Search results for: Neural Processing Element (NPE)

Authors: A. J. Al-Graitti, G. A. Khalid, P. Berthelson, A. Mason-Jones, R. Prabhu, M. D. Jones

Abstract:

Motor vehicle related pedestrian road traffic collisions are a major road safety challenge, since they are a leading cause of death and serious injury worldwide, contributing to a third of the global disease burden. The auto rickshaw, which is a common form of urban transport in many developing countries, plays a major transport role, both as a vehicle for hire and for private use. The most common auto rickshaws are quite unlike ‘typical’ four-wheel motor vehicle, being typically characterised by three wheels, a non-tilting sheet-metal body or open frame construction, a canvas roof and side curtains, a small drivers’ cabin, handlebar controls and a passenger space at the rear. Given the propensity, in developing countries, for auto rickshaws to be used in mixed cityscapes, where pedestrians and vehicles share the roadway, the potential for auto rickshaw impacts with pedestrians is relatively high. Whilst auto rickshaws are used in some Western countries, their limited number and spatial separation from pedestrian walkways, as a result of city planning, has not resulted in significant accident statistics. Thus, auto rickshaws have not been subject to the vehicle impact related pedestrian crash kinematic analyses and/or injury mechanics assessment, typically associated with motor vehicle development in Western Europe, North America and Japan. This study presents a parametric analysis of auto rickshaw related pedestrian impacts by computational simulation, using a Finite Element model of an auto rickshaw and an LS-DYNA 50^th percentile male Hybrid III Anthropometric Test Device (dummy). Parametric variables include auto rickshaw impact velocity, auto rickshaw impact region (front, centre or offset) and relative pedestrian impact position (front, side and rear). The output data of each impact simulation was correlated against reported injury metrics, Head Injury Criterion (front, side and rear), Neck injury Criterion (front, side and rear), Abbreviated Injury Scale and reported risk level and adds greater understanding to the issue of auto rickshaw related pedestrian injury risk. The parametric analyses suggest that pedestrians are subject to a relatively high risk of injury during impacts with an auto rickshaw at velocities of 20 km/h or greater, which during some of the impact simulations may even risk fatalities. The present study provides valuable evidence for informing a series of recommendations and guidelines for making the auto rickshaw safer during collisions with pedestrians. Whilst it is acknowledged that the present research findings are based in the field of safety engineering and may over represent injury risk, compared to “Real World” accidents, many of the simulated interactions produced injury response values significantly greater than current threshold curves and thus, justify their inclusion in the study. To reduce the injury risk level and increase the safety of the auto rickshaw, there should be a reduction in the velocity of the auto rickshaw and, or, consideration of engineering solutions, such as retro fitting injury mitigation technologies to those auto rickshaw contact regions which are the subject of the greatest risk of producing pedestrian injury.

Keywords: auto rickshaw, finite element analysis, injury risk level, LS-DYNA, pedestrian impact

Procedia PDF Downloads 181

Authors: Pallab Das, Nabam Zomleen

Abstract:

Effective dissipation of lateral loads that are coming due to seismic force determines the strength, durability and safety concern of the structure. Masonry infill has high stiffness and strength capabilities which can be put into an effective utilization for lateral load dissipation by incorporating it into building construction, but masonry behaves in highly nonlinear manner, so it is highly important to find out generalized, yet a rational approach to determine its nonlinear behavior and failure mode and it’s response when it is incorporated into building. But most of the countries do not specify the procedure for design of masonry infill wall. Whereas, there are many analytical modeling method available in literature, e.g. equivalent diagonal strut method, finite element modeling etc. In this paper the masonry infill is modeled and 6-storey bare framed building and building with masonry infill is analyzed using SAP-200014 in order to find out inter-storey drift by time-history analysis and capacity curve by Pushover analysis. The analysis shows that, while, the structure is well within CP performance level for both the case, whereas, there is considerable reduction of inter-storey drift of about 28%, when the building is analyzed with masonry infill wall.

Keywords: capacity curve, masonry infill, nonlinear analysis, time history analysis

Procedia PDF Downloads 364

Authors: Kristina Zuzek, Xuan Xu, Awais Ikram, Richard Sheridan, Allan Walton, Saso Sturm

Abstract:

Recycling of end-of-life REEs based Nd-Fe-B magnets is an important strategy for reducing the environmental dangers associated with rare-earth mining and overcoming the well-documented supply risks related to the REEs. However, challenges on their reprocessing still remain. We report on the possibility of direct electrochemical recycling and reprocessing of Nd-Fe(B)-based magnets. In this investigation, we were able first to electrochemically leach the end-of-life NdFeB magnet and to electrodeposit Nd–Fe using a 1-ethyl-3-methyl imidazolium dicyanamide ([EMIM][DCA]) ionic liquid-based electrolyte. We observed that Nd(III) could not be reduced independently. However, it can be co-deposited on a substrate with the addition of Fe(II). Using advanced TEM techniques of electron-energy-loss spectroscopy (EELS) it was shown that Nd(III) is reduced to Nd(0) during the electrodeposition process. This gave a new insight into determining the Nd oxidation state, as X-ray photoelectron spectroscopy (XPS) has certain limitations. This is because the binding energies of metallic Nd (Nd0) and neodymium oxide (Nd₂O₃) are very close, i. e., 980.5-981.5 eV and 981.7-982.3 eV, respectively, making it almost impossible to differentiate between the two states. These new insights into the electrodeposition process represent an important step closer to efficient recycling of rare piles of earth in metallic form at mild temperatures, thus providing an alternative to high-temperature molten-salt electrolysis and a step closer to deposit Nd-Fe-based magnetic materials. Further, we propose a new concept of recycling the sintered Nd-Fe-B magnets by direct recovering the 2:14:1 matrix phase. Via an electrochemical etching method, we are able to recover pure individual 2:14:1 grains that can be re-used for new types of magnet production. In the frame of physical reprocessing, we have successfully synthesized new magnets out of hydrogen (HDDR)-recycled stocks with a contemporary technique of pulsed electric current sintering (PECS). The optimal PECS conditions yielded fully dense Nd-Fe-B magnets with the coercivity Hc = 1060 kA/m, which was boosted to 1160 kA/m after the post-PECS thermal treatment. The Br and Hc were tackled further and increased applied pressures of 100 – 150 MPa resulted in Br = 1.01 T. We showed that with a fine tune of the PECS and post-annealing it is possible to revitalize the Nd-Fe-B end-of-life magnets. By applying advanced TEM, i.e. atomic-scale Z-contrast STEM combined with EDXS and EELS, the resulting magnetic properties were critically assessed against various types of structural and compositional discontinuities down to atomic-scale, which we believe control the microstructure evolution during the PECS processing route.

Keywords: electrochemistry, Nd-Fe-B, pulsed electric current sintering, recycling, reprocessing

Procedia PDF Downloads 142

Authors: Jonas Colin

Abstract:

Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

Procedia PDF Downloads 47

Authors: Chih-Chieh Yang, Chung-Neng Huang

Abstract:

In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

Procedia PDF Downloads 125

Authors: Vivienne Cameron

Abstract:

Background: Between 2010 and 2017, teachers in a suburban public school district struggled to get students to consistently produce adequate writing samples as measured by the Pennsylvania state writing rubric for measuring focus, content, organization, style, and conventions. A common thread in all of the data was the need to develop stamina in the student writers. Method: All of the teachers used the traditional writing process model (prewrite, draft, revise, edit, final copy) during writing instruction. One teacher taught the writing process using word processing and incentivizing with publication instead of the traditional pencil/paper/grading method. Students did not have instruction in typing/keyboarding. The teacher submitted resulting student work to real-life contests, magazines, and publishers. Results: Students in the test group increased both the quantity and quality of their writing over a seven month period as measured by the Pennsylvania state writing rubric. Reluctant writers, as well as students with autism spectrum disorder, benefited from this approach. This outcome was repeated consistently over a five-year period. Interpretation: Removing the burden of pencil and paper allowed students to participate in the writing process more fully. Writing with pencil and paper is physically tiring. Students are discouraged when they submit a draft and are instructed to use the Add, Remove, Move, Substitute (ARMS) method to revise their papers. Each successive version becomes shorter. Allowing students to type their papers frees them to quickly and easily make changes. The result is longer writing pieces in shorter time frames, allowing the teacher to spend more time working on individual needs. With this additional time, the teacher can concentrate on teaching focus, content, organization, style, conventions, and audience. S/he also has a larger body of works from which to work on whole group instruction such as developing effective leads. The teacher submitted the resulting student work to contests, magazines, and publishers. Although time-consuming, the submission process was an invaluable lesson for teaching about audience and tone. All students in the test sample had work accepted for publication. Students became highly motivated to succeed when their work was accepted for publication. This motivation applied to special needs students, regular education students, and gifted students.

Keywords: elementary-age students, reluctant writers, teaching strategies, writing process

Procedia PDF Downloads 159

Authors: Esther Lorrayne M. Pereira, Adriana Souza M. Batista, Fabíola A. S. Ribeiro, Adelina P. Santos, Clascídia A. Furtado, Luiz O. Faria

Abstract:

The combination of multi–walled carbon nanotubes (MWCNTs) with polymers offers an attractive route to reinforce the macromolecular compounds as well as the introduction of new properties based on morphological modifications or electronic interactions between the two constituents. As they are only a few nanometers in dimension, it offers ultra-large interfacial area per volume between the nano-element and polymer matrix. Nevertheless, the use of MWCNTs as a rough material in different applications has been largely limited by their poor processability, insolubility, and infusibility. Studies concerning the nanofiller reinforced polymer composites are justified in an attempt to overcome these limitations. This work presents one preliminary study of MWCNTs dispersion into the PVDF homopolymer. For preparation, the composite components were diluted in n,n-dimethylacetamide (DMAc) with mechanical agitation assistance. After complete dilution, followed by slow evaporation of the solvent at 60°C, the samples were dried. Films of about 80 μm were obtained. FTIR and UV-Vis spectroscopic techniques were used to characterize the nanocomposites. The appearance of absorption bands in the FTIR spectra of nanofilled samples, when compared to the spectrum of pristine PVDF samples, are discussed and compared with the UV-Vis measurements.

Keywords: composites materials, FTIR, MWNTs, PVDF, UV-vis

Procedia PDF Downloads 430

Authors: Swapnil V. Pakhale, Sunil S. Bhagwat

Abstract:

Three phase partitioning (TPP) an efficient bioseparation technique integrates the concentration and partial purification step of downstream processing of a biomolecule. Three Phase Partitioning is reported here for the first time for purification of Serratiopeptidase from fermentation broths of Serratia marcescens NRRL B-23112. The influence of various salts and solvents, Concentration of ammonium sulphate (20-60% w/v), Crude extract to t-butanol ratio (1:0.5-1:2.5) and system pH on Serratiopeptidase partitioning were investigated and optimum conditions for TPP were obtained in order to enhance the degree of purification and activity recovery of Serratiopeptidase. Under the optimal conditions of TPP, serratiopeptidase has been efficiently separated and concentrated with maximum recovery and degree of purification of 95.70% and 4.95 fold respectively. The present study shows TPP as an attractive downstream process for the purification of serratiopeptidase.

Keywords: three phase partitioning, serratiopeptidase, serratia marcescens NRRL B-23112, t-butanol, bioseparation

Procedia PDF Downloads 530

Authors: Talal Alhajri, Mahmood M. Tahir, Khaled Alenezi, Mohamad Ragaee

Abstract:

This work presents the experimental tests carried out to evaluate the behaviour of different types of shear connectors proposed for cold formed steel (CFS) section integrated with ferrocement slab as potential used for composite beam. Ten push-out test specimens of cold-formed steel lipped channel sections connected with ferrocement slab were tested. Three types of shear connectors were studied comprised of bolts, self-drilling-screw and bar angle. The connection behavior is analysed in terms of its load-slip relationship and the failure mode. The parametric studies were performed to investigate the effect on the shear connector’s capacity by varying the number of layers of wire mesh used in ferrocement slab and types of shear connector used. An analytical analysis using ANSYS program and theoretical analysis (Eurocode 4) were carried out to verify the experiment results. The results show that the experimental, theoretical, and numerical values proved to have good agreement with each other.

Keywords: cold-formed steel, composite beam, ferrocement, finite element method, push-out test, shear connector

Procedia PDF Downloads 347

Authors: M. Kowalski, M. Kastek, M. Szustakowski

Abstract:

Multispectral screening systems are becoming more popular because of their very interesting properties and applications. One of the most significant applications of multispectral screening systems is prevention of terrorist attacks. There are many kinds of threats and many methods of detection. Visual detection of objects hidden under clothing of a person is one of the most challenging problems of threats detection. There are various solutions of the problem; however, the most effective utilize multispectral surveillance imagers. The development of imaging devices and exploration of new spectral bands is a chance to introduce new equipment for assuring public safety. We investigate the possibility of long lasting detection of potentially dangerous objects covered with various types of clothing. In the article we present the results of comparative studies of passive imaging in three spectrums – visible, infrared and terahertz

Keywords: terahertz, infrared, object detection, screening camera, image processing

Procedia PDF Downloads 341

Authors: Paola Pannuzzo, Tak-Ming Chan

Abstract:

In seismic applications, hollow steel sections show, beyond undeniable esthetical appeal, promising structural advantages since, unlike open section counterparts, they are not susceptible to weak-axis and lateral-torsional buckling. In particular, hot-finished hollow steel sections have homogeneous material properties and favorable ductility but have been underutilized for cyclic bending. The main reason is that the parameters affecting their hysteretic behaviors are not yet well understood and, consequently, are not well exploited in existing codes of practice. Therefore, experimental investigations have been conducted on a wide range of hot-finished rectangular hollow section beams with the aim to providing basic knowledge for evaluating their seismic performance. The section geometry (width-to-thickness and depth-to-thickness ratios) and the type of loading (monotonic and cyclic) have been chosen as the key parameters to investigate the cyclic effect on the rotational capacity and to highlight the differences between monotonic and cyclic load conditions. The test results provide information on the parameters that affect the cyclic performance of hot-finished hollow steel beams and can be used to assess the design provisions stipulated in the current seismic codes of practice.

Keywords: bending, cyclic test, finite element modeling, hollow sections, hot-finished sections

Procedia PDF Downloads 139

Authors: S. Bahadır Yüksel, Alptuğ Ünal

Abstract:

The composite shear walls (CSW) with steel encased profiles can be used as lateral-load resisting systems for buildings that require considerable large lateral-load capacity. The aim of this work is to propose the experimental work conducted on CSW having L section folded plate (L shape steel made-up sections) as longitudinal reinforcement in boundary regions. The study in this paper present the experimental test conducted on CSW having L section folded plate as longitudinal reinforcement in boundary regions. The tested 1/3 geometric scaled CSW has aspect ratio of 3.2. L-shape structural steel materials with 2L-19x57x7mm dimensions were placed in shear wall boundary zones. The seismic behavior of CSW test specimen was investigated by evaluating and interpreting the hysteresis curves, envelope curves, rigidity and consumed energy graphs of this tested element. In addition to this, the experimental results, deformation and cracking patterns were evaluated, interpreted and suggestions of the design recommendations were proposed.

Keywords: shear wall, composite shear wall, boundary reinforcement, earthquake resistant structural design, L section

Procedia PDF Downloads 313

Authors: Hyun Ah Yoon, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

Abstract:

Reinforced concrete (RC) shear wall system of residential buildings is popular in South Korea. RC walls are subjected to axial forces in common and the effect of axial forces on the strength loss of the fire damaged walls has not been investigated. This paper aims at investigating temperature distribution on fire damaged concrete walls having different axial loads. In the experiments, a variable of specimens is axial force ratio. RC walls are fabricated with 150mm of wall thicknesses, 750mm of lengths and 1,300mm of heights having concrete strength of 24MPa. After curing, specimens are heated on one surface with ISO-834 standard time-temperature curve for 2 hours and temperature distributions during the test are measured using thermocouples inside the walls. The experimental results show that the temperature of the RC walls exposed to fire increases as axial force ratio increases. To verify the experiments, finite element (FE) models are generated for coupled temperature-structure analyses. The analytical results of thermal behaviors are in good agreement with the experimental results. The predicted displacement of the walls decreases when the axial force increases. 

Keywords: axial force ratio, fire, reinforced concrete wall, residual strength

Procedia PDF Downloads 446

Authors: Sohaib Z. Khan, Farrukh Mustahsan, Essam R. I. Mahmoud, S. H. Masood

Abstract:

Materials or structures that contract laterally on the application of a compressive load and vice versa are said to be Auxetic materials which exhibit Negative Poisson’s Ratio (NPR). Numerous auxetic structures are proposed in the literature. One of the most studied periodic auxetic structure is the re-entrant honeycomb model. In this paper, a modified re-entrant model is proposed to enhance the auxetic behavior. The paper aimed to investigate the elastic behaviour of the proposed model to improve Young’s modulus and NPR by evaluating the analytical model. Finite Element Analysis (FEA) is also conducted to support the analytical results. A significant increment in Young’s modulus and NPR can be achieved in one of the two orthogonal directions of the loading at the cost of compromising these values in other direction. The proposed modification resulted in lower relative densities when compared to the existing re-entrant honeycomb structure. A trade-off in the elastic properties in one direction at low relative density makes the proposed model suitable for uni-direction applications where higher stiffness and NPR is required, and strength to weight ratio is important.

Keywords: 2D model, auxetic materials, re-entrant honeycomb, negative Poisson's ratio

Procedia PDF Downloads 126

Authors: Riaan Kleyn

Abstract:

Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

Procedia PDF Downloads 71

Authors: Abdulwakeel B. Raji

Abstract:

This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

Procedia PDF Downloads 122

Authors: M. Abdollahi, S. N. Moghaddas Tafreshi

Abstract:

Expanded polystyrene (EPS) geofoam is often used in below ground applications in geotechnical engineering. A most recent configuration system implemented in roadways to protect lifelines such as buried pipes, electrical cables and culvert systems could be consisted of two EPS geofoam blocks, “posts” placed on each side of the structure, an EPS block capping, “beam” put atop two posts, and soil cover on the beam. In this configuration, a rectangular void space will be built atop the lifeline. EPS blocks will stand all the imposed vertical forces due to their strength and deformability, thus the lifeline will experience no vertical stress. The present paper describes the results of a numerical study on the post and beam configuration subjected to the static loading. Three-dimensional finite element analysis using ABAQUS software is carried out to investigate the effect of different parameters such as beam thickness, soil thickness over the beam, post height to width ratio, EPS density, and free span between two posts, on the stress distribution and the deflection of the beam. The results show favorable performance of EPS geofoam for protecting sensitive infrastructures.

Keywords: beam, EPS block, numerical analysis, post, stress distribution

Procedia PDF Downloads 232

Authors: Ildikó Balatoni, Nikolett Kosztin

Abstract:

In this study the importance of maintaining the mental and physical health of employees was examined from the perspective of the employers. To this end companies in Hajdú-Bihar county of Hungary that are within in the TOP 100 based on their net revenue were interviewed. Economic sectors that were represented the most in this survey were processing, services, trade, agriculture, and construction. We examined whether or not companies provided any benefits to their employees concerning health awareness. Among respondents those who offered various services of medical specialists and/or discounted gym or swim passes in addition to compulsory medical examinations were hard to find, however more employers organize health and sports days. Nevertheless, a significant albeit very shallow positive correlation were found between the number of offered benefits vs. total gross income and vs. number of employees (r2=0.2555, p<0.001 and r2=0.1196 and p<0.05, respectively). In conclusion, while workplace health promotion is necessary it requires a change in employers’attitudes.

Keywords: corporate health promotion, employees, employers, health

Procedia PDF Downloads 116

Authors: Xia Huo

Abstract:

The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu and 34 children from Haojiang. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and both the alpha diversity index and specific metabolites in single-element models. The study found that the Bayesian kernel machine regression (BKMR) model showed a negative correlation between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the Chao 1 index, particularly beyond the 55th percentile. Furthermore, the EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our research suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the gut microbiota and its metabolites. These alterations may be associated with neurodevelopmental abnormalities in children.

Keywords: gut microbiota, 6PPDQ, PBDEs, PCBs, metal(loid)s, BKMR

Procedia PDF Downloads 41

Authors: Sunusi Tijjani

Abstract:

Information and communication technology is an indispensable tool in the performance of office technology managers. Today's offices are automated and equipped with modern office machines that enhances and improve the work of office managers. However, today's office technology managers can process, evaluate, manage and communicate all forms of information using technological devices. Information and Communication Technology is viewed as the process of processing, storing ad dissemination information while office technology managers are trained professional who can effectively operate modern office machines, perform administrative duties and attend meetings to take dawn minute of meetings. This paper examines the importance of information and communication technology toward enhancing the work of office managers. It also stresses the importance of information and communication technology toward proper and accurate record management.

Keywords: communication, information, technology, managers

Procedia PDF Downloads 461

Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

Abstract:

Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

Procedia PDF Downloads 93

Authors: Hanan Mikhael Dawood, Afaneen Anwer Abood Al-Khazraji

Abstract:

The paper presents an investigation of field oriented control strategy of Permanent Magnet Synchronous Motor (PMSM) based on hardware in the loop simulation (HIL) over a wide speed range. A sensorless rotor position estimation using sliding mode observer for permanent magnet synchronous motor is illustrated considering the effects of magnetic saturation between the d and q axes. The cross saturation between d and q axes has been calculated by finite-element analysis. Therefore, the inductance measurement regards the saturation and cross saturation which are used to obtain the suitable id-characteristics in base and flux weakening regions. Real time matrix multiplication in Field Programmable Gate Array (FPGA) using floating point number system is used utilizing Quartus-II environment to develop FPGA designs and then download these designs files into development kit. dSPACE DS1103 is utilized for Pulse Width Modulation (PWM) switching and the controller. The hardware in the loop results conducted to that from the Matlab simulation. Various dynamic conditions have been investigated.

Keywords: magnetic saturation, rotor position estimation, sliding mode observer, hardware in the loop (HIL)

Procedia PDF Downloads 510

Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

Abstract:

With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

Procedia PDF Downloads 530

Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

Abstract:

In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

Procedia PDF Downloads 295

Authors: Tuğçe Yücel

Abstract:

A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

Procedia PDF Downloads 492

Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

Abstract:

Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

Procedia PDF Downloads 162

Authors: M. M. Bagheri, G. Doudak, M. Gong

Abstract:

The in-plane rigidity of light frame diaphragms has been investigated by researchers due to the importance of this subsystem regarding lateral force distribution between the lateral force resisting system (LFRS). Where research has lacked is in evaluating the impact of out-of-plane raigidity of the diaphragm on the deflection of shear walls. This study aims at investigating the effect of the diaphragm on the behavior of wood light-frame shear walls, in particular its out-of-plane rigidity was simulated by modeling the floors as beam. The out of plane stiffness of the diaphragm was investigated for idealized (infinitely stiff or flexible) as well as “realistic”. The results showed reductions in the shear wall deflection in the magnitude of approximately 80% considering the out of plane rigidity of the diaphragm. It was also concluded that considering conservative estimates of out-of-plane stiffness might lead to a very significant reduction in deflection and that assuming the floor diaphragm to be infinitely rigid out of plan seems to be reasonable. For diaphragms supported on multiple panels, further reduction in the deflection was observed. More work, particularly at the experimental level, is needed to verify the finding obtained in the numerical investigation related to the effect of out of plane diaphragm stiffness.

Keywords: finite element analysis, lateral deflection, out-of-plane stiffness of the diaphragm, wood light-frame shear wall

Procedia PDF Downloads 172

Authors: Hassan A. Alshahrani, Mehdi H. Hojjati

Abstract:

In order to predict and model wrinkling which is caused by out of plane deformation due to compressive loading in the plane of the material during composite prepregs forming, it is necessary to quantitatively understand the relative magnitude of the bending stiffness. This study aims to examine the bending properties of out-of-autoclave (OOA) thermosetting prepreg under vertical cantilever test condition. A direct method for characterizing the bending behavior of composite prepregs was developed. The results from direct measurement were compared with results derived from an image-processing procedure that analyses the captured image during the vertical bending test. A numerical simulation was performed using ABAQUS to confirm the bending stiffness value.

Keywords: Bending stiffness, out-of-autoclave prepreg, forming process, numerical simulation.

Procedia PDF Downloads 281

Authors: Yufen Qin

Abstract:

Text sentiment transfer is an important branch of text style transfer. The goal is to generate text with another sentiment attribute based on a text with a specific sentiment attribute while maintaining the content and semantic information unrelated to sentiment unchanged in the process. There are currently two main challenges in this field: no parallel corpus and text attribute entanglement. In response to the above problems, this paper proposed a novel solution: Mask-Prompt-Rerank. Use the method of masking the sentiment words and then using prompt regeneration to transfer the sentence sentiment. Experiments on two sentiment benchmark datasets and one formality transfer benchmark dataset show that this approach makes the performance of small pre-trained language models comparable to that of the most advanced large models, while consuming two orders of magnitude less computing and memory.

Keywords: language model, natural language processing, prompt, text sentiment transfer

Procedia PDF Downloads 59

Authors: Ssu-Han Chen, Der-Baau Perng

Abstract:

Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

Procedia PDF Downloads 417