Search results for: recursive least square algorithm

Authors: Sanjana S. Mallya, Roshan Arvind Sivakumar

Abstract:

Orthotics is the branch of medicine that deals with the provision and use of artificial casts or braces to alter the biomechanical structure of the limb and provide support for the limb. Custom-made orthoses provide more comfort and can correct issues better than those available over-the-counter. However, they are expensive and require intricate modelling of the limb. Traditional methods of modelling involve creating a plaster of Paris mould of the limb. Lately, CAD/CAM and 3D printing processes have improved the accuracy and reduced the production time. Ordinarily, digital cameras are used to capture the features of the limb from different views to create a 3D model. We propose a system to model the limb using Microsoft Kinect2 sensor. The Kinect can capture RGB and depth frames simultaneously up to 30 fps with sufficient accuracy. The region of interest is captured from three views, each shifted by 90 degrees. The RGB and depth data are fused into a single RGB-D frame. The resolution of the RGB frame is 1920px x 1080px while the resolution of the Depth frame is 512px x 424px. As the resolution of the frames is not equal, RGB pixels are mapped onto the Depth pixels to make sure data is not lost even if the resolution is lower. The resulting RGB-D frames are collected and using the depth coordinates, a three dimensional point cloud is generated for each view of the Kinect sensor. A common reference system was developed to merge the individual point clouds from the Kinect sensors. The reference system consisted of 8 coloured cubes, connected by rods to form a skeleton-cube with the coloured cubes at the corners. For each Kinect, the region of interest is the square formed by the centres of the four cubes facing the Kinect. The point clouds are merged by considering one of the cubes as the origin of a reference system. Depending on the relative distance from each cube, the three dimensional coordinate points from each point cloud is aligned to the reference frame to give a complete point cloud. The RGB data is used to correct for any errors in depth data for the point cloud. A triangular mesh is generated from the point cloud by applying Delaunay triangulation which generates the rough surface of the limb. This technique forms an approximation of the surface of the limb. The mesh is smoothened to obtain a smooth outer layer to give an accurate model of the limb. The model of the limb is used as a base for designing the custom orthotic brace or cast. It is transferred to a CAD/CAM design file to design of the brace above the surface of the limb. The proposed system would be more cost effective than current systems that use MRI or CT scans for generating 3D models and would be quicker than using traditional plaster of Paris cast modelling and the overall setup time is also low. Preliminary results indicate that the accuracy of the Kinect2 is satisfactory to perform modelling.

Keywords: 3d scanning, mesh generation, Microsoft kinect, orthotics, registration

Procedia PDF Downloads 187

Authors: Ramkumar R., Gaurav Shinde, Pratik Shroff, Sachin Kumar Jain, Nagesh Walke

Abstract:

Advancements in electric vehicles have significantly reduced the powertrain noise and moving components of vehicles. As a result, in-cab noises have become more noticeable to passengers inside the car. To ensure a comfortable ride for drivers and other passengers, it has become crucial to eliminate undesirable component noises during the development phase. Standard practices are followed to identify the severity of noises based on subjective ratings, but it can be a tedious process to identify the severity of each development sample and make changes to reduce it. Additionally, the severity rating can vary from jury to jury, making it challenging to arrive at a definitive conclusion. To address this, an automotive component was identified to evaluate squeak and rattle noise issue. Physical tests were carried out for random and sine excitation profiles. Aim was to subjectively assess the noise using jury rating method and objectively evaluate the same by measuring the noise. Suitable jury evaluation method was selected for the said activity, and recorded sounds were replayed for jury rating. Objective data sound quality metrics viz., loudness, sharpness, roughness, fluctuation strength and overall Sound Pressure Level (SPL) were measured. Based on this, correlation co-efficients was established to identify the most relevant sound quality metrics that are contributing to particular identified noise issue. Regression analysis was then performed to establish the correlation between subjective and objective data. Mathematical model was prepared using artificial intelligence and machine learning algorithm. The developed model was able to predict the subjective rating with good accuracy.

Keywords: BSR, noise, correlation, regression

Procedia PDF Downloads 77

Authors: Ebrahim Ghasemi Ardi, Ai Bing Yu, Run Yu Yang

Abstract:

Current study is aimed to develop an available in-house discrete element method (DEM) code and link it with direct breakage event. So, it became possible to determine the particle breakage and then its fragments size distribution, simultaneous with DEM simulation. It directly applies the particle breakage inside the DEM computation algorithm and if any breakage happens the original particle is replaced with daughters. In this way, the calculation will be followed based on a new updated particles list which is very similar to the real grinding environment. To validate developed model, a grinding ball impacting an unconfined particle bed was simulated. Since considering an entire ball mill would be too computationally demanding, this method provided a simplified environment to test the model. Accordingly, a representative volume of the ball mill was simulated inside a box, which could emulate media (ball)–powder bed impacts in a ball mill and during particle bed impact tests. Mono, binary and ternary particle beds were simulated to determine the effects of granular composition on breakage kinetics. The results obtained from the DEM simulations showed a reduction in the specific breakage rate for coarse particles in binary mixtures. The origin of this phenomenon, commonly known as cushioning or decelerated breakage in dry milling processes, was explained by the DEM simulations. Fine particles in a particle bed increase mechanical energy loss, and reduce and distribute interparticle forces thereby inhibiting the breakage of the coarse component. On the other hand, the specific breakage rate of fine particles increased due to contacts associated with coarse particles. Such phenomenon, known as acceleration, was shown to be less significant, but should be considered in future attempts to accurately quantify non-linear breakage kinetics in the modeling of dry milling processes.

Keywords: particle bed, breakage models, breakage kinetic, discrete element method

Procedia PDF Downloads 195

Authors: Yen-Fen Shen, Meng-Fan Li

Abstract:

The study aims to investigate the effect of full-body vertical rhythmic training on fatigue, physical activity, and quality of life among middle-aged and elderly hemodialysis patients. The study adopted a quasi-experimental research method and recruited 43 long-term hemodialysis patients from a medical center in northern Taiwan, with 23 and 20 participants in the experimental and control groups, respectively. The experimental group received full-body vertical rhythmic training as an intervention, while the control group received standard hemodialysis care without any intervention. Both groups completed the measurements by using "Fatigue Scale", "Physical Activity Scale" and "Chinese version of the Kidney Disease Quality of Life Questionnaire" before and after the study. The experimental group underwent a 10-minute full-body vertical rhythmic training three times per week, which lasted for eight weeks before receiving regular hemodialysis treatment. The data were analyzed by SPSS 25 software, including descriptive statistics such as frequency distribution, percentages, means, and standard deviations, as well as inferential statistics, including chi-square, independent samples t-test, and paired samples t-test. The study results are summarized as follows: 1. There were no significant differences in demographic variables, fatigue, physical activity, and quality of life between the experimental and control groups in the pre-test. 2. After the intervention of the “full-body vertical rhythmic training,” the experimental group showed significantly better results in the category of "feeling tired and fatigued in the lower back", "physical functioning role limitation", "bodily pain", "social functioning", "mental health", and "impact of kidney disease on life quality." 3. The paired samples t-test results revealed that the control group experienced significant differences between the pre-test and post-test in the categories of feeling tired and fatigued in the lower back, bodily pain, social functioning mental health, and impact of kidney disease on life quality, with scores indicating a decline in life quality. Conversely, the experimental group only showed a significant worsening in bodily pain" and the impact of kidney disease on life quality, with lower change values compared to the control group. Additionally, there was an improvement in the condition of "feeling tired and fatigued in the lower back" for the experimental group. Conclusion: The intervention of the “full-body vertical rhythmic training” had a certain positive effect on the quality of life of the experimental group. While it may not entirely enhance patients' quality of life, it can mitigate the negative impact of kidney disease on certain aspects of the body. The study provides clinical practice, nursing education, and research recommendations based on the results and discusses the limitations of the research.

Keywords: hemodialysis, full-body vertical rhythmic training, fatigue, physical activity, quality of life

Procedia PDF Downloads 17

Authors: Akintunde Alo

Abstract:

The incessant encroachments into the forest ecosystem by the farmers and local contractors constitute a major threat to the conservation of genetic resources and biodiversity in Nigeria. To propose a viable monitoring system, this study employed Geographic Information System (GIS) technology to assess the changes that occurred for a period of five years (between 2011 and 2016) in Ikere forest reserve. Landsat imagery of the forest reserve was obtained. For the purpose of geo-referencing the acquired satellite imagery, ground-truth coordinates of some benchmark places within the forest reserve was relied on. Supervised classification algorithm, image processing, vectorization and map production were realized using ArcGIS. Various land use systems within the forest ecosystem were digitized into polygons of different types and colours for 2011 and 2016, roads were represented with lines of different thickness and colours. Of the six land-use delineated, the grassland increased from 26.50 % in 2011 to 45.53% in 2016 of the total land area with a percentage change of 71.81 %. Plantations of Gmelina arborea and Tectona grandis on the other hand reduced from 62.16 % in 2011 to 27.41% in 2016. The farmland and degraded land recorded percentage change of about 176.80 % and 8.70 % respectively from 2011 to 2016. Overall, the rate of deforestation in the study area is on the increase and becoming severe. About 72.59% of the total land area has been converted to non-forestry uses while the remnant 27.41% is occupied by plantations of Gmelina arborea and Tectona grandis. Interestingly, over 55 % of the plantation area in 2011 has changed to grassland, or converted to farmland and degraded land in 2016. The rate of change over time was about 9.79 % annually. Based on the results, rapid actions to prevail on the encroachers to stop deforestation and encouraged re-afforestation in the study area are recommended.

Keywords: land use change, forest reserve, satellite imagery, geographical information system

Procedia PDF Downloads 352

Authors: Mahesh Kumar Jat, Manisha Choudhary

Abstract:

Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

Procedia PDF Downloads 124

Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

Abstract:

Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

Procedia PDF Downloads 66

Authors: Nikeshala Weerasekara, Roshan Ajward

Abstract:

Contemporary business environment, given the circumstance of stringent scrutiny toward corporate behavior, organizations are under pressure to develop and implement solid overarching Corporate Social Responsibility (CSR) strategies. In that milieu, in order to differentiate themselves from competitors and maintain stakeholder confidence banks spend millions of dollars on CSR programmes. However, knowledge on how non-western bank employees perceive such activities is inconclusive. At the same time recently only researchers have shifted their focus on positive effects of compassion at work or the organizational conditions under which it arises. Nevertheless, mediation mechanisms between CSR and compassion at work have not been adequately examined leaving a vacuum to be explored. Despite finding a purpose in work that is greater than extrinsic outcomes of the work is important to employees, meaningful work has not been examined adequately. Thus, in addition to examining the direct relationship between CSR and compassion at work, this study examined the mediating capability of meaningful work between these variables. Specifically, the researcher explored how CSR enables employees to sense work as meaningful which in turn would enhance their level of compassion at work. Hypotheses were developed to examine the direct relationship between CSR and compassion at work and the mediating effect of meaningful work on the relationship between CSR and compassion at work. Both Social Identity Theory (SIT) and Social Exchange Theory (SET) were used to theoretically support the relationships. The sample comprised of 450 respondents covering different levels of the bank. A convenience sampling strategy was used to secure responses from 13 local licensed commercial banks in Sri Lanka. Data was collected using a structured questionnaire which was developed based on a comprehensive review of literature and refined using both expert opinions and a pilot survey. Structural equation modeling using Smart Partial Least Square (PLS) was utilized for data analysis. Findings indicate a positive and significant (p < .05) relationship between CSR and compassion at work. Also, it was found that meaningful work partially mediates the relationship between CSR and compassion at work. As per the findings it is concluded that bank employees’ perception of CSR engagement not only directly influence compassion at work but also impact such through meaningful work as well. This implies that employees consider working for a socially responsible bank since it creates greater meaningfulness of work to retain with the organization, which in turn trigger higher level of compassion at work. By utilizing both SIT and SET in explaining relationships between CSR and compassion at work it amounts to theoretical significance of the study. Enhance existing literature on CSR and compassion at work. Also, adds insights on mediating capability of psychologically related variables such as meaningful work. This study is expected to have significant policy implications in terms of increasing compassion at work where managers must understand the importance of including CSR activities into their strategy in order to thrive. Finally, it provides evidence of suitability of using Smart PLS to test models with mediating relationships involving non normal data.

Keywords: compassion at work, corporate social responsibility, employee commitment, meaningful work, positive affect

Procedia PDF Downloads 125

Authors: Ilme Faridatul, Bo Wu

Abstract:

Bangladesh is often called as a motherland of rivers. It contains about 700 rivers among all these the Padma River is one of the largest rivers of Bangladesh. The change of river bank and erosion has become a common environmental natural hazard in Bangladesh. The river banks are under intense pressure from natural processes such as erosion and accretion as well as anthropogenic processes such as urban growth and pollution. The Padma River is flowing along ten districts of Bangladesh among all these Faridpur district is most vulnerable to river bank erosion. The severity of the river erosion is so high that each year a thousand of populations become homeless and lose their agricultural lands. Though the Faridpur district is most vulnerable to river bank erosion no specific research has been conducted to identify the changing pattern of river bank along this district. The outcome of the research may serve as guidance to prepare river bank monitoring program and management. This research has utilized integrated techniques of remote sensing and geographic information system to monitor the changes from 1995 to 2015 at Faridpur district. To discriminate the land water interface Modified Normalized Difference Water Index (MNDWI) algorithm is applied and on screen digitization approach is used over MNDWI images of 1995, 2002 and 2015 for river bank line extraction. The extent of changes in the river bank along Faridpur district is estimated through overlaying the digitized maps of all three years. The river bank lines are highlighted to infer the erosion and accretion and the changes are calculated. The result shows that the middle of the river is gaining land through sedimentation and the both side river bank is shifting causing severe erosion that consequently resulting the loss of farmland and homestead. Over the study period from 1995 to 2015 it witnessed huge erosion and accretion that played an active role in the changes of the river bank.

Keywords: river bank, erosion and accretion, change monitoring, remote sensing

Procedia PDF Downloads 319

Authors: Veena N. Hegde, S. R. Desai

Abstract:

Motivating a heterogeneous group of students towards engagement in research related activities is a challenging task in engineering education. An effort is being made at the Department of Electronics and Instrumentation Engineering, where two courses are taken up on a pilot basis to kindle research interests in students at the undergraduate level. The courses, namely algorithm and system design (ASD) and automation in process control (APC), are selected for experimentation purposes. The task is being accomplished by providing scope for implementation of research papers and proposing solutions for the current industrial problems by the student teams. The course instructors have proposed an alternative assessment tool to evaluate the undergraduate students that involve activities beyond the curriculum. The method was tested for the aforementioned two courses in a particular academic year, and as per the observations, there is a considerable improvement in the number of student engagement towards research in the subsequent years of their undergraduate course. The student groups from the third-year engineering were made to read, implement the research papers, and they were also instructed to develop simulation modules for certain processes aiming towards automation. The target audience being students, were common for both the courses and the students' strength was 30. Around 50% of successful students were given the continued tasks in the subsequent two semesters, and out of 15 students who continued from sixth semesters were able to follow the research methodology well in the seventh and eighth semesters. Further, around 30% of the students out of 15 ended up carrying out project work with a research component involved and were successful in producing four conference papers. The methodology adopted is justified using a sample data set, and the outcomes are highlighted. The quantitative and qualitative results obtained through this study prove that such practices will enhance learning experiences substantially at the undergraduate level.

Keywords: industrial problems, learning experiences, research related activities, student engagement

Procedia PDF Downloads 162

Authors: Kaori Narita, Juan de Dios Tena Horrillo, Claudio Detotto

Abstract:

Decisions on replacement of leaders are of significance and high prevalence in any organization, and concerns many of its stakeholders, whether it is a leader in a political party or a CEO of a firm, as indicated by high media coverage of such events. This merits an investigation into the consequences and implications of a leadership change on the performances and behavior of organizations and their workers. Sport economics provides a fruitful field to explore these issues due to the high frequencies of managerial changes in professional sports clubs and the transparency and regularity of observations of team performance and players’ abilities. Much of the existing research on managerial change focuses on how this affects the performance of an organization. However, there is scarcely attention paid to the consequences of such events on the behavior of individuals within the organization. Changes in behavior and attitudes of a group of workers due to a managerial change could be of great interest in management science, psychology, and operational research. On the other hand, these changes cannot be observed in the final outcome of the organization, as this is affected by many other unobserved shocks, for example, the stress level of workers with the need to deal with a difficult situation. To fill this gap, this study shows the first attempt to evaluate the impact of managerial change on players’ behaviors such as attack intensity, aggressiveness, and efforts. The data used in this study is from the top tier Italian football league (“Serie A”), where an average of 13 within season replacements of head coaches were observed over the period of seasons from 2000/2001 to 2017/18. The preliminary estimation employs Pooled Ordinary Least Square (POLS) and club-season Fixed Effect (FE) in order to assess the marginal effect of having a new manager on the number of shots, corners and red/yellow cards after controlling for a home-field advantage, ex ante abilities and current positions in the league of a team and their opponent. The results from this preliminary estimation suggest that the teams do not show a significant difference in their behaviors before and after the managerial change. To build on these preliminary results, other methods, including propensity score matching and non-linear model estimates, will be used. Moreover, the study will further investigate these issues by considering other measurements of attack intensity, aggressiveness, and efforts, such as possessions, a number of fouls and the athletic performance of players, respectively. Finally, the study is going to investigate whether these results vary over the characteristics of a new head coach, for example, their age and experience as a manager and a player. Thus far, this study suggests that certain behaviours of individuals in an organisation are not immediately affected by a change in leadership. To confirm this preliminary finding and lead to a more solid conclusion, further investigation will be conducted in the aforementioned manner, and the results will be elaborated in the conference.

Keywords: behaviour, effort, manager characteristics, managerial change, sport economics

Procedia PDF Downloads 130

Authors: Eric Yi-Hsiu Huang, Meng-Chun Kao, Wen-Chuan Kuo

Abstract:

For every laparoscopic surgery, a safe pneumoperitoneumcreation (gaining access to the peritoneal cavity) is the first and essential step. However, closed pneumoperitoneum is usually obtained by blind insertion of a Veress needle into the peritoneal cavity, which may carry potential risks suchas bowel and vascular injury.Until now, there remains no definite measure to visually confirm the position of the needle tip inside the peritoneal cavity. Therefore, this study established an image-guided Veress needle method by combining a fiber probe with optical coherence tomography (OCT). An algorithm was also proposed for determining the exact location of the needle tip through the acquisition of OCT images. Our method not only generates a series of “live” two-dimensional (2D) images during the needle puncture toward the peritoneal cavity but also can eliminate operator variation in image judgment, thus improving peritoneal access safety. This study was approved by the Ethics Committee of Taipei Veterans General Hospital (Taipei VGH IACUC 2020-144). A total of 2400 in vivo OCT images, independent of each other, were acquired from experiments of forty peritoneal punctures on two piglets. Characteristic OCT image patterns could be observed during the puncturing process. The ROC curve demonstrates the discrimination capability of these quantitative image features of the classifier, showing the accuracy of the classifier for determining the inside vs. outside of the peritoneal was 98% (AUC=0.98). In summary, the present study demonstrates the ability of the combination of our proposed automatic identification method and OCT imaging for automatically and objectively identifying the location of the needle tip. OCT images translate the blind closed technique of peritoneal access into a visualized procedure, thus improving peritoneal access safety.

Keywords: pneumoperitoneum, optical coherence tomography, automatic identification, veress needle

Procedia PDF Downloads 126

Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

Abstract:

Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector

Procedia PDF Downloads 330

Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

Procedia PDF Downloads 370

Authors: Minjeong Kim, Seungchul Lee, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

Abstract:

A trajectory of set-point of ventilation control systems plays an important role for efficient ventilation inside subway stations since it affects the level of indoor air pollutants and ventilation energy consumption. To maintain indoor air quality (IAQ) at a comfortable range with lower ventilation energy consumption, the optimal trajectory of the ventilation control system needs to be determined. The concentration of air pollutants inside the station shows a diurnal variation in accordance with the variations in the number of passengers and subway frequency. To consider the diurnal variation of IAQ, an iterative dynamic programming (IDP) that searches for a piecewise control policy by separating whole duration into several stages is used. When outdoor air is contaminated by pollutants, it enters the subway station through the ventilation system, which results in the deteriorated IAQ and adverse effects on passenger health. In this study, to consider the influence of outdoor air quality (OAQ), a new performance index of the IDP with the passenger health risk and OAQ is proposed. This study was carried out for an underground subway station at Seoul Metro, Korea. The optimal set-points of the ventilation control system are determined every 3 hours, then, the ventilation controller adjusts the ventilation fan speed according to the optimal set-point changes. Compared to manual ventilation system which is operated irrespective of the OAQ, the IDP-based ventilation control system saves 3.7% of the energy consumption. Compared to the fixed set-point controller which is operated irrespective of the IAQ diurnal variation, the IDP-based controller shows better performance with a 2% decrease in energy consumption, maintaining the comfortable IAQ range inside the station.

Keywords: indoor air quality, iterative dynamic algorithm, outdoor air information, ventilation control system

Procedia PDF Downloads 499

Authors: Emine Umran Topcu

Abstract:

In both urban design and architecture, the primary goal is considered to be looking for ways in which people feel and think about space and place. Humans, in general, see a place as security and space as freedom and feel attached to place and long for space. Contemporary urban design manifests itself by addressing basic physical and psychological human needs. Not much attention is paid to transcendence. There seems to be a gap in the hierarchy of human needs. Usually, social aspects of public space are addressed through urban design. More personal and intimately scaled needs of an individual are neglected. How does built form contribute to an individual’s growth, contemplation, and exploration? In other words, a greater meaning in the immediate environment. Architects love to talk about meaning, poetics, attachment and other ethereal aspects of space that are not visible attributes of places. This paper aims at describing spirituality through built form with a personal experience of Kamppi Chapel of Helsinki. Experience covers various modes through which a person unfolds or constructs reality. Perception, sensation, emotion, and thought can be counted as for these modes. To experience is to get to know. What can be known is a construct of experience. Feelings and thoughts about space and place are very complex in human beings. They grow out of life experiences. The author had the chance of visiting Kamppi Chapel in April 2017, out of which the experience grew. The Kamppi Chapel is located on the South side of the busy Narinnka Square in central Helsinki. It offers a place to quiet down and compose oneself in a most lively urban space. With its curved wooden facade, the small building looks more like a museum than a chapel. It can be called a museum for contemplation. With its gently shaped interior, it embraces visitors and shields them from the hustle bustle of the city outside. Places of worship in all faiths signify sacred power. The author, having origins in a part of the world where domes and minarets dominate the cityscape, was impressed by the size and the architectural visibility of the Chapel. Anyone born and trained in such a tradition shares the inherent values and psychological mechanisms of spirituality, sacredness and the modest realities of their environment. Spirituality in all cultural traditions has not been analyzed and reinterpreted in new conceptual frameworks. Fundamentalists may reject this positivist attitude, but Kamppi Chapel as it stands does not look like it has a say like “I’m a model to be followed”. It just faces the task of representing a religious facility in an urban setting largely shaped by modern urban planning, which seems to the author as looking for a new definition of individual status. The quest between the established and the new is the demand for modern efficiency versus dogmatic rigidity. The architecture here has played a very promising and rewarding role for spirituality. The designers have been the translators for human desire for better life and aesthetic environment for an optimal satisfaction of local citizens and the visitors alike.

Keywords: architecture, Kamppi Chapel, spirituality, urban

Procedia PDF Downloads 180

Authors: Magu Raam Prasaad R., Venkatramani Jagadish

Abstract:

Recent studies in the literature have shown that randomly fluctuating wind flows can give rise to a distinct regime of pre-flutter oscillations called intermittency. Intermittency is characterized by the presence of sporadic bursts of high amplitude oscillations interspersed amidst low-amplitude aperiodic fluctuations. The focus of this study is on investigating the energy harvesting potential of these intermittent oscillations. Available literature has by and large devoted its attention on extracting energy from flutter oscillations. The possibility of harvesting energy from pre-flutter regimes have remained largely unexplored. However, extracting energy from violent flutter oscillations can be severely detrimental to the structural integrity of airfoil structures. Consequently, investigating the relatively stable pre-flutter responses for energy extraction applications is of practical importance. The present study is devoted towards addressing these concerns. A pitch-plunge airfoil with cubic hardening nonlinearity in the plunge and pitch degree of freedom is considered. The input flow fluctuations are modelled using a sinusoidal term with randomly perturbed frequencies. An electromagnetic coupling is provided to the pitch-plunge equations, such that, energy from the wind induced vibrations of the structural response are extracted. With the mean flow speed as the bifurcation parameter, a fourth order Runge-Kutta based time marching algorithm is used to solve the governing aeroelastic equations with electro-magnetic coupling. The harnessed energy from the intermittency regime is presented and the results are discussed in comparison to that obtained from the flutter regime. The insights from this study could be useful in health monitoring of aeroelastic structures.

Keywords: aeroelasticity, energy harvesting, intermittency, randomly fluctuating flows

Procedia PDF Downloads 183

Authors: Kunyaporn Pipithsangchan, Alongkorn Korntong, Assanee Songserm, Phatchara Piriyavinit, Saowanee Dechakampoo

Abstract:

The Kingdom of Thailand is one of the South East Asian countries. From its area of 514,000 square kilometers (51 million ha), at least 18,000 plant species (8% of the world total) have been estimated to be found in the country. As a result, the conservation of plant genetic diversity, particularly food crops, is becoming important and is an assurance for the national food security. Department of Agriculture Genebank or DOA Genebank, Thailand is responsible for the conservation of plant germplasm by participating and accomplishing several collaborative projects both at national and international levels. Integrated Management System of Plant Genetic Resources or IMPGR is one of the most outstandingly successful cooperation. It is a multilateral project under the Asian Food and Agriculture Cooperation Initiative (AFACI) supported by the Rural Development Administration (RDA) of South Korea. The member countries under the project consist of 11 nations namely Bangladesh, Cambodia, Indonesia, Laos PDR, Mongolia, Nepal, Philippines, Sri Lanka, Thailand, Vietnam and South Korea. The project enabled the members to jointly address the global issues in plant genetic resource (PGR) conservation and strengthen their network in this aspect. The 1st phase of IMPGR project, entitled 'Collection, Conservation, Regeneration and Characterization of Cucurbitaceae and Solanaceae 2012-2014', comprises three main objectives that are: 1) To improve management in storage facilities, collection, and regeneration, 2) To improve linkage between Genebank and material sources (for regeneration), and 3) To improve linkage between Genebank and other field crop or/and horticultural research centers. The project was done for three years from 2012 to 2014. The activities of the project can be described as following details: In the 1st year, there were 9 target provinces for completing plant genetic resource survey and collection. 108 accessions of PGR were collected. In the 2nd year, PGR were continuously surveyed and collected from 9 provinces. The total number of collection was 140 accessions. In addition, the process of regeneration of 237 accessions collected from 1st and 2nd year was started at several sites namely Biotechnology Research and Development Office, Sukothai Horticultural Research Center, Tak Research, and Development Center and Nakhon Ratchasima Research and Development Center. In the 3rd year, besides survey and collection of 115 accessions from 9 target provinces, PGR characterization and evaluation were done for 206 accessions. Moreover, safety duplication of 253 PGR at the World Seed Vault, RDA, was also done according to Standard Agreement on Germplasm Safety Duplication between Department of Agriculture, Ministry of Agriculture and Cooperatives, the Kingdom of Thailand and the National Agrobiodiversity Center, Rural Development Administration of the Republic of Korea. The success of the 1st phase project led to the second phase which entitled 'Collection and Characterization for Effective Conservation of Local Capsicum spp., Solanum spp. and Lycopersicon spp. in Thailand 2015-2017'.

Keywords: characterization, conservation, DOA genebank, plant genetic resources

Procedia PDF Downloads 172

Authors: Faris Tarlochan, Siva Mahesh Tangutooru

Abstract:

Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies, each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 µm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral Geniculate Nucleus, visual cortex, finite element, glaucoma, neuroprostheses

Procedia PDF Downloads 268

Authors: Othman Maklouf, Abdunnaser Tresh

Abstract:

Land vehicle navigation is subject of great interest today. Global Positioning System (GPS) is the main navigation system for positioning in such systems. GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation (INS) is the implementation of inertial sensors to determine the position and orientation of a vehicle. The availability of low-cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop INS using an inertial measurement unit (IMU). INS has unbounded error growth since the error accumulates at each step. Usually, GPS and INS are integrated with a loosely coupled scheme. With the development of low-cost, MEMS inertial sensors and GPS technology, integrated INS/GPS systems are beginning to meet the growing demands of lower cost, smaller size, and seamless navigation solutions for land vehicles. Although MEMS inertial sensors are very inexpensive compared to conventional sensors, their cost (especially MEMS gyros) is still not acceptable for many low-end civilian applications (for example, commercial car navigation or personal location systems). An efficient way to reduce the expense of these systems is to reduce the number of gyros and accelerometers, therefore, to use a partial IMU (ParIMU) configuration. For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a field experiment for a low-cost strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach, we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of our low-cost IMU (Inertial Measurement Unit) and because of the relatively small area of the trajectory.

Keywords: GPS, IMU, Kalman filter, materials engineering

Procedia PDF Downloads 413

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

Abstract:

Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

Procedia PDF Downloads 125

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 84

Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

Abstract:

The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

Procedia PDF Downloads 143

Authors: Ishan Naidu, Jessica Ryvlin, Devin Videlefsky

Abstract:

Introduction: Back pain is a leading cause of years lived with disability and economic burden, exceeding over $20 billion in healthcare costs not including indirect costs such as absence from work and caregiving. The multifactorial nature of back pain leads to treatment modalities administered by a variety of specialists, which are often disjointed. Multiple studies have found that patients receiving delayed physical therapy for lower back pain had higher medical-related costs from increased health service utilization as well as a reduced improvement in pain severity compared to early management. Uncoordinated health care delivery can exacerbate the physical and economic toll of the chronic condition, thus improvements in interdisciplinary, shared decision-making may improve outcomes. Objective: To assess whether a multidisciplinary spine clinic (MSC), consisting of orthopedic surgery, neurosurgery, pain medicine, and physiatry, alters interventional and non-interventional planning and treatment compared to a traditional unidisciplinary spine clinic (USC) including only orthopedic surgery. Methods: We conducted a retrospective cohort study with patients initially presenting for spine care to orthopedic surgeons between July 1, 2018 to June 30, 2019. Time to treatment recommendation, time to treatment and rates of treatment recommendations were assessed, including physical therapy, injections and surgery. Treatment rates were compared between MSC and USC using Pearson’s chi-square test logistic regression. Time to treatment recommendation and time to treatment were compared using log-rank test and Cox proportional hazard regression. All analyses were repeated for the propensity score (PS) matched subsample. Results: This study included 1,764 patients, with 692 at MSC and 1,072 at USC. Patients in MSC were more likely to be recommended injection when compared to USC (8.5% vs. 5.4%, p=0.01). When adjusted for confounders, the likelihood of injection recommendation remained greater in MSC than USC (Odds ratio [OR]=2.22, 95% CI: (1.39, 3.53), p=0.001). MSC was also associated with a shorter time to receiving injection recommendation versus USC (median: 21 vs. 32 days, log-rank: p<0.001; hazard ratio [HR]=1.90, 95% CI: (1.25, 2.90), p=0.003). MSC was associated with a higher likelihood of injection treatment (OR=2.27, 95% CI: (1.39, 3.73), p=0.001) and shorter lead time (HR=1.98, 95% CI: (1.27, 3.09), p=0.003). PS-matched analyses yielded similar conclusions. Conclusions: Care delivered at a multidisciplinary spine clinic was associated with a higher likelihood of recommending injection and a shorter lead time to injection administration when compared to a traditional unidisciplinary spine surgery clinic. Multidisciplinary clinics may facilitate coordinated care amongst different specialties resulting in increased utilization of less invasive treatment modalities while also improving care efficiency. The multidisciplinary clinic model is an important advancement in care delivery and communication, which can be used as a powerful method of improving patient outcomes as treatment guidelines evolve.

Keywords: coordinated care, epidural steroid injection, multi-disciplinary, non-invasive

Procedia PDF Downloads 139

Authors: Oumaima Khlifati, Khadija Baba

Abstract:

Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

Procedia PDF Downloads 85

Authors: Abdulmohsen Alruwaili

Abstract:

A partial differential system featuring momentum and energy balance is often used to describe simulations of flow initiation and thermal shifting in boundary layers. The buoyancy force in terms of temperature is factored in the momentum balance equation. Buoyancy force causes the flow quantity to fluctuate along the streamwise direction 𝑋; therefore, the problem can be, to our best knowledge, analyzed through nonsimilar modeling. In this analysis, a nonsimilar model is evolved for radiative mixed convection of a magnetized power-law nanoliquid flow on top of a vertical plate installed in a stationary fluid. The upward linear stretching initiated the flow in the vertical direction. Assuming nanofluids are composite of copper (Cu) and alumina (Al₂O₃) nanoparticles, the viscous dissipation in this case is negligible. The nonsimilar system is dealt with analytically by local nonsimilarity (LNS) via numerical algorithm bvp4c. Surface temperature and flow field are shown visually in relation to factors like mixed convection, magnetic field strength, nanoparticle volume fraction, radiation parameters, and Prandtl number. The repercussions of magnetic and mixed convection parameters on the rate of energy transfer and friction coefficient are represented in tabular forms. The results obtained are compared to the published literature. It is found that the existence of nanoparticles significantly improves the temperature profile of considered nanoliquid. It is also observed that when the estimates of the magnetic parameter increase, the velocity profile decreases. Enhancement in nanoparticle concentration and mixed convection parameter improves the velocity profile.

Keywords: nanofluid, power law model, mixed convection, thermal radiation

Procedia PDF Downloads 21

Authors: Leizhang Wang, Baocang Wang

Abstract:

General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

Procedia PDF Downloads 58

Authors: Biruk Wolde, Atalay Ayele, Yonatan Garkabo, Trufat Hailmariam, Zemenu Germewu

Abstract:

A comprehensive three-dimensional (3D) geological modeling and engineering geological characterization of shallow subsurface soils and rocks are essential for a wide range of geotechnical and seismological engineering applications, particularly in urban environments. The spatial distribution and geological variation of the shallow subsurface of Addis Ababa city have not been studied so far in terms of geological and geotechnical modeling. This study aims at the construction of a 3D geological model, as well as provides awareness into the engineering geological characteristics of shallow subsurface soil and rock of Addis Ababa city. The 3D geological model was constructed by using more than 1500 geotechnical boreholes, well-drilling data, and geological maps. A well-known geostatistical kriging 3D interpolation algorithm was applied to visualize the spatial distribution and geological variation of the shallow subsurface. Due to the complex nature of geological formations, vertical and lateral variation of the geological profiles horizons-solid command has been selected via the Groundwater Modelling System (GMS) graphical user interface software. For the engineering geological characterization of typical soils and rocks, both index and engineering laboratory tests have been used. The geotechnical properties of soil and rocks vary from place to place due to the uneven nature of subsurface formations observed in the study areas. The constructed model ascertains the thickness, extent, and 3D distribution of the important geological units of the city. This study is the first comprehensive research work on 3D geological modeling and subsurface characterization of soils and rocks in Addis Ababa city, and the outcomes will be important for further future research on subsurface conditions in the city. Furthermore, these findings provide a reference for developing a geo-database for the city.

Keywords: 3d geological modeling, addis ababa, engineering geology, geostatistics, horizons-solid

Procedia PDF Downloads 89

Authors: Ajay Kumar Pandey

Abstract:

White grub (Coleoptera: Scarabaeidae), locally known as Kurmula, Pagra, Chinchu, is a major destructive pest in western Himalayan region of Uttarakhand state of India. Various crops like cereals (up land paddy, wheat, and barley), vegetables (capsicum, cabbage, tomato, cauliflower, carrot etc) and some pulse (like pigeon pea, green gram, black gram) are grown with limited availability of primary resources. Among the various limitations in successful cultivation of these crops, white grub has been proved a major constraint in for all crops grown in hilly area. The losses incurred due to white grubs are huge in case of commercial crops like sugarcane, groundnut, potato, maize and upland rice. Moreover, it has been proved major constraint in potato production in mid and higher hills of India. Adults emerge in May-June following the onset of monsoon and thereafter defoliate the apple, apricot, plum, and walnut during night while 2nd and 3rd instar grubs feed on live roots of cultivated as well as non cultivated crops from August to January. Survey was conducted in hilly (Pauri and Tehri) as well as plain area (Haridwar district) of Uttarakhand state. Collection of beetle was done from various locations from August to September of five consecutive years with the help of light trap and directly from host plant. The grub was also collected by excavating one square meter area from different locations and reared in laboratory to find out adult. During the collection, the diseased or dead cadaver were also collected and brought in the laboratory and identified the causal organisms. Total 25 species of white grub was identified out of which Holotrichia longipennis, Anomala dimidiata, Holotrichia lineatopennis, Maladera insanabilis, Brahmina sp. make complex problem in different area of Uttarakhand where they cause severe damage to various crops. During the survey, it was observed that white grubs beetles have variation in preference of host plant, even in choice of fruit and leaves of host plant. It was observed that, a white grub species, which identified as Lepidiota mansueta Burmeister., was causing severe havoc to sugarcane crop grown in major sugarcane growing belt of Haridwar district. The study also revealed that Bacillus cereus, Beauveria bassiana, Metarhizium anisopliae, Steinernema, Heterorhabditis are major disease causing agents in immature stage of white grub under rain-fed condition of Uttarakhand which caused 15.55 to 21.63 percent natural mortality of grubs with an average of 18.91 percent. However, among the microorganisms, B. cereus found to be significantly more efficient (7.03 percent mortality) then the entomopathogenic fungi (3.80 percent mortality) and nematodes (3.20 percent mortality).

Keywords: Lepidiota, profiling, Uttarakhand, whitegrub

Procedia PDF Downloads 218

Authors: Andrea Ghermandi

Abstract:

Natural treatment systems such as constructed wetlands and waste stabilization ponds are increasingly used to treat water and wastewater from a variety of sources, including stormwater and polluted surface water. The provision of ancillary benefits in the form of cultural ecosystem services makes these systems unique among water and wastewater treatment technologies and greatly contributes to determine their potential role in promoting sustainable water management practices. A quantitative analysis of these benefits, however, has been lacking in the literature. Here, a critical assessment of the recreational and educational benefits in natural treatment systems is provided, which combines observed public use from a survey of managers and operators with estimated public use as obtained using geotagged photos from social media as a proxy for visitation rates. Geographic Information Systems (GIS) are used to characterize the spatial boundaries of 273 natural treatment systems worldwide. Such boundaries are used as input for the Application Program Interfaces (APIs) of two popular photo-sharing websites (Flickr and Panoramio) in order to derive the number of photo-user-days, i.e., the number of yearly visits by individual photo users in each site. The adequateness and predictive power of four univariate calibration models using the crowdsourced data as a proxy for visitation are evaluated. A high correlation is found between photo-user-days and observed annual visitors (Pearson's r = 0.811; p-value < 0.001; N = 62). Standardized Major Axis (SMA) regression is found to outperform Ordinary Least Squares regression and count data models in terms of predictive power insofar as standard verification statistics – such as the root mean square error of prediction (RMSEP), the mean absolute error of prediction (MAEP), the reduction of error (RE), and the coefficient of efficiency (CE) – are concerned. The SMA regression model is used to estimate the intensity of public use in all 273 natural treatment systems. System type, influent water quality, and area are found to statistically affect public use, consistently with a priori expectations. Publicly available information regarding the home location of the sampled visitors is derived from their social media profiles and used to infer the distance they are willing to travel to visit the natural treatment systems in the database. Such information is analyzed using the travel cost method to derive monetary estimates of the recreational benefits of the investigated natural treatment systems. Overall, the findings confirm the opportunities arising from an integrated design and management of natural treatment systems, which combines the objectives of water quality enhancement and provision of cultural ecosystem services through public use in a multi-functional approach and compatibly with the need to protect public health.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, waste stabilization ponds

Procedia PDF Downloads 175