Impulse Response Research Articles

A Comparative Analysis of Bhumija-Style Gondeshwar Temple’s Acoustic Characteristics with Hemadpanti-Style Temples

ABSTRACT The study of the Hindu temple’s acoustics, acoustic characteristics, sound quality for clarity of music and speech intelligibility, and other applicable acoustic parameters must be addressed more in the literature. This study has conducted field measurements in Bhumija-style Gondeshwar temples in Nashik district, India. The temple has a distinctive tiered domed concave ceiling design in the pavilion and sanctum space and unique acoustic properties shaped by its architectural features. The research aims to report and investigate the acoustic characteristics through the well-known Impulse Response (IR) method to investigate empty temple conditions. A 3D model was imported and calibrated in ODEON 12.10 to compare scenarios when the worshippers were 100% present in the temple for various musical and chanting activities. Objective room-acoustic parameters such as Early Decay Time (EDT), Reverberation Time (T30), Clarity of Music (C80), Definition (D50), and Speech Transmission Index (STI) were measured and analyzed. The field measurements were also compared with previously studied Hemadpanti-style Hindu temples, such as the Markanda and Mrikunda temples. The results indicated that the tiered ceiling in Hemadpanti temples indicates a balance and moderate T30 values for all frequency ranges, as compared to the tiered concave domed ceiling in Bhumija-style Gondeshwar temple with higher T30 values observed at the lower frequency.

Internal tides and the inviscid dynamics of an oscillating ellipsoid in a stratified fluid

A boundary integral representation is derived for the translational oscillations of a triaxial ellipsoid in a uniformly stratified fluid. The representation is of single-layer type, a distribution of sources and sinks over the surface of the ellipsoid. The added mass tensor of the ellipsoid is deduced from it and, from this tensor, the impulse response function together with the energy radiated away as internal waves. Horizontal oscillations correspond to the generation of an internal or baroclinic tide by the oscillation of the barotropic tide over ellipsoidal topography at the bottom of the stratified ocean. Such topography is unconditionally supercritical, namely of slope larger than the slope of the wave rays, irrespective of the frequency of oscillation. So far, analytical work on supercritical topographies has been limited, for the most part, to two-dimensional set-ups. Here, for the ellipsoidal seamount, the orientation of the barotropic tide and the anisotropy of the topography have their effects analysed in detail. As the height of the seamount increases, the rate of conversion of barotropic energy into baroclinic form is seen to first increase according to the square law expected for a topography of small slope, then saturate and eventually decrease.

A Sinusoidal Current Generator IC with 0.04% THD for Bio-Impedance Spectroscopy Using a Digital ΔΣ Modulator and FIR Filter

This paper presents a highly efficient, low-power, compact mixed-signal sinusoidal current generator (CG) integrated circuit (IC) designed for bioelectrical impedance spectroscopy (BIS) with low total harmonic distortion (THD). The proposed system employs a 9-bit sine wave lookup table (LUT) which is simplified to a 4-bit data stream through a third-order digital delta–sigma modulator (ΔΣM). Unlike conventional analog low-pass filters (LPF), which statically limit bandwidth, the finite impulse response (FIR) filter attenuates high-frequency noise according to the operating frequency, allowing the frequency range of the sinusoidal signal to vary. Additionally, the output of the FIR filter is applied to a 6-bit capacitive digital-to-analog converter (CDAC) with data-weighted averaging (DWA), enabling dynamic capacitor matching and seamless interfacing. The sinusoidal CG IC, fabricated using a 65 nm CMOS process, produces a 5 μA amplitude and operates over a wide frequency range of 0.6 to 20 kHz. This highly synthesizable CG achieves a THD of 0.04%, consumes 19.2 μW of power, and occupies an area of 0.0798 mm2. These attributes make the CG IC highly suitable for compact, low-power bio-impedance applications.

Improving Visual Object Detection using General UFIR Filtering

Object detection is a fundamental task in computer vision, which involves the identification and localization of objects within image frames or video sequences. The problem is complicated by large variations in the video camera bounding box, which can be thought of as colored measurement noise (CMN). In this paper, we use the general unbiased finite impulse response (GUFIR) approach to improve detection performance under CMN. The results are compared to the general Kalman filter (GKF) and two detection methods: “Faster-RCNN” and “Tensorflow PASCAL Visual Object Classes (VOC)”. Experimental testing is carried out using the benchmark data ”Car4”. It is shown that GUFIR significantly improves the detection accuracy and demonstrates the properties of the effective tool for visual object tracking.

Fourier-optics imaging analysis with ABCD matrices: tutorial

The use of ABCD (ray-transfer) matrices to analyze wave propagation through paraxial optical systems, with emphasis on imaging systems, is described. It is shown how to find the image, Fourier transform, and exit pupil planes. Different forms of the propagation integrals are given. The propagation integral for an imaging system, which includes an aperture stop, is derived. The relationships between the aperture stop and the exit pupil and the impulse response of a paraxial imaging system are derived.

Linear prediction coefficients correction method for digital speech processing systems with data compression based on the autoregressive model of a voice signal

The problem of distortion of the autoregressive model of the voice signal under the influence of additive background noise in digital speech processing systems with data compression based on linear prediction is considered. In the frequency domain, these distortions are observed in the weakening of the main formants responsible for the intelligibility of the speaker’s speech. To compensate for formant attenuation, it is proposed to modify the parameters of the autoregressive model (linear prediction coefficients) using the impulse response of a recursive shaping filter. Along with the amplitude amplification of the formants, their frequencies remain unchanged to make the speaker’s voice recognizable. The effectiveness of the method was studied experimentally using specially developed software. Based on the experimental results, conclusions were drawn about a significant increase in the relative level of formants in the power spectrum of the corrected voice signal.

Event-Triggered Transmission of Sensor Measurements Using Twin Hybrid Filters for Renewable Energy Resource Management Systems

Recently, solar and wind power generation have gained attention as pathways to achieving carbon neutrality, and Renewable Energy Resource Management System (RERMS) technology has been developed to monitor and control small-scale, distributed renewable energy resources. In this work, we present an Event-Triggered Transmission (ETT) algorithm for RERMS, which transmits sensor measurements to the base station only when necessary. The ETT algorithm helps prevent congestion in the communication channel between RERMS and the base station, avoiding time delays or packet loss caused by the excessive transmission of sensor measurements. We design a hybrid state estimation algorithm that combines Kalman and Finite Impulse Response (FIR) filters to enhance the estimation performance, and we propose a new ETT algorithm based on this design. We evaluate the performance of the proposed algorithm through experiments that transmit actual sensor measurements from a photovoltaic power generation system to the base station, demonstrating that it outperforms existing algorithms.

Improved Cooperation Search Optimization Algorithm for Infinite Impulse Response System Identification

Improved Cooperation Search Optimization Algorithm for Infinite Impulse Response System Identification

Macroeconomic Uncertainty and Sectoral Output in Nigeria

The paper examined the impact of macroeconomic uncertainty on the ten largest subsectors of the Nigerian economy using quarterly data from Q1 1981 to Q4 2023. The rationale behind selecting the subsectors is that these sectors constitute about 89 percent of the entire productive activities in the economy. To achieve the objectives, the paper created an index for macroeconomic uncertainty using exchange rate uncertainty, interest rate uncertainty, inflation uncertainty, and real gross domestic product (GDP) uncertainty to create this index. Furthermore, the paper explored the impacts of macroeconomic uncertainty and these individual economic uncertainty indexes on sector output. The study employed the novel dynamic autoregressive distributed lag (novel dynamic ARDL) technique to estimate the results and used the canonical cointegrating regression (CCR) and fully modified ordinary least square (FMOLS) techniques as robustness on the main findings. The findings demonstrated that during periods of recession, macroeconomic uncertainty tends to heighten or reach its peak in Nigeria. Furthermore, the paper showed that the sectors react homogenously to macroeconomic uncertainty. In addition, the impulse response results from the novel dynamic ARDL estimation show that macroeconomic uncertainty can predict robust negative movements in sector output for Nigeria. Indeed, these findings are insightful as they show the importance of macroeconomic uncertainties as key drivers of sector output in Nigeria. The paper argues that the policy authorities should improve their efforts to reduce macroeconomic uncertainty and foster a stable real sector/sectoral output to enhance the macroeconomic environment for Nigeria to aim for higher levels of growth.

Computationally Efficient Inference via Time-Aware Modular Control Systems

Control in multi-agent decision-making systems is an important issue with a wide variety of existing approaches. In this work, we offer a new comprehensive framework for distributed control. The main contributions of this paper are summarized as follows. First, we propose PHIMEC (physics-informed meta control)—an architecture for learning optimal control by employing a physics-informed neural network when the state space is too large for reward-based learning. Second, we offer a way to leverage impulse response as a tool for system modeling and control. We propose IMPULSTM, a novel approach for incorporating time awareness into recurrent neural networks designed to accommodate irregular sampling rates in the signal. Third, we propose DIMAS, a modular approach to increasing computational efficiency in distributed control systems via domain-knowledge integration. We analyze the performance of the first two contributions on a set of corresponding benchmarks and then showcase their combined performance as a domain-informed distributed control system. The proposed approaches show satisfactory performance both individually in their respective applications and as a connected system.

A Sub-Channel Spatial Homogeneity-Based Channel Estimation Method for Underwater Optical Densely Arrayed MIMO Systems

The limited surface area and structural constraints of small underwater communication devices necessitate a dense placement of transmitting and receiving array elements in optical multiple-input multiple-output (MIMO) systems. The compact layout leads to the formation of sub-channels that exhibit notable spatial correlation and a tendency toward homogeneity. Although sub-channel spatial homogeneity (SSH) may diminish the communication capacity of MIMO systems, it provides a significant advantage by reducing the pilot overhead. In this study, we exploit the inherent SSH and the natural time-domain sparsity of channel impulse response (CIR) in the underwater optical densely arrayed MIMO (UODA-MIMO) system to propose an innovative SSH-based channel estimation (SSH-CE) method. We model the underwater optical CIR at Gbaud rates and integrate it with SSH characteristics. This approach transforms the reconstruction targets of compressive sensing (CS) from conventional CIR samples to prior CIR model parameters and the fitting residuals of the homogeneous sub-channels, reducing the pilot overhead. The simulation results of photon tracing for UODA-MIMO sub-channels in turbid harbor water indicate a monotonic, exponential decay in CIR at Gbaud rates, with transmission delays exceeding 5 nanoseconds for distances over 8 m. Moreover, the correlation coefficients among sub-channels reach a minimum of 0.975, confirming the presence of SSH in UODA-MIMO systems. In comparison to existing CS methods that rely on known sparsity, sparsity adaptation, and the structural sparsity of MIMO channels, the SSH-CE method achieves a lower degree of sparsity in reconstruction targets and a reduced lower bound for pilot requirements under the SPARK criterion. Specifically, the SSH-CE method achieves a reduction in the pilot overhead for reconstructing Nt sub-channels of K-sparse to 2Nt irrespective of CIR residual compensation.

Automatic Obstacle Avoidance Trolley System Based on Two-Dimensional ReS2/WSe2 Heterojunction Photodetector.

With the continuous advancement of intelligent vehicle technology, automatic obstacle avoidance (AOA) has become a crucial component of in-vehicle systems. This study introduces an AOA trolley system based on ReS2/WSe2 heterojunction photodetectors. The device with type-II band alignment exhibits an impressive on/off current ratio of 7.14 × 104, along with a rapid impulse response time of 32.3/24.4 μs, a detectivity of 2.0 × 1013 Jones, and an anisotropic ratio of 4.2 under 532 nm illumination. Additionally, the device is electrically tunable under an appropriate gate bias. These characteristics are ascribed to the engineering of the heterojunction interface between ReS2 and WSe2. Furthermore, this device was successfully integrated into an AOA system for autonomous vehicles. The system utilizes the high sensitivity and fast response features of two-dimensional materials, allowing it to effectively identify and avoid obstacles in real time, thereby enhancing driving safety.

Analysis of Price Transmission Chili at the Level from Producer to Consumer in Tapin Regency

The fluctuating prices of chili peppers can significantly impact farmers positively and negatively. Farmers cultivating bird’s eye chili can reap substantial profits with high prices. However, they earn less when bird’s eye chili prices are low. Currently, market integration refers to the evolution of costs across different market sectors and the extent to which market sectors in various geographical locations are informed about the supply and demand occurring in a market. This study aims to: 1) analyze the price developments of bird’s eye chili at the producer, wholesale, and consumer levels in Tapin Regency; 2) examine the price transmission of bird’s eye chili from the producer level to the consumer level through prices at the wholesale level and the production of bird’s eye chili in Tapin Regency. The data used in this research are secondary in the form of monthly time series data. The study utilized the documentation method, with data collected from January 2017 to December 2022, totaling 72 data points. The data analysis method employed is the Vector Error Correction Model (VECM), with tests including the Stationarity Test, Optimal Lag Length Test, Stability Test, Cointegration Test, VECM Estimation, Impulse Response Function (IRF), and Forecast Error Variance Decomposition (FEVD). The findings indicate that the prices of bird’s eye chili exhibit monthly fluctuations. The higher price fluctuations at the producer level indicate that farmers have weak bargaining power in setting the prices of bird’s eye chili. The stationarity test shows that the prices of bird’s eye chili at the consumer (HK), wholesale (HG), and producer (HP) levels, along with bird’s eye chili production (PC), are stationary at the first difference. The optimal lag test, with the smallest Akaike Information Criterion (AIC), is lag 2. The cointegration test shows that the trace statistic and max-eigen values are greater than the critical value, thus accepting H1, indicating a long-term relationship. In the short term, the increase in bird’s eye chili prices is influenced by the two previous periods. The analysis results demonstrate asymmetric price transmission from the producer level to the consumer price level.

Social protection for inclusive growth: a tale of two countries Pakistan and Bangladesh

PurposeThis paper examines and compares the role of social protection to promote inclusive growth in two countries (once related), Pakistan and Bangladesh, from 1984 to 2020, using annual time series data.Design/methodology/approachThe study used principal component analysis to develop the index of social protection, inclusive growth and macroeconomic stability. It also employed co-integration with impulse response function and fully modified ordinary least squares test for long-run cointegration.FindingsThe key results highlighted that social protection positively promotes inclusive growth in both countries. However, Bangladesh attains a high position in achieving inclusive growth through the mechanism of welfare programs. Findings show that institutional quality, macroeconomic stability and globalization are the positive and significant drivers of inclusive growth in both countries. It also confirms that macroeconomic stability and globalization are contributing more to achieving inclusive growth in Bangladesh as compared to Pakistan.Practical implicationsInstitutions and macroeconomic stability in both countries are critical toward providing a transparent system of welfare schemes to achieve inclusive growth. Shocks to social protection schemes in Pakistan are inconsistent for achieving inclusive growth as compared to Bangladesh.Originality/valueThe study extends the empirical measurement of social protection and inclusive growth while using protracted dimensions and indicators. It further examines and compares the dynamics of social protection programs for inclusive growth in two countries once related. For further originality and reliability, this study checks the robustness of long-run estimates by disaggregating the institutional quality and globalization into their key dimensions.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0548

Exchange rate innovation, global pandemic and stock market returns: Empirical evidence from ECOWAS countries

This study used the panel VAR impulse response function model and high-frequency monthly data from 2020M1 to 2021M12 to examine the response of innovations in the exchange rate and stock market returns to the COVID-19 pandemic in Economic Communities of West African States (ECOWAS). The study found that the effect of shocks of COVID-19 today on future exchange rate innovation worsens the real conditions of exchange rate innovation in ECOWAS countries. Again, the impact of the shocks of COVID-19 today on future stock market returns encourages the real conditions of stock market returns in ECOWAS countries. It was recommended that instead of lockdown, ECOWAS governments should explore other policy options peculiar to the region in COVID-19 containment and also strive harder to deepen the stock market and encourage increased utilization of information and communication technology in stock market trading to cut costs, raise returns and connect trade with the rest of the world’s stock markets.

Air Attenuation in Octave Bands and How to Normalize Room Acoustic Measurements to a Standard Atmosphere

The air attenuation of pure tones as a function of temperature and humidity is well known and described in ISO and ANSI standards. However, room acoustic measurements are performed in octave bands, which is the reason for the complicated, non-linear behavior of the air attenuation. It is known that room acoustic measurement results depend on air temperature and humidity, and these atmospheric data should always be reported in connection with room acoustic measurements. A calculation model for the air attenuation can make it possible to normalize the room acoustic results. For accurate results, it is possible to apply a summation method on each time sample in the impulse response. An approximation to the air attenuation at and above 1 kHz is possible by linearization using the pure-tone attenuation of two different frequencies, one frequency valid for the early part of the impulse response and another frequency valid for the later part of the impulse response. The purpose of the suggested methods is to make it possible to normalize room acoustic measurements to a standard atmosphere.

Losengram: An effective demodulation frequency band selection method for rolling bearing fault diagnosis under complex interferences

Abstract Resonance demodulation is one of the most effective methods for rolling bearing fault diagnosis. However, the selection of the proper demodulation frequency band (DFB) has always been considered as a substantial challenge. Although many popular DFB selection methods have been developed, such as fast Kurtogram (FK), Protrugram, and Autogram, they would suffer unsatisfactory performance degradation when encountering random impulsive noise or cyclostationary noise. Therefore, this paper proposes a novel DFB selection method called Losengram to address this problem. In the proposed method, a robust sub-band indicator, localized square envelope spectrum kurtosis, is designed to evaluate the fault information in a sub-band. With this indicator, the interferences of random impulsive noise and cyclostationary noise could be suppressed well. Besides, in order to circumvent the various adverse effects incurred by the utilization of a multi-rate finite impulse response filter bank, a frequency-domain sub-band filtering strategy is presented to filter the divided sub-bands in a 1/3-binary tree structure. The effectiveness of the proposed method is tested on both simulated and experimental signals, and the results show that it has a superior performance than the FK, Protrugram, as well as Autogram.

The Effect of Food Price Stabilization on Inflation in West Nusa Tenggara 2019-2023

One of the primary contributors to the inflation rate in West Nusa Tenggara Province is the fluctuation of prices for food commodities. The objective of this study is to examine the extent to which fluctuations in food commodity prices, including those of rice, red chili, and shallots, contribute to inflationary trends in West Nusa Tenggara. The data used is monthly data on inflation and food commodity prices from 2019-2023 obtained from BPS (Central Bureau of Statistics), DKP (Food Security Agency), and the Agriculture Office of West Nusa Tenggara Province. The analysis method used is vector autoregression (VAR), which includes stationarity test, VAR stability test, optimal lag test, cointegration test, VAR estimation, impulse response function (IRF), and variance decomposition. The results of this study indicate that in the short term premium rice prices, curly red chili prices, and shallots do not affect inflation. Conversely, in the long run, the variable price of shallots does not affect inflation, while the variable price of premium rice and curly red chili prices exert an influence on inflationary pressures in West Nusa Tenggara Province. The Variance Decomposition Test indicates that the price of curly red chili contributes 37.24 percent to inflation in the fifth period, while premium rice has an effect of 8.66 percent on inflation in the second period and shallots have an effect of 7.93 percent on inflation in the fifth period.

Investigation of the Dynamic Relationship between Oil Temperature and Bearing Gearbox Condition Indicator Values for the Bell 407 Helicopter Based on Cointegration Analysis

The primary objective of this study is to investigate the dynamic relationship between oil temperature and the Bearing Gearbox Condition Indicator (BGCI) values of the Bell 407 helicopter. To achieve this goal, we employ robust econometric tools, such as unit root tests, cointegration tests, and Autoregressive Distributed Lag (ARDL) models for both, long-run and short-run estimates. Our findings indicate that variable temperature tends to converge to its long-run equilibrium path in response to changes in other variables. The results of the ARDL analysis confirm that spectral kurtosis, inner race, cage, and ball energy significantly contribute to the increase in temperature. Furthermore, we use the impulse response function (IRF) to trace the dynamic response paths of shocks to the system. The identification of a cointegrating relationship between oil temperature and BGCI values suggests a practical and significant connection that can potentially be used to predict hazardous changes in oil temperature using BGCI values, which is an important implication for enhancing the safety and reliability of helicopter operations. This study presents a promising direction for condition monitoring (CM) in rotating aircraft machinery, emphasizing the potential of integrating temperature data to simplify the diagnostic process while still achieving reliable results.

Comparative analysis of RNN versus IIR digital filtering to optimize resilience to dynamic perturbations in pH sensing for vertical farming

AbstractVertical farming (VF) refers to systems of agriculture where crops are grown in trays stacked vertically by exposing them to artificial light and using sensing technology to improve product quality and yield. In this work, we propose an advanced filtering scheme based on recurrent neural networks (RNNs) and deep learning to enable efficient control strategies for VF applications. We demonstrate that the best RNN model incorporates five neuron layers, with the first and second containing 90 long short‐term memory neurons. The third layer implements one gated recurrent units neuron. The fourth segment incorporates one RNN network, while the output layer is designed by using a single neuron exhibiting a rectified linear activation function. By utilizing this RNN digital filter, we introduce two variations: (1) a scaled RNN model to tune the filter to the signal of interest, and (2) a moving average filter to eliminate harmonic oscillations of the output waveforms. The RNN models are contrasted with conventional digital Butterworth, Chebyshev I, Chebyshev II, and elliptic infinite impulse response (IIR) configurations. The RNN digital filtering schemes avoid introducing unwanted oscillations, which makes them more suitable for VF than their IIR counterparts. Finally, by utilizing the advanced features of scaling of the RNN model, we demonstrate that the RNN digital filter can be pH selective, as opposed to conventional IIR filters.