Intelligent Estimation Research Articles

Next Generation Monitoring of SiC mosfets Via Spectral Electroluminescence Sensing

This article presents a new methodology for monitoring next generation SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> -based converters. The methodology uses the spectral distribution of electroluminescence that is emitted by the body diodes of SiC <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> s and includes information on device current as well as the junction temperature. Intelligent estimation algorithms based on artificial neural networks allow processing the extracted information to separately estimate device current and junction temperature with high bandwidth. The resulting unified monitoring of device current and junction temperature galvanically isolates the sensors via optical guides from the power module. Thus, it can be effectively integrated into future power electronic modules to replace external temperature and current sensors and enable monitoring for safe and reliable long-term operation. Previous publications successfully investigated how either temperature or current information can be extracted from the intensity of the emitted light if the other variable is known. However, they did not aim to extract both variables at the same time from one measurement. This work presents how multiple optical sensors with different wavelength sensitivities and artificial-intelligence techniques can separately extract both variables. The proposed technology is evaluated using an automotive-grade SiC power module. Its utilization for monitoring future SiC-based converters allows reducing converter size and cost while increasing reliability.

Relationship between phoneme-level spectral acoustics and speech intelligibility in healthy speech: a systematic review

ABSTRACT This study aims to systematically review original articles investigating the link between spectral acoustic measures in healthy talkers and perceived speech intelligibility, according to the PRISMA guidelines. Twenty-two studies were retained. Eighteen papers investigated vowel acoustics, one studied glides and eight articles investigated consonants, mostly sibilants. Various spectral measures and intelligibility estimates were used. The following measures were shown to be linked to sub-lexical perceived speech intelligibility ratings: for vowels, steady-state F1 and F2 measures, the F1 range, the [i]-[U] F2 difference, F0-F1 and F1-F2 differences in [è-A] and [q-è], the vowel space area, the mean amount of formant movement, the vector length and the spectral change measure; for consonants, the centroid energy and the spectral peak in the [s]-sound, as well as the steady-state F1 offset frequency in vowels preceding [t] and [d].To conclude, as speech is highly variable even in healthy adult speakers, a better understanding of the imprecisions in healthy spontaneous speech will provide a more realistic baseline for the investigation of disordered speech. To date, no acoustic measure is able to predict speech intelligibility to a large extent. There is still extensive research to be carried out to identify relevant acoustic combinations that could account for perceived speech variations (e.g. vowel and consonant reductions) and to gather normative data from a large number of healthy speakers. To that end, speech-related terms (e.g. intelligibility, comprehensibility, severity) need to be clearly defined and methodologies described in sufficient details to allow for replication, cross-comparisons/meta-analyses and pooling of data. .

Discussion of “Artificial Intelligence and Parametric Construction Cost Estimate Modeling: State-of-the-Art Review” by Haytham H. Elmousalami

Discussion of “Artificial Intelligence and Parametric Construction Cost Estimate Modeling: State-of-the-Art Review” by Haytham H. Elmousalami

Closure to “Artificial Intelligence and Parametric Construction Cost Estimate Modeling: State-of-the-Art Review” by Haytham H. Elmousalami

Closure to “Artificial Intelligence and Parametric Construction Cost Estimate Modeling: State-of-the-Art Review” by Haytham H. Elmousalami

Glimpse-based estimation of speech intelligibility from speech-in-noise using artificial neural networks

While human listeners can, to some extent, understand the information conveyed by the speech signal when it is mixed with noise, traditional objective intelligibility measures usually fail to operate without a priori knowledge of the clean speech signal. This hence limits the usability of those measures in situations where the clean speech signal is inaccessible. In this paper a glimpse-based method is extended to make speech intelligibility predictions directly from speech-plus-noise mixtures. Using a neural network, the proposed method estimates the time-frequency regions with a local speech-to-noise ratio above a given threshold – known as glimpses – from the mixture signal, instead of separately comparing the speech signal against the noise signal. The number and locations of the glimpses can then be used to produce an intelligibility score. In Experiment I where listener intelligibilities were measured in one stationary and nine fluctuating noise maskers, the predictions produced by the proposed method were highly correlated with the subjective data, with correlation coefficients above 0.90. In Experiment II, with the same neural network trained on normal natural speech as in Experiment I, the proposed method was used to predict the intelligibility of speech signals modified by intelligibility-enhancement algorithms and synthetic speech. The method can still maintain its predictive power by demonstrating a similar performance to its intrusive counterpart with an overall correlation coefficient of 0.81, which is superior to many modern traditional measures evaluated under the same conditions. Therefore, the proposed method can be used to estimate speech intelligibility in place of traditional measures in conditions where their capacity falls short.

Impacting Culture Through Security Cooperation

JP 3-20 defines Security Cooperation (SC) as all Department of Defense DOD) interactions, programs, and activities with foreign security forces (FSF) and their institutions to build relationships that help promote US interests; enable partner nations (PNs) to provide the US access to territory, infrastructure, information, and resources; and/or to build and apply their capacity and capabilities consistent with US defense objectives. This essay examines security cooperation, how security cooperation works and the impact the US Security Cooperation (SC) program has on culture. In order to do this, we examine activities inherent in Security Cooperation and how the entire process works, including key driving doctrine, from end state to genesis. After we examine activities inherent in Security Cooperation and how the entire process works, we then assess impactby examining aspects such as: how we measure success; regional access gained; partnerships; doctrine and intent. This essay takes a unique approach in that it works backwards from end state objectives of noted action on the ground to genesis with the President’s National Security Strategy guided by the National Intelligence Estimate and National Security Council, concluding with my overall assessment of the impact of the program.Keywords: Security Cooperation, Theater Strategies, Theater Campaign Plan, Defense Security Cooperation Agency (DSCA), Joint Strategic Capabilities Plan (JSCP), Strategic Direction, National Security Strategy (NSS), National Defense Strategy (NDS), Comprehensive Joint Assessment (CJA), Joint Strategy Review

Estimating the reduced benefit of infant-directed speech in cochlear implant-related speech processing

Caregivers modify their speech when talking to infants, a specific type of speech known as infant-directed speech (IDS). This speaking style facilitates language learning compared to adult-directed speech (ADS) in infants with normal hearing (NH). While infants with NH and those with cochlear implants (CIs) prefer listening to IDS over ADS, it is yet unknown how CI processing may affect the acoustic distinctiveness between ADS and IDS, as well as the degree of intelligibility of these. This study analyzed speech of seven female adult talkers to model the effects of simulated CI processing on (1) acoustic distinctiveness between ADS and IDS, (2) estimates of intelligibility of caregivers’ speech in ADS and IDS, and (3) individual differences in caregivers’ ADS-to-IDS modification and estimated speech intelligibility. Results suggest that CI processing is substantially detrimental to the acoustic distinctiveness between ADS and IDS, as well as to the intelligibility benefit derived from ADS-to-IDS modifications. Moreover, the observed variability across individual talkers in acoustic implementation of ADS-to-IDS modification and the estimated speech intelligibility was significantly reduced due to CI processing. The findings are discussed in the context of the link between IDS and language learning in infants with CIs.

CIA support to policymakers: the 2007 National Intelligence Estimate on Iran’s Nuclear Intentions and Capabilities

‘We judge with high confidence that in fall 2003, Tehran halted its nuclear weapons program.’ So declared the opening words of the key judgments of the November 2007 national intelligence estimate ...

Tradecraft, the PIAB, and the 2007 NIE on Iran’s Nuclear Intentions and Capabilities

ABSTRACT The Office of the Director of National Intelligence’s Office of Analytic Integrity and Standards (AIS) conducted a rigorous evaluation of the tradecraft underlying the 2008 National Intelligence Estimate (NIE) on Iran’s Nuclear Intentions and Capabilities. AIS’s director and senior officials from several IC elements briefed the President’s Intelligence Advisory Board (PIAB) on the findings in order to demonstrate that the NIE manifested the Intelligence Community’s (IC’s) improved tradecraft capabilities. The PIAB’s response, however, was to criticize NIE’s substance and hence minimize the salience of its superior tradecraft. The result was a missed opportunity to bolster the IC’s reputation.

Study on electrochemical principle and characteristic curve of nickel hydrogen battery for mine

As a kind of high-energy secondary battery, mining Ni MH battery is very suitable for mine backup power because of its advantages of high capacity, high power, no pollution, long cycle life, strong charging and discharging ability and high safety. This paper mainly introduces the electrochemical reaction of Ni MH battery under normal operation, overcharge and over discharge, introduces the types and components of Ni MH battery, describes the change curve of charging and discharging terminal voltage with time under different conditions, analyzes the self discharge situation of Ni MH battery under different conditions, and analyzes the cycle life and safety of Ni MH battery. The software and hardware design of battery intelligent management and SOC estimation analysis provide the basic basis.

Analysis of the cost factors on E-government software cost using fuzzy decision making system

The reasonable cost budget of the e-government scheme can effectively promote the construction of the digital government. To analyze the cost impact components of the e-government system and find out the impact factor model works in China, this paper reviews relevant literature on software cost impact factors and proposes the impact factors model based on COCOMO II. Besides, combined with the actual construction of digital government and specific cases, this paper analyzes the mechanism of each impact factor in detail. The model can be used to guide the cost estimation of e-government software in China, especially with artificial intelligence estimation method. An enhanced decision theory of theory based on fuzzy set has been adopted for analysis of cost factor on E-government software cost.

Remaining Useful Life Estimation for Prognostics of Lithium-Ion Batteries Based on Recurrent Neural Network

Prognostic and condition-based maintenance of lithium-ion batteries is a fundamental topic, which is rapidly expanding since a long battery lifetime is required to ensure economic viability and minimize the life cycle cost. Remaining useful life (RUL) estimation is an essential tool for prognostic and health management of batteries. In this article, a hybrid approach based on both condition monitoring and physic model is presented to improve the accuracy and precision of RUL estimation for lithium-ion battery. An artificial intelligence estimation method based on recurrent neural network (RNN) is integrated with a state-space estimation technique, which is typical of filtering-based approach. The state-space estimation is used to generate a big dataset for the training of the RNN. Some additional deep layers are used to improve the prediction of nonlinear trends (typical of batteries), while the performance optimization of the RNN is ensured using a genetic algorithm. The performances of the proposed method have been tested using a battery degradation dataset from the data repository of Prognostics Center of Excellence at NASA. Two different degradation models are compared, the widely known empirical double exponential model and an innovative single exponential model that allows to ensure optimal performance with fewer parameters required to be estimated.

A Novel Polymorphic Topology with Hybrid Control Strategy Based LLC Resonant Converter for Ultra-Wide Input Voltage Range Applications

To realize effective utilization of renewable energy sources, a novel polymorphic topology with hybrid control strategy based LLC resonant converter was analyzed and designed in this paper. By combining the merits of a full bridge LLC resonant converter, three-level half bridge LLC resonant converter, and variable frequency control mode, the converter realizes an intelligent estimation of input voltage by automatically changing its internal circuit topology. Under this control strategy, different input voltages determine different operation modes. This is achieved in full bridge LLC mode when the input voltage is low. If the input voltage rises to a certain level, it operates in three-level half bridge LLC mode. These switches are digital and entirely carried out by the DSP (Digital Signal Processor), which means that an auxiliary circuit is unnecessary, where a simple strategy of software modification can be utilized. Experimental results of a 500W prototype with 100V~600V input voltage and full load efficiency of up to 92% are developed to verify feasibility and practicability. This type of converter is suitable for applications with an ultra-wide input voltage range, such as wind turbines, photovoltaic generators, bioenergy, and other renewable energy sources.

Artificial Software Complex "Artificial Head". Part 2 Evaluation of Speech Intelligibility in Classrooms

Experimental studies of the use of the developed hardware and software tool “Artificial Head” for two-channel estimation of the intelligibility of the speech distorted by reverberation have been performed in this paper. The peculiarity of this complex is that it contains electro-acoustic equipment of different quality, including household appliances with mediocre quality features.In the first stage of this evaluation, the response of the room to the test signal is recorded. The test signal was based on the maximum-length sequence (mls) which is a periodic two-level signal of length 216, which corresponds to a signal length of 1.49 s at a sampling rate of 44.1 kHz. This mls-sequence was repeated 17 times during radiation and averaging the last 16 bursts of the cross-correlation estimates have been made to increase the signal-to-noise ratio by 12 dB in the calculation of the room impulse response.The calculation of the cross-correlation function of the response and the test signal was performed in the second stage, while the correction of the frequency characteristic of the measuring path was performed by it dividing by the amplitude-frequency characteristic of the loudspeaker-microphone subsystem. To improve the accuracy of the calculations, the result of such division was multiplied by the regularization factor in the form of a Hann window.In the third stage, the modulation coefficients were calculated according to the Schroeder formula, using the room impulse response estimate. In the fourth, last step, speech intelligibility was evaluated by a modulation or formant-modulation method. The results of the speech intelligibility evaluation in two lecture rooms of small and medium size showed that the speech intelligibility in the middle of the room can be less than that near the wall of the room. These results are in line with the results of previous studies, where speech intelligibility has been evaluated by objective and subjective methods for another lecture room. It should be noted that although the estimates of the widely used C50 coefficient are consistent with the estimates of speech intelligibility, the phenomenon of increasing speech intelligibility near the walls of the room is more pronounced when applying the speech intelligibility estimates.The results presented in this paper indicate that the usefulness of early reflections in the room is different in different parts of the room. This important fact must be taken into account both in the design and the reconstruction of the lecture rooms.

Intelligent Analysis of the Ecological State of Environment with Application of Distributed Expertise (on the Example of Bryansk Region)

The paper considers the problem of assessing the ecological state of the environment in the region. An approach to the intelligent analysis and estimation of anthropo-technogenic pollution of a territory with the application of integral indicators which take into account environmental pollution is proposed. To estimate the integral indicator parameters, distributed group expertise technology is used, supporting a mechanism for control of expert estimates consistency, taking into account experts’ competency in the relevant subject areas. Using the proposed approach, the problem of risk assessment of environmental impact of chemical air pollutants has been solved. Methods for control of expert estimates consistency based on the procedure of feedback with experts made it possible to increase the reliability of evaluation results and also to decrease the influence of a random expert error on the final assessment. The obtained aggregated risk estimates were used to construct, calculate and visualize the integral indicator of radioactive and chemical contamination of the districts of Bryansk region.

Narcissism and intelligence among couples: Why are narcissistic women perceived as intelligent by their romantic partners?

The compatibility between partners in romantic relationships has been found for various characteristics, including intelligence. Theoretically, this phenomenon implies that people are able to discern the intelligence of themselves and others. In practice, however, the accuracy of such estimations is influenced by various factors, such as personality traits. Grandiose narcissism has been found to be the strongest personality predictor of self-overestimated intelligence, however, it remains to be determined whether the self-perceived bias generalises to people close to the narcissist, such as their romantic partners. In the current study, in a sample of 150 heterosexual couples, we examined whether grandiose narcissism was associated with self and partner's estimation of intelligence. Additionally, we measured participants' objective intelligence (Raven's test) and relationship satisfaction. First, we found that narcissism was associated with the overestimation of intelligence. Second, narcissistic women overestimated the intelligence of their partners. Furthermore, narcissistic women were perceived as highly intelligent by their partners, even after controlling for objective intelligence. Finally, we found support for assortative mating for narcissism. Thus, intelligence seems to be an important attribute in the way how narcissistic women perceive their partners, as well as how partners view the intelligence of narcissistic women.

Using artificial neural networks for the intelligent estimation of selectivity index and metallurgical responses of a sample coal bioflotation by rhamnolipid biosurfactants

ABSTRACT The present study investigated the effects of rhamnolipid (RL) biosurfactant on the flotation performance of a coal sample. The significance of the effect of RL on the system responses, including ash content, coal recovery, yield and separation efficiency, and process kinetics and selectivity, was statistically assessed using One-Way Analysis of Variance (ANOVA) methodology. The ANOVA results revealed that adding RL to the system significantly challenged the studied metallurgical aspects. Briefly, RL biosurfactant depressed coal flotation through physical interaction with the surface of coal particles through chemical bonding between the carboxyl group in the RL structure with those on the surface of coal particles. The potential mechanisms involved were schematically proposed. The correlation between the condition of RL addition and process responses was modeled using the Artificial Neural Network (ANN) approach. Rested in the mean squared error (MSE), root mean squared error (RMSE), and percentage error as the measures of model accuracy, the Levenberg-Marquardt algorithm (LMA) with [7–16-1] structure was found to be the most reliable algorithm to predict the process response. As evidenced, the correlation coefficient values of test data were 98.09%, 96.93%, 98.37%, 98.46%, 99.50%, and 97.37% for ash content, coal recovery, yield, separation efficiency, the rate constant, and selectivity index, respectively. These values confirmed that the process could be simulated using the ANN method with an appropriate structure.

Bringing prevost's sign into the third dimension: Artificial intelligence estimation of conjugate gaze adjusted length (CGAL) and correlation with acute ischemic stroke.

Conjugate gaze deviation is associated with acute ischemic stroke (AIS), although previously only measured on a 2D plane. The current study evaluates 3D imaging efficacy to assess conjugate gaze deviation and correlate direction and strength of deviation to neuro-clinical findings.A retrospective analysis of 519 patients who had CT scans for suspected AIS at our institution. Direction and angle of eye deviation were calculated based on 2D axial images. Volumetric reconstruction of CT scans allowed for calculation of 3D conjugate gaze adjusted length (CGAL). Angle, direction, and vector strength of both 2D and 3D scans were calculated by an artificial intelligence algorithm and tested for agreement with hemispheric ischemia location. CGAL measurements were correlated to NIHSS scores. Follow up MRI data was used to evaluate the sensitivity and specificity of CGAL in the identification of AIS.The final analysis included 122 patients. A strong agreement was found between 3D gaze direction and hemispheric ischemia location. CGAL measurements were highly correlated with NIHSS score (r = .72, P = .01). A CGAL >0.25, >0.28, and >0.35 exhibited a sensitivity of 91%, 86%, and 82% and specificity of 66%, 89%, and 89%, respectively, in AIS identification. A CGAL >0.28 has the best sensitivity-specificity balance in the identification of AIS. A CGAL >0.25 has the highest sensitivity.Given CED's correlation with NIHSS score a 1/4 deviation in the ipsilateral direction is a sensitive ancillary radiographic sign to assist radiologists in making a correct diagnosis even when not presented with full clinical data.

Estimation of Cognitive Performance Based on Premorbid Intelligence in Parkinson's Disease.

Background:The estimation of premorbid intelligence (PI) is needed for an accurate diagnosis.Objective:This study aimed to estimate the cognitive performance taking into account the PI in Parkinson’s disease (PD) compared to healthy controls (HC); and to analyze the discrepancies between the current and the predicted cognitive performance based on the PI.Method:Semantic fluency, verbal and visual memory, and executive functions were assessed in 39 PD and 162 HC. A linear regression model was used to analyze the discrepancies between the predicted cognitive performance and the current raw scores through PI variables (Word Accentuation Test (WAT), Pseudo-Words (PW) Reading subtest from PROLEC-R, age, and years of education). ROC analyses were performed to assess their diagnostic properties.Results:Significant differences were found in the raw cognitive scores between patients and HC [semantic fluency (t = 6.07; p < 0.001), verbal memory (t = 6.63; p < 0.001), and executive functions (t = 2.57; p = 0.013), and in visual memory (t = 1.97; p = 0.055 marginally significant)]. Compared to HC, PD patients presented higher discrepancies between the predicted cognitive performance and the raw scores in semantic fluency, verbal memory, visual memory, executive functions (AUC = 0.78, 0.78; 0.64, 0.61, respectively).Conclusion:The magnitude of the discrepancies scores between the current and the predicted cognitive performance based on PI indicates the presence of cognitive decline in the specific cognitive domain in PD patients. This study underlines the usefulness of premorbid measures and variables, such as WAT, PW, age, and years of education, to more accurately estimate the cognitive performance in PD.

Advanced Control for Electric Drives: Current Challenges and Future Perspectives

In the Special Issue “Advanced Control for Electric Drives”, the objective is to address a variety of issues related to advances in control techniques for electric drives, implementation challenges, and applications in emerging fields such as electric vehicles, unmanned aerial vehicles, maglev trains and motion applications. This issue includes 15 selected and peer-reviewed articles discussing a wide range of topics, where intelligent control, estimation and observation schemes were applied to electric drives for various applications. Different drives were studied such as induction motors, permanent magnet synchronous motors and brushless direct current motors.