Search results for: signal blocking

Authors: Cheng-Cao Sun, Shu-Jun Li, De-Jia Li

Abstract:

Determinants of growth and metastasis in cancer remain of great interest to define. MicroRNAs (miRNAs) have frequently emerged as tumor metastatic regulator by acting on multiple signaling pathways. Here, we report the definition of miR-346 as an oncogenic microRNA that facilitates non-small cell lung cancer (NSCLC) cell growth and metastasis. XPC, an important DNA damage recognition factor in nucleotide excision repair was defined as a target for down-regulation by miR-346, functioning through direct interaction with the 3'-UTR of XPC mRNA. Blocking miR-346 by an antagomiR was sufficient to inhibit NSCLC cell growth and metastasis, an effect that could be phenol-copied by RNAi-mediated silencing of XPC. In vivo studies established that miR-346 overexpression was sufficient to promote tumor growth by A549 cells in xenografts mice, relative to control cells. Overall, our results defined miR-346 as an oncogenic miRNA in NSCLC, the levels of which contributed to tumor growth and invasive aggressiveness.

Keywords: microRNA-346, miR-346, XPC, non-small cell lung cancer, oncogenesis

Procedia PDF Downloads 286

Authors: Eunseop Yeom

Abstract:

Many cardiovascular diseases, such as thrombosis and atherosclerosis, can change biochemical molecules in plasma and red blood cell. These alterations lead to excessive increase of blood viscosity contributing to peripheral vascular diseases. In this study, a simple microfluidic-based method is used to measure blood viscosity. Microfluidic device is composed of two parallel side channels and a bridge channel. To estimate blood viscosity, blood samples and reference fluid are separately delivered into each inlet of two parallel side channels using pumps. An interfacial line between blood samples and reference fluid occurs by blocking the outlet of one side-channel. Since width for this interfacial line is determined by pressure ratio between blood and reference flows, blood viscosity can be estimated by measuring width for this interfacial line. This microfluidic-based method can be used for evaluating variations in the viscosity of animal models with cardiovascular diseases under flow conditions.

Keywords: blood viscosity, microfluidic chip, pressure, shear rate

Procedia PDF Downloads 344

Authors: Nana Weng

Abstract:

Localization in the aspect of human resource means more diversity and more opportunities. The main purpose of this article is to identify the perception of local employees and intermediate managers (non-Japanese) and figure out exploratory factors which have been contributing and blocking the level of localization in the aspect of human resource management by using EFA (Exploratory Factors Analysis). Questionnaires will be designed for local employees and managers to inquire about the perceptions of regulations and implementation regarding recruitment, training and development, promotion and rewarding. The study finds that Japanese firms have worked well in the process of localization, especially in hiring and training local staffs in Taiwan. The significance of this study lies in paying more attention to the perception of local employees and intermediate managers regarding localization rather than interviews results from Japanese expatriates or top HR managers who are in charging of localization policy-making.

Keywords: Japanese firms in Taiwan, localization of human resources, exploratory factors analysis, local employees and intermediate managers

Procedia PDF Downloads 285

Authors: Mokhtar Nikgoo

Abstract:

Definition of bridge: A bridge is a structure that allows people to pass through the communication road with two points. There are many different types of bridges, each of which is designed to perform a specific function. This article introduces the concept, history, components, uses, types, construction methods, selected factors, damage factors and principles of bridge maintenance. A bridge is a structure to cross a passage such as a water, valley or road without blocking another path underneath. This structure makes it possible to pass obstacles that are difficult or impossible to pass. There are different designs for bridge construction, each of which is used for a particular function and condition. In the old definition, a bridge is an arch over a river, valley, or any type of passage that makes traffic possible. But today, in the topic of urban management, the bridge is considered as a structure to cross physical barriers, so that while using space (not just the surface of the earth), it can facilitate the passage and access to places. The useful life of bridges may be between 30 and 80 years depending on the location and the materials used. But with proper maintenance and improvement, their life may last for hundreds of years.

Keywords: bridge, road construction, surveying, transportation

Procedia PDF Downloads 488

Authors: Sallama Resen, Celal Öztürk

Abstract:

Distance estimation between tow nodes has wide scope of surveillance and tracking applications. This paper suggests a Bluetooth Low Energy (BLE) technology as a media for transceiver and receiver signal in small indoor areas. As an example, BLE communication technologies used in child safety domains. Local network is designed to detect child position in indoor school area consisting Mobile Beacons (MB), Access Points (AP) and Smart Phones (SP) where MBs stuck in children’s shoes as wearable sensors. This paper presents a technique that can detect mobile beacons’ position and help finding children’s location within dynamic environment. By means of bluetooth beacons that are attached to child’s shoes, the distance between the MB and teachers SP is estimated with an accuracy of less than one meter. From the simulation results, it is shown that high accuracy of position coordinates are achieved for multi-mobile beacons in different environments.

Keywords: bluetooth low energy, child safety, mobile beacons, received signal strength

Procedia PDF Downloads 327

Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin

Abstract:

A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.

Keywords: C-FAST- a valid and reliable device, distant cellular interaction, electromagnetic signal detection, non-invasive diagnosis of HCV

Procedia PDF Downloads 414

Authors: Meet Patel, Darshan Patel, Nilay Shah

Abstract:

Excess growth of wind-based renewable energy sources is required to identify the optimal location and damping capacity of doubly fed induction-generator-based (DFIG) wind farms while it penetrates into the transmission network. In this analysis, various ratings of DFIG wind farms are penetrated into the Single Machine Infinite Bus (SMIB ) at a different distance of the transmission line. On the basis of detailed examinations, a prime position is evaluated to maximize the stability of overall systems. A damping controller is designed at an optimum location to mitigate the small oscillations. The proposed model was validated using eigenvalue analysis, calculation of the participation factor, and time-domain simulation.

Keywords: DFIG, small signal stability, eigenvalues, time domain simulation

Procedia PDF Downloads 84

Authors: Sudhina H. K, Ravi M. Yadahalli, N. M. Shetti

Abstract:

Reconfigurable antennas represent a recent innovation in antenna design that changes from classical fixed-form, Fixed function antennas to modifiable structures that can be adapted to fit the requirements of a time varying system. The ability to control the operating band of an antenna system can have many useful applications. Systems that operate in an acquire-and-track configuration would see a benefit from active bandwidth control. In such systems a wide band search mode is first employed to find a desired signal, Then a narrow band track mode is used to follow only that signal. Utilizing active antenna bandwidth control, A single antenna would function for both the wide band and narrow band configurations providing the rejection of unwanted signals with the antenna hardware. This ability to move a portion of the RF filtering out of the receiver and onto the antenna itself will also aid in reducing the complexity of the often expensive RF processing subsystems.

Keywords: designing methods, mems, stack, reconfigurable elements

Procedia PDF Downloads 251

Authors: Hamidreza Namazi

Abstract:

Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 441

Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

Abstract:

This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

Procedia PDF Downloads 48

Authors: K. Yahia, A. Titaouine, A. Ghoggal, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), inter-turn short-circuits diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 529

Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

Abstract:

Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

Procedia PDF Downloads 85

Authors: Nikita Rajendra Sharma, Jai Prakash Kushvah, Gerhard Rinkenauer

Abstract:

Driving a car is a discrete aiming movement in which drivers aim at successful extraction of relevant information and elimination of potentially distracting one. It is the motor preparation which enables one to react to certain stimuli onsite by allowing perceptual process for optimal adjustment. Drivers prepare their responses according to the available resources of advanced and ongoing information to drive efficiently. It requires constant programming and reprogramming of the motor system. The reaction time (RT) is shorter when a response signal is preceded by a warning signal. The reason behind this reduced time in responding to targets is that the warning signal causes the participant to prepare for the upcoming response by updating the motor program before the execution. While performing the primary task of changing lanes while driving, the simultaneous occurrence of additional information during the presentation of cues (congruent or incongruent with respect to target cue) might impact the motor preparation and execution. The presence of additional information (other than warning or response signal) between warning signal and imperative stimulus influences human motor preparation to a reasonable extent. The present study was aimed to assess the impact of congruent and incongruent additional information (with respect to imperative stimulus) on driving performance (reaction time, steering wheel amplitude, and steering wheel duration) during a lane change task. implementing movement pre-cueing paradigm. 22 young valid car-drivers (Mage = 24.1+/- 3.21 years, M = 10, F = 12, age-range 21-33 years) participated in the study. The study revealed that additional information influenced the overall driving performance as potential distractors and relevant information. Findings suggest that the events of additional information relatively influenced the reaction time and steering wheel angle as potential distractor or irrelevant information. Participants took longer to respond, and higher steering wheel angles were reported for targets coupled with additional information in comparison with warning signs preceded by potential distractors and the participants' response time was more for a higher number of lanes (2 Lanes > 1 Lane). The same additional information appearing interchangeably at warning signals and targets worked as relevant information facilitating the motor programming in the trails where they were congruent with the direction of lane change direction.

Keywords: additional information, lane change task, motor preparation, movement pre-cueing, reaction time, steering wheel amplitude

Procedia PDF Downloads 171

Authors: S. Sharma, Gaballa Aqeelah, Tawfig Alghbaili, Ali Elmessmari

Abstract:

There were abrupt discontinuities in the Brute Stack in the northernmost locations during the acquisition of 2D (2007) and 3D (2021) seismic data in the northwest region of the Ghadames Basin, Libya. In both campaigns, complete fluid circulation loss was seen in these regions during up-hole drilling. Geophysics, sedimentology and shallow subsurface geology were all integrated to look into what was causing the seismic signal to disappear at shallow depths. The Upper Cretaceous Nalut Formation is the near-surface or surface formation in the studied area. It is distinguished by abnormally high resistivity in all the neighboring wells. The Nalut Formation in all the nearby wells from the present study and previous outcrop study suggests lithology of dolomite and chert/flint in nodular or layered forms. There are also reports of karstic caverns, vugs, and thick cracks, which all work together to produce the high resistivity. Four up-hole samples that were analyzed for microfacies revealed a near-coastal to tidal environment. Algal (Chara) infested deposits up to 30 feet thick and monotonous, very porous, are seen in two up-hole sediments; these deposits are interpreted to be scattered, continental algal travertine mounds. Chert/flint, dolomite, and calcite in varying amounts are confirmed by XRD analysis. Regional tracking of the high resistivity of the Nalut Formation, which is thought to be connected to the sea level drop that created the paleokarst layer, is possible. It is abruptly overlain by a blanket marine transgressive deposit caused by rapid sea level rise, which is a regional, relatively high radioactive layer of argillaceous limestone. The examined area's close proximity to the mountainous, E-W trending ridges of northern Libya made it easier for recent freshwater circulation, which later enhanced cavern development and mineralization in the paleokarst layer. Seismic signal loss at shallow depth is caused by extremely heterogeneous mineralogy of pore- filling or lack thereof. Scattering effect of shallow karstic layer on seismic signal has been well documented. Higher velocity inflection points at shallower depths in the northern part and deeper intervals in the southern part, in both cases at Nalut level, demonstrate the layer's influence on the seismic signal. During the Permian-Carboniferous, the Ghadames Basin underwent uplift and extensive erosion, which resulted in this karstic layer of the Nalut Formation uplifted to a shallow depth in the northern part of the studied area weakening the acoustic signal, whereas in the southern part of the 3D acquisition area the Nalut Formation remained at the deeper interval without affecting the seismic signal. Results from actions taken during seismic processing to deal with this signal loss are visible and have improved. This study recommends using denser spacing or dynamite to circumvent the karst layer in a comparable geographic area in order to prevent signal loss at lesser depths.

Keywords: well logging, seismic data acquisition, sesimic data processing, up-holes

Procedia PDF Downloads 64

Authors: Nor Asrina Binti Ramlee

Abstract:

Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

Procedia PDF Downloads 351

Authors: Imtiaz Sarwar

Abstract:

Air conditioning in homes may account for one-third of the electricity during period in summer when most of the energy is required in large cities. It is not consuming only electricity but also has a serious impact on environment including greenhouse effect. Circular polarizer filter can be used to selectively absorb or pass clockwise or counter-clock wise circularly polarized light. My research is about putting two circular polarized glasses parallel to each other and make a circular window with it. When we will place two circular polarized glasses exactly same way (0 degree to each other) then nothing will be noticed rather it will work as a regular window through which all light and heat can pass on. While we will keep rotating one of the circular polarized glasses, the angle between the glasses will keep increasing and the window will keep blocking more and more lights. It will completely block all the lights and a portion of related heat when one of the windows will reach 90 degree to another. On the other hand, we can just open the window when fresh air is necessary. It will reduce the necessity of using Air condition too much or consumer will use electric fan rather than air conditioning system. Thus, we can save a significant amount of electricity and we can go green.

Keywords: circular polarizer, window, air condition, light, energy

Procedia PDF Downloads 585

Authors: Sonali Banrjee, Swarup Kumar Mitra, Aritra Acharyya

Abstract:

A piano note recognition method has been proposed by the authors in this paper. The authors have used a comprehensive method for onset detection of each note present in a piano piece followed by segmented short-time Fourier transform (STFT) for the identification of piano notes. The performance evaluation of the proposed method has been carried out in different harsh noisy environments by adding different levels of additive white Gaussian noise (AWGN) having different signal-to-noise ratio (SNR) in the original signal and evaluating the note detection error rate (NDER) of different piano pieces consisting of different number of notes at different SNR levels. The NDER is found to be remained within 15% for all piano pieces under consideration when the SNR is kept above 8 dB.

Keywords: AWGN, onset detection, piano note, STFT

Procedia PDF Downloads 145

Authors: Saad Bakkali

Abstract:

Morocco is a major producer of phosphate, with an annual output of 19 million tons and reserves in excess of 35 billion cubic meters. This represents more than 75% of world reserves. Resistivity surveys have been successfully used in the Oulad Abdoun phosphate basin. A Schlumberger resistivity survey over an area of 50 hectares was carried out. A new field procedure based on analytic signal response of resistivity data was tested to deal with the presence of phosphate deposit disturbances. A resistivity map was expected to allow the electrical resistivity signal to be imaged in 2D. 2D wavelet is standard tool in the interpretation of geophysical potential field data. Wavelet transform is particularly suitable in denoising, filtering and analyzing geophysical data singularities. Wavelet transform tools are applied to analysis of a moroccan phosphate deposit ‘disturbances’. Wavelet approach applied to modeling surface phosphate “disturbances” was found to be consistently useful.

Keywords: resistivity, Schlumberger, phosphate, wavelet, Morocco

Procedia PDF Downloads 398

Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

Abstract:

In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

Procedia PDF Downloads 330

Authors: K. Yahia, M. Sahraoui, A. Guettaf

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental results, show the effectiveness of the used method.

Keywords: induction motors (IMs), inter-turn short-circuits diagnosis, discrete wavelet transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 435

Authors: Yi Zhang, Yuan Tian, Jiehua Chen, Sihong Gu

Abstract:

Chip-scale spin-exchange relaxation free (SERF) atomic magnetometer makes use of millimeter-scale vapor cells micro-fabricated by Micro-electromechanical Systems (MEMS) technique and SERF mechanism, resulting in the characteristics of high spatial resolution and high sensitivity. It is useful for biomagnetic imaging including magnetoencephalography and magnetocardiography. In a prevailing scheme, circularly polarized on-resonance laser beam is adapted for both pumping and probing the atomic polarization. And the magnetic-field-sensitive signal is extracted by transmission laser intensity enhancement as a result of atomic polarization increase on zero field level crossing resonance. The scheme is very suitable for integration, however, the laser amplitude modulation (AM) noise and laser frequency modulation to amplitude modulation (FM-AM) noise is superimposed on the photon shot noise reducing the signal to noise ratio (SNR). To suppress AM and FM-AM noise the paper puts forward a novel scheme which adopts circularly polarized on-resonance light pumping and linearly polarized frequency-detuning laser probing. The transmission beam is divided into transmission and reflection beams by a polarization analyzer, the angle between the analyzer's transmission polarization axis and frequency-detuning laser polarization direction is set to 45°. The magnetic-field-sensitive signal is extracted by polarization rotation enhancement of frequency-detuning laser which induces two beams intensity difference increase as the atomic polarization increases. Therefore, AM and FM-AM noise in two beams are common-mode and can be almost entirely canceled by differential detection. We have carried out an experiment to study our scheme. The experiment reveals that the noise in the differential signal is obviously smaller than that in each beam. The scheme is promising to be applied for developing more sensitive chip-scale magnetometer.

Keywords: atomic magnetometer, chip scale, differential detection, spin-exchange relaxation free

Procedia PDF Downloads 153

Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

Abstract:

This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

Procedia PDF Downloads 74

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we use a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation, estimates, full-band, mixtures, sub-band

Procedia PDF Downloads 428

Authors: Jer-Yuh Liu, Je-Chiuan Ye, Jin-Ming Hwang

Abstract:

Protein kinase C alpha (PKCα) is a key signaling molecule in human cancer development. As a therapeutic strategy, targeting PKCα is difficult because the molecule is ubiquitously expressed in non-malignant cells. PKCα is regulated by the cooperative interaction of the transcription factors myeloid zinc finger 1 (MZF-1) and Ets-like protein-1 (Elk-1) in human cancer cells. By conducting tissue array analysis, herein, we determined the protein expression of MZF-1/Elk-1/PKCα in various cancers. The data show that the expression of MZF-1/Elk-1 is correlated with that of PKCα in hepatocellular carcinoma (HCC), but not in bladder and lung cancers. In addition, the PKCα down-regulation by shRNA Elk-1 was only observed in the HCC SK-Hep-1 cells. Blocking the interaction between MZF-1 and Elk-1 through the transfection of their binding domain MZF-160–72 decreased PKCα expression. This step ultimately depressed the epithelial-mesenchymal transition potential of the HCC cells. These findings could be used to develop an alternative therapeutic strategy for patients with the PKCα-derived HCC.

Keywords: protein kinase C alpha, myeloid zinc finger 1, ets-like protein-1, hepatocellular carcinoma

Procedia PDF Downloads 204

Authors: Zhidong Zhang, Yingchen Yang

Abstract:

In this study, a diagnostic assessment model for Mastery Engineering Learning was established based on a group of undergraduate students who studied in an engineering course. A diagnostic assessment model can examine both students' learning process and report achievement results. One very unique characteristic is that the diagnostic assessment model can recognize the errors and anything blocking students in their learning processes. The feedback is provided to help students to know how to solve the learning problems with alternative strategies and help the instructor to find alternative pedagogical strategies in the instructional designs. Dynamics is a core course in which is a common course being shared by several engineering programs. This course is a very challenging for engineering students to solve the problems. Thus knowledge acquisition and problem-solving skills are crucial for student success. Therefore, developing an effective and valid assessment model for student learning are of great importance. Diagnostic assessment is such a model which can provide effective feedback for both students and instructor in the mastery of engineering learning.

Keywords: diagnostic assessment, mastery learning, engineering, bayesian network model, learning processes

Procedia PDF Downloads 137

Authors: Mohamad Baqer Heidari, Hefzollah.Mohammadian

Abstract:

This brief presents two original implementations of improved accuracy current-mode multiplier/divider circuits. Besides the advantage of their simplicity, these original multiplier/divider structures present the advantage of very small linearity errors that can be obtained as a result of the proposed design techniques (0.75% and 0.9%, respectively, for an extended range of the input currents). The original multiplier/divider circuits permit a facile reconfiguration, the presented structures representing the functional basis for implementing complex function synthesizer circuits. The proposed computational structures are designed for implementing in 0.18-µm CMOS technology, with a low-voltage operation (a supply voltage of 1.2 V). The circuits’ power consumptions are 60 and 75 µW, respectively, while their frequency bandwidths are 79.6 and 59.7 MHz, respectively.

Keywords: analog signal processing, current-mode operation, functional core, multiplier, reconfigurable circuits, industrial package systems

Procedia PDF Downloads 353

Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

Abstract:

In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like, CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique which is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: image compression, color image, q-coder, quantization, edge-detection

Procedia PDF Downloads 311

Authors: Lilia M. Fernando, Matthew K. Vasher, Evangelyn C. Alocilja

Abstract:

This paper describes the development of a DNA-based nanobiosensor to detect the dengue virus in mosquito using electrically active magnetic (EAM) nanoparticles as the concentrator and electrochemical transducer. The biosensor detection encompasses two sets of oligonucleotide probes that are specific to the dengue virus: the detector probe labeled with the EAM nanoparticles and the biotinylated capture probe. The DNA targets are double hybridized to the detector and the capture probes and concentrated from nonspecific DNA fragments by applying a magnetic field. Subsequently, the DNA sandwiched targets (EAM-detector probe–DNA target–capture probe-biotin) are captured on streptavidin modified screen printed carbon electrodes through the biotinylated capture probes. Detection is achieved electrochemically by measuring the oxidation–reduction signal of the EAM nanoparticles. Results indicate that the biosensor is able to detect the redox signal of the EAM nanoparticles at dengue DNA concentrations as low as 10 ng/ul.

Keywords: dengue, magnetic nanoparticles, mosquito, nanobiosensor

Procedia PDF Downloads 337

Authors: Christine F. Boos, Fernando M. Azevedo

Abstract:

Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

Procedia PDF Downloads 505

Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

Procedia PDF Downloads 351