Noncoherent MT-MFSK signals with diversity reception in arbitrarily correlated and unbalanced Nakagami-m fading channels

This paper studies the performance of diversity applied to an efficient modulation/coding scheme using M-ary frequency-shift keying (MFSK) signals, with postdetection noncoherent diversity reception and combining over slow nonselective arbitrarily correlated and unbalanced Nakagami-m fading channels, in which the diversity branches can have unequal signal-to-noise ratios (SNRs), as well as different severity parameter m. This modulation/coding scheme is referred to as multiple tone MFSK (MT-MFSK) and is implemented based on balanced incomplete block design (BIB-design) from combinatorial theory. In MT-MFSK modulation, the number of tones used to represent the signals set is reduced compared with the conventional MFSK modulation, and each MT-MFSK signal is represented by a number of distinct orthogonal tones selected according to BIB-design. This mechanism drastically increase the bandwidth efficiency of the modulated signal and allows the modulator to create implicit frequency diversity. In this paper, we show that by combining the implicit frequency diversity of MT-MFSK signals with the diversity reception introduced by employing multiple receiving antennas, substantial improvements in performance can be obtained. A noncoherent square-law combining (SLC) soft-decision receiver is introduced and a union bound expression for the average symbol error probability is obtained. The effects of arbitrarily values of fading severity parameter m and the arbitrarily correlation between the unbalanced L diversity channels are considered. The system performance is compared with that of the conventional MFSK system. The results show that this modulation/coding scheme creates a multiplicative diversity and, therefore, performs better than the conventional MFSK system in terms of power and bandwidth efficiency.     

Hydrocarbon potentiality and thermal maturity of the Cretaceous rocks in Al Baraka oil field,KomOmbo basin,south Egypt

This paper aims to evaluate the hydrocarbon potentiality and thermal maturity of the Cretaceous source rocks in Al Baraka oil field in KomOmbo basin, south Egypt. To achieve this aim, geochemical analyses (TOC), Rock eval pyrolysis and vitrinite reflectance measurements (R0) were carried out on the studied rocks. The analytical results of the samples that were collected from five exploratory oil wells revealed that almost Lower Cretaceous formations (Sabaya, Abu Ballas, Six Hills and KomOmbo C, B, A) and Upper Cretaceous formations (Dakhla, Duwi, Quseir, Taref and Maghrabi) are ranged from fair to excellent source rocks for hydrocarbon generation. Oil and gas are mainly the future products of the thermally transformed organic matters within almost samples of the Cretaceous formations, where the Lower and Upper Cretaceous formations contain mixed type II/III and III kerogen besides type II kerogen in KomOmbo (B) and Dakhla formations. The thermal maturity parameters clarified that the Lower Cretaceous formations are belonged to marginally mature (in Sabaya and Abu Ballas formations), whereas the rocks of KomOmbo (B) Formation are mature source rocks and fall in the stage of oil generation and reach to the late stage of oil generation (R0?=?1.25). On the contrary the Upper Cretaceous formations are ranged from immature to marginally mature source rocks and reach only the early stage of oil generation in Maghrabi Formation. This study indicated that there is still a good chance to find oil generated from the Dakhla, Duwi, Maghrabi, Sabaya and Abu Ballas formations if buried in greater depths as well as, KomOmbo B and A intervals which are source rock potentials.     

Burial and thermal history simulation of the subsurface Paleozoic source rocks in Faghur basin,north Western Desert,Egypt: Implication for hydrocarbon generation and expulsion history

Paleozoic Zeitoun, Desouqy and Dhiffah formations represent source rocks to hydrocarbon in Faghur basin, north Western Desert, Egypt. They are characterized by a sufficient amount of organic matter belonging to kerogen type III and mixed type II/III, which are in maturation stage. A 1D-basin modeling was performed by using geological and geochemical data of the Paleozoic source rocks from five wells in Faghur basin, north Western Desert, Egypt. These data used in 1D basin modeling for constructing and understanding of burial and thermal geo-histories of Faghur basin and for simulating and predicting the timing of petroleum and expulsion for the Paleozoic source rocks in the studied wells. Burial and thermal history models indicate that the Zeitoun Formation entered onset of oil generation in the studied wells during Late Cretaceous (100.10–91.65 my) with transformation ratio (TR) 10–25, peak oil during Late Cretaceous (91.65–79.30 my) with TR 25–50 and late oil stage at Late Cretaceous (79.30 my-0) to present day with TR 50–60.45. Desouqy Formation entered onset of oil generation also during Late Cretaceous (94.43–73.60 my) with TR 10–25 in the studied wells, peak oil during Late cretaceous (73.60–62.40 my) with TR 25–50 and Late oil stage during Late Cretaceous to present day (62.40 my-0) with TR 50–61.82. Dhiffah Formation entered onset of oil generation in the studied wells during Early to Late Cretaceous (102.11–92.27 my) with TR 10–25, peak oil during Late Cretaceous (92.27–86.40 my) with TR 25–50 and late oil stage at Late Cretaceous to present day (86.40 my-0) with TR 50–67.27. No cracking oil to gas in the studied Paleozoic source rocks in the studied wells. These basin modeling results also suggest that the Paleozoic source rocks act as an effective source rock where a significant amount of petroleum is expected to be generated and expelled to any nearby prospect reservoir rocks in the Faghur basin.     

Deliverable‐power dependence on distribution‐line resistance and number of loads in low‐voltage DC distribution system

In this paper, we show that in a low‐voltage DC distribution system the deliverable power to a load has an upper limit P_lim due to the voltage instability at the receiving ends. On the basis of the previously derived concept of P_lim, we obtain the dependence of P_lim on the distribution line resistance R. In addition, we investigate the influence of the number of loads on P_lim. The result shows that a distribution line of lower R causes P_lim to be lower. This reduction in P_lim becomes more distinct for a larger number of loads. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A novel approach to deliverable power in low‐voltage DC distribution system on the basis of voltage stability

This paper proposes that a deliverable power through a low‐voltage DC distribution system has an upper limitation. The upper limitation of the deliverable power, P_lim, is explained on the basis of a voltage instability phenomenon occurring for the load with a voltage sensitivity below 1. From theoretical‐calculation results, it is pointed out that P_lim diminishes with augment in the distribution‐line length. This phenomenon becomes more distinct for the higher distribution‐line inductance per unit length. Connection of the capacitor to the receiving end of the distribution line is discussed as a method for rising P_lim. Measurements of the voltage waveform at the load terminals successfully support P_lim derived from the theoretical calculation. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Traveling-Wave-Based Fault-Location Scheme for Multiend-Aged Underground Cable System

This paper presents a novel wavelet-based fault-location scheme for aged cable systems when synchronized digital fault recorded data are available at the two terminals of each cable. The proposed scheme estimates the fault location in multiend-aged cable systems using the theory of wavelet singularity detection as a powerful signal processing tool. The arrival of the first and second voltage traveling waves at both ends of the power cables can be identified reliably. The developed wavelet processing scheme is applied on the modal coordinates instead of the phase coordinates. The proposed scheme has the ability to eliminate the impact of the change in the propagation velocity of the traveling waves on the fault-location calculations. This will help solve the problem of cable changing parameters, especially the change of the relative permittivity of the cable with age. The method is valid even with faults that are very close to busbars. Characteristics of the proposed fault-location scheme are analyzed by extensive simulation studies using Alternative Transients Program/Electromagnetic Transients Program. The results indicate an accepted degree of accuracy for the suggested fault locator     

Effects of antimicrobial agents on the processing and performance properties of rubber material formulations with no cytotoxicity

The present work aims to develop antimicrobial rubber for safe industrial toys. For this purpose, natural rubber (NR) and synthetic rubber as styrene butadiene rubber (SBR) and ethylene propylene diene monomer (EPDM) were examined. Rubber and their ingredients as well as antimicrobial agents (doxycycline and cephalexin) were mixed in a rubber mixer. The rheological properties of compounded rubber were studied, and the curing time was determined. Mechanical properties and cytotoxicity were evaluated at optimally cured rubber compounds. Scanning electron micrographs of vulcanizates showed good dispersion of ingredients throughout the investigated matrices. Rheology study for the investigated vulcanizates in presence of tested antimicrobial species exhibited no significant change in their flow behaviors. It is significant to remember that the desired physical characteristics of rubber products, including their chemical and mechanical characteristics (elongation at break and tensile strength) enhanced when doxycycline and cephalexin are present, depending on their nature and concentration. Similar results were obtained for both the SBR and EPDM rubber vulcanizates. The cytotoxicity of the prepared vulcanizates towards human normal retina cell line (RPI-1) indicated good safety of these rubber products. Furthermore, developed rubber vulcanizates showed good antimicrobial efficacy towards the test bacteria and fungi strains.”     

Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute, making the machine learning (ML) solutions more appealing. Patients with cardiac arrhythmias can benefit from competent monitoring to save their lives. Cardiac arrhythmia classification and prediction have greatly improved in recent years. Arrhythmias are a category of conditions in which the heart's electrical activity is abnormally rapid or sluggish. Every year, it is one of the main reasons of mortality for both men and women, worldwide. For the classification of arrhythmias, this work proposes a novel technique based on optimized feature selection and optimized K-nearest neighbors (KNN) classifier. The proposed method makes advantage of the UCI repository, which has a 279-attribute high-dimensional cardiac arrhythmia dataset. The proposed approach is based on dividing cardiac arrhythmia patients into 16 groups based on the electrocardiography dataset’s features. The purpose is to design an efficient intelligent system employing the dipper throated optimization method to categorize cardiac arrhythmia patients. This method of comprehensive arrhythmia classification outperforms earlier methods presented in the literature. The achieved classification accuracy using the proposed approach is 99.8%.     

An Improved Deep Structure for Accurately Brain Tumor Recognition

Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the GLCM. Moreover, it manipulates the extraction of the additional high levels of salient features from a proposed CNN model. Finally, a fusion process has been utilized between these two types of features to form the input layer of additional proposed DNN model which is responsible for the recognition process. Two common datasets have been applied and tested, Br35H and FigShare datasets. The first dataset contains binary labels, while the second one splits the brain tumor into four classes; glioma, meningioma, pituitary, and no cancer. Moreover, several performance metrics have been evaluated from both datasets, including, accuracy, sensitivity, specificity, F-score, and training time. Experimental results show that the proposed methodology has achieved superior performance compared with the current state of art studies. The proposed system has achieved about 98.22% accuracy value in the case of the Br35H dataset however, an accuracy of 98.01% has been achieved in the case of the FigShare dataset.