AMA, Agricultural Mechanization in Asia, Africa and Latin America (AMA) (issn: 00845841) is a peer reviewed journal first published online after indexing scopus in 1982. AMA is published by Farm Machinery Industrial Research Corp and Shin-Norinsha Co. AMA publishes every subjects of general engineering and agricultural engineering. Shenyang Jianzhu Daxue Xuebao (Ziran Kexue Ban)/Journal of Shenyang Jianzhu University (Natural Science) General Medicine (ISSN:1311-1817) Chinese Journal of Evidence-Based Medicine Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Kexue Tongbao/Chinese Science Bulletin Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University
AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) is a peer-reviewed journal. The journal covers Agricultural and Biological Sciences and all sort of engineering topic. the journal's scopes are in the following fields but not limited to:
Recently there has been an increasing demand of an automated system for animal species identification, where it needs a perfect good knowledge, understanding of the nature under vision and proper efficient system design. Embedded systems nowadays are offering a brilliant solution. Based on nature of economic and feasibility of advanced, embedded technology is chosen. This paper proposes a design of real-time portable bioacoustics species identification system. It contains two major correlated modules apart, the identification module and the system control module. The identification module is to be implemented in FPGA hardware to achieve species identification process while the system control module will manage and control the entire system. The proposed system is a combination of hardware, software development and operating system customization. It is designed to be decentralize, therefore the need of any server is eliminated. It can be placed anywhere, can be viewed and accessed from anywhere through a web server built-in.
Effects of quarry dust and polypropylene fiber on compaction properties, shear strength parameters, and California bearing ratio (CBR) of a fly ash have been discussed in this paper. Quarry dust was added to a fly ash from 0 to 60% at an increment of 10%, compaction and soaked CBR tests were conducted on fly ash-quarry dust mixes and the optimum percentage of quarry dust was found out to be 40%. Polypropylene fiber was added to fly ash stabilized with optimum percentage of quarry dust, from 0 to 1.5% at an increment of 0.25%. Compaction, shear strength and soaked CBR tests were conducted on fly ash-quarry dust-polypropylene fiber mixes. From the test results the optimum percentage of polypropylene fiber was found out to be 1%. At the optimum percentage addition of quarry dust and polypropylene fiber there is slight decrease in maximum dry density and optimum moisture content, 28% increase in cohesion, 45% increase in angle of internal friction, and 597% increase in soaked CBR of the fly ash.
In VLSI design circuits, System-On-Chip consumes more area due to huge data volume in the hardware. In order to reduce that constraint, the size of the trace buffer should be maintained constant. The trace data should be compressed to acquire huge amount of data. To compress those data several conventional techniques has been followed. Here in the proposed system, an approach called Look-Up-Table based dictionary compression method for System-On-Chip is used. It implements dictionary in such way that the most of the test vector frequencies are calculated which is to compress the test data in an efficient manner. This compression technique holds three different test vectors of all zero’s, one’s and X’s value where most of benchmark circuitry frequency can be captured. This technique is implemented in those circuits using hardware description language and it is verified by XILINX Spartan-3E to know utilization of devices. Hence, it achieves more compression ratio with less area overhead without loss of data.
Convolutional coding is the most widely used coding technology for reliable data communication. At the receiver’s end, Viterbi decoders are used for extracting the message bits. A conventional Viterbi decoder not only occupies higher memory space, but also is computationally more complex. Though considerable research is performed in this area to overcome these challenges, an efficient architecture is yet to be developed. In this paper, feasibility of a soft computing technique that substitutes the Viterbi decoder has been explored. The proposed Viterbi decoder works satisfactorily in terms of accuracy in robust environment.
In a Wireless Sensor Network when an event is detected, the network traffic increases. It in turn increases the flow of data packets and congestion. Congestion in Wireless Sensor Network plays a vital role in degrading the performance of the network. Hence it necessitates, developing a novel technique to control congestion. In this paper, soft computing based congestion control technique is proposed. Fuzzy logic and neural network are the soft computing tools used for estimating the packet drop. The performance of the proposed technique is evaluated using Accuracy. From the results, it is proved that neural network based congestion control technique provides better results than fuzzy based congestion control technique.