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Electroencephalography (EEG) signals are usually affected by presence of missing data because of various reasons. Depending on the percentage of missing data, it affects significantly the classification accuracy which in turn affects the performance of prosthesis. Moreover, it has also been observed that there exists no universal classifier which performs best in all types of data. Therefore, in this paper, we propose a framework to employ tensor-based Canonical/Polyadiac Weighted-optmization (CP-WOPT) and Artificial Neural Network (ANN) to recover missing data and perform classification, respectively. The results of classification have been compared with established methods such as Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Logistic regression, Boosted trees, Bagged trees and k-nearest neighbor (kNN). The results indicate significant improvement in classification accuracy on complete, missing and recovered data when ANN is employed. Classifiers are applied on complete, missing and recovered data explicitly to test the performance of our framework. Results show that mean classification accuracy on complete data, missing data and recovered data was 88%, 62% and 81% respectively which shows applicability of our framework.

Thermal design and analysis of heat exchangers are predominantly conducted considering constant heat transfer coefficients. However, these vary along the length and affect the calculations of heat transfer rates and area allocations. The current paper investigates the variations in the heat transfer coefficients in plate heat exchangers (PHX), using different numerical approaches. The heat transfer coefficient is calculated at the inlet, outlet, and systematically selected intermediate points for each method. The analysis is conducted for two different systems, i.e., a laboratory-scale and an industrial scale PHX at different chevron angles. It is concluded that the effect of the variable heat transfer coefficient is more significant for the large-scale heat exchanger due to high flow rates, geometrical specifications, Reynolds number, and thermophysical properties. The deviation of the local heat transfer coefficient along the heat exchanger length is approximately 9–14% and 3–6% for industrial and laboratory scale PHX, while an area deviation of around 15% is observed.

This paper reviews the thermophysical properties of saline water correlations and data. The key parameters that influence the properties are considered, such as multi-component composition, high salinity, temperature, and pressure. Since the thermodynamic properties are reviewed in part I of the paper, this part (# II) focuses on the thermophysical properties involving viscosity, surface tension, electrical conductivity, thermal conductivity, osmotic coefficient, activity coefficient, and thermal expansivity. The properties are comprehensive to include all saline water types, i.e., brackish water, seawater, high saline water from basins, lakes, produced water from oil and gas hydraulic fracturing, and so on. The correlations are summarized in tabular forms and assessed based on their accuracy against available experimental data. Besides, guidelines for choosing some correlations are also discussed. Since the thermal conductivity has no multi-component model, a novel and straightforward model is proposed with excellent accuracy.

The concept of non-uniform heat flux distributions has emerged because of its potential to make the design of thermal systems more flexible. Therefore, the current study highlights the impact of non-uniform heat flux distributions on the thermal characteristics of a high Prandtl number fluid for forced convective laminar flow regime in a horizontal pipe. The steady-state 2-D simulations have been employed using ANSYS Fluent. The variations in heat flux distributions as a wall boundary condition are systematically analyzed while keeping the total heat transfer constant. The results obtained for various distributions are compared in terms of a dimensionless maximum wall temperature (hot spot), local and average Nusselt numbers, and entropy generation rate. The analysis showed that the heat flux distributions significantly affected the heat transfer pattern. It was found that the hot spot temperature was lower for the descending heat flux boundary conditions compared to the ascending type of distributions. However, a higher entropy generation rate was observed for descending distributions as compared to ascending ones. It was also found that the ascending heat flux distributions provided higher average Nusselt number values than the descending cases of heat flux.

Heat exchangers are used to transfer energy from one medium to another and increase contact area for higher efficiency. In case of fluids, higher flow area would lead to high/low flow zones that severely affect the fluid dynamics and thermal performance. Channels are used to distribute the flow uniformly to fully utilize the whole heat exchanger area. The flow uniformity in a flow distribution manifold is dependent on several factors such as flow rate, inlet and exit locations, and the manifold and channel geometrical configuration. In the current work, flow distribution measurements were performed using a particle image velocimetry (PIV) technique in two types of rectangular manifolds. The experimental results are further verified against the results obtained from numerical modeling with similar trends. The flow distribution in U- and Z-type arrangements are evaluated and compared with ten channels incorporated in the design. It was found that the flow is more in the channels near the inlet for U-type design, while more near the outlet for the Z-type. An increase in the inlet flow rate enhances the flow distribution for the U-type while results in more maldistribution for the Z-type. For the U-type, the normalized velocity varies from 1.34 to 0.52 in a wide manifold, and between 2.82 and 0.18 for a narrow manifold. A U-type wider manifold is recommended for all conditions examined in this work since at lower flow rates, both have similar mirrored distribution, while at higher flow rates, U-type manifold has better flow distribution.

Performance is analyzed for kinetic energy variation in high velocity stream heat exchangers that are subjected to external heat transfer. Analytical solutions are obtained using the method of inverse operators. They are verified against the reported expressions in the appropriate limits for constant kinetic energy system as well as for perfectly insulated conditions. Kinetic energy decay in hot stream enhances performance that exceeds the conventional heat exchanger effectiveness. For kinetic-to-thermal energy ratio and dimensionless characteristic length constant each equaling unity on the hot side, the terminal effectiveness under balanced operation is 136% for counter-flow arrangement and 82% for parallel-flow in the absence of external heat load. On the contrary, decay on the cold side lowers performance. For unbalanced flow, kinetic energy change in the higher heat capacity rate fluid has a lesser impact on the effectiveness. Thermal interaction with the ambient generally has a deleterious effect on the hot stream effectiveness of the cryogenic system. However, the performance improves under certain conditions such that the rise in fluid temperature caused by kinetic energy deterioration promotes heat loss to the surroundings.

This study investigates the performance of a novel humidification dehumidification (HDH) desalination system integrated into a vapor compression (VC) heat pump. The integrated heat pump delivers th...

Speaker diarization system identifies the speaker homogenous regions in those set of recordings where multiple speakers are present. It answers the question ‘who spoke when?’. The data set for speaker diarization usually consists of telephone, meetings, TV/ talk shows, broadcast news and other multi-speaker recordings. In this paper, we present the performance of our proposed multimodal speaker diarization system under noisy conditions. Two types of noises comprising additive white Gaussian noise (AWGN) and realistic environmental noise is used to evaluate the system. To mitigate the effect of noise, we propose to add an LSTM based speech enhancement block in our diarization pipeline. This block is trained on synthesized data set with more than 100 noise types to enhance the noisy speech. The enhanced speech is further used in multimodal speaker diarization system which utilizes a pre-trained audio-visual synchronization model to find the active speaker. High confidence active speaker segments are then used to train the speaker specific clusters on the enhanced speech. A subset of AMI corpus consisting of 5.4 h of recordings is used in this analysis. For AWGN, the LSTM model performance improvement is comparable with Wiener filter while in case of realistic environmental noise, the LSTM model improves significantly as compared to Wiener filter in terms of diarization error rate (DER).

Exergoeconomic analysis, a simultaneous investigation of exergetic and monetary performance has attained significant attention to analyze and improve the performance of energy conversion systems. This combined analysis allows an individual audit of all the components in the system. The research is particularly useful for multi-component systems to get a better understanding of how effectively each component consumes energy and economic capital. This chapter aims to present a comprehensive theoretical framework for exergoeconomic study of thermal systems. For this purpose, the framework is initially developed for standalone heat exchangers and then extended to commercial-scale thermal desalination systems consisting of preheaters, pumps, evaporators, and compressors, etc. The exergetic and economic values of each stream in the system were evaluated using the developed framework. The sensitivity and parametric analysis of different thermodynamic and economic parameters on the system performance was conducted to study the performance variations. The presented model can be generalized for performance analysis of other systems.

For non-axisymmetric conditions, the traditional fluid mean (bulk) temperature at a tube cross section, subjected to constant heat flux, can be higher than the temperature of a point on the wall. T...

Fast and effective recommender systems are fundamental to fulfill the growing requirements of the e-commerce industry. The strength of matrix factorization procedure based on stochastic gradient descent (SGD) algorithm is exploited widely to solve the recommender system problem. Modern computing paradigms are designed by utilizing the concept of fractional gradient in standard SGD and outperform the standard counterpart. The performance of fractional SGD improves considerably by adaptively tuning the learning rate parameter. A nonlinear computing paradigm based on normalized version of fractional SGD is developed in this paper to investigate the adaptive behavior of learning rate with novel application to recommender systems. The accuracy of the proposed approach is verified through root mean square error metric by using different latent features, learning rates, fractional orders and datasets. The superiority of the designed method is validated through comparison with the state-of-the-art counterparts.

Shell-and-tube heat exchangers are frequently used in several industrial applications. A model was developed using engineering equations solver software to predict the performance of variou...

This paper introduces a novel humidification-dehumidification (HDH) system coupled with adsorption desalination (AD) system to produce freshwater as well as to obtain chilled water for an air-conditioning purpose. Two hybrid HDH-AD schemes are proposed in which the condenser of the AD system replaces the HDH heater. The difference is that the HDH inlet seawater is precooled in the AD evaporator before feeding the HDH system in Scheme # 1, while in Scheme # 2 the seawater is used to cool the adsorption process. Seawater mass flowrate and temperature, heating source mass flowrate and temperature, cycling time, and HDH mass flowrate ratio are the key parameters investigated to influence the hybrid system performance. The results exhibit that the gained output ratio (GOR) and cost values are higher in Scheme #1 (about 7.8 and 0.64 ¢/Liter, respectively). Scheme # 2 achieves an excellent GOR and cost values (about 7.6 and 0.65 ¢/Liter) with a cooling effect as a by-product (coefficient of performance (COP) is >0.45 under the same conditions of optimal GOR value). For the hybrid HDH-AD system, the HDH contribution in the total performance is vital while AD system can be used to control the HDH operating conditions.

Reverse osmosis is becoming popular for the purification of water resources e.g. sea and brackish water. However, one of the major limitations in efficient operation are the fouling of membranes and relevant technique used to inhibit scaling due to the presence of sparingly soluble salts. The occurrence of this type of fouling results in a significant increase in both operation and maintenance. This review begins by providing a general overview of membrane fouling by minerals usually found in sea and inland water resources. The paper then discusses some important aspects of the phenomena itself: different mechanisms; concentration polarization; the major types of mineral scales including their prevalence and characteristics; and consequences of fouling on membrane performance. This is followed by a discussion of the major strategies currently considered for the control and prevention of scale formation. The penultimate section discusses the drawbacks and deficiencies of current systems in operation and highlights potential future directions that need to be pursued in order to achieve overall process improvements in terms of sustainability. In particular, the need for evaluation under more realistic conditions, studying the interactions between membrane and spacer surface and foulants, and the development of environmentally benign antiscalants are stressed.

The performance of photovoltaic modules is adversely affected by an increase in photovoltaic cell temperature. Cooling of panels may lead to temperature non-uniformity in the photovoltaic panel, thus limiting the maximum efficiency of the cooled photovoltaic panel. In the current work, the design of a novel heat exchanger that can be used for uniform cooling of photovoltaic modules is presented. For this purpose, a computational fluid dynamics model has been set up. Using the model, the effects of various heat exchanger design parameters (like channel numbers, manifold width, the location of inlet/exit ports, and tapered channels) on its performance are sequentially analyzed resulting in fourteen designs. The performance is quantified by three parameters: top surface average temperature, temperature non-uniformity for photovoltaic module cooling quality, and the heat transfer per unit pumping power. The resulting optimized design is found to be a novel V-shaped heat exchanger design for the photovoltaic module cooling. It has a lower average temperature and temperature non-uniformity, smaller hotspots, and lower pumping power. The optimal design is further examined using experimental particle image velocimetry measurements.

This paper evaluates an optimal airside thermal-hydraulic performance of compact heat exchangers. Seventy-five airside surfaces have been chosen, i.e. standard reference of Kays and London, to represent louver-fin, strip-fin, wavy-fin, plain-fin, pin-fin, finned circular tubes and finned flat tubes. A robust evaluation method is implemented by an estimation of the heat transfer rate per unit pumping power with and without considering the heat exchanger compactness. Experimental data of Colburn j-factor and Fanning friction factor (f) are used to estimate both the heat transfer rates and the friction power, respectively. The results demonstrate that strip-fin surface 1/10-27.03 shows an optimal heat transfer values per unit friction power when the compactness is taken into consideration. Nonetheless, pin-fin surface PF-4(F) shows an optimal heat transfer rate per pumping power when neglecting the importance of the compactness. The geometries having an optimal thermal-hydraulic performance for each airside type (with or without considering the compactness) are recommended as benchmarks to assess the performance of similar airside surfaces.

The trend of applying mathematical foundations of fractional calculus to solve problems arising in nonlinear sciences, is an emerging area of research with growing interest especially in communication, signal analysis and control. In the present study, normalized fractional adaptive strategies are exploited for automatic tuning of the step size parameter in nonlinear system identification based on Hammerstein model. The brilliance of the methodology is verified by mean of viable estimation of electrically stimulated muscle model used in rehabilitation of paralyzed muscles. The dominance of the schemes is established by comparing the results with standard counterparts in case of different noise levels and fractional order variations. The results of the statistical analyses for sufficient independent runs in terms of Nash-Sutcliffe efficiency, variance account for and mean square error metrics validated the consistent accuracy and reliability of the proposed methods. The proposed exploitation of fractional calculus concepts makes a firm branch of nonlinear investigation in arbitrary order gradient-based optimization schemes.

This work focuses on proposing generalized air-side thermal-hydraulic correlations for wavy-fin compact heat exchangers. The new correlations are modeled from experimental and numerical f- and j-factor data reported in the literature and presented in this paper. We have simulated twenty-one new geometries, using experimentally validated three-dimensional model implemented in ANSYS Fluent program, to obtain heat-transfer and fluid-flow characteristics of unreported geometries. Data of 50 geometries are used to propose new f and j correlations with an rms error of 9.23% and 9.90%, respectively. Testing and comparing the present correlations with those reported in the literature demonstrate that the present air-side f- and j-factor correlations are more accurate and generalized for regular wavy-fin compact heat exchangers.

While representing a class of signals in term of sparsifying transform, it is better to use a adapted learned dictionary instead of using a predefined dictionary as proposed in the recent literature. With this improved method, one can represent the sparsest representation for the given set of signals. In order to ease the approximation, atoms of the learned dictionary can further be grouped together to make blocks inside the dictionary that act as a union of small number of subspaces. The block structure of a dictionary can be learned by exploiting the latent structure of the desired signals. Such type of block dictionary leads to block sparse representation of the given signals which can be good for reconstruction of the medical images. In this article, we suggest a framework for MRI reconstruction based upon block sparsifying transform (dictionary). Our technique develops automatic detection of underlying block structure of MR images given maximum block sizes. This is done by iteratively alternating between updating the block structure of the sparsifying transform (dictionary) and block-sparse representation of the MR images. Empirically it is shown that block-sparse representation performs better for recovery of the given MR image with minimum errors.

To promote online businesses and sales, e-commerce industry focuses to fulfill users' demands by giving them top set of recommendations which are ranked through different ranking measures.Deep learning based auto-encoder models have further improved the performance of recommender systems. A state-of-the-art collaborative denoising auto-encoder (CDAE) models user-item interactions as a corrupted version of users rating inputs. However, this architecture still lacks users' ratings-trend information which is an important parameter to recommend top-N items to users. In this paper, building upon CDAE characteristics, we propose a novel users rating-trend based collaborative denoising auto-encoder (UT-CDAE) which determines user-item correlations by evaluating rating-trend(High or Low) of a user towards a set of items. This inclusion of a user's rating-trend provides additional regularization flexibility which helps to predict improved top-N recommendations. The correctness of the suggested method is verified through different ranking evaluation metrics i.e., (mean reciprocal rank, mean average precision and normalized discounted gain), for various input corruption values, learning rates and regularization parameters.Experiments on standard ML-100K and ML-1M datasets show that suggested model has improved performance overstate-of-the-art denoising auto-encodermodels.

The demand for recommender systems in E-commerce industry has increased tremendously. Efficient recommender systems are being proposed by different E-business companies with the intention to give users accurate and most relevant recommendation of products from huge amount of information. To improve the performance of recommender systems, various stochastic variants of gradient descent based algorithms have been reported. The scalability requirement of recommender systems needs algorithms with fast convergence to generate recommendations of specific items. Using the concepts of fractional calculus, an efficient variant of the stochastic gradient descent (SGD) was developed for fast convergence. Such fractional SGD (F-SGD) is further accelerated by adding a momentum term, thus termed as momentum fractional stochastic gradient descent (mF-SGD). The proposed mF-SGD method is shown to offer improved estimation accuracy and convergence rate, as compared to F-SGD and standard momentum SGD for different proportions of previous gradients, fractional orders, learning rates and number of features.

In this work, the fabrication and characterization of a dual-purpose membrane is reported: (i) oil-water separation with high efficiency, and (ii) effective and rapid photocatalytic degradation of hazardous environmental pollutants. Nanoparticles of a rare-earth oxide, cerium (IV) oxide, synthesized by a simple co-precipitation technique, were spray-coated onto stainless steel membranes to obtain a uniform coating with superwetting characteristics. The as-synthesized cerium (IV) oxide nanoparticles and its spray-coated stainless steel membrane were characterized by advanced analytical techniques. X-ray diffraction, selected area electron diffraction, and electron microscopy results of the cerium oxide particles showed a high degree of crystallinity and uniform particle size of ∼50 nm. Elemental surface analysis using X-ray photoelectron spectroscopy showed the characteristic peaks for Ce4+, thereby confirming the presence of cerium oxide nanoparticles. Contact angle measurements showed the coated membranes to be superhydrophobic (∼150°) and superoleophilic (∼0°). When used in a simple laboratory setup, the membranes were able to separate oil and water with a high efficiency (∼99%). Furthermore, the coated membrane showed enhanced photocatalytic activity under UV light irradiation resulting in the rapid degradation of organic persistent pollutants like MB dye in water. To summarize, this work presents an innovative approach in the application of multifunctional membranes for effective water treatment.

Integration of energy recovery section with thermal desalination systems improves their performance from thermodynamics, economics, and environmental viewpoints. This is because it significantly reduces input energy, heat transfer area, and capital cost requirements. Above all, the system outlet streams can achieve thermal equilibrium with the environment by supplying heat for useful preheating purposes thus reducing the environmental impacts. The plate heat exchangers are generally employed for this purpose as preheaters. The current paper presents a comprehensive investigation and optimization of these heat exchangers for thermal desalination systems applications. An experimentally validated numerical model employing Normalized Sensitivity Analysis and Genetic Algorithm based cost optimization is developed to investigate their performance at assorted operating conditions. The analysis showed that the heat transfer coefficient, pressure drop, and outlet water cost were improved by an increase in feed flow rate. However, with an increased flow rate, the comprehensive output parameter (h/ΔP) decreased due to the high degree increase in pressure drop. Moreover, an increase in the chevron angle reduced the heat transfer coefficient, pressure drop, and water cost. Finally, the optimization lowered the heat transfer area by ~79.5%, capital investment by ~62%, and the outlet cost of the cold stream by ~15.7%. The operational cost is increased due to the increased pressure drop but the overall impact is beneficial as Ctotal of equipment is reduced by ~52.7%.

An optimal assessment of heat transfer and friction power performance is investigated to address a robust method for facilitating performance evaluation of different wavy-fin arrangements. Two benchmark geometries are presented to compare the performance of all the reported wavy-fin arrangements with and without considering heat exchanger compactness. New 21 wavy-fin geometries are numerically studied to represent the unreported arrangements in the literature. The performance results of 105 geometries showed that the reference standard geometries of Kays and London could be used as benchmarks to evaluate the airside arrangements, with and without considering the compactness effect, respectively. Heat transfers versus friction power plots are found to be a useful approach for performance evaluation purpose. The surface GK2 is found to have the optimal thermal-hydraulic performance when comparing the heat exchanger compactness, whereas GI1 and GK1 might represent the geometries having optimal performances when neglecting the compactness importance.