Search results for: back propagation algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5687

Search results for: back propagation algorithm

3167 Speech Enhancement Using Kalman Filter in Communication

Authors: Eng. Alaa K. Satti Salih

Abstract:

Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.

Keywords: autoregressive process, Kalman filter, Matlab, noise speech

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3166 Effect of Tube Thickness on the Face Bending for Blind-Bolted Connection to Concrete Filled Tubular Structures

Authors: Mohammed Mahmood, Walid Tizani, Carlo Sansour

Abstract:

In this paper, experimental testing and numerical analysis were used to investigate the effect of tube thickness on the face bending for concrete filled hollow sections connected to other structural members using Extended Hollobolts. Six samples were tested experimentally by applying pull-out load on the bolts. These samples were designed to fail by column face bending. The main variable in all tests is the column face thickness. Finite element analyses were also performed using ABAQUS 6.11 to extend the experimental results and to quantify the effect of column face thickness. Results show that, the column face thickness has a clear impact on the connection strength and stiffness. However, the amount of improvement in the connection stiffness by changing the column face thickness from 5 mm to 6.3 mm seems to be higher than that when increasing it from 6.3 mm to 8 mm. The displacement at which the bolts start pulling-out from their holes increased with the use of thinner column face due to the high flexibility of the section. At the ultimate strength, the yielding of the column face propagated to the column corner and there was no yielding in its walls. After the ultimate resistance is reached, the propagation of the yielding was mainly in the column face with a miner yielding in the walls.

Keywords: anchored bolted connection, Extended Hollobolt, column faces bending, concrete filled hollow sections

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3165 Breast Cancer Metastasis Detection and Localization through Transfer-Learning Convolutional Neural Network Classification Based on Convolutional Denoising Autoencoder Stack

Authors: Varun Agarwal

Abstract:

Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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3164 From Tionghoa to Tjina: Historical Tracing on the Identity Politics in Demonization of Ethnic Chinese in Indonesia

Authors: Michael J. Kristiono

Abstract:

This paper attempts to investigate the reasons behind the negative sentiments directed towards Chinese Indonesians from International Relations (IR) perspective. By tracing back the treatment of the New Order government towards ethnic Chinese, it was found that such demonization initially happened due to two politically motivated reasons. Firstly, as part of de-Soekarnoization done by the New Order, the Chinese were outcast because Chinese identity does not conform to the 'Indonesian identity', which was in essence, the Javanese identity. Secondly, the condition reflected the change in Indonesian foreign policy which drifted apart from People’s Republic of China (PRC) as the latter was suspected to be involved in September 30 Movement. Then, this paper argues that due to those reasons, coupled by blatant maltreatment from the New Order Government, Chinese Indonesians were constructed as the Others, that is, as non-Indonesians. Such construct has been deeply embedded such that reconciliation attempts done by the Reformation Era government were not sufficient enough to stop ethnic discrimination towards Chinese Indonesians from happening even until the present.

Keywords: Chinese Indonesians, ethnic discrimination, identity, New Order

Procedia PDF Downloads 332
3163 Artificial Intelligence Based Online Monitoring System for Cardiac Patient

Authors: Syed Qasim Gilani, Muhammad Umair, Muhammad Noman, Syed Bilawal Shah, Aqib Abbasi, Muhammad Waheed

Abstract:

Cardiovascular Diseases(CVD's) are the major cause of death in the world. The main reason for these deaths is the unavailability of first aid for heart failure. In many cases, patients die before reaching the hospital. We in this paper are presenting innovative online health service for Cardiac Patients. The proposed online health system has two ends. Users through device developed by us can communicate with their doctor through a mobile application. This interface provides them with first aid.Also by using this service, they have an easy interface with their doctors for attaining medical advice. According to the proposed system, we developed a device called Cardiac Care. Cardiac Care is a portable device which a patient can use at their home for monitoring heart condition. When a patient checks his/her heart condition, Electrocardiogram (ECG), Blood Pressure(BP), Temperature are sent to the central database. The severity of patients condition is checked using Artificial Intelligence Algorithm at the database. If the patient is suffering from the minor problem, our algorithm will suggest a prescription for patients. But if patient's condition is severe, patients record is sent to doctor through the mobile Android application. Doctor after reviewing patients condition suggests next step. If a doctor identifies the patient condition as critical, then the message is sent to the central database for sending an ambulance for the patient. Ambulance starts moving towards patient for bringing him/her to hospital. We have implemented this model at prototype level. This model will be life-saving for millions of people around the globe. According to this proposed model patients will be in contact with their doctors all the time.

Keywords: cardiovascular disease, classification, electrocardiogram, blood pressure

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3162 Improvement of Data Transfer over Simple Object Access Protocol (SOAP)

Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

Abstract:

This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, web service, XML

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3161 Promotion of Renewable Marines Energies in Morocco: Perspectives and Strategies

Authors: Nachtane Mourad, Tarfaoui Mostapha, Saifaoui Dennoun, El Moumen Ahmed

Abstract:

The current energy policy recommends the subject of energy efficiency and to phase out fossil energy as a master question for the prospective years. The kingdom requires restructuring its power equipment by improving the percentage of renewable energy supply and optimizing power systems and storage. Developing energy efficiency, therefore, obliges as a consubstantial objection to reducing energy consumption. The objective of this work is to show the energy transition in Morocco towards renewable energies, in particular, to show the great potential of renewable marine energies in Morocco, This goes back to the advantages of cost and non-pollution in addition to that of the independence of fossil energies. Bearing in mind the necessity of the balance of the Moroccan energy mix, hydraulic and thermal power plants have also been installed which will be added to the power stations already established as a prospect for a balanced network that is flexible to fluctuate demand.

Keywords: renewable marine energy, energy transition, efficiency energy, renewable energy

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3160 Non-Destructive Static Damage Detection of Structures Using Genetic Algorithm

Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

Abstract:

To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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3159 Environmental Liability of Architects: Architects Destroying the City in Designed and Creative Way, Dhaka City

Authors: Md. Ratin

Abstract:

This paper aims to show how Dhaka city is getting destroyed and the creator and guide of the city – the architects destroying the city in more designed and creative way. The liability of architects should be first and foremost to make the would, country, city a better living environment. As without it where the architects will do their design? To make a better living environment architects should conserve the tress, river and other related ingredient related to the environment. This paper attempts to show how cutting down trees and filling rivers causing more problem than having a great architecture in those places. For increasing people in a city like Dhaka, we need more shelter. But for providing those architects building more living spaces. But as a liability of an architect, one should give something back to the environment too. With time the city’s greenery and water body are getting vanished like magic. And for this, the architects should be blamed for giving us a disastrous future. The analysis is based on literature survey and survey by questionnaire, interviews of users.

Keywords: architect, environment, liability, river

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3158 Analysis of Impact Load Induced by Ultrasonic Cavitation Bubble Collapse Using Thin Film Pressure Sensors

Authors: Moiz S. Vohra, Nagalingam Arun Prasanth, Wei L. Tan, S. H. Yeo

Abstract:

The understanding of generation and collapse of acoustic cavitation bubbles are prerequisites for application of cavitation erosion. Microbubbles generated due to rapid fluctuation of pressure induced by propagation of ultrasonic wave lead to formation of high velocity microjets and or shock waves upon collapse. Due to vast application of ultrasonic, it is important to characterize and understand cavitation collapse pressure under the radiating surface at different conditions. A comparative investigation is carried out to determine impact load and dynamic pressure distribution exerted upon bubble collapse using thin film pressure sensors. Measurements were recorded at different input conditions such as amplitude, stand-off distance, insertion depth of the horn inside the liquid and pulse on-off time of acoustic vibrations. Impact force of 2.97 N is recorded at amplitude of 108 μm and stand-off distance of 1 mm from the sensor film, whereas impulsive force as low as 0.4 N is recorded at amplitude of 12 μm and stand-off distance of 5 mm from the sensor film. The results drawn from the investigation indicated that variety of impact loads can be achieved by controlling generation and collapse of bubbles, making it suitable to use for numerous application.

Keywords: ultrasonic cavitation, bubble collapse, pressure mapping sensor, impact load

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3157 Advanced Mouse Cursor Control and Speech Recognition Module

Authors: Prasad Kalagura, B. Veeresh kumar

Abstract:

We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

Procedia PDF Downloads 578
3156 Prevalence and Risk Factors of Musculoskeletal Disorders among School Teachers in Mangalore: A Cross Sectional Study

Authors: Junaid Hamid Bhat

Abstract:

Background: Musculoskeletal disorders are one of the main causes of occupational illness. Mechanisms and the factors like repetitive work, physical effort and posture, endangering the risk of musculoskeletal disorders would now appear to have been properly identified. Teacher’s exposure to work-related musculoskeletal disorders appears to be insufficiently described in the literature. Little research has investigated the prevalence and risk factors of musculoskeletal disorders in teaching profession. Very few studies are available in this regard and there are no studies evident in India. Purpose: To determine the prevalence of musculoskeletal disorders and to identify and measure the association of such risk factors responsible for developing musculoskeletal disorders among school teachers. Methodology: An observational cross sectional study was carried out. 500 school teachers from primary, middle, high and secondary schools were selected, based on eligibility criteria. A signed consent was obtained and a self-administered, validated questionnaire was used. Descriptive statistics was used to compute the statistical mean and standard deviation, frequency and percentage to estimate the prevalence of musculoskeletal disorders among school teachers. The data analysis was done by using SPSS version 16.0. Results: Results indicated higher pain prevalence (99.6%) among school teachers during the past 12 months. Neck pain (66.1%), low back pain (61.8%) and knee pain (32.0%) were the most prevalent musculoskeletal complaints of the subjects. Prevalence of shoulder pain was also found to be high among school teachers (25.9%). 52.0% subjects reported pain as disabling in nature, causing sleep disturbance (44.8%) and pain was found to be associated with work (87.5%). A significant association was found between musculoskeletal disorders and sick leaves/absenteeism. Conclusion: Work-related musculoskeletal disorders particularly neck pain, low back pain, and knee pain, is highly prevalent and risk factors are responsible for the development of same in school teachers. There is little awareness of musculoskeletal disorders among school teachers, due to work load and prolonged/static postures. Further research should concentrate on specific risk factors like repetitive movements, psychological stress, and ergonomic factors and should be carried out all over the country and the school teachers should be studied carefully over a period of time. Also, an ergonomic investigation is needed to decrease the work-related musculoskeletal disorder problems. Implication: Recall bias and self-reporting can be considered as limitations. Also, cause and effect inferences cannot be ascertained. Based on these results, it is important to disseminate general recommendations for prevention of work-related musculoskeletal disorders with regards to the suitability of furniture, equipment and work tools, environmental conditions, work organization and rest time to school teachers. School teachers in the early stage of their careers should try to adapt the ergonomically favorable position whilst performing their work for a safe and healthy life later. Employers should be educated on practical aspects of prevention to reduce musculoskeletal disorders, since changes in workplace and work organization and physical/recreational activities are required.

Keywords: work related musculoskeletal disorders, school teachers, risk factors funding, medical and health sciences

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3155 Hardware-In-The-Loop Relative Motion Control: Theory, Simulation and Experimentation

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

Abstract:

This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

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3154 Comparison of Deep Learning and Machine Learning Algorithms to Diagnose and Predict Breast Cancer

Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

Abstract:

Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

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3153 Weight Estimation Using the K-Means Method in Steelmaking’s Overhead Cranes in Order to Reduce Swing Error

Authors: Seyedamir Makinejadsanij

Abstract:

One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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3152 Looking Forward, Looking Back: A Critical Reflection on the Impact of the Special Needs Assistant Scheme on Inclusionary Practices for Children with Significant Care Needs in the Irish Education System

Authors: C. P. Griffin

Abstract:

This paper seeks to critically review special educational needs (SEN) policy in the Irish education system since the introduction of the Education Act in 1998. In particular, the author seeks to focus on the impact of SEN policy on inclusionary practices for children with significant care needs in light of the introduction on the Special Needs Assistant (SNA) scheme. Following a systematic review of the literature, the growth of the SNA scheme in Ireland will be critically reviewed. Strengths and weaknesses of the scheme will be forwarded and comparisons drawn between contrasting international models of teaching assistant support. Based on this review, avenues for future research will be forwarded, with the aim of supporting effective inclusionary practices for children with SEN based on evidence-based practice.

Keywords: care needs, inclusion, Ireland, special needs assistants

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3151 Iraqi Women’s Rights Under State Civil Law and Conservative Influences: A Study of Legal Documents and Social Implementation

Authors: Rose Hattab

Abstract:

Women have been an important dynamic in religious context and the state-building process of Arab countries throughout history. During the 1970s as the movement for women’s activism and rights developed, the Iraqi state under the Ba’ath Party began to provide Iraqi women with legal and civil rights. This was done to liberate women from the grasps of social traditions and was a tangible espousing of equality between men and women in the process of nation-building. Whereas women’s rights were stronger and more supported throughout the earliest years of the Ba’ath Regime (1970-1990), the aftermath of the Gulf War and economic sanctions on the conditions of Iraqi society laid the foundation for a division of women’s rights between civil and religious authorities. Personal status codes that were secured in 1959 were being pushed back by amendments made in coordination with religious leaders. Civil laws were present on paper, but religious authority took prominence in practice. The written legal codes were inclusive of women’s rights, but there is not an active or ensured practice of these rights within Iraqi society. This is due to many different factors, such as religious, sectarian, political and conservative reasons that hold back or limit the ability for Iraqi women to have autonomy in aspects such as participation in the workforce, getting married, and ensuring social justice. This paper argues that the Personal Status Code introduced in 1959 – which replaced Sharia-run courts with personal status courts – provided Iraqi women with equality and increased mobility in social and economic dynamics. The statewide crisis felt after the Gulf War and the economic sanctions imposed by the United Nations led to a stark shift in the Ba’ath party’s political ideology. This ideological turn guided the social system to the embracement of social conservatism and religious traditions in the 1990s. The effect of this implementation continued after the establishment of a new Iraqi government during 2003-2005. Consequently, Iraqi women's rights in employment, marriage, and family became divided into paper and practice by religious authorities and civil law from that period to the present day. This paper also contributes to the literature by expanding on the gap between legal codes on paper and in practice, through providing an analysis of Iraqi women’s rights in the Iraqi Constitution of 2005 and Iraq’s Penal Code. The turn to conservative and religious traditions is derived from the multiplicity of identities that make up the Iraqi social fabric. In the aftermath of a totalitarian regime, active wars, and economic sanctions, the Iraqi people attempted to unite together through their different identities to create a sense of security in the midst of violence and chaos. This is not an excuse to diminish the importance of women’s rights, but in the process of building a new nation-state, women were lost from the narrative. Thus, the presence of gender equity is found in the written text but is not practiced and upheld in the social context.

Keywords: civil rights, Iraqi women, nation building, religion and conflict

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3150 A Radiomics Approach to Predict the Evolution of Prostate Imaging Reporting and Data System Score 3/5 Prostate Areas in Multiparametric Magnetic Resonance

Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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3149 Research on the Two-Way Sound Absorption Performance of Multilayer Material

Authors: Yang Song, Xiaojun Qiu

Abstract:

Multilayer materials are applied to much acoustics area. Multilayer porous materials are dominant in room absorber. Multilayer viscoelastic materials are the basic parts in underwater absorption coating. In most cases, the one-way sound absorption performance of multilayer material is concentrated according to the sound source site. But the two-way sound absorption performance is also necessary to be known in some special cases which sound is produced in both sides of the material and the both sides especially might contact with different media. In this article, this kind of case was research. The multilayer material was composed of viscoelastic layer and steel plate and the porous layer. The two sides of multilayer material contact with water and air, respectively. A theory model was given to describe the sound propagation and impedance in multilayer absorption material. The two-way sound absorption properties of several multilayer materials were calculated whose two sides all contacted with different media. The calculated results showed that the difference of two-way sound absorption coefficients is obvious. The frequency, the relation of layers thickness and parameters of multilayer materials all have an influence on the two-way sound absorption coefficients. But the degrees of influence are varied. All these simulation results were analyzed in the article. It was obtained that two-way sound absorption at different frequencies can be promoted by optimizing the configuration parameters. This work will improve the performance of underwater sound absorption coating which can absorb incident sound from the water and reduce the noise radiation from inside space.

Keywords: different media, multilayer material, sound absorption coating, two-way sound absorption

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3148 Doping Density Effects on Minority Carrier Lifetime in Bulk GaAs by Means of Photothermal Deflection Technique

Authors: Soufiene Ilahi

Abstract:

Photothermal effect occurs when absorbed light energy that generate a thermal wave that propagate into the sample and surrounding media. Subsequently, the propagation of the vibration of phonons or electrons causes heat transfer. In fact, heat energy is provided by non-radiative recombination process that occurs in semiconductors sample. Three heats sources are identified: surface recombination, bulk recombination and carrier thermalisation. In the last few years, Photothermal Deflection Technique PTD is a nondestructive and accurate technique that prove t ability for electronics properties investigation. In this paper, we have studied the influence of doping on minority carrier lifetime, i.e, nonradiative lifetime, surface and diffusion coefficient. In fact, we have measured the photothermal signal of two sample of GaAs doped with C et Cr.In other hand , we have developed a theoretical model that takes into account of thermal and electronics diffusion equations .In order to extract electronics parameters of GaAs samples, we have fitted the theoretical signal of PTD to the experimental ones. As a results, we have found that nonradiative lifetime is around of 4,3 x 10-8 (±11,24%) and 5 x 10-8 (±14,32%) respectively for GaAs : Si doped and Cr doped. Accordingly, the diffusion coefficient is equal 4,6 *10-4 (± 3,2%) and 5* 10-4 (± 0,14%) foe the Cr, C and Si doped GaAs respectively.

Keywords: nonradiative lifetime, mobility of minority carrier, diffusion length, surface and interface recombination in GaAs

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3147 Logical-Probabilistic Modeling of the Reliability of Complex Systems

Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

Abstract:

The paper presents logical-probabilistic methods, models, and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. It is important to design systems based on structural analysis, research, and evaluation of efficiency indicators. One of the important efficiency criteria is the reliability of the system, which depends on the components of the structure. Quantifying the reliability of large-scale systems is a computationally complex process, and it is advisable to perform it with the help of a computer. Logical-probabilistic modeling is one of the effective means of describing the structure of a complex system and quantitatively evaluating its reliability, which was the basis of our application. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of “weights” of elements of system. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research, and designing of optimal structure systems are carried out.

Keywords: complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability of systems, “weights” of elements

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3146 Dynamic Bandwidth Allocation in Fiber-Wireless (FiWi) Networks

Authors: Eman I. Raslan, Haitham S. Hamza, Reda A. El-Khoribi

Abstract:

Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.

Keywords: fiber-wireless (FiWi), dynamic bandwidth allocation (DBA), passive optical networks (PON), media access control (MAC)

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3145 Antibiotic and Fungicide Exposure Reveal the Evolution of Soil-Lettuce System Resistome

Authors: Chenyu Huang, Minrong Cui, Hua Fang, Luqing Zhang, Yunlong Yu

Abstract:

The emergence and spread of antibiotic resistance genes (ARGs) have become a pressing issue in global agricultural production. However, understanding how these ARGs spread across different spatial scales, especially when exposed to both pesticides and antibiotics, has remained a challenge. Here, metagenomic assembly and binning methodologies were used to determine the mechanism of ARG propagation within soil-lettuce systems exposed to both fungicides and antibiotics. The results of our study showed that the presence of fungicide and antibiotic stresses had a significant impact on certain bacterial communities. Notably, we observed that ARGs were primarily transferred from the soil to the plant through plasmids. The selective pressure exerted by fungicides and antibiotics contributed to an increase in unique ARGs present on lettuce leaves. Moreover, ARGs located on chromosomes and plasmids followed different transmission patterns. The presence of diverse selective pressures, a result of compound treatments involving antibiotics and fungicides, amplifies this phenomenon. Consequently, there is a higher probability of bacteria developing multi-antibiotic resistance under the combined pressure of fungicides and antibiotics. In summary, our findings highlight that combined fungicide and antibiotic treatments are more likely to drive the acquisition of ARGs within the soil-plant system and may increase the risk of human ingestion.

Keywords: soil-lettuce system, fungicide, antibiotic, ARG, transmission

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3144 Diasporic Literature

Authors: Shamsher Singh

Abstract:

The Diaspora Literature involves a concept of native land, from where the displacement occurs and a record of harsh journeys undertaken on account of economic compulsions. Basically, Diaspora is a splintered community living in eviction. The scattering (initially) signifies the location of a fluid human autonomous space involving a complex set of negotiations and exchange between the nostalgia and desire for the native land and the making of a new home, adapting to the relationships between the minority and majority, being spokes persons for minority rights and their people back native place and significantly transacting the Contact Zone - a space changed with the possibility of multiple challenges. They write in the background of the sublime qualities of their homeland and, at the same time, try to fit themselves into the traditions and cultural values of other strange communities or land. It also serves as an interconnection of the various cultures involved, and it is used to understand the customs of different cultures and countries; it is also a source of inspiration globally. Although diasporic literature originated back in the 20th century, it spread to other countries like Britain, Canada, America, Denmark, Netherland, Australia, Kenya, Sweden, Kuwait and different parts of Europe. Meaning of Diaspora is the combination of two words which means the movement of people away from their own country or motherland. From a historical point of view, the ‘Diaspora’ is often associated with Jewish bigotry. At the moment, the Diaspora is used for the dispersal of social or cultural groups. This group will be living in two different streams of cultures at the same time. One who left behind his culture and the other has to adapt himself to new cultural situations. The diasporic mind hangs between his birth land and place of work at the same time. A person’s mental state, living in dual existence, gives birth to Dysphoria sensation. Litterateurs had different experiences in this type of sensation e.g., social, universal, political, economic and experiences from the strange land. The struggle of these experiences is seen in diasporic literature. When a person moves to different land or country to fulfill his dreams, the discrimination of language, work and other difficulties with strangers make his relationship more emotional and deeper into his past. These past memories and relations create more difficulties in settling in a foreign land. He lives there physically, but his mental state is in his past constantly, and he ends up his life in those background memories. A person living in Diaspora is actually a dual visionary man. Although this double vision expands his global consciousness, due to this vision, he gains judgemental qualities to understand others. At the same time, he weighs his respect for his native land and the situations of foreign land he experiences, and he finds it difficult to survive in those conditions. It can be said that diaspora literature indicates a person or social organization who lives dual life inquisition structure which becomes the cause of diasporic literature.

Keywords: homeland sickness, language problem, quest for identity, materialistic desire

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3143 Category-Base Theory of the Optimum Signal Approximation Clarifying the Importance of Parallel Worlds in the Recognition of Human and Application to Secure Signal Communication with Feedback

Authors: Takuro Kida, Yuichi Kida

Abstract:

We show a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detailed algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory and it is indicated that introducing conversations with feedback does not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, conditional optimization

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3142 The Conservation of the Botanical Collar of Tutankhamun

Authors: Safwat Mohamed Sayed Ali, Hussein Kamal

Abstract:

This paper discusses the conservation procedures of the botanical collar of King Tutankhamun. It dates back to the new Kingdom. This collar was kept in a box but found in bad condition. Many parts of the collar were separated. The collar suffered from dryness and dust, so it needed to be cleaned mechanically and recollected together. Japanese paper was used to collect the separated parts of the collar on a linen thread. The linen thread was dyed with organic dye to match the color of the plant material. The guidance in collecting the different parts of the plant collar is the original photograph captured at the discovery of the tomb. Also, the optical microscope was used in collecting fractured parts. The weak parts of the collar were treated with a suitable consolidation material. Klucel G dissolved in Ethyl Alcohol 0.5% was used in the treatment and gave convenient results. Some investigations were executed in order to identify the plant types used in making the botanical collar. Scanning Electron microscope and optical microscope were used in plant identification.

Keywords: sustainable, consolidation, plant, investigation

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3141 Low Overhead Dynamic Channel Selection with Cluster-Based Spatial-Temporal Station Reporting in Wireless Networks

Authors: Zeyad Abdelmageid, Xianbin Wang

Abstract:

Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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3140 A False Introduction: Teaching in a Pandemic

Authors: Robert Michael, Kayla Tobin, William Foster, Rachel Fairchild

Abstract:

The COVID-19 pandemic has caused significant disruptions in education, particularly in the teaching of health and physical education (HPE). This study examined a cohort of teachers that experienced being a preservice and first-year teacher during various stages of the pandemic. Qualitative data collection was conducted by interviewing six teachers from different schools in the Eastern U.S. over a series of structured interviews. Thematic analysis was employed to analyze the data. The pandemic significantly impacted the way HPE was taught as schools shifted to virtual and hybrid models. Findings revealed five major themes: (a) You want me to teach HOW?, (b) PE without equipment and six feet apart, (c) Behind the Scenes, (d) They’re back…I became a behavior management guru, and (e) The Pandemic Crater. Overall, this study highlights the significant challenges faced by preservice and first-year teachers in teaching physical education during the pandemic and underscores the need for ongoing support and resources to help them adapt and succeed in these challenging circumstances.

Keywords: teacher education, preservice teachers, first year teachers, health and physical education

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3139 The Effect of COVID-19 Transmission, Lockdown Measures, and Vaccination on Stock Market Returns

Authors: Belhouchet Selma, Ben Amar Anis

Abstract:

We examine the impact of COVID-19 transmission, containment measures, and vaccination growth on daily stock market returns for the G7 countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) from January 22, 2020, to August 31, 2021, more than a year and a half after COVID-19. For this objective, we use panel pooled ordinary least squares regressions. Our findings indicate that the spread of the pandemic has a negative impact on the daily performance of the world's seven main stock markets. Government measures to improve stock market returns are no longer successful. Furthermore, our findings demonstrate that immunization efforts in G7 nations do not increase stock market performance in these countries. A variety of robustness tests back up our conclusions. Our findings have far-reaching implications for investors, governments, and regulators not only in the G7 countries but also in all developed countries and all countries globally.

Keywords: COVID-19, G7 stock market, containment measures, vaccination

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3138 An Analysis on Clustering Based Gene Selection and Classification for Gene Expression Data

Authors: K. Sathishkumar, V. Thiagarasu

Abstract:

Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

Procedia PDF Downloads 323