Search results for: fault tree analysis (FTA) method

Authors: Triano Nurhikmat

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Along with the progress of science and technology, the development of the industrialized world in Indonesia took place very rapidly. This leads to a process of industrialization of society Indonesia faster with the establishment of the company and the workplace are diverse. Development of the industry relates to the activity of the worker. Where in these work activities do not cover the possibility of an impending crash on either the workers or on a construction project. The cause of the occurrence of industrial accidents was the fault of electrical damage, work procedures, and error technique. The method of an association rule is one of the main techniques in data mining and is the most common form used in finding the patterns of data collection. In this research would like to know how relations of the association between the incidence of any industrial accidents. Therefore, by using methods of analysis association rule patterns associated with combination obtained two iterations item set (2 large item set) when every factor of industrial accidents with a West Jakarta so industrial accidents caused by the occurrence of an electrical value damage = 0.2 support and confidence value = 1, and the reverse pattern with value = 0.2 support and confidence = 0.75.

Keywords: association rule, data mining, industrial accidents, rules

Procedia PDF Downloads 267

Authors: Adji Achmad Rinaldo Fernandes

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Path analysis is an analytical technique to study the causal relationship between independent and dependent variables. In this study, the integration of Clusters in the Ward Linkage method was used in a variety of clusters with path analysis. The variables used are character (x₁), capacity (x₂), capital (x₃), collateral (x₄), and condition of economy (x₄) to on time pay (y₂) through the variable willingness to pay (y₁). The purpose of this study was to compare the Ward Linkage method cluster integration in various clusters with path analysis to classify willingness to pay (y₁). The data used are primary data from questionnaires filled out by customers of Bank X, using purposive sampling. The measurement method used is the average score method. The results showed that the Ward linkage method cluster integration with path analysis on 2 clusters is the best method, by comparing the coefficient of determination. Variable character (x₁), capacity (x₂), capital (x₃), collateral (x₄), and condition of economy (x₅) to on time pay (y₂) through willingness to pay (y₁) can be explained by 58.3%, while the remaining 41.7% is explained by variables outside the model.

Keywords: cluster integration, linkage, path analysis, compliant paying behavior

Procedia PDF Downloads 155

Authors: M. M. Sadeghi, S. Vahdani

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Masonry dome structures had been widely used for covering large spans in the past. The seismic assessment of these historical structures is very complicated due to the nonlinear behavior of the material, their rigidness, and special stability configuration. The assessment method based on energy balance concept, as well as the standard pushover analysis, is used to evaluate the effectiveness of these methods in the case of masonry dome structures. The Soltanieh dome building is used as an example to which two methods are applied. The performance points are given from superimposing the capacity, and demand curves in Acceleration Displacement Response Spectra (ADRS) and energy coordination are compared with the nonlinear time history analysis as the exact result. The results show a good agreement between the dynamic analysis and the energy balance method, but standard pushover method does not provide an acceptable estimation.

Keywords: energy balance method, pushover analysis, time history analysis, masonry dome

Procedia PDF Downloads 261

Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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One of the most common pieces of equipment still used today for pruning, felling, and processing trees is the chainsaw in forestry. However, chainsaw use highlights dangers and one of the highest rates of accidents in both professional and non-professional work. Felling is proportionally the most dangerous phase, both in severity and frequency, because of the risk of being hit by the plant the operator wants to cut down. To avoid this, a correct sequence of chainsaw cuts must be taught concerning the different conditions of the tree. Virtual reality (VR) makes it possible to virtually simulate chainsaw use without danger of injury. The limitations of the existing applications are as follow. The existing platforms are not symmetrical collaborative because the trainee is only in virtual reality, and the trainer can only see the virtual environment on a laptop or PC, and this results in an inefficient teacher-learner relationship. Therefore, most applications only involve the use of a virtual chainsaw, and the trainee thus cannot feel the real weight and inertia of a real chainsaw. Finally, existing applications simulate only a few cases of tree felling. The objectives of this research were to implement and test a symmetrical collaborative training application based on VR and mixed reality (MR) with the overlap between real and virtual chainsaws in MR. The research and training platform was developed for the Meta quest 2 head-mounted display. The research and training platform application is based on the Unity 3D engine, and Present Platform Interaction SDK (PPI-SDK) developed by Meta. PPI-SDK avoids the use of controllers and enables hand tracking and MR. With the combination of these two technologies, it was possible to overlay a virtual chainsaw with a real chainsaw in MR and synchronize their movements in VR. This ensures that the user feels the weight of the actual chainsaw, tightens the muscles, and performs the appropriate movements during the test allowing the user to learn the correct body posture. The chainsaw works only if the right sequence of cuts is made to felling the tree. Contact detection is done by Unity's physics system, which allows the interaction of objects that simulate real-world behavior. Each cut of the chainsaw is defined by a so-called collider, and the felling of the tree can only occur if the colliders are activated in the right order simulating a safe technique felling. In this way, the user can learn how to use the chainsaw safely. The system is also multiplayer, so the student and the instructor can experience VR together in a symmetrical and collaborative way. The platform simulates the following tree-felling situations with safe techniques: cutting the tree tilted forward, cutting the medium-sized tree tilted backward, cutting the large tree tilted backward, sectioning the trunk on the ground, and cutting branches. The application is being evaluated on a sample of university students through a special questionnaire. The results are expected to test both the increase in learning compared to a theoretical lecture and the immersive and telepresence of the platform.

Keywords: chainsaw, collaborative symmetric virtual reality, mixed reality, operator training

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Authors: Hayal Akyildirim Beğen, Özgür Emi̇nağaoğlu

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DNA barcoding is the method of description of species based on gene diversity. In current studies, registration, genetic identification and protection of especially endemic plants pecies are carried out by DNA barcoding techniques. Molecular studies are based on the amplification and sequencing of the barcode gene region by the PCR method. Endemic Campanula choruhensis Kit Tan & Sorger, Campanula troegera Damboldt and Campanula betulifolia K.Koch is widespread in Artvin, Erzurum and around Çoruh valley passing through it. Intense road and dam constructions are carried out in and around the distribution area of this species. This situation harms the habitat of the species and puts its extinction. In this study, the plastid matK barcode gene regions (650 bp) of three Campanula species were created. To make the identification of this species quickly and accurately, gene sequence compared with sequences of other Campanula L. species. As a result of phylogenetic analysis, C. choruhensis is close relative to C. betulifolia. Morphologically, these species were determined to be more similar to each other with flower and leaf characters. C. troegera formed a separate branch.

Keywords: campanula, DNA barcoding, endemic, türkiye, artvin

Procedia PDF Downloads 52

Authors: Mehmet Akköse

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Concern about seismic safety of concrete dams have been growing around the world, partly because the population at risk in locations downstream of major dams continues to expand and also because it is increasingly evident that the seismic design concepts in use at the time most existing dams were built were inadequate. Most of the investigations in the past have been conducted on large dams, typically above 100m high. A large number of concrete dams in our country and in other parts of the world are less than 50m high. Most of these dams were usually designed using pseudo-static methods, ignoring the dynamic characteristics of the structure as well as the characteristics of the ground motion. Therefore, it is important to carry out investigations on seismic behavior this category of dam in order to assess and evaluate the safety of existing dams and improve the knowledge for different high dams to be constructed in the future. In this study, size effects on structural performance of concrete gravity dams subjected to near and far-fault ground motions are investigated including dam-water-foundation interaction. For this purpose, a benchmark problem proposed by ICOLD (International Committee on Large Dams) is chosen as a numerical application. Structural performance of the dam having five different heights is evaluated according to damage criterions in USACE (U.S. Army Corps of Engineers). It is decided according to their structural performance if non-linear analysis of the dams requires or not. The linear elastic dynamic analyses of the dams to near and far-fault ground motions are performed using the step-by-step integration technique. The integration time step is 0.0025 sec. The Rayleigh damping constants are calculated assuming 5% damping ratio. The program NONSAP modified for fluid-structure systems with the Lagrangian fluid finite element is employed in the response calculations.

Keywords: concrete gravity dams, Lagrangian approach, near and far-fault ground motion, USACE damage criterions

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Authors: Funmilayo Sarah Eguakun, Peter Oluremi Adesoye

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One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV oxide (CO2) to the atmosphere. Carbon IV oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest landsare major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine)and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influencesthe carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density speciescould be relevant for management strategy to increase carbon storage.

Keywords: adaptation, carbon sequestration, climate change, growth variables, wood density

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Authors: Mohammad Ali Al-Deeb, Hamda Ateeq Al Dhaheri

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Insects cause major damage to crops and fruit trees worldwide. In the United Arab Emirates, the date palm tree is the most economically important tree which is used for date production as well as an ornamental tree. In 2002, the number of date palm trees in UAE was 40,700,000 and it is increasing over time. The longhorn stem borer (Jebusaea hammerschmidtii) and the lesser date month (Batrachedra amydraula) are important insect pests causing damage to date palm trees in UAE. Population dynamics of the Jebusaea hammerschmidtii and Batrachedra amydraula were studied by using light and pheromons traps, respectively in Al-Ain, UAE. The first trap catch of B. amydraula adults occurred on 19 April and the insect population peaked up on 26 April 2014. The first trap catch of J. hammerschmidtii occurred in April 2014. The numbers increased over time and the population peak occurred in June. The trapping was also done in 2015. The changes in insect numbers in relation to weather parameters are discussed. Also, the importance of the results on the management of these two pests is highlighted.

Keywords: date palm, integrated pest management, UAE, light trap, pheromone trap

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: Muhammad Asghar Saqib, Saad Saleem Khan, Syed Abdul Rahman Kashif

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In order to have higher efficiency, performance and reliability the regular monitoring of an electrical motor is required. This article presents a novel view of the air-gap magnetic field analysis of a switched reluctance motor under rotor cracks and rotor tilt along its shaft axis. The fault diagnosis is illustrated on the basis of a 3-D model of the motor using finite element analysis (FEA). The analytical equations of flux linkages have been used to determine the inductance. The results of the 3-D finite element analysis on a 6/4 switched reluctance motor (SRM) shows the variation of mutual inductance with the tilting of the rotor shaft and cracked rotor conditions. These results present useful information regarding the detection of shaft tilting and cracked rotors.

Keywords: switched reluctance motor, finite element analysis, cracked rotor, 3-D modelling of a srm

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generators (DFIG) due to their advantages like speed variation and four-quadrant operation, find its application in wind turbines. DFIG besides supplying power to the grid has to support reactive power (kvar) under grid voltage variations, should contribute minimum fault current during faults, have high efficiency, minimum weight, adequate rotor protection during crow-bar-operation from +20% to -20% of rated speed.  To achieve the optimum performance, a good electromagnetic design of DFIG is required. In this paper, a simple and heuristic global optimization – Differential Evolution has been used. Variables considered are lamination details such as slot dimensions, stack diameters, air gap length, and generator stator and rotor stack length. Two operating conditions have been considered - voltage and speed variations. Constraints included were reactive power supplied to the grid and limiting fault current and torque. The optimization has been executed separately for three objective functions - maximum efficiency, weight reduction, and grid fault stator currents. Subsequent calculations led to the conclusion that designs determined through differential evolution help in determining an optimum electrical design for each objective function.

Keywords: design optimization, performance, DFIG, differential evolution

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Ira Irawati, Muhammad Rangga Sururi

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The expansion of built-up areas in many cities, particularly, as the consequences of urbanization process, is a common phenomenon in our contemporary world. As happened in many cities in developing world, this horizontal expansion let only a handful size of the area left for green open spaces, creating an extreme unbalance between built-up and green spaces. Combined with the high density and variety of human activities with its transportation modes; a process of urban heat island will occur, resulting in an increase in air temperature. This is one of the indicators of decreasing of the quality of urban microclimate. This paper will explore the effect of several variables of built-up areas and open spaces to the increase of air temperature using multiple linear regression analysis. We selected 11 zones within the radius of 1 km in Inner Bandung city center, and each zones measured within 300 m radius to represent the variety of land use, as well as the composition of buildings and green open spaces. By using a quantitative method which is multiple linear regression analysis, six dependent variables which are a) tree density-x1, b) shade level of tree-x2, c) surface area of buildings’ side which are facing west and east-x3, d) surface area of building side material-x4, e) surface area of pathway material, and f) numbers of motorized vehicles-x6; are calculated to find those influence to the air temperature as an independent variable-y. Finally, the relationship between those variables shows in this equation: y = 30.316 - 3.689 X1 – 6.563 X2 + 0.002 X3 – 2,517E6 X4 + 1.919E-9 X5 + 1.952E-4 X6. It shows that the existence of vegetation has a great impact on lowering temperature. In another way around, built up the area and motorized vehicles would increase the temperature. However, one component of built up area, the surface area of buildings’ sides which are facing west and east, has different result due to the building material is classified in low-middle heat capacity.

Keywords: built-up area, microclimate, vehicles, urban heat island, vegetation

Procedia PDF Downloads 238

Authors: Krešimir Begović, Miloš Rydval, Jan Tumajer, Kristyna Svobodová, Thomas Langbehn, Yumei Jiang, Vojtech Čada, Vaclav Treml, Ryszard Kaczka, Miroslav Svoboda

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Environmental changes have increased the frequency and intensity of climatic extremes, particularly hotter droughts, leading to altered tree growth patterns and multi-year lags in tree recovery. The effects of shifting climatic conditions on tree growth are inhomogeneous across species’ natural distribution ranges, with large spatial heterogeneity and inter-population variability, but generally have significant consequences for contemporary forest dynamics and future ecosystem functioning. Despite numerous studies on the impacts of regional drought effects, large uncertainties remain regarding the mechanistic basis of drought legacy effects on wood formation and the ability of individual species to cope with increasingly drier growing conditions and rising year-to-year climatic variability. To unravel the complexity of climate-growth interactions and assess species-specific responses to severe droughts, we combined forward modeling of tree growth (VS-lite model) with correlation analyses against climate (temperature, precipitation, and the SPEI-3 moisture index) and growth responses to extreme drought events from multiple tree-ring parameters (tree-width and blue intensity parameters). We used an extensive dataset with over 1000 tree-ring samples from 23 nature forest reserves across an altitudinal range in Czechia and Slovakia. Our results revealed substantial spatiotemporal variability in growth responses to summer season temperature and moisture availability across species and tree-ring parameters. However, a general trend of increasing spring moisture-growth sensitivity in recent decades was observed in the Scots pine mountain forests and lowland forests of both species. The VS-lite model effectively captured nonstationary climate-growth relationships and accurately estimated high-frequency growth variability, indicating a significant incidence of regional drought events and growth reductions. Notably, growth reductions during extreme drought years and discrete legacy effects identified in individual wood components were most pronounced in the lowland forests. Together with the observed growth declines in recent decades, these findings suggest an increasing vulnerability of Norway spruce and Scots pine in dry lowlands under intensifying climatic constraints.

Keywords: dendroclimatology, Vaganova–Shashkin lite, conifers, central Europe, drought, blue intensity

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Authors: Deepti Kumari, Upamanyu Hore

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Cities are an example of a human-modified environment with few fragments of urban green spaces, which are widely considered for urban biodiversity. The study aims to address the avifaunal diversity in urban parks based on the park size and their urbanization intensity. Also, understanding the key factors affecting species composition and structure as birds are a good indicator of a healthy ecosystem, and they are sensitive to changes in the environment. A 50 m-long line-transect method is used to survey birds in 39 urban parks in Delhi, India. Habitat variables, including vegetation (percentage of non-native trees, percentage of native trees, top canopy cover, sub-canopy cover, diameter at breast height, ground vegetation cover, shrub height) were measured using the quadrat method along the transect, and disturbance variables (distance from water, distance from road, distance from settlement, park area, visitor rate, and urbanization intensity) were measured using ArcGIS and google earth. We analyzed species data for diversity and richness. We explored the relation of species diversity and richness to habitat variables using the multi-model inference approach. Diversity and richness are found significant in different park sizes and their urbanization intensity. Medium size park supports more diversity, whereas large size park has more richness. However, diversity and richness both declined with increasing urbanization intensity. The result of CCA revealed that species composition in urban parks was positively associated with tree diameter at breast height and distance from the settlement. On the model selection approach, disturbance variables, especially distance from road, urbanization intensity, and visitors are the best predictors for the species richness of birds in urban parks. In comparison, multiple regression analysis between habitat variables and bird diversity suggested that native tree species in the park may explain the diversity pattern of birds in urban parks. Feeding guilds such as insectivores, omnivores, carnivores, granivores, and frugivores showed a significant relation with vegetation variables, while carnivores and scavenger bird species mainly responded with disturbance variables. The study highlights the importance of park size in urban areas and their urbanization intensity. It also indicates that distance from the settlement, distance from the road, urbanization intensity, visitors, diameter at breast height, and native tree species can be important determining factors for bird richness and diversity in urban parks. The study also concludes that the response of feeding guilds to vegetation and disturbance in urban parks varies. Therefore, we recommend that park size and surrounding urban matrix should be considered in order to increase bird diversity and richness in urban areas for designing and planning.

Keywords: diversity, feeding guild, urban park, urbanization intensity

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Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

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We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering　severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

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Authors: Peter Antwi Buah, Yingbin Zhang, Jianxian He, Chenlin Xiang, Delali Atsu Y. Bakah

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Near-fault ground motions with velocity pulses are considered to cause significant damage to structures or slopes compared to ordinary ground motions without velocity pulses. The double pulsed pulse-like ground motion is as well known to be stronger than the single pulse. This study has numerically justified this perspective by studying the dynamic response of a homogeneous rock slope subjected to four pulse-like and two non-pulse-like ground motions using the Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D) software. Two of the pulse-like ground motions just have a single pulse. The results show that near-fault ground motions with velocity pulses can cause a higher dynamic response than regular ground motions. The amplification of the peak ground acceleration (PGA) in horizontal direction increases with the increase of the slope elevation. The seismic response of the slope under double pulse ground motion is stronger than that of the single pulse ground motion. The PGV amplification factor under the effect of the non-pulse-like records is also smaller than those under the pulse-like records. The velocity pulse strengthens the earthquake damage to the slope, which results in producing a more strong dynamic response.

Keywords: velocity pulses, dynamic response, PGV magnification effect, elevation effect, double pulse

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB/Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind energy, PWM inverter, modeling

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Authors: T. J. Laws-Nicola

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Henry Russell was best known as a composer of more than 300 songs. Many of his compositions were popular for both their sentimental texts, as in ‘The Old Armchair,’ and those of a more political nature, such as ‘Woodsman, Spare That Tree!’ Indeed, Russell had written such songs of advocacy as those associated with abolitionism (‘The Slave Ship’) and environmentalism (‘Woodsman, Spare that Tree!’). ‘The Maniac’ is his only composition addressing the issue of institutionalization. The text is borrowed and adapted from the monodrama The Captive by M.G. ‘Monk’ Lewis. Through an analysis of form, harmony, melody, text, and thematic development and interactions between text and music we can approach a clearer understanding of ‘The Maniac’ and how the text and music interact. Select periodicals, such as The London Times, provide contemporary critical review for ‘The Maniac.’ Additional nineteenth century songs whose texts focus on madness and/or institutionalization will assist in building a stylistic and cultural context for ‘The Maniac.’ Through comparative analyses of ‘The Maniac’ with a body of songs that focus on similar topics, we can approach a clear understanding of the song as a vehicle for deinstitutionalization.

Keywords: 19th century song, institutionalization, M. G. Lewis, Henry Russell

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Authors: Kazushi Murata, Fabian Watermann, O. B. Herve Gonroudobou, Le Thuy Hang, Toshiro Yamanaka, M. Larry Lopez C.

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Aims: Black pine coastal forests play an important role as a windbreak and as a natural barrier to sand and salt spray inland in Japan. The recent invasion of N₂-fxing black locust (Robinia pseudoacacia) trees in these forests is expected to have a nutritional contribution to black pine trees growth. Thus, the effect of this new source of N on black pine trees' N assimilation needs to be assessed. Methods: In order to evaluate this contribution, tree-ring isotopic composition (δ¹⁵N) and nitrogen content (%N) of black pine (Pinus thunbergii) trees in a pure stand (BPP) and a mixed stand (BPM) with black locust (BL) trees were measured for the period 2000–2019 for BPP and BL and 1990–2019 for BPM. The same measurements were conducted in plant tissues and in soil samples. Results: The tree ring δ15N values showed that for the last 30 years, BPM trees gradually switched from BPP to BL-derived soil N starting in the 1990s, becoming the dominant N source from 2000 as no significant diference was found between BPM and BL tree ring δ¹⁵N values from 2000 to 2019. No difference in root and sapwood BPM and BL δ¹⁵N values were found, but BPM foliage (−2.1‰) was different to BPP (−4.4‰) and BL (−0.3‰), which is related to the different N assimilation pathways between BP and BL. Conclusions: Based on the results of this study, the assimilation of BL-derived N inferred from the BPM tissues' δ¹⁵N values is the result of an increase in soil bioavailable N with a higher δ¹⁵N value.

Keywords: nitrogen-15, N₂-fxing species, mixed stand, soil, tree rings

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Authors: Rupam Saikia, Ashim Kanti Dey

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Sonapur is an intense hilly region on the border of Assam and Meghalaya lying in North-East India and is very near to a seismic fault named as Dauki besides which makes the region seismically active. Besides, these recently two earthquakes of magnitude 6.7 and 6.9 have struck North-East India in January and April 2016. Also, the slope concerned for this study is adjacent to NH 44 which for a long time has been a sole important connecting link to the states of Manipur and Mizoram along with some parts of Assam and so has been a cause of considerable loss to life and property since past decades as there has been several recorded incidents of landslide, road-blocks, etc. mostly during the rainy season which comes into news. Based on this issue this paper reports a static and dynamic slope stability analysis of Sonapur which has been carried out in MIDAS GTS NX. The slope being highly unreachable due to terrain and thick vegetation in-situ test was not feasible considering the current scope available so disturbed soil sample was collected from the site for the determination of strength parameters. The strength parameters were so determined for varying relative density with further variation in water content. The slopes were analyzed considering plane strain condition for three slope heights of 5 m, 10 m and 20 m which were then further categorized based on slope angles 30, 40, 50, 60, and 70 considering the possible extent of steepness. Initially static analysis under dry state was performed then considering the worst case that can develop during rainy season the slopes were analyzed for fully saturated condition along with partial degree of saturation with an increase in the waterfront. Furthermore, dynamic analysis was performed considering the El-Centro Earthquake which had a magnitude of 6.7 and peak ground acceleration of 0.3569g at 2.14 sec for the slope which were found to be safe during static analysis under both dry and fully saturated condition. Some of the conclusions were slopes with inclination above 40 onwards were found to be highly vulnerable for slopes of height 10 m and above even under dry static condition. Maximum horizontal displacement showed an exponential increase with an increase in inclination from 30 to 70. The vulnerability of the slopes was seen to be further increased during rainy season as even slopes of minimal steepness of 30 for height 20 m was seen to be on the verge of failure. Also, during dynamic analysis slopes safe during static analysis were found to be highly vulnerable. Lastly, as a part of the study a comparative study on Strength Reduction Method (SRM) versus Limit Equilibrium Method (LEM) was also carried out and some of the advantages and disadvantages were figured out.

Keywords: dynamic analysis, factor of safety, slope stability, strength reduction method

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Authors: Zouhaier Nasr, Mohamed Nouri

Abstract:

The increase in greenhouse gases since the pre-industrial period is a real threat to disrupting the balance of marine and terrestrial ecosystems. Along with the oceans, forest soils are considered to be the planet's second-largest carbon sink. North African forests have been subject to alarming degradation for several decades. The objective of this investigation is to determine and quantify the effect of thinning practiced in pine forests in northern Tunisia on the storage of organic carbon in the trees and in the soil. The plot planted in 1989 underwent thinning in 2005 on to plots; the density is therefore 1600 trees/ha in control and 400 trees/ha in thinning. Direct dendrometric measurements (diameter, height, branches, stem) were taken. In the soil part, six profiles of 1m / 1m / 1m were used for soil and root samples and biomass and organic matter measurements. The measurements obtained were statistically processed by appropriate software. The results clearly indicate that thinning improves tree growth, so the diameter increased from 24.3 cm to 30.1 cm. Carbon storage in the trunks was 35% more and 25% for the whole tree. At ground level, the thinned plot shows a slight increase in soil organic matter and quantity of carbon per tree, exceeding the control by 10 to 25%.

Keywords: forest, soil, carbon, climate change, Tunisia

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

Abstract:

Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: M. S. Baazzim, M. S. Al-Saud, M. A. El-Kady

Abstract:

In this paper, steady-state ampacity (current carrying capacity) evaluation of underground power cable system by using analytical and numerical methods for different conditions (depth of cable, spacing between phases, soil thermal resistivity, ambient temperature, wind speed), for two system voltage level were used 132 and 380 kV. The analytical method or traditional method that was used is based on the thermal analysis method developed by Neher-McGrath and further enhanced by International Electrotechnical Commission (IEC) and published in standard IEC 60287. The numerical method that was used is finite element method and it was recourse commercial software based on finite element method.

Keywords: cable ampacity, finite element method, underground cable, thermal rating

Procedia PDF Downloads 352

Authors: Benazzouz Djamel, Termeche Adel, Touati Youcef, Alem Said, Ouziala Mahdi

Abstract:

This paper presents an approach which detect and isolate efficiently a fault in a system. This approach avoids false alarms, non-detections and delays in detecting faults. A study case have been proposed to show the importance of taking into consideration the uncertainties in the decision-making procedure and their effect on the degradation diagnostic performance and advantage of using Bond Graph (BG) for such degradation. The use of BG in the Linear Fractional Transformation (LFT) form allows generating robust Analytical Redundancy Relations (ARR’s), where the uncertain part of ARR’s is used to generate the residuals adaptive thresholds. The study case concerns an electromechanical system composed of a motor, a reducer and an external load. The aim of this application is to show the effectiveness of the BG-LFT approach to robust fault detection.

Keywords: bond graph, LFT, uncertainties, detection and faults isolation, ARR

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Authors: Juan F. P. Ramírez, Jésica A. L. Isaza, Benjamín A. Rojano

Abstract:

This study proposes a novel use of a method to determine the mechanical properties of fruits by the use of the indentation tests. The method combines experimental results with a numerical finite elements model. The results presented correspond to a simplified numerical modeling of banana. The banana was assumed as one-layer material with an isotropic linear elastic mechanical behavior, the Young’s modulus found is 0.3Mpa. The method will be extended to multilayer models in further studies.

Keywords: finite element method, fruits, inverse analysis, mechanical properties

Procedia PDF Downloads 334

Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

Abstract:

Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

Procedia PDF Downloads 384

Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

Abstract:

We consider a linear programming model to help farmers to decide if it is convinient to choose among three kinds of export fruits for their future investment. We consider area, investment, water, productivitiy minimal unit, and harvest restrictions and a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability and initia investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market.

Keywords: mixed integer problem, fruit production, support decision model, fruit tree farms

Procedia PDF Downloads 434