An Improved Viscosity-Temperature Correlation for Crude Oils

The available data of crude oil viscosity over a temperature range 130-220°F and at atmospheric pressure are used to develop a method to predict the viscosity of crude oils. The proposed correlation based upon API gravity, and viscosity at reservoir temperature. The proposed new correlation has been verified using data base on crude oil of different densities, and it shows significantly better correlation, with an average absolute deviation (AAD) of 2.8%.     

Effects of Temperature and Pressure on Natural Gas Viscosity Which Has Different API Gravities

The theory of gas transport is simply stated, but it is quite complex to express in equations that can be used directly to calculate viscosity. A correlation was developed to predict viscosity of natural gas (of different API gravities) function of temperature and pressure. This correlation depends only on API gravity of natural gas. The proposed correlation has been verified using data of about 246 data points, and it is shows significantly better correlation, with an average absolute error of 3.2%.     

Properties and characterization of ([Mengkuang leaf fiber]‐filled ethylene vinyl acetate)/(natural rubber) blend: Effects of blending sequences and mengkuang leaf fiber loading

(Ethylene vinyl acetate [EVA])/(natural rubber [NR])/(Mengkuang leaf fiber) (MLF) thermoplastic elastomer composites were prepared by using three different blending sequences in an internal mixer. The blending sequences studied were (i) B1: NR was added followed by MLF into the molten EVA; (ii) B2: MLF was added followed by NR into the molten EVA; (iii) B3: MLF was added followed by EVA into the molten NR. The effect of different blending sequences and fiber loadings from 10 to 40 parts by weight per hundred parts of resin on the torque development, tensile properties, thermal degradation, and morphology of EVA/NR/MLF composites was studied. Of the blending sequences investigated, the B1 system is considered the best method for the preparation of EVA/NR/MLF composites. The B1 system produces composites with lower stabilization torque, higher tensile strength, and better thermal stability compared with other systems. At 40 parts by weight per hundred parts of resin of MLF loading, the tensile strength of the composite prepared by using the B1 system was 15% higher than that of B2 system composites, and 8% higher than that of the B3 system. Scanning electron micrographs of the tensile fracture surfaces indicated this system also had good fiber dispersion in the EVA/NR matrix. An increase in MLF loading resulted in an increase of the values of the stabilization torque and the Young's modulus, but a decrease in values of the tensile strength, the elongation at break, and the thermal stability of the composites. Scanning electron microscopy revealed increased fiber pullout in the composites as the loading increased. J. VINYL ADDIT. TECHNOL., 24:109–115, 2018. © 2016 Society of Plastics Engineers     

High payload image steganography scheme with minimum distortion based on distinction grade value method

Presently, the design and development of an effective image steganography system are facing several challenges including the low capacity, poor robustness and imperceptibility. To surmount such limitations, it is important to improve the capacity and security of the steganography system while maintaining a high signal-to-noise ratio (PSNR). Based on these factors, this study is aimed to design and develop a distinction grade value (DGV) method to effectively embed the secret data into a cover image for achieving a robust steganography scheme. The design and implementation of the proposed scheme involved three phases. First, a new encryption method called the shuffle the segments of secret message (SSSM) was incorporated with an enhanced Huffman compression algorithm to improve the text security and payload capacity of the scheme. Second, the Fibonacci-based image transformation decomposition method was used to extend the pixel’s bit from 8 to 12 for improving the robustness of the scheme. Third, an improved embedding method was utilized by integrating a random block/pixel selection with the DGV and implicit secret key generation for enhancing the imperceptibility of the scheme. The performance of the proposed scheme is assessed experimentally to determine the imperceptibility, security, robustness and capacity. The resistance of the proposed scheme is tested against the statistical, χ², Histogram and non-structural steganalysis detection attacks. The obtained PSNR values revealed the accomplishment of the higher imperceptibility and security by the proposed DGV scheme while maintaining higher capacity compared to the reported findings. In short, the proposed steganography scheme outperformed the commercially available data hiding schemes, thereby resolved the existing issues.

     

Analysis of duality-based interconnected kinematics of planar serial and parallel manipulators using screw theory

In this paper, a method has been proposed to analyze the planar architectures of serial and parallel manipulators, based on the duality associated with their interconnected kinematics. The interconnected kinematics states that model of one architecture can be derived from the kinematic model of the other, using screw theory approach. The performance of the initial and the derived manipulators was evaluated with three criteria: isotropy, maximum force transmission ratio and local transmission index. Without loss of generality, the serial manipulator derived from parallel has better isotropy, while the parallel manipulator derived from serial can be designed to have better force and power transmission.

     

Estimation of Wind-Driven Coastal Waves Near a Mangrove Forest Using Adaptive Neuro-Fuzzy Inference System

At the coastline of the Carey Island, mangroves provide natural protection against the wind-driven coastal waves. The area is located at the west Malaysia within the waters of the Straits of Malacca. Recently, its coastline has been exposed to increasing rates of coastal erosion due to mangrove deforestation. In order to provide mitigating measures, it is necessary to study wave characteristics in this region. For this purpose, we collected 5 years (2009 to 2013) of hourly measurements for wind direction, wave height, wind speed and wave period. Moreover, we used the adaptive neuro-fuzzy inference system (ANFIS) to estimate the wave period and height. The model was trained using the measured data. The validation of the model gave satisfactory R² values of 0.8484 and 0.9496 for wave height and wave period, respectively. The findings from this study suggest that fuzzy logic based technique satisfactorily predicts the differences between multiple inputs and single output in terms of non-linear relationship. The developed model can be used to further study the effect of non-linear wind-driven waves on the depleting coastal mangrove forests in similar tropical and sub-tropical areas. We suggest further research to test the model in different geographical locations, such as in deep-ocean, narrow straits and other coastal sites, which were not covered in this study.     

A low complexity high efficiency hybrid multiplicative-additive crest factor reduction for OFDM systems

In this paper, we propose a novel technique to reduce the crest factor (CF) in orthogonal frequency division multiplexing systems. It consists of two inverse fast Fourier transform (IFFT) blocks, the input symbols of the first IFFT are the mapped symbols, whereas the input symbols of the second IFFT are the summations of the absolute value of the real part of the outer signal constellation points and zero symbols. First, the output of the two IFFT blocks is partitioned into four subblocks, which are subsequently used to rearrange the subblocks with padding zeros in a specific manner. Then, a new optimization scheme is introduced, in which only a single two-phase sequence and four iterations need to be applied. Numerical analysis shows that the proposed hybrid technique achieves better CF reduction performance with significantly lower complexity and better bit error rate performance than the existing scrambling (multiplicative) and additive CF techniques.     

Multicast-Unicast Data Delivery Method in Wireless IPv6 Networks

Multicast IPv6 is an efficient way of transmitting data simultaneously to a group of IPv6 users. It has the advantage of reducing the required bandwidth of IPv6 data delivery compared to unicast transmission. The data rate of multicast transmission over WLAN is confined by the user with the lowest rate in the multicast group, which is called the fixed base rate problem. This paper proposes a delivery method that incorporates both multicast and unicast transmissions to solve the fixed base rate problem. The proposed method divides the IPv6 network into two levels: multicast mode for the upper level of the network [IPv6 server to Access Point (AP)], and unicast mode for the lower level (AP to mobile nodes). To maintain the end-to-end multicast transmission, the AP is responsible for converting multicast packets to unicast packets. Such a combination enables the proposed method to inherit the advantages of both multicast and unicast transmissions. The performance of our proposed method is evaluated in a test-bed environment that considers the transmission of real-time video application. The proposed multicast-unicast is able to improve the throughput and video quality experienced by the end user, with low packet loss and transmission delay.     

Malware analysis performance enhancement using cloud computing

Nowadays, computer based technology has taken a central role in every person life. Hence, damage caused by malicious software (malware) can reach and effect many people globally as what could be in the early days of computer. A close look at the current approaches of malware analysis shows that the respond time of reported malware to public users is slow. Hence, the users are unable to get prompt feedback when reporting suspicious files. Therefore, this paper aims at introducing a new approach to enhance malware analyzer performance. This approach utilizes cloud computing features and integrates it with malware analyzer. To evaluate the proposed approach, two systems had been prepared carefully with the same malware analyzer, one of them utilizes cloud computing and the other left without change. The evaluation results showed that the proposed approach is faster by 23 % after processing 3,000 samples. Furthermore, utilizing cloud computing can open door to crowd-source this service hence encouraging malware reporting and accelerate malware detection by engaging the public users at large. Ultimately this proposed system hopefully can reduce the time taken to detect new malware in the wild.     

THE BEHAVIOUR OF ADHESIVELY BONDED BEAMS VERSUS THEIR WELDED EQUIVALENT

The study aims to produce a design guide for the calculations of stresses and deflections of adhesively bonded beams fabricated from steel adherends using a structural epoxy adhesive. Such design calculations already exist for welded but not for bonded beams. Small models based on beams with a T-section profile, at various beam lengths, are formulated. A key to these calculations is the determination of the adhesive/adherend interface factors/coefficients, to correct the estimated values of stress and deflection from three-point bending conditions. This article presents the methodology for evaluating bonded beams in relation to equivalent welded (solid) beams. This includes mechanical testing, an analytical method based on beam and sandwich theory, and finite element techniques. Results from these techniques are presented and compared and values of the coefficients for T-section beams are determined.