Search results for: intermediate inputs

Authors: Balogun Azeez Olawale, Azeez S. A.

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Post occupancy evaluation (POE) is a process of assessing building performance for its users and intended function during the occupation. User satisfaction impacts the performance of educational environments and their users: students, faculty, and staff. In addition, buildings are maintained and managed by teams that spend a large amount of time and capital on their long-term sustenance. By evaluating the feedback from users of higher education facilities, university planning departments are more prepared to understand the inputs for programming and future project planning. In addition, university buildings will be closer to meeting user and maintenance needs. This paper reports on a research team made up of academics, facility personnel, and users that have developed a plan to improve the quality of campus facilities through a POE exercise on a recently built project. This study utilized a process of focus group interviews representing the different users and subsequent surveys. The paper demonstrates both the theory and practice of POE in higher education and learning environment through the case example of four universities in Nigeria's POE exercise.

Keywords: post occupancy evaluation, building performance, building analysis, building evaluation, quality control, building assessment, facility management, design quality

Procedia PDF Downloads 93

Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Jihene Bettaieb, Kaouther Ayouni, Ghassen Kharroubi, Rym Mallekh, Walid Hammemi, Afif Ben Salah, Henda Triki

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In Tunisia, the hepatitis A virus (HAV) represents a public health concern. Due to the progress in sanitation and socio-economic conditions, the epidemiology of HAV has shown dynamic changes over the past years. This study aimed to investigate the current seroprevalence of HAV antibodies (anti-HAV) among the residents of Thala, a rural setting in central-west Tunisia, to determine the age-specific seroprevalence for HAV infection and co-infection with hepatitis C and B virus. A total of 1379 subjects (mean age: 25.0 ± 17.3 years, 555 males/ 824 females) were recruited between January and June 2014. The study population included 95 individuals previously known as hepatitis C positive. Serum samples were collected and screened for the detection of IgG anti-HAV, HBsAg, and HBcAb by the Elisa Test. The overall anti- HAV seroprevalence was about 84.7%. There was no statistically significant difference between males and females. On the 1379 tested individual, 219 were positive for HBcAb, and 67 were positive for HBsAg. IgG anti- HAV were positive in 80.6% of HBsAg-positive patients (54 out of 67), 81.3% of HBcAb-positive patients (178 out of 219), and in 95.8% of HCV-positive patients (91 out of 95). HBV infection and HCV infection were statistically associated with a greater risk of positive anti-HAV antibody (p < 0.001). Our study revealed that Thala represents an intermediate endemicity level and that the introduction of vaccination against HAV in this region is recommended, especially for the hepatitis B or C infected person seronegative for HAV.

Keywords: coinfection, hepatitis A, seroprevalence, Tunisia

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Authors: Jane Aleksoski

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The mode of inheritance and heterotic effect were studied in ten F1 crosses obtained by one-way diallel crossing between five parental genotypes: MV-1, P 76/86, Adiyaman, Basma-Djebel, and P 66 9 7. The following quantitative traits were studied: the number of leaves per stalk, length of leaves from the middle belt of the stalk, and yield of green leaf mass per stalk and per hectare. The trial was set up in the experimental field of Scientific Tobacco Institute - Prilep, using a randomized block design with four replications in the period 2018-2019. Traditional cultural practices were applied during the growing season of tobacco in the field. The aim of this work was to study the mode of inheritance of the quantitative traits, to detect heterosis in the F1 generation, and to assess its economic viability. Analysis of variance determined statistically significant differences in traits between parents and their hybrids in the two-year investigation. The most common way of trait inheritance is partial-dominant, then intermediate. The negative heterotic effect on the number of leaves per stalk has P 76/86 x P 66 9 7. The hybrids MV-1 x Adiyaman, P 76/86 x Basma-Djebel, P 76/86 x P 66 9 7, and Basma-Djebel x P 66 9 7 have a positive heterotic effect on the length of the leaves. Oriental hybrids, where one of the parents is variety P 66 9 7, have positive heterosis in the yield of green leaf mass per stalk. The investigation provides very useful guidance for future successive selection activities.

Keywords: dominance, heterosis, inheritance, tobacco.

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Authors: Kevin D. Manalo, Jumelyn L. Torres, Noel B. Linsangan

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This paper focuses on a wireless myoelectric prosthesis of the upper-limb that uses a Multilayer Perceptron Neural network with back propagation. The algorithm is widely used in pattern recognition. The network can be used to train signals and be able to use it in performing a function on their own based on sample inputs. The paper makes use of the Neural Network in classifying the electromyography signal that is produced by the muscle in the amputee’s skin surface. The gathered data will be passed on through the Classification Stage wirelessly through Zigbee Technology. The signal will be classified and trained to be used in performing the arm positions in the prosthesis. Through programming using Verilog and using a Field Programmable Gate Array (FPGA) with Zigbee, the EMG signals will be acquired and will be used for classification. The classified signal is used to produce the corresponding Hand Movements (Open, Pick, Hold, and Grip) through the Zigbee controller. The data will then be processed through the MLP Neural Network using MATLAB which then be used for the surface myoelectric prosthesis. Z-test will be used to display the output acquired from using the neural network.

Keywords: field programmable gate array, multilayer perceptron neural network, verilog, zigbee

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Authors: Hesham A. Khalek, Shafik S. Khoury, Remon F. Aziz, Mohamed A. Hakam

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Slipforming operation’s linearity is a source of planning complications, and operation is usually subjected to bottlenecks at any point, so careful planning is required in order to achieve success. On the other hand, Discrete-event simulation concepts can be applied to simulate and analyze construction operations and to efficiently support construction scheduling. Nevertheless, preparation of input data for construction simulation is very challenging, time-consuming and human prone-error source. Therefore, to enhance the benefits of using DES in construction scheduling, this study proposes an integrated module to establish a framework for automating the generation of time schedules and decision support for Slipform construction projects, particularly through the project feasibility study phase by using data exchange between project data stored in an Intermediate database, DES and Scheduling software. Using the stored information, proposed system creates construction tasks attribute [e.g. activities durations, material quantities and resources amount], then DES uses all the given information to create a proposal for the construction schedule automatically. This research is considered a demonstration of a flexible Slipform project modeling, rapid scenario-based planning and schedule generation approach that may be of interest to both practitioners and researchers.

Keywords: discrete-event simulation, modeling, construction planning, data exchange, scheduling generation, EZstrobe

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Authors: D. C. Soares, J. T. S. Santos, D. G. Costa, A. K. S. Abud, T. P. Nunes, A. V. D. Figueiredo, A. M. de Oliveira Junior

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Mangabeira (Hancornia speciosa Gomes), a native plant in Brazil, is found growing spontaneously in various regions of the country. The high perishability of tropical fruits such as mangaba, causes it to be necessary to use technologies that promote conservation, aiming to increase the shelf life of this fruit and add value. The objective of this study was to compare the mangabas lyophilisation curves behaviours with different sizes and maturation stages. The fruits were freeze-dried for a period of approximately 45 hours at lyophilizer Liotop brand, model L -108. It has been considered large the fruits between 38 and 58 mm diameter and small, between 23 and 28 mm diameter and the two states of maturation, intermediate and mature. Large size mangabas drying curves in both states of maturation were linear behaviour at all process, while the kinetic drying curves related to small fruits, independent of maturation state, had a typical behaviour of drying, with all the well-defined steps. With these results it was noted that the time of lyophilisation was suitable for small mangabas, a fact that did not happen with the larger one. This may indicate that the large mangabas require a longer time to freeze until reaches the equilibrium level, as it happens with the small fruits, going to have constant moisture at the end of the process. For both types of fruit were analysed water activity, acidity, protein, lipid, and vitamin C before and after the process.

Keywords: freeze dryer, mangaba, conservation, chemical characteristics

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Authors: A. Soualem

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The design of multi stage deep drawing processes requires the evaluation of many process parameters such as the intermediate die geometry, the blank shape, the sheet thickness, the blank holder force, friction, lubrication etc..These process parameters have to be determined for the optimum forming conditions before the process design. In general sheet metal forming may involve stretching drawing or various combinations of these basic modes of deformation. It is important to determine the influence of the process variables in the design of sheet metal working process. Especially, the punch and die corner for deep drawing will affect the formability. At the same time the prediction of sheet metals springback after deep drawing is an important issue to solve for the control of manufacturing processes. Nowadays, the importance of this problem increases because of the use of steel sheeting with high stress and also aluminum alloys. The aim of this paper is to give a better understanding of the springback and its effect in various sheet metals forming process such as expansion and restraint deep drawing in the cup drawing process, by varying radius die, lubricant for two commercially available materials e.g. galvanized steel and Aluminum sheet. To achieve these goals experiments were carried out and compared with other results. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback.

Keywords: springback, deep drawing, expansion, restricted deep drawing

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Authors: Mohamed M. El-heweity, Ahmed Shamel Fahmy, Mostafa Shawky, Ahmed Sherif

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Cold-formed steel (CFS) lipped channel sections are popular as load-bearing members in building structures. These sections are used in the construction industry because of their high strength-to-weight ratio, lightweight, quick production, and ease of construction, fabrication, transportation, and handling. When those cold formed sections with high slenderness ratios are subjected to compression bending, they do not reach failure when reaching their ultimate bending stress, however, they sustain much higher loads due stress re-distribution. Hence, there is a need to study the sectional nominal capacity of CFS lipped channel beams with different web openings subjected to pure bending and uniformly distributed loads. By using finite element (FE) simulations using ANSYS APDL for numerical analysis. The results were verified and compared to previous experimental results. Then a parametric study was conducted and validated FE model to investigate the effect of different openings shapes on their nominal capacities. The results have revealed that CFS sections with hexagonal openings and intermediate notch can resist higher nominal capacities when compared to other sectional openings.

Keywords: cold-formed steel, nominal capacity, finite element, lipped channel beam, numerical study, web opening

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Authors: Z. Komeili, Sh. Abadikhah, H. Talebi

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Interaction and negotiation of meaning in the foreign language (FL) contexts are crucial to L2 development. Although research studies on children in EFL contexts have increased in recent years, the study of Iranian children negotiating meaning during their communicative task performance still needs further study. The purpose of this study was to investigate young EFL learners' interaction and negotiation of meaning (NoM) during task completion and examine the difference in meaning negotiation between the different proficiency levels and the association between the learners’ proficiency levels and their transfer of knowledge. The participants were twenty-eight young Iranian EFL learners forming 14 proficiency-matched dyads and were assigned into two different groups according to their proficiency levels. The dyads were asked to complete the collaborative task; their interaction was transcribed and analyzed in terms of their NoM. To test the transfer of knowledge to the subsequent performance, tailor-made tests were designed based on the NoM of each individual dyad. The results indicated a significant positive relationship between the learners’ level of proficiency and their transfer of knowledge to the subsequent performance. Our findings suggest that the elementary group had engaged in more negotiation of meaning compared to the intermediate group, and the higher the proficiency level, the better they performed in the post-test and benefited from the NoM. The study has some implications for researchers, teachers, and young learners.

Keywords: collaborative tasks, negotiation of meaning, proficiency levels, sociocultural theory, tailor-made test

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Authors: Jiaqi Yan, Yani Shi

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The blockchain technology is regarded as the most promising technology that has the potential to trigger a technological revolution. However, besides the bitcoin industry, we have not yet seen a large-scale application of blockchain in those domains that are supposed to be impacted, such as supply chain, financial network, and intelligent manufacturing. The reasons not only lie in the difficulties of blockchain implementation, but are also root in the challenges of blockchain-oriented information systems design. As the blockchain members are self-interest actors that belong to organizations with different existing information systems. As they expect different information inputs and outputs of the blockchain application, a common language protocol is needed to facilitate communications between blockchain members. Second, considering the decentralization of blockchain organization, there is not any central authority to organize and coordinate the business processes. Thus, the information systems built on blockchain should support more adaptive business process. This paper aims to address these difficulties by providing a modeling approach for blockchain-oriented information systems design. We will investigate the information structure of distributed-ledger data with conceptual modeling techniques and ontology theories, and build an effective ontology mapping method for the inter-organization information flow and blockchain information records. Further, we will study the distributed-ledger-ontology based business process modeling to support adaptive enterprise on blockchain.

Keywords: blockchain, ontology, information systems modeling, business process

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Authors: Ricardo Munguia-Perez, Nayeli Remigio-Alvarado, M.Miriam Hernandez-Arroyo, Elsa Castañeda-Roldan

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Fungi have emerged as important pathogens causing morbidity and mortality mainly in immunosuppressed, malnourished and elderly patients. It has detected an increase in resistance to azoles primarily to fluconazol. The fungal infections have become a problem of public health for the resistance to antifungal agents, they have developed new antifungals with broad-spectrum. The aim of this study was determine the antifungal susceptibility of yeasts isolated from clinical samples (respiratory secretions, exudates, wounds, blood cultures, urine cultures) obtained from inpatients and outpatients of a tertiary hospital from State of Puebla. The antifungal susceptibility of the yeast from several clinical samples were determined by the CLS M44-A disk diffusion methods. 149 samples of yeast were analyzed. All species were 100% susceptible to nystatin and amphotericin B. Candida albicans showed resistance of 95.5 % to fluconazole, 50.7 % to 5-flurocytosine and 55.2 % intermediate susceptibility to ketoconazole. Candida glabrata 81.3 % was susceptibility to ketoconazole and 75 % to fluconazole, for the case of 5-flurocytosine the 56.3 % was susceptible. Candida krusei 100 % was susceptible to ketoconazole, 50 % to fluconazole and 37.5 % to 5-flurocytosine. The internal medicine have greater diversity of yeast, the samples have susceptibility of 64.7% to ketoconazole, 47.1 % to fluconazole and 27.5 % to 5-flurocytosine. Hospitalized patients are more resistant to fluconazole and nystatin, but in the case of outpatients presents resistance to ketoconazole.

Keywords: antifungal, susceptibility, yeast, clinical samples

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Sai Sudarshan, Harsh Vyas, Riddhiman Sherlekar

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The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software.

Keywords: simulation, probability, confidence interval, sensitivity analysis

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Authors: Chanya Inprasit, Yi-Wen Lin

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Motion sickness (MS) is an acute disorder that occurs in healthy persons without considering gender, age or ethnicity worldwide. All signs and symptoms of MS are the results of confliction and mismatch among neural signal inputs. It is known that no singular remedy works for everybody, and electroacupuncture (EA) is one of the popular alternative therapies used for MS. Our study utilized a mouse model in order to exclude any psychological factors of MS and EA. Mice lack an emetic reflex. Therefore pica behavior, which is a normal consumption of non-nutritive substances, was found to measure the response of MS in mice. In the laboratory, Kaolin was used as a non-nutrient food substance instead of natural substances lacking nutritional value such as wood, cloth, charcoal, soil or grass. It was hypothesized that EA treatment could reduce the symptoms of MS through the TRPV1 pathways. The results of pica behavior showed a significantly increased intake of kaolin in the MS group throughout the experiment period. Moreover, the Kaolin intake of the EA group decreased to the average baseline of the control group. There was no recorded difference in the food and water intake of each group. The results indicated an increase of the TRPV1, pERK, pJNK and pmTOR protein levels in the thalamus after MS stimulation, and a significant decrease in the EA group compared with that of the control group. These findings suggest that TRPV1 pathways are associated in MS mechanisms and can be reduced by EA.

Keywords: electroacupuncture, motion sickness, Thalamus, TRPV1

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Authors: Mohamed Amine Helali, Walid Oueslati, Ayed Added

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Sedimentation rates and total fluxes of heavy metals (Fe, Mn, Pb, Zn and Cu) was measured in three different depths (10m, 20m and 40m) during March and August 2012, offshore of the Mejerda River outlet (Gulf of Tunis, Tunisia). The sedimentation rates are estimated from the fluxes of the suspended particulate matter at 7.32, 5.45 and 4.39 mm y⁻¹ respectively at 10m, 20m and 40m depth. Heavy metals sequestration in sediments was determined by chemical speciation and the total metal contents in each core collected from 10, 20 and 40m depth. Heavy metals intake to the sediment was measured also from the suspended particulate matter, while the fluxes from the sediment to the water column was determined using the benthic chambers technique and from the diffusive fluxes in the pore water. Results shown that iron is the only metal for which the balance transfer between intake/uptake (45 to 117 / 1.8 to 5.8 g m² y⁻¹) and sequestration (277 to 378 g m² y⁻¹) was negative, at the opposite of the Lead which intake fluxes (360 to 480 mg m² y⁻¹) are more than sequestration fluxes (50 to 92 mg m² y⁻¹). The balance transfer is neutral for Mn, Zn, and Cu. These clearly indicate that the contributions of Mejerda have consistently varied over time, probably due to the migration of the River mouth and to the changes in the mining activity in the Mejerda catchment and the recent human activities which affect the delta area.

Keywords: delta, fluxes, heavy metals, sediments, sedimentation rates

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Authors: Naso Isaiah Thanavisuth

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Medical cannabis can be used for treatment including pain, multiple sclerosis, Parkinson's disease, and cancer. However, medical cannabis leads to adverse effects (AEs), which is delta-9-tetrahydrocannabinol (THC). In previous studies, the major of THC metabolism enzymes are CYP2C9. Especially, the variation of CYP2C9 gene consist of CYP2C9*2 on exon 3 and CYP2C9*3 on exon 7 to decrease enzyme activity. Notwithstanding, there is no data describing whether the variant of CYP2C9 genes are apharmacogenetics marker for the prediction of THC-induced AEs in Thai patients. We want to investigate the association between CYP2C9 gene and THC-induced AEs in Thai patients. We enrolled 39 Thai patients with medical cannabis treatment who were classified by clinical data. The CYP2C9*2 and *3 genotyping were conducted using the TaqMan real time PCR assay. All Thai patients who received the medical cannabis consist of twenty-four (61.54%) patients were female, and fifteen (38.46%) were male, with age range 27- 87 years. Moreover, the most AEs in Thai patients who were treated with medical cannabis between cases and controls were tachycardia, arrhythmia, dry mouth, and nausea. Particularly, thirteen (72.22%) medical cannabis-induced AEs were female and age range 33 – 69 years. In this study, none of the medical cannabis groups carried CYP2C9*2 variants in Thai patients. The CYP2C9*3 variants (*1/*3, intermediate metabolizer, IM) and (*3/*3, poor metabolizer, PM) were found, three of thirty-nine (7.69%) and one of thirty-nine (2.56%), respectively. Although, our results indicate that there is no found the CYP2C9*2. However, the variation of CYP2C9 allele might serve as a pharmacogenetics marker for screening before initiating the therapy with medical cannabis for the prevention of medical cannabis-induced AEs.

Keywords: CYP2C9, medical cannabis, adverse effects, THC, P450

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Bin Bian, Liang Wang

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A hydraulic spherical motion mechanism (HSMM) is proposed. Unlike traditional systems using serial or parallel mechanisms for multi-DOF rotations, the HSMM is capable of implementing continuous 2-DOF rotational motions in a single joint without the intermediate transmission mechanisms. It has some advantages of compact structure, low inertia and high stiffness. However, as HSMM is a nonlinear and multivariable system, it is very complicate to realize accuracy control. Therefore, an augmented active disturbance rejection controller (ADRC) is proposed in this paper. Compared with the traditional PD control method, three compensation items, i.e., dynamics compensation term, disturbance compensation term and nonlinear error elimination term, are added into the proposed algorithm to improve the control performance. The ADRC algorithm aims at offsetting the effects of external disturbance and realizing accurate control. Euler angles are applied to describe the orientation of rotor. Lagrange equations are utilized to establish the dynamic model of the HSMM. The stability of this algorithm is validated with detailed derivation. Simulation model is formulated in Matlab/Simulink. The results show that the proposed control algorithm has better competence of trajectory tracking in the presence of uncertainties.

Keywords: hydraulic spherical motion mechanism, dynamic model, active disturbance rejection control, trajectory tracking

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

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Authors: Burak Bal

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Mechanical characterization tests might come with a remarkable cost of time and money for both companies and academics. The inquiry to transform laboratory experiments to the computational media is getting a trend; accordingly, the literature supplies many analytical ways to explain the mechanics of deformation. In our work, we focused on the crystal plasticity finite element modeling (CPFEM) analysis on various materials in various crystal structures to predict the stress-strain curve without tensile tests. For FEM analysis, which we used in this study was ABAQUS, a standard user-defined material subroutine (UMAT) was prepared. The geometry of a specimen was created via DREAM 3D software with the inputs of Euler angles taken by Electron Back-Scattered Diffraction (EBSD) technique as orientation, or misorientation angles. The synthetic crystal created with DREAM 3D is also meshed in a way the grains inside the crystal meshed separately, and the computer can realize interaction of inter, and intra grain structures. The mechanical deformation parameters obtained from the literature put into the Fortran based UMAT code to describe how material will response to the load applied from specific direction. The mechanical response of a synthetic crystal created with DREAM 3D agrees well with the material response in the literature.

Keywords: crystal plasticity finite element modeling, ABAQUS, Dream.3D, microstructure

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: M. Gobinath, S. Balaji

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Assumptions in model inputs: Grade of concrete=40 N/mm2 (for slab), Grade of concrete=40 N/mm2 (for shear wall), Grade of Structural steel (plate girder)=350 N/mm2 (yield strength), Ultimate strength of structural steel=490 N/mm2, Grade of rebar=500 N/mm2 (yield strength), Applied Load=1716 kN (un-factored). Following assumptions are made for the mathematical modelling of RCC with steel embedment: (1) The bond between the structural steel and concrete is neglected. (2) The stiffener is provided with shear studs to transfer the shear force. Hence nodal connectivity is established between solid nodes (concrete) and shell elements (stiffener) at those locations. (3) As the end reinforcements transfer either tension/compression, it is modeled as line element and connected to solid nodes. (4) In order to capture the bearing of bottom flange on to the concrete, the line element of plan size of solid equal to the cross section of line elements is connected between solid and shell elements below for bottom flange and above for top flange. (5) As the concrete cannot resist tension at the interface (i.e., between structural steel and RCC), the tensile stiffness is assigned as zero and only compressive stiffness is enabled to take. Hence, non-linear static analysis option is invoked.

Keywords: structure, construction, signature tower, embedment design concept

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Christelle Tchoupé Makougoum

Abstract:

In the context of agriculture, differences across localities in term of climate change can create systematic variation among farmers technical efficiency. Failure to account for climate variability could lead to wrong conclusions about farmers’ technical efficiency and also it could bias the ranking of farmers according to their managerial performance. The literature on agricultural productivity has given little attention to this issue whereas it is necessary for establishing to what extent climate affects farmers efficiency. This article contributes to the preview literature by two ways. First, it proposed a new econometric model that accounting for the climate change influences on technical efficiency in the specific area of agriculture. Second it estimates the inefficiency due to climate change and the real managerial performance of Malian farmers. Using the Mali’s data from agricultural census and CRU TS3 climatic database we implemented an adjusted stochastic frontier methodology to account for the impact of environmental factors. The results yield three main findings. First, instability in temperatures and rainfall decreases technical efficiency on average. Second, the climate change modifies the classification of the farmers according to their efficiency scores. Thirdly it is noted that, although climate changes are partly responsible for the deviation from the border, the capacity of farmers to combine inputs into the optimal proportion is more to undermine. The study concluded that improving farmer efficiency should include fostering their resilience to climate change.

Keywords: agriculture, climate change, stochastic production function, technical efficiency

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Authors: Kevin Anderson, Sukhwinder Singh Sandhu, Nouh Anies, Shilpa Ravichandra, Steven Dobbs, Donald Edberg

Abstract:

This paper presents the results of a Finite Element based vibration analysis of a solar powered Unmanned Aerial Vehicle (UAV). The purpose of this paper was to quantify the free vibration, forced vibration response due to differing point inputs in order to mimic the vibration induced by actuators (magnet in coil generators) used to aid in the flight of the UAV. A Fluid-Structure Interaction (FSI) study was performed in order to ascertain pertinent deigns stresses and deflections as well as aerodynamic parameters of the UAV airfoil. The 10 ft span airfoil is modeled using Mylar as the primary material. Results show that the free mode in bending is 4.8 Hz while the first forced bending mode is in the range of 16.2 to 16.7 Hz depending on the location of excitation. The free torsional bending mode is 28.3 Hz, and the first forced torsional mode is in the range of 26.4 to 27.8 Hz, depending on the location of excitation. The FSI results predict the coefficients of aerodynamic drag and lift of 0.0052 and 0.077, respectively, which matches hand-calculations used to validate the Finite Element based results. FSI based maximum von Mises stresses and deflections were found to be 0.282 MPa and 3.4 mm, respectively. Dynamic pressures on the airfoil range of 1.04 to 1.23 kPa corresponding to velocity magnitudes in the range of 22 to 66 m/s.

Keywords: ANSYS, finite element, FSI, UAV, vibrations

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Authors: Masoud Safarishaal

Abstract:

Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, Alfred V. Gborie

Abstract:

The goal of this study was to increase the awareness of the description and assessments of rice acreage response and to offer mechanisms for agricultural policy scrutiny. The Ordinary Least Square (OLS) technique was utilized to determine the coefficients of acreage response models for the rice varieties. The magnitudes of the coefficients (λ) of both the ROK lagged and NERICA lagged acreages were found positive and highly significant, which indicates that farmers’ adjustment rate was very low. Regarding lagged actual price for both the ROK and NERICE rice varieties, the short-run price elasticities were lower than long-run, which is suggesting a long-term adjustment of the acreage, is under the crop. However, the apparent recommendations for policy transformation are to open farm gate prices and to decrease government’s involvement in agricultural sector especially in the acquisition of agricultural inputs. Impending research have to be centred on how this might be better realized. Necessary conditions should be made available to the private sector by means of minimizing price volatility. In accordance with structural reforms, it is necessary to convey output prices to farmers with minimum distortion. There is a need to eradicate price subsidies and control, which generate distortion in the market in addition to huge financial costs.

Keywords: acreage response, rate of adjustment, rice varieties, Sierra Leone

Procedia PDF Downloads 307

Authors: Quan Li, Dongcai Shen, Zhengting Xiao, Xin Liu Mingrui Wu, Licheng Liu, Qin Li, Xianguo Li, Wentai Wang

Abstract:

Direct electrocatalytic nitrogen oxidation (NOR) provides a promising alternative strategy for synthesizing high-value-added nitric acid from widespread N₂, which overcomes the disadvantages of the Haber-Bosch-Ostwald process. However, the NOR process suffers from the limitation of high N≡N bonding energy (941 kJ mol− ¹), sluggish kinetics, low efficiency and yield. It is a prerequisite to develop more efficient electrocatalysts for NOR. Herein, we synthesized double-shelled CeO₂ hollow spheres (D-CeO₂) and further modified with Ti₃C₂ MXene quantum dots (MQDs) for electrocatalytic N₂ oxidation, which exhibited a NO₃− yield of 71.25 μg h− ¹ mgcat− ¹ and FE of 31.80% at 1.7 V. The unique quantum size effect and abundant edge active sites lead to a more effective capture of nitrogen. Moreover, the double-shelled hollow structure is favorable for N₂ fixation and gathers intermediate products in the interlayer of the core-shell. The in-situ infrared Fourier transform spectroscopy confirmed the formation of *NO and NO₃− species during the NOR reaction, and the kinetics and possible pathways of NOR were calculated by density functional theory (DFT). In addition, a Zn-N₂ reaction device was assembled with D-CeO₂/MQDs as anode and Zn plate as cathode, obtaining an extremely high NO₃− yield of 104.57 μg h− ¹ mgcat− ¹ at 1 mA cm− ².

Keywords: electrocatalytic N₂ oxidation, nitrate production, CeO₂, MXene quantum dots, double-shelled hollow spheres

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Authors: Sai Rajeev Reddy, Ishita Roy, M. Anji Reddy

Abstract:

The paper describes the importance of preventive measures and immediate Emergency logistics during accidents and unfortunate Disasters for the Hyderabad Metro Rails in their various stages of construction. This is the need of the modern generation where accidents, explosions, attacks and sudden crisis are frequent casualties which take huge tolls of life in the present world. The paper utilizes the workflow and application of Geographical information System (GIS) to provide information about problems and crisis structures for efficient Metro Transportation in the city. The study analyzes the difficulties and problems which cause accidents during operation and maintenance stages of the Metro Rail. The paper focuses upon the intermediate and firsthand information of Crisis with the help of GIS technology to share Disaster data for effective measures by the Cyber Police stations, Emergency Responders, Hospitals and First Aid Centre to act immediately and save lives. The results and conclusions have nevertheless proved very informative and useful for the safety board authorities of the Hyderabad Metro Rail. The operation and Maintenance are integral stages in the development of any Multipurpose transportation Projects and are usually prone to various Disasters and tragedies. Hence, the GIS technologies help in distribution of information among the masses with the web Technologies and advanced software developed to prevent and manage crisis widely and in a cost-benefits manner.

Keywords: Geographical Information System, emergency assessment, accident zones, surveillance

Procedia PDF Downloads 552