An Investigation on High-Temperature Oxidation and Hot Corrosion Resistance Behavior of Coated TLP (Transient Liquid Phase)-Bonded IN738-LC

Despite all achievements to improve nickel-based superalloy, these classes of alloys are still prone to degradation via high-temperature oxidation and hot corrosion. Repairing damaged parts could decrease the life cycle, cost of equipment, and a transient liquid phase (TLP) bonding is a favorable method that has successfully been used for this purpose. One way to increase the lifetime of the repaired parts and the main body is to utilize protective coating. In the current study, aluminized coating was applied on IN738-LC which was first bonded by TLP process. Coating performance on the joint centerline compared to the other parts of the sample was investigated using a scanning electron microscope (SEM and FESEM) and X-ray diffraction method (XRD). The oxidation test result showed that coating provided less protection on the joint centerline due to coating’s chemical composition difference in this area: particularly Fe and Cr. XRD results showed that at the initial time of oxidation, all (α, γ, δ and θ)-Al₂O₃ were formed and by prolonged exposure were transformed to α-Al₂O₃. The hot corrosion test also proved that the joint centerline and the diffusion-affected zone were less resistant to the corrosion attack of 3Na₂SO₄?+?NaCl salts and severity of damage in these zones were clearly distinguished from microscopic images.     

Decision support for moving from a single product to a product portfolio in evolving software systems

Successful software systems continuously evolve to accommodate ever-changing needs of customers. Accommodating the feature requests of all the customers in a single product increases the risks and costs of software maintenance. A possible approach to mitigate these risks is to transition the evolving software system (ESS) from a single system to a portfolio of related product variants, each addressing a specific customers’ segment. This evolution should be conducted such that the extent of modifications required in ESS's structure is reduced. The proposed method COPE+ uses preferences of customers on product features to generate multiple product portfolios each containing one product variant per segment of customers. Recommendations are given to the decision maker to update the product portfolios based on structural analysis of ESS. Product portfolios are compared with the ESS using statechart representations to identify the level of similarity in their behaviors. A proof of concept is presented by application to an open-source text editing system. Structural and behavioral analysis of candidate portfolios helped the decision maker to select one portfolio out of three candidates.     

Spike detection and clustering with unsupervised wavelet optimization in extracellular neural recordings

Automatic and accurate detection of action potentials of unknown waveforms in noisy extracellular neural recordings is an important requirement for developing brain-computer interfaces. This study introduces a new, wavelet-based manifestation variable that combines the wavelet shrinkage denoising with multiscale edge detection for robustly detecting and finding the occurrence time of action potentials in noisy signals. To further improve the detection performance by eliminating the dependence of the method to the choice of the mother wavelet, we propose an unsupervised optimization for best basis selection. Moreover, another unsupervised criterion based on a correlation similarity measure was defined to update the wavelet selection during the clustering to improve the spike sorting performance. The proposed method was compared to several previously proposed methods by using a wide range of realistic simulated data as well as selected experimental recordings of intracortical signals from freely moving rats. The detection performance of the proposed method substantially surpassed previous methods for all signals tested. Moreover, updating the wavelet selection for the clustering task was shown to improve the classification performance with respect to maintaining the same wavelet as for the detection stage.     

On the Effects of Frequency Scaling Over Capacity Scaling in Underwater Networks—Part II: Dense Network Model

This is the second in a two-part series of papers on information-theoretic capacity scaling laws for an underwater acoustic network. Part II focuses on a dense network scenario, where nodes are deployed in a unit area. By deriving a cut-set upper bound on the capacity scaling, we first show that there exists either a bandwidth or power limitation, or both, according to the operating regimes (i.e., path-loss attenuation regimes), thus yielding the upper bound that follows three fundamentally different information transfer arguments. In addition, an achievability result based on the multi-hop (MH) transmission is presented for dense networks. MH is shown to guarantee the order optimality under certain operating regimes. More specifically, it turns out that scaling the carrier frequency faster than or as $n^{1/4}$ is instrumental towards achieving the order optimality of the MH protocol.     

High performance dye-sensitized solar cells (DSSCs) achieved via electrophoretic technique by optimizing of photoelectrode properties

This paper describes a simple method utilizing electrophoretic deposition (EPD) of commercial P25 nanoparticles (NPs) films on fluoride-doped tin oxide (FTO) substrate. In this process, voltage and the number of deposition cycles are well controlled to achieve TiO₂ film thickness of around 1.5–26 μm, without any mechanical compression processing. The experimental results indicate that the TiO₂ film thickness plays an important role as the photoelectrode in DSSCs because it adsorbs a large number of dye molecules which are responsible for electrons supply. Furthermore, it was found that effects of the bulk traps and surface states within the TiO₂ films on the recombination of the photo-injected electrons (electron–hole pairs) strongly depend on the TiO₂ electrode annealing temperature. Finally, a DSSC with a 24 μm thick TiO₂ film and annealed at 500 °C produced the highest conversion efficiency (η=6.56%, I_SC=16.4, V_OC=0.72, FF=0.55) with an incident solar energy of 100 mW/cm².     

Spatial Based Pilot Allocation (SBPA) in Crowded Massive MIMO Systems

Nowadays, the internet of things (IoT) has gained significant research attention. It is becoming critically imperative to protect IoT devices against cyberattacks with the phenomenal intensification. The malicious users or attackers might take control of the devices and serious things will be at stake apart from privacy violation. Therefore, it is important to identify and prevent novel attacks in the IoT context. This paper proposes a novel attack detection system by interlinking the development and operations framework. This proposed detection model includes two stages such as proposed feature extraction and classification. The preliminary phase is feature extraction, the data from every application are processed by integrating the statistical and higher-order statistical features together with the extant features. Based on these extracted features the classification process is evolved for this, an optimized deep convolutional neural network (DCNN) model is utilized. Besides, the count of filters and filter size in the convolution layer, as well as the activation function, are optimized using a new modified algorithm of the innovative gunner (MAIG), which is the enhanced version of the AIG algorithm. Finally, the proposed work is compared and proved over other traditional works concerning positive and negative measures as well. The experimental outcomes show that the proposed MAIG algorithm for application 1 under the GAF-GYT attack achieves higher accuracy of 64.52, 2.38 and 3.76% when compared over the methods like DCNN, AIG and FAE-GWO-DBN, respectively.

     

Determination of Critical Temperatures in Hot Rolling of a Nb-Microalloyed Steel Sheet

To design the controlled hot rolling and thermomechanical processes of microalloyed steels,it is essential to know the various critical transformation temperatures like the grain coarsening temperature (T gc),the non-recrystallization temperature (T nr),the start of austenite-to-ferrite transformation (A r3),and the finish of the austenite-to-ferrite transformation (A r1).In this work,the heat treatment and continuous cooling compression (CCC) testing were performed to determine the critical temperatures of a Nb-microalloyed steel.Results obtained from the CCC testing on the strain-stress curves were confirmed by metallographic tests.To carry out the CCC testing,T nr equals 960℃;A r3 equals 830℃ and A r1 equals 665℃ were determined.In addition,to specify the grain coarsening temperature that it usually occurs during reheating the slabs,seven different reheating temperatures between 1000 to 1300℃ with 50℃ increments for the soaking treatment were chosen.By soaking the specimens in furnace,the grain coarsening temperature (T gc) was obtained about the temperature of 1250 ℃.Moreover,it was observed that increasing the reheating temperatures causes more decline of the precipitates percentage.Therefore,the temperature range of 1200 to 1250℃ is recommended to reheat these types of steels.     

CogNS: A Simulation Framework for Cognitive Radio Networks

Cognitive radio technology has been used to efficiently utilize the spectrum in wireless networks. Although many research studies have been done recently in the area of cognitive radio networks (CRNs), little effort has been made to propose a simulation framework for CRNs. In this paper, a simulation framework based on NS2 (CogNS) for cognitive radio networks is proposed. This framework can be used to investigate and evaluate the impact of lower layers, i.e., MAC and physical layer, on the transport and network layers protocols. Due to the importance of packet drop probability, end-to-end delay and throughput as QoS requirements in real-time reliable applications, these metrics are evaluated over CRNs through CogNS framework. Our simulations demonstrate that the design of new network and transport layer protocols over CRNs should be considered based on CR-related parameters such as activity model of primary users, sensing time and frequency.     

Defense against SYN flooding attacks: A particle swarm optimization approach

SYN flooding attack is a threat that has been designed based on vulnerabilities of the connection establishment phase of the TCP protocol. In this attack some sources send a large number of TCP SYN segments, without completing the third handshake step to quickly exhaust connection resources of the victim server. Hence, a main part of the server’s buffer space is allocated to the attack half open connections and incoming new connection requests will be blocked. This paper proposes a novel framework, in which, the defense issue is formulated as an optimization problem. Then it employs the particle swarm optimization (PSO) algorithm to solve this optimization problem. Our theoretical analysis and packet-level simulations in ns-2 environment show that the proposed defense strategy called PSO_SYN decreases the number of blocked TCP connection requests and cuts down share of attack connections from the buffer space.     

Dual hierarchical genetic-optimal control: A new global optimal path planning method for robots

A new two-stage analytical-evolutionary algorithm considering dynamic equations is presented to find global optimal path. The analytical method is based on the indirect open loop optimal control problem and the evolutionary method is based on genetic algorithm (GA). Initial solutions, as start points of optimal control problem, are generated by GA to be used by optimal control. Then, a new sub-optimal path is generated through optimal control. The cost function is calculated for every optimal solution and the best solutions are chosen for the next step. The obtained path is used by GA to produce new generation of start points. This process continues until the minimum cost value is achieved. In addition, a new GA operator is introduced to be compatible with optimal control. It is used to select the pair chromosomes for crossover. The proposed method eliminates the problem of optimal control (being trapped in locally optimal point) and problem of GA (lack of compatibility with analytical dynamic equations). Hence problem is formulated and verification is done by comparing the results with a recent work in this area. Furthermore effectiveness of the method is approved by a simulation study for spatial non-holonomic mobile manipulators through conventional optimal control and the new proposed algorithm.