Search results for: sturgeons monitoring (adults and juveniles)

Authors: Seyedvahid Najafi, Viliam Makis

Abstract:

In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

Procedia PDF Downloads 122

Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

Abstract:

Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344，p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

Procedia PDF Downloads 205

Authors: Divya Kanchibhotla

Abstract:

Of all the major health threats to emerge, none has challenged the very foundation of public health so profoundly as the rise of non-communicable diseases (NCD). Encouraging a holistic health approach encompasses the community’s well-being. Competent public health grounded with holistic health approach can lay a better foundation in the modern world. Yoga has been increasingly explored as an adjunct therapy to major disorders. This study explores the efficacy of Yoga as a tool for public health. A survey was administered to 5500 adults, and 300 teens were selected from 25 states of India. The study explored the differences in health, happiness, and sustainable living between Yoga-practitioners and Non-yoga practitioners. The study also explored the practice and habits of yoga practitioners (frequency, place, reasons to practice) and Health, Happiness, and Sustainable Living. The subjects were grouped based on age, education, experience in yoga (years of practice), and occupational background. The study population comprised of 54% males and 46% females. Majority of the respondents (59%) were from 18 to 30 years age group. The study indicated that 96.4% of the total respondents have heard of Yoga. However, only 46.8% of the total study population practice yoga (YP) and the rest 53.2% were non-practitioners (NP). From a perspective of how Yoga and health, 72.7% yoga practitioners asserted a peaceful and happy life, 71.9% yoga practitioners felt satisfaction in life, and 70.2 % yoga practitioners had satisfactory health. 61.9% of yoga practitioners report being vegetarian, not eating junk food, and not drinking alcohol than 38.1% Non-Practitioners population. 47% of yoga practitioners found themselves to be more sensitive to the environment compared to only 40% of non-practitioners. India has been witnessing an unprecedented rise in the NCDs, accounting for 61% deaths. The importance of yoga as an adjunct therapy for various disorders and diseases is gaining momentum across the globe. There are various studies on yoga that have indicated benefits of yoga as a unique holistic approach towards lifestyle and a consistent, complementary solution that could be adopted for long-term viability for a well being. The comprehensive study is the first of its kind that takes a holistic look at the prevalence of Yoga for public health in India. Our study is unique and stands out as it is detailed in its outlook with extensive coverage of almost the whole country (surveying 25 out of 29 states) and contemplates on the benefits to an individual at the grass-root level – physical, mental and social outlook. The insights from the study will enable the health care systems and grassroots organizations to make the holistic practice of Yoga accessible to spread sustainable living for a healthy community.

Keywords: non-communicable disease (NCD), sustainable development goal (SDG 3), public health, healthy living

Procedia PDF Downloads 194

Authors: Lunthita M. Duthely, John T. Avella, John Ganapati Coleman

Abstract:

For as many as one in three adolescents living in the United States, the adolescent years is a period of low well-being and mental health challenges—from depressive symptoms to mild to moderate psychological diagnoses. Longitudinal population health studies demonstrated that these challenges persist in young adulthood, and beyond. The positive psychology (PS) approach is a more preventative approach to well-being, which contrasts the traditional, deficits approach to curing mental illness. The research among adult populations formed the basis for PS studies among adolescents. The empirical evidence for the effectiveness of PS interventions exists for both adult and youth populations. Positive Psychology interventions target individuals’ strengths, such as hope and optimism, and positive emotions, such as gratitude. Positive psychology interventions such as increasing gratitude, proved effective in many outcomes among youth, including psychological, social, and academically-related outcomes. Although gratitude-inducing studies have been conducted for the past decade in the United States, few studies have been conducted among samples of urban youth, particularly youth of diverse cultural backgrounds. For nearly two decades, the secular practice of meditation has been tested among adults and more recently among youth, focused mostly among clinical samples. The field of Contemplative Sciences explores practices such as Hatha Yoga, Tai Chi, and Meditation, as preventative practices among children and adolescents. A more recent initiative is to explore Contemplative Practices in the school environment. Contemplative Practices yield a variety of positive outcomes, including academic, social, psychological, physiological, and neurological changes among children and adolescents. Again, few studies were conducted among adolescents of diverse cultural backgrounds. The purpose of this doctoral dissertation research study was to test a gratitude-meditation intervention among middle school students attending a public charter school, located in an urban region of Metropolitan Miami. The objective of this presentation is to summarize the challenges and success of bringing a positive psychology and meditation intervention into an urban middle school. Also, the most recent findings on positive psychology and meditation interventions conducted in school environments will be presented as well.

Keywords: adolescents, contemplative intervention, gratitude, secular meditation, positive psychology, school engagement, Sri Chinmoy

Procedia PDF Downloads 396

Authors: Ali Akbar Heydari

Abstract:

Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values.

Keywords: control chart, markov chain approach, statistical design, synthetic, variable parameter

Procedia PDF Downloads 153

Authors: Muhammad Alif Bin Razali, Cheng-Gang Xie, Wai Lam Loh

Abstract:

A venturi device is commonly used as an integral part of a multiphase flowmeter (MPFM) in real-time oil-gas production monitoring. For an accurate determination of individual phase fraction and flowrate, a gas-liquid flow ideally needs to be well mixed in the venturi measurement section. Partial flow mixing is achieved by installing a venturi vertically downstream of the blind-tee pipework that ‘homogenizes’ the incoming horizontal gas-liquid flow. In order to study in-depth the flow-mixing effect of the blind-tee, gas-liquid flows are captured at blind-tee and venturi sections by using a high-speed video camera and a purpose-built transparent test rig, over a wide range of superficial liquid velocities (0.3 to 2.4m/s) and gas volume fractions (10 to 95%). Electrical capacitance sensors are built to measure the instantaneous holdup (of oil-gas flows) at the venturi inlet and throat. Flow regimes and flow (a)symmetry are investigated based on analyzing the statistical features of capacitance sensors’ holdup time-series data and of the high-speed video time-stacked images. The perceived homogenization effect of the blind-tee on the incoming intermittent horizontal flow regimes is found to be relatively small across the tested flow conditions. A horizontal (blind-tee) to vertical (venturi) flow-pattern transition map is proposed based on gas and liquid mass fluxes (weighted by the Baker parameters).

Keywords: blind-tee, flow visualization, gas-liquid two-phase flow, MPFM

Procedia PDF Downloads 126

Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

Abstract:

Wet mills are one of the most important equipment in the mining industries and any defect occurrence in them can stop the production line and it can make some irrecoverable damages to the system. Electromotors are the significant parts of a mill and their monitoring is a necessary process to prevent unwanted defects. The purpose of this study is to investigate the Electromotor bearing defects, theoretically and practically, using the vibration analysis method. When a defect happens in a bearing, it can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. The electromotor defects source can be electrical or mechanical. Sometimes, the electrical and mechanical defect frequencies are modulated and the bearing defect detection becomes difficult. In this paper, to detect the electromotor bearing defects, the electrical and mechanical defect frequencies are extracted firstly. Then, by calculating the bearing defect frequencies, and the spectrum and time signal analysis, the bearing defects are detected. In addition, the obtained frequency determines that the bearing level in which the defect has happened and by comparing this level to the standards it determines the bearing remaining lifetime. Finally, the defect length is calculated by theoretical equations to demonstrate that there is no need to replace the bearing. The results of the proposed method, which has been implemented on the wet mills in the Golgohar mining and industrial company in Iran, show that this method is capable of detecting the electromotor bearing defects accurately and on time.

Keywords: bearing defect length, defect frequency, electromotor defects, vibration analysis

Procedia PDF Downloads 500

Authors: K. P. Ganesh, T. Gomathi, L. Arul Pragasan

Abstract:

Degradation of lake water quality is one of the serious environmental threats for the last few decades, particularly, the lakes situated in and around urban and industrial areas. The present study aimed to analyze the physicochemical and biological parameters, and metal elements to determine the water quality of Krishnampathi, Ukkadam, Kurichi, Sulur and Singanallur Lakes. Of the 23 physicochemical parameters analyzed in the five lakes, except TDS, Chloride and Total hardness values all the 20 parameters were found within the prescribed limit as recommended by World Health Organization (WHO) and Bureau of Indian Standards (BIS). In case of biological parameter, both Total Coliform and Fecal Coliform bacteria (Escherichia coli) were identified. This indicates the contamination of lakes by fecal matter, and warns of potential of disease causing by viruses, bacteria and other organisms. Among the twelve metal elements (Al, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Mo, Cd and Pb) determined by inductively coupled plasma-mass spectroscopy, except Cd (for all lakes), and Pb (for Ukkadam, Kurichi, Sulur & Singanallur), all the elements were found above the prescribed limits of BIS. The results of the present study revealed that all the five major lakes of Coimbatore were contaminated. It is recommended that proper implementation of the new wetland waste management system and monitoring of water quality be of the urgent need to sustain the water bodies for future generations.

Keywords: heavy metals, inductively coupled plasma-mass spectroscopy, physicochemical and biological parameters, water quality

Procedia PDF Downloads 177

Authors: Dr. Rebecca Kimelman

Abstract:

Teaching students to self-advocate has become a central topic in special education literature and practice. However, many special education programs do not address this important skill area. To this end, I created and implemented the Self Advocacy Made Easy (S.A.M.E.) program of instruction, intended to enhance the self-advocacy skills of young adults with mild to moderate disabilities. The effectiveness of S.A.M.E., the degree to which self-advocacy skills were acquired and demonstrated by the students, the level of parental support, and the impact of culture on the process, and teachers’ beliefs and attitudes about the role of self-advocacy skills for their students were measured using action research that employed mixed methodology. Conducted at an overseas American International School, this action research study sought answers to these questions by providing an in-depth portrayal of the S.A.M.E. program, as well as the attitudes and perceptions of the stakeholders involved in the study (thirteen students, their parents, teachers and counsellors). The findings of this study were very positive. The S.A.M.E. program was found to be a valid and valuable instructional tool for teaching self-advocacy skills to students with learning disabilities and ADHD. The study showed participation in the S.A.M.E. program led to an increased understanding of the important elements of self-advocacy, an increase in students’ skills and abilities to self-advocate, and a positive increase in students’ feelings about themselves. Inclusion in the Student-Led IEP meetings, an authentic student assessment within the S.A.M.E. program, also yielded encouraging results, including a higher level of ownership of one’s profile and learning needs, a higher level of student engagement and participation in the IEP meeting, and a growing student awareness of the relevance of the document and the IEP process to their lives. Without exception, every parent believed that participating in the Student-Led IEP led to a growth in confidence in their children, including that it taught them how to ‘own’ their disability and an improvement in their communication skills. Teachers and counsellors that participated in the study felt the program was worthwhile, and led to an increase in the students’ ability to acknowledge their learning profile and to identify and request the accommodations (such as extended time or use of a calculator) they need to overcome or work around their disability. The implications for further research are many, and include an examination of the degree to which participation in S.A.M.E. fosters student achievement, the long-term effects of participation in the program, and the degree to which student participation in the Student-Led IEP meeting increases parents’ level of understanding and involvement.

Keywords: self-advocacy, learning disabilities, ADHD, student-led IEP process

Procedia PDF Downloads 54

Authors: Sharon Milberger, Jane Turner, Denise White-Perkins

Abstract:

Michigan shares the overall U.S. national need for more highly qualified professionals who have knowledge and experience in the use of evidence-based practices to meet the special health care needs of children, adolescents, and adults with neurodevelopmental disabilities including autism spectrum disorder (DD/ASD). The Michigan Leadership Education in Neurodevelopmental Disabilities (MI-LEND) program is a consortium of six universities that spans the state of Michigan and serves more than 181,800 undergraduate, graduate, and professional students. The purpose of the MI LEND program is to improve the health of infants, children and adolescents with disabilities in Michigan by training individuals from different disciplines to assume leadership roles in their respective fields and work across disciplines. The MI-LEND program integrates “L.I.F.E.” perspectives into all training components. L.I.F.E. is an acronym for Leadership, Interdisciplinary, Family-Centered and Equity perspectives. This paper will describe how L.I.F.E. perspectives are embedded into all aspects of the MI-LEND training program including the application process, didactic training, community and clinical experiences, discussions, journaling and projects. Specific curriculum components will be described including content from a training module dedicated to Equity. Upon completion of the Equity module, trainees are expected to be able to: 1) Use a population health framework to identify key social determinants impacting families and children; 2) Explain how addressing bias and providing culturally appropriate linguistic care/services can influence patient/client health and wellbeing; and 3) Describe the impact of policy and structural/institutional factors influencing care and services for children with DD/ASD and their families. Each trainee completes two self-assessments: the Cultural and Linguistic Competence Health Practitioner Assessment and the other assessing social attitudes/implicit bias. Trainees also conduct interviews with a family with a child with DD/ASD. In addition, interdisciplinary Equity-related group activities are incorporated into face-to-face training sessions. Each MI-LEND trainee has multiple ongoing opportunities for self-reflection through discussion and journaling and completion of a L.I.F.E. project as a culminating component of the program. The poster will also discuss the challenges related to teaching and measuring successful outcomes related to diversity/equity perspectives.

Keywords: disability, diversity, equity, training

Procedia PDF Downloads 164

Authors: Zeynep Altinkaya, Ugur Dal, Figen Dag, Dilan D. Koyuncu, Merve Turkegun

Abstract:

Obesity is defined as abnormal fat-tissue accumulation as a result of imbalance between energy intake and expenditure. Since 50-70% daily energy expenditure of sedantary individuals is consumed as resting energy expenditure (REE), it takes an important place in the evaluation of new methods for obesity treatment. Also, it is known that walking is a prevalent activity in the prevention of obesity. The primary purpose of this study is to evaluate and compare the resting and walking energy expenditures of individuals with different body mass index (BMI). In this research, 4 groups are formed as underweight (BMI < 18,5 kg/m2), normal (BMI=18,5-24,9 kg/m2), overweight (BMI=25-29,9 kg/m2), and obese (BMI ≥ 30) according to BMI of individuals. 64 healthy young adults (8 man and 8 woman per group, age 18-30 years) with no known gait disabilities were recruited in this study. The body compositions of all participants were measured via bioelectric empedance analysis method. The energy expenditure of individuals was measured with indirect calorimeter method as inspired and expired gas samples are collected breath-by-breath through a special facemask. The preferred walking speed (PWS) of each subject was determined by using infrared sensors placed in 2nd and 12th meters of 14 m walkway. The REE was measured for 15 min while subjects were lying, and walking energy expenditure was measured during subjects walk in their PWS on treadmill. The gross REE was significantly higher in obese subjects compared to underweight and normal subjects (p < 0,0001). When REE was normalized to body weight, it was higher in underweight and normal groups than overweight and obese groups (p < 0,0001). However, when REE was normalized to fat-free mass, it did not differ significantly between groups. The gross walking energy expenditure in PWS was higher in obese and overweight groups than underweight and normal groups (p < 0,0001). The regression coefficient between gross walking energy expenditure and body weight was significiant among normal and obese groups (p < 0.05). It accounted for 70,5% of gross walking energy expenditure in normal group, and 57,9% of gross walking energy expenditure in obese group. It is known that obese individuals have more metabolically inactive fat-tissue compared to other groups. While excess fat-tissue increases total body weight, it does not contribute much to REE. Therefore, REE results normalized to body weight could lead to misleading results. In order to eliminate fat-mass effect on REE of obese individuals, REE normalized to fat-free mass should be used to acquire more accurate results. On the other hand, the fat-mass increasement raises energy requirement while walking to retain the body balance. Thus, gross walking energy expenditure should be taken into consideration for the evaluating energy expenditure of walking.

Keywords: body composition, obesity, resting energy expenditure, walking energy expenditure

Procedia PDF Downloads 387

Authors: A. Bouzekri, H. Benmassaud

Abstract:

Aurès region is one of the arid and semi-arid areas that have suffered climate crises and overexploitation of natural resources they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and its spatiotemporal changes in the Aurès between 1987 and 2013, for this work, we adopted a method of analysis based on the exploitation of the images satellite Landsat TM 1987 and Landsat OLI 2013, from the supervised classification likelihood coupled with field surveys of the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover maps from 1987 and 2013, one can extract a spatial map change of different land cover units. The results show that between 1987 and 2013 vegetation has suffered negative changes are the significant degradation of forests and steppe rangelands, and sandy soils and bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013 allows us to understand the extensive or regressive orientation of vegetation and soil, this map shows that dense forests give his place to clear forests and steppe vegetation develops from a degraded forest vegetation and bare, sandy soils earn big steppe surfaces that explain its remarkable extension. The analysis of remote sensing data highlights the profound changes in our environment over time and quantitative monitoring of the risk of desertification.

Keywords: remote sensing, spatiotemporal, land use, Aurès

Procedia PDF Downloads 333

Authors: Anton A. Bykov, Irina O. Glot, Igor N. Shardakov, Alexey P. Shestakov

Abstract:

This paper presents the results of experimental and theoretical investigations of the mechanisms of crack formation in reinforced concrete beams subjected to quasi-static bending. The boundary-value problem has been formulated in the framework of brittle fracture mechanics and has been solved by using the finite-element method. Numerical simulation of the vibrations of an uncracked beam and a beam with cracks of different size serves to determine the pattern of changes in the spectrum of eigenfrequencies observed during crack evolution. Experiments were performed on the sequential quasistatic four-point bending of the beam leading to the formation of cracks in concrete. At each loading stage, the beam was subjected to an impulse load to induce vibrations. Two stages of cracking were detected. At the first stage the conservative process of deformation is realized. The second stage is an active cracking, which is marked by a sharp change in eingenfrequencies. The boundary of a transition from one stage to another is well registered. The vibration behavior was examined for the beams strengthened by carbon-fiber sheet before loading and at the intermediate stage of loading after the grouting of initial cracks. The obtained results show that the vibrodiagnostic approach is an effective tool for monitoring of cracking and for assessing the quality of measures aimed at strengthening concrete structures.

Keywords: crack formation, experiment, mathematical modeling, reinforced concrete, vibrodiagnostics

Procedia PDF Downloads 304

Authors: Jingting Luo, Yong Wang, Ying Wang

Abstract:

Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

Procedia PDF Downloads 141

Authors: Homa Torabizadeh, Mohaddeseh Mikani

Abstract:

Inulinase from Aspergillus niger was covalently immobilized on magnetic nanoparticles (MNPs/Fe₃O₄) covered with soy protein isolate (SPI/Fe₃O₄) functionalized by bovine serum albumin (BSA) nanoparticles. MNPs are promising enzyme carriers because they separate easily under external magnetic fields and have enhanced immobilized enzyme reusability. As MNPs aggregate simply, surface coating strategy was employed. SPI functionalized by BSA was a suitable candidate for nanomagnetite coating due to its superior biocompatibility and hydrophilicity. Fe₃O₄@SPI-BSA nanoparticles were synthesized as a novel carrier with narrow particle size distribution. Step by step fabrication monitoring of Fe₃O₄@SPI-BSA nanoparticles was performed using field emission scanning electron microscopy and dynamic light scattering. The results illustrated that nanomagnetite with the spherical morphology was well monodispersed with the diameter of about 35 nm. The average size of the SPI-BSA nanoparticles was 80 to 90 nm, and their zeta potential was around −34 mV. Finally, the mean diameter of fabricated Fe₃O₄@SPI-BSA NPs was less than 120 nm. Inulinase enzyme from Aspergillus niger was covalently immobilized through gluteraldehyde on Fe₃O₄@SPI-BSA nanoparticles successfully. Fourier transform infrared spectra and field emission scanning electron microscopy images provided sufficient proof for the enzyme immobilization on the nanoparticles with 80% enzyme loading.

Keywords: high fructose syrup, inulinase immobilization, functionalized magnetic nanoparticles, soy protein isolate

Procedia PDF Downloads 296

Authors: Kalbende Krunal Ramesh

Abstract:

The Carbon Capture and Storage Technology (CCS) provides a veritable platform to bridge the gap between the seemingly irreconcilable twin global challenges of ensuring a secure, reliable and diversified energy supply and mitigating climate change by reducing atmospheric emissions of carbon dioxide. Making its proper regulatory policy and making it flexible for the government and private company by law to regulate, also exploring the opportunity in this sector is the main aim of this paper. India's total annual emissions was 1725 Mt CO2 in 2011, which comprises of 6% of total global emission. It is very important to control the greenhouse gas emission for the environment protection. This paper discusses the various regulatory policy and technology adopted by some of the countries for successful using CCS technology. The brief geology of sedimentary basins in India is studied, ranging from the category I to category IV and deep water and potential for mature technology in CCS is reviewed. Areas not suitable for CO2 storage using presently mature technologies were over viewed. CSS and Clean development mechanism was developed for India, considering the various aspects from research and development, project appraisal, approval and validation, implementation, monitoring and verification, carbon credit issued, cap and trade system and its storage potential. The opportunities in oil and gas operations, power sector, transport sector is discussed briefly.

Keywords: carbon credit issued, cap and trade system, carbon capture and storage technology, greenhouse gas

Procedia PDF Downloads 432

Authors: Berhane Gebreslassie

Abstract:

Conventional commericial buildings are among the highest unwisely consumes enormous amount of energy and as consequence produce significant amount Carbon Dioxide (CO2). Traditional/conventional buildings have been built for years without consideration being given to their impact on the global warming issues as well as their CO2 contributions. Since 1973, simulation of Green Building (GB) for Energy Efficiency started and many countries in particular the US showed a positive response to minimize the usage of energy in respect to reducing the CO2 emission. As a consequence many software companies developed their own unique building energy efficiency simulation software, interfacing interoperability with Building Information Modeling (BIM). The last decade has witnessed very rapid growing number of researches on GB energy efficiency system. However, the study also indicates that the results of current GB simulation are not yet satisfactory to meet the objectives of GB. In addition most of these previous studies are unlikely excluded the studies of ultimate building energy efficiencies simulation. The aim of this project is to meet the objectives of GB by design, modeling and simulation of building ultimate energy efficiencies system. This research project presents multi-level, L-shape office building in which every particular part of the building materials has been tested for energy efficiency. An overall of 78.62% energy is saved, approaching to NetZero energy saving. Furthermore, the building is implements with distributed energy resources like renewable energies and integrating with Smart Building Automation System (SBAS) for controlling and monitoring energy usage.

Keywords: ultimate energy saving, optimum energy saving, green building, sustainable materials and renewable energy

Procedia PDF Downloads 273

Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

Abstract:

Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

Procedia PDF Downloads 4

Authors: Carlos Fontanillas

Abstract:

The implementation of the lean six sigma methodology aims to implement practices to systematically improve processes by eliminating defects, making them cheaper. The implementation of projects with the methodology uses a division into five phases: definition, measurement, analysis, implementation, and control. In this process, it is understood that the implementation of said methodology generates benefits to organizations that adhere through the improvement of their processes. In the case of a telecommunications company, it was realized that the implementation of a lean six sigma project contributed to the improvement of the presented process, generating a financial return with the avoided cost. However, such study has limitations such as a specific segment of performance and procedure, i.e., it can not be defined that return under other circumstances will be the same. It is also concluded that lean six sigma projects tend to contribute to improved processes evaluated due to their methodology that is based on statistical analysis and quality management tools and can generate a financial return. It is hoped that the present study can be used to provide a clearer view of the methodology for entrepreneurs who wish to implement process improvement actions in their companies, as well as to provide a foundation for professionals working with lean six sigma projects. After the review of the processes, the completion of the project stages and the monitoring for three months in partnership with the owner of the process to ensure the effectiveness of the actions, the project was completed with the objective reached. There was an average of 60% reduction with the issuance of undue invoices generated after the deactivation and it was possible to extend the project to other companies, which allowed a reduction well above the initially stipulated target.

Keywords: quality, process, lean six sigma, organization

Procedia PDF Downloads 128

Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

Abstract:

This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

Procedia PDF Downloads 54

Authors: Bulcha Belay Etana

Abstract:

Research shows that several challenges are to be resolved for textile sensors and wearable smart textiles systems to make it accurate and reproducible minimizing variability issues when tested. To achieve this, we developed stimulating embroidery electrode with three different filling textiles such as 3Dknit, microfiber, and nonwoven fabric, and tested with FTT for high recoverability on compression. Hence The impedance characteristics of wetted electrodes were caried out after 1hr of wetting under normal environmental conditions. The wetted 3D knit (W-3D knit), Wetted nonwoven (W-nonwoven), and wetted microfiber (W-microfiber) developed using Satin stitch performed better than a dry standard stitch or dry Satin stitch electrodes. Its performance was almost the same as that of the gel electrode (Ag/AgCl) as shown by the impedance result in figure 2 .The impedance characteristics of Dry and wetted 3D knit based Embroidered electrodes are better than that of the microfiber, and nonwoven filling textile. This is due to the fact that 3D knit fabric has high recoverability on compression to retain electrolyte gel than microfiber, and nonwoven. However,The non-woven fabric held the electrolyte for longer time without releasing it to the skin when needed, thus making its impedance characteristics poor as observed from the results. Whereas the dry Satin stitch performs better than the standard stitch based developed electrode. The inter electrode distance of all types of the electrode was 25mm, with the area of the electrode being 20mm by 20mm. Detail evaluation and further analysis is in progress for EMG monitoring application

Keywords: impedance, moisture retention, 3D knit fabric, microfiber, nonwoven

Procedia PDF Downloads 138

Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

Abstract:

Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

Procedia PDF Downloads 353

Authors: Ki Hwa Lee, Eunsu Kang, Jae Hong Park

Abstract:

Background: Interventional neuroradiology (INR) has been a rapidly growing and evolving neurosurgical part during the past few decades. Sevoflurane and propofol are both suitable anesthetics for INR procedure. Monitoring of depth of anesthesia is being used very widely. SEDLine™ monitor, a 4-channel processed EEG monitor, uses a proprietary algorithm to analyze the raw EEG signal and displays the Patient State Index (PSI) values. There are only a fewer studies examining the PSI in the neuro-anesthesia. We aimed to investigate the difference of PSI values and hemodynamic variables between sevoflurane and propofol anesthesia during INR procedure. Methods: We reviewed the medical records of patients who scheduled to undergo embolization of non-ruptured intracranial aneurysm by a single operator from May 2013 to December 2014, retrospectively. Sixty-five patients were categorized into two groups; sevoflurane (n = 33) vs propofol (n = 32) group. The PSI values, hemodynamic variables, and the use of hemodynamic drugs were analyzed. Results: Significant differences were seen between PSI values obtained during different perioperative stages in both two groups (P < 0.0001). The PSI values of propofol group were lower than that of sevoflurane group during INR procedure (P < 0.01). The patients in propofol group had more prolonged time of extubation and more phenylephrine requirement than sevoflurane group (p < 0.05). Anti-hypertensive drug was more administered to the patients during extubation in sevoflurane group (p < 0.05). Conclusions: The PSI can detect depth of anesthesia and changes of concentration of anesthetics during INR procedure. Extubation was faster in sevoflurane group, but smooth recovery was shown in propofol group.

Keywords: interventional neuroradiology, patient state index, propofol, sevoflurane

Procedia PDF Downloads 179

Authors: Mei Lin, Lana Yj Liu, Thin Ngoc Pham

Abstract:

Postgraduate taught (PGT) students’ learning strategies align with what the learning task constitutes and the environment that the task creates. Cognitively, they can discover new perspectives, challenge general assumptions, establish clear connections, and synthesise information. Metacognitively, their engagement is conducive to the development of planning, monitoring, and evaluating strategies. Given that there has been a lack of longitudinal insights into international PGT students’ experiences of the cognitive and metacognitive space created in the tasks, this paper presentation aims to fill the gaps by longitudinally exploring (1) the fundamentals of task designs to create cognitive and metacognitive space and (2) the opportunities and challenges of multicultural group discussions as a pedagogical approach for the implementation of cognitive and metacognitive space in the learning tasks. Data were collected from the two rounds of semi-structured interviews with 11 international PGT students in two programmes at a UK university -at the end of semester one and at the end of semester two. The findings show that the task designs, to create cognitive and metacognitive space, need to include four interconnected factors: clarity, relevance, motivation, and practicality. In addition, international PGT students perceived that they practised and developed their cognitive and metacognitive abilities while getting immersed in multicultural group discussions. The findings, from the learners’ point of view, make some pedagogy-related suggestions to the task designs at the master’s level, particularly how to engage students in learning during their transition into higher education in a different cultural setting.

Keywords: cognitive space, master students, metacognitive space, task design

Procedia PDF Downloads 58

Authors: Apostolos Lagarias, Anastasia Stratigea

Abstract:

Coastal urbanization is heavily affecting the Mediterranean, taking the form of linear urban sprawl along the coastal zone. This process is posing extreme pressure on ecosystems, leading to an unsustainable model of growth. The aim of this research is to analyze coastal urbanization patterns in the Mediterranean using High-resolution multi-temporal data provided by the Global Human Settlement Layer (GHSL) database. Methodology involves the estimation of a set of spatial metrics characterizing the density, aggregation/clustering and dispersion of built-up areas. As case study areas, the Spanish Coast and the Adriatic Italian Coast are examined. Coastalization profiles are examined and selected sub-areas massively affected by tourism development and suburbanization trends (Costa Blanca/Murcia, Costa del Sol, Puglia, Emilia-Romagna Coast) are analyzed and compared. Results show that there are considerable differences between the Spanish and the Italian typologies of spatial development, related to the land use structure and planning policies applied in each case. Monitoring and analyzing spatial patterns could inform integrated Mediterranean strategies for coastal areas and redirect spatial/environmental policies towards a more sustainable model of growth

Keywords: coastalization, Mediterranean, multi-temporal, urban sprawl, spatial metrics

Procedia PDF Downloads 137

Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

Abstract:

Several problems in industrial supervision software development projects may lead to the delay or cancellation of projects. These problems can be avoided or contained by using identification methods, analysis and control of risks. These procedures can give an overview of the possible problems that can happen in the projects and what are the immediate solutions. Therefore, we propose a risk management method applied to the teaching and development of industrial supervision software. The method is developed through a literature review and previous projects can be divided into phases of management and have basic features that are validated with experimental research carried out by mechatronics engineering students and professionals. The management is conducted through the stages of identification, analysis, planning, monitoring, control and communication of risks. Programmers use a method of prioritizing risks considering the gravity and the possibility of occurrence of the risk. The outputs of the method indicate which risks occurred or are about to happen. The first results indicate which risks occur at different stages of the project and what risks have a high probability of occurring. The results show the efficiency of the proposed method compared to other methods, showing the improvement of software quality and leading developers in their decisions. This new way of developing supervision software helps students identify design problems, evaluate software developed and propose effective solutions. We conclude that the risk management optimizes the development of the industrial process control software and provides higher quality to the product.

Keywords: supervision software, risk management, industrial supervision, project management

Procedia PDF Downloads 354

Authors: Yun-Tsuen Chen, Shih-Ting Huang, Pi-Fen Cheng, Yu-Ting Su, Joffrey Hsu, Hui-Zhu Chen

Abstract:

Acute intestinal obstruction is one of the differentials of acute abdomen and requires timely alleviation of intestinal distention and abdominal pain to avoid perforation, intra-abdominal infection, and peritonitis. Investigation to identify the cause of obstruction will direct treatment planning and allow for more effective management. In this study, we present a 71-year-old female presenting with symptoms of acute intestinal obstruction for five days. After extensive history taking, physical exam, medical imaging, and pathology, the patient was diagnosed with colon cancer with lung metastasis and acute intestinal obstruction. The patient was placed on nil per os status with intravenous fluid support, intravenous antibiotics, and a decompression nasogastric tube was placed. The patient received decompression with colostomy creation surgery. After assessing the patient’s clinical condition and tumor staging, a multidisciplinary healthcare team created an individualized treatment plan, which included plans to prepare the patient for home self-care and maintain good mental health with regular monitoring in the clinic setting. This case demonstrates the importance of early diagnosis, effective treatment, and a multidisciplinary approach to the management of acute intestinal obstruction secondary to colon cancer.

Keywords: acute intestinal obstruction, colostomy surgery, metastatic colon cancer, multidisciplinary healthcare team

Procedia PDF Downloads 114

Authors: Sarwat un Nisa

Abstract:

One of the remarkable gifts that a human being is blessed with is the ability to speak using a combination of sounds. Different combinations of sounds combine to form a word which in turn make a sentence and therefore give birth to a language. A person can either be a monolingual, i.e., can speak one language or bilingual, i.e., can speak more than one language. Whether a person speaks one language or multiple languages or in whatever language a person speaks, the main aim is to communicate, express ideas, feelings or thoughts. Sometimes the choice of a language is deliberate and sometimes it is a habitual act. The language which is used to put our ideas across speaks many things about our cultural, linguistic and ethnic identities. It can never be claimed that bilinguals are better than monolinguals in terms of linguistic skills, bilinguals or multilinguals have more than one language at their disposal. Therefore, how effectively two languages are used by the same person keeps linguists always intrigued. The most prominent and common features found in the speech of bilingual speakers are code switching and code mixing. The aim of the present paper is to explore these features among the adolescent speakers of Kashmir. The reason for studying the linguistics behavior of adolescents is the age when a person is neither an adult nor a child. They want to drift away from the norms and make a new norm for themselves. Therefore, how their linguistics skills are influenced by their age is of great interest because it can set the trend for the future generation. Kashmir is a multilingual society where three languages, i.e., Kashmiri, Urdu, and English are regularly used by the speakers, especially the educated ones. Kashmiri is widely used at home or mostly among adults. Urdu is the official language, and English is used in schools and for most of the written official correspondences. Thus, it is not uncommon to find these three languages coming in contact with each other quite frequently. The language contact results in the code switching and code mixing. In this paper different aspects of code switching and code mixing are discussed. Research Method: The data were collected from the different districts of Kashmir. The informants did not have prior knowledge of the survey. The situation was spontaneous and natural. The topics were introduced by the interviewer to the group of informants which comprised of three participants. They were asked to discuss the topic, most of the times without any intervention of the interviewer. Along with conversations, the informants also filled in written questionnaires comprising sociolinguistic questions. Questionnaires were analysed to get an idea about the sociolinguistic attitude of the informants. Percentage, frequency, and average were used as statistical tools to analyse the data. Conclusions were drawn taking into consideration of interpretations of both speech samples and questionnaires.

Keywords: code mixing, code switching, Kashmir, bilingualism

Procedia PDF Downloads 142

Authors: A. Rinaldi, A. Proietti, C. Aquarelli, F. Marra, A. Tamburrano, M. Ciminello, M. S. Sarto

Abstract:

A new type of high sensitive piezoresistive sensors based on graphene was developed within the SARISTU project for application on Structural Health Monitoring (SHM). The new sensor consists of a graphene-based film, obtained through the spray deposition of a colloidal suspension of Multi-Layer Graphene (MLGs) nano platelets over a substrate. MLGs are produced by liquid exfoliation of thermally expanded Graphite Intercalation Compound. An array of 8 sensors is produced by spray deposition over an aeronautical CFRC plate of dimensions 550 mm (length) × 550 mm (width) × 3 mm (thickness). Electromechanical tests were performed in order to assess the sensitivity of the new piezoresistive sensors, which are characterized by an isotropic response. In the quasi-static characterizations, the CFRC plate was clamped on one side and loaded on the opposite one. The local strain map of the plate was then obtained from displacement measurements and numerical analysis. The dynamic tests were performed lying the plate over an anti-vibration table and actuating a piezoelectric element located in the middle of the sensing array. The obtained experimental results demonstrated that the sensors possess a good repeatability and a high constant gauge factor (~200) in the applied strain range 0.001%-0.02%. Moreover, they can follow dynamics up to 400 kHz and for this reason they are good candidates for Lamb-wave analysis.

Keywords: graphene, strain sensor, spray deposition, lamb-wave analysis

Procedia PDF Downloads 430

Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

Abstract:

Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

Procedia PDF Downloads 232