Search results for: trained graphic designers

Authors: David Dean Hampton, William Morrison, Mary Rizza, Jan Osborn

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This evaluation examined the effects of a supplemental reading intervThis evaluation examined the effects of a supplemental reading intervention for students with specific learning disabilities in reading who were presented with below grade level on fall benchmark scores on DIBELS 6th ed. Revised. Participants consisted of a condition group, those who received supplemental reading instruction in addition to core + special education services and a comparison group of students who were at grade level in their fall benchmark scores. The students in the condition group received 26 weeks of Project MORE instruction delivered multiple times each week from trained volunteer tutors. Using a regression-discontinuity design, condition and comparison groups were compared on reading development growth using DIBELS ORF. Significant findings were reported for grade 2, 3, and 4. ntion for students with specific learning disabilities in reading who presented with below grade level on fall benchmark scores on DIBELS 6th ed. Revised. Participants consisted of a condition group, those who received supplemental reading instruction in addition to core + special education services and a comparison group of students who were at grade level in their fall benchmark scores. The students in the condition group received 26 weeks of Project MORE instruction delivered multiple times each week from trained volunteer tutors. Using a regression-discontinuity design, condition and comparison groups were compared on reading development growth using DIBELS ORF. Significant findings were reported for grade 2, 3, and 4.

Keywords: special education, evidence-based practices, curriculum, tutoring

Procedia PDF Downloads 48

Authors: C. S. Subhashini, H. L. Premaratne

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Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

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Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani

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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.

Keywords: material point method, woven fabric composites, forming, material handling

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Authors: Sushil Kumar, M. Dakshina Murty

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Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

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Authors: A. Chellil, A. Nour, S. Lecheb , H. Mechakra, L. Addar, H. Kebir

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This paper present a mechanical characteristics on fatigue crack propagation in Aluminium Plate based on strain and stress distribution using the abaqus software. The changes in shear strain and stress distribution during the fatigue cycle with crack growth is identified. In progressive crack in the strain distribution and the stress is increase in the critical zone. Numerical Modal analysis of the model developed, prove that the Eigen frequencies of aluminium plate were decreased after cracking, and this reduce is nonlinear. These results can provide a reference for analysts and designers of aluminium alloys in aeronautical systems. Therefore, the modal analysis is an important factor for monitoring the aeronautic structures.

Keywords: aluminum alloys, plate, crack, failure

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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Authors: Amirul Adlan, Robert McCulloch, Scott Evans, Michael Parry, Jonathan Stevenson, Lee Jeys

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Background and Objectives: The gastrocnemius myofascial flap is used to manage soft-tissue defects over the anterior aspect of the knee in the context of a patient presenting with a sinus and periprosthetic joint infection (PJI) or extensor mechanism failure. The aim of this study was twofold: firstly, to evaluate the outcomes of gastrocnemius flaps performed by appropriately trained orthopaedic surgeons in the context of PJI and, secondly, to evaluate the infection-free survival of this patient group. Methods: We retrospectively reviewed 30 patients who underwent gastrocnemius flap reconstruction during staged revision total knee arthroplasty for prosthetic joint infection (PJI). All flaps were performed by an orthopaedic surgeon with orthoplastics training. Patients had a mean age of 68.9 years (range 50–84) and were followed up for a mean of 50.4 months (range 2–128 months). A total of 29 patients (97 %) were categorized into Musculoskeletal Infection Society (MSIS) local extremity grade 3 (greater than two compromising factors), and 52 % of PJIs were polymicrobial. The primary outcome measure was flap failure, and the secondary outcome measure was a recurrent infection. Results: Flap survival was 100% with no failures or early returns to theatre for flap problems such as necrosis or haematoma. Overall infection-free survival during the study period was 48% (13 of 27 infected cases). Using limb salvage as the outcome, 77% (23 of 30 patients) retained the limb. Infection recurrence occurred in 48% (10 patients) in the type B3 cohort and 67% (4 patients) in the type C3 cohort (p = 0.65). Conclusion: The surgical technique for a gastrocnemius myofascial flap is reliable and reproducible when performed by appropriately trained orthopaedic surgeons, even in high-risk groups. However, the risks of recurrent infection and amputation remain high within our series due to poor host and extremity factors.

Keywords: gastrocnemius flap, limb salvage, revision arthroplasty, outcomes

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Authors: Mark Lindquist

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This paper presents preliminary results of exploratory empirical research investigating the effect of viewing 3D landscape visualizations in virtual reality compared to a computer monitor, and how sound impacts perception. Five landscape types were paired with three sound conditions (no sound, generic sound, realistic sound). Perceived realism, preference, recreational value, and biodiversity were evaluated in a controlled laboratory environment. Results indicate that sound has a larger perceptual impact than display mode regardless of sound source across all perceptual measures. The results are considered to assess how sound can impact landscape preference and spatiotemporal understanding. The paper concludes with a discussion of the impact on designers, planners, and the public and targets future research endeavors in this area.

Keywords: landscape experience, perception, soundscape, virtual reality

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Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

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Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

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Authors: Weera Chotithammaporn, Bannasorn Santhan

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The purpose of this study was to investigate the students’ satisfaction towards the counseling services of the Faculty of Industrial Technology, Suan Sunandha Rajabhat University. The sample group consisted of 311 students coming for counseling services during September to October 2012 BE to complete the questionnaires developed by the researcher. The data were analyzed to find percentage, arithmetic mean, and SD, from which it can be concluded that: 1) Personal information including gender, GPA, department, year of the study, and hometown revealed that most of the students in the Faculty of Industrial Technology, Suan Sunandha Rajabhat University were female with the GPA between 2.01 and 2.50 and studied in the Department of Interior and Exhibition Design and Graphic and Multimedia Design. Most of them were in the first year of the study and came from the southern part of Thailand. 2) The level of students’ satisfaction towards the counseling services of the Faculty of Industrial Technology, Suan Sunandha Rajabhat University was in overall at high level with the highest aspect on IT services followed by follow-up and evaluation service, counseling service, individual personal data collecting service, and personal placement service respectively.

Keywords: satisfaction, students, counseling service, Faculty of Industrial Technology

Procedia PDF Downloads 258

Authors: Joy Cao, Min Zhou

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Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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Authors: Lewis Mehl-Madrona, Barbara Mainguy, Patrick McFarlane

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Introduction: There are many risk factors for attempting suicide, including young age, “minority stress,” which would include Transgender and Gender Diverse orientations (TGD). The rate of TGD youths for suicide attempts is 3 times higher than heterosexual cis-gender youth. Half of TGD youth have seriously contemplated taking their own lives; of those, about half attempted suicide; and 18% of the TGD teenagers reported suicidal thoughts linked to their gender identity. Native American TGD have a six times higher suicide attempt rate. Conventional mental health has not generally helped these individuals. Stigma and discrimination contribute to healthcare disparities. Storytelling plays a crucial role in the development of human culture and individual identities. Sharing narrative artwork, creative writing, and personal stories allow people to build trust and to share their vulnerabilities. This helps people become aware of themselves in relation to others and gain a sense of comfort that their stories are similar; they may also be transformed in the process. Art provides a means to reach people who are otherwise difficult to engage in services. Methods: TGD individuals are recruited through a snowballing procedure. Following a life story interview, participants complete a scale of gender dysphoria, identification with conventional masculinity, patient-reported anxiety, and depression measure, and a quality-of-life scale. The interview completes the Columbia Suicide Scale. Following this, an artist and a therapist works with the participant to create a story related to their gender identity using the six-part story method. This story is then rendered to an artists’ book, which combines narrative with art (drawings, collage, computer images, etc.) and can take the form of a graphic novella, a zine, or a comic book. The pages can range from plain to ornate, as can the covers. Participants describe their process of making the books as the work unfolds and then participate in an exit interview at the completion of their book, remarking on what has changed for them and how the process affected them. Results: Preliminary results show high levels of suicidal thoughts among this population, as expected. Participants participate enthusiastically in the life story interview process and in the construction of a story related to gender identity. They enthusiastically participate in the studio process of putting their story into the form of a graphic novel, zine, or comic book. Participants reported feeling more comfortable with their TGD identity after the process and more able to resist negative judgments of family members and society. Suicidal thoughts diminish, and participants reported improved emotional wellbeing. Quantitative analysis of questionnaire data is underway Conclusions: A process in which narrative therapy is combined with art therapy shows promise for attracting and helping TGD individuals to reduce their risk for suicide without the stigma of going for mental health treatment. This process can be done outside of conventional mental health settings, on college and University campuses. This can provide an exciting alternative pathway for minority stressed and stigmatized individuals to engage in reflective, psychotherapeutic work without the trappings of psychotherapy or mental health treatment.

Keywords: minority stress, narrative process, artists' books, life story interview

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Authors: Leszek Szpakowski, Daniel Celiński, Sławomir Pilip, Grzegorz Michalak

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The aim of the study was to analyse the usefulness of the 'E-rescuer' pilot project planned to be implemented in a chosen area of Eastern Poland in the cases of suspected sudden cardiac arrests in the extra-urban areas. Inventing an application allowing to dispatch simultaneously both Medical Emergency Teams and the E-rescuer to the place of the accident is the crucial assumption of the mentioned pilot project. The E-rescuer is defined to be the trained person able to take effective basic life support and to use automated external defibrillator. Having logged in using a smartphone, the E-rescuer's readiness is reported online to provide cardiopulmonary resuscitation exactly at the given location. Due to the accurately defined location of the E-rescuer, his arrival time is possible to be precisely fixed, and the substantive support through the displayed algorithms is capable of being provided as well. Having analysed the medical records in the years 2015-2016, cardiopulmonary resuscitation was considered to be effective when an early indication of circulation was provided, and the patient was taken to hospital. In the mentioned term, there were 2.291 cases of a sudden cardiac arrest. Cardiopulmonary resuscitation was taken in 621 patients in total including 205 people in the urban area and 416 in the extra-urban areas. The effectiveness of cardiopulmonary resuscitation in the extra-urban areas was much lower (33,8%) than in the urban (50,7%). The average ambulance arrival time was respectively longer in the extra-urban areas, and it was 12,3 minutes while in the urban area 3,3 minutes. There was no significant difference in the average age of studied patients - 62,5 and 64,8 years old. However, the average ambulance arrival time was 7,6 minutes for effective resuscitations and 10,5 minutes for ineffective ones. Hence, the ambulance arrival time is a crucial factor influencing on the effectiveness of cardiopulmonary resuscitation, especially in the extra-urban areas where it is much longer than in the urban. The key role of trained E-rescuers being nearby taking basic life support before the ambulance arrival can effectively support Emergency Medical Services System in Poland.

Keywords: basic life support, bystander, effectiveness, resuscitation

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Authors: Mohammad Bagher Anvari, Arman Shojaei

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Incremental launching, a widely adopted bridge erection technique, offers numerous advantages for bridge designers. However, accurately simulating and modeling the dynamic behavior of the bridge during each step of the launching process proves to be tedious and time-consuming. The perpetual variation of internal forces within the deck during construction stages adds complexity, exacerbated further by considerations of other load cases, such as support settlements and temperature effects. As a result, there is an urgent need for a reliable, simple, economical, and fast algorithmic solution to model bridge construction stages effectively. This paper presents a novel Finite Element (FE) model that focuses on studying the static behavior of bridges during the launching process. Additionally, a simple method is introduced to normalize all quantities in the problem. The new FE model overcomes the limitations of previous models, enabling the simulation of all stages of launching, which conventional models fail to achieve due to underlying assumptions. By leveraging the results obtained from the new FE model, this study proposes solutions to improve the accuracy of conventional models, particularly for the initial stages of bridge construction that have been neglected in previous research. The research highlights the critical role played by the first span of the bridge during the initial stages, a factor often overlooked in existing studies. Furthermore, a new and simplified model termed the "semi-infinite beam" model, is developed to address this oversight. By utilizing this model alongside a simple optimization approach, optimal values for launching nose specifications are derived. The practical applications of this study extend to optimizing the nose-deck system of incrementally launched bridges, providing valuable insights for practical usage. In conclusion, this paper introduces a comprehensive Finite Element model for studying the static behavior of bridges during incremental launching. The proposed model addresses limitations found in previous approaches and offers practical solutions to enhance accuracy. The study emphasizes the importance of considering the initial stages and introduces the "semi-infinite beam" model. Through the developed model and optimization approach, optimal specifications for launching nose configurations are determined. This research holds significant practical implications and contributes to the optimization of incrementally launched bridges, benefiting both the construction industry and bridge designers.

Keywords: incremental launching, bridge construction, finite element model, optimization

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Authors: Hai-Ning Liang, Xiaowei Dai, Nancy Diniz, Charles Fleming, Woon Kian Chong

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Media displays in public areas are becoming increasingly pervasive—they are used in many settings, come in different sizes, serve different purposes, and have varied degrees of interactivity. In this paper, we aim to provide a survey of how these displays, often named media façades, are used in the wild in a city in China which is undergoing a rapid growth. This survey is intended to raise greater awareness and discussion about the use and effect of these displays in public areas. Through this survey, we have been able to distill some lessons of what is good, bad, and ugly about some current examples of media displays used in a city that is transitioning into becoming a modern one and one that is located in one of the fastest growing areas in Asia. With this research, we hope that we can provide technology designers and architects with some general principles that can help them integrate these types of technologies into their architectural creations.

Keywords: large displays, media façades, interaction design, architectural displays

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

Procedia PDF Downloads 126

Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, gazebo, navigation

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Authors: Chiedu C. Ifekandu, Olusegun Sangowawa, Jean E. Njab

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Background: Health care providers (HCPs) in Nigeria receive little or no training of the healthcare needs of men who have sex with men (MSM) limiting the quality and effectiveness of comprehensive HIV prevention and treatment services. Consequently, most MSM disguise themselves to access services which limit the quality of care provided partly due to challenges related to stigma and discrimination, and breach of confidentiality. Objective: To assess the knowledge of healthcare providers on effective intervention for MSM. Methods: We trained 122 HIV focal persons drawn from 60 health facilities from twelve Nigerian states. , the participants were requested to complete a pre-training questionnaire to assess their level of working experience with key populations as a baseline. Participants included male and female doctors, nurses and counselors/testers. A test was administered to measure their knowledge on MSM sexual risk practices, HIV prevention and healthcare needs and also to assess their attitudes (including homophobia) and beliefs and how it affects service uptake by key populations particularly MSM prior and immediately after the training to ascertain the impact of the training. Results: The mean age of the HCP was 38 years +/- SD Of the 122 HCPs (45 % female, 55 % male; 85 % counsellor/testers; 15 % doctors and nurses; 92 % working in government facilities) from 42 health facilities were trained, of which 105 attempted the test questions. At the baseline, few HCPs reported any prior sensitivity training on MSM. Most of the HCPs had limited knowledge of MSM sexual health needs. Over 90% of the HCPs believed that homosexuality is a mental illness. 8 % do not consider MSM, FSW and PWID as key populations for HIV infection. 45 % lacked knowledge on MSM anal sexual practices. The post-test showed that homophobic attitudes had decreased significantly by the end of the training; the health care providers have acquired basic knowledge compared to the pre-test. Conclusions: Scaling up MSM sensitivity training for Nigerian HCPs is likely to be a timely and effective means to improve their understanding of MSM-related health issues, reduce homophobic sentiments and enhance their capacity to provide responsive HIV prevention, treatment and care services in a supportive and non-stigmatizing environment.

Keywords: healthcare providers, key population, men who have sex with men, HCT

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Authors: Sunethra Jayathilake, Vathsala Jayasuriya-Illesinghe, Kerstin Samarasinghe, Himani Molligoda, Rasika Perera

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In Sri Lanka, postnatal care in the state hospitals is provided by different professional categories: Midwifery trained registered nurses (MTRNs), Registered Nurses (RNs) who do not have midwifery training, doctors and midwives. Even though four professional categories provide postnatal care to mothers and newborn babies, they are not aware of their own tasks and responsibilities in postnatal care. Particularly MTRN’s role in the postnatal unit is unclear. The current study aimed to identify nurses’ (both MTRN and RNs) perception on MTRN’s tasks and responsibilities in postnatal care. This is a descriptive cross sectional study using postal survey. All nurses who were currently working in postnatal units at five selected tertiary care hospitals in the Western Province at that time were invited to participate in the study. Accordingly, the pre evaluated self-administered questionnaire was sent to 201 nurses (53 MTRNs and 148 RNs) in the study setting. The number of valid return questionnaire was 166; response rate was 83%. Respondents rated the responsibility of four professional categories: MTRN, RN, doctor and midwife whether they are 'primarily responsible', 'responsible in absence' and 'not responsible', for each of 15 postnatal (PN) tasks which were previously identified from focus group discussions with care providers during the first phase of the study. Data were analyzed using SPSS version 20; descriptive statistics were calculated. Out of the 15 PN tasks, 13 were identified as MTRNs’ primary responsibilities by 71%-93% of respondents. The respondents also considered six (6) tasks out of 15 as primary responsibility of both MTRN and RN, seven (7) tasks as primary responsibility of MTRN, RN and doctor and the remaining two (2) tasks were identified as the primary responsibility of MTRN, RN and midwife. All 15 PN tasks overlapped with other professional categories. Overlapping tasks may create role confusion leading to conflicts among professional categories which affect the quality of care they provide, eventually, threaten the safety of the client. It is recommended that an official job description for each care provider is needed to recognize their own professional boundaries for ensuring safe, quality care delivery in Sri Lanka.

Keywords: overlapping, postnatal, responsibilities, tasks

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Authors: Sasha Goodwin

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Public perceptions can play a crucial role in influencing criminal justice policy and legislation, particularly concerning sex offenders. Studies have found a proximate relationship between public perception and policy to manage the risks posed by sex offenders. A significant body of research on public perceptions about sex offenders primarily uses survey methods and standardised instruments such as the Community Attitude Towards Sex Offenders (CATSO) and Perceptions of Sex Offenders (PSO) scales and finds a mostly negative and punitive attitude informed by common misconceptions. A transformative methodology from the emerging sub-field of visual criminology is where the construction of offences and offenders are understood via novel ways of collecting and analysing data. This research paper examines the public perceptions of sex offenders through the utilization of a content analysis of drawings. The study aimed to disentangle the emotions, stereotypes, and myths embedded in public perceptions by analysing the graphic representations and specific characteristics depicted by participants. Preliminary findings highlight significant discrepancies between public perceptions and empirical profiles of sex offenders, shedding light on the misunderstandings surrounding this heterogeneous group. By employing visual data, this research contributes to a deeper understanding of the complex interplay between societal perceptions and the realities of sex offenders.

Keywords: emotions, figural drawings, public perception, sex offenders

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Authors: Chukwuma Anya, Mekwa Eme

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The term ‘’FORM’’ in design could be referred to as the combination of various shapes of different sizes and assembling them in appropriate positions to achieve a unique figure of high aesthetic value. A deduction from this definition is that forms contribute immensely to the actualization of aesthetics in a building. When these various shapes and figures are properly assembled, it may give rise to a concept in design. However some architects and other designers either misuse or abuse the use of these shapes, hence resulting to a design imbalance, lack of uniformity and expression. This academic work is designed to educate the public on the proper usage of some regular shapes like circles, rectangles, pentagons, hexagons, triangles etc, to achieve a unique form in design. By the end of this work, one should be able to assemble different shapes to express different emotions of the mind, such as peace, love, confusion, war, and unity. Some elements of design, such as balance, stability, functionality and aesthetics, will also be achieved even as the building maintains its unique form.

Keywords: aesthetics, form, balance, stability

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Authors: Ofoegbu Ositadinma Edward

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This research paper discusses a web based monitoring system that enables effective monitoring of fuel pump output and sales volume from distributed fuel stations under the domain of a single company/organization. The traditional method of operation by these organizations in Nigeria is non-automated and accounting for dispensed product is usually approximated and manual as there is little or no technology implemented to presently provide information relating to the state of affairs in the station both to on-ground staff and to supervisory staff that are not physically present in the station. This results in unaccountable losses in product and revenue as well as slow decision making. Remote monitoring technology as a vast research field with numerous application areas incorporating various data collation techniques and sensor networks can be applied to provide information relating to fuel pump status in distributed fuel stations reliably. Thus, the proposed system relies upon a microcontroller, keypad and pump to demonstrate the traditional fuel dispenser. A web-enabled PC with an accompanying graphic user interface (GUI) was designed using virtual basic which is connected to the microcontroller via the serial port which is to provide the web implementation.

Keywords: fuel pump, microcontroller, GUI, web

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Authors: Lancer Scott

Abstract:

Purpose: High quality clinical disaster medicine requires providers working collaboratively to care for multiple patients in chaotic environments; however, many providers lack adequate training. To address this deficit, we created a competency-based, 5-hour Emergency Preparedness Training (EPT) curriculum using didactics, small-group discussion, and kinetic learning. The goal was to evaluate the effect of a short course on improving provider knowledge, confidence and skills in disaster scenarios. Methods: Diverse groups of medical university students, health care professionals, and community members were enrolled between 2011 and 2014. The course consisted of didactic lectures, small group exercises, and two live, multi-patient mass casualty incident (MCI) scenarios. The outcome measures were based on core competencies and performance objectives developed by a curriculum task force and assessed via trained facilitator observation, pre- and post-testing, and a course evaluation. Results: 708 participants completed were trained between November 2011 and August 2014, including 49.9% physicians, 31.9% medical students, 7.2% nurses, and 11% various other healthcare professions. 100% of participants completed the pre-test and 71.9% completed the post-test, with average correct answers increasing from 39% to 60%. Following didactics, trainees met 73% and 96% of performance objectives for the two small group exercises and 68.5% and 61.1% of performance objectives for the two MCI scenarios. Average trainee self-assessment of both overall knowledge and skill with clinical disasters improved from 33/100 to 74/100 (overall knowledge) and 33/100 to 77/100 (overall skill). The course assessment was completed by 34.3% participants, of whom 91.5% highly recommended the course. Conclusion: A relatively short, intensive EPT course can improve the ability of a diverse group of disaster care providers to respond effectively to mass casualty scenarios.

Keywords: clinical disaster medicine, training, hospital preparedness, surge capacity, education, curriculum, research, performance, training, student, physicians, nurses, health care providers, health care

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Authors: Petri Solanti, Russell Klein

Abstract:

Many designers are asking for an automated path from an abstract mathematical MATLAB model to a high-quality Register-Transfer Level (RTL) hardware description. Manual transformations of MATLAB or intermediate code are needed, when the design abstraction is changed. Design conversion is problematic as it is multidimensional and it requires many different design steps to translate the mathematical representation of the desired functionality to an efficient hardware description with the same behavior and configurability. Yet, a manual model conversion is not an insurmountable task. Using currently available design tools and an appropriate design methodology, converting a MATLAB model to efficient hardware is a reasonable effort. This paper describes a simple and flexible design methodology that was developed together with several design teams.

Keywords: design methodology, high-level synthesis, MATLAB, verification

Procedia PDF Downloads 118

Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

Abstract:

In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

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Authors: Xabier Olaz Moratinos

Abstract:

Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Dorsa Pourmojib, Marc J. Boutin

Abstract:

Urban space is used everyday by a diverse range of urban dwellers, each with different expectations. In this space, opportunities and resources are not distributed equitably among urban dwellers, despite the importance of inclusivity. In addition, some marginalized groups may not be considered. These include people with low incomes, immigrants from diverse cultures, various age groups, and those with special needs. To this end, this research aims to enhance social equity in urban space by bridging the gap between social equity and spatial equity in the urban context. This gap in the knowledge base related to urban design may be present for several reasons; lack of studies on relationship between social equity and spatial equity in urban open space, lack of practical design strategies for promoting social equity in urban open space, lack of proper site analysis in terms of context and users of the site both for designing new urban open spaces and developing the existing ones, and lack of researchers that are designers and finally it could be related to priorities of the city’s policies in addressing such issues, since it is time, money and energy consuming. The main objective of this project is addressing the aforementioned gap in the knowledge by exploring the relationship between social equity and spatial equity in urban open space. Answering the main question of this research is a promising step to this end; 'What are the considerations towards providing social equity through the design of urban elements that offer spatial equity?' To answer the main question of this research there are several secondary questions which should be addressed. Such as; how can the characteristics of social equity be translated to spatial equity? What are the diverse user’s needs and which of their needs are not considered in that site? What are the specific elements in the site which should be designed in order to promote social equity? What is the current situation of social and spatial equity in the proposed site? To answer the research questions and achieve the proposed objectives, a three-step methodology has been implemented. Firstly, a comprehensive research framework based on the available literature has been presented. Afterwards, three different urban spaces have been analyzed in terms of specific key research questions as the precedent studies; Naqsh-e Jahan Square (Iran), Superkilen Park (Denmark) and Campo Dei Fiori (Italy). In this regard, a proper gap analysis of the current situation and the proposed situation of these sites has been conducted. Finally, by combining the extracted design considerations from the precedent studies and the literature review, practical design strategies have been introduced as a result of this research. The presented guidelines enable the designers to create socially equitable urban spaces. To conclude, this research proposes a spatial approach to social inclusion and equity in urban space by presenting a practical framework and criteria for translating social equity to spatial equity in urban areas.

Keywords: inclusive urban design, social equity, social inclusion, spatial equity

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Authors: C. W. Kan, H. F. Cheung, Y. S. Lee

Abstract:

This study examines the results of colour fading of cotton fabric by plasma-induced ozone treatment, with an aim to provide learning materials for fashion designers when designing colour fading effects in fashion products. Cotton knitted fabrics were dyed with red reactive dye with a colour depth of 1.5% and were subjected to ozone generated by a commercially available plasma machine for colour fading. The plasma-induced ozone treatment was conducted with different parameters: (i) air concentration = 10%, 30%, 50% and 70%; (ii) water content in fabric = 35% and 45%, and (iii) treatment time = 10 minutes, 20 minutes and 30 minutes. Finally, the colour properties of the plasma–induced ozone treated fabric were measured by spectrophotometer under illuminant D₆₅ to obtain the CIE L*, CIE a* and CIE b* values.

Keywords: learning materials, colour fading, colour properties, fashion products

Procedia PDF Downloads 259

Authors: Alireza Barari, Saeed Shirali, Ahmad Abdi

Abstract:

Abstract: Introduction: Physical activity may be related to male reproductive function by affecting on thehypothalamic-pituitary-gonadal(HPG) axis. Our aim was to determine the effects of 6 weeks resistance exercise on reproductive hormones, HPG axis. The hypothalamic-pituitary-gonadal (HPG) axis refers tothe effects of endocrine glands in three-level including (i) the hypothalamic releasing hormone GnRH, which is synthesized in in a small heterogenous neuronal population and released in a pulsatile fashion, (ii) the anterior pituitary hormones, follicle-stimulating hormone(FSH) and luteinizing hormone (LH) and (iii) the gonadal hormones, which include both steroid such as testosterone (T), estradiol and progesterone and peptide hormones (such as inhibin). Hormonal changes that create a more anabolic environment have been suggested to contribute to the adaptation to strength exercise. Physical activity has an extensive impact on male reproductive function depending upon the intensity and duration of the exercise and the fitness level of the individual. However, strenuous exercise represents a physical stress and inflammation changed that challenges homeostasis. Materials and methods: Sixteen male volunteered were included in a 6-week control period followed by 6 weeks of resistance training (leg press, lat pull, chest press, squat, seatedrow, abdominal crunch, shoulder press, biceps curl and triceps press down) four times per week. intensity of training loading was 60%-75% of one maximum repetition. Participants performed 3 sets of 10 repetitions. Rest periods were two min between exercises and sets. Start with warm up exercises include: The muscles relax and stretch the body, which was for 10 minutes. Body composition, VO2max and the circulating level of free testosterone (fT), luteinizing hormone (LH), follicle-stimulating hormone (FSH), sex hormone binding globulin (SHBG) and inhibin B measured prior and post 6-week intervention. The hormonal levels of each serum sample were measured using commercially available ELISA kits. Analysis of anthropometrical data and hormonal level were compared using the independent samples t- test in both groups and using SPSS (version 19). P ≤ 0.05 was considered statistically significant. Results: For muscle strength, both lower- and upper-body strength were increased significantly. Aerobic fitness level improved in trained participant from 39.4 ± 5.6 to 41.9 ± 5.3 (P = 0.002). fT concentration rise progressively in the trained group and was significantly greater than those in the control group (P = 0.000). By the end of the 6-week resistance training, serum SHBG significantly increased in the trained group compared with the control group (P = 0.013). In response to resistance training, LH, FSH and inhibin B were not significantly changed. Discussion: According to our finfings, 6 weeks of resistance training induce fat loss without any changes in body weight and BMI. A decline of 25.3% in percentage of body fat with statiscally same weight was due to increase in muscle mass that happened during resistance exercise periods . Six weeks of resistance training resulted in significant improvement in BF%, VO2max and increasing strength and the level of fT and SHBG.

Keywords: resistance, hypothalamic, pituitary, gonadal axis

Procedia PDF Downloads 384