There has been an increased interest in speech pattern analysis applications of Parkinsonism for building predictive telediagnosis and telemonitoring models. For this purpose, we have collected a ...wide variety of voice samples, including sustained vowels, words, and sentences compiled from a set of speaking exercises for people with Parkinson's disease. There are two main issues in learning from such a dataset that consists of multiple speech recordings per subject: 1) How predictive these various types, e.g., sustained vowels versus words, of voice samples are in Parkinson's disease (PD) diagnosis? 2) How well the central tendency and dispersion metrics serve as representatives of all sample recordings of a subject? In this paper, investigating our Parkinson dataset using well-known machine learning tools, as reported in the literature, sustained vowels are found to carry more PD-discriminative information. We have also found that rather than using each voice recording of each subject as an independent data sample, representing the samples of a subject with central tendency and dispersion metrics improves generalization of the predictive model.
In this paper, both a sliding mode controller (SMC) and proportional-integral-derivative (PID) controller are designed for a multi-degrees-of-freedom structure, which has an active mass damper (AMD) ...to suppress earthquakeor wind-induced vibration. Since the model might have uncertainties and/or parameter changes, a SMC has been included because of its robust character and performance. The structural system has five degrees of freedom and has been simulated against an initial displacement of the first floor. At the end of the paper, we present the time histories of the first floor, top floor, and AMD displacements, the control voltage and frequency response of the uncontrolled, PID controlled, and sliding mode controlled structures, and we discuss the results.
Full text
Available for:
NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
This paper presents a hardware-efficient memory allocation technique, called EMA, that detects the existence of any free block of requested size in memory. EMA can allocate a free memory block of any ...number of chunks in any part of memory without having any internal fragmentation. The gate-level design of the hardware unit, along with its area-time measurements is given in this paper. Simulation results indicate that EMA is fast and flexible enough to allocate/deallocate a free block in any part of memory resulting in efficient utilization of memory spaces. In addition, the VHDL synthesis with FPGA implementation shows that EMA has less complicated hardware, and is faster than the known hardware techniques.
Full text
Available for:
BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
In this paper, both a sliding mode controller (SMC) and proportional-integral-deriva ive (PID) controller are designed for a multi-degrees-of-freedom structure, which has an active mass damper AMD) ...to suppress earthquake- or wind-induced vibration. Since the model might have uncertainties and/or arameter changes, a SMC has been included because of its robust character and performance. The structu al system has five degrees of freedom and has been simulated against an initial displacement of the first flo r. At the end of the paper, we present the time histories of the first floor, top floor, and AMD displacements, e control voltage and frequency response of the uncontrolled, PID controlled, and sliding mode controlled tructures, and we discuss the results.
Full text
Available for:
NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
In exploratory association studies of genes with certain diseases, a single or a small number of genes (features) related with the diseases are selected 1 among many thousands investigated. We ...investigate the statistical bias and variance of simple yet common (correlation and mutual information based) feature selection algorithms using well-known cross-validation methods (leave-one-out and k-fold) on a gene finding study for hypertension prediction. Our findings show that selected genes are different for different methods and different cross-validation runs for both single gene selection and gene subset selection.
A computer-aided method for the design of lossless broadband matching networks with lumped elements and commensurate transmission lines is presented. The method is based on combining the simplifield ...real frequency technique with the algebraic network decomposition by Fettweis. To show the application of the Computer-Aided Design (CAD) approach, an UHF antenna matching problem is solved.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A numerical technique is presented to model and analyse interconnects encountered in the design of high speed/high frequency analog RF/microwave circuits with mixed, lumped and distributed elements ...to be implemented on-chip. In this method, the interconnect networks are modeled by lossless two-ports composed of simple lumped elements and commensurate transmission lines, which are defined by two-variable scatting functions.
Main reason of genetic defects is the disorders in gene regions which are responsible for coding the proteins necessary for normal body functions. By gene therapy, the regions with disorders can be ...detected and their genetic content can be changed for good. These regions may have special characteristics in terms of nucleotide dispersion which are beyond the known statistical norms of genome. In this study, such a characteristic is defined and its effect on predicting the strand direction of genomic reads (classification) is analyzed. By the analyses, it is observed that Canonical Correlation Analysis (CCA) method outperforms well known Support Vector Machines (SVM) approach considering the discrimination of reads according to their strand directions.
This paper proposes a combination of the Fast Wavelet Transform (FWT) and Adaptive Neuro-fuzzy Inference System (ANFIS) methods. The goal is classification of breast masses as benign or malignant by ...applying this method consecutively to the extracted features of the Region of Interests (ROIs). This study is developed to decrease the number of the missing cancerous regions or unnecessary biopsies. The neuro-fuzzy subtractive clustering classification method achieved a classification accuracy of 85% without using FWT multi-resolution analysis and 92% with FWT. The satisfying results demonstrate that the developed system could help the radiologists for a true diagnosis.
