Search results for: command line input

Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

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The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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Authors: Zhou BingHai, Fradet Victor

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Lean philosophy follows the simple principle of “creating more value with fewer resources”. In accordance with this policy, material handling can be managed by the mean of Kanban which by triggering every feeding tour only when needed regulates the flow of material in one of the most efficient way. This paper focuses on Kanban Supermarket’s parameters and their optimization on a purely cost-based point of view. Number and size of forklifts, as well as size of the containers they carry, will be variables of the cost function which includes handling costs, inventory costs but also shortage costs. With an innovative computational approach encoded into industrial engineering software Tecnomatix and reproducing real-life conditions, a fictive assembly line is established and produces a random list of orders. Multi-scenarios are then run to study the impact of each change of parameter and the variation of costs it implies. Lastly, best-case scenarios financially speaking are selected.

Keywords: Kanban, supermarket, parts-feeding policies, multi-scenario simulation, assembly line

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Authors: Zita Fomukong Andam

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With a general objective of evaluating the importance and Performance attributes of Volunteer Tourism in Ethiopia and also specifically intending to rank out the importance to evaluate the competitive performance of Ethiopia to host volunteer tourists, laying them in a four quadrant grid and conduct the IPA Iso-Priority Line comparison of Volunteer Tourism in Ethiopia. From hosts and guests point of view, a deeper research discourse was conducted with a randomly selected 384 guests and 165 hosts in Ethiopia. Findings of the discourse through an exploratory research design on both the hosts and the guests confirm that attributes of volunteer tourism generally and marginally fall in the South East quadrant of the matrix where their importance is relatively higher than their performance counterpart, also referred as ‘Concentrate Here’ quadrant. The fact that there are more items in this particular place in both the host and guest study, where they are highly important, but their relative performance is low, strikes a message that the country has more to do. Another focus point of this study is mapping the scores of attributes regarding the guest and host importance and performance against the Iso-Priority Line. Results of Iso-Priority Line Analysis of the IPA of Volunteer Tourism in Ethiopia from the Host’s Perspective showed that there are no attributes where their importance is exactly the same as their performance. With this being found, the fact that this research design inhabits many characters of exploratory nature, it is not confirmed research output. This paper reserves from prescribing anything to the applied world before further confirmatory research is conducted on the issue and rather calls the scientific community to augment this study through comprehensive, exhaustive, extensive and extended works of inquiry in order to get a refined set of recommended items to the applied world.

Keywords: volunteer tourism, competitive performance importance-performance analysis, Ethiopian tourism

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Yuxiao Jiang, Lingjun Meng, Mengyu Zhan, Lichunyi Zhang, Yingxia Yun

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On August 8th of 2015, a serious explosion occurred in Binhai New Area of Tianjin. This explosion led to the suspension of Tianjin-Binhai Light Rail Line 9 which was an important transportation mean connecting the old and new urban areas and the suspension causes inconvenience to commuters traveling from Tianjin to Binhai or Binhai to Tianjin and residents living by Line 9. On this regard, this paper intends to give suggestions on how to develop multi-mode transportation system rapidly and effectively after a disaster and tackle with the problems in terms of transportation infrastructure facilities. The paper proposes the idea of traffic resilience which refers to the city’s ability to restore its transportation system and reduce risks when the transportation system is destroyed by a disaster. By doing questionnaire research, on the spot study and collecting data from the internet, a GIS model is established so as to analyze the alternative traffic means used by different types of residents and study the transportation supply and demand. The result shows that along the Line 9, there is a larger demand for alternative traffic means in the place which is nearer to the downtown area. Also, the distribution of bus stations is more reasonable in the place nearer to downtown area, however, the traffic speed in the area is slower. Based on traffic resilience, the paper raises strategies to develop post-disaster multi-mode transportation system such as establishing traffic management mechanism timely and effectively, building multi-mode traffic networks, improving intelligent traffic systems and so on.

Keywords: traffic resilience, multi-mode transportation system, public traffic, transportation demand

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Pooree Sakot, Marndarath Suksanga

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Organizations are under increasing pressure to improve performance and maximize the contribution of every employee. Employee engagement has become an attractive business proposition. The triple bottom line consists of three Ps: profit, people and planet. It aims to measure the financial, social and environmental performance of the corporation over a period of time. People are the most important asset of every organization. Most of the studies suggest that employee engagement improves the bottom line in almost every instance and it is well worth all organizational efforts to actively engage employees. Engaged employees have an impact on productivity and financial performance. Efficient leadership and effective management can take place if emerging paradigm like employee engagement is appropriately understood and put into practice. Employee engagement starts at the first step i.e. recruitment of an employee to the last step i.e. retirement .The HR Practices of an organization play the most major role in helping the employees walk the extra mile. Effective employee engagement is the key component for improved organizational performance.

Keywords: employee engagement, higher education, tool, success

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Authors: Hanan Rizk

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A heat exchanger is a device used to mix liquids having different temperatures. In this case, the temperature control becomes a critical objective. This research work presents the temperature control of the double-pipe heat exchanger (multi-input multi-output (MIMO) system), which is modeled as first-order coupled hyperbolic partial differential equations (PDEs), using conventional and advanced control techniques and develops appropriate robust control strategy to meet stability requirements and performance objectives. We designed a PID controller and H-infinity controller for a heat exchanger (HE) system. Frequency characteristics of sensitivity functions and open-loop and closed-loop time responses are simulated using MATLAB software, and the stability of the system is analyzed using Kalman's test. The simulation results have demonstrated that the H-infinity controller is more efficient than PID in terms of robustness and performance.

Keywords: heat exchanger, multi-input multi-output system, MATLAB simulation, partial differential equations, PID controller, robust control

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Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

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Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

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Authors: Mahmut Genc, Seda Genc

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Wine is the most popular alcoholic drink in the World with 274.4 million of hectoliter annual production in the year of 2015. The wine industry is very important for some regions as well as creating significant value in their economies. This industry is very sensitive to the global warming since viticulture highly depends on climate and geographical region. Sustainability concept is a crucial issue for the wine industry and sustainability performances of wine production processes should be determined. Although wine production industry is an energy intensive sector as a whole, the most energy intensive products are widely used both in the viti and vinicultural process. In this study, gate-to-gate LCA approach in energy resource utilization and global warming potential impacts for white wine production line were attempted and carbon footprint and exergy destruction footprint were calculated, accordingly. As a result, carbon footprint and exergy destruction footprint values were calculated to be 1.75 kg CO2eq and 365.3kW, respectively.

Keywords: carbon footprint, exergy analysis, exergy destruction footprint, white wine

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Samantha Rix

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The purpose of this research paper is to investigate the cognitive processing of learners who receive input but produce very little or no output, and who, when they do produce output, exhibit a similar language proficiency as do those learners who produced output more regularly in the language classroom. Previous studies have investigated the benefits of output (with somewhat differing results); therefore, the presentation will begin with an investigation of what may underlie gains in proficiency without output. Consequently, a pilot study was designed and conducted to gain insight into the cognitive processing of low-output language learners looking, for example, at quantity and quality of noticing. This will be carried out within the paradigm of action classroom research, observing and interviewing low-output language learners in an intensive English program at a small Midwest university. The results of the pilot study indicated that autonomy in language learning, specifically utilizing strategies such self-monitoring, self-talk, and thinking 'out-loud', were crucial in the development of language proficiency for academic-level performance. The presentation concludes with an examination of pedagogical implication for classroom use in order to aide students in their language development.

Keywords: cognitive processing, language learners, language proficiency, learning strategies

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Authors: Kim Dongwon, Yu Songjin

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This study identifies the business value of VOC (Voice of Customer) on the business. Precisely, we intend to demonstrate how much negative and positive sentiment of VOC has an influence on car sales market share in the unites states. We extract 7 emotions such as sadness, shame, anger, fear, frustration, delight and satisfaction from the VOC data, 23,204 pieces of opinions, that had been posted on car-related on-line community from 2007 to 2009(a part of data collection from 2007 to 2015), and intend to clarify the correlation between negative and positive sentimental keywords and contribution to market share. In order to develop a lexicon for each category of negative and positive sentiment, we took advantage of Corpus program, Antconc 3.4.1.w and on-line sentimental data, SentiWordNet and identified the part of speech(POS) information of words in the customers' opinion by using a part-of-speech tagging function provided by TextAnalysisOnline. For the purpose of this present study, a total of 45,741 pieces of customers' opinions of 28 car manufacturing companies had been collected including titles and status information. We conducted an experiment to examine whether the inclusion, frequency and intensity of terms with negative and positive emotions in each category affect the adoption of customer opinions for vehicle organizations' market share. In the experiment, we statistically verified that there is correlation between customer ideas containing negative and positive emotions and variation of marker share. Particularly, "Anger," a domain of negative domains, is significantly influential to car sales market share. The domain "Delight" and "Satisfaction" increased in proportion to growth of market share.

Keywords: data mining, opinion mining, sentiment analysis, VOC

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Xavier Bertrand, Alexandre Cayrel

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The early phase of an aircraft development is instrumental as it really drives the potential of a new concept. Any weakness in the high-level design (wing planform, moveable surfaces layout etc.) will be extremely difficult and expensive to recover later in the aircraft development process. Aerodynamic evaluation in this very early development phase is driven by two main criteria: a short lead-time to allow quick iterations of the geometrical design, and a high quality of the calculations to get an accurate & reliable assessment of the current status. These two criteria are usually quite contradictory. Actually, short lead time of a couple of hours from end-to-end can be obtained with very simple tools (semi-empirical methods for instance) although their accuracy is limited, whereas higher quality calculations require heavier/more complex tools, which obviously need more complex inputs as well, and a significantly longer lead time. At this point, the choice has to be done between accuracy and lead-time. A brand new approach has been developed within Airbus, aiming at obtaining quickly high quality evaluations of the aerodynamic of an aircraft. This methodology is based on a joint use of Surrogate Modelling and a lifting line code. The Surrogate Modelling is used to get the wing sections characteristics (e.g. lift coefficient vs. angle of attack), whatever the airfoil geometry, the status of the moveable surfaces (aileron/spoilers) or the high-lift devices deployment. From these characteristics, the lifting line code is used to get the 3D effects on the wing whatever the flow conditions (low/high Mach numbers etc.). This methodology has been applied successfully to a concept of medium range aircraft.

Keywords: aerodynamics, lifting line, surrogate model, CFD

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Authors: Arii Bowo Yudhaprasetya, Ario Guritno, Agus Setiawan, Recky Tehupuring, Cosmas Supriatna

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The offshore facilities condition of Pertamina Hulu Energi Offshore North West Java (PHE ONWJ) varies greatly from place to place, depending on the characteristics of the presently installed facilities. In some locations, such as ESA platform, gas trap is mainly caused by the occurrence of flash gas phenomenon which is known as mechanical-physical separation process of multiphase flow. Consequently, the presence of gas trap at main oil line would accumulate on certain areas result in a reduced oil stream throughout the pipeline. Any presence of discrete gaseous along continuous oil flow represents a unique flow condition under certain specific volume fraction and velocity field. From gas lift source, a benefit line is used as a motive flow for ejector which is designed to generate a syphon effect to minimize the gas trap phenomenon. Therefore, the ejector’s exhaust stream will flow to the designated point without interfering other systems.

Keywords: diffuser, ejector, flow, fluent

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Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

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This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

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Authors: Vijay Kumar Bajpai, Sudhir Kumar Singh

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In this study, the performance analyses of the twenty five coal-fired power plants (CFPPs) used for electricity generation are carried out through various data envelopment analysis (DEA) models. Three efficiency indices are defined and pursued. During the calculation of the operational performance, energy and non-energy variables are used as input, and net electricity produced is used as desired output. CO2 emitted to the environment is used as the undesired output in the computation of the pure environmental performance while in Model-3 CO2 emissions is considered as detrimental input in the calculation of operational and environmental performance. Empirical results show that most of the plants are operating in increasing returns to scale region and Mettur plant is efficient one with regards to energy use and environment. The result also indicates that the undesirable output effect is insignificant in the research sample. The present study will provide clues to plant operators towards raising the operational and environmental performance of CFPPs.

Keywords: coal fired power plants, environmental performance, data envelopment analysis, operational performance

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Authors: Oluwatosin S. Adeoye

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The power quality issues in the world today are critical to the development of different nations. Prosperity of each nation depends on availability of constant power supply. Constant power supply is a major challenge in Africa particularly in Nigeria where the generated power is than thirty percent of the required power. The metrics of power quality are voltage dip, flickers, spikes, harmonics and interruptions. The level of interruptions in Ekiti State was examined through the investigation of the causes of power interruptions in the State. The method used was the collection of data from the Distribution Company, assessment through simple programming as a command for plotting the graphs through the use of MATLAB 2015 depicting the behavioural pattern of the interruption for a period of six months in 2016. The result shows that the interrelationship between the interruptions and development. Recommendations were suggested with the objective of solving the problems being set up by interruptions in the State and these include installation of reactors, automatic voltage regulators and effective tap changing system on the lines, busses and transformer substation respectively.

Keywords: development, frequency, interruption, power, quality

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Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

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Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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Authors: Bryan Young, Andrew Wodehouse, Marion Sheridan

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The availability of working memory has long been identified as a critical aspect of an instructional design. Many conventional instructional procedures impose irrelevant or unrelated cognitive loads on the learner due to the fact that they were created without contemplation, or understanding, of cognitive work load. Learning to physically operate traditional products can be viewed as a learning process akin to any other. As such, many of today's products, such as cars, boats, and planes, which have traditional controls that predate modern user-centered design techniques may be imposing irrelevant or unrelated cognitive loads on their operators. The goal of the research was to investigate the fundamental relationships between physical inputs, resulting actions, and learnability. The results showed that individuals can quickly adapt to input/output reversals across dimensions, however, individuals struggle to cope with the input/output when the dimensions are rotated due to the resulting increase in cognitive load.

Keywords: cognitive load theory, instructional design, physical product interactions, usability design

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Authors: Alec Wells, Aminu Bello Usman, Justin McKeown

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The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analysed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.

Keywords: direct voice input, risk, security, technology, trust

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Authors: Yidan Shao

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With the advancement of the economy, technology promotes online teaching, and learning has become one of the common features in the educational field. Meanwhile, the dramatic expansion of the online environment provides opportunities for more learners, including second language learners. A greater command of vocabulary improves students’ learning capacity, and word acquisition and development play a critical role in learning. Furthermore, the Word Wall is an effective tool to improve students’ knowledge of words, which works for a wide range of age groups. Therefore, this study is going to use the Word Wall as an intervention to examine whether it can bring some memorization changes in an online English language class for a second language learner based on the word morphology method. The participant will take ten courses in the experiment as it plans. The findings show that the Word Wall activity plays a slight role in improving word memorizing, but it does affect instant memorization. If longer periods and more comprehensive designs of research can be applied, it is expected to have more value.

Keywords: second language acquisition, word morphology, word memorization, the Word Wall

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Authors: Kashish Sareen, Jatinder Singh Bal

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The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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Authors: Özlem Ateş Sönmezoğlu, Begüm Terzi, Ahmet Yıldırım, Leyla Gündüz

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Durum wheat quality is defined as its suitability for pasta processing, that is pasta making quality. Another factor that determines the quality of durum wheat is the nutritional value of wheat or its final products. Wheat is a basic source of calories, proteins and minerals for humans in many countries of the world. For this reason, improvement of wheat nutritional value is of great importance. In recent years, deficiencies in protein and micronutrients, particularly in iron and zinc, have seriously increased. Therefore, basic foods such as wheat must be improved for micronutrient content. The effects of some major genes for grain quality established. Gpc-B1 locus is one of the genes increased protein and micronutrients content, and used in improvement studies of durum wheat nutritional value. The aim of this study was to increase the protein content and the micronutrient (Fe, Zn ve Mn) contents of an advanced durum wheat line (TMB 1) that was previously improved for its protein quality. For this purpose, TMB1 advanced durum wheat line were used as the recurrent parent and also, UC1113-Gpc-B1 line containing the Gpc-B1 gene was used as the gene source. In all of the generations, backcrossed plants carrying the targeted gene region were selected by marker assisted selection (MAS). BC4F1 plants MAS method was employed in combination with embryo culture and rapid plant growth in a controlled greenhouse conditions in order to shorten the duration of the transition between generations in backcross breeding. The Gpc-B1 gene was selected specific molecular markers. Since Yr-36 gene associated with Gpc-B1 allele, it was also transferred to the Gpc-B1 transferred lines. Thus, the backcrossed plants selected by MAS are resistance to yellow rust disease. This research has been financially supported by TÜBİTAK (112T910).

Keywords: Durum wheat, Gpc-B1, MAS, Triticum durum, Yr-36

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Authors: Behnaz Jamshidi, Seyed Hassan Hashemabadi

Abstract:

The main objective of this study is to investigate on pigging operation of two phase flow pipeline and compare the empirical and simulation results for 108 km long , 0.7934 mm (32 inches) diameter sea line of "Phase 1 South Pars Gas Complex", located in south of Iran. The pigging time, pig velocity, the amount of slug and slug catcher pressure were calculated and monitored closely as the key parameters. Simulation was done by "OLGA" dynamic simulation software and obtained results were compared and validated with empirical data in real operation. The relative errors between empirical data and simulation of the process were 3 % and 9 % for pigging time and accumulated slug volume respectively. Simulated pig velocity and changes of slug catcher pressure were consistent with real values, too. It was also found the slug catcher and condensate stabilization units have been adequately sized for gas-liquid separation and handle the slug batch during transient conditions such as pigging and start up.

Keywords: sea line, pigging, slug catcher, two-phase flow, dynamic simulation

Procedia PDF Downloads 507

Authors: Saiful Islam, Deuk Jong Bae

Abstract:

The purpose of this study is to examine citizen satisfaction and competitiveness of a Public Private Partnership project. The study focuses on PPP in the transport sector and investigates the New Bundang Subway Line (NBL) in South Korea as the object of a case study. Most PPP studies are dominated by the study of public and private sector interests, which are classified in to three major areas comprising of policy, finance, and management. This study will explore the user perspective by assessing customer satisfaction upon NBL cost and service quality, also the competitiveness of NBL compared to other alternative transport modes which serve the Jeongja – Gangnam trip or vice versa. The regular Bundang Subway Line, New Bundang Subway Line, bus and private vehicle are selected as the alternative transport modes. The study analysed customer satisfaction of NBL and citizen’s preference of alternative transport modes based on a survey in Bundang district, South Korea. Respondents were residents and employees who live or work in Bundang city, and were divided into the following areas Pangyo, Jeongjae – Sunae, Migeun – Ori – Jukjeon, and Imae – Yatap – Songnam. The survey was conducted in January 2015 for two weeks, and 753 responses were gathered. By applying the Hedonic Utility approach, the factors which affect the frequency of using NBL were found to be overall customer satisfaction, convenience of access, and the socio economic demographic of the individual. In addition, by applying the Analytic Hierarchy Process (AHP) method, criteria factors influencing the decision to select alternative transport modes were identified. Those factors, along with the author judgement of alternative transport modes, and their associated criteria and sub-criteria produced a priority list of user preferences regarding their alternative transport mode options. The study found that overall the regular Bundang Subway Line (BL), which was built and operated under a conventional procurement method was selected as the most preferable transport mode due to its cost competitiveness. However, on the sub-criteria level analysis, the NBL has competitiveness on service quality, particularly on journey time. By conducting a sensitivity analysis, the NBL can become the first choice of transport by increasing the NBL’s degree of weight associated with cost by 0,05. This means the NBL would need to reduce either it’s fare cost or transfer fee, or combine those two cost components to reduce the total of the current cost by 25%. In addition, the competitiveness of NBL also could be obtained by increasing NBL convenience through escalating access convenience such as constructing an additional station or providing more access modes. Although these convenience improvements would require a few extra minutes of journey time, the user found this to be acceptable. The findings and policy suggestions can contribute to the next phase of NBL development, showing that consideration should be given to the citizen’s voice. The case study results also contribute to the literature of PPP projects specifically from a user side perspective.

Keywords: public private partnership, customer satisfaction, public transport, new Bundang subway line

Procedia PDF Downloads 351

Authors: Zahraa Al Ali, Ammar Abulibdeh, Talal Al-Awadhi, Midhun Mohan, Mohammed Al-Barwani, Mohammed Al-Barwani, Sara Al Nabbi, Meshal Abdullah

Abstract:

This study aims to evaluate the performance and effectiveness of six spectral water indices - derived from Multispectral sentinel-2 data - to detect soil moisture and inundated area in arid regions to be used as an indicator of mudflow phenomena to predict high-risk areas. Herein, the validation of the performance of spectral indices was conducted using threshold method, spectral curve performance, and soil-line method. These indirect validation techniques play a key role in saving time, effort, and cost, particularly for large-scale and inaccessible areas. It was observed that the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (mNDWI), and RSWIR indices have the potential to detect soil moisture and inundated areas in arid regions. According to the temporal spectral curve performance, the spectral characteristics of water and soil moisture were distinct in the Near infrared (NIR), Short-wave Infrared (SWIR1,2) bands. However, the rate and degree differed between these bands, depending on the amount of water in the soil. Furthermore, the soil line method supported the appropriate selection of threshold values to detect soil moisture. However, the threshold values varied with location, time, season, and between indices. We concluded that considering the factors influencing the behavior of water and soil reflectivity could support decision-makers in identifying high-risk mudflow locations.

Keywords: spectral reflectance curve, soil-line method, spectral indices, Shaheen cyclone

Procedia PDF Downloads 73

Authors: Nadine Maier, Martin Mensinger, Enea Tallushi

Abstract:

In general, today, two types of launching bearings are used in the construction of large steel and steel concrete composite bridges. These are sliding rockers and systems with hydraulic bearings. The advantages and disadvantages of the respective systems are under discussion. During incremental launching, the center of the webs of the superstructure is not perfectly in line with the center of the launching bearings due to unavoidable tolerances, which may have an influence on the buckling behavior of the web plates. These imperfections are not considered in the current design against plate buckling, according to DIN EN 1993-1-5. It is therefore investigated whether the design rules have to take into account any eccentricities which occur during incremental launching and also if this depends on the respective launching bearing. Therefore, at the Technical University Munich, large-scale buckling tests were carried out on longitudinally stiffened plates under biaxial stresses with the two different types of launching bearings and eccentric load introduction. Based on the experimental results, a numerical model was validated. Currently, we are evaluating different parameters for both types of launching bearings, such as load introduction length, load eccentricity, the distance between longitudinal stiffeners, the position of the rotation point of the spherical bearing, which are used within the hydraulic bearings, web, and flange thickness and imperfections. The imperfection depends on the geometry of the buckling field and whether local or global buckling occurs. This and also the size of the meshing is taken into account in the numerical calculations of the parametric study. As a geometric imperfection, the scaled first buckling mode is applied. A bilinear material curve is used so that a GMNIA analysis is performed to determine the load capacity. Stresses and displacements are evaluated in different directions, and specific stress ratios are determined at the critical points of the plate at the time of the converging load step. To evaluate the load introduction of the transverse load, the transverse stress concentration is plotted on a defined longitudinal section on the web. In the same way, the rotation of the flange is evaluated in order to show the influence of the different degrees of freedom of the launching bearings under eccentric load introduction and to be able to make an assessment for the case, which is relevant in practice. The input and the output are automatized and depend on the given parameters. Thus we are able to adapt our model to different geometric dimensions and load conditions. The programming is done with the help of APDL and a Python code. This allows us to evaluate and compare more parameters faster. Input and output errors are also avoided. It is, therefore, possible to evaluate a large spectrum of parameters in a short time, which allows a practical evaluation of different parameters for buckling behavior. This paper presents the results of the tests as well as the validation and parameterization of the numerical model and shows the first influences on the buckling behavior under eccentric and multi-axial load introduction.

Keywords: buckling behavior, eccentric load introduction, incremental launching, large scale buckling tests, multi axial stress states, parametric numerical modelling

Procedia PDF Downloads 107

Authors: Khenfer-Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

Abstract:

this paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a man-machine interface with a voice recognition system that allows the operator to tele-operate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands spoken in two languages: French and Arabic. The recognition rate obtained is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equal to 30 db, the Arabic speech recognition rate is 69% and 80% for French speech recognition rate. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: voice command, HMM, TIMIT, noise, HTK, Arabic, speech recognition

Procedia PDF Downloads 382