Solar Energy Harvesting Using a Timer-Based Relay Selection

In this paper,the throughput and delay of cooperative communications are derived when solar energy is used and relay node is selected using a timer.The source and relays harvest energy from sun using a photo voltaic system.The harvested power is used by the source to transmit data to the relays.Then,a selected relay amplifies the signal to the destination.Opportunistic,partial and reactive relay selection are used.The relay transmits when its timer elapses.The timer is set to a value proportional to the inverse of its Signal to Noise Ratio(SNR).Therefore,the relay with largest SNR will transmit first and its signal will be detected by the other relays that will remain idle to avoid collisions.Harvesting duration is optimized to maximize the throughput.Packet’s waiting time and total delay are also computed.We also derive the statistics of SNR when solar energy is used.The harvested power from sun is proportional to the sum of a deterministic radiation intensity and a random attenuation due to weather effects and clouds occlusion.The fixed radiation intensity depends on season,month and time t in hour.The throughput of cooperative communications with energy harvesting from sun was not yet studied.

Selection of Sinopec Lubricating Oil Producing Bases by Using the AHP Model

The factors affecting the developmcnt of Sinopec lubricating oil were analyzed in this paper, and an analytic hierarchy process （AHP） model for selecting lubricating-oil producing bases was developed. By using this model, nine lubricating oil producing companies under Sinopec were comprehensively evaluated. The evaluation result showed that the Maoming Lubricating Oil Company （Guangdong province）, Jingmen Lubricating Oil Company （Hubei province） and Changcheng Lube Oil Company （Beijing） are top three choices, and should be developed preferentially for the development of Sinopec producing bases of lubricating oil in the future. The conclusions provide the theoretical basis for selecting lubricating oil producing bases for decision makers.

An Intrusion Detection System for SDN Using Machine Learning

Software Defined Networking(SDN)has emerged as a promising and exciting option for the future growth of the internet.SDN has increased the flexibility and transparency of the managed,centralized,and controlled network.On the other hand,these advantages create a more vulnerable environment with substantial risks,culminating in network difficulties,system paralysis,online banking frauds,and robberies.These issues have a significant detrimental impact on organizations,enterprises,and even economies.Accuracy,high performance,and real-time systems are necessary to achieve this goal.Using a SDN to extend intelligent machine learning methodologies in an Intrusion Detection System(IDS)has stimulated the interest of numerous research investigators over the last decade.In this paper,a novel HFS-LGBM IDS is proposed for SDN.First,the Hybrid Feature Selection algorithm consisting of two phases is applied to reduce the data dimension and to obtain an optimal feature subset.In thefirst phase,the Correlation based Feature Selection(CFS)algorithm is used to obtain the feature subset.The optimal feature set is obtained by applying the Random Forest Recursive Feature Elimination(RF-RFE)in the second phase.A LightGBM algorithm is then used to detect and classify different types of attacks.The experimental results based on NSL-KDD dataset show that the proposed system produces outstanding results compared to the existing methods in terms of accuracy,precision,recall and f-measure.

Prediction of Gas Chromatographic Retention Indices of Organophosphates by DFT and VSMP Method

Polychlorinated dibenzothiophenes（PCDTs） are a group of important persistent organic pollutants.In the present study,geometrical optimization and electrostatic potential calculations have been performed for all 135 PCDTs congeners at the B3LYP/6-31G＊ level of theory.By means of the VSMP（variable selection and modeling based on prediction） program,one optimal descriptor（molecular polarizability,α） was selected to develop a QSRR model for the prediction of gas chromatographic retention indices（GC-RI） of PCDTs.The estimated correlation coefficients（r2） and LOO-validated correlation coefficients（q2）,all more than 0.99,were built by multiple linear regression,which shows a good estimation ability and stability of the models.A prediction power for the external samples was validated by the model built from the training set with 17 polychlorinated dibenzothiophenes.

Apple leaf disease identification using genetic algorithm and correlation based feature selection method

Apple leaf disease is one of the main factors to constrain the apple production and quality.It takes a long time to detect the diseases by using the traditional diagnostic approach,thus farmers often miss the best time to prevent and treat the diseases.Apple leaf disease recognition based on leaf image is an essential research topic in the field of computer vision,where the key task is to find an effective way to represent the diseased leaf images.In this research,based on image processing techniques and pattern recognition methods,an apple leaf disease recognition method was proposed.A color transformation structure for the input RGB(Red,Green and Blue)image was designed firstly and then RGB model was converted to HSI(Hue,Saturation and Intensity),YUV and gray models.The background was removed based on a specific threshold value,and then the disease spot image was segmented with region growing algorithm(RGA).Thirty-eight classifying features of color,texture and shape were extracted from each spot image.To reduce the dimensionality of the feature space and improve the accuracy of the apple leaf disease identification,the most valuable features were selected by combining genetic algorithm(GA)and correlation based feature selection(CFS).Finally,the diseases were recognized by SVM classifier.In the proposed method,the selected feature subset was globally optimum.The experimental results of more than 90%correct identification rate on the apple diseased leaf image database which contains 90 disease images for there kinds of apple leaf diseases,powdery mildew,mosaic and rust,demonstrate that the proposed method is feasible and effective.

Compact on-chip 1×2 wavelength selective switch based on silicon microring resonator with nested pairs of subrings

We propose and experimentally demonstrate compact on-chip 1×2 wavelength selective switches(WSSs) based on silicon microring resonators(MRRs) with nested pairs of subrings(NPSs). Owing to the resonance splitting induced by the inner NPSs, the proposed devices are capable of performing selective channel routing at certain resonance wavelengths of the outer MRRs. System demonstration of dynamic channel routing using fabricated devices with one and two NPSs is carried out for 10 Gb∕s non-return-to-zero signal. The experimental results verify the effectiveness of the fabricated devices as compact on-chip WSSs.

Sorbents with high efficiency for CO2 capture based on amines-supported carbon for biogas upgrading

Sorbents for CO2 capture have been prepared by wet impregnation of a commercial active carbon （Ketjen-black, Akzo Nobel） with two CO2-philic compounds, polyethylenimine （PEI） and tetraethylenepentamine （TEPA）, respectively. The effects of amine amount （from 10 to 70 wt.%）, CO2 concentration in the feed, sorption temperature and gas hourly space velocity on the CO2 capture performance have been investigated. The sorption capacity has been evaluated using the breakthrough method, with a fixed bed reactor equipped with on line gas chromatograph. The samples have been characterized by N2 adsorption-desorption, scanning electron microscopy and energy dispersive X-ray （SEM/EDX）. A promising CO2 sorption capacity of 6.90 mmo1/gsorbent has been obtained with 70 wt.% of supported TEPA at 70℃ under a stream containing 80 vol% of CO2. Sorption tests, carried out with simulated biogas compositions （CH4/CO2 mixtures）, have revealed an appreciable CO2 separation selectivity; stable performance was maintained for 20 adsorption-desorption cycles.

Superimposed Fiber Gratings Based Wavelength Selectable Fiber Laser

A novel wavelength selectable fiber ring laser was proposed. Superimposed fiber Bragg gratings with uniform reflectivity were made to serve as comb-like filter. Optical tunable filter combined with the comb filter realized fast and accurately wavelength selectivity. The SMSR at each wavelength is more than 50dB.

Step-size selection for split-step based nonlinear compensation with coherent detection in 112-Gb/s 16-QAM transmission

Non-uniform step-size distribution is implemented for split-step based nonlinear compensation in singlechannel 112-Gb/s 16 quadrature amplitude modulation （QAM） transmission. Numerical simulations of the system including a 20 × 80 km uncompensated link are performed using logarithmic step size distribution to compensate signal distortions. 50% of reduction in number of steps with respect to using constant step sizes is observed. The performance is further improved by optimizing nonlinear calculating position （NLCP） in case of using constant step sizes while NLCP optimization becomes unnecessary when using logarithmic step sizes, which reduces the computational effort due to uniformly distributed nonlinear phase for all successive steps.

850 nm centered wavelength-swept laser based on a wavelength selection galvo filter

A wavelength-swept laser is constructed using a free space external cavity configuration coupled with a fiber- based ring cavity at the 850 nm region. The external cavity filter employs a galvo-mirror scanner with a diffraction grating for wavelength selection. The filter is connected to a ring cavity through an optical circulator. The ring cavity contains a broadband semiconductor optical amplifier with a high optical output. The perfor- mance of this laser is demonstrated with broad bandwidths and narrow linewidths. The 3 dB linewidth and the bandwidth of this source are 0.05 nm （-20 GHz） and 48 nm, respectively. The maximum output power is 26 mW at 160 mA current.

Radiometric calibration of hyper-spectral imaging spectrometer based on optimizing multi-spectral band selection

Hyper-spectral imaging spectrometer has high spatial and spectral resolution. Its radiometric calibration needs the knowledge of the sources used with high spectral resolution. In order to satisfy the requirement of source, an on-orbit radiometric calibration method is designed in this paper. This chain is based on the spectral inversion accuracy of the calibration light source. We compile the genetic algorithm progress which is used to optimize the channel design of the transfer radiometer and consider the degradation of the halogen lamp, thus realizing the high accuracy inversion of spectral curve in the whole working time. The experimental results show the average root mean squared error is 0.396%, the maximum root mean squared error is 0.448%, and the relative errors at all wavelengths are within 1% in the spectral range from 500 nm to 900 nm during 100 h operating time. The design lays a foundation for the high accuracy calibration of imaging spectrometer.

Expert systems for HPLC in biochemistry—The knowledge base for selection of HPLC column system in the separation of amino acids, peptides and proteins

The strategy of expert system for high performance liquid chromatography was discussed, the attentions are mainly placed on the knowledge base for selection of column system, separation modes and detection modes in the analysis of amino acids, peptides and proteins.

Traditional Chinese medicinal herbs combined with epidermal growth factor receptor tyrosine kinase inhibitor for advanced non-small cell lung cancer: a systematic review and meta-analysis

BACKGROUND： Epidermal growth factor receptor tyrosine kinase inhibitor （EGFR-TKI） targeted treatment has been a standard therapy for advanced non-small cell lung cancer （NSCLC）, but it is not tolerated well by all patients. In China, some studies have reported that traditional Chinese medicinal herbs （TCMHs） may increase efficacy and reduce toxicity when combined with EGFR-TKI, but outside of China few studies of this kind have been attempted. OBJECTIVE： This study is intended to systematically review the existing clinical evidence on TCMHs combined with EGFR-TKI for treatment of advanced NSCLC. SEARCH STRATEGY： PubMed, the Cochrane Library, the Excerpta Medica Database （EMBASE）, the China BioMedical Literature （CBM）, and the China National Knowledge Infrastructure （CNKI） and web site of the American Society of Clinical Oncology （ASCO）, the European Society for Medical Oncology （ESMO）, the World Conference of Lung Cancer （WCLC） were searched; the search included all documents published in English or Chinese before October 2013. INCLUSION CRITERIA： We selected randomized controlled trials based on specific criteria, the most important of which was that a TCMH plus EGFR-TKI treatment group was compared with an EGFR-TKI control group in patients with advanced NSCLC. DATA EXTRACTION AND ANALYSIS： The modified Jadad scale was used to assess the quality of studies. For each included study, patient characteristics, treatment details, therapeutic approach and clinical outcomes were collected on a standardized form. When disagreements on study inclusion or data extracted from a study emerged, the consensus of all coauthors provided the resolution. The clinical outcome metrics consisted of objective response rate （ORR; complete response ＋ partial response divided by the total number of patients）, disease control rate （DCR; complete response ＋ partial response ＋ no change divided by the total number of patients）, survival rate, improved or stabilized Karnofsky performance status （KPS）, and severe toxicity. RevMan 5.0 software was used for data syntheses and analyses. Risk ratio （RR） and 95% confidence interval （CI） were calculated; if the hypothesis of homogeneity was not rejected （P〉0.1, I2〈50%）, the fixed-effect model was used to calculate the summary RR and the 95% CI. Otherwise, a random-effect model was used.

Microstructure Characteristics of Inconel 625 Superalloy Manufactured by Selective Laser Melting

Selective laser melting （SLM）, an additive manufacturing process, is capable of manufacturing metallic parts with complex shapes directly from computer-aided design （CAD） models. SLM parts are created on a layer-by-layer manner, making it more flexible than traditional material processing techniques, in this paper, Inconel 625 alloy, a widely used material in the aerospace industry, were chosen as the build material. Scanning electron microscopy （SEM）, electron back scattering diffraction （EBSD） and X-ray diffraction （XRD） analysis techniques were employed to analyze its microstructure. It was observed that the molten pool was composed of elongated columnar crystal, Due to the rapid cooling speed, the primary dendrite arm space was approximately 0.5 μm and the hardness of SLM state was very high （343 HV）. The inverse pole figure （IPF） indicated that the growing orientation of the most grains was 〈001〉 due to the epitaxial growth and heat conduction. The XRD results revealed that the austenite structure with large lattice distortion was fully formed. No carbides or precipitated phases were found. After heat treatment the grains grew into two microstructures with distinct morphological characters, namely, rectangular grains and limited in the molten pool, and equiaxed grains along the molten boundaries. Upon experiencing the heat treatment, MC carbides with triangular shapes gradually precipitated. The results also identified that a large number of zigzag grain boundaries were formed. In this study, the grain formation and microstructure, and the laws of the molten pool evolution were also analyzed and discussed,

Computing a ground appropriateness index for route selection in permafrost regions

The reasonable calculation of ground appropriateness index in permafrost region is the precondition of highway route design in permafrost region. The theory of knowledge base and fuzzy mathematics are applied, and the damage effect of permafrost is considered in the paper. Based on the idea of protecting permafrost the calculation method of ground appro- priateness index is put forward. Firstly, based on the actual environment conditions, the paper determines the factors affecting the road layout in permafrost areas by qualitative and quantitative analysis, including the annual slope, the average annual ground temperature of permafrost, the amount of ice in frozen soil, and the interference engineering. Secondly, based on the knowledge base theory and the use of Delphi method, the paper establishes the knowledge base, the rule base of the permafrost region and inference mechanism. The method of selecting the road in permafrost region is completed and realized by using the software platform. Thirdly, taking the Tuotuo River to Kaixin Mountain section of permafrost region as an example, the application of the method is studied by using an ArcGIS platform. Results show that the route plan determined by the method of selecting the road in perma-frost region can avoid the high temperature and high ice content area, conform the terrain changes and evade the heat disturbance among the existing projects. A reasonable route plan can be achieved, and it can provide the basis for the next engineering construction.