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This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

This paper presents a VHDL‐AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance.

The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL‐AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench.

Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular‐shape, triangular or trapezoidal membership functions.

The test of the FLC has only been done in the simulation stage, no physical prototype has been made.

This paper proposes a novel way of improving the FLC's performance and a new application area for VHDL‐AMS.

As voice search has progressively become a new way of information acquisition and human–computer interaction, this paper aims to explore the users' voice search behavior in human–vehicle interaction.

This study employed mixed research methods, including questionnaires and interviews. A total of 151 Amazon MTurk volunteers were recruited to complete a questionnaire based on their most recent and impressive voice search experience. After the questionnaire, this paper conducted an online interview with the participants.

This paper studied users' voice search behavior characteristics in the context of the human–vehicle interaction and analyzed the voice search content, search need, search motivation and user satisfaction. In addition, this paper studied the barriers and suggestions for voice search in human–vehicle interaction through a content analysis of the interviews.

This paper's analysis of users' barriers and suggestions has a specific reference value for optimizing the voice search interaction system and improving the service.

This study is exploratory research that seeks to identify users' voice search needs and tasks and investigate voice search satisfaction in human–vehicle interaction context.

The purpose of this paper is to present the methods of concurrent optimization of the analogue and digital parts (software‐hardware) of estimating, identifying and filtering systems with adaptively adjusted analogue parts – adaptive estimation systems (AES).

Concurrent (complete) optimization of AES permits the determination of the most efficient algorithms for computing the estimates and the controls adjusting analogue units of AES in the way maximally improving the quality of observations delivered by them to the digital part. Performance of AES is assessed by the mean square error (MSE) of estimates which is constructed employing the models of input excitation, analogue and digital parts. Global extremum of MSE is searched by Bayesian methods taking into account the always bounded input range of AES and its possible overloading.

There are determined upper boundaries of potentially achievable accuracy of estimates, as well as optimal estimating and controlling observation units' algorithms, ensuring their achievement. New effects appearing in completely optimal AES are analysed.

The paper presents the backgrounds of new and analytically complex approach. To clarify basic ideas and methods, the simplest but useful for applications single input‐single output and single input‐multiple output models of ASE were considered. The obtained results create wide field for further investigations.

The results of the paper can be applied in the development of new classes of high‐efficient adaptive data acquisition, measurement, controlling, communication and other systems.

Concurrent optimisation of AES is important task having no general solution until now. Known approaches allow only the separate optimisation of the analogue and digital parts. Presented original approach enables the correct formalisation and solution of this task that permits the design and realization of systems with characteristics close to theoretically achievable ones and exceeding the characteristics of the known systems of similar predestination.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

This paper aims to present a pipeline to progressively deal with the online external parameter calibration and estimator initialization of the Stereo-inertial measurement unit (IMU) system, which does not require any prior information and is suitable for system initialization in a variety of environments.

Before calibration and initialization, a modified stereo tracking method is adopted to obtain a motion pose, which provides prerequisites for the next three steps. Firstly, the authors align the pose obtained with the IMU measurements and linearly calculate the rough external parameters and gravity vector to provide initial values for the next optimization. Secondly, the authors fix the pose obtained by the vision and restore the external and inertial parameters of the system by optimizing the pre-integration of the IMU. Thirdly, the result of the previous step is used to perform visual-inertial joint optimization to further refine the external and inertial parameters.

The results of public data set experiments and actual experiments show that this method has better accuracy and robustness compared with the state of-the-art.

This method improves the accuracy of external parameters calibration and initialization and prevents the system from falling into a local minimum. Different from the traditional method of solving inertial navigation parameters separately, in this paper, all inertial navigation parameters are solved at one time, and the results of the previous step are used as the seed for the next optimization, and gradually solve the external inertial navigation parameters from coarse to fine, which avoids falling into a local minimum, reduces the number of iterations during optimization and improves the efficiency of the system.

The purpose of this paper is to propose a methodology that may aid in assessing information technology (IT) quality characteristic optimisation through the use of simple and robust tools with minimal effort.

Non‐linear saturated fractional factorial designs proposed by Taguchi receive robust data processing by the efficient nonparametric test of Jonckheere and Terpstra.

The paper finds that e‐mail quality improvement is achieved by collecting data through an unreplicated‐saturated L₉(3⁴) design. Active influences are attributed to the e‐mail volume and the receiving hardware type.

The overall efficiency of the method is greatly enhanced due to incorporation of a nonparametric analysis tool that is known to perform effectively when data availability is minimal. The method does not succumb to normality and multi‐distributional effects which may easily handicap the decision‐making process when derived from other mainstream methods.

There are obvious professional and pedagogical aspects in this work aiming at IT quality practitioners offering facilitation towards implementing robust techniques while suppressing quality costs. It is noteworthy that nonparametric data processing improves on the ability to make predictions over Taguchi's regular Design of Experiments (DOE) formulation for small sampling conditions.

This method embraces designing efficiency by non‐linear orthogonal arrays with multi‐level order statistics providing the weaponry to deal with quality optimisation in complex environments such as those in the IT area. The value of this work may be appreciated best by quality managers and engineers engaged in routine quality improvement projects in the area of information systems which also augments the general database of quality‐related testing cases.

In this paper, the authors present different methods for reconfigurable finite impulse response (RFIR) filter design. Distributed arithmetic (DA)-based reconfigurable FIR filter design is suitable for software-defined radio (SDR) applications. The main contribution of reconfiguration is reuse of registers, multipliers, adders and to optimize various parameters such as area, power dissipation, speed, throughput, latency and hardware utilizations of flip-flops and slices. Therefore, effective design of building blocks will be optimized for RFIR filter with all the above parameters.

The modified, direct form register structure of FIR filter contributes the reuse concept and allows utilization of less number of registers and parallel computation operations. The disadvantage of DA and other conventional methods is delay increases proportionally with filter length. This is due to different partial products generated by adders. The usage of adder and multipliers in DA-FIR filter restricts the area and power dissipation because of their complexity of generation of sum and carry bits. The hardware implementation time of an adder can be reduced by parallel prefix adder (PPA) usage based on Ling equation. PPA uses shift-add multiplication, which is a repetitive process of addition, and this process is known as Bypass Zero feed multiplicand in direct multiplication, and the proposed technique optimizes area-power product efficiently. The modified DA (MDA)-based RFIR filter is designed for 64 taps filter length (N). The design is developed by using Verilog hardware description language and implemented on field-programmable gate array. Also, this design validates SDR channel equalizer.

Both RFIR and SDR are integrated as single system and implemented on Artix-7 development board of XC7A100tCSG324 and exploited the advantages in area-delay, power-speed products and energy efficiency. The theoretical and practical comparisons have been carried out, and the results are compared with existing DA-RFIR designs in terms of throughput, latency, area-delay, power-speed products and energy efficiency, which are improved by 14.5%, 23%, 6.5%, 34.2% and 21%, respectively.

The DA-based RFIR filter is validated using Chipscope Pro software tool on Artix-7 FPGA in Xilinx ISE design suite and compared constraint parameters with existing state-of-art results. It is also tested the filtering operation by applying the RFIR filter on Audio signals for removal of noisy signals and it is found that 95% of noise signals are filtered effectively.

The area behind the engine/wing junction of conventional civil aircraft configurations with underwing-mounted turbofans is susceptible to local flow separation at high angles of attack, which potentially impacts maximum lift performance of the aircraft. This paper aims to present the design, testing and optimization of two distinct systems of fluidic actuation dedicated to reduce separation at the engine/wing junction.

Active flow control applied at the unprotected leading edge inboard of the engine pylon has shown considerable potential to alleviate or even eliminate local flow separation, and consequently regain maximum lift performance. Two actuator systems, pulsed jet actuators with and without net mass flux, are tested and optimized with respect to an upcoming large-scale wind tunnel test to assess the effect of active flow control on the flow behavior. The requirements and parameters of the flow control hardware are set by numerical simulations of project partners.

The results of ground test show that full modulation of the jets of the non-zero mass flux actuator is achieved. In addition, it could be shown that the required parameters can be satisfied at design mass flow, and that pressure levels are within bounds. Furthermore, a new generation of zero-net mass flux actuators with improved performance is presented and described. This flow control system includes the actuator devices, their integration, as well as the drive and control electronics system that is used to drive groups of actuators.

The originality is given by the application of the two flow control systems in a scheduled large-scale wind tunnel test.