Search results for: study time

Authors: Farzad Danaei, Yilmaz Akkaya

Abstract:

In many civil engineering applications, especially in the construction of large concrete structures, the early age behavior of concrete has shown to be a crucial problem. The uneven rise in temperature within the concrete in these constructions is the fundamental issue for quality control. Therefore, developing accurate and fast temperature prediction models is essential. The thermal properties of concrete fluctuate over time as it hardens, but taking into account all of these fluctuations makes numerical models more complex. Experimental measurement of the thermal properties at the laboratory conditions also can not accurately predict the variance of these properties at site conditions. Therefore, specific heat capacity and the heat conductivity coefficient are two variables that are considered constant values in many of the models previously recommended. The proposed equations demonstrate that these two quantities are linearly decreasing as cement hydrates, and their value are related to the degree of hydration. The effects of changing the thermal conductivity and specific heat capacity values on the maximum temperature and the time it takes for concrete to reach that temperature are examined in this study using numerical sensibility analysis, and the results are compared to models that take a fixed value for these two thermal properties. The current study is conducted in 7 different mix designs of concrete with varying amounts of supplementary cementitious materials (fly ash and ground granulated blast furnace slag). It is concluded that the maximum temperature will not change as a result of the constant conductivity coefficient, but variable specific heat capacity must be taken into account, also about duration when a concrete's central node reaches its max value again variable specific heat capacity can have a considerable effect on the final result. Also, the usage of GGBFS has more influence compared to fly ash.

Keywords: early-age concrete, mass concrete, specific heat capacity, thermal conductivity coefficient

Procedia PDF Downloads 82

Authors: Qinglin Liu, Zhiyong Lin, Zongheng Wei, Jianfeng Wen, Congming Yi, Hai Liu

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The multi-channel blind rendezvous problem in distributed cognitive radio networks (DCRNs) refers to how users in the network can hop to the same channel at the same time slot without any prior knowledge (i.e., each user is unaware of other users' information). The channel hopping (CH) technique is a typical solution to this blind rendezvous problem. In this paper, we propose a quinary coding and matrix structure-based CH algorithm called QCMS-CH. The QCMS-CH algorithm can guarantee the rendezvous of users using only one cognitive radio in the scenario of the asynchronous clock (i.e., arbitrary time drift between the users), heterogeneous channels (i.e., the available channel sets of users are distinct), and symmetric role (i.e., all users play a same role). The QCMS-CH algorithm first represents a randomly selected channel (denoted by R) as a fixed-length quaternary number. Then it encodes the quaternary number into a quinary bootstrapping sequence according to a carefully designed quaternary-quinary coding table with the prefix "R00". Finally, it builds a CH matrix column by column according to the bootstrapping sequence and six different types of elaborately generated subsequences. The user can access the CH matrix row by row and accordingly perform its channel, hoping to attempt rendezvous with other users. We prove the correctness of QCMS-CH and derive an upper bound on its Maximum Time-to-Rendezvous (MTTR). Simulation results show that the QCMS-CH algorithm outperforms the state-of-the-art in terms of the MTTR and the Expected Time-to-Rendezvous (ETTR).

Keywords: channel hopping, blind rendezvous, cognitive radio networks, quaternary-quinary coding

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Authors: Dior Grita F. De Torres, Edielyn Gonzalvo, Jovielyn Manibo

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The experimental study aims to measure the level of aggression and frustration brought about by computer games with incentives and the interrelationship of the said variables. With 50 participants for each four groups, a total of 200 males who are avid of playing computer games participated in the study. The results and analyses presented in the study concluded that incentives differentially affect the level of aggression and frustration of the players with tobt = 7.18 and 6.521 > tcrit = 2.021 using t-test for dependent groups and Fobt = 4.527 and 8.340 > Fcrit = 3.89 using ANOVA with alpha level of 0.05, two tailed. At the same time, computer game’s level of difficulty also affects the level of aggression and frustration of the players with tobt = 7.53 and 4.783 > tcrit = 2.021 respectively and Fobt = 6.524 and 10.167 > Fcrit = 3.89. Moreover, there is also an interaction between incentive and the level of difficulty of computer game with tobt = 9.68 for aggression and tobt = 7.356 > 2.021 for frustration. Computer games and /with incentives has a large effect on the among male students of LPU.

Keywords: aggression, frustration, computer game, incentive

Procedia PDF Downloads 538

Authors: Karthiyayini Nagarajan, P. V. Ramakrishna

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Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar (SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System (Lab Bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench, imaging engineering

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Authors: Xuguang Leng

Abstract:

The crater pattern on the Moon indicates the Moon was captured by Earth in the more recent years, disproves the theory that the Moon was born as a satellite to the Earth. The Moon was tidal locked since it became the satellite of the Earth. Moon’s near side is shielded by Earth from asteroid/comet collisions, with the center of the near side most protected. Yet the crater pattern on the Moon is fairly random, with no distinguishable empty spot/strip, no distinguishable difference near side vs. far side. Were the Moon born as Earth’s satellite, there would be a clear crater free spot, or strip should the tial lock shifts over time, on the near side; and far more craters on the far side. The nonexistence of even a vague crater free spot on the near side of the Moon indicates the capture was a more recent event. Given Earth’s much larger mass and sphere size over the Moon, Earth should have collided with asteroids and comets in much higher frequency, resulting in significant mass gain over the lifespan. Earth’s larger mass and magnetic field are better at retaining water and gas from solar wind’s stripping effect, thus accelerating the mass gain. A dwarf planet Moon can be pulled closer and closer to the Earth over time as Earth’s gravity grows stronger, eventually being captured as a satellite. Given enough time, it is possible Earth’s mass would be large enough to cause the Moon to collide with Earth.

Keywords: moon, origin, crater, pattern

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Authors: Yunbin Deng

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Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

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Authors: Madara Apsalone

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Knowledge management and innovation is key to competitive advantage and sustainable business development in advanced economies. Small and medium-sized enterprises (SMEs) have lower capacity and more constrained resources for long-term and high-uncertainty research and development investments. At the same time, SMEs can implement organizational innovation to improve their performance and further foster other types of innovation. The purpose of this study is to analyze, how socio-cultural factors such as shared values, organizational behaviors, work organization and decision making processes can influence knowledge management and help to develop organizational innovation via an empirical study. Surveying 600 SMEs in Latvia, the author explores the contribution of different socio-cultural factors to organizational innovation and the role of knowledge management and organizational learning in this process. A conceptual model, explaining the impact of organizational team, development, result-orientation and structure is created. The study also proposes insights that contribute to theoretical and practical discussions on fostering innovation of small businesses in small economies.

Keywords: knowledge management, organizational innovation, small and medium-sized enterprises, socio-cultural factors

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Authors: Sanjay Singh, Swati Jaiswal, Prashant Mishra

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Nanoparticle based formulations of drug delivery systems have shown their potential in improving the performance of existing drugs and have opened avenues for new therapies. Calendula extract is a low cost, wide spectrum bioactive material that has been used for a long term therapy of various infections. Aim: The aim of this study was to develop Calendula officinalis extract based nanoformulations and to study the antibacterial activity of either Calendula extract loaded chitosan nanoparticles or Calendula extract coated silver nanoparticles for increased bioavailability and their long term effect. Methods: Chitosan nanoparticles were prepared by the process of ionotropic gelation, based on interaction between the negative groups of tri polyphosphate (TPP) and positively charged amino groups of chitosan. The size of the Calendula extract-loaded chitosan particles was determined using dynamic light scattering and scanning electron microscopy. Antibacterial activities of these formulations were determined based on minimum inhibitory concentration and time kill studies. In addition, silver nanoparticles were also synthesized in the presence of Calendula extract and characterized by UV visible spectrum, DLS and XRD. Experiments were conducted on 96-plates against two Gram-positive bacteria; Staphylococcus aureus and Bacillus subtilis two Gram-negative bacteria; Escherichia coli and Pseudomonas aeruginosa. Results: Results demonstrated time dependent antibacterial activity against different microbes studied. Both Calendula extract and Calendula extract loaded chitosan nanoparticles have shown good antimicrobial activity against both Gram positive and Gram negative bacteria. Conclusion: Calendula extract loaded chitosan nanoparticles and calendula extract coated silver nanoparticles are potential antibacterial for their long term antibacterial effects.

Keywords: antibacterial, Calendula extract, chitosan nanoparticles, silver nanoparticles

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Authors: Rajiv Arora

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Biodiesel may be economical if produced from inexpensive feedstock which commonly contains high level of free fatty acids (FFA) as an inhibitor in production of methyl ester. In this study, a two-step process for biodiesel production from high FFA spent bleach earth oil in a batch reactor is developed. Oil sample extracted from spent bleaching earth (SBE) was utilized for biodiesel process. In the first step, FFA of the SBE oil was reduced to 1.91% through sulfuric acid catalyzed esterification. In the second step, the product prepared from the first esterification process was carried out transesterification with an alkaline catalyst. The influence of four variables on conversion efficiency to methyl ester, i.e., methanol/ SBE oil molar ratio, catalyst amount, reaction temperature and reaction time, was studied in the second stage. The optimum process variables in the transesterification were methanol/oil molar ratio 6:1, heterogeneous catalyst conc. 5 wt %, reaction temperature 65 °C and reaction time 60 minutes to produce biodiesel. Major fuel properties of SBE biodiesel were measured to comply with ASTM and EN standards. Therefore, an optimized process for production of biodiesel from a low-cost high FFA source was accomplished.

Keywords: biodiesel, esterification, free fatty acids, residual oil, spent bleaching earth, transesterification

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Authors: Umme Shahera, Saifullah Munshi, Munira Jahan, Afzalun Nessa, Shahinul Alam, Shahina Tabassum

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The development of HCC is a multi-stage process. Several extrinsic factors, such as aflatoxin, HBV, nutrition, alcohol, and trace elements are thought to initiate or/and promote the hepatocarcinogenesis. Alteration of p53 status is an important intrinsic factor in this process as p53 is essential for preventing inappropriate cell proliferation and maintaining genome integrity following genotoxic stress. This study was designed to assess the correlation of p53 gene expression with HBV-DNA and serum Alanine transaminase (ALT) in patients with cirrhosis and HCC. The study was conducted among 60 patients. The study population were divided into four groups (15 in each groups)-HBV positive cirrhosis, HBV negative cirrhosis, HBV positive HCC and HBV negative HCC. Expression of p53 gene was observed using real time PCR. P53 gene expressions in the above mentioned groups were correlated with serum ALT level and HBV viral load. p53 gene was significantly higher in HBV-positive patients with HCC than HBV-positive cirrhosis. Similarly, the expression of p53 was significantly higher in HBV-positive HCC than HBV-negative HCC patients. However, the expression of p53 was reduced in HBV-positive cirrhosis in comparison with HBV-negative cirrhosis. P53 gene expression in liver was not correlated with the serum levels of ALT in any of the study groups. HBV- DNA load also did not correlated with p53 gene expression in HBV positive HCC and HBV positive cirrhosis patients. This study shows that there was no significant change with the expression of p53 gene in any of the study groups with ALT level or viral load, though differential expression of p53 gene were observed in cirrhosis and HCC patients.

Keywords: P53, ALT, HBV-DNA, liver cirrhosis, hepatocellular carcinoma

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Sung Ho Oh

Abstract:

The advanced traffic lights, the system of traffic information collection and provision, the CCTVs for traffic control, and the traffic information center were installed in Asuncion, capital of Paraguay. After pre-post comparison of the installation, significant changes were found. Even though the traffic volumes were increased, travel speed was higher, so that travel time from origin to destination was decreased. the saving values for travel time, gas cost, and environmental cost are about 47 million US dollars per year. Satisfaction survey results for the installation were presented with statistical significance analysis.

Keywords: advanced transport management systems, effectiveness, Paraguay, traffic lights

Procedia PDF Downloads 358

Authors: Clara Tramuta, Lucia Decastelli, Elisa Barcucci, Sandra Fragassi, Samantha Lupi, Enrico Arletti, Melissa Bizzarri, Daniela Manila Bianchi

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Introdution: Food allergies occurs, in the Western World, 2% of adults and up to 8% of children. The protection of allergic consumers is guaranted, in Eurrope, by Regulation (EU) No 1169/2011 of the European Parliament which governs the consumer's right to information and identifies 14 food allergens to be mandatory indicated on the label. Among these, mustard is a popular spice added to enhance the flavour and taste of foods. It is frequently present as an ingredient in spice blends, marinades, salad dressings, sausages, and other products. Hypersensitivity to mustard is a public health problem since the ingestion of even low amounts can trigger severe allergic reactions. In order to protect the allergic consumer, high performance methods are required for the detection of allergenic ingredients. Food safety laboratories rely on validated methods that detect hidden allergens in food to ensure the safety and health of allergic consumers. Here we present the test results for the validation and accreditation of a Real time PCR assay (RT-PCR: SPECIALfinder MC Mustard, Generon), for the detection of mustard traces in food. Materials and Methods. The method was tested on five classes of food matrices: bakery and pastry products (chocolate cookies), meats (ragù), ready-to-eat (mixed salad), dairy products (yogurt), grains, and milling products (rice and barley flour). Blank samples were spiked starting with the mustard samples (Sinapis Alba), lyophilized and stored at -18 °C, at a concentration of 1000 ppm. Serial dilutions were then prepared to a final concentration of 0.5 ppm, using the DNA extracted by ION Force FAST (Generon) from the blank samples. The Real Time PCR reaction was performed by RT-PCR SPECIALfinder MC Mustard (Generon), using CFX96 System (BioRad). Results. Real Time PCR showed a limit of detection (LOD) of 0.5 ppm in grains and milling products, ready-to-eat, meats, bakery, pastry products, and dairy products (range Ct 25-34). To determine the exclusivity parameter of the method, the ragù matrix was contaminated with Prunus dulcis (almonds), peanut (Arachis hypogaea), Glycine max (soy), Apium graveolens (celery), Allium cepa (onion), Pisum sativum (peas), Daucus carota (carrots), and Theobroma cacao (cocoa) and no cross-reactions were observed. Discussion. In terms of sensitivity, the Real Time PCR confirmed, even in complex matrix, a LOD of 0.5 ppm in five classes of food matrices tested; these values are compatible with the current regulatory situation that does not consider, at international level, to establish a quantitative criterion for the allergen considered in this study. The Real Time PCR SPECIALfinder kit for the detection of mustard proved to be easy to use and particularly appreciated for the rapid response times considering that the amplification and detection phase has a duration of less than 50 minutes. Method accuracy was rated satisfactory for sensitivity (100%) and specificity (100%) and was fully validated and accreditated. It was found adequate for the needs of the laboratory as it met the purpose for which it was applied. This study was funded in part within a project of the Italian Ministry of Health (IZS PLV 02/19 RC).

Keywords: allergens, food, mustard, real time PCR

Procedia PDF Downloads 170

Authors: Karthiyayini Nagarajan, P. V. RamaKrishna

Abstract:

Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar(SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System(lab bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench

Procedia PDF Downloads 472

Authors: Ruichong Zhang

Abstract:

This study proposes a recording-based approach to characterize and quantify earthquake-induced site nonlinearity, exemplified as soil nonlinearity and/or liquefaction. Alternative to Fourier spectral analysis (FSA), the paper introduces time-frequency analysis of earthquake ground motion recordings with the aid of so-called Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the nonlinear features shown in the recordings. With the use of the 2001 Nisqually earthquake recordings, this study shows that the proposed approach is effective in characterizing site nonlinearity and quantifying the influences in seismic ground responses.

Keywords: site nonlinearity, site amplification, site damping, Hilbert-Huang Transform (HHT), liquefaction, 2001 Nisqually Earthquake

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Authors: Benga Ebouele, Thomas Tengen

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Due to long lead time, work in process (WIP) inventory can manifest within the supply chain of most manufacturing system. It implies that there are lesser finished good on hand and more in the process because the work remains in the factory too long and cannot be sold to either customers The supply chain of most manufacturing system is then considered as inefficient as it take so much time to produce the finished good. Time consumed in each operation of the supply chain has an associated energy costs. Such phenomena can be harmful for a hybrid inventory system because a lot of space to store these semi-finished goods may be needed and one is not sure about the final energy cost of producing, holding and delivering the good to customers. The principle that reduces waste of energy within the supply chain of most manufacturing firms should therefore be available to all inventory managers in pursuit of profitability. Decision making by inventory managers in this condition is a modeling process, whereby a dynamical approach is used to depict, examine, specify and even operationalize the relationship between energy consumption and hybrid inventory level. The relationship between energy consumption and inventory level is established, which indicates a poor level of control and hence a potential for energy savings.

Keywords: dynamic modelling, energy used, hybrid inventory, supply chain

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

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Authors: Olayinka Oduwole, Steve Sheard

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The magnetic separation of biological cells using super-magnetic beads has been used widely for various bioassays. These bioassays can further be integrated with other laboratory components to form a biosensor which can be used for cell sorting, mixing, purification, transport, manipulation etc. These bio-sensing applications have also been facilitated by the wide availability of magnetic beads which range in size and magnetic properties produced by different manufacturers. In order to improve the efficiency and separation capabilities of these biosensors, it is important to determine the magnetic force induced velocities and interaction of beads within the magnetic field; this will help biosensor users choose the desired magnetic bead for their specific application. This study presents for the first time the interaction between a pair of different sized super-paramagnetic beads suspended in a static fluid moving within a uniform magnetic field using a modified finite-time-finite-difference scheme. A captured video was used to record the trajectory pattern and a good agreement was obtained between the simulated trajectories and the video data. The model is, therefore, a good approximation for predicting the velocities as well as the interaction between various magnetic particles which differ in size and magnetic properties for bio-sensing applications requiring a low concentration of magnetic beads.

Keywords: biosensor, magnetic field, magnetic separation, super-paramagnetic bead

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: A. Bhattacharya, Sanjay Gupta, S. H. Bodakhe

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HbA1c is form of the haemoglobin that is used to measure the average plasma glucose concentration over prolonged periods of time. It is formed in a non-enzymatic glycation pathway by hemoglobin's exposure to plasma glucose. In diabetes mellitus, higher amounts of glycated hemoglobin, indicating poorer control of blood glucose levels, have been associated with cardiovascular disease, nephropathy, and retinopathy. Guraku’s basic components are nicotine and jaggery, jaggery is made up of sugarcane so can have a diabetogenic potential which is exacerbated in presence of nicotine. This work had done with the aim to find correlation between Diabetic cataract, HbA1c and Guraku. Subjects were enrolled according to the inclusion and exclusion criteria. In this study total 75 subjects were included. In the study it was found that people consuming Guraku had a high level of HbA1c thus are more prone to the development of diabetic cataract. Male subjects are the more than female subjects. Most of the subjects belong to the lower socioeconomical class and not very educated. It could be concluded that this type of study could be useful in indentifying number of subjects suffering from diabetic cataract whose condition get worse by use of nicotine product like Guraku and preventive measure to be taken in prevention of this type of diabetic complication.

Keywords: diabetic cataract, HbA1c, Guraku, diabetogenic potential

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Authors: Reza Behboodian

Abstract:

Monitoring the structural health and diagnosing their damage in the early stages has always been one of the topics of concern. Nowadays, research on structural damage detection methods based on vibration analysis is very extensive. Moreover, these methods can be used as methods of permanent and timely inspection of structures and prevent further damage to structures. Non-destructive methods are the low-cost and economical methods for determining the damage of structures. In this research, a non-destructive method for detecting and identifying the failure location in structures based on dynamic responses resulting from time history analysis is proposed. When the structure is damaged due to the reduction of stiffness, and due to the applied loads, the displacements in different parts of the structure were increased. In the proposed method, the damage position is determined based on the calculation of the strain energy difference in each member of the damaged structure and the healthy structure at any time. Defective members of the structure are indicated by the amount of strain energy relative to the healthy state. The results indicated that the proper accuracy and performance of the proposed method for identifying failure in structures.

Keywords: failure, time history analysis, dynamic response, strain energy

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Authors: Salwa M. Almomen, Mona A. Almaghrabi, Saja M. Alhabardi, Adel A. Alrwisan

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Background: Hepatotoxicity is a major reason for medication withdrawal from the markets. Unfortunately, serious adverse hepatic effects can occur after marketing with limited indicators during clinical development. Therefore, finding possible predictors for hepatotoxicity might guide the monitoring program of various stakeholders. Methods: We examined the clinical review documents for drugs approved in the US from 2011 to 2016 to evaluate their hepatic safety profile. Predictors: we assessed whether these medications meet Hy’s Law with hepatotoxicity grade ≥ 3, labeled hepatic adverse effects at approval, or accelerated approval status. Outcome: post-marketing regulatory action related to hepatotoxicity, including product withdrawal or updates to warning, precaution, or adverse effects sections. Statistical analysis: drugs were included in the analysis from the time of approval until the end of 2019 or the first post-marketing regulatory action related to hepatotoxicity, whichever occurred first. The hazard ratio (HR) was estimated using Cox-regression analysis. Results: We included 192 medications in the study. We classified 48 drugs as having grade ≥ 3 hepatotoxicities, 43 had accelerated approval status, and 74 had labeled information about hepatotoxicity prior to marketing. The adjusted HRs for post-marketing regulatory action for products with grade ≥ 3 hepatotoxicity was 0.61 (95% confidence interval [CI], 0.17-2.23), 0.92 (95%CI, 0.29-2.93) for a drug approved via accelerated approval program, and was 0.91 (95%CI, 0.33-2.56) for drugs with labeled hepatotoxicity information at approval time. Conclusion: This study does not provide conclusive evidence on the association between post-marketing regulatory action and grade ≥ 3 hepatotoxicity, accelerated approval status, or availability of labeled information at approval due to sampling size and channeling bias.

Keywords: accelerated approvals, hepatic adverse effects, drug-induced liver injury, hepatotoxicity predictors, post-marketing withdrawal

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Pello Alfonso-Muniozguren, Madeleine Bussemaker, Devendra Saroj, Judy Lee

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Wastewater treatment is becoming a worldwide concern due to new and tighter environmental regulations, and the increasing need for fresh water for the exponentially growing population. The meat industry has one of the highest consumption of water producing up to 10 times more polluted (BOD) wastewaters in comparison to domestic sewage. Therefore, suitable wastewater treatment methods are required to ensure the wastewater quality meet regulations before discharge. In the present study, a combined lab scale activated sludge-sonication system was used to treat pre-treated abattoir wastewater. A hydraulic retention time of 24 hours and a solid retention time of 13 days were used for the activated sludge process and using ultrasound as tertiary treatment. Different ultrasonic frequencies, powers and sonication times were applied to the samples and results were analysed for chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solids, pH, total coliforms and total viable counts. Additionally, both mechanical and chemical effects of ultrasound were quantified for organic matter removal (COD and BOD) and disinfection (microorganism inactivation) using different techniques such as aluminum foil pitting, flow cytometry, and KI dosimetry.

Keywords: abattoir wastewater, ultrasound, wastewater treatment, water disinfection

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Gloria Patricia Manurung

Abstract:

Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

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Authors: Sudip Subedi, Nipesh Pradhananga

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The musculoskeletal disorders, also known as MSDs, are common in construction workers. MSDs include lower back injuries, knee injuries, spinal injuries, and joint injuries, among others. Since most construction tasks are still manual, construction workers often need to perform repetitive, labor-intensive tasks. And they need to stay in the same or an awkward posture for an extended time while performing such tasks. It induces significant stress to the joints and spines, increasing the risk of getting into MSDs. Manual monitoring of such tasks is virtually impossible with the handful of safety managers in a construction site. This paper proposes a methodology for performing kinetic analysis of the working postures while performing such tasks in real-time. Skeletal of different workers will be tracked using a depth-sensing camera while performing the task to create training data for identifying the best posture. For this, the kinetic analysis will be performed using a human musculoskeletal model in an open-source software system (OpenSim) to visualize the stress induced by essential joints. The “safe posture” inducing lowest stress on essential joints will be computed for different actions involved in the task. The identified “safe posture” will serve as a basis for real-time monitoring and identification of awkward and unsafe postural behaviors of construction workers. Besides, the temporal simulation will be carried out to find the associated long-term effect of repetitive exposure to such observed postures. This will help to create awareness in workers about potential future health hazards and encourage them to work safely. Furthermore, the collected individual data can then be used to provide need-based personalized training to the construction workers.

Keywords: construction workers’ safety, depth sensing camera, human body kinetics, musculoskeletal disorders, real time monitoring, repetitive labor-intensive tasks

Procedia PDF Downloads 139

Authors: Chil-Chyuan Kuo, Chen-Hsuan Tsai

Abstract:

This study presents a cost-effective approach for rapid fabricating modeling platforms utilized in fused deposition modeling system. A small-batch production of modeling platforms about 20 pieces can be obtained economically through silicone rubber mold using vacuum casting without applying the plastic injection molding. The air venting systems is crucial for fabricating modeling platform using vacuum casting. Modeling platforms fabricated can be used for building rapid prototyping model after sandblasting. This study offers industrial value because it has both time-effectiveness and cost-effectiveness.

Keywords: vacuum casting, fused deposition modeling, modeling platform, sandblasting, surface roughness

Procedia PDF Downloads 387

Authors: Temesgen Yadeta, Abbi Lemma, Maina Faith, Adula Bekele Hunde

Abstract:

Effective teaching plays a central role in students’ success in school. The main purpose of the study was to understand how engaging in a lesson study could help to develop secondary school mathematics teachers’ effective teaching practices to support students’ learning better. The research was conducted in Jimma City and employed design-based research with qualitative and quantitative data collected from two secondary schools and 12 mathematics teachers. A purposive sampling technique was used to select participants. Interviews, observations, document analysis, and questionnaires were the main sources of data. Qualitative data were analyzed through coding, categorizing, and thematizing supported by Atlas-ti qualitative data analysis software. Quantitative data were analyzed using mean, standard deviations, medians, and a Wilcoxon-ranked signed test supported by statistical packages for social sciences software. The findings of the study revealed that engaging in lesson study built mathematics teachers’ effective teaching practices. School leaders’ positive attitudes and initiative towards the lesson study were found to be supportive. Teachers’ collaboration, commitment with determination, and active participation during the study periods were also found to be supportive. Shortage of time and teachers’ high teaching load had constrained teachers’ active engagement in lesson study during study periods. In conclusion, the lesson study provided a more practical link between teachers’ professional learning activities and actual classroom practices. Therefore, it would be crucial to integrate lesson study into the present school-based teachers’ pedagogical capacity-building program in the country. It would also be beneficial to extend the merits of lesson study to other school subjects and more schools in the country based on their specific school contexts to build teachers’ effective teaching practices.

Keywords: effective teaching practices, lesson study, mathematics teachers, professional development, secondary school

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