Hard Red Spring wheat/C-TRIM 20 bread: Formulation,processing and texture analysis

C-TRIM, a β-glucan-rich fraction, was added to Hard Red Spring wheat (HRSW) flour to increase soluble fiber content of bread, and to obtain a minimum of 0.75 g/bread serving (0.75 g/30 g or 2.5%) required by FDA for health claim. Three treatments or blends FGT0 (100% wheat flour – control), FGT1 (58% flour, 25% gluten and 17% C-TRIM) and FGT2 (60% flour, 22.5% gluten, and 17% C-TRIM) were used in the study. The total amount of soluble fiber from C-TRIM in FGT1 and FGT2 was 4.07–4.17% which was more than the amount required by FDA. The presence of C-TRIM increased both, the Farinograph water absorption and the arrival time. The dough mixing tolerance index (MTI) was also increased by C-TRIM. The FGT1 had higher stability than FGT2, whereas, the loaf volume of FGT1-B was also significantly higher than FGT0-B control and FGT2-B bread. The DSC results indicated that the amount of freezable-water in C-TRIM treated bread (FGT1-B and FGT2-B) was significantly higher than the control wheat flour bread (FGT0-B). This may be attributed to the higher amount of water absorbed by C-TRIM during bread dough (FGT1-D and FGT2-D) preparation and trapped or bound within the bread matrix after baking as compared to the control. After storage of FGT0-B, FGT1-B, and FGT2-B breads 2, 5, and 7 days storage at 25 °C, 4 °C, and −20 °C, the texture of bread were measured with a Texture Analyzer and the data analyzed statistically. The FTG0-B control bread firmness was significantly higher than FGT1-B and FGT2-B C-TRIM treated breads after 7 days storage at 25 °C. The amount of 0.1 M acetic acid-extractable protein was lower in FGT1-B than the control wheat flour (FGT0-B) sample. In addition, more protein was extracted at pH 7.0 than pH 4.5 because of less charges at neutral pH than pH 4.5. The free zone capillary electrophoresis analysis showed obvious differences in the protein charge and size between the dough and bread.     

The economic design of cumulative sum charts used to maintain current control of non-normal process means

This paper proposes a method for the economic design of cusum charts to maintain the current control of the non-normal process means. The economic design involves the determination of the design parameters that minimize a relevant cost function. An expression for the expected loss-cost function for the process is defined. An algorithm for near-optimal determination of the design parameters is presented. A computer program is designed for the application of the algorithm, and deriving the values of the design parameters and loss-cost function of an economic design of cusum chart to control non-normal process means. Also a numerical example is provided. Finally, a simplified scheme, which would be appliable at the workshop level is presented.     

Synthesis and Time Partitioning for Reconfigurable Systems

This paper aims to introduce a time partitioning algorithm which is an important step during the design process for fully reconfigurable systems. This algorithm is used to solve the time partitioning problem. It divides the input task graph model to an optimal number of partitions and puts each task in the appropriate partition so that the latency of the input task graph is optimal. Also a part of this paper is consecrated for implementation of some examples on a fully reconfigurable architecture following our approach.     

CGAM: A community and geography aware mobility model

The advances of localization‐enabled technologies have led to huge volumes of large‐scale human mobility data collected from Call Data Records (CDR), Global Positioning System (GPS) tracking systems, and Location Based Social networks (LBSN). These location data that encompass mobility patterns could generate an important value for building accurate and realistic mobility models and hence important value for fields of application including context‐aware advertising, city‐wide sensing applications, urban planning, and more. In this paper, we investigate the underlying spatio‐temporal and structural properties for human mobility patterns, and propose the Community and Geography Aware Mobility (CGAM) model, which characterizes user mobility knowledge through several properties such as home location distribution, community members' distribution, and radius of gyration. We validate the CGAM synthetic traces against real‐world GPS traces and against the traces generated by the baseline mobility model SMOOTH and assess that CGAM is accurate in predicting the performance of flooding‐based and community‐based routing protocols.     

Data traffic‐based analysis of delay and energy consumption in cognitive radio networks with and without resource reservation

A new opportunistic cross‐layer MAC protocol involving channel allocation and packet scheduling for cognitive radio networks is proposed. Cognitive radio allows secondary users (SUs) to exploit the available portions of the licensed spectrum bands without interfering with primary users. In particular, we consider a cognitive radio system, where SUs are equipped with two transceivers: a control transceiver and a software‐defined radio transceiver. Data traffic characteristics of SUs are considered to ameliorate system performance. So, we propose a mechanism of resource reservation to improve QoS requirements that favors successful SUs to transmit data during x time slots without interfering with primary users. The key novelty of this paper is giving priority for SUs with important data traffic and which frequently solicits data channels to transmit for the remaining time of the ongoing time slot and for the next time slots directly after checking the channel availability. We develop a new analytical model to evaluate delay parameter for two scenarios with and without resource reservation and we then investigate the impact of those scenarios on the energy consumption. We show through simulations that cognitive radio performances increase noticeably with the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

Environmental investigation using geophysical data at East Sadat City,Egypt

Three geophysical techniques such as resistivity, seismic refraction, and GPR have been applied to delineate the depth to the groundwater surface, subsurface stratigraphy and subsurface structures which control the configuration and distribution of the groundwater aquifer. Five vertical electrical sounding (VES) were measured by using Syscal-R2 instrument of electrode separation ranging from AB/2?=?1–500?m to reach depth of investigation about 150?m. The results of quantitative interpretation of the VES data indicate that the subsurface sequence composed of six geoelectric units; the first unit is characterized by resistivity values up to 2007?Ohm.m corresponding to sand & gravel and thickness up to 1.2?m. The second geoelectric unit is corresponding to sandy clay which exhibits resistivity up to 235?Ohm.m and depth up to 1.2?m. The third geoelectric unit is characterized by resistivity values up to 1483?Ohm.m corresponding to dry sand which of depth up to 2.6?m. The fourth geoelectrical unit consists of sand saturated with ground water and exhibits resistivity values ranging from 20.2 to 52.9?Ohm.m and depth ranging from 7 to 16.8?m. The fifth geoelectrical unit reveals resistivity values ranging from 7 to 32.6?Ohm.m and consists of sandy clay saturated with groundwater of depth up to 111?m overlaying the sixth unit which reached to depth up to 165?m and characterized by resistivity values ranging from 54 to 91?Ohm.m corresponding to sandstone saturated with ground water. Five shallow seismic refraction spreads of geophone spacing 4?m were measured to investigate the subsurface sequence, where the results of interpretation indicate that the subsurface section consists of three seismic layers; the first layer is unsaturated overburden with seismic velocity range from 280 to 770?m/s and thickness reach about 6?m. The second layer is sand saturated with ground water with velocity range from 760 to 1300?m/s and maximum thickness of about 7?m overlaying the third layer reached to depth up to 24?m and corresponding sandy clay saturated with groundwater with seismic velocity range from 1130 to 2260?m/s. Five GPR profiles are measured using MALA RAMAC GPR System with a Rough Terrain Antenna (RTA) system of central frequency of 100?MHz. The interpretation of GPR data indicate that the expected water table ranging from 8?m to 11?m in the study area. Interpretation of the obtained results and correlation with the available geological and different geophysical data revealed that, the depth to the groundwater table of the investigated area ranges between 7 and 16.8?m.     

Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions

Early detection of melanoma remains a daily challenge due to the increasing number of cases and the lack of dermatologists. Thus, AI-assisted diagnosis is considered as a possible solution for this issue. Despite the great advances brought by deep learning and especially convolutional neural networks (CNNs), computer-aided diagnosis (CAD) systems are still not used in clinical practice. This may be explained by the dermatologist’s fear of being misled by a false negative and the assimilation of CNNs to a “black box”, making their decision process difficult to understand by a non-expert. Decision theory, especially game theory, is a potential solution as it focuses on identifying the best decision option that maximizes the decision-maker’s expected utility. This study presents a new framework for automated melanoma diagnosis. Pursuing the goal of improving the performance of existing systems, our approach also attempts to bring more transparency in the decision process. The proposed framework includes a multi-class CNN and six binary CNNs assimilated to players. The players’ strategies is to first cluster the pigmented lesions (melanoma, nevus, and benign keratosis), using the introduced method of evaluating the confidence of the predictions, into confidence level (confident, medium, uncertain). Then, a subset of players has the strategy to refine the diagnosis for difficult lesions with medium and uncertain prediction. We used EfficientNetB5 as the backbone of our networks and evaluated our approach on the public ISIC dataset consisting of 8917 lesions: melanoma (1113), nevi (6705) and benign keratosis (1099). The proposed framework achieved an area under the receiver operating curve (AUROC) of 0.93 for melanoma, 0.96 for nevus and 0.97 for benign keratosis. Furthermore, our approach outperformed existing methods in this task, improving the balanced accuracy (BACC) of the best compared method from 77% to 86%. These results suggest that our framework provides an effective and explainable decision-making strategy. This approach could help dermatologists in their clinical practice for patients with atypical and difficult-to-diagnose pigmented lesions. We also believe that our system could serve as a didactic tool for less experienced dermatologists.     

On the Barbalat lemma extension for the generalized conformable fractional integrals: Application to adaptive observer design

The Barbalat-type lemma for the generalized conformable fractional-order derivative is examined in this work. An adaptive observer design is presented as an application to validate such proposed theory.     

Stability of conformable stochastic systems depending on a parameter

In this work, we study the almost sure exponential stability ( A.S.E.S ) and the exponential stability in p-th moment ( E.S.P.M ) of conformable stochastic systems depending on a parameter (CSSP) by using the Lyapunov methods and the classical stochastic analysis techniques. In the last section, we apply the main result for an illustrative example.