Search results for: cost prediction

Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: adult, basal metabolic rate, fao/who/unu, obesity, prediction equations

Procedia PDF Downloads 136

Authors: Wabinyai Fidel Raja, Gideon Lubisa

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Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.

Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management

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Authors: Fatemeh Sadat Sharifi

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In this research, a barotropic model was employed to consider the tidal studies in the Persian Gulf and Oman Sea, where the only sufficient force was the tidal force. To do that, a finite-difference, free-surface model called Regional Ocean Modeling System (ROMS), was employed on the data over the Persian Gulf and Oman Sea. To analyze flow patterns of the region, the results of limited size model of The Finite Volume Community Ocean Model (FVCOM) were appropriated. The two points were determined since both are one of the most critical water body in case of the economy, biology, fishery, Shipping, navigation, and petroleum extraction. The OSU Tidal Prediction Software (OTPS) tide and observation data validated the modeled result. Next, tidal elevation and speed, and tidal analysis were interpreted. Preliminary results determine a significant accuracy in the tidal height compared with observation and OTPS data, declaring that tidal currents are highest in Hormuz Strait and the narrow and shallow region between Iranian coasts and Islands. Furthermore, tidal analysis clarifies that the M_2 component has the most significant value. Finally, the Persian Gulf tidal currents are divided into two branches: the first branch converts from south to Qatar and via United Arab Emirate rotates to Hormuz Strait. The secondary branch, in north and west, extends up to the highest point in the Persian Gulf and in the head of Gulf turns counterclockwise.

Keywords: numerical model, barotropic tide, tidal currents, OSU tidal prediction software, OTPS

Procedia PDF Downloads 136

Authors: O. Nkwonta, B. Dzwairo, F. Otieno, J. Adeyemo

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The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective, management

Procedia PDF Downloads 455

Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

Procedia PDF Downloads 112

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

Procedia PDF Downloads 155

Authors: Sh. Wafa, M. Alanoud, S. Liyakathunisa

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Online booking for a trip or hotel has become an indispensable traveling tool today, people tend to be more interested in selecting air flight travel as their first choice when going for a long trip. People's shopping behavior has greatly changed by the advent of social network. Traditional ticket booking methods are considered as outdated with the advancement in tools and technology. Web based booking framework is an 'absolute necessity to have' for any visit or movement business that is investing heaps of energy noting telephone calls, sending messages or considering employing more staff. In this paper, we propose a process model for online trip reservation for our designed web application. Our proposed system will be highly beneficial and helps in reduction in time and cost for customers.

Keywords: trip, hotel, reservation, process model, time, cost, web app

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Authors: Darwin Castillo Huamaní, Francisco A. M. Gomes

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The aim of the multi-material topology optimization (MTO) is to obtain the optimal topology of structures composed by many materials, according to a given set of constraints and cost criteria. In this work, we seek the optimal distribution of materials in a domain, such that the flexibility of the structure is minimized, under certain boundary conditions and the intervention of external forces. In the case we have only one material, each point of the discretized domain is represented by two values from a function, where the value of the function is 1 if the element belongs to the structure or 0 if the element is empty. A common way to avoid the high computational cost of solving integer variable optimization problems is to adopt the Solid Isotropic Material with Penalization (SIMP) method. This method relies on the continuous interpolation function, power function, where the base variable represents a pseudo density at each point of domain. For proper exponent values, the SIMP method reduces intermediate densities, since values other than 0 or 1 usually does not have a physical meaning for the problem. Several extension of the SIMP method were proposed for the multi-material case. The one that we explore here is the ordered SIMP method, that has the advantage of not being based on the addition of variables to represent material selection, so the computational cost is independent of the number of materials considered. Although the number of variables is not increased by this algorithm, the optimization subproblems that are generated at each iteration cannot be solved by methods that rely on second derivatives, due to the cost of calculating the second derivatives. To overcome this, we apply a globally convergent version of the sequential linear programming method, which solves a linear approximation sequence of optimization problems.

Keywords: globally convergence, multi-material design ordered simp, sequential linear programming, topology optimization

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Authors: Pedram Khazaie, Sajjad Moein

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In the conventional hot forging of Tongue, which is a fitting for polymer insulator, the material wasted to flash accounts for 20-30% of workpiece. In order to reduce the cost of forged products, this waste material must be minimized. In this study, a flashless forging die is designed and simulated using the finite element method (FEM). A solution to avoid overloading the die with a simple preform is also presented. Moreover, since in flashless forging, burr is formed on the edge of workpiece, a controlled flash forging method is proposed to solve this problem. The simulation results have been validated by experiments; achieving close agreement between simulated and experimental data. It was shown that numerical modeling is helpful in reducing cost and time in the manufacturing process.

Keywords: burr formation, die design, finite element method, flashless forging

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Kwong Yeung

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Theories about strategic purchasing and quality performance are underdeveloped. Understanding the evolving role of purchasing from reactive to proactive is a pressing strategic issue. Using survey responses from 176 manufacturing and electronics industry professionals, we study the relationships between strategic purchasing and supply chain partners’ quality performance to answer the following questions: Can transaction cost economics be used to elucidate the strategic purchasing-quality performance relationship? Is this strategic purchasing-quality performance relationship moderated by critical item analysis? The findings indicate that critical item analysis positively and significantly moderates the strategic purchasing-quality performance relationship.

Keywords: critical item analysis, moderation, quality performance, strategic purchasing, transaction cost economics

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Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Obsi Terfasa, Bhanupriya Das, Mithilish Passawan

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The large-scale application of microbial fuel cell (MFC) technology is significantly hindered by the high cost of the commonly used proton exchange membrane, Nafion. This has led to the recent development of ceramic membranes using various clay minerals. This study evaluates the characteristics and potential use of a new ceramic membrane made from potter’s clay © mixed with different proportions (0, 5, 10 wt%) of fly ash (FA), labeled as CFA0, CFA5, CFA10, for cost-effective and sustainable MFC use. Among these, the CFA10 membrane demonstrated superior quality with a fine pore size distribution (average 0.41 μm), which supports higher water uptake and reduced oxygen diffusion. Its oxygen mass transfer coefficient was 4.13 ± 0.13 × 10⁻⁴ cm/s, about 40% lower than the control. X-ray diffraction analysis revealed that the CFA membrane is rich in quartz, which enhances proton conductance and water retention. Electrochemical kinetics studies, including cyclic voltammetry and electrochemical impedance spectroscopy (EIS), also confirmed the effectiveness of the CFA10 membrane in MFC, showing a peak current output of 15.35 mA and low ohmic resistance (78.2 Ω). The novel CFA10 ceramic membrane, incorporating coal fly ash, a waste material, shows promise for high MFC performance at a significantly reduced cost (96%), making it suitable for sustainable scaling up of the technology.

Keywords: ceramic membrane, Coulombic efficiency, electro-chemical kinetics, fly ash, proton conductivity, microbial fuel cell

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Authors: Xin Chang, Daping Chu

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Oxygen gas sensing technology has progressed since the last century and it has been extensively used in a wide range of applications such as controlling the combustion process by sensing the oxygen level in the exhaust gas of automobiles to ensure the catalytic converter is in a good working condition. Similar sensors are also used in industrial boilers to make the combustion process economic and environmentally friendly. Different gas sensing mechanisms have been developed: ceramic-based potentiometric equilibrium sensors and semiconductor-based sensors by oxygen absorption. In this work, we present a highly sensitive and low-cost oxygen gas sensor based on Zinc Oxide nanoparticles (average particle size of 35nm) dispersion in ethanol. The sensor is able to measure the pressure range from 103 mBar to 10-5 mBar with a sensitivity of more than 102 mA/Bar. The sensor is also erasable with heat.

Keywords: nanoparticles, oxygen, sensor, ZnO

Procedia PDF Downloads 141

Authors: Gabriella Fardhiyanti, Victor Wee

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Air connectivity is the crucial factors to boost a region economics growth. It will open the accessibility to support regional competitiveness and helps to achieve ASEAN (Association of Southeast Asian Nations) integration in term of economic integration, business investment, promote intra-regional trade, and creates the sense of belongingness among ASEAN people in the region. An increasing number of air connectivity and transportation will be benefiting the region because air transportation is a vital hub for ASEAN. The aim of this paper is to address the importance of air connectivity in promoting ASEAN Integration, by focusing on the ASEAN vision for a more integrated region. The assessment uses based on the Netscan Air connectivity model based on the flight destination and airport connectivity index, further analysis present that air connectivity significantly influence ASEAN tourism sector. Follow by the implications of open skies policy for the liberation of the aviation industry and the growth of low cost-carriers (LCCs) in the region. This paper provides recommendation and strategy for overcoming the challenges faced by ASEAN to boost ASEAN tourism integration successfully. The findings can assist in guiding policy and industry stakeholders in the future decision relating to air liberalization and more integrated system in the region.

Keywords: air connectivity, ASEAN integration, low-cost carries, NetScan connectivity model, open skies policy

Procedia PDF Downloads 219

Authors: M. Pallikonda Rajasekaran, J. Joshapath, Abhishek Prasad Shaw

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Various techniques has been employed to find location such as GPS, GLONASS, Galileo, and Beidou (compass). This paper currently deals with finding location using the existing FM signals that operates between 88-108 MHz. The location can be determined based on the received signal strength of nearby existing FM stations by mapping the signal strength values using trilateration concept. Thus providing security to users data and maintains eco-friendly environment at zero installation cost as this technology already existing FM stations operating in commercial FM band 88-108 MHZ. Along with the signal strength based trilateration it also finds azimuthal angle of the transmitter by employing directional antenna like Yagi-Uda antenna at the receiver side.

Keywords: location, existing FM signals, received signal strength, trilateration, security, eco-friendly, direction, privacy, zero installation cost

Procedia PDF Downloads 525

Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

Procedia PDF Downloads 384

Authors: Mohammed N. Al Kindi, Mazin Al Khabouri, Khalsa Al Lamki, Tommasso Pappuci, Giovani Romeo, Nadia Al Wardy

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Hereditary hearing loss is a heterogeneous group of complex disorders with an overall incidence of one in every five hundred newborns presented as syndromic and non-syndromic forms. Cadherin-related 23 (CDH23) is one of the listed deafness causative genes. CDH23 is found to be expressed in the stereocilia of hair cells and the retina photoreceptor cells. Defective CDH23 has been associated mostly with prelingual severe-to-profound sensorineural hearing loss (SNHL) in either syndromic (USH1D) or non-syndromic SNHL (DFNB12). An Omani family diagnosed clinically with severe-profound sensorineural hearing loss was genetically analysed by whole exome sequencing technique. A novel homozygous missense variant, c.A7451C (p.D2484A), in exon 53 of CDH23 was detected. One hundred and thirty control samples were analysed where all were negative for the detected variant. The variant was analysed in silico for pathogenicity verification using several mutation prediction software. The variant proved to be a pathogenic mutation and is reported for the first time in Oman and worldwide. It is concluded that in silico mutation prediction analysis might be used as a useful molecular diagnostics tool benefiting both genetic counseling and mutation verification. The aspartic acid 2484 alanine missense substitution might be the main disease-causing mutation that damages CDH23 function and could be used as a genetic hearing loss marker for this particular Omani family.

Keywords: Cdh23, d2484a, in silico, Oman

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Authors: Henry Okoh, Obaro Verisa Omayuli, Gladys A. Osagie

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One of the challenges of developing nations is the dearth of measurement devices. Aside the shortage, when available, they are either old or obsolete and also very expensive. When this is the situation, researchers must design alternative systems to help meet the desired needs of academia. This paper presents a design of cost-effective multi-disciplinary virtual instrument system for scientific research. This design was based on NI USB-6255 multifunctional DAQ which was used for earth resistivity measurement in Schlumberger array and the result obtained compared closely with that of a conventional ABEM Terrameter. This instrument design provided a hands-on experience as related to full-waveform signal acquisition in the field.

Keywords: cost-effective, data acquisition (DAQ), full-waveform, multi-disciplinary, Schlumberger array, virtual Instrumentation (VI).

Procedia PDF Downloads 474

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Talat Baran

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Palladium-catalyzed Suzuki coupling reactions are powerful ways for synthesis of biaryls compounds and so far different palladium sources as have been used in catalyst systems. However, the high cost of the ligands using as support materials for palladium ion and so researchers have explored alternative low-cost support materials such as silica, cellule and zeolite. A natural polymer chitosan is suitable for support material because of it unique properties such as eco-friendly, renewable, abundant, low cost, biodegradable and it has free reactive -NH2 and –OH groups. Especially, pendant amino groups of chitosan can easily react with carbonyl groups of aldehyde or ketone by Schiff base formation and thus palladium ions can coordinate with imine groups of Schiff base. This purpose, in this study, firstly a new chitosan Schiff base supported palladium (II) catalyst was synthesized and its chemical structure was characterized with FT-IR, SEM/EDAX, XRD, TG-DTG, ICP-OES and magnetic moment techniques. Then catalytic performance of the catalyst was investigated in Suzuki cross coupling reactions under simple and fast microwave heating methods. Also, recycle activity of palladium catalyst was tested under optimum condition and the catalyst showed long life time. At the end of catalytic performance tests of chitosan supported palladium (II) catalysts indicated high turnover numbers, turnover frequency and selectivity with very small loading catalyst

Keywords: catalyst, chitosan, Schiff base, Suzuki coupling

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Authors: Prof. Ammal Mokhtar Metwally, Samia M. Sami, Nihad A. Ibrahim, Fatma A. Shaaban, Iman I. Salama

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Objectives: Reducing neonatal mortality by 2030 is still a challenging goal in developing countries. low birth weight (LBW) is a significant contributor to this, especially where weighing newborns is not possible routinely. The present study aimed to determine a simple, easy, reliable anthropometric measure(s) that can predict LBW) and neonatal mortality. Methods: A prospective cohort study of 570 babies born in districts of El Menia governorate, Egypt (where most deliveries occurred at home) was examined at birth. Newborn weight, length, head, chest, mid-arm, and thigh circumferences were measured. Follow up of the examined neonates took place during their first four weeks of life to report any mortalities. The most predictable anthropometric measures were determined using the statistical package of SPSS, and multiple Logistic regression analysis was performed.: Results: Head and chest circumferences with cut-off points < 33 cm and ≤ 31.5 cm, respectively, were the significant predictors for LBW. They carried the best combination of having the highest sensitivity (89.8 % & 86.4 %) and least false negative predictive value (1.4 % & 1.7 %). Chest circumference with a cut-off point ≤ 31.5 cm was the significant predictor for neonatal mortality with 83.3 % sensitivity and 0.43 % false negative predictive value. Conclusion: Using chest circumference with a cut-off point ≤ 31.5 cm is recommended as a single simple anthropometric measurement for the prediction of both LBW and neonatal mortality. The predicted measure could act as a substitute for weighting newborns in communities where scales to weigh them are not routinely available.

Keywords: low birth weight, neonatal mortality, anthropometric measures, practical screening

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Authors: Charawee Butbumrung

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The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation

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Authors: Hans Frenk, Sonya Javadi, Semih Onur Sezer

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We consider the so-called end of life inventory problem for the supplier of a product in its final phase of the service life cycle. This phase starts when the production of the items stops and continues until the warranty of the last sold item expires. At the beginning of this phase, the supplier places a final order for spare parts to serve customers coming with defective items. At any time during the final phase, the supplier may also decide to switch to an alternative and more cost-effective policy. This alternative policy may be in the form of replacing a defective item with a substitutable product or offering discounts / rebates on new generation products. In this setup, the objective is to find a final order quantity and also a switching time which will minimize the total expected discounted cost. We study this problem under a general cost structure in a continuous-time framework where arrivals of defective items are given by a non-homogeneous Poisson process. We consider four formulations which differ by the nature of the switching time. These formulations are studied in detail and properties of the objective function are derived in each case. Using these properties, we provide exact algorithms for efficient numerical implementations. Numerical examples are provided illustrating the application of these algorithms. In these examples, we also compare the costs associated with these different formulations.

Keywords: End-of-life inventory control, martingales, optimization, service parts

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Authors: Ramin Rezaei, Terry Ng, Abdollah Afjeh

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Near wake development of a wind turbine affects the aerodynamic loads on the tower and the wind turbine. Design considerations of both isolated wind turbines and wind farms must include unsteady wake flow conditions under which the turbines must operate. The consequent aerodynamic loads could lead to over design of wind turbines and adversely affect the cost of wind turbines and, in turn, the cost of energy produced by wind turbines. Reducing the weight of turbine rotors is particularly desirable since larger wind turbine rotors can be utilized without significantly increasing the cost of the supporting structure. Larger rotor diameters produce larger swept areas and consequently greater energy production from the wind thereby reducing the levelized cost of wind energy. To understand the development and structure of the near tower wake of a wind turbine, an experimental study was conducted to describe the flow field of the near wake for both upwind and downwind turbines. The study was conducted under controlled environment of a wind tunnel using a scaled model of a turbine. The NREL 5 MW reference wind turbine was used as a baseline design and was modified as necessary to design and build upwind and downwind scaled wind turbine models. This paper presents the results of the wind tunnel study using turbine models to quantify the near wake of upwind and downwind wind turbine configurations for various lengths of tower-to-turbine spacing. The variations of mean velocity and turbulence are measured using a computer-controlled, traversing hot wire probe. Additionally, smoke flow visualizations were conducted to qualitatively study the wake. The results show a more rapid dissipation of the near wake for an upwind configuration. The results can readily be incorporated into low fidelity system level turbine simulation tools to more accurately account for the wake on the aerodynamic loads of a upwind and downwind turbines.

Keywords: hot wire anemometry, near wake, upwind and downwind turbine. Hot wire anemometry, near wake, upwind and downwind turbine

Procedia PDF Downloads 671

Authors: Nur Sahver Uslu, Ali̇ Hakan Büyüklü

Abstract:

Maintenance, Repair, and Overhaul (MRO) costs are significant in the aviation industry. On the other hand, companies that provide MRO services to the aviation industry but are not dominant in the sector, need to determine the right strategies for sustainable profitability in a competitive environment. This study examined the operational real data of a small medium enterprise (SME) MRO company where analytical methods are not widely applied. The company's customers were divided into two categories: airline companies and non-airline companies, and the variables that best explained profitability were analyzed with Logistic Regression for each category and the results were compared. First, data reduction was applied to the transformed variables that went through the data cleaning and preparation stages, and the variables to be included in the model were decided. The misclassification rates for the logistic regression results concerning both customer categories are similar, indicating consistent model performance across different segments. Less profit margin is obtained from airline customers, which can be explained by the variables part description, time to quotation (TTQ), turnaround time (TAT), manager, part cost, and labour cost. The higher profit margin obtained from non-airline customers is explained only by the variables part description, part cost, and labour cost. Based on the two models, it can be stated that it is significantly more challenging for the MRO company, which is the subject of our study, to achieve profitability from Airline customers. While operational processes and organizational structure also affect the profit from airline customers, only the type of parts and costs determine the profit for non-airlines.

Keywords: aircraft, aircraft components, aviation, data analytics, data science, gini index, maintenance, repair, and overhaul, MRO, logistic regression, profit, variable clustering, variable reduction

Procedia PDF Downloads 41

Authors: Vinay Singh, Chandra Deo, Asit Chakrabarti, Lopamudra Sahoo, Mahak Singh, Rakesh Kumar, Dinesh Kumar, H. Bharati, Biswajit Das, V. K. Mishra

Abstract:

The most widely used feed resources in poultry feed, like maize and soybean, are expensive as well as in short supply. Hence, there is a need to utilize non-conventional feed ingredients to cut down feed costs. As an alternative, brewery by-products like brewers’ dried grains are potential non-conventional feed resources. North-East India is inhabited by many tribes, and most of these tribes prepare their indigenous local brew, mostly using rice grains as the primary substrate. Choak, a homemade rice beer waste, is an excellent and cheap source of protein and other nutrients. Fresh homemade rice beer waste (rice brewer’s grain) was collected locally. The proximate analysis indicated 28.53% crude protein, 92.76% dry matter, 5.02% ether extract, 7.83% crude fibre, 2.85% total ash, 0.67% acid insoluble ash, 0.91% calcium, and 0.55% total phosphorus. A feeding trial with 5 treatments (incorporating rice beer waste at the inclusion levels of 0,10,20,30 & 40% by replacing maize and soybean from basal diet) was conducted with 25 laying hens per treatment for 16 weeks under completely randomized design in order to study the production performance, blood-biochemical parameters, immunity, egg quality and cost economics of laying hens. The results showed substantial variations (P<0.01) in egg production, egg mass, FCR per dozen eggs, FCR per kg egg mass, and net FCR. However, there was not a substantial difference in either body weight or feed intake or in egg weight. Total serum cholesterol reduced significantly (P<0.01) at 40% inclusion of rice beer waste. Additionally, the egg haugh unit grew considerably (P<0.01) when the graded levels of rice beer waste increased. The inclusion of 20% rice brewers dried grain reduced feed cost per kg egg mass and per dozen egg production by Rs. 15.97 and 9.99, respectively. Choak (homemade rice beer waste) can thus be safely incorporated into the diet of laying hens at a 20% inclusion level for better production performance and cost-effectiveness.

Keywords: choak, rice beer waste, laying hen, production performance, cost economics

Procedia PDF Downloads 65

Authors: Junaid N. Chauhdary, Bernard A. Engel, Allah Bakhsh

Abstract:

Solar powered tubewells can be a reliable and affordable source of supplying irrigation water compared with electric or diesel operated tubewells due to frequent load shedding and soaring energy prices. A study was conducted on a solar tubewell installed at the Water Management Research Center (WMRC), University of Agriculture, Faisalabad to investigate the viability of a solar powered tubewell in terms of discharge and benefit cost ratio. The tubewell discharge was 50 m3hr-1 with a total dynamic head of 30 m. The depth of bore was 31 m (14 m blind + 17 m screen) with a casing diameter of 15.2 cm (6 inches). A 3-stage submersible pump of 10.2 cm (4 inch) diameter was lowered in the casing to a depth of 22 m. The pump was powered from 21 solar panels of 200 W capacity each. The tubewell peak discharge was observed as 6 and 7 hr day-1 in winter and summer, respectively. The breakeven analysis of the solar tubewell showed that the payback period of the solar tubewell was 1.5 years of its 10 year usable life with an IRR (internal rate of return) of 69 %. The BCR (benefit cost ratio) of the solar tubewell at 2, 4, 6, and 8 percent discount rate were 3.75, 3.45, 3.19 and 2.96, respectively. The NPV (net present value) of the solar tubewell at 2, 4, 6, and 8 % discount rates were 1.89, 1.65, 1.45 and 1.27 million rupees, respectively. These results indicated that the solar powered tubewells are a viable option as well as environmentally friendly and can be adopted by the farmers due to their affordable payback period.

Keywords: benefit cost ratio, internal rate of return (IRR), net present value (NPV), solar tubewell

Procedia PDF Downloads 213

Authors: RuiJin Zhang, HengJiang Cai, JinSong Gui

Abstract:

It takes Patinopecten yessoensis larvae more than 20 days from spawning to settlement. Due to the natural environmental factors such as current, Patinopecten yessoensis larvae are transported to a distance more than hundreds of kilometers, leading to a high instability of their spatial and temporal distribution and great difficulties in the natural spat collection. Therefore predicting the distribution is of great significance to improve the operating efficiency of the collecting. Hydrodynamic model of Northern China Yellow Sea was established and the motions equations of physical oceanography and verified by the tidal harmonic constants and the measured data velocities of Dalian Bay. According to the passivity drift characteristics of the larvae, combined with the hydrodynamic model and the particle tracking model, the spatial and temporal distribution prediction model was established and the spatial and temporal distribution of the larvae under the influence of flow and wind were simulated. It can be concluded from the model results: ocean currents have greatest impacts on the passive drift path and diffusion of Patinopecten yessoensis larvae; the impact of wind is also important, which changed the direction and speed of the drift. Patinopecten yessoensis larvae were generated in the sea along Zhangzi Island and Guanglu-Dachangshan Island, but after two months, with the impact of wind and currents, the larvae appeared in the west of Dalian and the southern of Lvshun, and even in Bohai Bay. The model results are consistent with the relevant literature on qualitative analysis, and this conclusion explains where the larvae come from in the perspective of numerical simulation.

Keywords: numerical simulation, Patinopecten yessoensis larvae, predicting model, spatial and temporal distribution

Procedia PDF Downloads 308

Authors: Alpana Saini, Sanghamitra Barman

Abstract:

Investigations were carried out to determine whether low cost peanut hull as adsorbent hold promise in removal of thionine dyes in the biomedical industries. Pollution of water due to presence of colorants is a severe socio-environmental problem caused by the discharge of industrial wastewater. In view of their toxicity, non-biodegradability and persistent nature, their removal becomes an absolute necessity. For the removal of Thionine Dye using Peanut Hull, the 10mg/L concentration of dyes, 0.5g/l of adsorbent and 200 rpm agitation speed are found to be optimum for the adsorption studies. The Spectrophotometric technique was adopted for the measurement of concentration of dyes before and after adsorption at ʎmax 598nm. The adsorption data has been fitted well to Langmuir isotherm than to Freundlich adsorption isotherm. The adsorbent was characterized by Scanning Electron Microscopy (SEM).

Keywords: adsorption, langmuir isotherm, peanut hull, thionine

Procedia PDF Downloads 383