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This paper attempted a novel approach for system-level modeling and simulation of sigma-delta modulator for low-frequency CMOS integrated analog to digital interfaces. Comparative analysis of various architectures topologies, circuit implementation techniques are described with analytical procedure for effective selection of topologies for targeted specifications.

Virtual instruments are presented in labview environment to analyze the correlation of circuit-level non-ideal effects with key design parameters over sampling ratio, coarse quantizer bits and loop filter order. A fourth-order single-loop sigma-delta modulator is designed and verified in MATLAB simulink environment with careful selection of integrator weights to meet stable desired performance.

The proposed designed achieved SNDR of 122 dB and 20 bit resolution satisfying high-resolution requirements of low-frequency biomedical signal processing applications. Even though the simulation performed at behavioral level, the results obtained are considered as accurate, by including all non-ideal and non-linear circuit errors in simulation process.

Virtual instruments using labview environment used to analyze the correlation of circuit-level non-ideal effects with key design parameters over sampling ratio, coarse quantizer bits and loop filter order for accurate design.

The purpose of this paper is to exploit the multiple-Toeplitz matrices reconstruction method combined with quadratic spatial smoothing processing to improve the direction-of-arrival (DOA) estimation performance of coherent signals at low signal-to-noise ratio (SNRs).

An improved multiple-Toeplitz matrices reconstruction method is proposed via quadratic spatial smoothing processing. Our proposed method takes advantage of the available information contained in the auto-covariance matrices of individual Toeplitz matrices and the cross-covariance matrices of different Toeplitz matrices, which results in a higher noise suppression ability.

Theoretical analysis and simulation results show that, compared with the existing Toeplitz matrix processing methods, the proposed method improves the DOA estimation performance in cases with a low SNR. Especially for the cases with a low SNR and small snapshot number as well as with closely spaced sources, the proposed method can achieve much better performance on estimation accuracy and resolution probability.

The study investigates the possibility of reusing pre-existing designs for the DOA estimation of the coherent signals. The proposed technique enables achieve good estimation performance at low SNRs.

The paper includes implications for the DOA problem at low SNRs in communication systems.

The proposed method proved to be useful for the DOA estimation at low SNR.

The purpose of this paper is to develop an integrated approach for a green product cradle-to-cradle (C2C) fuzzy recycling production planning model.

This paper applies the failure mode and effects analysis technique and Taguchi experimental design method, develops a green product C2C performance evaluation system that considers the fuzzy impacts of environmental laws and regulations, green goodwill, and environmental efficiency of targeting countries, and decides both the optimal green production plan and estimated optimal life cycles.

This study compares the different degree of maturity in environmental regulations, and various recycling situations are simulated to demonstrate the successful applicability of the proposed model as well as the incentive policy for Taiwan, the USA and Bangladesh.

Previous studies failed both to develop a holistic recycling production plan which is able to consider both the optimal combination of recycled components used and final green products produced with the maximum total resultant sales profit and to consider the potential failure phenomenon of recycled components adopted in the final product. Furthermore, most prior studies ignored the influence of environmental law, goodwill of the product and the efficiency of recycling mechanism of the community.

Multiple input multiple-output (MIMO) has emerged as one among the many noteworthy technologies in recent wireless applications because of its powerful ability to improve bandwidth efficiency and performance, i.e. through developing its unique spatial multiplexing capability and spatial diversity gain. For carrying out an enhanced communication in next-generation networks, the MIMO and orthogonal frequency division multiple systems were combined that facilitate the spatial multiplexing on resource blocks (RBs) based on time-frequency. This paper aims to propose a novel approach for maximizing the throughput of cell-edge users and cell-center users.

In this work, the specified multi-objective function is defined as the single objective function, which is solved by the introduction of a new improved algorithm as well. This optimization problem can be resolved by the fine-tuning of certain parameters such as assigned power for RB, cell-center user, cell-edge user and RB allocation. The fine-tuning of parameters is attained by a new improved Lion algorithm (LA), termed as Lion with new cub generation (LA-NCG) model. Finally, the betterment of the presented approach is validated over the existing models in terms of signal to interference plus noise ratio, throughput and so on.

On examining the outputs, the adopted LA-NCG model for 4BS was 66.67%, 66.67% and 20% superior to existing joint processing coordinated multiple point-based dual decomposition method (JC-DDM), fractional programming (FP) and LA models. In addition, the throughput of conventional JC-DDM, FP and LA models lie at a range of 10, 45 and 35, respectively, at the 100th iteration. However, the presented LA-NCG scheme accomplishes a higher throughput of 58. Similarly, the throughput of the adopted scheme observed for 8BS was 59.68%, 44.19% and 9.68% superior to existing JC-DDM, FP and LA models. Thus, the enhancement of the adopted LA-NCG model has been validated effectively from the attained outcomes.

This paper adopts the latest optimization algorithm called LA-NCG to establish a novel approach for maximizing the throughput of cell-edge users and cell-center users. This is the first that work uses LA-NCG-based optimization that assists in fine-tuning certain parameters such as assigned power for RB, cell-center user, cell-edge user and RB allocation.

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.

The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.

The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.

In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.

The study presents the case of an automotive component, which illustrates practical relevance.

In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

The purpose of this study is to investigate the prediction and optimization of multiple performance characteristics in the face milling process of tool steel ASSAB XW-42.

The face milling parameters (cutting speed, feed rate and axial depth of cut) and flow rate (FR) of cryogenic cooling were optimized with consideration of multiple performance characteristics, i.e. surface roughness (SR), cutting force (F_c) and metal removal rate (MRR). FR of cryogenic cooling has two levels, whereas the three face milling parameters each have three levels. Using Taguchi method, an L₁₈ mixed-orthogonal array was selected as the design of experiments. The rough estimation of the optimum face milling parameters was determined by using grey fuzzy analysis. The global optimum face milling parameters were searched by applying the backpropagation neural network-based genetic algorithm (BPNN-GA) method.

The optimum SR, cutting force (F_c) and MRR could be obtained by setting FR, cutting speed, feed rate and axial depth of cut at 0.5 l/min, 280 m/min, 90 mm/min and 0.2 mm, respectively. The experimental confirmation results showed that BPNN-based GA optimization method could accurately predict and significantly improve all of the multiple performance characteristics.

To the best of the authors’ knowledge, there were no publications available regarding multi-response optimization using the combination of grey fuzzy analysis and BPNN-based GA methods during cryogenically face milling process.

A third-order discrete time sigma delta modulator (SDM) is proposed with optimum performance by addressing instability and power dissipations issues, and a novel SDM architecture is designed and verified in behavioural modelling in MATLAB/SIMULINK environment. Simulation results show that performance parameters of proposed modulator achieved SNR of 105.41 dB, SNDR of 101.96 dB and DR of 17 bits for the signal bandwidth of 20 kHz.

This paper describes single-loop SDM design with optimum selection of integrator weights for physiological signal processing in IoT applications.

The proposed discrete time modulator designed with 1-bit quantizer and optimum oversampling ratio proved as power efficient. Integrator scaling coefficients are generated in LabVIEW environment for pure third-order noise shaping.

This paper contains the novelty in the work, and it is suitable for cognitive Internet of Things applications.

Some facilities managers will be in the position of adapting existing space to cope with changing needs, while others will be concerned with drawing up specifications for new spaces. Both need practical advice from the acoustician about how to deal with existing problems of speech and noise in rooms. Many offices facing crises in space planning and in staff management are also faced with difficulties concerning speech acoustics, particularly in the areas of speech intelligibility, speech privacy and noise. Research into these aspects of room acoustics by the present author has resulted in an improved approach to measuring the information characteristics of both speech and noise in rooms. A design index is described for predicting the intelligibility of speech and is illustrated by a typical example of conditions in the open plan office. Advice is also needed on the implications of new speech technologies (speech synthesis and speech recognition) on office layout. These new products have already been in everyday use for over 10 years in some office environments and are becoming more commonplace. It is shown that as the new, speech‐driven equipment is taken up, the problems of containing noise in open‐plan spaces will increase, unless speech acoustics in the office is given a new priority.

The purpose of this paper is to investigate the possibility to replace radio equipment compliance requirements based on equipment parameters with a set of simple metrics that accurately reflects spectrum utilization and spectrum-sharing efficiency.

The approach taken is to go back to the basic factors that determine radio system behavior in a shared spectrum environment: radio frequency power, duty cycle and frequency occupation. By normalizing these parameters, device specificity is avoided and a statistical perspective on spectrum utilization and sharing becomes possible.

The analysis shows that two technology-neutral metrics would be adequate to govern spectrum utilization and sharing: a spectrum utilization metric and a spectrum-sharing efficiency metric. These metrics form the core of regulatory requirements for shared frequency bands. Each shared frequency band could be assigned criteria based on these metrics that take into account the types of applications for which that band will be used.

This work is a first step that identifies the main factors that affect shared spectrum usage from a statistical point of view. More work is needed on the relationship between real-world interference and its abstraction in the spectrum-sharing rules.

The metrics proposed could be considered as the basis for a new approach to the regulation of the license-exempt spectrum, and, by extension, as the basis for generic compliance criteria. Their use would facilitate the compliance assessment of software-defined radio technology.

This work has no direct social implications.

This paper combines new work on spectrum utilization criteria with extensions of previous work on spectrum-sharing efficiency into a comprehensive proposal for a new approach to the regulation of the license-exempt spectrum.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.