Simplified and efficient calibration of a mechanistic cutting force model for ball-end milling

Accurate evaluation of the empirical coefficients of a mechanistic cutting force model is critical to the reliability of the predicted cutting forces. This paper presents a simplified and efficient method to determine the cutting force coefficients of a ball-end milling model. The unique feature of this new method is that only a single half-slot cut is to be performed to calibrate the empirical force coefficients that are valid over a wide range of cutting conditions. The instantaneous cutting forces are used with the established helical cutting edge profile on the ball-end mill. The half-slot calibration cut enables successive determination of the lumped discrete values of the varying cutting mechanics parameters along the cutter axis whereas the size effect parameters are determined from the known variation of undeformed chip thickness with cutter rotation. The effectiveness of the present method in determining the cutting force coefficients has been demonstrated experimentally with a series of verification test cuts.     

Fuzzy-HLSTM (Hierarchical Long Short-Term Memory) for Agricultural Based Information Mining

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches. Hierarchical Long Short-Term Memory (HLSTM) is used to evaluate the efficiency, similarity of the models, and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year. Based on the results, the proposed approaches allows for rapid case retrieval with high accuracy.     

On l∞ and l2 robustness of spatially invariant systems

We consider spatiotemporal systems and study their l_∞ and l₂ robustness properties in the presence of spatiotemporal perturbations. In particular, we consider spatially invariant nominal models and provide necessary and sufficient conditions for system robustness for the cases when the underlying perturbations are linear spatiotemporal varying, and nonlinear spatiotemporal invariant, unstructured or structured. It turns out that these conditions are analogous to the scaled small gain condition (which is equivalent to a spectral radius condition and a linear matrix inequality for the l_∞ and l₂ cases, respectively) derived for standard linear time‐invariant models subject to time‐varying linear and time‐invariant nonlinear perturbations. Copyright © 2009 John Wiley & Sons, Ltd.     

Multiple human tracking in high-density crowds

In this paper, we introduce a fully automatic algorithm to detect and track multiple humans in high-density crowds in the presence of extreme occlusion. Typical approaches such as background modeling and body part-based pedestrian detection fail when most of the scene is in motion and most body parts of most of the pedestrians are occluded. To overcome this problem, we integrate human detection and tracking into a single framework and introduce a confirmation-by-classification method for tracking that associates detections with tracks, tracks humans through occlusions, and eliminates false positive tracks. We use a Viola and Jones AdaBoost detection cascade, a particle filter for tracking, and color histograms for appearance modeling. To further reduce false detections due to dense features and shadows, we introduce a method for estimation and utilization of a 3D head plane that reduces false positives while preserving high detection rates. The algorithm learns the head plane from observations of human heads incrementally, without any a priori extrinsic camera calibration information, and only begins to utilize the head plane once confidence in the parameter estimates is sufficiently high. In an experimental evaluation, we show that confirmation-by-classification and head plane estimation together enable the construction of an excellent pedestrian tracker for dense crowds.     

Alternative approach to compute shear amplification in high‐rise reinforced concrete core wall buildings using uncoupled modal response history analysis procedure

The seismic response of the high‐rise reinforced concrete (RC) wall structures is really complicated as several vibration modes other than the fundamental mode normally contribute significantly to the response—commonly recognized as ‘higher mode effects’. Response spectrum analysis (RSA) procedure, which can account for higher mode effects, is usually employed to compute the seismic design demand for the high‐rise structures. Recent studies show that the inelastic seismic force demands obtained from the rigorous nonlinear response history analysis procedure are much larger than the seismic force design demands obtained from the code‐based RSA procedure for the high‐rise RC wall structures. Though, the nonlinear response history analysis procedure is widely accepted for its ability to provide the most accurate estimate of nonlinear seismic responses, the obtained responses are generally so complex that it is quite difficult for engineers to grasp the overall picture of the responses and gain some insight into them and use them to understand the cause of high seismic demands. Another important issue related to the nonlinear seismic response prediction of the high‐rise RC wall structures is the realistic and accurate numerical modeling of RC walls. In this study, a simplified but reasonably accurate procedure called the uncoupled modal response history analysis procedure is used to interpret the complex nonlinear behavior of high‐rise RC wall structures. Moreover, a finite element model based on modified compression field theory is employed for accurate numerical modeling of RC walls by incorporating the axial‐flexure‐shear interaction. This study, by making use of a better computer modeling approach and an in‐depth analysis by modal decomposition, aims to resolve some of the unanswered questions regarding realistic prediction of nonlinear seismic demands of high‐rise structures.     

Structural and magnetic properties of Pr–Ni substituted Ca0.5Ba0.5Fe12O19 hexa-ferrite nanoparticles

Effect of Pr–Ni substitution on structural and magnetic properties of Ca_0.5Ba_0.5−xPr_xNi_yFe_12−yO₁₉ (x=0.00–0.10 and y=0.00–1.00) prepared by the sol–gel auto combustion method were investigated. The XRD analysis confirmed the single phase M-type hexa-ferrite structure. The lattice parameters were found to increase as Pr–Ni content increases, which is attributed to the ionic size of the implicated cations. The Pr–Ni seems to be completely soluble in the lattice. Transmission electron microscopy reveals that the grain size decreases with increase of Pr–Ni substitution. The coercivity and remanent magnetization ranges from 1511 to 1925 (Oe) and 21.4 to 26.5 (emu/g), respectively. The coercivity values of all the samples fall in the range of M-type hexa-ferrites.     

A comparative study on in vitro behavior of calcium silicate ceramics synthesized from biowaste resources

Calcium silicate ceramics have received significant attention for biomedical applications for their excellent bioactivity and osteoconduction properties. Sol-gel process is extensively used for the fabrication of calcium silicates. In sol-gel process, calcium nitrate tetra hydrate (Ca(NO₃)₂·4H₂O) and tetraethylorthosilicate (TEOS) are used as precursors. However, these precursors are expensive. The objective of this work was to compare in vitro behavior of calcium silicate (CaSiO₃) produced using biowaste such as rice husk ash (RHA) and eggshells (coded; NCS) with CaSiO₃ prepared using TEOS and Ca(NO₃)₂·4H₂O (coded; CCS). Thermal investigation results revealed that the crystallization temperature for NCS is relatively lower (772°C) than for CCS (870°C). Bioactivity was studied in vitro using simulated body fluid (SBF) with respect to mineralization rate of hydroxyapatite. Mineralization of a greater hydroxyapatite was observed on NCS ceramics than CCS ceramics after incubation for 3, 7, 14 days in SBF solution, which was confirmed using X-ray diffractometer, Fourier transform infrared spectroscopy, scanning electron microscopy-energy dispersive spectroscopy. Degradation studies were conducted in Tris-HCl solution and the test results revealed that NCS ceramics has lower dissolution rate than CCS ceramics. The antimicrobial assay has shown that NCS samples exhibit significant zone of inhibition against Escherichia coli and Staphylococcus aureus which confirmed that the CaSiO₃ prepared from RHA and eggshell can prevent bacteria from adhering to the surface. In addition cell culture studies revealed that NCS ceramics possess good cytocompatibility with MG-63 cells and significantly promoted cell proliferation.     

Evaluation of alumina reinforced oil fly ash composites prepared by spark plasma sintering

The thermomechanical behavior of micro/nano-alumina (Al₂O₃) ceramics reinforced with 1-5 wt.% of acid-treated oil fly ash (OFA) was investigated. Composites were sintered using spark plasma sintering (SPS) technique at a temperature of 1400°C by applying a constant uniaxial pressure of 50 MPa. It was evaluated that the fracture toughness of micro- and nanosized composites improved in contrast with the monolithic alumina. Highest fracture toughness value of 4.85 MPam^1/2 was measured for the nanosized composite reinforced with 5 wt.% OFA. The thermal conductivity of the composites (nano-/microsized) decreased with the increase in temperature. However, the addition of OFA (1-5 wt.%) in nanosized alumina enhanced the thermal conductivity at an evaluated temperature. Furthermore, a minimum thermal expansion value of 6.17 ppm*K⁻¹ was measured for nanosized Al₂O₃/5 wt.% OFA composite. Microstructural characterization of Al₂O₃-OFA composites was done by x-ray diffraction and Raman spectroscopy. Oil fly ash particles were seen to be well dispersed within the alumina matrix. Moreover, the comparative analysis of the nano-/microsized Al₂O₃/OFA composites shows that the mechanical and thermal properties were improved in nanosized alumina composites.