The kinetic rate of combustion of electrode carbon in the temperature range of 1000-1200 k

Kinetic rates of combustion of electrode carbon particles were measured in a temperature range of 1000-1200 K. Spherical carbon particles of size 7-9 mm are burnt in hot streams of nitrogen-oxygen mixtures. The velocity and the temperature of the mixture were varied. To compensate for the mass transfer resistance to the flow of oxygen to the carbon surface a mass transfer experiment was carried out in the same apparatus. By using mass transfer coefficients from the above experiment kinetic rates are analysed statistically to give the following Arrhenius type correlation of the kinetic rate: where n is in the range of 0.3 to 0.5.     

Alternate Testing of RF Transceivers Using Optimized Test Stimulus for Accurate Prediction of System Specifications

In the recent past, with the emergence of System-on-Chip (SoC), focus has shifted towards testing system specifications rather than device or module specifications. While the problem of test accessibility for test stimulus application and response capture for such high-speed systems remains a challenge to the test engineers, new test strategies are needed which can address the problem in a practical manner. In this paper, the problem of testing the transmitter and the receiver subsystems of a RF transceiver for system level specification is addressed. Instead of using different conventional test stimuli for testing each of the system level specifications of RF subsystems, a specially crafted test stimulus is used for testing all the specifications from the response of the subsystem-under-test. A new simulation approach has also been developed to perform fast behavioral simulations in frequency domain for the system-under-test. In the test method, frequency domain test response spectra are captured and non-linear regression models are constructed to map the spectral measurements onto the specifications of interest. In the presented simulation results, the test stimuli have been validated using netlist level simulation of the subsystem-under-test and specifications have been predicted within an error of ±3% of the actual value.Soumendu Bhattacharya was born in Calcutta, India, in 1978. He received his Bachelors degree from Indian Institute of Technology, Kharagpur, India, in 2000. In 2002, he received the M.S.E.E. degree in electrical engineering from Georgia Institute of Technology, Atlanta, USA. He is currently working toward his Ph.D. degree. In the summer of 2001, he worked as a summer intern in National Semiconductor, Santa Clara, CA, USA. His research interests are in the area of test generation for mixed-signal and RF circuits and systems and design-for-test.Achintya Halder received the B.S. degree in electronics and electrical communication engineering from the Indian Institute of Technology, Kharagpur, in 1998. He worked as an IC design engineer with Texas Instruments until 2000. Currently, he is a Ph.D. student and a research assistant with the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta. His research area is analog/RF and mixed signal testing.Ganesh P. Srinivasan received the B.E. degree in Electronics and Communication Engineering from the National Institute of Technology and Science, University of Madras, Chennai (Madras), India, in 2002. He received the M.S. degree in Electrical and Computer engineering from the Georgia Institute of Technology, Atlanta, GA, in 2004 and is currently pursuing his Ph.D. degree in Electrical and Computer Engineering at the Georgia Institute of Technology, Atlanta, GA. His research interests include low cost testing approaches for analog/RF and mixed-signal circuits, and improving performance of low cost testers for enabling high quality tests.Abhijit Chatterjee received the Bachelor of Technology degree in electrical engineering from the Indian Institute of Technology, Kanpur, India, in 1981, the M.S. degree in electrical engineering and computer science from University of Illinois at Chicago in 1983 and the Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana-Champaign in 1990. Until December 1992, he was a Research Staff Member at the General Electric Research and Development Center in Schenectady, NY. His work has been cited by the Wall Street Journal and presented on a Japanese network TV program called High Tech Shower International. He is a collaborating partner in NASAs New Millennium Project. Dr. Abhijit Chatterjee is also the author of one U.S. patent and has over one hundred publications in referenced journals and conferences.     

Possibility to Use Hydrothermally Synthesized CuFeS<Subscript>2</Subscript> Nanocomposite as an Acceptor in Hybrid Solar Cell

Here we have approached the plausible use of CuFeS₂ nanocomposite as an acceptor in organic–inorganic hybrid solar cell. To produce CuFeS₂ nanocomposite, hydrothermal strategy was employed. The room-temperature XRD pattern approves the synthesized material as CuFeS₂ with no phase impurity (JCPDS Card no: 37-0471). The elemental composition of the material was analyzed from the TEM-EDX data. The obtained selected area electron diffraction (SAED) planes harmonized with the XRD pattern of the synthesized product. Optical band gap (4.14 eV) of the composite from UV–Vis analysis depicts that the synthesized material is belonging to wide band gap semiconductor family. The HOMO (? 6.97 eV) and LUMO (? 2.93 eV) positions from electrochemical study reveal that there is a possibility of electron transfer from MEH-PPV to CuFeS₂. The optical absorption and photoluminescence spectra of MEH-PPV:CuFeS₂ (donor:acceptor) composite were recorded sequentially by varying weight ratios. The monotonic blue shifting of the absorption peak position indicated the interaction between donor and acceptor materials. The possibility of electron transfer from donor (MEH-PPV) to acceptor (CuFeS₂) was approved with photoluminescence analysis. Subsequently, we have fabricated a hybrid solar cell by incorporating CuFeS₂ nanocomposite with MEH-PPV in open atmosphere and obtained 0.3% power conversion efficiency.     

Fault diagnosis in wireless sensor network using clonal selection principle and probabilistic neural network approach

The fault diagnosis in wireless sensor networks is one of the most important topics in the recent years of research work. The problem of fault diagnosis in wireless sensor network can be resembled with artificial immune system in many different ways. In this paper, a detection algorithm has been proposed to identify faulty sensor nodes using clonal selection principle of artificial immune system, and then the faults are classified into permanent, intermittent, and transient fault using the probabilistic neural network approach. After the actual fault status is detected, the faulty nodes are isolated in the isolation phase. The performance metrics such as detection accuracy, false alarm rate, false‐positive rate, fault classification accuracy, false classification rate, diagnosis latency, and energy consumption are used to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm gives superior results as compared with existing algorithms in terms of the performance metrics. The fault classification performance is measured by fault classification accuracy and false classification rate. It has also seen that the proposed algorithm provides less diagnosis latency and consumes less energy than that of the existing algorithms proposed by Mohapatra et al, Panda et al, and Elhadef et al for wireless sensor network.     

Fault diagnosis in wireless sensor network using negative selection algorithm and support vector machine

In this article, an improved negative selection algorithm (INSA) has been proposed to identify faulty sensor nodes in wireless sensor network (WSN) and then the faults are classified into soft permanent, soft intermittent, and soft transient fault using the support vector machine technique. The performance metrics such as fault detection accuracy, false alarm rate, false positive rate, diagnosis latency (DL), energy consumption, fault classification accuracy (FCA), and false classification rate (FCR) are used to evaluate the performance of the proposed INSA. The simulation result shows that the INSA gives better result as compared to the existing algorithms in terms of performance metrics. The fault classification performance is measured by FCA and FCR. It has also seen that the proposed algorithm gives less DL and consumes less energy than that of existing algorithms proposed by Mohapatra et al, Zhang et al, and Panda et al for WSN.     

Fire Controlling Under Uncertainty in Urban Region Using Smart Vehicular Ad hoc Network

Every year thousands of urban and industrial fires occur, which leads to the destruction of infrastructure, buildings, and loss of lives. One of the reasons behind this is the delayed transmission of information to the fire station and the nearer hospitals for ambulance service as the transmission of information is dependent on observer at the location where the fire is caught and cellular network. This paper proposed an automated routing protocol for the urban vehicular ad-hoc network to send the information from the location where the fire is caught to the nearest fire stations and hospitals with optimum service time. This transmission of information involves Road Side Unit (RSU) at the junction and the vehicles present in the transmission path. Selection of route to transmit faulty vehicle information from the RSU to the required faulty vehicle is based on a parameter called path value. The computation of path value is done by the attributes such as expected End To End (E2E) delay, the shortest distance to destination, the density of vehicle between the junctions, and attenuation. From the current junction, the selection of the next junction is based on minimum path value. The proposed routing protocol considers the performance parameters such as E2E delay, total service time (TST), number of network fragments or network gaps, number of hops, and attenuation for the propagation path for the evaluation of the proposed methodology. The proposed routing algorithm is implemented through OmNet++ and SUMO. Results obtained for the proposed routing protocol is compared with three existing VANET protocols (GSR, A-STAR, and ARP) in terms of End To End delay, number of hops, number of vehicular gaps, and Total Service Time (TST).