Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-Stream Convolutional Network Extracting Effective Spatiotemporal Information for Gait Recognition

Gait recognition identifies a person based on gait feature which is a kind of unique biometric feature that can be acquired at a distance and needn’t cooperation. Gait features consist of abundant temporal features and spatial features. To make good use of the spatiotemporal information in gait features, we propose a two-stream network for gait recognition. In the temporal stream, we insert M3D architecture to an 2D network to capture the temporal information of different time perception domains. What’s more, we combine triplet loss, center loss with ID loss as our loss function to reduce the intra-class distance while increasing the inter-class distance which aids in classification. Our proposed method achieves a new state-of-the-art recognition accuracy in the CASIA-B database with the average rank-l accuracy of 95.63% on the NM subset, 90.86% on the BG subset and 72.15% on the CL subset.
Research on Airport Runway FOD Detection Algorithm Based on Texture Segmentation

In recent years, with the rapid development of aviation science and technology, the role of civil air transportation and military air transportation has become more and more important. As the hub of air transportation, the runway safety has become increasingly important. Foreign objects debris detection has become an urgent problem to ensure the safety of aircraft flight. In view of this problem, based on the theory of machine vision and digital image processing, this paper proposes to use Gabor filters to analyze the texture of airport runway images, segment foreign objects, and prove the effectiveness and practicability of the algorithm through simulation experiments.
Fast Spectral Clustering algorithm based on wavelet basis decomposition

Spectral clustering is a widely used unsupervised clustering algorithm that performs very well in many cases. However, for complex scenes and high-resolution images, the application is limited due to the high computational complexity. In this paper, we propose an efficient spectral clustering algorithm based on wavelet basis decomposition. According to the hierarchical structure of wavelet decomposition, the algorithm reduces the dimension of the eigendecomposition of the graph Laplacian by wavelet basis matrix, the low-frequency eigenvectors of the whole graph Laplacian are solved hierarchically from wavelet subspaces with different levels. Its computational complexity is $O(n) + O(m3/2)$, where $n$ and m. are the number of pixels and selected wavelet coefficients in an image, respectively. To verify the effectiveness and performance of the proposed algorithm, a series of experiments were done on both the Weizmann and BSDS500 segmentation datasets and find that our method, which in practice provides on average about 5 × speed-up to the eigendecomposition computation required for the Laplacian matrix with comparable segmentation accuracy.
NTX: A 260 Gflop/sW Streaming Accelerator for Oblivious Floating-Point Algorithms in 22 nm FD-SOI

In this work we present the first complete design, silicon implementation and measurements in 22 nm FD-SOI of the Network Training Accelerator (NTX) architectural concept [1]. NTX is based on a newly designed partial carrysave "wide-inside" (300 bit) fused multiply-accumulate (FMAC) unit ensuring IEEE 754 compliance and a Root Mean Squared Error 1. 7_lower than a conventional 32 bit FPU on long accumulations such as dot products and convolutions.
Closed-Loop Control and Performance Evaluation of Reduced Part Count Multilevel Inverter Interfacing Grid-Connected PV System

Multilevel inverters (MLIs) have drawn tremendous attention in the power sector. Application of MLI has grown extensively to improve the power quality and efficiency of the photovoltaic (PV) system. For an MLI interfacing PV system, the size, cost and voltage stress are the key constraints of the MLI that need to be minimized. This paper presents a novel reduced part count MLI interfacing single-stage grid-tied PV system along with a closed-loop control strategy. The proposed MLI consists of <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> repeating units and a level boosting circuit (LBC) that assists in generating <inline-formula> <tex-math notation="LaTeX">$4n+7$ </tex-math></inline-formula> voltage levels instead of <inline-formula> <tex-math notation="LaTeX">$2n+3$ </tex-math></inline-formula> levels. Three different algorithms are proposed for a proper selection of dc-link voltages to enhance the levels further. A comparative analysis is carried out to confirm the superiority of the developed MLI. The workability of the proposed MLI is investigated with a 1.3 kW PV system. The closed-loop control strategy ensures the maximum power tracking, dc-link voltage balancing, satisfactory operation of the MLI and injection of clean sinusoidal grid current under any dynamic changes. Comprehensive simulation analysis is carried out considering a 15-level MLI structure. Experimental tests further confirm the practicality of the topological advancement for a PV system under different dynamic conditions.
Optimal Tuning of LQR for Load Frequency Control in Deregulated Power System for Given Time Domain Specifications

Present work proposes a two stage process of designing a linear quadratic regulator (LQR) for load frequency control (LFC) in two area deregulated power system. Primary objective of proposed algorithm is to design an optimal state feedback closed loop system which embodies a set of desired time domain specifications. First stage of the algorithm comprises of desired time response model formulation, with aim that it embodies a given set of time domain specifications. In second stage, optimal selection of elements of weighting matrices "Q" and "R", used in standard LQR design procedure are carried out with objective of minimizing the error between designed responses and the desired response models. In present work, optimal selection of weighting matrices elements is formulated in an optimization framework which is solved by the application of a simple, parameter-less population based optimization technique called Jaya algorithm. The proposed algorithm reduces the tedious selection process of LQR weighting matrices elements. Optimal tuning of LQR weighting matrices elements is based on minimization of objective function which is formulated with objective of achieving a designed state feedback closed loop system response as close to that a desired time response model. The proposed algorithm has been illustrated for design of a state feedback load frequency controller (LFC) in two area deregulated power system with aim of achieving a given set of time domain specification. The performance of the proposed method is evaluated by carrying out design and simulation for a bilateral contract scenario in two area deregulated power system. Obtained results show that the designed closed loop system responses closely match with that of the desired time response models with minimum control effort and less computation time.
Visual 3D Reconstruction System Based on RGBD Camera

With the development of computer science and artificial intelligence, the industrial field is gradually becoming unmanned. In this paper, a 3D point cloud image is created with an RGBD camera, the scene is restored through dense 3D reconstruction, and then the color information in the 3D point cloud image is recognized to obtain the 3D coordinates of the area to be painted. Finally, the coordinates are sent to the painting robot to achieve the purpose of automatic painting. This article describes the visual 3D reconstruction part. Unlike the current painting system, this system can automatically obtain the position information without the need to fix the position of the object. In the end, the system can realize the dense reconstruction of 3D point clouds of objects, which provides a certain reference for industrial unmanned management.
Optimization Method to Maximize Efficiency Map of a Drive Motor With Electrical Winding Changeover Technique for Hybrid EV

The electrical winding changeover technique (EWCT) in hybrid electric vehicles will become key to improving the efficiency maps over the whole operating range in the future. This technique can enhance a flux weakening control and reduce a back electromotive force at high speed operation by changing the effective winding turn number. It can increase the efficiency at high speed by a reduction of winding resistance. In this paper, the motor is operated with two step modes, where the winding turn number of the first step mode is twice that of the second step mode. Each step mode is addressed in terms of torque production, back-EMF, voltage and efficiency. Finally, an optimal design of the interior permanent magnet synchronous motor with EWCT is implemented for maximizing the efficiency map based on finite element analysis.
Effect of nitrogen-sulfur ratio on the digestibility of roughage based diet incubated with rumen liquor of buffalo

Abstract In a compeletely randomized experiment, with factorial arrangment, the effects of three levels of urea and four levels of sulfur were tested on in vitro digestibilty and fermentability of rouphage based ration, incubated in rumen liqure of buffalo. Results showed that in vitro digestibility were not affected by the levels of urea, sulfur, or interaction of these factores. There was no variation among the treatments up to 12h of incubation for the cummulative gas production, but it was reduced when surful level increased from 0.37 to 0.41 or 0.45 percent of diet. Regardless of sulfur, urea significantly (p<0.05) affected gas production. There was also an interaction effect between nitrogen and sulfur levels on gas production, after 12 or 24h of fermentation (p<0.05) but not for the longer times of incubation. It could be concluded that 0.33% sulfur and 0.5 or 1.0% urea which provided a total N/S ratio of 4.68 to 5.28 or urea N/S ratio of 0.66 to 1.34 may be optimum ranges for rumen fermentations of rouphage based diets in buffalo.
Proposing a Framework for Resilient Active Distribution Systems using Withstand, Respond, Adapt, and Prevent Element

The increasing frequency of natural disasters and man-made attacks have increased power outages worldwide. Thus, a resilient infrastructure must be constructed to reduce power system damages which directly impacts on the social and economic lives of people. In this paper, a new framework called withstand, respond, adapt, and prevent (WRAP) is presented to evaluate and improve the resilience of distribution networks following a review on existing studies. This resilience enhancement may happen through microgrid and multi- microgrid development in planning or operation stages. Each element of the WRAP framework is responsible for the improvement of the power system resilience in terms of its own attributes and resilience evaluation index. Furthermore, the WRAP framework is defined on the basis of a flowchart with respect to conditional statements. The WRAP framework can be a helpful solution in measuring the resiliency of the power system in terms of robustness, rapidity, adaptability, and predictability. Finally, a case study considering energy-not- supplied as a resilience evaluation index is presented.
Dynamic Bandwidth Scheduling of Software Defined Networked Collaborative Control System

From the perspective of collaborative design of control and scheduling, a software-defined networked collaborative control system (SD-NCCS) is established. On this basis, the system performance of SD-NCCS is analyzed and the average sensitivities of reference are used in utility function to evaluate the effects of network-induced delays. Moreover, the network pricing mechanism and game theory are introduced and a dynamic bandwidth resource allocation model of the overall control system for optimal performance is obtained. Thus, the problem of the network resource allocation of the SD-NCCS has been converted to be the problem of solving the Nash equilibrium point under the non-cooperative game model. Furthermore, the Nash equilibrium solution under this frame is obtained using the estimation distributed algorithm (EDA). Finally, a simple example is included to illustrate the performance of our scheme.
Distributed Gradient Methods for Convex Machine Learning Problems in Networks: Distributed Optimization

This article provides an overview of distributed gradient methods for solving convex machine learning problems of the form min<sub><italic>x</italic> ∈ R<sup><italic>n</italic></sup></sub> (1/<italic>m</italic>) ∑<sub><italic>i</italic> = 1</sub><sup><italic>m</italic></sup> <italic>f</italic><sub><italic>i</italic></sub>(<italic>x</italic>) in a system consisting of <italic>m</italic> agents that are embedded in a communication network. Each agent <italic>i</italic> has a collection of data captured by its privately known objective function <italic>f</italic><sub><italic>i</italic></sub>(<italic>x</italic>). The distributed algorithms considered here obey two simple rules: privately known agent functions <italic>f</italic><sub><italic>i</italic></sub>(<italic>x</italic>) cannot be disclosed to any other agent in the network and every agent is aware of the local connectivity structure of the network, i.e., it knows its one-hop neighbors only. While obeying these two rules, the distributed algorithms that agents execute should find a solution to the overall system problem with the limited knowledge of the objective function and limited local communications. Given in this article is an overview of such algorithms that typically involve two update steps: a gradient step based on the agent local objective function and a mixing step that essentially diffuses relevant information from one to all other agents in the network.
Prevalence of Pulmonary Tuberculosis

Aims: This study was conducted to determine the prevalence of tuberculosis among prison inmates at Mbarara Central prison Design: A cross sectional study was carried out at Mbarara Central Prison in Mbarara district, Kiswahili cell in Mbarara municipality among female and male prison in mates between June 2012 to August 2012. A questionnaire was administered to each prison inmate who consented in writing and two sputum specimens were collected and examined by Ziehl-Neelsen technique.
Chemical Medicine: Novel 10‐Substituted Cytisine Derivatives with Increased Selectivity for α4β2 Nicotinic Acetylcholine Receptors

Neuronal nicotinic acetylcholine receptors (nAChR) are widely distributed in the central and peripheral nervous systems. These receptors are crucial to many normal physiological functions, and they are involved in a wide range of diseases. For these reasons nAChRs are important targets for drug discovery. Neuronal nAChRs are composed of subunits (a2-a10, b2-b4) that form pentameric ligand-gated cation channels. Different combinations of subunits define the nAChR subtypes. Among all heteromeric nAChR subtypes in the vertebrate brain, the a4b2 receptor is the predominant subtype. In contrast, the a3b4 nAChR is the major subtype in ganglia. The a4b2 receptors are involved in important brain functions, including memory, cognition, arousal, relaxation, and pleasure. 20,21] Several lines of evidence suggest that the a4b2 nAChRs mediate addiction to nicotine in tobacco smoking. In addition to acetylcholine and ( )-nicotine (1), many nAChR ligands have been discovered from natural sources, including epibatidine (2) and ( )-cytisine (3). The structures of nicotine, epibatidine, cytisine, and other natural nicotinic ligands have led to the development of a host of other synthetic compounds that act on neuronal nicotinic receptors. Although many of the synthetic analogues of these natural ligands exhibit excellent overall selectivity to neuronal nAChRs over other families of receptors, the development of ligands highly selective for a certain nAChR subtype over other subtypes has been slow because of the large number of nAChR subtypes together with the relatively subtle differences in their structures. ( )-Cytisine (3) is a plant alkaloid isolated originally from the gold chain tree (Laburnum anagyroides). This ligand binds to a4b2 nAChRs with a much higher affinity than it binds to a3b4 receptors in in vitro ligand binding assays. However, when its effects on nAChR channel function were measured in heterologous expression models, cytisine is a full or nearly full agonist at a3b4 nAChRs but a partial agonist at b2-containing receptors, stimulating less than 50% of the maximal response elicited by acetylcholine or nicotine. Cytisine has been marketed in central and eastern Europe for aiding smoking cessation for more than 40 years though its effectiveness and safety have not been conclusively established through randomized, double-blind, placebo-controlled clinical trials. As cytisine shows poor penetration of the bloodbrain barrier this may be one of the reasons that cytisine failed to show a robust effect in the clinic. In spite of these clinical shortcomings, the interesting pharmacological profile of cytisine has led to a number of medicinal chemistry efforts in recent years to create analogues with an improved subtype selectivity or PK parameters. 10,39–42] Most of these reported structural modifications involve the introduction of substituents at the alicyclic nitrogen (position 3), or at the 9or 11positions of the pyridone ring (Figure 1).
Effects of defoliation on carbohydrate status, nodules and spring growth in white clover in a sub-arctic climate

Abstract In order to improve the basis for utilizing white clover (Trifolium repens L) in northern agriculture, we studied the effects of defoliation intensity on spring growth in a sub-arctic climate in relation to carbohydrate and nodule status. White clover plants (cv Snowy) were studied in a pot experiment in the field on the coast of northern Norway from spring 2001 until spring 2002. The experiment was repeated with some modifications from spring 2002 until spring 2003. During the growing season from summer to autumn, the plants were totally stripped of leaves down to the stolon, cut at four or seven cm height or left undisturbed. The plants were sampled destructively in autumn, early spring and late spring and sorted into leaves, stolons and roots. The plant material was weighed and analysed for carbohydrate reserves and nodule number. Defoliation during the growing season resulted in reduced concentration of reserve carbohydrates in autumn and reduced winter survival of the stolons. The most severe defoliation treatment reduced the herbage growth in spring. In contrast, the two milder defoliation treatments had no effect on herbage growth during spring or on total plant dry matter and nodule status in late spring. In conclusion, moderate defoliation during the growing season had no effect on herbage growth the following spring nor on carbohydrate, nodule or dry matter status of the plant in late spring. Moderate defoliation increased spring growth and thereby also the nitrogen demand of the plants. This probably enhanced nodule formation and development of inactive to active nodules.
Ecotypic differentiation in photosynthesis and growth of Eriophorum vaginatum along a latitudinal gradient in the Arctic

Ecotypic differentiation reduces climatic niche breadth at the population level relative to a species' spatial distribu- tion. For species that form climatic ecotypes, if future climate exceeds local population tolerance, climate change will precipitate the decline of extant populations range-wide. Here, we examine the variation in physiological and morphological traits of Eriophorum vaginatum L. collected from a 30-year-old reciprocal transplant experiment, in which six populations of E. vaginatum were transplanted along a latitudinal gradient from Eagle Creek to Prudhoe Bay, Alaska. We tested for ecotypic differentiation of photosynthesis, respiration, chlorophyll fluorescence, and biomass per tiller, which is a metric correlated with population growth in E. vaginatum. The light-saturated photosynthetic rate (Amax) showed homesite advantage in that tussocks in their homesites had significantly higher values of Amax relative to nonlocal populations. This pattern of homesite advantage was also observed for biomass per tiller, but not for fluorescence and respiration. Photosynthetic rate was positively correlated with biomass per tiller and survival, suggesting that adaptations related to photosynthesis may optimize performance of local populations to homesite conditions. Taken together, these findings indicate that a rapidly changing climate may elicit popula- tion decline of E. vaginatum, rendering this species at a competitive disadvantage to shrubs and boreal forest species, which are expanding northward as the climate changes. Transition from tussock-sedge tundra to boreal forest and shrubland alters features, such as albedo, soil temperature, and water-table depth, in ways that may accelerate climate change.
X‐ray Microanalysis of the Mineral Contents of Some Protozoa

With the aid of energy-dispersive X-ray microanalysis, several protozoa were tested for content of cations within inorganic minerals. The skeleton of acantharia consists mainly of Sr with small quantities of Ca and Ba. Two Loxodes species contain nothing but Ba, while in some Remanella species Sr with small quantities of Ba were present. In one Geleia species, Ca with small quantities of Sr was found; in two Trachelocerca species from Sylt (Germany), Ba is there in addition. Another Trachelocerca species from northern Italy lacked Ba, but did possess Mn. In Prorodon only Ca was found.
Drought tolerant bacterial endophytes with potential plant probiotic effects from Ananas comosus

Endophytic bacteria with multi-trait plant probiotic features have been demonstrated to have applications to enhance agricultural productivity by supporting the plant growth, yield and disease resistance under harsh environmental conditions. The xerophytic plant Ananas comosus was selected as the source for endophytic bacterial isolation in the current study . This has resulted in the identification of organisms with antifungal and plant growth promoting properties. Interestingly, endophytic bacteria with antifungal activity were found to have drought tolerance property also. These organisms were demonstrated to express the plant beneficial mechanisms like IAA, ACC deaminase and nitrogen fixation under drought condition. The selected organisms were further identified as Bacillus sp. (Acb9), Providencia sp. (Acb11), Staphylococcus sp. (Acb12), Staphylococcus sp. (Acb13) and Staphylococcus sp . (Acb14)(Acb 14). In addition, LC-MS/MS analysis of extract from Acb 9 has resulted in the identification of surfactin with m/z of 994. Priming of selected endophytes with Vigna radiata seedlings also showed enhanced growth parameters such as shoot length, root length and root numbers when compared to the control . The shoot length of Acb 9 treatment was found to be 18.833 ± 0.687 cm, where the control value for same was 13.976 ± 0.585 cm and the root length was 3.9 ± 0.99 when compared to control (1.54 ± 0.628). The root length was 3.9±0.99 which was also higher than control (1.54±0.62). The results of the study indicate the promise of endophytic bacteria for field application under changing agro-climatic conditions.