Search results for: time reduction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21928

Search results for: time reduction

19498 An Introduction to Critical Chain Project Management Methodology

Authors: Ranjini Ramanath, Nanjunda P. Swamy

Abstract:

Construction has existed in our lives since time immemorial. However, unlike any other industry, construction projects have their own unique challenges – project type, purpose and end use of the project, geographical conditions, logistic arrangements, largely unorganized manpower and requirement of diverse skill sets, etc. These unique characteristics bring in their own level of risk and uncertainties to the project, which cause the project to deviate from its planned objectives of time, cost, quality, etc. over the many years, there have been significant developments in the way construction projects are conceptualized, planned, and managed. With the rapid increase in the population, increased rate of urbanization, there is a growing demand for infrastructure development, and it is required that the projects are delivered timely, and efficiently. In an age where ‘Time is Money,' implementation of new techniques of project management is required in leading to successful projects. This paper proposes a different approach to project management, which if applied in construction projects, can help in the accomplishment of the project objectives in a faster manner.

Keywords: critical chain project management methodology, critical chain, project management, construction management

Procedia PDF Downloads 424
19497 Crystalline Silica Exposure in Tunnelling: Identifying Barriers to Safe Practices

Authors: Frederick Anlimah, Vinod Gopaldasani, Catherine MacPhail, Brian Davies

Abstract:

The construction industry, particularly tunnel construction, exposes workers to respirable crystalline silica (RCS), which can cause incurable illnesses such as silicosis and lung cancer. Despite various control measures, exposures remain inadequately controlled. This research aimed to identify the barriers and challenges hindering the implementation of effective controls and the adoption of safe work practices to protect workers from RCS exposure in tunnelling. A mixed-method approach was employed for this research. Tunnel construction workers were observed, surveyed and interviewed to gauge their knowledge and attitudes and understand their challenges in reducing RCS exposure. The preliminary analysis of the data reveals a diverse array of sociotechnical factors interacting to influence RCS exposure. It is noteworthy that participants consistently emphasised the project as the most exemplary one they have been involved in, although there is room for improvement. While there is a commendable level of knowledge about RCS exposure and control in tunnelling, there is a striking lack of perceived satisfaction regarding dust control. Several factors were identified as interacting to prevent the effective management of dust. These include perceived time pressure, absence of on-tool dust controls, low risk perceptions among workers, and inadequate enforcement of controls. Moreover, participants highlighted communication and heat-related challenges as hindrances to the continuous wear of respirators. This research highlights the need for a paradigm shift in tunnel construction to address the barriers associated with RCS exposure reduction. It emphasises the importance of collaboration among various stakeholders, advocating for more effective controls and enforcement strategies and enhanced worker education through knowledge sharing.

Keywords: respirable crystalline silica, dust control, worker practices, exposure prevention, silicosis

Procedia PDF Downloads 68
19496 Effect of Incineration Temperatures to Time on the Rice Husk Ash (RHA) Silica Structure: A Comparative Study to the Literature with Experimental Work

Authors: Binyamien Ibrahim Rasoul

Abstract:

Controlled burning of rice husk can produce amorphous rice husk ash (RHA) with high silica content which can significantly enhance the properties of concrete. This study has been undertaken to investigate the relationship between the incineration temperatures and time to produce RHA with ultimate reactivity. The rice husk samples were incinerated in an electrical muffle furnace at 350°C, 400°C, 425°C 450°C, 475°C, and 500°C for 60 and 90 minutes, respectively. The silica structure in the Rice Husk Ash (RHA) was determined using X-Ray diffraction analysis, while chemical properties obtained using X-Ray Fluorescence. The results show that RHA appeared to be the totally amorphous when the husk incineration up to 425°C for 60 and even at 90 minutes. However, with increased temperature to 450°C, 475°C and 500°C, traces of crystalline silica (quartz) were detected. However, cannot be taken into account as it does not affect on the ash structure. In conclusion, the result gives an idea of the temperature and the time required to produce ash from rice husk with totally amorphous form.

Keywords: rice husk ash, silica, compressive strength, tensile strength, X-Ray diffraction, X-R florescence, pozzolanic activity

Procedia PDF Downloads 162
19495 A Method to Compute Efficient 3D Helicopters Flight Trajectories Based On a Motion Polymorph-Primitives Algorithm

Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

Abstract:

Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real-time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: robotics, aerial robots, motion primitives, helicopter

Procedia PDF Downloads 617
19494 A Fluorescent Polymeric Boron Sensor

Authors: Soner Cubuk, Mirgul Kosif, M. Vezir Kahraman, Ece Kok Yetimoglu

Abstract:

Boron is an essential trace element for the completion of the life circle for organisms. Suitable methods for the determination of boron have been proposed, including acid - base titrimetric, inductively coupled plasma emission spectroscopy flame atomic absorption and spectrophotometric. However, the above methods have some disadvantages such as long analysis times, requirement of corrosive media such as concentrated sulphuric acid and multi-step sample preparation requirements and time-consuming procedures. In this study, a selective and reusable fluorescent sensor for boron based on glycosyloxyethyl methacrylate was prepared by photopolymerization. The response characteristics such as response time, pH, linear range, limit of detection were systematically investigated. The excitation/emission maxima of the membrane were at 378/423 nm, respectively. The approximate response time was measured as 50 sec. In addition, sensor had a very low limit of detection which was 0.3 ppb. The sensor was successfully used for the determination of boron in water samples with satisfactory results.

Keywords: boron, fluorescence, photopolymerization, polymeric sensor

Procedia PDF Downloads 284
19493 An Efficient Algorithm of Time Step Control for Error Correction Method

Authors: Youngji Lee, Yonghyeon Jeon, Sunyoung Bu, Philsu Kim

Abstract:

The aim of this paper is to construct an algorithm of time step control for the error correction method most recently developed by one of the authors for solving stiff initial value problems. It is achieved with the generalized Chebyshev polynomial and the corresponding error correction method. The main idea of the proposed scheme is in the usage of the duplicated node points in the generalized Chebyshev polynomials of two different degrees by adding necessary sample points instead of re-sampling all points. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. Two stiff problems are numerically solved to assess the effectiveness of the proposed scheme.

Keywords: stiff initial value problem, error correction method, generalized Chebyshev polynomial, node points

Procedia PDF Downloads 575
19492 Modelling the Effect of Alcohol Consumption on the Accelerating and Braking Behaviour of Drivers

Authors: Ankit Kumar Yadav, Nagendra R. Velaga

Abstract:

Driving under the influence of alcohol impairs the driving performance and increases the crash risks worldwide. The present study investigated the effect of different Blood Alcohol Concentrations (BAC) on the accelerating and braking behaviour of drivers with the help of driving simulator experiments. Eighty-two licensed Indian drivers drove on the rural road environment designed in the driving simulator at BAC levels of 0.00%, 0.03%, 0.05%, and 0.08% respectively. Driving performance was analysed with the help of vehicle control performance indicators such as mean acceleration and mean brake pedal force of the participants. Preliminary analysis reported an increase in mean acceleration and mean brake pedal force with increasing BAC levels. Generalized linear mixed models were developed to quantify the effect of different alcohol levels and explanatory variables such as driver’s age, gender and other driver characteristic variables on the driving performance indicators. Alcohol use was reported as a significant factor affecting the accelerating and braking performance of the drivers. The acceleration model results indicated that mean acceleration of the drivers increased by 0.013 m/s², 0.026 m/s² and 0.027 m/s² for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Results of the brake pedal force model reported that mean brake pedal force of the drivers increased by 1.09 N, 1.32 N and 1.44 N for the BAC levels of 0.03%, 0.05% and 0.08% respectively. Age was a significant factor in both the models where one year increase in drivers’ age resulted in 0.2% reduction in mean acceleration and 19% reduction in mean brake pedal force of the drivers. It shows that driving experience could compensate for the negative effects of alcohol to some extent while driving. Female drivers were found to accelerate slower and brake harder as compared to the male drivers which confirmed that female drivers are more conscious about their safety while driving. It was observed that drivers who were regular exercisers had better control on their accelerator pedal as compared to the non-regular exercisers during drunken driving. The findings of the present study revealed that drivers tend to be more aggressive and impulsive under the influence of alcohol which deteriorates their driving performance. Drunk driving state can be differentiated from sober driving state by observing the accelerating and braking behaviour of the drivers. The conclusions may provide reference in making countermeasures against drinking and driving and contribute to traffic safety.

Keywords: alcohol, acceleration, braking behaviour, driving simulator

Procedia PDF Downloads 147
19491 African Swine Fewer Situation and Diagnostic Methods in Lithuania

Authors: Simona Pileviciene

Abstract:

On 24th January 2014, Lithuania notified two primary cases of African swine fever (ASF) in wild boars. The animals were tested positive for ASF virus (ASFV) genome by real-time PCR at the National Reference Laboratory for ASF in Lithuania (NRL), results were confirmed by the European Union Reference Laboratory for African swine fever (CISA-INIA). Intensive wild and domestic animal monitoring program was started. During the period of 2014-2017 ASF was confirmed in two large commercial pig holding with the highest biosecurity. Pigs were killed and destroyed. Since 2014 ASF outbreak territory from east and south has expanded to the middle of Lithuania. Diagnosis by PCR is one of the highly recommended diagnostic methods by World Organization for Animal Health (OIE) for diagnosis of ASF. The aim of the present study was to compare singleplex real-time PCR assays to a duplex assay allowing the identification of ASF and internal control in a single PCR tube and to compare primers, that target the p72 gene (ASF 250 bp and ASF 75 bp) effectivity. Multiplex real-time PCR assays prove to be less time consuming and cost-efficient and therefore have a high potential to be applied in the routine analysis. It is important to have effective and fast method that allows virus detection at the beginning of disease for wild boar population and in outbreaks for domestic pigs. For experiments, we used reference samples (INIA, Spain), and positive samples from infected animals in Lithuania. Results show 100% sensitivity and specificity.

Keywords: African swine fewer, real-time PCR, wild boar, domestic pig

Procedia PDF Downloads 168
19490 Preparation and Characterization of Nanocrystalline Cellulose from Acacia mangium

Authors: Samira Gharehkhani, Seyed Farid Seyed Shirazi, Abdolreza Gharehkhani, Hooman Yarmand, Ahmad Badarudin, Rushdan Ibrahim, Salim Newaz Kazi

Abstract:

Nanocrystalline cellulose (NCC) were prepared by acid hydrolysis and ultrasound treatment of bleached Acacia mangium fibers. The obtained rod-shaped nanocrystals showed a uniform size. The results showed that NCC with high crystallinity can be obtained using 64 wt% sulfuric acid. The effect of synthesis condition was investigated. Different reaction times were examined to produce the NCC and the results revealed that an optimum reaction time has to be used for preparing the NCC. Morphological investigation was performed using the transmission electron microscopy (TEM). Fourier transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA) were performed. X-ray diffraction (XRD) analysis revealed that the crystallinity increased with successive treatments. The NCC suspension was homogeneous and stable and no sedimentation was observed for a long time.

Keywords: acid hydrolysis, nanocrystalline cellulose, nano material, reaction time

Procedia PDF Downloads 508
19489 Parathyroid Hormone Receptor 1 as a Prognostic Indicator in Canine Osteosarcoma

Authors: Awf A. Al-Khan, Michael J. Day, Judith Nimmo, Mourad Tayebi, Stewart D. Ryan, Samantha J. Richardson, Janine A. Danks

Abstract:

Osteosarcoma (OS) is the most common type of malignant primary bone tumour in dogs. In addition to their critical roles in bone formation and remodeling, parathyroid hormone-related protein (PTHrP) and its receptor (PTHR1) are involved in progression and metastasis of many types of tumours in humans. The aims of this study were to determine the localisation and expression levels of PTHrP and PTHR1 in canine OS tissues using immunohistochemistry and to investigate if this expression is correlated with survival time. Formalin-fixed, paraffin-embedded tissue samples from 44 dogs with known survival time that had been diagnosed with primary osteosarcoma were analysed for localisation of PTHrP and PTHR1. Findings showed that both PTHrP and PTHR1 were present in all OS samples. The dogs with high level of PTHR1 protein (16%) had decreased survival time (P<0.05) compared to dogs with less PTHR1 protein. PTHrP levels did not correlate with survival time (P>0.05). The results of this study indicate that the PTHR1 is expressed differently in canine OS tissues and this may be correlated with poor prognosis. This may mean that PTHR1 may be useful as a prognostic indicator in canine OS and could represent a good therapeutic target in OS.

Keywords: dog, expression, osteosarcoma, parathyroid hormone receptor 1 (PTHR1), parathyroid hormone-related protein (PTHrP), survival

Procedia PDF Downloads 277
19488 Experiences of Timing Analysis of Parallel Embedded Software

Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

Abstract:

The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

Procedia PDF Downloads 325
19487 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks

Authors: Danilo López, Edwin Rivas, Leyla López

Abstract:

This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time

Procedia PDF Downloads 332
19486 COVID-19 Pandemic Influence on Toddlers and Preschoolers’ Screen Time

Authors: Juliana da Silva Cardoso, Cláudia Correia, Rita Gomes, Carolina Fraga, Inês Cascais, Sara Monteiro, Beatriz Teixeira, Sandra Ribeiro, Carolina Andrade, Cláudia Oliveira, Diana Gonzaga, Catarina Prior, Inês Vaz Matos

Abstract:

The average daily screen time (ST) has been increasing in children, even at young ages. This seems to be associated with a higher incidence of neurodevelopmental disorders, and as the time of exposure increases, the greater is the functional impact. This study aims to compare the daily ST of toddlers and preschoolers previously and during the COVID-19 pandemic. A questionnaire was applied by telephone to parents/caregivers of children between 1 and 5 years old, followed up at 4 primary care units belonging to the Group of Primary Health Care Centers of Western Porto, Portugal. 520 children were included: 52.9% male, mean age 39.4 ± 13.9 months. The mean age of first exposure to screens was 13.9 ± 8.0 months, and most of the children were exposed to more than one screen daily. Considering the WHO recommendations, before the COVID-19 pandemic, 385 (74.0%) and 408 (78.5%) children had excessive ST during the week and the weekend, respectively; during the lockdown, these values increased to 495 (95.2%) and 482 (92.7%). Maternal education and both the child's median age and the median age of first exposure to screens had a statistically significant association with excessive ST, with OR 0.2 (p = 0.03, CI 95% 0.07-0.86), OR 1.1 (p = 0.01, 95% CI 1.05-1.14) and OR 0.9 (p = 0.05, 95% CI 0. 87-0.98), respectively. Most children in this sample had a higher than recommended ST, which increased with the onset of the COVID-19 pandemic. These results are worrisome and point to the need for urgent intervention.

Keywords: COVID-19 pandemic, preschoolers, screen time, toddlers

Procedia PDF Downloads 219
19485 Real-Time Recognition of Dynamic Hand Postures on a Neuromorphic System

Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

Procedia PDF Downloads 473
19484 Piaui Solar: State Development Impulsed by Solar Photovoltaic Energy

Authors: Amanda Maria Rodrigues Barroso, Ary Paixao Borges Santana Junior, Caio Araujo Damasceno

Abstract:

In Piauí, the Brazilian state, solar energy has become one of the renewable sources targeted by internal and external investments, with the intention of leveraging the development of society. However, for a residential or business consumer to be able to deploy this source, there is usually a need for a high initial investment due to its high cost. The countless high taxes on equipment and services are one of the factors that contribute to this cost and ultimately fall on the consumer. Through analysis, a way of reducing taxes is sought in order to encourage consumer adhesion to the use of photovoltaic solar energy. Thus, the objective is to implement the Piauí Solar Program in the state of Piauí in order to stimulate the deployment of photovoltaic solar energy, through benefits granted to users, providing state development by boosting the diversification of the state's energy matrix. The research method adopted was based on the analysis of data provided by the Teresina City Hall, by the Brazilian Institute of Geography and Statistics and by a private company in the capital of Piauí. The account was taken of the total amount paid in Property and Urban Territorial Property Tax (IPTU), in electricity and in the service of installing photovoltaic panels in a residence with 6 people. Through Piauí Solar, a discount of 80% would be applied to the taxes present in the budgets regarding the implementation of these photovoltaic plates in homes and businesses, as well as in the IPTU. In addition, another factor also taken into account is the energy savings generated after the implementation of these boards. In the studied residence, the annual payment of IPTU went from R $ 99.83 reais to R $ 19.96, the reduction of taxes present in the budget for the implantation of solar panels, caused the value to increase from R $ 42,744.22 to R $ 37,241.98. The annual savings in electricity bills were estimated at around R $ 6,000. Therefore, there is a reduction of approximately 24% in the total invested. The trend of the Piauí Solar program, then, is to bring benefits to the state, providing an improvement in the living conditions of the population, through the savings generated by this program. In addition, an increase in the diversification of the Piauí energy matrix can be seen with the advancement of the use of this renewable energy.

Keywords: development, economy, energy, taxes

Procedia PDF Downloads 140
19483 Improvement of Transient Voltage Response Using PSS-SVC Coordination Based on ANFIS-Algorithm in a Three-Bus Power System

Authors: I Made Ginarsa, Agung Budi Muljono, I Made Ari Nrartha

Abstract:

Transient voltage response appears in power system operation when an additional loading is forced to load bus of power systems. In this research, improvement of transient voltage response is done by using power system stabilizer-static var compensator (PSS-SVC) based on adaptive neuro-fuzzy inference system (ANFIS)-algorithm. The main function of the PSS is to add damping component to damp rotor oscillation through automatic voltage regulator (AVR) and excitation system. Learning process of the ANFIS is done by using off-line method where data learning that is used to train the ANFIS model are obtained by simulating the PSS-SVC conventional. The ANFIS model uses 7 Gaussian membership functions at two inputs and 49 rules at an output. Then, the ANFIS-PSS and ANFIS-SVC models are applied to power systems. Simulation result shows that the response of transient voltage is improved with settling time at the time of 4.25 s.

Keywords: improvement, transient voltage, PSS-SVC, ANFIS, settling time

Procedia PDF Downloads 581
19482 Formulation and Evaluation of Mouth Dissolving Tablet of Ketorolac Tromethamine by Using Natural Superdisintegrants

Authors: J. P. Lavande, A. V.Chandewar

Abstract:

Mouth dissolving tablet is the speedily growing and highly accepted drug delivery system. This study was aimed at development of Ketorolac Tromethamine mouth dissolving tablet (MDTs), which can disintegrate or dissolve rapidly once placed in the mouth. Conventional Ketorolac tromethamine tablet requires water to swallow it and has limitation like low disintegration rate, low solubility etc. Ketorolac Tromethamine mouth dissolving tablets (formulation) consist of super-disintegrate like Heat Modified Karaya Gum, Co-treated Heat Modified Agar & Filler microcrystalline cellulose (MCC). The tablets were evaluated for weight variation, friability, hardness, in vitro disintegration time, wetting time, in vitro drug release profile, content uniformity. The obtained results showed that low weight variation, good hardness, acceptable friability, fast wetting time. Tablets in all batches disintegrated within 15-50 sec. The formulation containing superdisintegrants namely heat modified karaya gum and heat modified agar showed better performance in disintegration and drug release profile.

Keywords: mouth dissolving tablet, Ketorolac tromethamine, disintegration time, heat modified karaya gum, co-treated heat modified agar

Procedia PDF Downloads 283
19481 Enhancing Patch Time Series Transformer with Wavelet Transform for Improved Stock Prediction

Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

Abstract:

Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

Procedia PDF Downloads 55
19480 Identification of Crimean-Congo Hemorrhagic Fever Virus in Patients Referred to Ahvaz and Gilan Hospitals in Iran by real-time PCR Technique

Authors: Najmeh Jafari, Sona Rostampour Yasouri

Abstract:

Crimean-Congo hemorrhagic fever (CCHF) is an acute hemorrhagic disease. This disease is one of the common diseases between humans and animals, transmitted through tick bites or contact with the blood and secretions or carcasses of infected animals and humans. CCHF is more common in people who work with livestock, such as ranchers, butchers, farmers, slaughterhouse workers, healthcare workers, etc. Its hospital prevalence is also very high. Considering that CCHF can be transmitted through the consumption of food such as beef and sheep meat, this study aims to quickly identify and diagnose the Crimean-Congo fever virus in suspected patients through real-time PCR technique. In the summer of 1402, 20 blood samples were collected separately from Ahvaz and Gilan hospitals. An extraction kit was used to extract the virus RNA. Primers and probes were designed based on the S genomic region, the conserved region in CCHFV. Then, a real-time PCR technique was performed with specific primers and probes. It should be noted that the mentioned technique was repeated several times. The number of 4 samples from the examined samples was determined positive by real-time PCR. This technique has high sensitivity and specificity and the possibility of rapid detection of CCHFV. Therefore, the above method is a good candidate for quick disease diagnosis. By diagnosing the disease, the treatment process can be done faster, and the best prevention methods can be used to control the disease and prevent the death of patients.

Keywords: ahvaz, crimean-congo hemorrhagic fever, gilan, real time PCR

Procedia PDF Downloads 75
19479 Genetic Algorithm for In-Theatre Military Logistics Search-and-Delivery Path Planning

Authors: Jean Berger, Mohamed Barkaoui

Abstract:

Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

Procedia PDF Downloads 361
19478 Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model

Authors: Navid Daryasafar, Nima Farshidfar

Abstract:

In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

Procedia PDF Downloads 542
19477 3-D Strain Imaging of Nanostructures Synthesized via CVD

Authors: Sohini Manna, Jong Woo Kim, Oleg Shpyrko, Eric E. Fullerton

Abstract:

CVD techniques have emerged as a promising approach in the formation of a broad range of nanostructured materials. The realization of many practical applications will require efficient and economical synthesis techniques that preferably avoid the need for templates or costly single-crystal substrates and also afford process adaptability. Towards this end, we have developed a single-step route for the reduction-type synthesis of nanostructured Ni materials using a thermal CVD method. By tuning the CVD growth parameters, we can synthesize morphologically dissimilar nanostructures including single-crystal cubes and Au nanostructures which form atop untreated amorphous SiO2||Si substrates. An understanding of the new properties that emerge in these nanostructures materials and their relationship to function will lead to for a broad range of magnetostrictive devices as well as other catalysis, fuel cell, sensor, and battery applications based on high-surface-area transition-metal nanostructures. We use coherent X-ray diffraction imaging technique to obtain 3-D image and strain maps of individual nanocrystals. Coherent x-ray diffractive imaging (CXDI) is a technique that provides the overall shape of a nanostructure and the lattice distortion based on the combination of highly brilliant coherent x-ray sources and phase retrieval algorithm. We observe a fine interplay of reduction of surface energy vs internal stress, which plays an important role in the morphology of nano-crystals. The strain distribution is influenced by the metal-substrate interface and metal-air interface, which arise due to differences in their thermal expansion. We find the lattice strain at the surface of the octahedral gold nanocrystal agrees well with the predictions of the Young-Laplace equation quantitatively, but exhibits a discrepancy near the nanocrystal-substrate interface resulting from the interface. The strain in the bottom side of the Ni nanocube, which is contacted on the substrate surface is compressive. This is caused by dissimilar thermal expansion coefficients between Ni nanocube and Si substrate. Research at UCSD support by NSF DMR Award # 1411335.

Keywords: CVD, nanostructures, strain, CXRD

Procedia PDF Downloads 394
19476 Comparison of Two Transcranial Magnetic Stimulation Protocols on Spasticity in Multiple Sclerosis - Pilot Study of a Randomized and Blind Cross-over Clinical Trial

Authors: Amanda Cristina da Silva Reis, Bruno Paulino Venâncio, Cristina Theada Ferreira, Andrea Fialho do Prado, Lucimara Guedes dos Santos, Aline de Souza Gravatá, Larissa Lima Gonçalves, Isabella Aparecida Ferreira Moretto, João Carlos Ferrari Corrêa, Fernanda Ishida Corrêa

Abstract:

Objective: To compare two protocols of Transcranial Magnetic Stimulation (TMS) on quadriceps muscle spasticity in individuals diagnosed with Multiple Sclerosis (MS). Method: Clinical, crossover study, in which six adult individuals diagnosed with MS and spasticity in the lower limbs were randomized to receive one session of high-frequency (≥5Hz) and low-frequency (≤ 1Hz) TMS on motor cortex (M1) hotspot for quadriceps muscle, with a one-week interval between the sessions. To assess the spasticity was applied the Ashworth scale and were analyzed the latency time (ms) of the motor evoked potential (MEP) and the central motor conduction time (CMCT) of the bilateral quadriceps muscle. Assessments were performed before and after each intervention. The difference between groups was analyzed using the Friedman test, with a significance level of 0.05 adopted. Results: All statistical analyzes were performed using the SPSS Statistic version 26 programs, with a significance level established for the analyzes at p<0.05. Shapiro Wilk normality test. Parametric data were represented as mean and standard deviation for non-parametric variables, median and interquartile range, and frequency and percentage for categorical variables. There was no clinical change in quadriceps spasticity assessed using the Ashworth scale for the 1 Hz (p=0.813) and 5 Hz (p= 0.232) protocols for both limbs. Motor Evoked Potential latency time: in the 5hz protocol, there was no significant change for the contralateral side from pre to post-treatment (p>0.05), and for the ipsilateral side, there was a decrease in latency time of 0.07 seconds (p<0.05 ); for the 1Hz protocol there was an increase of 0.04 seconds in the latency time (p<0.05) for the contralateral side to the stimulus, and for the ipsilateral side there was a decrease in the latency time of 0.04 seconds (p=<0.05), with a significant difference between the contralateral (p=0.007) and ipsilateral (p=0.014) groups. Central motor conduction time in the 1Hz protocol, there was no change for the contralateral side (p>0.05) and for the ipsilateral side (p>0.05). In the 5Hz protocol for the contralateral side, there was a small decrease in latency time (p<0.05) and for the ipsilateral side, there was a decrease of 0.6 seconds in the latency time (p<0.05) with a significant difference between groups (p=0.019). Conclusion: A high or low-frequency session does not change spasticity, but it is observed that when the low-frequency protocol was performed, there was an increase in latency time on the stimulated side, and a decrease in latency time on the non-stimulated side, considering then that inhibiting the motor cortex increases cortical excitability on the opposite side.

Keywords: multiple sclerosis, spasticity, motor evoked potential, transcranial magnetic stimulation

Procedia PDF Downloads 92
19475 Screening of Indigenous Rhizobacteria for Growth Promoting and Antagonistic Activity against Fusarium Oxysporoum in Tomato

Authors: Mohammed H. Abu-Dieyeh, Mohammad M. Zalloum

Abstract:

Plant growth-promoting rhizobacteria (PGPR) are known to enhance plant growth and/or reduce plant damage due to soil-borne pathogens. Tomato is the highest consumable vegetable world-wide including Jordan. Fusarium oxysporum is a pathogen that causes well-known damages and losses to many vegetable crops including tomato. In this study, purification of 112 isolates of PGPR strains from rhizosphere environment of different regions in Jordan was accomplished. All bacterial isolates were In-vitro screened for antagonistic effects against F. oxysporum. The eleven most effective isolates that caused 30%-50% in-vitro growth reduction of F. oxysporum were selected. 8 out of 11 of these isolates were collected from Al-Halabat (arid-land). 7 isolates of Al-Halabat exerted 40-54% In-vitro growth reduction of F. oxysporum. Four-week-old seedlings of tomato cultivar (Anjara, the most susceptible indigenous cultivar to F. oxysporum) treated with PGPR5 (Bacillus amyloliquefaciens), and exposed to F. oxysporum, showed no disease symptoms and no significant changes in biomasses or chlorophyll contents indicating a non-direct mechanism of action of PGPR on tomato plants. However PGPR3 (Bacillus sp.), PGPR4 (Bacillus cereus), and PGPR38 (Paenibacillus sp.) treated plants or PGPR treated and exposed to F. oxysporum showed a significant increasing growth of shoot and root biomasses as well as chlorophyll contents of leaves compared to control untreated plants or plants exposed to the fungus without PGPR treatment. A significant increase in number of flowers per plant was also recorded in all PGPR treated plants. The characterization of rhizobacterial strains were accomplished using 16S rRNA gene sequence analysis in addition to microscopic characterization. Further research is necessary to explore the potentiality of other collected PGPR isolates on tomato plants in addition to investigate the efficacy of the identified isolates on other plant pathogens and then finding a proper and effective methods of formulation and application of the successful isolates on selected crops.

Keywords: antagonism, arid land, growth promoting, rhizobacteria, tomato

Procedia PDF Downloads 373
19474 Molecular Dynamics Simulation Study of the Influence of Potassium Salts on the Adsorption and Surface Hydration Inhibition Performance of Hexane, 1,6 - Diamine Clay Mineral Inhibitor onto Sodium Montmorillonite

Authors: Justine Kiiza, Xu Jiafang

Abstract:

The world’s demand for energy is increasing rapidly due to population growth and a reduction in shallow conventional oil and gas reservoirs, resorting to deeper and mostly unconventional reserves like shale oil and gas. Most shale formations contain a large amount of expansive sodium montmorillonite (Na-Mnt), due to high water adsorption, hydration, and when the drilling fluid filtrate enters the formation with high Mnt content, the wellbore wall can be unstable due to hydration and swelling, resulting to shrinkage, sticking, balling, time wasting etc., and well collapse in extreme cases causing complex downhole accidents and high well costs. Recently, polyamines like 1, 6 – hexane diamine (HEDA) have been used as typical drilling fluid shale inhibitors to minimize and/or cab clay mineral swelling and maintain the wellbore stability. However, their application is limited to shallow drilling due to their sensitivity to elevated temperature and pressure. Inorganic potassium salts i.e., KCl, have long been applied for restriction of shale formation hydration expansion in deep wells, but their use is limited due to toxicity. Understanding the adsorption behaviour of HEDA on Na-Mnt surfaces in present of organo-salts, organic K-salts e.g., HCO₂K - main component of organo-salt drilling fluid, is of great significance in explaining the inhibitory performance of polyamine inhibitors. Molecular dynamic simulations (MD) were applied to investigate the influence of HCO₂K and KCl on the adsorption mechanism of HEDA on the Na-Mnt surface. Simulation results showed that adsorption configurations of HEDA are mainly by terminal amine groups with a flat-lying alkyl hydrophobic chain. Its interaction with the clay surface decreased the H-bond number between H₂O-clay and neutralized the negative charge of the Mnt surface, thus weakening the surface hydration ability of Na-Mnt. The introduction of HCO₂K greatly improved inhibition ability, coordination of interlayer ions with H₂O as they were replaced by K+, and H₂O-HCOO- coordination reduced H₂O-Mnt interactions, mobility and transport capability of H₂O molecules were more decreased. While KCl showed little ability and also caused more hydration with time, HCO₂K can be used as an alternative for offshore drilling instead of toxic KCl, with a maximum concentration noted in this study as 1.65 wt%. This study provides a theoretical elucidation for the inhibition mechanism and adsorption characteristics of HEDA inhibitor on Na-Mnt surfaces in the presence of K+-salts and may provide more insight into the evaluation, selection, and molecular design of new clay-swelling high-performance WBDF systems used in oil and gas complex offshore drilling well sections.

Keywords: shale, hydration, inhibition, polyamines, organo-salts, simulation

Procedia PDF Downloads 50
19473 Efficiency of Geocell Reinforcement for Using in Expanded Polystyrene Embankments via Numerical Analysis

Authors: S. N. Moghaddas Tafreshi, S. M. Amin Ghotbi

Abstract:

This paper presents a numerical study for investigating the effectiveness of geocell reinforcement in reducing pressure and settlement over EPS geofoam blocks in road embankments. A 3-D FEM model of soil and geofoam was created in ABAQUS, and geocell was also modeled realistically using membrane elements. The accuracy of the model was tested by comparing its results with previous works. Sensitivity analyses showed that reinforcing the soil cover with geocell has a significant influence on the reduction of imposed stresses over geofoam and consequently decreasing its deformation.

Keywords: EPS geofoam, geocell, reinforcement, road embankments, lightweight fill

Procedia PDF Downloads 275
19472 Predictive Factors of Nasal Continuous Positive Airway Pressure (NCPAP) Therapy Success in Preterm Neonates with Hyaline Membrane Disease (HMD)

Authors: Novutry Siregar, Afdal, Emilzon Taslim

Abstract:

Hyaline Membrane Disease (HMD) is the main cause of respiratory failure in preterm neonates caused by surfactant deficiency. Nasal Continuous Positive Airway Pressure (NCPAP) is the therapy for HMD. The success of therapy is determined by gestational age, birth weight, HMD grade, time of NCAP administration, and time of breathing frequency recovery. The aim of this research is to identify the predictive factor of NCPAP therapy success in preterm neonates with HMD. This study used a cross-sectional design by using medical records of patients who were treated in the Perinatology of the Pediatric Department of Dr. M. Djamil Padang Central Hospital from January 2015 to December 2017. The samples were eighty-two neonates that were selected by using the total sampling technique. Data analysis was done by using the Chi-Square Test and the Multiple Logistic Regression Prediction Model. The results showed the success rate of NCPAP therapy reached 53.7%. Birth weight (p = 0.048, OR = 3.34 95% CI 1.01-11.07), HMD grade I (p = 0.018, OR = 4.95 CI 95% 1.31-18.68), HMD grade II (p = 0.044, OR = 5.52 95% CI 1.04-29.15), and time of breathing frequency recovery (p = 0,000, OR = 13.50 95% CI 3.58-50, 83) are the predictive factors of NCPAP therapy success in preterm neonates with HMD. The most significant predictive factor is the time of breathing frequency recovery.

Keywords: predictive factors, the success of therapy, NCPAP, preterm neonates, HMD

Procedia PDF Downloads 63
19471 Optimization of Beneficiation Process for Upgrading Low Grade Egyptian Kaolin

Authors: Nagui A. Abdel-Khalek, Khaled A. Selim, Ahmed Hamdy

Abstract:

Kaolin is naturally occurring ore predominantly containing kaolinite mineral in addition to some gangue minerals. Typical impurities present in kaolin ore are quartz, iron oxides, titanoferrous minerals, mica, feldspar, organic matter, etc. The main coloring impurity, particularly in the ultrafine size range, is titanoferrous minerals. Kaolin is used in many industrial applications such as sanitary ware, table ware, ceramic, paint, and paper industries, each of which should be of certain specifications. For most industrial applications, kaolin should be processed to obtain refined clay so as to match with standard specifications. For example, kaolin used in paper and paint industries need to be of high brightness and low yellowness. Egyptian kaolin is not subjected to any beneficiation process and the Egyptian companies apply selective mining followed by, in some localities, crushing and size reduction only. Such low quality kaolin can be used in refractory and pottery production but not in white ware and paper industries. This paper aims to study the amenability of beneficiation of an Egyptian kaolin ore of El-Teih locality, Sinai, to be suitable for different industrial applications. Attrition scrubbing and classification followed by magnetic separation are applied to remove the associated impurities. Attrition scrubbing and classification are used to separate the coarse silica and feldspars. Wet high intensity magnetic separation was applied to remove colored contaminants such as iron oxide and titanium oxide. Different variables affecting of magnetic separation process such as solid percent, magnetic field, matrix loading capacity, and retention time are studied. The results indicated that substantial decrease in iron oxide (from 1.69% to 0.61% ) and TiO2 (from 3.1% to 0.83%) contents as well as improving iso-brightness (from 63.76% to 75.21% and whiteness (from 79.85% to 86.72%) of the product can be achieved.

Keywords: Kaolin, titanoferrous minerals, beneficiation, magnetic separation, attrition scrubbing, classification

Procedia PDF Downloads 361
19470 Reed: An Approach Towards Quickly Bootstrapping Multilingual Acoustic Models

Authors: Bipasha Sen, Aditya Agarwal

Abstract:

Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

Procedia PDF Downloads 124
19469 Chassis Level Control Using Proportional Integrated Derivative Control, Fuzzy Logic and Deep Learning

Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

Abstract:

This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

Procedia PDF Downloads 82