Search results for: path loss model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20154

Search results for: path loss model

12654 Developed CNN Model with Various Input Scale Data Evaluation for Bearing Faults Prognostics

Authors: Anas H. Aljemely, Jianping Xuan

Abstract:

Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

Procedia PDF Downloads 200
12653 Building an Opinion Dynamics Model from Experimental Data

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

Abstract:

Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

Procedia PDF Downloads 107
12652 Integrations of the Instructional System Design for Students Learning Achievement Motives and Science Attitudes with Stem Educational Model on Stoichiometry Issue in Chemistry Classes with Different Genders

Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

Abstract:

This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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12651 Evaluation of the Ability of COVID-19 Infected Sera to Induce Netosis Using an Ex-Vivo NETosis Monitoring Tool

Authors: Constant Gillot, Pauline Michaux, Julien Favresse, Jean-Michel Dogné, Jonathan Douxfils

Abstract:

Introduction: NETosis has emerged as a crucial yet paradoxical factor in severe COVID-19 cases. While neutrophil extracellular traps (NETs) help contain and eliminate viral particles, excessive NET formation can lead to hyperinflammation, exacerbating tissue damage and acute respiratory distress syndrome (ARDS). Aims: This study evaluates the relationship between COVID-19-infected sera and NETosis using an ex-vivo model. Methods: Sera from 8 post-admission COVID-19 patients, after receiving corticoid therapy, were used to induce NETosis in neutrophils from a healthy donor. NET formation was tracked using fluorescent markers for DNA and neutrophil elastase (NE) every 2 minutes for 8 hours. The results were expressed as a percentage of DNA/NE released over time. Key metrics, including T50 (time to 50% release) and AUC (area under the curve), representing total NETosis potential), were calculated. A 27-cytokine screening kit was used to assess the cytokine composition of the sera. Results: COVID-19 sera induced NETosis based on their cytokine profile. The AUC of NE and DNA release decreased with time following corticoid therapy, showing a significant reduction in 6 of the 8 patients (p<0.05). T50 also decreased in parallel with AUC for both markers. Cytokines concentration decrease with time after therapy administration. There is correlation between 14 cytokines concentration and NE release. Conclusion: This ex-vivo model successfully demonstrated the induction of NETosis by COVID-19 sera using two markers. A clear decrease in NETosis potential was observed over time with glucocorticoid therapy. This model can be a valuable tool for monitoring NETosis and investigating potential NETosis inducers and inhibitors.

Keywords: NETosis, COVID-19, cytokine storm, biomarkers

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12650 Soil Arching Effect in Columnar Embankments: A Numerical Study

Authors: Riya Roy, Anjana Bhasi

Abstract:

Column-supported embankments provide a practical and efficient solution for construction on soft soil due to the low cost and short construction times. In the recent years, geosynthetic have been used in combination with column systems to support embankments. The load transfer mechanism in these systems is a combination of soil arching effect, which occurs between columns and membrane effect of the geosynthetic. This paper aims at the study of soil arching effect on columnar embankments using finite element software, ABAQUS. An axisymmetric finite element model is generated and using this model, parametric studies are carried out. Thus the effects of various factors such as height of embankment fill, elastic modulus of pile and tensile stiffness of geosynthetic, on soil arching have been studied. The development of negative skin friction along the pile-soil interface have also been studied and the results obtained from this study are compared with the current design methods.

Keywords: ABAQUS, geosynthetic, negative skin friction, soil arching

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12649 The Impact of Diesel Exhaust Particles on Tight Junction Proteins on Nose and Lung in a Mouse Model

Authors: Kim Byeong-Gon, Lee Pureun-Haneul, Hong Jisu, Jang An-Soo

Abstract:

Background: Diesel exhaust particles (DEPs) lead to trigger airway hyperresponsiveness (AHR) and airway dysfunction or inflammation in respiratory systems. Whether tight junction protein changes can contribute to development or exacerbations of airway diseases remain to be clarified. Objective: The aim of this study was to observe the effect of DEP on tight junction proteins in one airway both nose and lung in a mouse model. Methods: Mice were treated with saline (Sham) and exposed to 100 μg/m³ DEPs 1 hour a day for 5 days a week for 4 weeks and 8 weeks in a closed-system chamber attached to a ultrasonic nebulizer. Airway hyperresponsiveness (AHR) was measured and bronchoalveolar lavage (BAL) fluid, nasal lavage (NAL) fluid, lung and nasal tissue was collected. The effects of DEP on tight junction proteins were estimated using western blot, immunohistochemical in lung and nasal tissue. Results: Airway hyperresponsiveness and number of inflammatory cells were higher in DEP exposure group than in control group, and were higher in 4 and 8 weeks model than in control group. The expression of tight junction proteins CLND4, -5, and -17 in both lung and nasal tissue were significantly increased in DEP exposure group than in the control group. Conclusion: These results suggesting that CLDN4, -5 and -17 may be involved in the airway both nose and lung, suggesting that air pollutants cause to disruption of epithelial and endothelial cell barriers. Acknowledgment: This research was supported by Korea Ministry of Environment (MOE) as 'The Environmental Health Action Program' (2016001360009) and Soonchunhyang University Research Fund.

Keywords: diesel exhaust particles, air pollutant, tight junction, Claudin, Airway inflammation

Procedia PDF Downloads 139
12648 The Impact of Artificial Intelligence on Digital Factory

Authors: Mona Awad Wanis Gad

Abstract:

The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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12647 Using Machine Learning to Predict Answers to Big-Five Personality Questions

Authors: Aadityaa Singla

Abstract:

The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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12646 A Mixed Approach to Assess Information System Risk, Operational Risk, and Congolese Microfinance Institutions Performance

Authors: Alfred Kamate Siviri, Angelus Mafikiri Tsongo, Jean Robert Kala Kamdjoug

Abstract:

Digitalization and information systems well organized have been selected as relevant measures to mitigate operational risks within organizations. Unfortunately, information system comes with new threats that can cause severe damage and quick organization lockout. This study aims to measure perceived information system risks and their effects on operational risks within the microfinance institution in D.R. Congo. Also, the factors influencing the operational risk are identified, and the link between operational risk with other risks and performance is to be assessed. The study proposes a research model drawn on the combination of Resources-Based-View, dynamic capabilities, the agency theory, the Information System Security Model, and social theories of risk. Therefore, we suggest adopting a mixed methods research with the sole aim of increasing the literature that already exists on perceived operational risk assessment and its link with other risk and performance, a focus on IT risk.

Keywords: Democratic Republic Congo, information system risk, microfinance performance, operational risk

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12645 Estimation and Utilization of Landfill Gas from Egyptian Municipal Waste: A Case Study

Authors: Ali A. Hashim Habib, Ahmed A. Abdel-Rehim

Abstract:

Assuredly, massive amounts of wastes that are not utilized and dumped in uncontrolled dumpsites will be one of the major sources of diseases, fires, and emissions. With easy steps and minimum effort, energy can be produced from these gases. The present work introduces an experimental and theoretical analysis to estimate the amount of landfill gas and the corresponding energy which can be produced based on actual Egyptian municipal wastes composition. Two models were utilized and compared, EPA (Environmental Protection Agency) model and CDM (Clean Development Mechanisms) model to estimate methane generation rates and total CH4 emissions based on a particular landfill. The results showed that for every ton of municipal waste, 140 m3 of landfill gas can be produced. About 800 kW of electricity for a minimum of 24 years can be generated form one million ton of municipal waste. A total amount of 549,025 ton of carbon emission can be avoided during these 24 years.

Keywords: energy from landfill gases, landfill biogas, methane emission, municipal solid waste, renewable energy sources

Procedia PDF Downloads 217
12644 Autonomous Exploration, Navigation and Mapping Payload Integrated on a Quadruped Robot

Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

Abstract:

The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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12643 A Method of Effective Planning and Control of Industrial Facility Energy Consumption

Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

Abstract:

A method of effective planning and control of industrial facility energy consumption is offered. The method allows to optimally arrange the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics

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12642 Study of the Behavior of Geogrid Mechanically Stabilized Earth Walls Under Cyclic Loading

Authors: Yongzhe Zhao, Ying Liu, Zhiyong Liu, Hui You

Abstract:

The soil behind retaining wall is normally subjected to cyclic loading, for example traffic loading. Geotextile has been widely used to reinforce the soil for the purpose of reducing the settlement of the soil. A series of physical model tests were performed to investigate the settlement of footing under cyclic loading. The settlement of the footing, ground deformation and the vertical earth pressure in subsoil were presented and discussed under different types of geotextiles. The results indicate that including geotextiles significantly decreases the footing settlement and the stiffer the geotextile, the less the settlement. Under cyclic loading, the soil below the footing shows dilation within certain depths and beyond that it experiences contraction. The location of footing relative to the retaining wall has important effects on the deformation behavior of the soil in the ground, and the closer the footing to the retaining wall, the greater the contraction soil shows. This is because the retaining wall experienced greater lateral displacement.

Keywords: physical model tests, reinforced retaining wall, cyclic loading, footing

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12641 Determination of Water Pollution and Water Quality with Decision Trees

Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

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

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

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12640 Utility Assessment Model for Wireless Technology in Construction

Authors: Yassir AbdelRazig, Amine Ghanem

Abstract:

Construction projects are information intensive in nature and involve many activities that are related to each other. Wireless technologies can be used to improve the accuracy and timeliness of data collected from construction sites and shares it with appropriate parties. Nonetheless, the construction industry tends to be conservative and shows hesitation to adopt new technologies. A main concern for owners, contractors or any person in charge on a job site is the cost of the technology in question. Wireless technologies are not cheap. There are a lot of expenses to be taken into consideration, and a study should be completed to make sure that the importance and savings resulting from the usage of this technology is worth the expenses. This research attempts to assess the effectiveness of using the appropriate wireless technologies based on criteria such as performance, reliability, and risk. The assessment is based on a utility function model that breaks down the selection issue into alternatives attribute. Then the attributes are assigned weights and single attributes are measured. Finally, single attribute are combined to develop one single aggregate utility index for each alternative.

Keywords: analytic hierarchy process, decision theory, utility function, wireless technologies

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12639 Investigation of Self-Assembling of Maghemite Nanoparticles into Chain–Like Structures Using Birefringence Measurements

Authors: C. R. Stein; K. Skeff Neto, K. L. C. Miranda, P. P. C. Sartoratto, M. E. Xavier, Z. G. M. Lacava, S. M. De Freita, P. C. Morais

Abstract:

In this study, static magnetic birefringence (SMB) and transmission electron microscopy (TEM) were used to investigate the self-assembling of maghemite nanoparticles suspended as biocompatible magnetic fluid (BMF) while incubated or not with the Black Eyed–Pea Trypsin Chymotripsin Inhibitor–BTCI protein. The stock samples herein studied are dextran coated maghemite nanoparticles (average core diameter of 7.1 nm, diameter dispersion of 0.26, and containing 4.6×1016 particle/mL) and the dextran coated maghemite nanoparticles associated with the BTCI protein. Several samples were prepared by diluting the stock samples with deionized water while following their colloidal stability. The diluted samples were investigated using SMB measurements to assess the average sizes of the self-assembled and suspended mesoscopic structures whereas the TEM micrographs provide the morphology of the as-suspended units. The SMB data were analyzed using a model that includes the particle-particle interaction within the mean field model picture.

Keywords: biocompatible magnetic fluid, maghemite nanoparticles, self-assembling

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12638 Integrated Business Model Innovation in Nigerian Higher Education: Challenges and Prospects

Authors: Nonso Ochinanwata, Patrick Oseloka Ezepue

Abstract:

This paper explores challenges and prospects in Nigerian higher education. The paper develops an integrated business model that aimed to innovate Nigeria higher education system. A survey and semi-structured interview among Nigerian higher education academics, students and graduates are used to explore the challenges and prospects. The study provides a comparison between lecturers, students and graduates opinions to evaluate challenges and prospects in Nigerian higher institutions. The study found to achieve efficient and effectiveness innovation in Nigerian higher education, there is a need for higher institutions to collaborate with industry professionals and other stakeholders such as company management, and government policy makers in designing higher education institutions curricula. The study found that the curriculum design and delivery need to blend theoretical understanding and real-life experience from industry, and with social cultural influences related to Nigerian environment. This will enable lecturers to organise their teaching and assessments such that students can learn around theoretical and practical study themes. The curriculum design and delivery need to link the core ideas to challenging problems in society, nationally and globally. Hence, this approach will support business start-ups and social entrepreneurship which resolve key societal problems. The study suggests that higher education executives, directors, deans, head of departments, and even individual academics need to emulate innovative business managers to create value-adding products and services from innovative research and academic work.

Keywords: higher education, curriculum innovation, business model innovation, teaching and research excellence, economic development

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12637 Pakistan’s Counterinsurgency Operations: A Case Study of Swat

Authors: Arshad Ali

Abstract:

The Taliban insurgency in Swat which started apparently as a social movement in 2004 transformed into an anti-Pakistan Islamist insurgency by joining hands with the Tehrik-e-Taliban Pakistan (TTP) upon its formation in 2007. It quickly spread beyond Swat by 2009 making Swat the second stronghold of TTP after FATA. It prompted the Pakistan military to launch a full-scale counterinsurgency military operation code named Rah-i-Rast to regain the control of Swat. Operation Rah-i-Rast was successful not only in restoring the writ of the State but more importantly in creating a consensus against the spread of Taliban insurgency in Pakistan at political, social and military levels. This operation became a test case for civilian government and military to seek for a sustainable solution combating the TTP insurgency in the north-west of Pakistan. This study analyzes why the counterinsurgency operation Rah-i-Rast was successful and why the previous ones came into failure. The study also explores factors which created consensus against the Taliban insurgency at political and social level as well as reasons which hindered such a consensual approach in the past. The study argues that the previous initiatives failed due to various factors including Pakistan army’s lack of comprehensive counterinsurgency model, weak political will and public support, and states negligence. Also, the initial counterinsurgency policies were ad-hoc in nature fluctuating between military operations and peace deals. After continuous failure, the military revisited its approach to counterinsurgency in the operation Rah-i-Rast. The security forces learnt from their past experiences and developed a pragmatic counterinsurgency model: ‘clear, hold, build, and transfer.’ The military also adopted the population-centric approach to provide security to the local people. This case Study of Swat evaluates the strengths and weaknesses of the Pakistan's counterinsurgency operations as well as peace agreements. It will analyze operation Rah-i-Rast in the light of David Galula’s model of counterinsurgency. Unlike existing literature, the study underscores the bottom up approach adopted by the Pakistan’s military and government by engaging the local population to sustain the post-operation stability in Swat. More specifically, the study emphasizes on the hybrid counterinsurgency model “clear, hold, and build and Transfer” in Swat.

Keywords: Insurgency, Counterinsurgency, clear, hold, build, transfer

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12636 Numerical Simulation of Liquid Nitrogen Spray Equipment for Space Environmental Simulation Facility

Authors: He Chao, Zhang Lei, Liu Ran, Li Ang

Abstract:

Temperature regulating system by gaseous nitrogen is of importance to the space environment simulator, which keep the shrouds in the temperature range from -150℃ to +150℃. Liquid nitrogen spray equipment is one of the most critical parts in the temperature regulating system by gaseous nitrogen. Y type jet atomizer and internal mixing atomizer of the liquid nitrogen spray equipment are studied in this paper, 2D/3D atomizer model was established and grid division was conducted respectively by the software of Catia and ICEM. Based on the above preparation, numerical simulation on the spraying process of the atomizer by FLUENT is performed. Using air and water as the medium, comparison between the tests and numerical simulation was conducted and the results of two ways match well. Hence, it can be conclude that this atomizer model can be applied in the numerical simulation of liquid nitrogen spray equipment.

Keywords: space environmental simulator, liquid nitrogen spray, Y type jet atomizer, internal mixing atomizer, numerical simulation, fluent

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12635 A Study on Solutions to Connect Distribution Power Grid up to Renewable Energy Sources at KEPCO

Authors: Seung Yoon Hyun, Hyeong Seung An, Myeong Ho Choi, Sung Hwan Bae, Yu Jong Sim

Abstract:

In 2015, the southern part of the Korean Peninsula has 8.6 million poles, 1.25 million km power lines, and 2 million transformers, etc. It is the massive amount of distribution equipments which could cover a round-trip distance from the earth to the moon and 11 turns around the earth. These distribution equipments are spread out like capillaries and supplying power to every corner of the Korean Peninsula. In order to manage these huge power facility efficiently, KEPCO use DAS (Distribution Automation System) to operate distribution power system since 1997. DAS is integrated system that enables to remotely supervise and control breakers and switches on distribution network. Using DAS, we can reduce outage time and power loss. KEPCO has about 160,000 switches, 50%(about 80,000) of switches are automated, and 41 distribution center monitoring&control these switches 24-hour 365 days to get the best efficiency of distribution networks. However, the rapid increasing renewable energy sources become the problem in the efficient operation of distributed power system. (currently 2,400 MW, 75,000 generators operate in distribution power system). In this paper, it suggests the way to interconnect between renewable energy source and distribution power system.

Keywords: distribution, renewable, connect, DAS (Distribution Automation System)

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12634 CO2 Adsorption on the Activated Klaten-Indonesian Natural Zeolite in a Packed Bed Adsorber

Authors: Sang Kompiang Wirawan, Chandra Purnomo

Abstract:

Carbon dioxide (CO2) adsorption on the activated Klaten-Indonesian natural zeolite (AKINZ) in a packed bed adsorber has been studied. Experiment works consisted of acid activation and adsorption experiments. The natural zeolite sample was activated using 0.3 M HCl at the temperature of 353 K. In the adsorption experiments the feed gas concentrations were 40 and 80 % CO2 in helium within various temperatures of 303; 323 and 373 K. The experiments were conducted by using transient step change adsorption and 20 % Ar/He tracer experiment was conducted to measure dispersion and time lag effect of the packed bed system. A mathematical model of CO2 adsorption had been set up by assuming plug flow;isothermal;isobaric and no gas film mass transport resistance. Single site Langmuir physisorption and Maxwell Stefan mass transport in micropore were applied. All the data were then optimized to get the best value of modified fitted parameter. The model was in a good agreement with the experiment data. Diffusivity tended to increase by increasing temperatures.

Keywords: adsorption, Langmuir, Maxwell-Stefan, natural zeolite, surface diffusion

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12633 GIS Model for Sanitary Landfill Site Selection Based on Geotechnical Parameters

Authors: Hecson Christian, Joel Macwan

Abstract:

Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.

Keywords: GIS, AHP, MCDA, Geo-technical

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12632 An Industrial Scada System Remote Control Using Mobile Phones

Authors: Ahmidah Elgali

Abstract:

SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.

Keywords: control, industrial, mobile, network, remote, SCADA

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12631 Application of Liquid Chromatographic Method for the in vitro Determination of Gastric and Intestinal Stability of Pure Andrographolide in the Extract of Andrographis paniculata

Authors: Vijay R. Patil, Sathiyanarayanan Lohidasan, K. R. Mahadik

Abstract:

Gastrointestinal stability of andrographolide was evaluated in vitro in simulated gastric (SGF) and intestinal (SIF) fluids using a validated HPLC-PDA method. The method was validated using a 5μm ThermoHypersil GOLD C18column (250 mm × 4.0 mm) and mobile phase consisting of water: acetonitrile; 70: 30 (v/v) delivered isocratically at a flow rate of 1 mL/min with UV detection at 228 nm. Andrographolide in pure form and extract Andrographis paniculata was incubated at 37°C in an incubator shaker in USP simulated gastric and intestinal fluids with and without enzymes. Systematic protocol as per FDA Guidance System was followed for stability study and samples were assayed at 0, 15, 30 and 60 min intervals for gastric and at 0, 15, 30, 60 min, 1, 2 and 3 h for intestinal stability study. Also, the stability study was performed up to 24 h to see the degradation pattern in SGF and SIF (with enzyme and without enzyme). The developed method was found to be accurate, precise and robust. Andrographolide was found to be stable in SGF (pH ∼ 1.2) for 1h and SIF (pH 6.8) up to 3 h. The relative difference (RD) of amount of drug added and found at all time points was found to be < 3%. The present study suggests that drug loss in the gastrointestinal tract takes place may be by membrane permeation rather than a degradation process.

Keywords: andrographolide, Andrographis paniculata, in vitro, stability, gastric, Intestinal HPLC-PDA

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12630 A Mixed Expert Evaluation System and Dynamic Interval-Valued Hesitant Fuzzy Selection Approach

Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

Abstract:

In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting

Procedia PDF Downloads 323
12629 Performance Comparison of Deep Convolutional Neural Networks for Binary Classification of Fine-Grained Leaf Images

Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

Abstract:

Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

Procedia PDF Downloads 182
12628 Optimization of Hybrid off Grid Energy Station

Authors: Yehya Abdellatif, Iyad M. Muslih, Azzah Alkhalailah, Abdallah Muslih

Abstract:

Hybrid Optimization Model for Electric Renewable (HOMER) software was utilized to find the optimum design of a hybrid off-Grid system, by choosing the optimal solution depending on the cost analysis of energy based on different capacity shortage percentages. A complete study for the site conditions and load profile was done to optimize the design and implementation of a hybrid off-grid power station. In addition, the solution takes into consecration the ambient temperature effect on the efficiency of the power generation and the economical aspects of selection depending on real market price. From the analysis of the HOMER model results, the optimum hybrid power station was suggested, based on wind speed, and solar conditions. The optimization function objective is to minimize the Net Price Cost (NPC) and the Cost of Energy (COE) with zero and 10 percentage of capacity shortage.

Keywords: energy modeling, HOMER, off-grid system, optimization

Procedia PDF Downloads 560
12627 The Effect of Green Power Trading Mechanism on Interregional Power Generation and Transmission in China

Authors: Yan-Shen Yang, Bai-Chen Xie

Abstract:

Background and significance of the study: Both green power trading schemes and interregional power transmission are effective ways to increase green power absorption and achieve renewable power development goals. China accelerates the construction of interregional power transmission lines and the green power market. A critical issue focusing on the close interaction between these two approaches arises, which can heavily affect the green power quota allocation and renewable power development. Existing studies have not discussed this issue adequately, so it is urgent to figure out their relationship to achieve a suitable power market design and a more reasonable power grid construction.Basic methodologies: We develop an equilibrium model of the power market in China to analyze the coupling effect of these two approaches as well as their influence on power generation and interregional transmission in China. Our model considers both the Tradable green certificate (TGC) and green power market, which consists of producers, consumers in the market, and an independent system operator (ISO) minimizing the total system cost. Our equilibrium model includes the decision optimization process of each participant. To reformulate the models presented as a single-level one, we replace the producer, consumer, ISO, and market equilibrium problems with their Karush-Kuhn-Tucker (KKT) conditions, which is further reformulated as a mixed-integer linear programming (MILP) and solved in Gurobi solver. Major findings: The result shows that: (1) the green power market can significantly promote renewable power absorption while the TGC market provides a more flexible way for green power trading. (2) The phenomena of inefficient occupation and no available transmission lines appear simultaneously. The existing interregional transmission lines cannot fully meet the demand for wind and solar PV power trading in some areas while the situation is vice versa in other areas. (3) Synchronous implementation of green power and TGC trading mechanism can benefit the development of green power as well as interregional power transmission. (4) The green power transaction exacerbates the unfair distribution of carbon emissions. The Carbon Gini Coefficient is up to 0.323 under the green power market which shows a high Carbon inequality. The eastern coastal region will benefit the most due to its huge demand for external power.

Keywords: green power market, tradable green certificate, interregional power transmission, power market equilibrium model

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12626 Identifying Key Factors for Accidents’ Severity at Rail-Road Level Crossings Using Ordered Probit Models

Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri

Abstract:

The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.

Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors

Procedia PDF Downloads 146
12625 Lateral Torsional Buckling Resistance of Trapezoidally Corrugated Web Girders

Authors: Annamária Käferné Rácz, Bence Jáger, Balázs Kövesdi, László Dunai

Abstract:

Due to the numerous advantages of steel corrugated web girders, its application field is growing for bridges as well as for buildings. The global stability behavior of such girders is significantly larger than those of conventional I-girders with flat web, thus the application of the structural steel material can be significantly reduced. Design codes and specifications do not provide clear and complete rules or recommendations for the determination of the lateral torsional buckling (LTB) resistance of corrugated web girders. Therefore, the authors made a thorough investigation regarding the LTB resistance of the corrugated web girders. Finite element (FE) simulations have been performed to develop new design formulas for the determination of the LTB resistance of trapezoidally corrugated web girders. FE model is developed considering geometrical and material nonlinear analysis using equivalent geometric imperfections (GMNI analysis). The equivalent geometric imperfections involve the initial geometric imperfections and residual stresses coming from rolling, welding and flame cutting. Imperfection sensitivity analysis was performed to determine the necessary magnitudes regarding only the first eigenmodes shape imperfections. By the help of the validated FE model, an extended parametric study is carried out to investigate the LTB resistance for different trapezoidal corrugation profiles. First, the critical moment of a specific girder was calculated by FE model. The critical moments from the FE calculations are compared to the previous analytical calculation proposals. Then, nonlinear analysis was carried out to determine the ultimate resistance. Due to the numerical investigations, new proposals are developed for the determination of the LTB resistance of trapezoidally corrugated web girders through a modification factor on the design method related to the conventional flat web girders.

Keywords: corrugated web, lateral torsional buckling, critical moment, FE modeling

Procedia PDF Downloads 279