This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence. 相似文献
Crowded urban environments are composed of different types of dynamic and static elements. Learning and classification of features is a major task in solving the localization problem in such environments. This work presents a gradual learning methodology to learn the useful features using multiple experiences. The usefulness of an observed element is evaluated by a scoring mechanism which uses two scores – reliability and distinctiveness. The visual features thus learned are used to partition the visual map into smaller regions. The robot is efficiently localized in such a partitioned environment using two-level localization. The concept of active map (AM) is proposed here, which is a map that represents one partition of the environment in which there is a high probability of the robot existing. High-level localization is used to track the mode of the AMs using discrete Bayes filter. Low-level localization uses a bag-of-words model to retrieve images and accurately localize the robot. The pose of the robot is the one retrieved from the AM that has maximum a posteriori. Experiments have been conducted on a unique highly crowded data-set collected from Indian roads. The results support the proposed method due to speed and localization accuracy. 相似文献
Emotion recognition from speech signals is an interesting research with several applications like smart healthcare, autonomous voice response systems, assessing situational seriousness by caller affective state analysis in emergency centers, and other smart affective services. In this paper, we present a study of speech emotion recognition based on the features extracted from spectrograms using a deep convolutional neural network (CNN) with rectangular kernels. Typically, CNNs have square shaped kernels and pooling operators at various layers, which are suited for 2D image data. However, in case of spectrograms, the information is encoded in a slightly different manner. Time is represented along the x-axis and y-axis shows frequency of the speech signal, whereas, the amplitude is indicated by the intensity value in the spectrogram at a particular position. To analyze speech through spectrograms, we propose rectangular kernels of varying shapes and sizes, along with max pooling in rectangular neighborhoods, to extract discriminative features. The proposed scheme effectively learns discriminative features from speech spectrograms and performs better than many state-of-the-art techniques when evaluated its performance on Emo-DB and Korean speech dataset.
The effect of Ag on the stationary and non-stationary anodic corrosion rates of PbSbCd and PbSb alloys in H2SO4 has been studied. Anodic polarization curves were constructed under galvanostatic and potentiostatic conditions. Optical microscopic examination and microprobe analysis of the alloys were conducted. The beneficial effect of Ag was ascribed to a delay in closure of pores in the initial PbSO4 film. The leaching out of Sb from the outermost layers and the simultaneous nucleation of PbSO4 and Ag2SO4 from supersaturated solutions in the pores is thus made possible. 相似文献
Global rise of infections and deaths caused by drug-resistant bacterial pathogens are among the unmet medical needs. In an age of drying pipeline of novel antibiotics to treat bacterial infections, antimicrobial peptides (AMPs) are proven to be valid therapeutics modalities. Direct in vivo applications of many AMPs could be challenging; however, works are demonstrating encouraging results for some of them. In this review article, we discussed 3-D structures of potent AMPs e.g., polymyxin, thanatin, MSI, protegrin, OMPTA in complex with bacterial targets and their mode of actions. Studies on human peptide LL37 and de novo-designed peptides are also discussed. We have focused on AMPs which are effective against drug-resistant Gram-negative bacteria. Since treatment options for the infections caused by super bugs of Gram-negative bacteria are now extremely limited. We also summarize some of the pertinent challenges in the field of clinical trials of AMPs. 相似文献
Rare earths(REs) play a key role in distorting spinel structure by creating some defects at the lattice sites and make them suitable for magnetodielectric applications.In the present study,the nanoferrites of CuRE_(0.02)Fe_(1.98)O_4,where REs=Y~(3+),Yb~(3+),Gd~(3+),were prepared using one step sol-gel method.The prepared samples are copper ferrite(CFO),yttrium doped copper ferrite(Y-CFO),ytterbium doped copper ferrite(Yb-CFO) and gadolinium doped copper ferrite(Gd-CFO),respectively.The single-phase structure of all the REs doped nanoferrites was determined by X-ray diffraction(XRD) analysis.The porosity,agglomerations and grain size of the REs doped copper ferrite were examined using field emission scanning electron microscopy(FESEM) analysis.Fourier transform infrared spectroscopy(FTIR)elaborates the phase formation and environmental effects on the REs doped nanoparticles(NPs).The recorded room temperature M-H loops from a vibrating sample magnetometer(VSM) elucidate the magnetic properties of the REs doped spinel nanoferrites.The magnetic saturation(M_s) was calculated in the range of 23.08 to 51.78 emu/g.The calculated coercivity values(272.6 to 705.60 Oe) confirm the soft magnetic behavior of REs doped copper ferrites.Furthermore,the electromagnetic and dielectric properties were assessed using a Vector network analyzer(VNA) from 1 to 6 GHz.The permeability,permittivity,dielectric tangent loss and electric modulus of the REs doped spinel ferrites illustrate that the prepared NPs may be suitable for microwave and high frequency applications. 相似文献
Clostridium butyricum EB6 successfully produced hydrogen gas from palm oil mill effluent (POME). In this study, central composite design and response surface methodology were applied to determine the optimum conditions for hydrogen production (Pc) and maximum hydrogen production rate (Rmax) from POME. Experimental results showed that the pH, temperature and chemical oxygen demand (COD) of POME affected both the hydrogen production and production rate, both individually and interactively. The optimum conditions for hydrogen production (Pc) were pH 5.69, 36 °C, and 92 g COD/l; with an estimated Pc value of 306 ml H2/g carbohydrate. The optimum conditions for maximum hydrogen production rate (Rmax) were pH 6.52, 41 °C and 60 g COD/l; with an estimated Rmax value of 914 ml H2/h. An overlay study was performed to obtain an overall model optimization. The optimized conditions for the overall model were pH 6.05, 36 °C and 94 g COD/l. The hydrogen content in the biogas produced ranged from 60% to 75%. 相似文献
Communication systems are needed to integrate generated power from wind farms with the electrical grid. This paper provides a comprehensive review of available communication technologies, protocols and objectives related to wind energy and electrical grid integration. This paper summarizes the communication system solutions for wind generation. A major obstacle is an absence of unified communication architectures and standards. 相似文献