Soft-Computing-Based Embedded Design of an Intelligent Wall/Lane-Following Vehicle

Soft computing techniques are generally well suited for vehicular control systems that are usually modeled by highly nonlinear differential equations and working in unstructured environments. To demonstrate their applicability in real-world applications, two intelligent controllers based on fuzzy logic and artificial neural network are designed for performing a wall-following task. Based on performance and flexibility considerations, the two controllers are implemented onto a reconfigurable hardware platform, namely a field-programmable gate array. As comparative studies of these two embedded hardware controllers designed for the same vehicular application are limited in literature, this research also presents an evaluation of the two controllers, comparing them in terms of hardware resource requirements, operational speeds, and trajectory tracking errors in following different predefined trajectories.     

Multi-criteria decision making in workforce choice using AHP,WSM and WPM

This paper focuses on the implementation of Multi-Criteria Decision Making (MCDM) methods to evaluate the workforce competence in apparel industry. In this study, the Analytic Hierarchy Process (AHP), the Weighted Sum Model (WSM) and the Weighted Product Model (WPM) are suggested to solve workforce selection problem. The use of these methods is expected to help choose the best operator among several alternatives. Based on three criteria, each worker is evaluated in each executed operation. The criteria are a Quality Index ‘QI’, an Activity ‘A’ and an Attendance Rate ‘AR’. Thanks to the MCDM methods, scores allowing an objective classification of operators are obtained. Experimental results on AHP, WSM and WPM methods show the same decisions with the same workers’ classification from the best to the worst alternative. The resulting database contributes to the line balancing optimization by choosing for each operation, and as far as possible, the most competent operator.     

Crystallization of P Type Amorphous Silicon (a-Si: H) by AIC Method: Effect of Aluminum Thickness

In this work, we will study the crystallization of P type hydrogenated amorphous silicon (a-Si:H) by Aluminum Induced Crystallization technique (CIA) by varying the thickness of the aluminum films. We have deposited a 100 nm thickness of p-type a-Si:H layer on Corning glass substrates using PECVD technique. An aluminum layer with thickness ranging from 10 to 400 nm was thermally evaporated on the a-Si:H surface. The thermal annealing was performed in a conventional furnace at temperature of 550 °C for 4 h in flowing N2 ambient. The study of the crystallization of the Al/a-Si:H/Glass structure according the aluminum thickness was carried out by using Raman spectroscopy, X-rays diffraction and Hall Effect measurements. Raman results reveal the presence of the peaks between 510 and 520 cm−1, which are close to the peak of crystallized Si (about 521 cm−1) proving the crystallization of all samples. The XRD measurements show the presence of the characteristic peaks of the crystalline silicon, thus the a-Si: H (p) layer was effectively crystallized by the AIC method in a short time. Through Hall measurements we found an improvement in electrical properties and an increase in dopant concentration (+ 5.3 1014 to + 2.9 1017 cm2).     

Perfect tracking of ZMP trajectory for humanoid locomotion using repetitive control

Journal of Mechanical Science and Technology - In this paper, the tracking of the zero moment point (ZMP) trajectory for humanoid locomotion is addressed. For that, a combination of a repetitive...     

An Innovative Genetic Algorithm for a Multi-Objective Optimization of Two-Dimensional Cutting-Stock Problem

This paper addressed an important variant of two-dimensional cutting stock problem. The objective was not only to minimize trim loss, as in traditional cutting stock problems, but rather to minimize the number of machine setups. This additional objective is crucial for the life of the machines and affects both the time and the cost of cutting operations. Since cutting stock problems are well known to be NP-hard, we proposed an approximate method to solve this problem in a reasonable time. This approach differs from the previous works by generating a front with many interesting solutions. By this way, the decision maker or production manager can choose the best one from the set based on other additional constraints. This approach combined a genetic algorithm with a linear programming model to estimate the optimal Pareto front of these two objectives. The effectiveness of this approach was evaluated through a set of instances collected from the literature. The experimental results for different-size problems show that this algorithm provides Pareto fronts very near to the optimal ones.     

Dual-Color Antenna-Coupled LEKID for Next-Generation Multi-chroic CMB Focal Planes

We present an antenna-coupled Kinetic Inductance Detector for millimeter wave astronomy. Next-generation telescopes for observing the cosmic microwave background are demanding in terms of number of detectors and focal plane area filling efficiency. Moreover, foreground reduction in B-Mode polarimetry requires sky observation with multiple frequency bands. In this context, KIDs are a promising technology because of their large multiplexing rate, while antenna coupling can provide multi-band and dual-polarization solutions in compact design. We have developed polarization-sensitive dual-band pixel at 140 and 160 GHz with a bandwidth of almost 8% for each sub-band. The design involves a microstrip-excited slot antenna and two open-stub band-pass filters to direct the signal toward two resonators. These are lumped elements capacitively coupled to the antenna and include an aluminum strip as absorber. The architecture proposed is particularly simple to fabricate, via-less and only involves two metallization levels. The transition does not require any dielectric deposition above the resonator, thus preventing limitations from any source of noise due to a non-monocrystalline substrate. Furthermore, the same coupling technique can be applied to many types of microstrip-excited antennas, which allow to accommodate band-pass filters.     

Lot-sizing in a multi-stage flow line production system with energy consideration

In this paper, a single-item capacitated lot-sizing problem in a flow-shop system with energy consideration is studied. The planning horizon is defined by a set of periods where each one is characterised by a length, an allowed maximal power, an electricity price, a power price and a demand. The objective is to determine the quantities to be produced by each machine at each period while minimising the production cost in terms of electrical, inventory, set-up and power required costs. For medium- and large-scale problems, lot-sizing problems are hard to solve. Therefore, in this study, two heuristics are developed to solve this problem in a reasonable time. To evaluate the performances of these heuristics, computational experiments are presented and numerical results are discussed and analysed.     

Segmentation of brain MRI using active contour model

Alzheimer disease is a neurodegenerative disorder that impairs memory, cognitive function, and gradually leads to dementia, physical deterioration, loss of independence, and death of the affected individual. In this context, segmentation of medical images is a very important technique in the field of image analysis and Computer‐Assisted Diagnosis. In this article, we introduce a new automatic method of brain images’ segmentation based on the Active Contour (AC) model to extract the Hippocampus and the Corpus Callosum (CC). Our contribution is to combine the geometric method with the statistical method of the AC. We used the Caselle Level Set and added a learning phase to build an average shape and to make the initialization task automatic. For the step of contour evolution, we used the principle of Level set and we added to it the a priori knowledge. Experimental results are very promising. © 2017 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 27, 3–11, 2017     

A novel architecture design for VLSI implementation of integer DCT in HEVC standard

This paper presents novel hardware of a unified architecture to compute the 4?×?4, 8?×?8, 16?×?16 and 32?×?32 efficient two dimensional (2-D) integer DCT using one block 1-D DCT for the HEVC standard with less complexity and material design. As HEVC large transforms suffer from the huge number of computations especially multiplications, this paper presents a proposition of a modified algorithm reducing the computational complexity. The goal is to ensure the maximum circuit reuse during the computation while keeping the same quality of encoded videos. The hardware architecture is described in VHDL language and synthesized on Altera FPGA. The hardware architecture throughput reaches a processing rate up to 52 million of pixels per second at 90 MHz frequency clock. An IP core is presented using the embedded video system on a programmable chip (SoPC) for implementation and validation of the proposed design. Finally, the proposed architecture has significant advantages in terms of hardware cost and improved performance compared to related work existing in the literature. This architecture can be used in ultra-high definition real-time TV coding (UHD) applications.