Ant colony optimization algorithm to solve for the transportation problem of cross-docking network

This paper addresses the transportation problem of cross-docking network where the loads are transferred from origins (suppliers) to destinations (retailers) through cross-docking facilities, without storing them in a distribution center (DC). We work on minimizing the transportation cost in a network by loading trucks in the supplier locations and then route them either directly to the customers or indirectly to cross-docking facilities so the loads can be consolidated. For generating a truck operating plan in this type of distribution network, the problem was formulated using an integer programming (IP) model and solved using a novel ant colony optimization (ACO) algorithm. We solved several numerical examples for verification and demonstrative purposes and found that our proposed approach finds solutions that significantly reduce the shipping cost in the network of cross-docks and considerably outperform Branch-and-Bound algorithm especially for large problems.     

A computer-aided ECG diagnostic tool

Jordan lacks companies that provide local medical facilities with products that are of help in daily performed medical procedures. Because of this, the country imports most of these expensive products. Consequently, a local interest in producing such products has emerged and resulted in serious research efforts in this area. The main goal of this paper is to provide local (the north of Jordan) clinics with a computer-aided electrocardiogram (ECG) diagnostic tool in an attempt to reduce time and work demands for busy physicians especially in areas where only one general medicine doctor is employed and a bulk of cases are to be diagnosed. The tool was designed to help in detecting heart defects such as arrhythmias and heart blocks using ECG signal analysis depending on the time-domain representation, the frequency-domain spectrum, and the relationship between them. The application studied here represents a state of the art ECG diagnostic tool that was designed, implemented, and tested in Jordan to serve wide spectrum of population who are from poor families. The results of applying the tool on randomly selected representative sample showed about 99% matching with those results obtained at specialized medical facilities. Costs, ease of interface, and accuracy indicated the usefulness of the tool and its use as an assisting diagnostic tool.     

Modified Buffalo Optimization with Big Data Analytics Assisted Intrusion Detection Model

Lately, the Internet of Things (IoT) application requires millions of structured and unstructured data since it has numerous problems, such as data organization, production, and capturing. To address these shortcomings, big data analytics is the most superior technology that has to be adapted. Even though big data and IoT could make human life more convenient, those benefits come at the expense of security. To manage these kinds of threats, the intrusion detection system has been extensively applied to identify malicious network traffic, particularly once the preventive technique fails at the level of endpoint IoT devices. As cyberattacks targeting IoT have gradually become stealthy and more sophisticated, intrusion detection systems (IDS) must continually emerge to manage evolving security threats. This study devises Big Data Analytics with the Internet of Things Assisted Intrusion Detection using Modified Buffalo Optimization Algorithm with Deep Learning (IDMBOA-DL) algorithm. In the presented IDMBOA-DL model, the Hadoop MapReduce tool is exploited for managing big data. The MBOA algorithm is applied to derive an optimal subset of features from picking an optimum set of feature subsets. Finally, the sine cosine algorithm (SCA) with convolutional autoencoder (CAE) mechanism is utilized to recognize and classify the intrusions in the IoT network. A wide range of simulations was conducted to demonstrate the enhanced results of the IDMBOA-DL algorithm. The comparison outcomes emphasized the better performance of the IDMBOA-DL model over other approaches.     

A Brownian control problem for a simple queueing system in the Halfin–Whitt regime

We consider a formal diffusion limit for a control problem of a multi-type multi-server queueing system, in the regime proposed by Halfin and Whitt. This takes the form of a control problem where the dynamics are driven by a Brownian motion. In one dimension, a pathwise minimum is obtained and is characterized as the solution to a stochastic differential equation. The pathwise solution to a special multi-dimensional problem (corresponding to a multi-type system) follows.     

NATURAL CONVECTION HEAT AND MASS TRANSFER FROM A VERTICAL FLAT PLATE WITH VARIABLE WALL TEMPERATURE AND CONCENTRATION TO POWER-LAW FLUIDS WITH YIELD STRESS IN A POROUS MEDIUM

The problem of natural convection coupled heat and mass transfer of non-Newtonian power law fluids with yield stress from a vertical flat plate in a fluid-saturated porous medium is analyzed under boundary layer approximations. Similarity solutions are obtained for the general case of power law variations of the wall temperature and concentration. Velocity, temperature, and concentration profiles as well as local heat and mass transfer rates are presented and discussed for different values of the rheological parameters of a power-law fluid, the Lewis number, and the thermal and concentration buoyancy ratio.     

Selective inhibition of HIV-1 reverse transcriptase (HIV-1 RT) RNase H by small RNA hairpins and dumbbells

We present here the design of a novel class of RNA inhibitors of the RNase H domain of HIV-1 RT, a ribonuclease activity that is essential for viral replication in vivo. Specifically, we show that small RNA hairpins and dumbbells can selectively inhibit the RNase H activity of HIV-1 RT without affecting other cellular RNases H (e.g., E. coli and human RNase H). These results suggest that the inhibitors do not interact with the nucleic acid binding site of RT RNase H, as this region should be well conserved among the various enzymes. The most potent inhibitors displayed IC50 values in the 3-8 microM range. Remarkably, the DNA polymerase activity, an intrinsic property of HIV RT, was not inhibited by the hairpin and dumbbell aptamers, a property not previously observed for any nucleic acid aptamer directed against RT RNase H. The results described here suggest a noncompetitive binding mechanism, as outlined in the differential inhibitory characteristics of each of the nucleic acid aptamers against the bacterial, human, and viral RNase H homologues.     

Repair of heat-damaged RC shallow beams using advanced composites

Several repair techniques for restoring the structural capacity of heat-damaged high-strength reinforced concrete shallow beams using advanced composites are proposed. A series of 16 under-reinforced concrete hidden beams were cast, heated at 600°C for 3 h, repaired, and then tested under four point-loading. Tests were conducted to study the effectiveness of externally applied composite materials on increasing the flexural capacity of beams. The composites used include high strength fiber reinforced concrete jackets; ferrocement laminates; and high-strength fiber glass sheets. The beams repaired with steel and high performance polypropylene fiber reinforced concrete jackets regained up to 108 and 99% of the control beams’ ultimate load capacity, with a corresponding increase in stiffness of up to 104 and 98%, respectively. The beams repaired with fiber glass sheets and ferrocement meshes regained up to 126 and 99% of the control beams’ ultimate load capacity, with a corresponding increase in stiffness of up to 160 and 156%, respectively. Most of the beams repaired showed a typical flexural failure with very fine and well-distributed hairline cracks in the constant moment region.     

Nonlinear constitutive models for FRP composites using artificial neural networks

This paper presents a new approach to generate nonlinear and multi-axial constitutive models for fiber reinforced polymeric (FRP) composites using artificial neural networks (ANNs). The new nonlinear ANN constitutive models are complete and have been integrated with displacement-based FE software for the nonlinear analysis of composite structures. The proposed ANN constitutive models are trained with experimental data obtained from off-axis tension/compression and pure shear (Arcan) tests. The proposed ANN constitutive model is generated for plane–stress states with assumed functional response in some parts of the multi-axial stress space with no experimental data. The ability of the trained ANN models to predict material response is examined directly and through FE analysis of a notched composite plate. The experimental part of this study involved coupon testing of thick-section pultruded FRP E-glass/polyester material. Nonlinear response was pronounced including in the fiber direction due to the relatively low overall fiber volume fraction (FVF). Notched composite plates were also tested to verify the FE, with ANN material models, to predict general non-homogeneous responses at the structural level.     

Experimental and numerical analysis of delamination growth in double cantilever laminated beams

Delamination crack growth in laminated composites is investigated using experiments and finite element (FE) models. Tests are performed on cross-ply graphite/epoxy specimens under static conditions. The load-displacement response is monitored in the tested coupons along with crack length. The FE models employ a cohesive layer that is used to simulate the debonding and crack propagation. The cohesive parameters are calibrated from the experimental load-displacement curves. Crack growth and strain measurements are compared with those from the FE models. The predicted results from the FE models are in good agreement with the test results. The same modeling approach is also used to simulate crack propagation in the transverse direction of a notched laminate. The proposed FE analysis with cohesive layers can simplify fracture toughness assessment in multilayered specimens.