A simnet simulation model for estimating system reliability

A general SIMNET simulation model is developed for estimating system reliability. The input data to the model is comprised of the minimal cut sets of the block diagram representing the system. The time-to-failure of the (parallel-series) components may be descriebd by different distributions. The model can be readily extended to include repair and maintenance of the components.     

Reliability-based design of blast-resistant composite laminates incorporating carbon nanotubes

Research efforts have reported on the ability of carbon nanotubes (CNTs) to enhance the stiffness and strength of carbon fiber composites. Systematic design of blast-resistant composites requires considering CNTs–carbon composites characteristics and the uncertainty of blast events. This article suggests a systematic reliability-based design approach where system reliability is used to compute the probability of failure of a composite laminate. A case study for the design of a five-layer composite laminate incorporating CNTs and subjected to uncertain blast event is demonstrated. 0.5–1% CNTs contents by weight seem capable of significantly reducing the composite probability of failure during blast.     

Performance of straw bale wall: A case of study

This research aimed to evaluate a straw bale house located in Bavaria, Germany. An extensive test program was carried out. The experimental work includes compression tests, moisture content, thermal stability of bales and pH. The in situ work includes temperature and relative humidity inside the straw bale wall. The stress-strain behavior of straw bales was investigated including nonlinearity and anisotropy. Thermal stability of bales under constant temperature and relative humidity was studied considering time dependence. The moisture content of straw bale was about 11%, while pH value inside the bale was about 7.29. Moreover, the temperature and the relative humidity between the interior (inside straw bale wall) and the exterior were investigated.     

Full and reduced-order H∞ filtering of Takagi–Sugeno fuzzy time-varying delay systems: Input–output approach

This article addresses the issue of delay-dependent H_∞ filtering design for TakagiŮSugeno fuzzy time-varying delay systems using the input–output approach. A three-term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper-bound inequalities have been added to the obtained conditions. Based on the scaled small gain theorem, nonquadratic Lyapunov–Krasovskii functional approach and considering the bounds of the MF time-derivative, the H_∞ full- and reduced-order filters are designed and then formulated in terms of linear matrix inequalities. Finally, illustrative examples are presented to demonstrate the validity of the proposed methods.     

Detection of Abnormal Activities from Various Signals Based on Statistical Analysis

We perceive big data with massive datasets of complex and variegated structures in the modern era. Such attributes formulate hindrances while analyzing and storing the data to generate apt aftermaths. Privacy and security are the colossal perturb in the domain space of extensive data analysis. In this paper, our foremost priority is the computing technologies that focus on big data, IoT (Internet of Things), Cloud Computing, Blockchain, and fog computing. Among these, Cloud Computing follows the role of providing on-demand services to their customers by optimizing the cost factor. AWS, Azure, Google Cloud are the major cloud providers today. Fog computing offers new insights into the extension of cloud computing systems by procuring services to the edges of the network. In collaboration with multiple technologies, the Internet of Things takes this into effect, which solves the labyrinth of dealing with advanced services considering its significance in varied application domains. The Blockchain is a dataset that entertains many applications ranging from the fields of crypto-currency to smart contracts. The prospect of this research paper is to present the critical analysis and review it under the umbrella of existing extensive data systems. In this paper, we attend to critics' reviews and address the existing threats to the security of extensive data systems. Moreover, we scrutinize the security attacks on computing systems based upon Cloud, Blockchain, IoT, and fog. This paper lucidly illustrates the different threat behaviour and their impacts on complementary computational technologies. The authors have mooted a precise analysis of cloud-based technologies and discussed their defense mechanism and the security issues of mobile healthcare.

     

Catalytic oxidation and flow detection of carbohydrates at ruthenium dioxide modified electrodes

Ruthenium dioxide (RuO2) containing carbon paste electrodes exhibiting electrocatalytic response toward carbohydrates are described. The electrocatalytic behavior is exploited for developing a highly stable and sensitive flow detection scheme for carbohydrates at a low and fixed potential (+0.4 V vs Ag/AgCl). The effects of pH, flow rate, operating potential, surface "loading", concentration, and other variables are explored. The electrode response was stable for more than 48 h, with a signal loss of less than 10% over this period. The detection limits at the picomole level and a relative standard deviation of 1.2% (n = 72) are reported. Electrocatalytic oxidation is described also for related polyhydroxyl compounds (aldonic and aldaric acids and alditols).     

Extensions for Internet QoS paradigms to mobile IP: a survey

Mobile IP has been chosen as the core mobility management mechanism for wireless LANs, 3G cellular networks, and, most recently, aeronautical networks. It is viewed as a key element in providing a universal roaming solution across different wireless access technologies. However, mobile IP in its basic form inherits the IP incapability to provide QoS guarantees. This results in mobile IP's lack of support for seamless intradomain mobility. This article surveys extensions that have been proposed to enhance the QoS functionality of mobile IP. It gives a brief overview of mobile IP and Internet QoS paradigms, and describes their general shortcomings with regard to QoS and mobility, respectively. It then discusses the extensions that have been proposed in the literature and provides a qualitative comparison.     

W-CDMA Uplink Capacity and Interference Statistics of a Long Tunnel Cigar-shaped Microcells Using the Hybrid Model of Propagation with Imperfect Power Control

The uplink capacity and the interference statistics (mean and variance) of the sectors of the cigar-shaped W-CDMA microcell are studied. A model with eighteen sectors is used to analyze the uplink. The microcells are assumed to exist in a long tunnel with at least nine base stations. The hybrid model of propagation is used in the calculations. The capacity and the interference statistics of the sectors are studied in terms of the most important parameters: sector radius, specific attenuation factor, antenna sidelobe levels, bend losses and the power control standard deviation error.     

A neuro-fuzzy model for inflow forecasting of the Nile river at Aswan high dam

River flow forecasting is an essential procedure that is necessary for proper reservoir operation. Accurate forecasting results in good control of water availability, refined operation of reservoirs and improved hydropower generation. Therefore, it becomes crucial to develop forecasting models for river inflow. Several approaches have been proposed over the past few years based on stochastic modeling or artificial intelligence (AI) techniques. In this article, an adaptive neuro-fuzzy inference system (ANFIS) model is proposed to forecast the inflow for the Nile River at Aswan High Dam (AHD) on monthly basis. A major advantage of the fuzzy system is its ability to deal with imprecision and vagueness in inflow database. The ANFIS model divides the input space into fuzzy sub-spaces and maps the output using a set of linear functions. A historical database of monthly inflows at AHD recorded over the past 130 years is used to train the ANFIS model and test its performance. The performance of the ANFIS model is compared to a recently developed artificial neural networks (ANN) model. The results show that the ANFIS model was capable of providing higher inflow forecasting accuracy specially at extreme inflow events compared with that of the ANN model. It is concluded that the ANFIS model can be quite beneficial in water management of Lake Nasser reservoir at AHD.     

Lipidemic effect of methanol

The effect of methanol on some of the lipid components in serum was studied in rats. Methanol was administered by stomach tube in doses of 2 and 6 ml/kg b.wt daily for 21 and 6 days, respectively. Methanol was found to accumulate lipids; thus, cholesterol, phospholipids and triglycerides increased significantly. Concurrently, modification of the lipoid content of organs has been considered. It was concluded that methanol and not only formate, is toxic to rats, inspite of the alleged difference in routes of its metabolism in primates and rodents.