Earthquake onset detection using spectro-ratio on multi-threshold time–frequency sub-band

Automatic onset detection and picking algorithm has been proposed by applying the spectro-ratio on time–frequency sub-band. The proposed algorithm does not need any parameter settings as it will work on data generated by either short or very broad band seismometers. Our algorithm is applied on local events from Cairo region recorded by three stations of the Egyptian National Seismic Network (ENSN). Maximum standard deviation is observed to be 0.113 s of the corresponding manual picks made by analysts.     

Extended Kalman filter based speeds estimation of series-connected five-phase two-motor drive system

The multi-phase machines enables independent control of a few number of machines that are connected in series in a particular manner, and the supply is fed from a single voltage source inverter (VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases. The number of series-connected machines is a function of the phase number of VSI. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an EKF-based sensorless control of vector controlled series-connected two-motor five-phase drive system with current control in the stationary reference frame. Results, obtained with fixed voltage and fixed frequency supply fed and hysteresis current control, is presented for various operating conditions on the basis of simulation. The purpose of this paper is to report first time, the simulation results on a sensorless control of a five-phase two-motor series-connected drive system using EKF estimator.     

Design and characterization of coherent integrated fiber-optic imaging probes

An integrated fiber-optic probe comprising a short length of multimode fiber that is fusion spliced to a monomode optical fiber has been fabricated for imaging and nonimaging applications. The fiber probe, typically 250 μm in diameter, can deliver a focused Gaussian spot approximately 25 μm in diameter at a distance of approximately 500 μm from the tip. Two off-the-shelf graded-index multimode fibers have been used in the fabrication of imaging and nonimaging probes. These integrated probes have considerably improved the spatial resolution of backscatter lensless fiber probes being utilized in the dynamic light-scattering characterization of colloidal suspension.     

Epidemiology and ethics: the perspective of the Third World

The relation of epidemiology and ethics is discussed from a Third World perspective, including the following issues: the structure and dynamics of a Third World Society; the nature of the relationship between the First World "islanders" in the Third World and their counterparts in the First World, and between the "islanders" and their fellow citizens; the inner dynamics of Third World researchers; the different knowledge systems; and the role of institutions in the Third World and the First World.     

Alpha Fusion Adversarial Attack Analysis Using Deep Learning

The deep learning model encompasses a powerful learning ability that integrates the feature extraction, and classification method to improve accuracy. Convolutional Neural Networks (CNN) perform well in machine learning and image processing tasks like segmentation, classification, detection, identification, etc. The CNN models are still sensitive to noise and attack. The smallest change in training images as in an adversarial attack can greatly decrease the accuracy of the CNN model. This paper presents an alpha fusion attack analysis and generates defense against adversarial attacks. The proposed work is divided into three phases: firstly, an MLSTM-based CNN classification model is developed for classifying COVID-CT images. Secondly, an alpha fusion attack is generated to fool the classification model. The alpha fusion attack is tested in the last phase on a modified LSTM-based CNN (CNN-MLSTM) model and other pre-trained models. The results of CNN models show that the accuracy of these models dropped greatly after the alpha-fusion attack. The highest F1 score before the attack was achieved is 97.45 And after the attack lowest F1 score recorded is 22%. Results elucidate the performance in terms of accuracy, precision, F1 score and Recall.     

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

Laser-treated austenitic steel and nickel alloy for human implants

The recent research in biocompatible materials has been useful in replacing and supporting the fractured natural human bones/joints. Under some condition, negative reaction like release of ions from the bare metal toward the human body fluid leads to corrosion. In this proposed research paper, the biocompatibility of the laser surface-modified austenitic stainless steel (SS316L) and nickel-based superalloy (Inconel 718) was studied. The investigation on laser-modified surfaces is evaluated through electrochemical polarization analysis using simulated body fluid (SBF). The samples subjected to electrochemical polarization analysis were characterized by optical image analysis, SEM, EDS, and XRD analysis. It was inferred that laser surface-modified materials provided enhanced corrosion resistance and bare nickel alloy is more susceptible to corrosion by SBF.     

Greenhouse gases mitigation by CO<Subscript>2</Subscript> reforming of methane to hydrogen-rich syngas using praseodymium oxide supported cobalt catalyst

This study focuses on the potential of hydrogen-rich syngas production by CO₂ reforming of methane over Co/Pr₂O₃ catalyst. The Co/Pr₂O₃ catalyst was synthesized via wet-impregnation method and characterized for physicochemical properties by TGA, XRD, BET, H₂-TPR, FESEM, EDX, and FTIR. The CO₂ reforming of methane over the as-synthesized catalyst was studied in a tubular stainless steel fixed-bed reactor at feed ratio ranged 0.1–1.0, temperature ranged 923–1023 K, and gas hourly space velocity (GHSV) of 30,000 h^?1 under atmospheric pressure condition. The catalyst activity studies showed that the increase in the reaction temperature from 923 to 1023 K and feed ratio from 0.1 to 1.0 resulted in a corresponding increase in the reactant’s conversion and the product’s yields. At 1023 K and feed ratio of 1.0, the activity of the Co/Pr₂O₃ catalyst climaxed with CH₄ and CO₂ conversions of 41.49 and 42.36 %. Moreover, the catalyst activity at 1023 K and feed ratio of 1.0 resulted in the production of H₂ and CO yields of 40.7 and 40.90 %, respectively. The syngas produced was estimated to have H₂:CO ratio of 0.995, making it suitable as chemical building blocks for the production of oxygenated fuel and other value-added chemicals. The used Co/Pr₂O₃ catalyst which was characterized by TPO, XRD, and SEM-EDX show some evidence of carbon formation and deposition on its surface.