Frequency dependence of the complex dielectric constant of sodium carboxymethyl cellulose

The dielectric constant, ε′, and dielectric loss, ε″, were determined for three solid carboxymethyl cellulose samples having different levels of substitution and different degrees of polymerization over a frequency range of 0.1 – 10 000 kHz at temperatures from 10–60°C. In contrast to the two relaxation processes, γ and β, previously observed in native cotton cellulose, only one relaxation process within a frequency range of 0.1 – 1 kHz was identified. It was found that the dielectric properties do not only depend on the degree of substitution, but also on the weight-average degree of polymerization and uniformity of distribution.     

Iterative interference cancellation for high spectral efficiencysatellite communications

The problem of efficient utilization of the frequency spectrum for satellite systems is investigated; one which results as a consequence of highly crowding adjacent channels. An analytical characterization of the resulting interference channel is introduced and then exploited for interference cancellation. Two classes of cancelers are investigated. The first approach does not benefit from the forward error control (FEC) coding information which limits the performance gain. This motivates the second approach where a joint implementation of interference cancellation and decoding is developed using soft-input-soft-output (SISO) modules along with the iterative structure. It is shown that iterative interference cancellation techniques can achieve significant gains compared with the single-user matched filter receiver     

Physicochemical investigation of the decomposition products of ammonium metal carboxylates: ammonium ferric citrate hydrate

The thermal decomposition up to 400 °C of ammonium ferric citrate hydrate, of unknown structure and formula weight, was studied by thermogravimetry, differential thermal analysis, infrared (IR) spectroscopy and X-ray diffractometry. The possible identities of the formula weight and the intermediate products of calcination are discussed. The results revealed that the parent material is amorphous and contains two moles of water and two moles of ammonia. Decomposition takes place via six weight-loss processes, three endothermic (90–230 °C) and three exothermic (240–298 °C), leading eventually to the formation of Fe₂O₃. The intermediate solid products are mainly unstable amorphous oxycarbonates, as indicated by X-ray and IR spectroscopies. The gas-phase decomposition products identified by IR spectroscopy are NH₃, CO₂, CO, CH₃COCH₃, CH₄ and NH₄OH. Surface area measurement and scanning electron microscopy showed that Fe₂O₃, the final product at 400 °C, hada surface area of 40 m²/g and good crystalline and porous character.     

Modification of sandy soil using water‐borne polymer

A new polymeric system has been applied for structural modification of (noncompactable) sandy soils. The system is based on a water‐borne styrene acrylic polymeric formulation (emulsion) containing varying amounts of solid polymer. The present work deals with system optimization and measurements designed to examine the effects of polymer content on hydraulic conductivity and compressive strength. Samples were prepared from prescribed amounts of polymer, water, and sand by using two different preparations methods (mixing and spraying). Measurements of hydraulic conductivity for both sets of samples were conducted in a flexible membrane test apparatus. For the first set of samples, the permeability coefficient of the sand was noted to be reduced 10‐fold (from 10^?5 to 10^?6 m s^?1) upon the incorporation of about 2% polymer. In the second set (samples prepared with the spraying method), the hydraulic conductivity was further reduced to 7.2 × 10^?7 at a polymer concentration of about 2%. Stress–strain measurements made on dry cylindrical specimens disclosed remarkable enhancement in the mechanical behavior of the system. For both types of preparation methods, the compressive strength and modulus of elasticity increased linearly with the polymer concentration in the sample. Scanning electron microscopic examination revealed that the dramatic reduction in the permeability and the improved mechanical properties are attributed to the polymer coverage of the sand particles and the development of interconnecting ties between them. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 2484–2491, 2003     

An efficient IoT based smart farming system using machine learning algorithms

Multimedia Tools and Applications - This paper suggests an IoT based smart farming system along with an efficient prediction method called WPART based on machine learning techniques to predict crop...     

Image Super Resolution and Enhancement Using E-spline

E-splines （Exponential spline） polynomials represent the best smooth transition between continuous and discrete domains. As they are constructed from convolution of exponential segments, there are many degrees of freedom to optimally choose the most convenient E-spline, suitable for a specific application. In this paper, the parameters of these E-splines were optimally chosen, to enhance the performance of image zooming and interpolation schemes. The proposed technique is based on minimizing the total variation function of the detail coefficients of the E-spline based wavelet decomposition. In zooming applications, the quality of interpolated images are further improved and sharpened by applying ICA technique to them, in order to remove any dependency. Illustrative examples are given to verify image enhancement of the proposed E-spline scheme, when compared with the existing approaches.     

Type 2 Diabetes Risk Prediction Using Deep Convolutional Neural Network Based-Bayesian Optimization

Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization. Therefore, the selection of hyper-parameters is critical in improving classification performance. This study presents Convolutional Neural Network (CNN) that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm (BOA) has been employed for hyperparameters selection and parameters optimization. Two issues have been investigated and solved during the experiment to enhance the results. The first is the dataset class imbalance, which is solved using Synthetic Minority Oversampling Technique (SMOTE) technique. The second issue is the model's poor performance, which has been solved using the Bayesian optimization algorithm. The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%, F1-score of 0.88.6, and Matthews Correlation Coefficient (MCC) of 0.88.6.     

A 0.18-/spl mu/m CMOS bioluminescence detection lab-on-chip

The paper describes a bioluminescence detection lab-on-chip consisting of a fiber-optic faceplate with immobilized luminescent reporters/probes that is directly coupled to an optical detection and processing CMOS system-on-chip (SoC) fabricated in a 0.18-/spl mu/m process. The lab-on-chip is customized for such applications as determining gene expression using reporter gene assays, determining intracellular ATP, and sequencing DNA. The CMOS detection SoC integrates an 8 /spl times/ 16 pixel array having the same pitch as the assay site array, a 128-channel 13-bit ADC, and column-level DSP, and is fabricated in a 0.18-/spl mu/m image sensor process. The chip is capable of detecting emission rates below 10/sup -6/ lux over 30 s of integration time at room temperature. In addition to directly coupling and matching the assay site array to the photodetector array, this low light detection is achieved by a number of techniques, including the use of very low dark current photodetectors, low-noise differential circuits, high-resolution analog-to-digital conversion, background subtraction, correlated multiple sampling, and multiple digitizations and averaging to reduce read noise. Electrical and optical characterization results as well as preliminary biological testing results are reported.     

A unified framework for tree search decoding: rediscovering the sequential decoder

We consider receiver design for coded transmission over linear Gaussian channels. We restrict ourselves to the class of lattice codes and formulate the joint detection and decoding problem as a closest lattice point search (CLPS). Here, a tree search framework for solving the CLPS is adopted. In our framework, the CLPS algorithm is decomposed into the preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. We argue that the forward and feedback (matrix) filters of the minimum mean-square error decision feedback equalizer (MMSE-DFE) are instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for solving underdetermined linear systems and using lattice reduction methods to diminish complexity, at the expense of a marginal performance loss. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases. The proposed generic algorithm further allows for an interesting classification of tree search decoders, sheds more light on the structural properties of all known sphere decoders, and inspires the design of more efficient decoders. In particular, an efficient decoding algorithm that resembles the well-known Fano sequential decoder is identified. The excellent performance-complexity tradeoff achieved by the proposed MMSE-DFE Fano decoder is established via simulation results and analytical arguments in several multiple-input multiple-output (MIMO) and intersymbol interference (ISI) scenarios.