Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation

Based on a cascaded Kalman–Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method.     

Determination of the Optimum Conditions for Leaching of Zinc Cathode Melting Furnace Slag in Ammonium Chloride Media

This research is part of a continuing effort to leach zinc from zinc cathode melting furnace slags (ZCMFSs) to produce zinc oxide. The slag with an assay of 68.05 pct Zn was used in ammonium chloride leaching for zinc extraction. In this paper, the effects of influential factors on extraction efficiency of Zn from a ZCMFS were investigated. The Taguchi’s method based on orthogonal array (OA) design has been used to arrange the experimental runs in order to maximize zinc extraction from a slag. The softwares named Excel and Design-Expert 7 have been used to design experiments and subsequent analysis. OA L ₂₅ (5⁵) consisting of five parameters, each with five levels, was employed to evaluate the effects of reaction time (t = 10, 30, 50, 70, 90 minutes), reaction temperature [T = 313, 323, 333, 343, 353 (40, 50, 60, 70, 80) K (°C)], pulp density (S/L = 20, 40, 60, 80, 100 g/L), stirring speed (R = 300, 400, 500, 600, 700 rpm), and ammonium chloride concentration (C = 10, 15, 20, 25, 30 pctwt), on zinc extraction percent. Statistical analysis, ANOVA, was also employed to determine the relationship between experimental conditions and yield levels. The results showed that the significant parameters affecting leaching of slag were ammonium chloride concentration and pulp density, and increasing pulp density reduced leaching efficiency of zinc. However, increasing ammonium chloride concentration promoted the extraction of zinc. The optimum conditions for this study were found to be t ₄: 70 minutes, T ₅: 353 K (80 °C), (S/L)₂: 40 g/L, R ₃: 500 rpm, and C ₄: 25 pctwt. Under these conditions, the dissolution percentage of Zn in ammonium chloride media was 94.61 pct.     

Violence detection in videos using interest frame extraction and 3D convolutional neural network

Multimedia Tools and Applications - With the rapid development of detecting violent behaviors in surveillance cameras, requests on systems that automatically recognize violent events are expanded....     

Conversion of CO into CO2 by high active and stable PdNi nanoparticles supported on a metal-organic framework

The solubility of Pd(NO₃)₂ in water is moderate whereas it is completely soluble in diluted HNO₃ solution. Pd/MIL-101(Cr) and Pd/MIL-101-NH₂(Cr) were synthesized by aqueous solution of Pd(NO₃)₂ and Pd(NO₃)₂ solution in dilute HNO₃ and used for CO oxidation reaction. The catalysts synthesized with Pd(NO₃)₂ solution in dilute HNO₃ showed lower activity. The aqueous solution of Pd(NO₃)₂ was used for synthesis of mono-metal Ni, Pd and bimetallic PdNi nanoparticles with various molar ratios supported on MOF. Pd₇₀Ni₃₀/MIL-101(Cr) catalyst showed higher activity than monometallic counterparts and Pd+ Ni physical mixture due to the strong synergistic effect of PdNi nanoparticles, high distribution of PdNi nanoparticles, and lower dissociation and desorption barriers. Comparison of the catalysts synthesized by MIL-101(Cr) and MIL-101-NH₂(Cr) as the supports of metals showed that Pd/MIL-101-NH₂(Cr) outperforms Pd/MIL-101-(Cr) because of the higher electron density of Pd resulting from the electron donor ability of the NH₂ functional group. However, the same activities were observed for Pd₇₀Ni₃₀/MIL-101(Cr) and Pd₇₀Ni₃₀/MIL-101-NH₂(Cr), which is due to a less uniform distribution of Pd nanoparticles in Pd₇₀Ni₃₀/MIL-101-NH₂(Cr) originated from amorphization of MIL-101-NH₂(Cr) structure during the reduction process. In contrast, Pd₇₀Ni₃₀/MIL-101(Cr) revealed the stable structure and activity during reduction and CO oxidation for a long time.     

A circuit-level methodology for leakage power reduction of high-efficient compressors in 22-nm CMOS technology

Analog Integrated Circuits and Signal Processing - A new circuit-level methodology called input controlled leakage restrainer transistor (ICLRT) compatible with single threshold CMOS technology is...     

Resource discovery in the Internet of Things integrated with fog computing using Markov learning model

The Journal of Supercomputing - Due to high and unpredictable connection delays, privacy gaps, and traffic load of networks connecting cloud computing to end users in many of the Internet of Things...     

Proposing a new local density estimation outlier detection algorithm: an empirical case study on flow pattern experiments

Pattern Analysis and Applications - Outlier or anomaly detection is an important branch of data analysis that becomes a crucial task in many application domains. Data objects which significantly...     

Innovative Diagnostic Peptide-Based Technologies for Cancer Diagnosis: Focus on EGFR-Targeting Peptides

Active targeting using biological ligands has emerged as a novel strategy for the targeted delivery of diagnostic agents to tumor cells. Conjugating functional targeting moieties with diagnostic probes can increase their accumulation in tumor cells and tissues, enhancing signal detection and, thus, the sensitivity of diagnosis. Due to their small size, ease of chemical synthesis and site-specific modification, high tissue penetration, low immunogenicity, rapid blood clearance, low cost, and biosafety, peptides offer several advantages over antibodies and proteins in diagnostic applications. Epidermal growth factor receptor (EGFR) is one of the most promising cancer biomarkers for actively targeting diagnostic and therapeutic agents to tumor cells due to its active involvement and overexpression in various cancers. Several peptides for EGFR-targeting have been identified in the last decades, which have been obtained by multiple means including derivation from natural proteins, phage display screening, positional scanning synthetic combinatorial library, and in silico screening. Many studies have used these peptides as a targeting moiety for diagnosing different cancers in vitro, in vivo, and in clinical trials. This review summarizes the progress of EGFR-targeting peptide-based assays in the molecular diagnosis of cancer.     

Robust non-aggressive three-axis attitude control of spacecraft: dynamic sliding mode approach

Conventional sliding mode control (SMC) has been extensively applied in controlling spacecrafts because of its appealing characteristics such as robustness and a simple design procedure. Several methods such as second-order sliding modes and discontinuous controllers are applied for the SMC implementation. However, the main problems of these methods are convergence and error tracking in a finite amount of time. This paper combines an improved dynamic sliding mode controller and model predictive controller for spacecrafts to solve the chattering phenomenon in traditional sliding mode control. To this aim, this paper develops dynamic sliding mode control for spacecraft’s applications to omit the chattering issue. The proposed approach shows robust attitude tracking by a set of reaction wheels and stabilizes the spacecraft subject to disturbances and uncertainties. The proposed method improves the performance of the SMC for spacecraft by avoiding chattering. A set of simulation results are provided that show the advantages and improvements of this approach (in some sense) compared to SMC approaches.