Search results for: EM signal blind analysis method

Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

Abstract:

The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

Procedia PDF Downloads 128

Authors: Hana Porkertová, Pavel Doboš

Abstract:

Based on a research project studying the experience of visually disabled people with urban space in the Czech Republic, the conference contribution discusses the limits of social-science methodologies used in sociology and human geography. It draws on actor-network theory, assuming that science does not describe reality but produces it. Methodology connects theory, research questions, ways to answer them (methods), and results. A research design utilizing ableist methodologies can produce ableist realities. Therefore, it was necessary to adjust the methods so that they could mediate blind experience to the scientific community without reproducing ableism. The researchers faced multiple challenges, ranging from questionable validity to how to research experience that differs from that of the researchers who are able-bodied. Finding a suitable theory that could be used as an analytical tool that would demonstrate space and blind experience as multiple, dynamic, and mutually constructed was the first step that could offer a range of potentially productive methods and research questions, as well as bring critically reflected results. Poststructural theory, mainly Deleuze-Guattarian philosophy, was chosen, and two methods were used: interviews and go-along interviews that had to be adjusted to be able to explore blind experience. In spite of a thorough preparation of these methods, new difficulties kept emerging, which exposed the ableist character of scientific knowledge. From the beginning of data collecting, there was an agreement to work in teams with slightly different roles of each of the researchers, which was significant especially during go-along interviews. In some cases, the anticipations of the researchers and participants differed, which led to unexpected and potentially dangerous situations. These were not caused only by the differences between scientific and lay communities but also between able-bodied and disabled people. Researchers were sometimes assigned to the assistants’ roles, and this new position – doing research together – required further negotiations, which also opened various ethical questions.

Keywords: ableist methodology, blind experience, go-along interviews, research ethics, scientific knowledge

Procedia PDF Downloads 161

Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

Abstract:

This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

Procedia PDF Downloads 389

Authors: Omar Nasr, Yasser Naguib, Mohamed Hafez

Abstract:

This paper aims at providing an innovative solution for blind interference threshold estimation in an underlay cognitive network to be used in adaptive beamforming by secondary user Transmitter and Receiver. For the task of threshold estimation, blind detection of modulation and SNR are used. For the sake of beamforming several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as LCMV (Linear Constraint Minimum Variance) and MVDR (Minimum Variance Distortion less) are also proposed and compared. The idea of just nulling the primary user after knowledge of its location is discussed against the idea of working under interference threshold.

Keywords: cognitive radio, underlay, beamforming, MUSIC, MVDR, LCMV, threshold estimation

Procedia PDF Downloads 575

Authors: Mai Yen Nhi Doan, Viet Le, Chamindika Weerakoon

Abstract:

Social enterprises have emerged as sustainable organisations that deliver social achievement along with long-term financial advancement. However, recorded financial barriers have urged social enterprises to divert to other financing methods due to the misaligned ideology with traditional financing capitalists, in which crowdfunding can be a promising alternative. Previous studies in crowdfunding have inadequately addressed crowdfunding for social enterprises, with conflicting results due to the unsuitable analysis of signals in isolation rather than in combinations, using the data from platforms that do not support social enterprises. Extending the signalling theory, this study suggests that crowdfunding success results from the collaboration between costly and costless signals. The proposed conceptual framework enlightens the interaction between costly signals as “organisational information”, “social entrepreneur’s credibility,” and “third-party endorsement” and costless signals as various sub-signals under the “campaign preparedness” signal to achieve crowdfunding success. Using Qualitative Comparative Analysis, this study examined 45 crowdfunding campaigns run by Australian social enterprises on StartSomeGood and Chuffed. The analysis found that different combinations of costly and costless signals can lead to crowdfunding success, allowing social enterprises to adopt suitable combinations of signals to their context. Costless signal – campaign preparedness is fundamental for success, though different costless sub-signals under campaign preparedness can interact with different costly signals for the desired outcome. Third-party endorsement signal was found to be the necessary signal for crowdfunding success for Australian social enterprises.

Keywords: crowdfunding, qualitative comparative analysis (QCA), signalling theory, social enterprises

Procedia PDF Downloads 91

Authors: Muhammad Ashfaq

Abstract:

Main theme: This prime focus of this study is on the role of digital technology in crime prevention, with special focus on Cellular Forensic Unit, Capital City Police Peshawar-Khyber Pakhtunkhwa-Pakistan. Objective(s) of the study: The prime objective of this study is to provide statistics, strategies and pattern of analysis used for crime prevention in Cellular Forensic Unit of Capital City Police Peshawar, Khyber Pakhtunkhwa-Pakistan. Research Method and Procedure: Qualitative method of research has been used in the study for obtaining secondary data from research wing and Information Technology (IT) section of Peshawar police. Content analysis was the method used for the conduction of the study. This study is delimited to Capital City Police and Cellular Forensic Unit Peshawar-KP, Pakistan. information technologies. Major finding(s): It is evident that the old traditional approach will never provide solutions for better management in controlling crimes. The best way to control crimes and promotion of proactive policing is to adopt new technologies. The study reveals that technology have transformed police more effective and vigilant as compared to traditional policing. The heinous crimes like abduction, missing of an individual, snatching, burglaries and blind murder cases are now traceable with the help of technology. Recommendation(s): From the analysis of the data, it is reflected that Information Technology (IT) expert should be recruited along with research analyst to timely assist and facilitate operational as well as investigation units of police.A mobile locator should be Provided to Cellular Forensic Unit to timely apprehend the criminals .Latest digital analysis software should be provided to equip the Cellular Forensic Unit.

Keywords: crime prevention, digital technology, pakistan, police

Procedia PDF Downloads 60

Authors: Rogelio Luck, Yucheng Liu

Abstract:

This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

Procedia PDF Downloads 149

Authors: Feng Tao, Han Ye, Shaoyi Liao

Abstract:

City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m.

Keywords: signal propagation model, centroid algorithm, localization, mixed filtering, RSSI

Procedia PDF Downloads 293

Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

Procedia PDF Downloads 89

Authors: Ayad Dalloo, Sulaf Dalloo

Abstract:

Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

Procedia PDF Downloads 290

Authors: Agus Hariyadi, Hiroatsu Fukuda

Abstract:

In tropical country like Indonesia, especially in Jakarta, most of the energy consumption on building is for the cooling system, the second one is from lighting electric consumption. One of the passive design strategy that can be done is optimizing the use of natural light from the sun. In this area, natural light is always available almost every day around the year. Natural light have many effect on building. It can reduce the need of electrical lighting but also increase the external load. Another thing that have to be considered in the use of natural light is the visual comfort from occupant inside the room. To optimize the effectiveness of natural light need some modification of façade design. By using external shading device, it can minimize the external load that introduces into the room, especially from direct solar radiation which is the 80 % of the external energy load that introduces into the building. It also can control the distribution of natural light inside the room and minimize glare in the perimeter zone of the room. One of the horizontal blind that can be used for that purpose is Sudare. It is traditional Japanese blind that have been used long time in Japanese traditional house especially in summer. In its original function, Sudare is used to prevent direct solar radiation but still introducing natural ventilation. It has some physical characteristics that can be utilize to optimize the effectiveness of natural light. In this research, different scale of Sudare will be simulated using EnergyPlus and DAYSIM simulation software. EnergyPlus is a whole building energy simulation program to model both energy consumption—for heating, cooling, ventilation, lighting, and plug and process loads—and water use in buildings, while DAYSIM is a validated, RADIANCE-based daylighting analysis software that models the annual amount of daylight in and around buildings. The modelling will be done in Ladybug and Honeybee plugin. These are two open source plugins for Grasshopper and Rhinoceros 3D that help explore and evaluate environmental performance which will directly be connected to EnergyPlus and DAYSIM engines. Using the same model will maintain the consistency of the same geometry used both in EnergyPlus and DAYSIM. The aims of this research is to find the best configuration of façade design which can reduce the external load from the outside of the building to minimize the need of energy for cooling system but maintain the natural light distribution inside the room to maximize the visual comfort for occupant and minimize the need of electrical energy consumption.

Keywords: façade, natural light, blind, energy

Procedia PDF Downloads 340

Authors: Fatemeh Deldarabdolmaleki, Mohamad Fakri Zaky Bin Ja'afar

Abstract:

Having a daylit space together with view results in a pleasant and productive environment for office employees. A daylit space is a space which utilizes daylight as a basic source of illumination to fulfill user’s visual demands and minimizes the electric energy consumption. Malaysian weather is hot and humid all over the year because of its location in the equatorial belt. however, because most of the commercial buildings in Malaysia are air-conditioned, huge glass windows are normally installed in order to keep the physical and visual relation between inside and outside. As a result of climatic situation and mentioned new trend, an ordinary office has huge heat gain, glare, and discomfort for occupants. Balancing occupant’s comfort and energy conservation in a tropical climate is a real challenge. This study concentrates on evaluating a venetian blind system using per pixel analyzing tools based on the suggested cut-out metrics by the literature. Workplace area in a private office room has been selected as a case study. Eight-day measurement experiment was conducted to investigate the effect of different venetian blind angles in an office area under daylight conditions in Serdang, Malaysia. The study goal was to explore daylight comfort of a commercially available venetian blind system, its’ daylight sufficiency and excess (8:00 AM to 5 PM) as well as Glare examination. Recently developed software, analyzing High Dynamic Range Images (HDRI captured by CCD camera), such as radiance based Evalglare and hdrscope help to investigate luminance-based metrics. The main key factors are illuminance and luminance levels, mean and maximum luminance, daylight glare probability (DGP) and luminance ratio of the selected mask regions. The findings show that in most cases, morning session needs artificial lighting in order to achieve daylight comfort. However, in some conditions (e.g. 10° and 40° slat angles) in the second half of day the workplane illuminance level exceeds the maximum of 2000 lx. Generally, a rising trend is discovered toward mean window luminance and the most unpleasant cases occur after 2 P.M. Considering the luminance criteria rating, the uncomfortable conditions occur in the afternoon session. Surprisingly in no blind condition, extreme case of window/task ratio is not common. Studying the daylight glare probability, there is not any DGP value higher than 0.35 in this experiment.

Keywords: daylighting, energy simulation, office environment, Venetian blind

Procedia PDF Downloads 248

Authors: Dong Wook Lee, Adrian Mistreanu

Abstract:

The authors have studied a method for analyzing containment and penetration using an explicit nonlinear Finite Element Analysis. This method may be used in the stage of concept design for the protection of external configurations or components of aircraft engines and nuclear power plant structures. This paper consists of the modeling method, the results obtained from the method and the comparison of the results with those calculated from simple analytical method. It shows that the containment capability obtained by proposed method matches well with analytically calculated containment capability.

Keywords: computer aided engineering, containment analysis, finite element analysis, impact analysis, penetration analysis

Procedia PDF Downloads 129

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 158

Authors: Omer Cahana, Ofer Levi, Maya Herman

Abstract:

Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

Procedia PDF Downloads 84

Authors: Juan-Pedro Rica-Peromingo

Abstract:

The important change taking place with respect to the media and the audiovisual world in Europe needs to benefit all populations, in particular those with special needs, such as the deaf and hard-of-hearing population (SDH) and blind and partially-sighted population (AD). This recent interest in the field of audiovisual translation (AVT) can be observed in the teaching and learning of the different modes of AVT in the degree and post-degree courses at Spanish universities, which expand the interest and practice of AVT linguistic accessibility. We present a research project led at the UCM which consists of the compilation of AVT activities for teaching purposes and tries to analyze the creation and reception of SDH and AD: the AVLA Project (Audiovisual Learning Archive), which includes audiovisual materials carried out by the university students on different AVT modes and evaluations from the blind and deaf informants. In this study, we present the materials created by the students. A group of the deaf and blind population has been in charge of testing the student's SDH and AD corpus of audiovisual materials through some questionnaires used to evaluate the students’ production. These questionnaires include information about the reception of the subtitles and the audio descriptions from linguistic and technical points of view. With all the materials compiled in the research project, a corpus with both the students’ production and the recipients’ evaluations is being compiled: the CALING (Corpus de Accesibilidad Lingüística) corpus. Preliminary results will be presented with respect to those aspects, difficulties, and deficiencies in the SDH and AD included in the corpus, specifically with respect to the length of subtitles, the position of the contextual information on the screen, and the text included in the audio descriptions and tone of voice used. These results may suggest some changes and improvements in the quality of the SDH and AD analyzed. In the end, demand for the teaching and learning of AVT and linguistic accessibility at a university level and some important changes in the norms which regulate SDH and AD nationally and internationally will be suggested.

Keywords: audiovisual translation, corpus linguistics, linguistic accessibility, teaching

Procedia PDF Downloads 75

Authors: Savita, Anurag Sharma, Harsukhpreet Singh

Abstract:

Fetal Electrocardiogram (fECG) is a widely used technique to assess the fetal well-being and identify any changes that might be with problems during pregnancy and to evaluate the health and conditions of the fetus. Various techniques or methods have been employed to diagnose the fECG from abdominal signal. This paper describes the facile approach for the estimation of the fECG known as Adaptive Comb. Filter (ACF). The ACF can adjust according to the temporal variations in fundamental frequency by itself that used for the estimation of the quasi periodic signal of ECG signal.

Keywords: aECG, ACF, fECG, mECG

Procedia PDF Downloads 401

Authors: Peter A. L’vov, Roman S. Konovalov, Alexey A. L’vov

Abstract:

The paper presents the advanced digital modification of the conventional current loop circuit for pressure piezoelectric transducers. The optimal DSP algorithms of current loop responses by the maximum likelihood method are applied for diminishing of measurement errors. The loop circuit has some additional advantages such as the possibility to operate with any type of resistance or reactance sensors, and a considerable increase in accuracy and quality of measurements to be compared with AC bridges. The results obtained are dedicated to replace high-accuracy and expensive measuring bridges with current loop circuits.

Keywords: current loop, maximum likelihood method, optimal digital signal processing, precise pressure measurement

Procedia PDF Downloads 520

Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

Procedia PDF Downloads 203

Authors: Junfeng Yan, Wenkui Hou

Abstract:

Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

Procedia PDF Downloads 373

Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

Abstract:

In this paper, altera de1-SoC FPGA board technology is utilized as a distinguished tool for nondestructive characterization of an aluminum circular cylindrical shell of radius ratio b/a (a: outer radius; b: inner radius). The acoustic backscattered signal processing system has been developed using OpenMP architecture. The design is built in three blocks; it is implemented per functional block, in a heterogeneous Intel-Altera system running under Linux. The useful data to determine the performances of SoC FPGA is computed by the analytical method. The exploitation of SoC FPGA has lead to obtain the backscattering form function and resonance spectra. A0 and S0 modes of propagation in the tube are shown. The findings are then compared to those achieved from the Matlab simulation of analytical method. A good agreement has, therefore, been noted. Moreover, the detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 5 times faster than the Matlab implementation using almost the same data. This FPGA-based system implementation of processing algorithms is realized with a coefficient of correlation R and absolute error respectively about 0.962 and 5 10⁻⁵.

Keywords: OpenMP, signal processing system, acoustic backscattering, nondestructive characterization, thin tubes

Procedia PDF Downloads 85

Authors: Muhammad Ashfaq

Abstract:

Main theme: This prime focus of this study is on the role of digital technology in crime prevention, with special focus on Cellular Forensic Unit, Capital City Police Peshawar-Khyber Pakhtunkhwa-Pakistan. Objective(s) of the study: The prime objective of this study is to provide statistics, strategies, and pattern of analysis used for crime prevention in Cellular Forensic Unit of Capital City Police Peshawar, Khyber Pakhtunkhwa-Pakistan. Research Method and Procedure: Qualitative method of research has been used in the study for obtaining secondary data from research wing and Information Technology (IT) section of Peshawar police. Content analysis was the method used for the conduction of the study. This study is delimited to Capital City Police and Cellular Forensic Unit Peshawar-KP, Pakistan. information technologies. Major finding(s): It is evident that the old traditional approach will never provide solutions for better management in controlling crimes. The best way to control crimes and promotion of proactive policing is to adopt new technologies. The study reveals that technology have transformed police more effective and vigilant as compared to traditional policing. The heinous crimes like abduction, missing of an individual, snatching, burglaries, and blind murder cases are now traceable with the help of technology. Recommendation(s): From the analysis of the data, it is reflected that Information Technology (IT) expert should be recruited along with research analyst to timely assist and facilitate operational as well as investigation units of police. A mobile locator should be Provided to Cellular Forensic Unit to timely apprehend the criminals. Latest digital analysis software should be provided to equip the Cellular Forensic Unit.

Keywords: criminology-pakistan, crime prevention-KP, digital forensics, digital technology-pakistan

Procedia PDF Downloads 89

Authors: Attiq Ur Rahman Dogar, Sohaib Ishaq

Abstract:

Pakistan had experienced rapid motorization in the last decade. Due to the soft leasing schemes of banks and increase in average household income, even the middle class can now afford cars. The public transit system is inadequate and sparse. Due to these reasons, traffic demand on urban arterials has increased manifold. Poor urban transit planning and aging transportation systems have resulted in traffic congestion. The focus of this study is to improve traffic flow on a section of N-5 passing through the Rawalpindi downtown. Present efforts aim to carry out the analysis of traffic conditions on this section and to investigate the impact of traffic signal co-ordination on travel time. In addition to signal co-ordination, we also examined the effect of different infrastructure improvements on the travel time. After the economic analysis of alternatives and discussions, the improvement plan for Rawalpindi downtown urban arterial section is proposed for implementation.

Keywords: signal coordination, infrastructure intervention, infrastructure improvement, cycle length, fuel consumption cost, travel time cost, economic analysis, travel time, Rawalpindi, Pakistan, traffic signals

Procedia PDF Downloads 310

Authors: Amanda de Oliveira Ferreira Leite, Ana Luiza del Pino Ferreira, Bruna Garcez Correa, Janaíne de Souza Mello, Marla Manquevich, Mirna Wetters Portuguez

Abstract:

Objective: We sought to investigate a neuropsychological intervention focused on improving cognition, psychological aspects, and quality of life of elderly people with mild cognitive impairment. Method: A controlled and randomized study, blind to the evaluator, was executed. We evaluated 78 elderly people, divided into the neuropsychological and control groups, through a semi-structured interview, Addenbrooke’s Cognitive Examination, Katz Index, Lawton and Brody Scale, Geriatric Depression Scale, Beck Anxiety Inventory, Personal Development Scale, WHOQOL-bref and WHOQOL--old. Results: After the intervention, the neuropsychological group showed improvement in the cognitive subtests and in the total score, reduction in the frequency of symptoms associated with anxiety and depression, better psychological well-being, and quality of life. The research highlights useful intervention strategies for improving the general condition of these patients and rehabilitating damaged areas. Conclusion: We concluded that there is a relationship between neuropsychological intervention and improvement in cognitive and psychological performance, as well as in the quality of life in elderly people with mild cognitive impairment.

Keywords: aging, mild cognitive impairment, neuropsychology, quality of life

Procedia PDF Downloads 103

Authors: Muhammad Ashfaq

Abstract:

Main theme: This prime focus of this study is on the role of digital technology in crime prevention, with special focus on Cellular Forensic Unit, Capital City Police Peshawar-Khyber Pakhtunkhwa-Pakistan. Objective(s) of the study: The prime objective of this study is to provide statistics, strategies and pattern of analysis used for crime prevention in Cellular Forensic Unit of Capital City Police Peshawar, Khyber Pakhtunkhwa-Pakistan. Research Method and Procedure: Qualitative method of research has been used in the study for obtaining secondary data from research wing and Information Technology (IT) section of Peshawar police. Content analysis was the method used for the conduction of the study. This study is delimited to Capital City Police and Cellular Forensic Unit Peshawar-KP, Pakistan. information technologies.Major finding(s): It is evident that the old traditional approach will never provide solutions for better management in controlling crimes. The best way to control crimes and promotion of proactive policing is to adopt new technologies. The study reveals that technology have transformed police more effective and vigilant as compared to traditional policing. The heinous crimes like abduction, missing of an individual, snatching, burglaries and blind murder cases are now traceable with the help of technology.Recommendation(s): From the analysis of the data, it is reflected that Information Technology (IT) expert should be recruited along with research analyst to timely assist and facilitate operational as well as investigation units of police .A mobile locator should be Provided to Cellular Forensic Unit to timely apprehend the criminals .Latest digital analysis software should be provided to equip the Cellular Forensic Unit.

Keywords: crime-prevention, cellular-forensic unit-pakistan, crime prevention-digital-pakistan, crminology-pakistan

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

Abstract:

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

Abstract:

In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Aleksandar Jovanovic, Katarina Kukic, Ana Uzelac, Dusan Teodorovic

Abstract:

Wisdom of the Crowd (WoC) is a decentralized method that uses the collective intelligence of humans. Individual guesses may be far from the target, but when considered as a group, they converge on optimal solutions for a given problem. We will utilize WoC to address the challenge of controlling traffic lights within intersections from the streets of Kragujevac, Serbia. The problem at hand falls within the category of NP-hard problems. We will employ an algorithm that leverages the swarm intelligence of bees: Bee Colony Optimization (BCO). Data regarding traffic signal timing at a single intersection will be gathered from citizens through a survey. Results obtained in that manner will be compared to the BCO results for different traffic scenarios. We will use Vissim traffic simulation software as a tool to compare the performance of bees’ and humans’ collective intelligence.

Keywords: wisdom of the crowd, traffic signal control, combinatorial optimization, bee colony optimization

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Authors: Nurul Na'imy Wan, Mohamad Sazali Said, Jaharah Ab. Ghani, Rusli Othman

Abstract:

This paper presents the surface roughness of the aluminium silicon alloy (AlSi) matrix composite which has been reinforced with aluminium nitride (AlN). Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to a standard orthogonal array L27 of Taguchi method using TiN coating tool of insert. The signal-to-noise (S/N) ratio and analysis of variance are applied to study the characteristic performance of cutting speeds, feed rates and depths of cut in measuring the surface roughness during the milling operation. The surface roughness was observed using Mitutoyo Formtracer CS-500 and analyzed using the Taguchi method. From the Taguchi analysis, it was found that cutting speed of 230 m/min, feed rate of 0.4 mm/tooth, depth of cut of 0.3 mm were the optimum machining parameters using TiN coating insert.

Keywords: AlSi/AlN metal matrix composite (MMC), surface roughness, Taguchi method, machining parameters

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Authors: Rohit Gupta, Ravinder Agarwal

Abstract:

Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

Procedia PDF Downloads 288