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Openings on walls, such as windows or doors, facilitate the propagation of external noises to interior spaces. Active noise control is a promising technique for the reduction of low frequency noise propagating through such openings. To preserve the full functionality of the opening, especially for natural ventilation, it is required to minimize the physical size of the secondary sources. In this scenario, using compact speakers and limiting their distances from the reference microphones are critical requirements. In this paper, we present a comparative study on the noise reduction performance of an active noise control system using compact cone-shaped and flat-panel speakers in identical configurations. The performance was measured based on multi-tonal noise with frequency components below 1.2 kHz, using different setups of single reference sensor, single error sensor, and up to four secondary sources. In evaluating the measurement data, including frequency responses, harmonic distortion, radiation patterns, and noise reduction, we highlight key differences of these two types of speakers and determine their respective application contexts.

Background Internationally, there have been efforts to adjust hospital funding based on the quality of care provided by the hospital. A variety of approaches has been used by different countries and payers. Incorporating quality signals into activity-based funding is also a possibility for Australia. This study set out to explore the cost impact of potentially poor quality care in Australian hospitals, and to understand the implications from a funding perspective.

Background Internationally, there have been efforts to adjust hospital funding based on the quality of care provided by the hospital. A variety of approaches has been used by different countries and payers. Incorporating quality signals into activity-based funding is also a possibility for Australia. This study set out to explore the cost impact of potentially poor quality care in Australian hospitals, and to understand the implications from a funding perspective.

Background Internationally, there have been efforts to adjust hospital funding based on the quality of care provided by the hospital. A variety of approaches has been used by different countries and payers. Incorporating quality signals into activity-based funding is also a possibility for Australia. This study set out to explore the cost impact of potentially poor quality care in Australian hospitals, and to understand the implications from a funding perspective.

In this letter, we consider the spectrum sensing of digital video broadcasting-terrestrial (DVB-T) signals with energy detection (ED). ED delivers a superior performance among low computational complexity detectors, but it is vulnerable to noise uncertainty. By exploiting the pilot periodicity in DVB-T signals, we propose a low complexity noise power estimator which works in multipath channels, and does not require time and frequency synchronization. Simulations show that, with the noise power estimator, ED significantly outperforms the pilot correlation-based detection which is often used in DVB-T spectrum sensing.

In this letter, we consider the spectrum sensing of digital video broadcasting-terrestrial (DVB-T) signals with energy detection (ED). ED delivers a superior performance among low computational complexity detectors, but it is vulnerable to noise uncertainty. By exploiting the pilot periodicity in DVB-T signals, we propose a low complexity noise power estimator which works in multipath channels, and does not require time and frequency synchronization. Simulations show that, with the noise power estimator, ED significantly outperforms the pilot correlation-based detection which is often used in DVB-T spectrum sensing.

We investigated the sensitivity change of multiple-elevated-temperature (MET) stimulated post-infrared infrared-stimulated luminescence (MET-pIRIR) signals as a response to irradiation, sunlight bleaching and heating using samples from the Mu Us Desert, central China. A strong dose dependence of MET-pIRIR signal sensitivity was observed. The intensity of the test-dose signals (Tx) increase with the pre-dose received. Furthermore, the signal sensitivity can be reset by sunlight bleaching or heating. This suggests that both the electron traps and hole centres in K-feldspar can be bleached by sunlight, and can, therefore, be used for dating. Using the test-dose signal as a monitor for sensitivity change, it was found that the sensitivity (or hole centres) saturate at a higher dose (D0 = ∼750 Gy) than the sensitivity-corrected signals (or electron traps) (D0 = ∼400 Gy). We propose a multi-aliquot regenerative-dose (MAR) MET-pIRIR dating protocol, which utilises the high saturation dose of hole centres. This protocol was tested using aeolian sediments from north China with ages ranging from 0 to 470 ka. It was found that, compared to the dose limit of ∼800–1000 Gy using the normal MET-pIRIR or pIRIR procedure, the new method can measure a natural dose of up to ∼1500 Gy and produce ages consistent with the expected ages for the samples investigated.

The residual doses and sensitivity change for potassium-rich feldspar (K-feldspar) have been studied using the post-infrared infrared stimulated luminescence (pIRIR) and multi-elevated-temperature post-IR IRSL (MET-pIRIR) protocols. Laboratory simulated poorly-bleached and well-bleached samples were those K-feldspar grains bleached using a solar simulator for 10 minutes and 8 hours, respectively. The residual doses rise with stimulation temperature and time. The poorly-bleached sample has larger residual doses than the well-bleached sample, especially at high stimulation temperatures. The high-temperature pIRIR signals contain a large amount of hard-to-bleach signals. A decrease of luminescence sensitivity was observed after conducting a high-temperature-treatment in the measurement cycles. The sensitivity decreases significantly between the first and the second cycle. The extent of decrease in sensitivity shows a clear temperature trend. The higher the stimulation temperature of pIRIR signals is, the larger the sensitivity decreases. This decrease is more severe for the poorly-bleached sample than for the well-bleached sample, and could possibly lead to problems in sensitivity correction.

We investigated the sensitivity change of multiple-elevated-temperature (MET) stimulated post-infrared infrared-stimulated luminescence (MET-pIRIR) signals as a response to irradiation, sunlight bleaching and heating using samples from the Mu Us Desert, central China. A strong dose dependence of MET-pIRIR signal sensitivity was observed. The intensity of the test-dose signals (Tx) increase with the pre-dose received. Furthermore, the signal sensitivity can be reset by sunlight bleaching or heating. This suggests that both the electron traps and hole centres in K-feldspar can be bleached by sunlight, and can, therefore, be used for dating. Using the test-dose signal as a monitor for sensitivity change, it was found that the sensitivity (or hole centres) saturate at a higher dose (D0 = ∼750 Gy) than the sensitivity-corrected signals (or electron traps) (D0 = ∼400 Gy). We propose a multi-aliquot regenerative-dose (MAR) MET-pIRIR dating protocol, which utilises the high saturation dose of hole centres. This protocol was tested using aeolian sediments from north China with ages ranging from 0 to 470 ka. It was found that, compared to the dose limit of ∼800–1000 Gy using the normal MET-pIRIR or pIRIR procedure, the new method can measure a natural dose of up to ∼1500 Gy and produce ages consistent with the expected ages for the samples investigated.

The residual doses and sensitivity change for potassium-rich feldspar (K-feldspar) have been studied using the post-infrared infrared stimulated luminescence (pIRIR) and multi-elevated-temperature post-IR IRSL (MET-pIRIR) protocols. Laboratory simulated poorly-bleached and well-bleached samples were those K-feldspar grains bleached using a solar simulator for 10 minutes and 8 hours, respectively. The residual doses rise with stimulation temperature and time. The poorly-bleached sample has larger residual doses than the well-bleached sample, especially at high stimulation temperatures. The high-temperature pIRIR signals contain a large amount of hard-to-bleach signals. A decrease of luminescence sensitivity was observed after conducting a high-temperature-treatment in the measurement cycles. The sensitivity decreases significantly between the first and the second cycle. The extent of decrease in sensitivity shows a clear temperature trend. The higher the stimulation temperature of pIRIR signals is, the larger the sensitivity decreases. This decrease is more severe for the poorly-bleached sample than for the well-bleached sample, and could possibly lead to problems in sensitivity correction.

We investigated the sensitivity change of multiple-elevated-temperature (MET) stimulated post-infrared infrared-stimulated luminescence (MET-pIRIR) signals as a response to irradiation, sunlight bleaching and heating using samples from the Mu Us Desert, central China. A strong dose dependence of MET-pIRIR signal sensitivity was observed. The intensity of the test-dose signals (Tx) increase with the pre-dose received. Furthermore, the signal sensitivity can be reset by sunlight bleaching or heating. This suggests that both the electron traps and hole centres in K-feldspar can be bleached by sunlight, and can, therefore, be used for dating. Using the test-dose signal as a monitor for sensitivity change, it was found that the sensitivity (or hole centres) saturate at a higher dose (D0 = ∼750 Gy) than the sensitivity-corrected signals (or electron traps) (D0 = ∼400 Gy). We propose a multi-aliquot regenerative-dose (MAR) MET-pIRIR dating protocol, which utilises the high saturation dose of hole centres. This protocol was tested using aeolian sediments from north China with ages ranging from 0 to 470 ka. It was found that, compared to the dose limit of ∼800–1000 Gy using the normal MET-pIRIR or pIRIR procedure, the new method can measure a natural dose of up to ∼1500 Gy and produce ages consistent with the expected ages for the samples investigated.

In this paper, we present a compressed sensing method for complex-valued signals based on multiple measurement vector compressed sensing model. The proposed method constrains the real and imaginary parts of the recovered signal to have the same sparsity profile. It is applied to a compressed sensing through-the-wall radar imaging problem. Experiments based on synthetic data shows that the proposed method achieves lower reconstruction error than the existing CS method.

We investigated the sensitivity change of multiple-elevated-temperature (MET) stimulated post-infrared infrared-stimulated luminescence (MET-pIRIR) signals as a response to irradiation, sunlight bleaching and heating using samples from the Mu Us Desert, central China. A strong dose dependence of MET-pIRIR signal sensitivity was observed. The intensity of the test-dose signals (Tx) increase with the pre-dose received. Furthermore, the signal sensitivity can be reset by sunlight bleaching or heating. This suggests that both the electron traps and hole centres in K-feldspar can be bleached by sunlight, and can, therefore, be used for dating. Using the test-dose signal as a monitor for sensitivity change, it was found that the sensitivity (or hole centres) saturate at a higher dose (D0 = ∼750 Gy) than the sensitivity-corrected signals (or electron traps) (D0 = ∼400 Gy). We propose a multi-aliquot regenerative-dose (MAR) MET-pIRIR dating protocol, which utilises the high saturation dose of hole centres. This protocol was tested using aeolian sediments from north China with ages ranging from 0 to 470 ka. It was found that, compared to the dose limit of ∼800–1000 Gy using the normal MET-pIRIR or pIRIR procedure, the new method can measure a natural dose of up to ∼1500 Gy and produce ages consistent with the expected ages for the samples investigated.

The residual doses and sensitivity change for potassium-rich feldspar (K-feldspar) have been studied using the post-infrared infrared stimulated luminescence (pIRIR) and multi-elevated-temperature post-IR IRSL (MET-pIRIR) protocols. Laboratory simulated poorly-bleached and well-bleached samples were those K-feldspar grains bleached using a solar simulator for 10 minutes and 8 hours, respectively. The residual doses rise with stimulation temperature and time. The poorly-bleached sample has larger residual doses than the well-bleached sample, especially at high stimulation temperatures. The high-temperature pIRIR signals contain a large amount of hard-to-bleach signals. A decrease of luminescence sensitivity was observed after conducting a high-temperature-treatment in the measurement cycles. The sensitivity decreases significantly between the first and the second cycle. The extent of decrease in sensitivity shows a clear temperature trend. The higher the stimulation temperature of pIRIR signals is, the larger the sensitivity decreases. This decrease is more severe for the poorly-bleached sample than for the well-bleached sample, and could possibly lead to problems in sensitivity correction.

The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroen- cephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise inter- ferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identifica- tion of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detect- ing the R peaks; Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.

Self-mixing interferometry (SMI) signals are observed from a laser diode (LD) with optical feedbacks induced by an external target. SMI signals carry information related to both of the target and parameters of the LDs. However, the noise contained in SMI signals greatly degrades the applications of the SMI systems. This paper proposes a wavelet transform based de-noising method which can effectively eliminate noise while keeping an SMI waveform less changed. The proposed method is verified by both simulations and experiments

The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroen- cephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise inter- ferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identifica- tion of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detect- ing the R peaks; Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.

Self-mixing interferometry (SMI) signals are observed from a laser diode (LD) with optical feedbacks induced by an external target. SMI signals carry information related to both of the target and parameters of the LDs. However, the noise contained in SMI signals greatly degrades the applications of the SMI systems. This paper proposes a wavelet transform based de-noising method which can effectively eliminate noise while keeping an SMI waveform less changed. The proposed method is verified by both simulations and experiments

The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroen- cephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise inter- ferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identifica- tion of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detect- ing the R peaks; Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.

Self-mixing interferometry (SMI) signals are observed from a laser diode (LD) with optical feedbacks induced by an external target. SMI signals carry information related to both of the target and parameters of the LDs. However, the noise contained in SMI signals greatly degrades the applications of the SMI systems. This paper proposes a wavelet transform based de-noising method which can effectively eliminate noise while keeping an SMI waveform less changed. The proposed method is verified by both simulations and experiments

In this paper we present an automatic classification system for ground penetrating radar (GPR) signals. The system extracts the magnitude spectra at resonant frequencies and classifies them using support vector machines. To locate the resonant frequencies, we propose an approach based on compressed sensing and orthogonal matching pursuit. The performance of the system is evaluated by classifying GPR traces from different ballast fouling conditions. The experimental results show that the proposed approach, compared to the approach of using frequencies at local maxima, represents the GPR signal more efficiently using a small number of coefficients, and obtains higher classification accuracy. 2012 IEEE.

In this paper we present an automatic classification system for ground penetrating radar (GPR) signals. The system extracts the magnitude spectra at resonant frequencies and classifies them using support vector machines. To locate the resonant frequencies, we propose an approach based on compressed sensing and orthogonal matching pursuit. The performance of the system is evaluated by classifying GPR traces from different ballast fouling conditions. The experimental results show that the proposed approach, compared to the approach of using frequencies at local maxima, represents the GPR signal more efficiently using a small number of coefficients, and obtains higher classification accuracy. 2012 IEEE.

In this paper we present an automatic classification system for ground penetrating radar (GPR) signals. The system extracts the magnitude spectra at resonant frequencies and classifies them using support vector machines. To locate the resonant frequencies, we propose an approach based on compressed sensing and orthogonal matching pursuit. The performance of the system is evaluated by classifying GPR traces from different ballast fouling conditions. The experimental results show that the proposed approach, compared to the approach of using frequencies at local maxima, represents the GPR signal more efficiently using a small number of coefficients, and obtains higher classification accuracy. 2012 IEEE.

In this paper we present an automatic classification system for ground penetrating radar (GPR) signals. The system extracts the magnitude spectra at resonant frequencies and classifies them using support vector machines. To locate the resonant frequencies, we propose an approach based on compressed sensing and orthogonal matching pursuit. The performance of the system is evaluated by classifying GPR traces from different ballast fouling conditions. The experimental results show that the proposed approach, compared to the approach of using frequencies at local maxima, represents the GPR signal more efficiently using a small number of coefficients, and obtains higher classification accuracy. 2012 IEEE.

Self-mixing interferometry (SMI) signals are observed from a laser diode (LD) with optical feedbacks induced by an external target. SMI signals carry information related to both of the target and parameters of the LDs. However, the noise contained in SMI signals greatly degrades the applications of the SMI systems. This paper proposes a wavelet transform based de-noising method which can effectively eliminate noise while keeping an SMI waveform less changed. The proposed method is verified by both simulations and experiments

The evaluation of distortion diagnosis using Wavelet function for Electrocardiogram (ECG), Electroen- cephalogram (EEG) and Phonocardiography (PCG) is not novel. However, some of the technological and economic issues remain challenging. The work in this paper is focusing on the reduction of the noise inter- ferences and analyzes different kinds of ECG signals. Furthermore, a physiological monitoring system with a programming model for the filtration of ECG is presented. Kaiser based Finite Impulse Response (FIR) filter is used for noise reduction and identifica- tion of R peaks based on Peak Detection Algorithm (PDA). Two approaches are implemented for detect- ing the R peaks; Amplitude Threshold Value (ATV) and Peak Prediction Technique (PPT). Daubechies wavelet transform is applied to analyze the ECG of driver under stress, arrhythmia and sudden cardiac arrest signals. From the obtained results, it was found that the PPT is an effective and efficient technique in detecting the R peaks compared to ATV.

Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a real-world GPR data set. The experimental results show that our system can correctly distinguish ground penetrating radar signals reflected by different materials.

Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a real-world GPR data set. The experimental results show that our system can correctly distinguish ground penetrating radar signals reflected by different materials.

Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a real-world GPR data set. The experimental results show that our system can correctly distinguish ground penetrating radar signals reflected by different materials.

Bradykinin (BK) is an inflammatory mediator and one of the most potent endogenous pain-inducing substances. When released at sites of tissue damage or inflammation, or applied exogenously, BK produces acute spontaneous pain and causes hyperalgesia (increased sensitivity to potentially painful stimuli). The mechanisms underlying spontaneous pain induced by BK are poorly understood. Here we report that in small nociceptive neurons from rat dorsal root ganglia, BK, acting through its B2 receptors, PLC, and release of calcium from intracellular stores, robustly inhibits M-type K+ channels and opens Ca2+-activated Cl- channels (CaCCs) encoded by Tmem16a (also known as Ano1). Summation of these two effects accounted for the depolarization and increase in AP firing induced by BK in DRG neurons. Local injection of inhibitors of CaCC and specific M-channel openers both strongly attenuated the nociceptive effect of local injections of BK in rats. These results provide a framework for understanding spontaneous inflammatory pain and may suggest new drug targets for treatment of such pain.

Ground penetrating radar has been widely used in many areas. However, the processing and interpretation of acquired signals remains a challenging task since it requires experienced users to manage the whole operations. In this paper, we propose an automatic classification system to categorise GPR signals based on magnitude spectrum amplitudes and support vector machines. The system is tested on a real-world GPR data set. The experimental results show that our system can correctly distinguish ground penetrating radar signals reflected by different materials.

Bradykinin (BK) is an inflammatory mediator and one of the most potent endogenous pain-inducing substances. When released at sites of tissue damage or inflammation, or applied exogenously, BK produces acute spontaneous pain and causes hyperalgesia (increased sensitivity to potentially painful stimuli). The mechanisms underlying spontaneous pain induced by BK are poorly understood. Here we report that in small nociceptive neurons from rat dorsal root ganglia, BK, acting through its B2 receptors, PLC, and release of calcium from intracellular stores, robustly inhibits M-type K+ channels and opens Ca2+-activated Cl- channels (CaCCs) encoded by Tmem16a (also known as Ano1). Summation of these two effects accounted for the depolarization and increase in AP firing induced by BK in DRG neurons. Local injection of inhibitors of CaCC and specific M-channel openers both strongly attenuated the nociceptive effect of local injections of BK in rats. These results provide a framework for understanding spontaneous inflammatory pain and may suggest new drug targets for treatment of such pain.

Bradykinin (BK) is an inflammatory mediator and one of the most potent endogenous pain-inducing substances. When released at sites of tissue damage or inflammation, or applied exogenously, BK produces acute spontaneous pain and causes hyperalgesia (increased sensitivity to potentially painful stimuli). The mechanisms underlying spontaneous pain induced by BK are poorly understood. Here we report that in small nociceptive neurons from rat dorsal root ganglia, BK, acting through its B2 receptors, PLC, and release of calcium from intracellular stores, robustly inhibits M-type K+ channels and opens Ca2+-activated Cl- channels (CaCCs) encoded by Tmem16a (also known as Ano1). Summation of these two effects accounted for the depolarization and increase in AP firing induced by BK in DRG neurons. Local injection of inhibitors of CaCC and specific M-channel openers both strongly attenuated the nociceptive effect of local injections of BK in rats. These results provide a framework for understanding spontaneous inflammatory pain and may suggest new drug targets for treatment of such pain.

Bradykinin (BK) is an inflammatory mediator and one of the most potent endogenous pain-inducing substances. When released at sites of tissue damage or inflammation, or applied exogenously, BK produces acute spontaneous pain and causes hyperalgesia (increased sensitivity to potentially painful stimuli). The mechanisms underlying spontaneous pain induced by BK are poorly understood. Here we report that in small nociceptive neurons from rat dorsal root ganglia, BK, acting through its B2 receptors, PLC, and release of calcium from intracellular stores, robustly inhibits M-type K+ channels and opens Ca2+-activated Cl- channels (CaCCs) encoded by Tmem16a (also known as Ano1). Summation of these two effects accounted for the depolarization and increase in AP firing induced by BK in DRG neurons. Local injection of inhibitors of CaCC and specific M-channel openers both strongly attenuated the nociceptive effect of local injections of BK in rats. These results provide a framework for understanding spontaneous inflammatory pain and may suggest new drug targets for treatment of such pain.

Functional magnetic resonance imaging (FMRI) has revolutionized the study of linking physical stimuli with localized brain activity. Among the challenges of working with FMRI data, they are noisy, they exhibit spatial correlation, and they are usually large containing tens of thousands of voxels of information. The notion of False Discovery Rate (FDR) has made a great impact on how to perform powerful multiple hypothesis tests to detect signals in such large multivariate data. The spatial dependence in FMRI data requires special care since, if ignored, it can lead to a loss of control of size as well as a deterioration in power of FDR procedures. This article advocates transforming the voxel-wise test statistics to wavelet space, where the coefficients are approximately uncorrelated. We demonstrate, through a series of experiments, that an FDR procedure in wavelet space enhanced by P-value adaptive thresholding (EPAT), maintains control of the size of the multiple-testing procedure and offers substantially increased power over an FDR procedure that is applied directly to the map of (spatially dependent) test statistics. The EPAT methodology, developed here for FMRI data, is generic and can be applied in other dependent data settings.

It is a peculiar fact that while the natural environment is one of geography's key research and teaching foci, it is difficult to specify what the discipline's distinctive contributions to environmental understanding are. In part, this is because geographical research on the environment remains theoretically and empirically diverse, indeed fragmented. In turn, this is a function of the fact that the precision of this putative focus is deceptive since the term environment is enormously. On the one side, physical geographers study the environment in their own subdisciplinary languages. On the other side, human geographers apply the tools of everything from Marxism to post-structuralism to make sense of environmental discourses and transformations.

Spontaneous and tone-evoked changes in light reflectance were recorded from primary auditory cortex (A1) of anesthetized cats (barbiturate induction, ketamine maintenance). Spontaneous 0.1-Hz oscillations of reflectance of 540- and 690-nm light were recorded in quiet. Stimulation with tone pips evoked localized reflectance decreases at 540 nm in 3/10 cats. The distribution of patches "activated" by tones of different frequencies reflected the known tonotopic organization of auditory cortex. Stimulus-evoked reflectance changes at 690 nm were observed in 9/10 cats but lacked stimulus-dependent topography. In two experiments, stimulus-evoked optical signals at 540 nm were compared with multiunit responses to the same stimuli recorded at multiple sites. A significant correlation (P < 0.05) between magnitude of reflectance decrease and multiunit response strength was evident in only one of five stimulus conditions in each experiment. There was no significant correlation when data were pooled across all stimulus conditions in either experiment. In one experiment, the spatial distribution of activated patches, evident in records of spontaneous activity at 540 nm, was similar to that of patches activated by tonal stimuli. These results suggest that local cerebral blood volume changes reflect the gross tonotopic organization of A1 but are not restricted to the sites of spiking neurons.

Spontaneous and tone-evoked changes in light reflectance were recorded from primary auditory cortex (A1) of anesthetized cats (barbiturate induction, ketamine maintenance). Spontaneous 0.1-Hz oscillations of reflectance of 540- and 690-nm light were recorded in quiet. Stimulation with tone pips evoked localized reflectance decreases at 540 nm in 3/10 cats. The distribution of patches "activated" by tones of different frequencies reflected the known tonotopic organization of auditory cortex. Stimulus-evoked reflectance changes at 690 nm were observed in 9/10 cats but lacked stimulus-dependent topography. In two experiments, stimulus-evoked optical signals at 540 nm were compared with multiunit responses to the same stimuli recorded at multiple sites. A significant correlation (P < 0.05) between magnitude of reflectance decrease and multiunit response strength was evident in only one of five stimulus conditions in each experiment. There was no significant correlation when data were pooled across all stimulus conditions in either experiment. In one experiment, the spatial distribution of activated patches, evident in records of spontaneous activity at 540 nm, was similar to that of patches activated by tonal stimuli. These results suggest that local cerebral blood volume changes reflect the gross tonotopic organization of A1 but are not restricted to the sites of spiking neurons.

In unmanned CNC turning operations, the accuracy of tool wear predictions is very important for accurate tool replacement policies and avoiding unnecessary tool insert changes. This paper introduces two new parameters, namely the total energy and the total entropy of force signals, for tool condition monitoring. The correlation between the new parameters, tool wear and a wide range of cutting conditions is examined. The experimental results show that the energy of force signal can be reliably used to monitor tool flank and crater wear over a wide range of cutting conditions. However, the total entropy of forces does not appear to be sensitive to feed rate, rake angle and tool wear. The experimental results also indicate that crater wear causes an increase in the effective rake angle resulting in lower total energy of forces. For some particular shapes of worn tool, however, the crater wear results in a decreased rake angle which increases the total energy of forces. The influence of crater wear on forces and the root mean square of acoustic emission (AErms) signals is also observed in this research.

In unmanned CNC turning operations, the accuracy of tool wear predictions is very important for accurate tool replacement policies and avoiding unnecessary tool insert changes. This paper introduces two new parameters, namely the total energy and the total entropy of force signals, for tool condition monitoring. The correlation between the new parameters, tool wear and a wide range of cutting conditions is examined. The experimental results show that the energy of force signal can be reliably used to monitor tool flank and crater wear over a wide range of cutting conditions. However, the total entropy of forces does not appear to be sensitive to feed rate, rake angle and tool wear. The experimental results also indicate that crater wear causes an increase in the effective rake angle resulting in lower total energy of forces. For some particular shapes of worn tool, however, the crater wear results in a decreased rake angle which increases the total energy of forces. The influence of crater wear on forces and the root mean square of acoustic emission (AErms) signals is also observed in this research.

In unmanned CNC turning operations, the accuracy of tool wear predictions is very important for accurate tool replacement policies and avoiding unnecessary tool insert changes. This paper introduces two new parameters, namely the total energy and the total entropy of force signals, for tool condition monitoring. The correlation between the new parameters, tool wear and a wide range of cutting conditions is examined. The experimental results show that the energy of force signal can be reliably used to monitor tool flank and crater wear over a wide range of cutting conditions. However, the total entropy of forces does not appear to be sensitive to feed rate, rake angle and tool wear. The experimental results also indicate that crater wear causes an increase in the effective rake angle resulting in lower total energy of forces. For some particular shapes of worn tool, however, the crater wear results in a decreased rake angle which increases the total energy of forces. The influence of crater wear on forces and the root mean square of acoustic emission (AErms) signals is also observed in this research.

In unmanned CNC turning operations, the accuracy of tool wear predictions is very important for accurate tool replacement policies and avoiding unnecessary tool insert changes. This paper introduces two new parameters, namely the total energy and the total entropy of force signals, for tool condition monitoring. The correlation between the new parameters, tool wear and a wide range of cutting conditions is examined. The experimental results show that the energy of force signal can be reliably used to monitor tool flank and crater wear over a wide range of cutting conditions. However, the total entropy of forces does not appear to be sensitive to feed rate, rake angle and tool wear. The experimental results also indicate that crater wear causes an increase in the effective rake angle resulting in lower total energy of forces. For some particular shapes of worn tool, however, the crater wear results in a decreased rake angle which increases the total energy of forces. The influence of crater wear on forces and the root mean square of acoustic emission (AErms) signals is also observed in this research.