Modeling the Effect of Subjective Factors on Productivity of Trenchless Technology Application to Buried Infrastructure Systems

Trenchless technology (TT) includes a large family of methods utilized for installing and rehabilitating underground utility systems with minimal surface disruption and destruction resulting from conventional excavation. Productivity of TT techniques is affected by a number of subjective factors that need to be evaluated. A productivity index (PI) model is developed in order to represent this subjective effect in refining productivity assessment. The analytic hierarchy process and fuzzy logic are used to develop the proposed PI model that relies on the actual performance of 12 subfactors under three main categories: management, environmental, and physical conditions. The developed PI model resulted in PI equal to 0.7323 and 0.7251 for microtunneling and horizontal directional drilling (HDD) projects, respectively. Multiattribute decision support system software is developed to determine the PI for a specific TT technique using Visual Basic. The PI model is tested, which shows reasonable results. This research is relevant to both industry practitioners and researchers. It provides practitioners with a model that justifies their productivity calculation by quantifying subjective factors effect, which will affect their schedule and cost estimation for trenchless projects. In addition, it provides researchers with the development methodology for the PI model.     

Validation of chlorophyll-α concentration maps from Aqua MODIS over the Gulf of Gabes (Tunisia): comparison between MedOC3 and OC3M bio-optical algorithms

Few studies have focused on the use of ocean colour remote sensors in the Gulf of Gabes (southeastern Tunisia). This work is the first study to evaluate the ocean colour chlorophyll-a product in this area. Chlorophyll-a concentrations were measured during oceanographic cruises performed off the Gulf of Gabes. These measurements were used to validate satellite data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. First, two atmospheric correction procedures (standard and shortwave infrared) were tested to derive the remote-sensing reflectance, and then a comparison between two bio-optical (OC3M and MedOC3) algorithms were realized using the in situ measurements. Both atmospheric correction procedures gave similar results when applied to our study area indicating that most pixels were non-turbid. The comparison between bio-optical algorithms shows that using the regional bio-optical algorithm MedOC3 improves chlorophyll-a estimation in the Gulf of Gabes for the low values of this parameter.     

A synchronization algorithm for distributed multimedia environments

Network synchronization plays a significant role in transmitting multimedia objects over computer networks. Even packets from a single channel must be synchronized due to the problems in a packet switching environment, such as network jitter, frequency, and time offsets. We present an algorithm that determines the set of packets generated periodically by various participants arriving at a node. The basic advantage of the proposed algorithm is that the receiver estimates the reference times (expected arrival times of the packets) and achieves synchronization, without knowledge of the packet delays. The accuracy is improved and the complexity is reduced by predicting the time/frequency offsets between the clocks at the source and the mixer. The error is calculated by the Chernoff bound, demonstrated by simulation, and shown to be acceptable in practical applications.     

Intelligent Intrusion Detection System for Industrial Internet of Things Environment

Rapid increase in the large quantity of industrial data, Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation, data sensing and collection, real-time data processing, and high request arrival rates. The classical intrusion detection system (IDS) is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity. To resolve these issues, this paper designs a new Chaotic Cuckoo Search Optimization Algorithm (CCSOA) with optimal wavelet kernel extreme learning machine (OWKELM) named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform. The CCSOA-OWKELM technique focuses on the design of feature selection with classification approach to achieve minimum computation complexity and maximum detection accuracy. The CCSOA-OWKELM technique involves the design of CCSOA based feature selection technique, which incorporates the concepts of chaotic maps with CSOA. Besides, the OWKELM technique is applied for the intrusion detection and classification process. In addition, the OWKELM technique is derived by the hyperparameter tuning of the WKELM technique by the use of sunflower optimization (SFO) algorithm. The utilization of CCSOA for feature subset selection and SFO algorithm based hyperparameter tuning leads to better performance. In order to guarantee the supreme performance of the CCSOA-OWKELM technique, a wide range of experiments take place on two benchmark datasets and the experimental outcomes demonstrate the promising performance of the CCSOA-OWKELM technique over the recent state of art techniques.     

A Variance Equality Test for Two Correlated Complex Gaussian Variables With Application to Spectral Power Comparison

Complex-valued Gaussian distributions occur frequently in signal processing. We derive a simple statistic, independent of any complex-valued correlation, for testing for the equality of variances using a sample drawn from such a bivariate distribution. The percentage points of the distribution are easy to compute. The power of the test is determined and shown to be high even for very small sample sizes when the variables are highly correlated. The new test is used to determine whether the spectral power associated with an ultralow-frequency wave in the solar magnetic field is equal at two different observing spacecraft     

Performance of glass fiber reinforced polymer bars under elevated temperatures

This paper investigates the residual tensile properties of newly developed glass fiber reinforced polymer (GFRP) bars after being subjected to elevated temperatures for different periods. A total of 120 GFRP specimens were tested in this study. Half of the samples were covered with concrete while the other half were bare bars. The specimens were subjected to three different controlled temperatures (100, 200 and 300 °C) for three different periods (1, 2, and 3 h). Test results showed that almost no losses were observed in the tensile modulus after all exposure periods and temperatures. Losses in the tensile strength, proportional to the level of temperature and exposure period, were recorded. The bars with concrete cover showed higher residual tensile strength compared to their counterparts without coating. The concrete cover was more effective at the lowest temperature level (100 °C) and at the shortest time period (1 h). Scanning Electronic Microscopy (SEM) technique was also used to investigate the effect of elevated temperature on the degradation mechanism of the GFRP bars. The results showed that increasing the temperature level affected the resin matrix surrounding the glass fibers and consequently affected the bond between the fibers and the matrix.     

A physically based diode model for circuit simulation

A physically based power PiN diode model is presented. Eigen value internal approximation method is used to solve the ambipolar diffusion equation. This model is implemented in SIMPLORER circuit simulator using VHDL‐AMS language. The proposed model can be used in both circuit simulators and the optimization of a given power PiN diode. Good agreement is obtained by comparing the results of the suggested model with experimental data. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust backstepping for the Euler approximate model of sampled-data strict-feedback systems

Stabilization of uncertain sampled-data strict-feedback systems is addressed. The stability study is carried out on the Euler approximation of the exact discretized model of the plant. Firstly, a class of state-feedback controllers is developed that guarantees an input-to-state stability property for the closed-loop system. Additionally, assuming some hypotheses on the uncertain terms hold, a practical asymptotic stability property is ensured by designing an appropriate class of controllers.     

Feature‐based recursive observer design for homography estimation and its application to image stabilization

This paper presents a new algorithm for online estimation of a sequence of homographies applicable to image sequences obtained from robotic vehicles equipped with vision sensors. The approach taken exploits the underlying Special Linear group structure of the set of homographies along with gyroscope measurements and direct point‐feature correspondences between images to develop temporal filter for the homography estimate. Theoretical analysis and experimental results are provided to demonstrate the robustness of the proposed algorithm. The experimental results show excellent performance and robustness even in the case of very fast camera motions (relative to frame rate) and severe occlusions.