Cognitive radio network in vehicular ad hoc network (VANET): a survey

Cognitive radio network and vehicular ad hoc network (VANET) are recent emerging concepts in wireless networking. Cognitive radio network obtains knowledge of its operational geographical environment to manage sharing of spectrum between primary and secondary users, while VANET shares emergency safety messages among vehicles to ensure safety of users on the road. Cognitive radio network is employed in VANET to ensure the efficient use of spectrum, as well as to support VANET’s deployment. Random increase and decrease of spectrum users, unpredictable nature of VANET, high mobility, varying interference, security, packet scheduling, and priority assignment are the challenges encountered in a typical cognitive VANET environment. This paper provides survey and critical analysis on different challenges of cognitive radio VANET, with discussion on the open issues, challenges, and performance metrics for different cognitive radio VANET applications

Galvanostatic Electrodeposition of Ni-Co Alloys in DMSO under a Magnetic Field

This paper focuses on the galvanostatic magneto-electrodeposition of Ni-Co alloys in dimethyl sulphoxide (DMSO) in the presence and absence of a permanent parallel magnetic field (PPMF) to the cathode surface. It was found that the mass deposition was enhanced in the presence of PPMF(9 T) compared with the deposition without PPMF. The percentage enhancement potential (ξ%) was elevated (ξ5%=23.11, ξ2%=10.65, ξ0.5%= 4.85) with current densities of 5, 2 and 0.5 mA cm–2, respectively, in the presence of PPMF (9 T). Atomic force microscopy (AFM) showed that the roughness of the Ni-Co alloy films was reduced from 56.187 to 31.716 nm(at 0.2 mA cm–2) and 97.541 to 52.644 nm(at 0.5 mA cm–2) with applied PPMF(9 T) compared with that without the PPMF. The deposited layers were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD) and energy dispersive X-ray analysis (EDX).Keywords: Potential enhancement, roughness, DMSO, magnetic electrodepositio

Contingent Valuation Method: Valuing Cultural Heritage

Cultural heritage is not easy to be valued in a market because it is a very unique product which gives a community (ies), nation(s) an identity and a sense of belonging. Debate on the valuation of cultural heritage surrounds despite growing attention by economists and policy makers. The attention on the estimation of economic values for cultural goods and services has been great by economics throughout the past two decades (Choi, et al., 2009; Kaminski, McLoughlin, & Sodagar, 2007; Navrud & Ready, 2002, Noonan, 2003; Venkatachalam, 2004). The two stated preference methods which are commonly used in valuing non-use goods; i.e. contingent valuation method and choice modelling. Each of these two valuation method has its own strengths and weaknesses and may even complement each other depending on the parameters of the study. However, according to Kaminski et al., 2007; Noonan, 2003, the usage of choice modelling to estimate cultural values has been limited due to the growing usage of contingent valuation. Therefore, this paper will discuss contingent valuation method in valuing amenities and aim to contribute the knowledge on contingent valuation method for nonmarket goods. (Abstract by author

Numerical analysis of spray-dic modeling for fruit concentration drying process into powder based on computational fluid dynamic

The drying process is most popular preservation methods. It is important in producing the powder and natural dye by concentration fruit drying. Spray-DIC is one of the concentration techniques for drying process using the nozzle flow application in computational fluid dynamic. The mathematical modeling for drying process in this paper includes mass conservation and energy conservation of fruit concentration based on partial differential equation. The discretization of mathematical model will use the finite difference method with the initial and boundary conditions of nozzle flow application. The mathematical modeling computes numerical in sequential algorithm. Jacobi and Gauss-Seidel scheme will use to solve the linear system of mathematical modeling. The execution time, no of iteration, accuracy, root mean square error and maximum error are measured for investigating the numerical analysis. The results show the Gauss Seidel method is the alternative method compared to Jacobi method for solving the Spray-DIC modeling

Interference temperature measurements and spectrum occupancy evaluation in the context of cognitive radio

This paper presents a refined radio spectrum measurement platform specifically designed for spectrum occupancy surveys in the context of Cognitive radio. Cognitive radio permits the opportunistic usage of licensed bands by unlicensed users without causing harmful interference to the licensed user. In this work, a study based on the measurement of the 800 MHz to 2.4 GHz frequency band at two different locations inside Universiti Teknologi Malaysia (UTM), Johor Bahru campus, Malaysia is presented. Two Tektronix RSA306B spectrum analyzer are set up to conduct simultaneous measurements at different locations for a 24 hours period. The analysis conducted in this work is based on the real spectrum data acquired from environment in the experimental set up. Busy and idle channels were identified. The channels subject to adjacent-channel interference were also identified, and the impact of the detection threshold used to detect channel activities was also discussed. The consistency of the observed channel occupation over a range of thresholds and a sudden drop has good characteristics in determining an appropriate threshold needed in order to avoid interference

Comparison between controlled and uncontrolled spray-DIC modeling for dehydration process

The work reported here focuses on the controllability expressions in the mathematical modeling of dehydration process of food concentrates in producing powder using spray-DIC (spray-Détente Instantaneé Controlee or spray-instant controlled pressure drop). This paper presents the second-order partial differential equations for mathematical modeling of moisture and heat transfer in spray-DIC process. This paper proposes the enhancement in the simple model of DIC technique with controllability expression to be used in the spray-DIC. The controllability expression in the drying process models gives better results when compared to the models without the controllability expression. The results were computed and shown by MATLAB 2013 with Windows 8 operating systems. The controllability expression in dehydration process model using the spray-DIC drier manage to succesfully control the dehydration process

Positioning Control of an Antagonistic Pneumatic Muscle Actuated System using Feedforward Compensation with Cascaded Control Scheme

This paper presents a feedforward compensation with cascaded control scheme (FFC) for the positioning control of a vertical antagonistic based pneumatic muscle actuated (PMA) system. Owing to the inherent nonlinearities and time varying parameters exhibited by PMA, conventional fixed controllers unable to demonstrate high positioning performance. Hence, the feedforward compensation with cascaded control scheme is proposed whereby the scheme includes a PID controller coupled with nonlinear control elements. The proposed scheme has a simple control structure in addition to its straightforward design procedures. Though there are nonlinear control elements involved, these elements are derived from the open loop system responses that does not requires any accurate known parameters. Performance of the FFC scheme are then evaluated experimentally and compared to a PID controller with feedforward compensation (FF-PID) in point-to-point motion of different step heights. Overall, the experimental results show that the effectiveness of the proposed FFC scheme in reducing the steady state error to zero in comparison to FF-PID controller for all cases of step heights examined

A real-time pothole detection based on deep learning approach

Today, the number of vehicles using the road including highways and single carriage way is increasing. road structure safety monitoring system that is safe for road users and also important to ensure long-term vehicle safety and prevent accidents due to road damage such as potholes, landslides and uneven roads. Most news reports of road accidents are also caused by potholes that are almost 10-30 cm deep, coupled with heavy rainfall that reduces visibility among drivers, significant damage to the suspension system to the vehicle or unnecessary traffic congestion. In this paper, deep learning detection with YOLOv3 algorithm is proposed apart from researches ranging from accelerometer detection, image processing or machine learning based detection as it is easier to develop and provide more accurate results. After pothole has been detected in real-time webcam, the location will be logged and displayed using Google Maps API for visualization. a total of 330 sets of data were sampled for the implementation of the pothole detection training model. As the results, the model provided 65.05 mAP and 0.9 % precision rate and 0.41 recall rate. The limitation of YOLOv3 algorithm detection can be improve further using GPU with higher specification performances and can sample 1000 to 10,000 datasets. The proposed algorithm provides acceptably high precision and efficient pothole monitoring solution under different scenarios for the users and may benefit the public and the government to monitor pothole in real-time

Chronology of brain tumor classification of intelligent systems based on mathematical modeling, simulation and image processing techniques

Tumor classification using image processing techniques is becoming a powerful tool nowadays. Based on the importance of this technique, the motivation of this review paper is to present the chronology of brain tumor classification using the digital images and govern the mathematical modeling and simulation of intelligent systems. The intelligent system involves artificial neural network (ANN), fuzzy logic (FL), support vector machine (SVM), and parallel support vector machine (PSVM). The chronology of brain tumor classification presents the latest part of the literature reviews related to the principal, type and interpretation of segmentation and classification of brain tumors via the large digital dataset from magnetic resonance imaging (MRI) images. This paper has been classified the modeling and simulation in classical and automatic models. Around 115 literature reviews in high ranking journal and high citation index are referred. This paper contains 6 contents, including mathematical modeling, numerical simulation, image processing, numerical results and performance, lastly is the conclusion to standardize the frame concept for the future of chronological framework involving the mathematical modeling and simulation. Research outcome to differentiate the tumor classification based on MRI images, modeling and simulation. Future work outlier in segmentation and classification are given in conclusion

Parallel computing of numerical schemes and big data analytic for solving real life applications

This paper proposed the several real life applications for big data analytic using parallel computing software. Some parallel computing software under consideration are Parallel Virtual Machine, MATLAB Distributed Computing Server and Compute Unified Device Architecture to simulate the big data problems. The parallel computing is able to overcome the poor performance at the runtime, speedup and efficiency of programming in sequential computing. The mathematical models for the big data analytic are based on partial differential equations and obtained the large sparse matrices from discretization and development of the linear equation system. Iterative numerical schemes are used to solve the problems. Thus, the process of computational problems are summarized in parallel algorithm. Therefore, the parallel algorithm development is based on domain decomposition of problems and the architecture of difference parallel computing software. The parallel performance evaluations for distributed and shared memory architecture are investigated in terms of speedup, efficiency, effectiveness and temporal performance