Header Detection to Improve Multimedia Quality Over Wireless Networks

Wireless multimedia studies have revealed that forward error correction (FEC) on corrupted packets yields better bandwidth utilization and lower delay than retransmissions. To facilitate FEC-based recovery, corrupted packets should not be dropped so that maximum number of packets is relayed to a wireless receiver's FEC decoder. Previous studies proposed to mitigate wireless packet drops by a partial checksum that ignored payload errors. Such schemes require modifications to both transmitters and receivers, and incur packet-losses due to header errors. In this paper, we introduce a receiver-based scheme which uses the history of active multimedia sessions to detect transmitted values of corrupted packet headers, thereby improving wireless multimedia throughput. Header detection is posed as the decision-theoretic problem of multihypothesis detection of known parameters in noise. Performance of the proposed scheme is evaluated using trace-driven video simulations on an 802.11b local area network. We show that header detection with application layer FEC provides significant throughput and video quality improvements over the conventional UDP/IP/802.11 protocol stack     

New classification techniques for electroencephalogram (EEG) signals and a real-time EEG control of a robot

This paper studies the state-of-the-art classification techniques for electroencephalogram (EEG) signals. Fuzzy Functions Support Vector Classifier, Improved Fuzzy Functions Support Vector Classifier and a novel technique that has been designed by utilizing Particle Swarm Optimization and Radial Basis Function Networks (PSO-RBFN) have been studied. The classification performances of the techniques are compared on standard EEG datasets that are publicly available and used by brain–computer interface (BCI) researchers. In addition to the standard EEG datasets, the proposed classifier is also tested on non-EEG datasets for thorough comparison. Within the scope of this study, several data clustering algorithms such as Fuzzy C-means, K-means and PSO clustering algorithms are studied and their clustering performances on the same datasets are compared. The results show that PSO-RBFN might reach the classification performance of state-of-the art classifiers and might be a better alternative technique in the classification of EEG signals for real-time application. This has been demonstrated by implementing the proposed classifier in a real-time BCI application for a mobile robot control.     

A cost-sensitive decision tree approach for fraud detection

With the developments in the information technology, fraud is spreading all over the world, resulting in huge financial losses. Though fraud prevention mechanisms such as CHIP&PIN are developed for credit card systems, these mechanisms do not prevent the most common fraud types such as fraudulent credit card usages over virtual POS (Point Of Sale) terminals or mail orders so called online credit card fraud. As a result, fraud detection becomes the essential tool and probably the best way to stop such fraud types. In this study, a new cost-sensitive decision tree approach which minimizes the sum of misclassification costs while selecting the splitting attribute at each non-terminal node is developed and the performance of this approach is compared with the well-known traditional classification models on a real world credit card data set. In this approach, misclassification costs are taken as varying. The results show that this cost-sensitive decision tree algorithm outperforms the existing well-known methods on the given problem set with respect to the well-known performance metrics such as accuracy and true positive rate, but also a newly defined cost-sensitive metric specific to credit card fraud detection domain. Accordingly, financial losses due to fraudulent transactions can be decreased more by the implementation of this approach in fraud detection systems.     

Variance sensitive adaptive threshold-based PCA method for fault detection with experimental application

Principal Component Analysis (PCA) is a statistical process monitoring technique that has been widely used in industrial applications. PCA methods for Fault Detection (FD) use data collected from a steady-state process to monitor T² and Q statistics with a fixed threshold. For the systems where transient values of the processes must be taken into account, the usage of a fixed threshold in PCA method causes false alarms and missing data that significantly compromise the reliability of the monitoring systems. In the present article, a new PCA method based on variance sensitive adaptive threshold (T_vsa) is proposed to overcome false alarms which occur in the transient states according to changing process conditions and the missing data problem. The proposed method is implemented and validated experimentally on an electromechanical system. The method is compared with the conventional monitoring methods. Experimental tests and tabulated results confirm the fact that the proposed method is applicable and effective for both the steady-state and transient operations and gives early warning to operators.     

Exact Analysis of Non-Linear Fractionalized Jeffrey Fluid. A Novel Approach of Atangana-Baleanu Fractional Model

It is a very difficult task for the researchers to find the exact solutions to mathematical problems that contain non-linear terms in the equation. Therefore, this article aims to investigate the viscous dissipation (VD) effect on the fractional model of Jeffrey fluid over a heated vertical flat plate that suddenly moves in its own plane. Based on the Atangana-Baleanu operator, the fractional model is developed from the fractional constitutive equations. VD is responsible for the non-linear behavior in the problem. Upon taking the Laplace and Fourier sine transforms, exact expressions have been obtained for momentum and energy equations. The influence of relative parameters on fluid flow and temperature distribution is shown graphically. As special cases, and for the sake of correctness, the corresponding results for second-grade fluid and Newtonian viscous fluid are also obtained. It is interesting to note that fractional parameter α provides more than one line as compared to the classical model. This effect represents the memory effect in the fluid which is not possible to elaborate by the classical model. It is also worth noting that the temperature profile of the generalized Jeffrey fluid rises for higher values of Eckert number which is due to the enthalpy difference of the boundary layer.     

Al₂O₃ and γAl₂O₃ Nanomaterials Based Nanofluid Models with Surface Diffusion: Applications for Thermal Performance in Multiple Engineering Systems and Industries

Thermal transport investigation in colloidal suspensions is taking a significant research direction. The applications of these fluids are found in various industries, engineering, aerodynamics, mechanical engineering and medical sciences etc. A huge amount of thermal transport is essential in the operation of various industrial production processes. It is a fact that conventional liquids have lower thermal transport characteristics as compared to colloidal suspensions. The colloidal suspensions have high thermal performance due to the thermophysical attributes of the nanoparticles and the host liquid. Therefore, researchers focused on the analysis of the heat transport in nanofluids under diverse circumstances. As such, the colloidal analysis of H₂O composed by γAl₂O₃ and Al₂O₃ is conducted over an elastic cylinder. The governing flow models of γAl₂O₃/H₂O and Al₂O₃/H₂O is reduced in the dimensionless form by adopting the described similarity transforms. The colloidal models are handled by implementing the suitable numerical technique and provided the results for the velocity, temperature and local thermal performance rate against the multiple flow parameters. From the presented results, it is shown that the velocity of Al₂O₃–H₂O increases promptly against a high Reynolds number and it decreases for high-volume fraction. The significant contribution of the volumetric fraction is examined for thermal enhancement of nanofluids. The temperature of Al₂O₃–H₂O and γAl₂O₃–H₂O significantly increases against a higher ϕ. Most importantly, the analysis shows that γAl₂O₃–H₂O has a high local thermal performance rate compared to Al₂O₃–H₂O. Therefore, it is concluded that γAl₂O₃–H₂O is a better heat transfer fluid and is suitable for industrial and technological uses.     

Comparison of abrasive wear behavior of ductile iron with different dual matrix structures

Abrasive wear behavior of ductile irons with different dual matrix structures has been investigated. In order to obtain ductile irons with different dual matrix structures an unalloyed ductile iron specimens were austenitized in the two-phase region (α + γ) at various temperature (795 °C and 815 °C) and then rapidly transferred to a salt bath held at the 365 °C for austempering for 30, 90 and 120 min. Some specimens were quenched from same intercritical austenitizing temperatures and tempered at 550 °C for 60 and 300 min. Some specimens were also conventionally austempered and/or quenched from 900 °C for comparison. Experimental results showed that, the tensile strength increased and ductility decreased with increasing martensite volume fraction in the specimen with martensite dual matrix structure. By increasing the tempering time, the yield and UTS decreased and ductility increased. In addition, the specimens with ausferrite dual matrix structures exhibited much greater ductility than conventionally austempered ones. The tensile strength increased while ductility decreased with increasing ausferrite volume fraction. Furthermore in all austenitized specimens, the abrasive weight loss of austempered specimens (A series) was lower than those of quenched specimens (Q series) irrespective of all loads due to increased AFVFs and total elongation. It was shown that wear loss of both tested materials in abrasive wear was proportional to the applied load. However, there was a decreasing trend in the weight loss of the A795 with dual matrix structure austempered for 30 and 90 min with increasing load. The reason was because of the fact that the specimen surface was work hardened with cutting efficiency of the abrasive reduced through clogging, and attrition jointly leading to less weight loss. Moreover, increasing the austempering time caused more ductile ausferritic structure to displace hard martensite. In all austempered samples, the abrasive weight loss increased with increasing the austempering time. As for the case of Q samples, the abrasive weight loss increased more or less linearly with load since an increase in the applied load might increase the contact stress. Among the Q samples, the highest weight loss was obtained for the Q795-300, Q815-300 sample because of lower martensite volume fraction, but the lowest weight loss was observed for the Q900 sample due to the highest martensite volume fraction. For Q900 samples, the amount of fracture of the abrasives was found to be increase with the harder specimen, and it may have contributed somewhat to the increased wear.Furthermore, microchips were dominant wear mechanism by cutting mode for higher ductile materials while micro-ploughing was predominant wear for harder materials, but wear also occurred by combinations of ploughing and embedding particles into the surface for Q samples. Cross-section examination by SEM through the wear surfaces revealed that a more smoother surface was observed for the A795 sample than that of the Q795 sample. However, a more rougher surface was observed for the A900-120 sample than that of the Q900 sample.     

Propham mineralization in aqueous medium by anodic oxidation using boron-doped diamond anode: influence of experimental parameters on degradation kinetics and mineralization efficiency

This study aims the removal of a carbamate herbicide, propham, from aqueous solution by direct electrochemical advanced oxidation process using a boron-doped diamond (BDD) anode. This electrode produces large quantities of hydroxyl radicals from oxidation of water, which leads to the oxidative degradation of propham up to its total mineralization. Effect of operational parameters such as current, temperature, pH and supporting electrolyte on the degradation and mineralization rate was studied. The applied current and temperature exert a prominent effect on the total organic carbon (TOC) removal rate of the solutions. The mineralization of propham can be performed at any pH value between 3 and 11 without any loss in oxidation efficiency. The propham decay and its overall mineralization reaction follows a pseudo-first-order kinetics. The apparent rate constant value of propham oxidation was determined as 4.8×10⁻⁴ s⁻¹ at 100 mA and 35 °C in the presence of 50 mM Na₂SO₄ in acidic media (pH: 3). A general mineralization sequence was proposed considering the identified oxidation intermediates.     

Flow and heat transfer of two immiscible fluids in double-layer optical fiber coating

The coatings of optical fibers are generally characterized by a multi-layer coating structure. In this work, the mathematical modeling of two immiscible non-Newtonian fluids for optical fiber coating inside a straight annular die is developed in the form of a nonlinear differential equation with nonhomogeneous boundary conditions. Two non-Newtonian fluids, namely power law and Phan-Thien–Tanner fluids, are used in the primary and secondary coating dies, respectively. An exact solution is obtained for velocity fields and temperature distributions for the primary and secondary coating resins. The thickness of coated fiber optics is also calculated for both layers. The effect of different emerging parameters on the solution is discussed and sketched.