Outage Performance of Cognitive DF Relaying Networks Employing SWIPT

In this paper, the outage perfor- mance of a cognitive relaying network over Nakagami-m fading channels, employing simultaneous wireless information and power transfer （SWIPT） technology is analyzed and evaluated. The operation of this network is considered in conjunction with the convention- al decode-and-forward （DF） and incremental DF （IDF） protocols. For the conventional DF protocol, it is assumed that there is no direct link between the secondary transmitter （S） and the secondary destination （D）, while （for both protocols） after harvesting energy, the relay node （R） always helps to forward the resulting signal to D. However, for the IDF protocol, R assists in relaying S＇s information to D only when the direct communication between S and D has failed. Furthermore, for both DF and IDF protocols, we assume there is no power supply for R, and R harvests energy from the transmitted signal of S. We derive exact ana- lytical expressions for the outage probability at D in DF and IDF protocols, respectively, in terms of the bivariate Meijer＇s G-function. Performance evaluation results obtained by means of Monte-Carlo simulations are also provided and have validated the correctness of the oroDosed analysis.

Modified Natural Zeolites as Catalysts for Catalytic Reduction of NO with COmMain Components of Exhaust Gases

The study of oxidized-reduced properties of modified natural zeolites from deposits of Georgia--clinoptilolite and mordenite in reaction of reduction NO with H2, NH3, CH4 and especially CO was carried out for the purpose to obtain effective catalyst for afterburning of toxic components of automobile exhaust. The activity of zeolites essentially depends on nature of cation and temperature of reaction and slightly depends on structure of zeolite and ratio of reactants. The introduction of copper and iron ions in preliminary decationated clinoptilolite and mordenite causes growth of conversion degree of nitrogen and carbon monoxides almost on a degree, especially in low temperature interval. The reaction between NO and CO molecules proceeds in coordinative sphere of TM cations through formation ofnitrosyl and carbonyl complexes.

Measuring the Complexity of Business Organization and Business Software Using Analytic Hierarchy Process （AHP）

The paper shows a proposition of metrics for measuring the complexity of the business organization and business software. The metrics is based on a subjective estimation of complexity of the elements from a part of the structure of business organization or business software in relation to other elements from the observed part. Estimation is performed based on the measuring scale for comparison of complexity of elements, and reaching a final conclusion on the complexity of elements in relation to other elements, through the Analytic Hierarchy Process （AHP）. Defined in this manner, the metrics represents a unique metrics for measuring the complexity of elements of business organization and business software, which enables their comparison. The paper also presents a short overview of existing metrics for measuring the complexity of business organization and business software.

Automated Building Block Extraction and Building Density Classification Using Aerial Imagery and LiDAR Data

This paper examines the utility of high-resolution airborne RGB orthophotos and LiDAR data for mapping residential land uses within the spatial limits of suburb of Athens, Greece. Modem remote sensors deliver ample information from the AOI （area of interest） for the estimation of 2D indicators or with the inclusion of elevation data 3D indicators for the classification of urban land. In this research, two of these indicators, BCR （building coverage ratio） and FAR （floor area ratio） are automatically evaluated. In the pre-processing step, the low resolution elevation data are fused with the high resolution optical data through a mean-shift based discontinuity preserving smoothing algorithm. The outcome is an nDSM （normalized digital surface model） comprised of upsampled elevation data with considerable improvement regarding region filling and ＂straightness＂ of elevation discontinuities. Following this step, a MFNN （multilayer feedforward neural network） is used to classify all pixels of the AOI into building or non-building categories. The information derived from the BCR and FAR building indicators, adapted to landscape characteristics of the test area is used to propose two new indices and an automatic post-classification based on the density of buildings.

A Stochastic Model for Protein Synthesis and Activation through RNA-Protein Interaction in BioAmbients Calculus

Cells use various RNA （Ribonucleic Acid） regulatory mechanisms in order to temporally and coordinately influence the rate of protein synthesis. A deeper understanding of the dynamics of RNA regulation can ultimately bridge the gap between transcriptional control and protein expression. The nonlinear process of RNA-Protein Interaction （RIP）, which can be viewed as the RNA analog of the better-known chromatin immunoprecipitation application （CHIP） plays a crucial role in post-transcriptional regulation of gene expression. While ChIP identifies DNA （Deoxyribonucleic Acid） targets of DNA-binding proteins in their cellular context, RIP can be used to identify specific RNA molecules associated with specific nuclear or cytoplasmic RNA-binding proteins. In this paper, a stochastic model in BioAmbients calculus for the protein synthesis and activation through RIP process is presemed.

The Merits of Passive Compliant Joints in Legged Locomotion： Fast Learning, Superior Energy Efficiency and Versatile Sensing in a Quadruped Robot

A quadruped robot with four actuated hip joints and four passive highly compliant knee joints is used to demonstrate the potential of underactuation from two standpoints： learning locomotion and perception. First, we show that： （i） forward locomotion on flat ground can be learned rapidly （minutes of optimization time）; （ii） a simulation study reveals that a passive knee configuration leads to faster, more stable, and more efficient locomotion than a variant of the robot with active knees; （iii） the robot is capable of learning turning gaits as well. The merits of underactuation （reduced controller complexity, weight, and energy consumption） are thus preserved without compromising the versatility of behavior. Direct optimization on the reduced space of active joints leads to effective learning of model-free controllers. Second, we find passive compliant joints with po- tentiometers to effectively complement inertial sensors in a velocity estimation task and to outperform inertial and pressure sensors in a terrain detection task. Encoders on passive compliant joints thus constitute a cheap and compact but powerful sensing device that gauges joint position and force/torque, and -- if mounted more distally than the last actuated joints in a legged robot -- it delivers valuable information about the interaction of the robot with the ground.

A study of optimal switching problem in limited-cycle with multiple periods

In a social system or production line,the restrictions of the cost and the due-time exist in each period.Generally,whether these restrictions are satisfied is dependent not only on the risks of this period,but also on the risks generated beforehand.We consider controlling the production process by switching the processing rate to a faster one at a given period.This paper deals with the optimal switching period to minimize the total expected cost of the production process.We first propose the optimal switching period model,and then the mathematic formulation of the total expectation is presented.Finally,the policy of optimal switching period is investigated in detail by numerical experiments.