impact of near via voiding in downstream cases. Lending further credence to its predictive merits, the model predicts and explains complex R-shift signatures occurring at high temperature electromigration experiments due to void dynamics.
Two Inversion Layers and Their Impacts on PM2.5 Concentration over the Yangtze River Delta, China

An integrated winter field campaign was conducted to investigate the atmospheric boundary layer structure and PM2.5 concentration at three sites over the Yangtze River delta (YRD) in China: Shouxian (a rural area), a site in a northern suburb of Nanjing, and Dongshan (a residential area). Two temperature inversion layers and air pollution events occurred simultaneously from 30 to 31 December 2016, local time, over the YRD. It was found that the two inversion layers were related to the presence of a high pressure system, resulting in divergence in the upper boundary layer and radiative cooling near the ground at night. Dominated by agricultural and residential biomass burning, the surface emission sources from the Shouxian rural area were moderately strong. After the formation of the two inversions, the vertical distribution of PM2.5 concentration below the upper inversion layer was uniform as a result of thorough boundary layer mixing in the earlier hours. During nighttime at the Nanjing site, air pollutant plumes from nearby elevated point sources could not easily diffuse downward/upward between the two inversion layers, which led to a distinct peak in the PM2.5 concentration. At the Dongshan site, the emission sources were weak and the nighttime PM2.5 concentration above 100 m was high. The surface PM2.5 concentration gradually increased from early morning to noon, which was attributed to emissions related to the local residents. The results indicated that the vertical distribution of pollutants was affected by a combination of local emissions, vertical boundary layer structure, and horizontal and vertical transports.
Searches for charged Higgs bosons at CMS

An overview of the results on the charged Higgs boson searches by the CMS Collaboration is presented. As different models with extended Higgs sectors predict different production and decay modes for these particles, the CMS search program for charged Higgs bosons covers a variety of final states targeting different models. The results of searches for charged Higgs bosons decaying into $\mathrm{c}\overline{\mathrm{s}}$, $\mathrm{c}\overline{\mathrm{b}}$, $\mathrm{t}\overline{\mathrm{b}}$, $\tau^{+}\nu_\tau$, $\mathrm{W}^{+}\mathrm{Z}$ (or charge-conjugate final states) and for doubly-charged Higgs bosons decaying into $\mathrm{W}^{\pm}\mathrm{W}^{\pm}$ are summarized. The observed limits agree with the standard model predictions.
Ffssa-Fiege Fiat Shamir Security Algorithm anEfficient Security Algorithm for Body AreaWireless Sensor Networks

WSN’s are generally deployed for collecting data from unattended or hostile environment. Several application specific sensor network cryptography algorithms have been proposed in research. however wsn’s has many constrictions, including low computation capability, less memory, limited energy resourses, vulnerability to physical capture ,which enforce unique security challenges needs to make a lot of improvements. In this paper presents a novel cryptography algorithm for wireless sensor network security, which presents a generic transformation from weak secure symmetric and asymmetric scheme to a hybrid encryption scheme. A revised Feige-Fiat-Shamir ZKP scheme for the Wireless sensor Networks (WSNs) that reduces the execution dynamics in the scheme and increases the trust of the Verifier and prover, and makes the authentication process faster and more efficient.
The minimum flow rate of electrosprays in the cone-jet mode

Stable electrospraying in the cone-jet mode is restricted to flow rates above a minimum, and understanding the physics of this constraint is important to improve this atomization technique. We study this problem by measuring the minimum flow rate of electrosprays of tributyl phosphate and propylene carbonate at varying electrical conductivity $K$ (all other physical properties such as the density $\unicode[STIX]{x1D70C}$ , surface tension $\unicode[STIX]{x1D6FE}$ and viscosity $\unicode[STIX]{x1D707}$ are kept constant and equal to those of the pure liquids), and through the analysis of numerical solutions. The experiments show that the dimensionless minimum flow rate is a function of both the dielectric constant $\unicode[STIX]{x1D700}$ of the liquid and its Reynolds number, $Re=(\unicode[STIX]{x1D70C}\unicode[STIX]{x1D700}_{o}\unicode[STIX]{x1D6FE}^{2}/\unicode[STIX]{x1D707}^{3}K)^{1/3}$ . This result is unexpected in the light of existing theories which, for the conditions investigated, predict a minimum flow rate that depends only on $\unicode[STIX]{x1D700}$ and/or is marginally affected by $Re$ . The experimental dependency on the Reynolds number requires the viscous stress to be a factor in the determination of the minimum flow rate. However, the numerical solutions suggest that a balance of opposing forces including the fixing viscous stress, which at decreasing flow rates may lower the acceleration of the flow to the point of making it unstable, is unlikely to be the cause. An alternative mechanism is the significant viscous dissipation taking place in the transition from cone to jet, and which at low flow rates cannot be supplied by the work done by the tangential electric stress in the same area. Instead, mechanical energy injected into the system farther downstream must be transferred upstream where dissipation predominantly takes place. This mechanism is supported by the balance between the energy dissipated and the work done by the electric stress in the transition from cone to jet, which yields a relationship between the minimum flow rate, the Reynolds number and the dielectric constant that compares well with experiments.
Kemampuan Berpikir Kritis Siswa Sdn Margorejo VI Surabaya melalui Model Jigsaw

Kemampuan berpikir kritis merupakan kemampuan menganalisis berdasarkan penalaran logis. Pada prinsipnya, orang yang mampu berpikir kritis adalah orang yang tidak begitu saja menerima atau menolak sesuatu, mereka akan mencermati, menganalisis dan mengevalusi sebelum menentukan apakah mereka menerima atau menolak informasi. Tujuan penelitian ini adalah untuk mengetahui pengaruh model pembelajaran Jigsaw pada mata pelajaran IPA terhadap kemampuan berpikir kritis siswa. Peneliti mengukur kemampuan berpikir kritis siswa dengan menggunakan soal pretest dan posttest dengan ketuntasan KKM 75. Model pembelajaran Jigsaw merupakan model pembelajaran yang di desain dengan pola kelompok asal dan ahli untuk meningkatkan rasa tanggungjawab siswa terhadap pembelajarannya sendiri dan orang lain. Sintaks model pembelajaran Jigsaw yang digunakan adalah (1) pembagian kelompok (2) pemberian materi (3) anggota kelompok mempelajari bagian materi yang di tugaskan (4) pertemuan kelompok ahli (5) kembali ke kelompok asal (6) pemberian kuis. Peneliti mengukur model pembelajaran Jigsaw dengan mengggunakan lembar keterlaksanaan model Jigsaw. Pada penelitian ini menggunakan 2 kelas yakni kelas kontrol dan kelas eksperimen. Jenis penelitian ini adalah deskriptif kuantitatif dengan metode eksperimen, dan menggunakan desain penelitian pretest posttest control group design dengan jumlah subyek sebanyak 40 siswa. Teknik pengumpulan data yang digunakan adalah metode observasi dan tes. Analisis data yang digunakan adalah uji statistic non-parametrik dengan analisis uji Mann Whitney, karena data tidak berdistribusi normal dan tidak homogen. Berdasarkan hasil output “Test Statistics” dari uji Mann Whitney menunjukkan Asymp. Sig. (2-tailed) bernilai 0,000 < 0,05, maka dapat disimpulkan bahwa hipotesis 1 (H_1) diterima, yang artinya ada perbedaan pada nilai pretest dan posttest serta ada pengaruh model pembelajaran Jigsaw terhadap kemampuan berpikir kritis siswa.
Preliminary Neurophysiological Evidence of Altered Cortical Activity and Connectivity With Neurologic Music Therapy in Parkinson's Disease

Neurologic Music Therapy (NMT) is a novel impairment-focused behavioral intervention system whose techniques are based on the clinical neuroscience of music perception, cognition, and production. Auditory Stimulation (RAS) is one of the NMT techniques, which aims to develop and maintain a physiological rhythmic motor activity through rhythmic auditory cues. In a series of breakthrough studies beginning in the mid-nineties, we discovered that RAS durably improves gait velocity, stride length, and cadence in Parkinson's disease (PD). No study to date reports the neurophysiological evidence of auditory-motor frequency entrainment after a NMT intervention in the Parkinson's community. We hypothesized that NMT-related motor improvements in PD are due to entrainment-related coupling between auditory and motor activity resulting from an increased functional communication between the auditory and the motor cortices. Spectral analysis in the primary motor and auditory cortices during a cued finger tapping task showed a simultaneous increase in evoked power in the beta-range along with an increased functional connectivity after a course of NMT in a small sample of three older adults with PD. This case study provides preliminary evidence that NMT-based motor rehabilitation may enhance cortical activation in the auditory and motor areas in a synergic manner. With a lack of both control subjects and control conditions, this neuroimaging case-proof of concept series of visible changes suggests potential mechanisms and offers further education on the clinical applications of musical interventions for motor impairments.
Miniature Dual-Band Meander-Line Monopole Chip Antenna With Independent Band Control

A dual-band monopole chip antenna with an overall size of 5 × 3 × 2.1 mm3 is investigated for 2.4/5.2/5.8 GHz WLAN applications. The chip antenna has three substrates with four copper layers in total. It deploys a modified nonuniform folded meander line and capacitive loading patches to reduce the antenna size. A fundamental monopole mode and a higher order mode are excited to obtain the 2.4 GHz (2.40–2.48 GHz) and 5 GHz (5.150–5.350 GHz and 5.725–5.875 GHz) WLAN bands, respectively. The lower and upper bands can be independently controlled by the widths of the meander lines on the first and third layers, respectively. A prototype was fabricated and measured to verify the idea. A reasonable agreement between the measured and simulated results is observed. The measured 10 dB impedance bandwidths of the lower and upper bands are 5.3% (2.38–2.51 GHz) and 19.3% (5.14–6.24 GHz), respectively, fully covering the 2.4/5.2/5.8 GHz WLAN bands. The measured efficiency of the chip antenna is higher than 60% for the two bands.
Thickness Effect of Nanocrystalline Layer on the Deformation Mechanism of Amorphous/Crystalline Multilayered Structure

Different thickness of amorphous/nanocrystalline multi-layered structure can be used to modulate the strength and ductility of the composite materials. In this work, molecular dynamics simulations were conducted to study the thickness effect of nanocrystalline layer on mechanical properties and deformation behavior of the Cu64Zr36/Cu multi-layer structure. The stress-strain relationship, local stress, local strain, and deformation mechanism are investigated. The results reveal that the change of thickness of the crystalline layer significantly affects the mechanical properties and deformation behavior. As the strain at the elastic region, the amorphous Cu64Zr36 layer dominates the mechanical behavior, leading the fact that Young’s modulus, first yielding stress, and first yielding strain are close to that of Cu64Zr36 BMG. As the strain at the plastic region, the contribution of the crystalline layer on the mechanical behavior becomes more and more significant with increasing the thickness of the crystalline layer. For the thickness ratio (amorphous/crystalline) of 4, the shear band deformation of amorphous layer dominates the mechanical properties. For the thickness ratio is 1, the glide dislocation of the crystalline layer dominates the stress-strain behavior.