Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomic Information Entropy Selection Based Generalized Orthogonal Matching Pursuit Algorithm

To solve the problem of atom selection errors in low signal-to-noise ratio environment and large-scale data processing by generalized orthogonal matching pursuit algorithm, a new atomic information entropy selection based gOMP algorithm is proposed. Firstly, the entropy of each atom, in the support set, is calculated one by one in the current iteration. Then, compared with the entropy value of current atom with the preset entropy value and determined whether to eliminate the atom. By the above iteration steps, the reconstruction accuracy of sparse signal is effectively enhanced due to the atoms of the support set are constantly being updated and become more reasonable. The experiment results prove that the proposed algorithm has better reconstruction ability for one-dimensional sparse signal or two-dimensional image when compared to the gOMP.
Decision Tree Algorithm for Depression Diagnosis from Facial Images

Depression refers to a condition in which mental function continues to deteriorate and adversely affects daily life. Therefore, it is very important to diagnose depression accurately in the early stages. This study extracted depression-related features such as head pose, gaze, and facial expression changes from facial images and proposed a model for diagnosing depression using a decision tree. The proposed model learned the data using two databases. The performance of the algorithm was evaluated through the confusion matrix, receiver operating characteristic (ROC) curve, and achieved value 0.99 for area under the curve (AUC).
Robot Skill Learning Algorithm Based on Dynamic Motion Primitive

In order to realize the complex operation skills learning of a UR 10 collaborative robot, we propose a dynamic-motion-primitive robot skill learning algorithm based on reinforcement learning and imitation learning. Shapes of demonstrated trajectories is re-trained with dynamic motion primitives, and the robot arm replaces the explicit coordinates to reach the target point in an exploratory manner. Experiment results show that the optimized trajectory of the robot can preserves the shape of the teach-and-fit track well.
Subset selection for improved parameter estimation in on-line identification of a synchronous generator

This paper examines subset selection for nonlinear least squares parameter estimation, and applies the methodology to a test system previously studied in the power system literature, involving the on-line identification of a synchronous generator model with many parameters. Subset selection partitions the parameters into well-conditioned and ill-conditioned subsets. We show for the test system that fixing the ill-conditioned parameters to prior estimates (even if these prior estimates are substantially in error), and estimating only the remaining parameters, significantly improves the performance of the estimation algorithm and greatly enhances the quality of the estimated parameters. It is shown that attempts to estimate all of the model parameters, as done in the original work with this test system, can yield extremely unreliable results.
EdgeGym: A Reinforcement Learning Environment for Constraint-Aware NFV Resource Allocation

Optimizing resource allocation in Network Functions Virtualization (NFV) deployment remains a challenging problem due to the complex interactions between network functions and the limited resources available at the network edge. Deep reinforcement learning (DRL) has achieved impressive results in a variety of domains. This paper presents EdgeGym, a reinforcement learning environment to simulate the edge network contexts and constraints for NFV resource allocation. EdgeGym allows researchers and practitioners to evaluate and compare different reinforcement learning algorithms for optimizing the allocation of resources in NFV environments, taking into account various constraints such as affinity policies and maximum latency. We demonstrate the effectiveness of EdgeGym through extensive experiments on training and action masking efficiency. EdgeGym provides a reliable framework for advancing the DRL agent performance in NFV resource allocation and paves the way for further research in this area.
Comparative study of Junctionless and Inverted Mode FinFET for detection of breast cancer cell HS578t at microwave frequency

The timely detection of invasive breast cancer cell HS578t is very important to provide early treatment to the patients suffering from this disease. Thus, in the current work detection of cancerous breast cells is performed using FinFET device. The breast cancer cell (HS578t) and healthy breast cell (MCF-10A) have variable permittivity at microwave frequency which is the basic principle utilized for sensing of these cells. Breast cancer detector is designed using Junctionless (JL) and Inverted mode (IM) FinFET and further their comparison is performed to find suitable device structure for cancer cell detection. Sensitivity is evaluated by studying the change in peak drain current, surface potential and Electric Field. The analysis of drain current sensitivity is also performed for JL and IM FinFET.
Deep Learning for 2D-MIMO scheme based on Optical Camera Communication

Radio frequency (RF) waveforms are widely used in wireless technologies, such as mobile system, smart factory, and smart home systems. Due to its simplicity of installation, wireless communication is better than wire communication. However, the use of high frequencies for data transmission can be harmful to human health. To replace RF waveform for communication system, Optical Wireless Communication (OWC), which deploys visible light waveform for communication, was researched widely by researchers around the world. Visible Light Communication (VLC), Light Fidelity (LiFi), and Optical Camera Communication (OCC) are the three candidates for replacing RF system. In this research, we present an multiple-input multiple-output (MIMO) modulation system based on on-off keying (OOK) modulation in the time domain and a light-emitting diode (LED) array. By adjusting the exposure time, focal length, forward error correction, and Deep learning for object detection, it is still possible to implement this technique with 10 links in various locations at a distance of 20 m with a velocity of 2 m/s.
The Effective Properties of one-Dimensional Hexagonal Qouasicrystal Reinforced Composites

Eshelby tensors regard as the fundamental theory of micromechanics to deal with the particle mixed composite materials. In order to deal with the problem of the effective properties of piezoelectric material reinforced by one-dimensional hexagonal quasicrystal particles, a theoretical model to conduct the effective properties of the composites is obtained with assistance of the received Eshelby tensor. According to these Eshelby tensors, we can establish a connection between inclusions and matrix by employing the equivalent inclusion method. Based on the numerical results, it is obviously noted that the received effective properties of the composites are the functions in term of the particles volume fractionand the shape of particle. Furthermore, it is clearly observed that the effective properties have a markedly changes with respect to the aspect ratio of the particles and the particles volume fraction.
Inverse heat conduction problem solutions via second-order design sensitivities and newton's method

Analytical first- and second-order design sensitivities are derived and for a general nonlinear system. These analytical techniques as well as approximate techniques are then discussed and illustrated via a two degree-of-freedom nonlinear spring system. The design sensitivity concepts are next applied to a nonlinear steady-state conduction system. The first- and second-order design sensitivities are used in conjunction with Newton's method to solve an inverse heat conduction problem. These results are compared to results obtained from the first-order Broyton-Fletcher-Goldfarb-Shanno (BFGS) variable metric method. Analyses are first performed for materials with constant thermal conductivity since an exact solution is known. Subsequent analyses are then performed for materials with temperature dependent thermal conductivity. The second-order sensitivity based method is shown to be superior to the first-order method due to its faster convergence rates, more stable solutions, and limited dependence on regular.
Relay Selection, Eavesdropper-Aware Relaying, PHY-Secrecy Capacity Analysis of Cooperative Wireless System over Hybrid Fading Channels

Physical layer (PHY) security (PLS) exploits the randomness of wireless fading channels and offers better secrecy capacity. Cooperative and eavesdropper-aware relays are useful in establishing reliable and energy-efficient communication links between the source transmitter and destination receiver and enhancing PHY secrecy. We consider a four-node, two-hop cooperative PHY-security model with one eavesdropper node. For it, we propose relay selection probabilistically and relaying in the presence of hybrid fading channels. We derive closed-form expressions for probabilities with which the regenerative relay is selected. Further, we develop an analysis of PHY-secrecy capacity and gain useful insights. We evaluate and validate the performance of the proposed strategy and present different numerical results. The proposed model with the relay selection and energy-efficient relaying strategy is a useful potential benchmark for more complex power-adaptive cooperative PHY-secure systems and networks.
Design of multipolar plasmon excitations in silver nanoparticles

We report on the experimental observation of multipolar plasmon excitations in lithographically designed elongated silver particles. In contrast to spheres, where the extinction bands of the respective multipolar plasmons overlap considerably to form a broad spectrum, spectrally well-separated extinction bands corresponding to plasmons of multipolar order up to n=6 are found. The results agree well with numerical simulations based on the Green’s Dyadic method.
Functions as Selected Effects: The Conceptual Analyst's Defense

In this paper I defend an etiological theory of biological functions (according to which the proper function of a trait is the effect for which it was selected by natural selection) against three objections which have been influential. I argue, contrary to Millikan, that it is wrong to base our defense of the theory on a rejection of conceptual analysis, for conceptual analysis does have an important role in philosophy of science. I also argue that biology requires a normative notion of a "proper function", and that a normative notion is not ahistorical.
Fault detection for linear stochastic systems with sensor stuck faults

This paperaddresses the fault detection (FD) problem for Itô‐type linear stochastic systems with a class of sensor stuck faults and reference inputs. Considering all the possible sensor stuck faults, the stochastic systems are modeled via multi‐models, i.e. fault‐free model and faulty models. The main contributions are that a novel FD scheme in stochastic setting is proposed that is valid for arbitrary small sensor stuck faults including outage cases (the stuck values are zero). In addition, convex conditions for characterizing fault sensitivity performance and disturbance attenuation performance in stochastic sense are presented and these conditions include some previous results on deterministic systems as a special case. Finally, two examples are used to demonstrate the method and its effectiveness. Copyright © 2011 John Wiley & Sons, Ltd.
State-space realization theory of two-dimensional filters

The realization problem of two-dimensional linear filters is approached from a system theoretic point of view. The input-output behavior of such a system is defined by formal power series in two variables, and a Nerode state space is constructed. This state space is, in general, infinite dimensional. If the power series is rational, the dynamics of the filter is described by updating equations on finite-dimensional local state space. The notions of local reachability and observability are defined in a natural way and an algorithm for obtaining a reachable and observable realization is given. In general, local reachability and observability do not imply the minimality of the realization.
Physical processes influencing acoustic radiation from jet engine inlets

Abstract Numerical simulations of acoustic radiation from a jet engine inlet are performed using advanced computational aeroacoustics algorithms and high-quality numerical boundary treatments. As a model of modern commercial jet engine inlets, the inlet geometry of the NASA Source Diagnostic Test is used. Fan noise consists of tones and broadband sound. This investigation considers the radiation of tones associated with upstream-propagating duct modes. The primary objective is to identify the dominant physical processes that determine the directivity of the radiated sound. Two such processes have been identified. They are acoustic diffraction and refraction. Diffraction is the natural tendency for an acoustic duct mode to follow a curved solid surface as it propagates. Refraction is the turning of the direction of propagation of a duct mode by mean flow gradients. Parametric studies on the changes in the directivity of radiated sound due to variations in forward flight Mach number, duct mode frequency, azimuthal mode number and radial mode number are carried out. It is found there is a significant difference in directivity for the radiation of the same duct mode from an engine inlet when operating in static condition versus one in forward flight. It will be shown that the large change in directivity is the result of the combined effects of diffraction and refraction.
The development of an automatic scanning path generation method for the spinneret test

An automatic scanning path generation method is developed. The method is based on a 3-axis automatic inspection system which is used to detect the clearance ratio of spinneret plate. The user can rely on this method to automatically generate the scanning path for an unknown spinneret plate in the spinneret test. Then the scanning path can be learned by the inspection system and repeated it for other the same spinneret. Two type spinnerets are introduced in this paper to describe the automatic scanning path generation method. In this paper, the 3-axis automatic inspection system includes a 3-axes motorized linear stage, a telcentric lens, a top light source, a bottom light source, 1 CCD camera and a controlled PC.
Growth of high-quality single crystals of KYF4 by TSSG method

We report for the first time the growth of large size high quality single crystals of KYF4 (KYF) by TSSG method using the conventional weight-feed-back automatic diameter control Czochralski puller. We have made major revision of the KF-YF3 phase diagram and showed that KYF melts peritectically. The crystals can accommodate large size variations of the dopants. We were able to dope it with a large number of rare earth elements. The crystal has long fluorescence lifetime and weak phonon energy making it ideal as upconversion laser host.
High-throughput process parallelization for laser surface modification on Si-solar cells: determination of the process window

The laser is an extremely suitable non-contact tool for fast and automated in-line processes for example used to improve the efficiency of solar cells. With ultra-short pulsed laser radiation it is possible to decrease the reflectivity by modifying the surface topology of silicon. For the proposed modification, the optimum process window for altering the silicon surface topology on a micrometer scale is found at small laser fluencies at finite repetition rates. A promising up scaling method is process parallelization using in parallel a multiple set of interaction zones with the optimized process characteristics for single process interaction. Based on the single process, required laser process parameters and optical parameters for parallel processing are derived theoretically in order to enable a wafer processing in standard cycle times. Exemplarily 5-inch mc-silicon solar wafers are machined using a linear 7-times diffractive optical element (DOE), and in a second step solar cells are built up to determine the efficiency gain by the laser surface modification. A preliminary absolute efficiency gain of Δη > 0.2 % is achieved.
Simulating flow of DNA suspension using dissipative particle dynamics

We simulate DNA suspension microchannel flows using the dissipative particle dynamics (DPD) method. Two developments make this simulation more realistic. One is to improve the dynamic characteristics of a DPD system by modifying the weighting function of the dissipative force and increasing its cutoff radius, so that the Schmidt number can be increased to a practical level. Another is to set up a wormlike chain model in the DPD framework, according to the measured extension properties of a DNA molecule in uniform flows. This chain model is then used to study flows of a DNA suspension through microchannels. Interesting results on the conformation evolution of DNA molecules passing through the microchannels, including periodic contraction-diffusion microchannels, are reported.
The geometry and thermodynamics of dissipative quantum systems

Dirac's method of classical analogy is employed to include quantum degrees of freedom into a geometric framework of nonequilibrium thermodynamics. The proposed formulation of dissipative quantum mechanics builds entirely upon the geometric structures implied by commutators and canonical correlations. A lucid formulation of a nonlinear quantum master equation follows from the thermodynamic structure. The approach is applicable even at very low temperatures and complex classical environments with internal structure can be handled readily.
Becoming a teacher: experiences of female trainees in initial teacher education in northern Nigeria

: This article foregrounds the experiences of female trainees on a scholarship programme for pre-service teacher education aimed at increasing the number of qualified female teachers from rural northern Nigeria, and boosting female pupil enrolments. Challenging conditions in colleges of education, including curricular shortcomings, overcrowding, limited resources and inadequate learning support were compounded by non-academic factors – especially financial, and gendered constraints. Collectively, they threatened student retention, learning and attainment, and the programme’s gender equity goals. Findings highlight the need to move beyond increasing numbers of female student-teachers, to improving quality in teacher education, paying attention to out-of-college conditions too.
Spatiotemporal Analysis of Surface Changes by Tessellations

This paper develops a method for analyzing the change of surface, a continuous function defined over the two-dimensional space. The surface change is represented by a scalar field in a spatiotemporal region. The region is divided into subregions called hills and waves which are based on the local form of the surface. They are both three-dimensional tessellations of the spatiotemporal region, and provide an overview of the surface change. To summarize the tessellations, four operations are proposed: section, projection, merging, and graph representation. They extract useful information from tessellations to describe the structure of surface change. To test the validity of the method, the change of a retail cluster in Shinjuku and Shibuya area in Tokyo is analyzed. The empirical study yields some interesting findings that help us understand changes in the spatial structure of retailing.
Outcomes of Functional Testing Versus Invasive Cardiac Catheterization for the Evaluation of Intermediate Severity Coronary Stenosis Detected on Cardiac Computed Tomography Angiography

Introduction: The aim of this study was to evaluate the effectiveness of functional testing in comparison to invasive coronary angiography (ICA) among acute chest pain patients whose first diagnostic modality was a coronary computed tomography angiogram (CCTA) and were found to have intermediate coronary stenosis, defined as 50%–70% luminal stenosis. Methods: We conducted a retrospective review of 4763 acute chest pain patients ≥18 years old who received a CCTA as the initial diagnostic modality. Of these, 118 patients met enrollment criteria and proceeded to either stress test (80/118) or directly to ICA (38/118). The primary outcome was 30-day major adverse cardiac event, consisting of acute myocardial infarction, urgent revascularization, or death. Results: There was no difference in 30-day major adverse cardiac event among patients who underwent initial stress testing versus directly referred to ICA (0% vs. 2.6%, P = 0.322) following CCTA. The rate of revascularization without acute myocardial infarction was significantly higher among those who underwent ICA versus stress test [36.8% vs. 3.8%, P < 0.0001; adjusted odds ratio: 9.6, 95% confidence interval, 1.8–49.6]. Patients who underwent ICA had a higher rate of catheterization without revascularization within 30 days of the index admission in comparison to those who underwent initial stress testing (55.3% vs. 12.5%, P < 0.0001; adjusted odds ratio: 26.7, 95% confidence interval, 6.6–109.5). Conclusion: Among patients with intermediate coronary stenosis on CCTA, a functional stress test compared with ICA may prevent unnecessary revascularization and improve cardiac catheterization yield without negatively affecting the 30-day patient safety profile.