A charge sharing–based switching scheme for SAR ADCs

This paper presents an energy-efficient switching scheme for successive approximation register (SAR) analogue-to-digital converter (ADC). The proposed scheme employs charge recycling method to keep the capacitor arrays free of transitional energy between bit generations except reset phase. In comparison with the conventional switching scheme, the proposed one achieves 100% transitional energy saving without considering reset phase. In addition, configuration of a 10-bit SAR ADC shows that the proposed switching scheme reduces the capacitor area by 25% compared with the conventional switching scheme.     

Energy and load balancing routing protocol for IoT

Due to the limitation of node energy resources, the management of energy consumption is one of the most important problems of the internet of things (IoT). Therefore, many studies have tried to optimize and manage energy consumption by focusing on different techniques. Although each of these studies has improved and optimized energy consumption, there are many important problems, including maintaining traffic balance and energy consumption of network nodes. Therefore, a new method is necessary to maintain the load and energy balancing of network nodes. Therefore, this paper introduces energy and load balancing routing protocol for IoT (ELBRP) based on the development of the RPL routing protocol and the efficiency of data distribution technique. The ELBRP performance has three steps. In the first step, along with the process of sending DODAG information object (DIO) messages, the status of network nodes is evaluated. In the second step, the DODAG communication graph is formed according to the ELBRP. In the third step, data transmission is done according to the distribution technique with the goal of balancing traffic and energy. The simulation results using cooja simulator showed the superiority of ELBRP in improving energy consumption and successful delivery ratio, reducing delay and increasing the network lifetime compared to the similar methods.     

A meshless method for solving 1D time-dependent heat source problem

A novel meshless numerical procedure based on the method of fundamental solutions (MFS) and the heat polynomials is proposed for recovering a time-dependent heat source and the boundary data simultaneously in an inverse heat conduction problem (IHCP). We will transform the problem into a homogeneous IHCP and initial value problems for the first-order ordinary differential equation. An improved method of MFS is used to solve the IHCP and a finite difference method is applied for solving the initial value problems. The advantage of applying the proposed meshless numerical scheme is producing the shape functions which provide the important delta function property to ensure that the essential conditions are fulfilled. Numerical experiments for some examples are provided to show the effectiveness of the proposed algorithm.     

A modified particle swarm optimization for economic dispatch with non-smooth cost functions

This paper presents a new approach to economic dispatch (ED) problems with non-smooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have non-smooth cost functions with equality and inequality constraints, which makes the problem of finding the global optimum difficult when using any mathematical approaches. Since, standard PSO may converge at the early stage, in this paper, a modified PSO (MPSO) mechanism is suggested to deal with the equality and inequality constraints in the ED problems. To validate the results obtained by MPSO, standard particle swarm optimization (PSO) and guaranteed convergence particle swarm optimization (GCPSO) are applied for comparison. Also, the results obtained by MPSO, PSO and GCPSO are compared with the previous approaches reported in the literature. The results show that the MPSO produces optimal or nearly optimal solutions for the study systems.     

An efficient classifier to diagnose of schizophrenia based on the EEG signals

In this paper, electroencephalogram (EEG) signals of 13 schizophrenic patients and 18 age-matched control participants are analyzed with the objective of classifying the two groups. For each case, multi-channels (22 electrodes) scalp EEG is recorded. Several features including autoregressive (AR) model parameters, band power and fractal dimension are extracted from the recorded signals. Leave-one (participant)-out cross validation is used to have an accurate estimation for the separability of the two groups. Boosted version of Direct Linear Discriminant Analysis (BDLDA) is selected as an efficient classifier which applied on the extracted features. To have comparison, classifiers such as standard LDA, Adaboost, support vector machine (SVM), and fuzzy SVM (FSVM) are applied on the features. Results show that the BDLDA is more discriminative than others such that their classification rates are reported 87.51%, 85.36% and 85.41% for the BDLDA, LDA, Adaboost, respectively. Results of SVM and FSVM classifiers were lower than 50% accuracy because they are more sensitive to outlier instances. In order to determine robustness of the suggested classifier, noises with different amplitudes are added to the test feature vectors and robustness of the BDLDA was higher than the other compared classifiers.     

Taguchi Optimization of Solvent-Antisolvent Crystallization to Prepare Ammonium Perchlorate Particles

The sphericity and size of ammonium perchlorate (AP) particles significantly influence the properties of composite propellants. As the AP particles become more spherical, the accumulation coefficient increases, the viscosity during casting decreases, and the particle loading and burning rate increase. Hence, the production of micronized AP particles with an average size between 1 and 20 μm is important to increase the loading percentage of AP in the composite propellant. Here, the Taguchi experimental design was used to optimize the solvent-antisolvent crystallization (SAC) process for the preparation of micronized AP particles with higher sphericity. SAC parameters such as the type of antisolvent, the solvent-to-antisolvent ratio, the antisolvent temperature, the stirring speed, and the retention time were investigated at four levels. The type of antisolvent and the solvent-to-antisolvent ratio were found to mainly contribute to improving the sphericity and size of the AP particles, respectively.     

A SAR-based ΣΔ modulator using shared DAC

In this paper a new successive approximation (SA) quantizer based on the elimination of the digital to analog converter (DAC) from the quantizer structure is presented. Instead; the feedback DAC block of the ΣΔ modulator is shared by SA quantizer. Using an efficient decoding algorithm in the proposed structure in conjunction with the above SA quantizer DAC elimination method, results in a reduction of the level number of the feedback DAC, and hence, a significant drop in power and area consumption is achieved. In order to study the performance of the proposed structure, a third order discrete-time ΣΔ modulator is designed and simulated in 0.18 μm CMOS technology with the following performance characteristics; a signal to noise ratio of 79.2 dB, dynamic range of 84.8 dB, power consumption of 3.75 mW and a figure of merit of 0.66 pJ/conv from a 1.8 V supply with an input signal of 200 kHz bandwidth.     

Information requirements analysis for holonic manufacturing systems in a virtual environment

The design and development of holonic manufacturing systems requires careful, and sometimes risky, decision making to ensure that they will successfully satisfy the demands of an ever-changing market. In this paper, the authors propose a methodology for a holonic manufacturing systems requirement analysis that is based on a virtual reality approach and aimed at assisting designers of such systems along the entire systems design and development process. Exploiting virtual reality helps the user collect valid information quickly and in a correct form by putting the user and the information support elements in direct relation with the operation of the system in a more realistic environment. A prototype software system tool is designed to realise the features outlined in each phase of the methodology. A virtual manufacturing environment for matching the physical and the information model domains is utilised to delineate the information system requirements of holonic manufacturing systems implementation. A set of rules and a knowledge base is appended to the virtual environment to remove any inconsistency that could arise between the material and the information flows during the requirement analysis.     

Differential current conveyor based current comparator

A New differential current conveyor based current comparator is presented in this paper. Differential current conveyor II (DCCII) is designed, modified, and exploited as a comparator with reduced propagation delay and power consumption. New DCCII decreases propagation delay and increases comparator accuracy considerably. Simulation results using Hspice and 0.18 μm CMOS technology with 1.8V supply voltage confirms a less than 0.63 ns propagation delay at ±1 μA input current. Average power dissipation in ±1 μA input current has a value of 300 μW.     

Two new low-power Full Adders based on majority-not gates

Two novel low-power 1-bit Full Adder cells are proposed in this paper. Both of them are based on majority-not gates, which are designed with new methods in each cell. The first cell is only composed of input capacitors and CMOS inverters, and the second one also takes advantage of a high-performance CMOS bridge circuit. These kinds of designs enjoy low power consumption, a high degree of regularity, and simplicity. Low power consumption is targeted in implementation of our designs. Eight state-of-the-art 1-bit Full Adders and two proposed Full Adders are simulated using 0.18 μm CMOS technology at many supply voltages. Simulation results demonstrate improvement in terms of power consumption and power-delay product (PDP).