Search results for: real time stress detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25412

Search results for: real time stress detection

24092 Evaluating the Nexus between Energy Demand and Economic Growth Using the VECM Approach: Case Study of Nigeria, China, and the United States

Authors: Rita U. Onolemhemhen, Saheed L. Bello, Akin P. Iwayemi

Abstract:

The effectiveness of energy demand policy depends on identifying the key drivers of energy demand both in the short-run and the long-run. This paper examines the influence of regional differences on the link between energy demand and other explanatory variables for Nigeria, China and USA using the Vector Error Correction Model (VECM) approach. This study employed annual time series data on energy consumption (ED), real gross domestic product (GDP) per capita (RGDP), real energy prices (P) and urbanization (N) for a thirty-six-year sample period. The utilized time-series data are sourced from World Bank’s World Development Indicators (WDI, 2016) and US Energy Information Administration (EIA). Results from the study, shows that all the independent variables (income, urbanization, and price) substantially affect the long-run energy consumption in Nigeria, USA and China, whereas, income has no significant effect on short-run energy demand in USA and Nigeria. In addition, the long-run effect of urbanization is relatively stronger in China. Urbanization is a key factor in energy demand, it therefore recommended that more attention should be given to the development of rural communities to reduce the inflow of migrants into urban communities which causes the increase in energy demand and energy excesses should be penalized while energy management should be incentivized.

Keywords: economic growth, energy demand, income, real GDP, urbanization, VECM

Procedia PDF Downloads 298
24091 Pressure Losses on Realistic Geometry of Tracheobronchial Tree

Authors: Michaela Chovancova, Jakub Elcner

Abstract:

Real bronchial tree is very complicated piping system. Analysis of flow and pressure losses in this system is very difficult. Due to the complex geometry and the very small size in the lower generations is examination by CFD possible only in the central part of bronchial tree. For specify the pressure losses of lower generations is necessary to provide a mathematical equation. Determination of mathematical formulas for calculating the pressure losses in the real lungs is due to its complexity and diversity lengthy and inefficient process. For these calculations is necessary the lungs to slightly simplify (same cross-section over the length of individual generation) or use one of the models of lungs. The simplification could cause deviations from real values. The article compares the values of pressure losses obtained from CFD simulation of air flow in the central part of the real bronchial tree with the values calculated in a slightly simplified real lungs by using a mathematical relationship derived from the Bernoulli equation and continuity equation. Then, evaluate the desirability of using this formula to determine the pressure loss across the bronchial tree.

Keywords: pressure gradient, airways resistance, real geometry of bronchial tree, breathing

Procedia PDF Downloads 313
24090 MITOS-RCNN: Mitotic Figure Detection in Breast Cancer Histopathology Images Using Region Based Convolutional Neural Networks

Authors: Siddhant Rao

Abstract:

Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

Procedia PDF Downloads 205
24089 Low Probability of Intercept (LPI) Signal Detection and Analysis Using Choi-Williams Distribution

Authors: V. S. S. Kumar, V. Ramya

Abstract:

In the modern electronic warfare, the signal scenario is changing at a rapid pace with the introduction of Low Probability of Intercept (LPI) radars. In the modern battlefield, radar system faces serious threats from passive intercept receivers such as Electronic Attack (EA) and Anti-Radiation Missiles (ARMs). To perform necessary target detection and tracking and simultaneously hide themselves from enemy attack, radar systems should be LPI. These LPI radars use a variety of complex signal modulation schemes together with pulse compression with the aid of advancement in signal processing capabilities of the radar such that the radar performs target detection and tracking while simultaneously hiding enemy from attack such as EA etc., thus posing a major challenge to the ES/ELINT receivers. Today an increasing number of LPI radars are being introduced into the modern platforms and weapon systems so these LPI radars created a requirement for the armed forces to develop new techniques, strategies and equipment to counter them. This paper presents various modulation techniques used in generation of LPI signals and development of Time Frequency Algorithms to analyse those signals.

Keywords: anti-radiation missiles, cross terms, electronic attack, electronic intelligence, electronic warfare, intercept receiver, low probability of intercept

Procedia PDF Downloads 450
24088 Models of Environmental, Crack Propagation of Some Aluminium Alloys (7xxx)

Authors: H. A. Jawan

Abstract:

This review describes the models of environmental-related crack propagation of aluminum alloys (7xxx) during the last few decades. Acknowledge on effects of different factors on the susceptibility to SCC permits to propose valuable mechanisms on crack advancement. The reliable mechanism of cracking give a possibility to propose the optimum chemical composition and thermal treatment conditions resulting in microstructure the most suitable for real environmental condition and stress state.

Keywords: microstructure, environmental, propagation, mechanism

Procedia PDF Downloads 407
24087 Sensing Mechanism of Nano-Toxic Ions Using Quartz Crystal Microbalance

Authors: Chanho Park, Juneseok You, Kuewhan Jang, Sungsoo Na

Abstract:

Detection technique of nanotoxic materials is strongly imperative, because nano-toxic materials can harmfully influence human health and environment as their engineering applications are growing rapidly in recent years. In present work, we report the DNA immobilized quartz crystal microbalance (QCM) based sensor for detection of nano-toxic materials such as silver ions, Hg2+ etc. by using functionalization of quartz crystal with a target-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz crystal is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated fast and in situ detection of nanotoxic materials using quartz crystal microbalance. We report the label-free and highly sensitive detection of silver ion for present case, which is a typical nano-toxic material by using QCM and silver-specific DNA. The detection is based on the measurement of frequency shift of Quartz crystal from constitution of the cytosine-Ag+-cytosine binding. It is shown that the silver-specific DNA measured frequency shift by QCM enables the capturing of silver ions below 100pM. The results suggest that DNA-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nano-toxic ions, quartz crystal microbalance, frequency shift, target-specific DNA

Procedia PDF Downloads 310
24086 Micromechanical Investigation on the Influence of Thermal Stress on Elastic Properties of Fiber-Reinforced Composites

Authors: Arber Sejdiji, Jan Schmitz-Huebsch, Christian Mittelstedt

Abstract:

Due to its use in a broad range of temperatures, the prediction of elastic properties of fiber composite materials under thermal load is significant. Especially the transversal stiffness dominates the potential of use for fiber-reinforced composites (FRC). A numerical study on the influence of thermal stress on transversal stiffness of fiber-reinforced composites is presented. In the numerical study, a representative volume element (RVE) is used to estimate the elastic properties of a unidirectional ply with finite element method (FEM). For the investigation, periodic boundary conditions are applied to the RVE. Firstly, the elastic properties under pure mechanical load are derived numerically and compared to results, which are obtained by analytical methods. Thereupon thermo-mechanical load is implemented into the model to investigate the influence of temperature change with low temperature as a key aspect. Regarding low temperatures, the transversal stiffness increases intensely, especially when thermal stress is dominant over mechanical stress. This paper outlines the employed numerical methods as well as the derived results.

Keywords: elastic properties, micromechanics, thermal stress, representative volume element

Procedia PDF Downloads 93
24085 Exploring the Role of Building Information Modeling for Delivering Successful Construction Projects

Authors: Muhammad Abu Bakar Tariq

Abstract:

Construction industry plays a crucial role in the progress of societies and economies. Furthermore, construction projects have social as well as economic implications, thus, their success/failure have wider impacts. However, the industry is lagging behind in terms of efficiency and productivity. Building Information Modeling (BIM) is recognized as a revolutionary development in Architecture, Engineering and Construction (AEC) industry. There are numerous interest groups around the world providing definitions of BIM, proponents describing its advantages and opponents identifying challenges/barriers regarding adoption of BIM. This research is aimed at to determine what actually BIM is, along with its potential role in delivering successful construction projects. The methodology is critical analysis of secondary data sources i.e. information present in public domain, which include peer reviewed journal articles, industry and government reports, conference papers, books, case studies etc. It is discovered that clash detection and visualization are two major advantages of BIM. Clash detection option identifies clashes among structural, architectural and MEP designs before construction actually commences, which subsequently saves time as well as cost and ensures quality during execution phase of a project. Visualization is a powerful tool that facilitates in rapid decision-making in addition to communication and coordination among stakeholders throughout project’s life cycle. By eliminating inconsistencies that consume time besides cost during actual construction, improving collaboration among stakeholders throughout project’s life cycle, BIM can play a positive role to achieve efficiency and productivity that consequently deliver successful construction projects.

Keywords: building information modeling, clash detection, construction project success, visualization

Procedia PDF Downloads 249
24084 A Proposed Optimized and Efficient Intrusion Detection System for Wireless Sensor Network

Authors: Abdulaziz Alsadhan, Naveed Khan

Abstract:

In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

Procedia PDF Downloads 351
24083 Hardware Implementation for the Contact Force Reconstruction in Tactile Sensor Arrays

Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

Abstract:

Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 183
24082 The Effect of Heat Stress on the Gastro-Intestinal Microbiota of Pigs

Authors: Yadnyavalkya Patil, Ravi Gooneratne, Xiang-Hong Ju

Abstract:

Heat stress (HS) negatively affects the physiology of pigs. In this study, 6 pigs will be subjected to temperatures of 35 ± 2℃ for 12 hrs/day for a duration of 21 days. The changes in the gastrointestinal tract (GIT) microbiota will be observed by analyzing the freshly collected faeces on days 1, 3, 7, 14 and 21. The changes will be compared to faeces from a set of 6 control pigs kept simultaneously at temperatures of 26 ± 2℃ for the same duration of 21 days. Different types of stresses such a weaning have a detrimental effect on GIT microflora. Similarly, HS is expected to have a harmful effect on the microbial diversity of the GIT. How these changes affect the immune system of the pigs will be studied and therapeutics to reduce the negative effects of HS will be developed.

Keywords: GIT microbiota, heat stress, immune system, therapeutics

Procedia PDF Downloads 188
24081 Discovery of Exoplanets in Kepler Data Using a Graphics Processing Unit Fast Folding Method and a Deep Learning Model

Authors: Kevin Wang, Jian Ge, Yinan Zhao, Kevin Willis

Abstract:

Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars).

Keywords: algorithms, astronomy data analysis, deep learning, exoplanet detection methods, small planets, habitable planets, transit photometry

Procedia PDF Downloads 206
24080 Online Versus Offline Learning: A Comparative Analysis of Modes of Education Amidst Pandemic

Authors: Nida B. Syed

Abstract:

Following second wave of the current pandemic COVID-19, education transmission is occurring via both the modes of education, that is, online as well as offline in the college. The aim of the current study was, therefore, to bring forth the comparative analysis of both the modes of education and their impact on the levels of academic stress and states of the mental wellbeing of the students amidst the current pandemic. Measures of the constructs were obtained by the online Google forms, which consist of the Perceptions of Academic Stress Scale (PASS) by and Warwick-Edinburg Mental Well-being Scale, from a sample of 100 undergraduate students aged 19-25 years studying in different colleges of Bengaluru, India. Modes of education were treated as the predictor variables whilst academic stress, and mental wellbeing constituted the criterion variables. Two-way ANOVA was employed. Results show that the levels of academic stress are found to be a bit higher in students attending online classes as compared to those taking offline classes in college (MD = 1.10, df = 98, t = 0.590, p > 0.05), whereas mental wellbeing is found to be low in students attending offline classes in colleges than those taking online classes (MD = 5.180, df = 98, t =2.340, p > 0.05 level). The combined interactional effect of modes of education and academic stress on the states of the mental wellbeing of the students is found to be low (R2 = 0.053), whilst the combined impact of modes of education and mental wellbeing on the levels of academic stress was found to be quite low (R2 = 0.014). It was concluded that modes of education have an impact on levels of academic stress and states of the mental well-being of the students amidst the current pandemic, but it is low.

Keywords: modes of education, online learning, offline learning, pandemic

Procedia PDF Downloads 95
24079 For Post-traumatic Stress Disorder Counselors in China, the United States, and around the Globe, Cultural Beliefs Offer Challenges and Opportunities

Authors: Anne Giles

Abstract:

Trauma is generally defined as an experience, or multiple experiences, overwhelming a person's ability to cope. Over time, many people recover from the neurobiological, physical, and emotional effects of trauma on their own. For some people, however, troubling symptoms develop over time that can result in distress and disability. This cluster of symptoms is classified as Post-traumatic Stress Disorder (PTSD). People who meet the criteria for PTSD and other trauma-related disorder diagnoses often hold a set of understandable but unfounded beliefs about traumatic events that cause undue suffering. Becoming aware of unhelpful beliefs—termed "cognitive distortions"—and challenging them is the realm of Cognitive Behavior Therapy (CBT). A form of CBT found by researchers to be especially effective for PTSD is Cognitive Processing Therapy (CPT). Through the compassionate use of CPT, people identify, examine, challenge, and relinquish unhelpful beliefs, thereby reducing symptoms and suffering. Widely-held cultural beliefs can interfere with the progress of recovery from trauma-related disorders. Although highly revered, largely unquestioned, and often stabilizing, cultural beliefs can be founded in simplistic, dichotomous thinking, i.e., things are all right, or all wrong, all good, or all bad. The reality, however, is nuanced and complex. After studying examples of cultural beliefs from China and the United States and how these might interfere with trauma recovery, trauma counselors can help clients derive criteria for preserving helpful beliefs, discover, examine, and jettison unhelpful beliefs, reduce trauma symptoms, and live their lives more freely and fully.

Keywords: cognitive processing therapy (CPT), cultural beliefs, post-traumatic stress disorder (PTSD), trauma recovery

Procedia PDF Downloads 234
24078 Low-Cost IoT System for Monitoring Ground Propagation Waves due to Construction and Traffic Activities to Nearby Construction

Authors: Lan Nguyen, Kien Le Tan, Bao Nguyen Pham Gia

Abstract:

Due to the high cost, specialized dynamic measurement devices for industrial lands are difficult for many colleges to equip for hands-on teaching. This study connects a dynamic measurement sensor and receiver utilizing an inexpensive Raspberry Pi 4 board, some 24-bit ADC circuits, a geophone vibration sensor, and embedded Python open-source programming. Gather and analyze signals for dynamic measuring, ground vibration monitoring, and structure vibration monitoring. The system may wirelessly communicate data to the computer and is set up as a communication node network, enabling real-time monitoring of background vibrations at various locations. The device can be utilized for a variety of dynamic measurement and monitoring tasks, including monitoring earthquake vibrations, ground vibrations from construction operations, traffic, and vibrations of building structures.

Keywords: sensors, FFT, signal processing, real-time data monitoring, ground propagation wave, python, raspberry Pi 4

Procedia PDF Downloads 88
24077 Improvement in Drought Stress Tolerance in Wheat by Arbuscular Mycorrhizal Fungi

Authors: Seema Sangwan, Ekta Narwal, Kannepalli Annapurna

Abstract:

The aim of this study was to determine the effect of arbuscular mycorrhizal fungi (AMF) inoculation on drought stress tolerance in 3 genotypes of wheat subjected to moderate water stress, i.e. HD 3043 (drought tolerant), HD 2987 (drought tolerant), and HD 2967 (drought sensitive). Various growth parameters were studied, e.g. total dry weight, total shoot and root length, root volume, root surface area, grain weight and number, leaf area, chlorophyll content in leaves, relative water content, number of spores and percent colonisation of roots by arbuscular mycorrhizal fungi. Total dry weight, root surface area and chlorophyll content were found to be significantly high in AMF inoculated plants as compared to the non-mycorrhizal ones and also higher in drought-tolerant varieties of wheat as compared to the sensitive variety HD 2967, in moderate water stress treatments. Leakage of electrolytes was lower in case of AMF inoculated stressed plants. Under continuous water stress, leaf water content and leaf area were significantly increased in AMF inoculated plants as compared to un-inoculated stressed plants. Overall, the increased colonisation of roots of wheat by AMF in inoculated plants weather drought tolerant or sensitive could have a beneficial effect in alleviating the harmful effects of water stress in wheat and delaying its senescence.

Keywords: Arbuscular mycorrhizal fungi, wheat, drought, stress

Procedia PDF Downloads 180
24076 An Efficient Clustering Technique for Copy-Paste Attack Detection

Authors: N. Chaitawittanun, M. Munlin

Abstract:

Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: image detection, forgery image, copy-paste, attack detection

Procedia PDF Downloads 328
24075 Developing a Methodology to Examine Psychophysiological Responses during Stress Exposure and Relaxation: An Experimental Paradigm

Authors: M. Velana, G. Rinkenauer

Abstract:

Nowadays, nurses are facing unprecedented amounts of pressure due to the ongoing global health demands. Work-related stress can cause a high physical and psychological workload, which can lead, in turn, to burnout. On the physiological level, stress triggers an initial activation of the sympathetic nervous and adrenomedullary systems resulting in increases in cardiac activity. Furthermore, activation of the hypothalamus-pituitary-adrenal axis provokes endocrine and immune changes leading to the release of cortisol and cytokines in an effort to re-establish body balance. Based on the current state of the literature, it has been identified that resilience and mindfulness exercises among nurses can effectively decrease stress and improve mood. However, it is still unknown what relaxation techniques would be suitable for and to what extent would be effective to decrease psychophysiological arousal deriving from either a physiological or a psychological stressor. Moreover, although cardiac activity and cortisol are promising candidates to examine the effectiveness of relaxation to reduce stress, it still remains to shed light on the role of cytokines in this process so as to thoroughly understand the body’s response to stress and to relaxation. Therefore, the main aim of the present study is to develop a comprehensive experimental paradigm and assess different relaxation techniques, namely progressive muscle relaxation and a mindfulness exercise originating from cognitive therapy by means of biofeedback, under highly controlled laboratory conditions. An experimental between-subject design will be employed, where 120 participants will be randomized either to a physiological or a psychological stress-related experiment. Particularly, the cold pressor test refers to a procedure in which the participants have to immerse their non-dominant hands into ice water (2-3 °C) for 3 min. The participants are requested to keep their hands in the water throughout the whole duration. However, they can immediately terminate the test in case it would be barely tolerable. A pre-test anticipation phase and a post-stress period of 3 min, respectively, are planned. The Trier Social Stress Test will be employed to induce psychological stress. During this laboratory stressor, the participants are instructed to give a 5-min speech in front of a committee of communication specialists. Before the main task, there is a 10-min anticipation period. Subsequently, participants are requested to perform an unexpected arithmetic task. After stress exposure, the participants will perform one of the relaxation exercises (treatment condition) or watch a neutral video (control condition). Electrocardiography, salivary samples, and self-report will be collected at different time points. The preliminary results deriving from the pilot study showed that the aforementioned paradigm could effectively induce stress reactions and that relaxation might decrease the impact of stress exposure. It is of utmost importance to assess how the human body responds under different stressors and relaxation exercises so that an evidence-based intervention could be transferred in a clinical setting to improve nurses’ general health. Based on suggestive future laboratory findings, the research group plans to conduct a pilot-level randomized study to decrease stress and promote well-being among nurses who work in the stress-riddled environment of a hospital located in Northern Germany.

Keywords: nurses, psychophysiology, relaxation, stress

Procedia PDF Downloads 97
24074 Early Detection of Breast Cancer in Digital Mammograms Based on Image Processing and Artificial Intelligence

Authors: Sehreen Moorat, Mussarat Lakho

Abstract:

A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

Procedia PDF Downloads 248
24073 Vibrations of Springboards: Mode Shape and Time Domain Analysis

Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

Abstract:

Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain.

Keywords: springboard analysis, modal analysis, time domain analysis, vibrations

Procedia PDF Downloads 443
24072 Deep Learning and Accurate Performance Measure Processes for Cyber Attack Detection among Web Logs

Authors: Noureddine Mohtaram, Jeremy Patrix, Jerome Verny

Abstract:

As an enormous number of online services have been developed into web applications, security problems based on web applications are becoming more serious now. Most intrusion detection systems rely on each request to find the cyber-attack rather than on user behavior, and these systems can only protect web applications against known vulnerabilities rather than certain zero-day attacks. In order to detect new attacks, we analyze the HTTP protocols of web servers to divide them into two categories: normal attacks and malicious attacks. On the other hand, the quality of the results obtained by deep learning (DL) in various areas of big data has given an important motivation to apply it to cybersecurity. Deep learning for attack detection in cybersecurity has the potential to be a robust tool from small transformations to new attacks due to its capability to extract more high-level features. This research aims to take a new approach, deep learning to cybersecurity, to classify these two categories to eliminate attacks and protect web servers of the defense sector which encounters different web traffic compared to other sectors (such as e-commerce, web app, etc.). The result shows that by using a machine learning method, a higher accuracy rate, and a lower false alarm detection rate can be achieved.

Keywords: anomaly detection, HTTP protocol, logs, cyber attack, deep learning

Procedia PDF Downloads 194
24071 An Erudite Technique for Face Detection and Recognition Using Curvature Analysis

Authors: S. Jagadeesh Kumar

Abstract:

Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

Procedia PDF Downloads 268
24070 Study of Energy Efficient and Quality of Service Based Routing Protocols in Wireless Sensor Networking

Authors: Sachin Sharma

Abstract:

A wireless sensor network (WSN) consists of a large number of sensor nodes which are deployed over an area to perform local computations based on information gathered from the surroundings. With the increasing demand for real-time applications in WSN, real-time critical events anticipate an efficient quality-of-service (QoS) based routing for data delivery from the network infrastructure. Hence, maximizing the lifetime of the network through minimizing the energy is an important challenge in WSN; sensors cannot be easily replaced or recharged due to their ad-hoc deployment in a hazardous environment. Considerable research has been focused on developing robust energy efficient QoS based routing protocols. The main focus of this article is primarily on periodical cycling schemes which represent the most compatible technique for energy saving and we also focus on the data-driven approaches that can be used to improve the energy efficiency. Finally, we will make a review on some communication protocols proposed for sensor networks.

Keywords: energy efficient, quality of service, wireless sensor networks, MAC

Procedia PDF Downloads 331
24069 Estimation of Stress-Strength Parameter for Burr Type XII Distribution Based on Progressive Type-II Censoring

Authors: A. M. Abd-Elfattah, M. H. Abu-Moussa

Abstract:

In this paper, the estimation of stress-strength parameter R = P(Y < X) is considered when X; Y the strength and stress respectively are two independent random variables of Burr Type XII distribution. The samples taken for X and Y are progressively censoring of type II. The maximum likelihood estimator (MLE) of R is obtained when the common parameter is unknown. But when the common parameter is known the MLE, uniformly minimum variance unbiased estimator (UMVUE) and the Bayes estimator of R = P(Y < X) are obtained. The exact con dence interval of R based on MLE is obtained. The performance of the proposed estimators is compared using the computer simulation.

Keywords: Burr Type XII distribution, progressive type-II censoring, stress-strength model, unbiased estimator, maximum-likelihood estimator, uniformly minimum variance unbiased estimator, confidence intervals, Bayes estimator

Procedia PDF Downloads 445
24068 Effect of 8-OH-DPAT on the Behavioral Indicators of Stress and on the Number of Astrocytes after Exposure to Chronic Stress

Authors: Ivette Gonzalez-Rivera, Diana B. Paz-Trejo, Oscar Galicia-Castillo, David N. Velazquez-Martinez, Hugo Sanchez-Castillo

Abstract:

Prolonged exposure to stress can cause disorders related with dysfunction in the prefrontal cortex such as generalized anxiety and depression. These disorders involve alterations in neurotransmitter systems; the serotonergic system—a target of the drugs that are commonly used as a treatment to these disorders—is one of them. Recent studies suggest that 5-HT1A receptors play a pivotal role in the serotonergic system regulation and in stress responses. In the same way, there is increasing evidence that astrocytes are involved in the pathophysiology of stress. The aim of this study was to examine the effects of 8-OH-DPAT, a selective agonist of 5-HT1A receptors, in the behavioral signs of anxiety and anhedonia as well as in the number of astrocytes in the medial prefrontal cortex (mPFC) after exposure to chronic stress. They used 50 male Wistar rats of 250-350 grams housed in standard laboratory conditions and treated in accordance with the ethical standards of use and care of laboratory animals. A protocol of chronic unpredictable stress was used for 10 consecutive days during which the presentation of stressors such as motion restriction, water deprivation, wet bed, among others, were used. 40 rats were subjected to the stress protocol and then were divided into 4 groups of 10 rats each, which were administered 8-OH-DPAT (Tocris, USA) intraperitoneally with saline as vehicle in doses 0.0, 0.3, 1.0 and 2.0 mg/kg respectively. Another 10 rats were not subjected to the stress protocol or the drug. Subsequently, all the rats were measured in an open field test, a forced swimming test, sucrose consume, and a cero maze test. At the end of this procedure, the animals were sacrificed, the brain was removed and the tissue of the mPFC (Bregma: 4.20, 3.70, 2.70, 2.20) was processed in immunofluorescence staining for astrocytes (Anti-GFAP antibody - astrocyte maker, ABCAM). Statistically significant differences were found in the behavioral tests of all groups, showing that the stress group with saline administration had more indicators of anxiety and anhedonia than the control group and the groups with administration of 8-OH-DPAT. Also, a dose dependent effect of 8-OH-DPAT was found on the number of astrocytes in the mPFC. The results show that 8-OH-DPAT can modulate the effect of stress in both behavioral and anatomical level. Also they indicate that 5-HT1A receptors and astrocytes play an important role in the stress response and may modulate the therapeutic effect of serotonergic drugs, so they should be explored as a fundamental part in the treatment of symptoms of stress and in the understanding of the mechanisms of stress responses.

Keywords: anxiety, prefrontal cortex, serotonergic system, stress

Procedia PDF Downloads 310
24067 A Study on Puzzle-Based Game to Teach Elementary Students to Code

Authors: Jaisoon Baek, Gyuhwan Oh

Abstract:

In this study, we developed a puzzle game based on coding and a web-based management system to observe the user's learning status in real time and maximize the understanding of the coding of elementary students. We have improved upon and existing coding game which cannot be connected to textual language coding or comprehends learning state. We analyzed the syntax of various coding languages for the curriculum and provided a menu to convert icon into textual coding languages. In addition, the management system includes multiple types of tutoring, real-time analysis of user play data and feedback. Following its application in regular elementary school software classes, students reported positive effects on understanding and interest in coding were shown by students. It is expected that this will contribute to quality improvement in software education by providing contents with proven educational value by breaking away from simple learning-oriented coding games.

Keywords: coding education, serious game, coding, education management system

Procedia PDF Downloads 129
24066 Evaluation of Rheological Properties, Anisotropic Shrinkage, and Heterogeneous Densification of Ceramic Materials during Liquid Phase Sintering by Numerical-Experimental Procedure

Authors: Hamed Yaghoubi, Esmaeil Salahi, Fateme Taati

Abstract:

The effective shear and bulk viscosity, as well as dynamic viscosity, describe the rheological properties of the ceramic body during the liquid phase sintering process. The rheological parameters depend on the physical and thermomechanical characteristics of the material such as relative density, temperature, grain size, and diffusion coefficient and activation energy. The main goal of this research is to acquire a comprehensive understanding of the response of an incompressible viscose ceramic material during liquid phase sintering process such as stress-strain relations, sintering and hydrostatic stress, the prediction of anisotropic shrinkage and heterogeneous densification as a function of sintering time by including the simultaneous influence of gravity field, and frictional force. After raw materials analysis, the standard hard porcelain mixture as a ceramic body was designed and prepared. Three different experimental configurations were designed including midpoint deflection, sinter bending, and free sintering samples. The numerical method for the ceramic specimens during the liquid phase sintering process are implemented in the CREEP user subroutine code in ABAQUS. The numerical-experimental procedure shows the anisotropic behavior, the complete difference in spatial displacement through three directions, the incompressibility for ceramic samples during the sintering process. The anisotropic shrinkage factor has been proposed to investigate the shrinkage anisotropy. It has been shown that the shrinkage along the normal axis of casting sample is about 1.5 times larger than that of casting direction, the gravitational force in pyroplastic deformation intensifies the shrinkage anisotropy more than the free sintering sample. The lowest and greatest equivalent creep strain occurs at the intermediate zone and around the central line of the midpoint distorted sample, respectively. In the sinter bending test sample, the equivalent creep strain approaches to the maximum near the contact area with refractory support. The inhomogeneity in Von-Misses, pressure, and principal stress intensifies the relative density non-uniformity in all samples, except in free sintering one. The symmetrical distribution of stress around the center of free sintering sample, cause to hinder the pyroplastic deformations. Densification results confirmed that the effective bulk viscosity was well-defined with relative density values. The stress analysis confirmed that the sintering stress is more than the hydrostatic stress from start to end of sintering time so, from both theoretically and experimentally point of view, the sintering process occurs completely.

Keywords: anisotropic shrinkage, ceramic material, liquid phase sintering process, rheological properties, numerical-experimental procedure

Procedia PDF Downloads 329
24065 An Integrated DANP-PROMETHEE II Approach for Air Traffic Controllers’ Workload Stress Problem

Authors: Jennifer Loar, Jason Montefalcon, Kissy Mae Alimpangog, Miriam Bongo

Abstract:

The demanding, professional roles that air traffic controllers (ATC) play in air transport operation provided the main motivation of this paper. As the controllers’ workload stress becomes more complex due to various stressors, the challenge to overcome these in the pursuit of improving the efficiency of controllers and safety level of aircrafts has been relevant. Therefore, in order to determine the main stressors and surface the best alternative, two widely-known multi-criteria decision-making (MCDM) methods, DANP and PROMETHEE II, are applied. The proposed method is demonstrated in a case study at Mactan Civil Aviation Authority of the Philippines (CAAP). The results showed that the main stressors are high air traffic volume, extraneous traffic, unforeseen events, limitations and reliability of equipment, noise/distracter, micro climate, bad posture, relations with supervisors and colleagues, private life conditions/relationships, and emotional conditions. In the outranking of alternatives, compartmentalization is believed to be the most preferred alternative to overcome controllers’ workload stress. This implies that compartmentalization can best be applied to reduce controller workload stress.

Keywords: air traffic controller, DANP, MCDM, PROMETHEE II, workload stress

Procedia PDF Downloads 256
24064 Pigging Operation in Two-Phase Flow Pipeline- Empirical and Simulation

Authors: Behnaz Jamshidi, Seyed Hassan Hashemabadi

Abstract:

The main objective of this study is to investigate on pigging operation of two phase flow pipeline and compare the empirical and simulation results for 108 km long , 0.7934 mm (32 inches) diameter sea line of "Phase 1 South Pars Gas Complex", located in south of Iran. The pigging time, pig velocity, the amount of slug and slug catcher pressure were calculated and monitored closely as the key parameters. Simulation was done by "OLGA" dynamic simulation software and obtained results were compared and validated with empirical data in real operation. The relative errors between empirical data and simulation of the process were 3 % and 9 % for pigging time and accumulated slug volume respectively. Simulated pig velocity and changes of slug catcher pressure were consistent with real values, too. It was also found the slug catcher and condensate stabilization units have been adequately sized for gas-liquid separation and handle the slug batch during transient conditions such as pigging and start up.

Keywords: sea line, pigging, slug catcher, two-phase flow, dynamic simulation

Procedia PDF Downloads 482
24063 A Review of Intelligent Fire Management Systems to Reduce Wildfires

Authors: Nomfundo Ngombane, Topside E. Mathonsi

Abstract:

Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

Procedia PDF Downloads 69