Search results for: energy modeling techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16859

Search results for: energy modeling techniques

4589 Study on the Effect of Weather Variables on the Spider Abundance in Two Ecological Zones of Ogun State, Nigeria

Authors: Odejayi Adedayo Olugbenga, Aina Adebisi

Abstract:

Weather variables (rainfall and temperature) affect the diversity and abundance of both fauna and flora species. This study compared the weather variables with spider abundance in two ecological zones of Ogun State, Nigeria namely Ago-iwoye (Rainforest) in the Ijebu axis and Aiyetoro (Derived Savannah) in the Yewa axis. Seven study sites chosen by Simple Random Sampling in each ecosystem were used for the study. In each sampling area, a 60 m x 120 m land area was marked and sampled, spider collection techniques were; hand picking, use of sweep netting, and Pitfall trap. Adult spiders were identified to the species level. Species richness was estimated by a non-parametric species estimator while the diversity of spider species was assessed by Simpson Diversity Index and Species Richness by One-way Analysis of Variance. Results revealed that spiders were more abundant in rainforest zones than in derived savannah ecosystems. However, the pattern of spider abundance in rainforest zone and residential areas were similar. During high temperatures, the activities of spiders tended to increase according to this study. In contrast, results showed that there was a negative correlation between rainfall and spider species abundance in addition to a negative and weak correlation between rainfall and species richness. It was concluded that heavy downpour has lethal effects on both immature and sometimes matured spiders, which could lead to the extinction of some unknown species of spiders. Tree planting should be encouraged, as this shelters the spider.

Keywords: spider, abundance, species richness, species diversity

Procedia PDF Downloads 65
4588 Exclusive Value Adding by iCenter Analytics on Transient Condition

Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

Abstract:

During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

Procedia PDF Downloads 54
4587 A Comparative Evaluation of Stone Spout Management Systems in Heritage and Non-heritage Areas of the Kathmandu Valley, Nepal

Authors: Mira Tripathi, Ken Hughey, Hamish G. Rennie

Abstract:

Management of water resources is a major challenge throughout the world and in many long-established societies people still use traditional water harvesting and management techniques. Despite often being seen as efficient and cost effective, traditional methods are in decline or have been abandoned in many countries. Nevertheless, traditional approaches continue to be useful in some countries such as Nepal. The extent to which such traditional measures, in this case via stone spouts, may survive modernization, while fulfilling socio-cultural, tourism, and other needs is the focus of the research. The research develops an understanding of the socio-cultural, tourism and other values of stone spouts for the people of urban and peri-urban heritage and non-heritage areas of the Kathmandu Valley to help ongoing sustainable management of remaining spouts. Three research questions are addressed: the impacts of changes in social and cultural norms and values; development activities; and, the incremental and ongoing loss of traditional stone spout infrastructure. A meta-theory framework has been developed which synthesizes Institutional, Attachment, Central Place and Common Property theories, which form analytical lenses for the mixed-method research approach. From the exploration of the meta-theory approach, it was found that no spouts are in pristine condition but those in non-heritage areas are in better condition than those in heritage areas. “Utility value” is the main driver that still motivates people to conserve spouts.

Keywords: stone spouts, social and cultural norms and values, meta-theory, Kathmandu Valley

Procedia PDF Downloads 290
4586 [Keynote Speech]: Simulation Studies of Pulsed Voltage Effects on Cells

Authors: Jiahui Song

Abstract:

In order to predict or explain a complicated biological process, it is important first to construct mathematical models that can be used to yield analytical solutions. Through numerical simulation, mathematical model results can be used to test scenarios that might not be easily attained in a laboratory experiment, or to predict parameters or phenomena. High-intensity, nanosecond pulse electroporation has been a recent development in bioelectrics. The dynamic pore model can be achieved by including a dynamic aspect and a dependence on the pore population density into pore formation energy equation to analyze and predict such electroporation effects. For greater accuracy, with inclusion of atomistic details, molecular dynamics (MD) simulations were also carried out during this study. Besides inducing pores in cells, external voltages could also be used in principle to modulate action potential generation in nerves. This could have an application in electrically controlled ‘pain management’. Also a simple model-based rate equation treatment of the various cellular bio-chemical processes has been used to predict the pulse number dependent cell survival trends.

Keywords: model, high-intensity, nanosecond, bioelectrics

Procedia PDF Downloads 206
4585 Highly Efficient Iron Oxide-Sulfonated Graphene Oxide Catalyst for Esterification and Trans-Esterification Reactions

Authors: Reena D. Souza, Tripti Vats, Prem F. Siril

Abstract:

Esterification of free fatty acid (oleic acid) and transesterification of waste cooking oil (WCO) with ethanol over graphene oxide (GO), GO-Fe2O3, sulfonated GO (GO-SO3H), and Fe2O3/GO-SO3H catalysts were examined in the present study. Iron oxide supported graphene-based acid catalyst (Fe2O3/GO-SO3H) exhibited highest catalytic activity. GO was prepared by modified Hummer’s process. The GO-Fe2O3 nanocomposites were prepared by the addition of NaOH to a solution containing GO and FeCl3. Sulfonation was done using concentrated sulfuric acid. Transmissionelectron microscopy (TEM) and atomic force microscopy (AFM) imaging revealed the presence of Fe2O3 particles having size in the range of 50-200 nm. Crystal structure was analyzed by XRD and defect states of graphene were characterized using Raman spectroscopy. The effects of the reaction variables such as catalyst loading, ethanol to acid ratio, reaction time and temperature on the conversion of fatty acids were studied. The optimum conditions for the esterification process were molar ratio of alcohol to oleic acid at 12:1 with 5 wt% of Fe2O3/GO-SO3H at 1000C with a reaction time of 4h yielding 99% of ethyl oleate. This is because metal oxide supported solid acid catalysts have advantages of having both strong Brønsted as well as Lewis acid properties. The biodiesel obtained by transesterification of WCO was characterized by 1H NMR and Gas Chromatography techniques. XRD patterns of the recycled catalyst evidenced that the catalyst structure was unchanged up to the 5th cycle, which indicated the long life of the catalyst.

Keywords: Fe₂O₃/GO-SO₃H, Graphene Oxide, GO-Fe₂O₃, GO-SO₃H, WCO

Procedia PDF Downloads 251
4584 Determination of Critical Organ Doses for Liver Scintigraphy Using Cr-51

Authors: O. Maranci, A. B. Tugrul

Abstract:

Scintigraphy is an imaging method of nuclear events provoked by collisions or charged current interactions with radiation. It is used for diagnostic test used in nuclear medicine via radiopharmaceuticals emitting radiation which is captured by gamma cameras to form two-dimensional images. Liver scintigraphy is widely used in nuclear medicine.Tc-99m and Cr-51 gamma radioisotopes can be used for this purpose. Cr-51 usage is more important for patients’ organ dose that has higher energy and longer half-life as compared to Tc-99m. In this study, it is aimed to determine the required dose for critical organs of patient through liver scintigraphy via Cr-51 gamma radioisotope. Experimental studies were conducted on patients even though conducting experimental studies on patients is extremely difficult for determination of critical organ doses. Torso phantom was utilized to simulate the liver scintigraphy by using 20 mini packages of Cr-51 that were placed on the organ. The radioisotope was produced by irradiation in central thimble of TRIGA MARK II Reactor at 250 KW power. As the results of the study, critical organ doses were determined and evaluated with different critic organs.

Keywords: critical organ doses, liver, scintigraphy, TRIGA Mark-II

Procedia PDF Downloads 533
4583 Management of Coronary Heart Disease through Yoga

Authors: Subramaniam Iyer

Abstract:

The most common disease that is pertaining to all human beings is heart-related. The reasons for coronary artery disease are due to lifestyle and eating habits. Due to this, many people mentally become sick, feeling that soon they will die due to their heart problems. This results in stress and anxiety, which has become common amongst all the Indians. Medicines are the commonest curative remedy in India, but it is proposed through this article some remedies through yoga. This article does not guarantee a 100% result, but it is a preventive remedy for coronary artery disease. Yoga is giving a new lease of life to many, so to tackle chronic diseases, it provides remedies that will be lifelong. It is brought to many people by Patanjali. Yoga will provide support to patients having coronary artery disease through its various relevant postures (asanas), which can be done very easily. Yoga does not send a message that if you do it regularly, you will be relieved from a particular disease. If it is performed every day, it will add vital energy for a smooth life, even if you are suffering from any chronic disease. In this article, we will be providing 6 postures (asanas), which can be performed at any time in the day, but the early morning will always be preferred (empty stomach) to get a good result. Secondly, these postures must be implemented after due consultation with your physician. If your physician disapproves, don’t do these postures as it will be harmful to your body.

Keywords: coronary artery, yoga, disease, remedy, medicine

Procedia PDF Downloads 139
4582 Alternative Approach to the Machine Vision System Operating for Solving Industrial Control Issue

Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

Abstract:

The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

Procedia PDF Downloads 90
4581 Dimension of Water Accessibility in the Southern Part of Niger State, Nigeria

Authors: Kudu Dangana, Pai H. Halilu, Osesienemo R. Asiribo-Sallau, Garba Inuwa Kuta

Abstract:

The study examined the determinants of household water accessibility in Southern part of Niger State, Nigeria. Data for the study was obtained from primary and secondary sources using questionnaire, interview, personal observation and documents. 1,192 questionnaires were administered; sampling techniques adopted are combination of purposive, stratified and simple random. Purposive sampling technique was used to determine sample frame; sample unit was determined using stratified sampling method and simple random technique was used in administering questionnaires. The result was analyzed within the scope of “WHO” water accessibility indicators using descriptive statistics. Major sources of water in the area are well; hand and electric pump borehole and streams. These sources account for over 90% of household’s water. Average per capita water consumption in the area is 22 liters per day, while location efficiency of facilities revealed an average of 80 people per borehole. Household water accessibility is affected mainly by the factors of distances, time spent to obtain water, low income status of the majority of respondents to access modern water infrastructure, and to a lesser extent household size. Recommendations includes, all tiers of government to intensify efforts in providing water infrastructures and existing ones through budgetary provisions, and communities should organize fund raising bazaar, so as to raise fund to improve water infrastructures in the area.

Keywords: accessibility, determined, stratified, scope

Procedia PDF Downloads 369
4580 Self-Determination among Individuals with Intellectual Disability: An Experiment

Authors: Wasim Ahmad, Bir Singh Chavan, Nazli Ahmad

Abstract:

Objectives: The present investigation is an attempt to find out the efficacy of training the special educators on promoting self-determination among individuals with intellectual disability. Methods: The study equipped the special educators with necessary skills and knowledge to train individuals with the intellectual disability for practicing self-determination. Subjects: Special educators (N=25) were selected for training on self-determination among individuals with intellectual disability. After receiving the training, (N=50) individuals with an intellectual disability were selected and intervened by the trained special educators. Tool: Self-Determination Scale for Adults with Mild Mental Retardation (SDSAMR) developed by Keshwal and Thressiakutty (2010) has been used. It’s a reliable and valid tool used by many researchers. It has 36 items distributed in five domains namely: personal management, community participation, recreation and leisure time, choice making and problem solving. Analysis: The collected data was analyzed using the statistical techniques such as t-test, ANCOVA, and Posthoc Tuckey test. Results: The findings of the study reveal that there is a significant difference at 1% level in the pre and post tests mean scores (t-15.56) of self-determination concepts among the special educators. This indicates that the training enhanced the performance of special educators on the concept of self-determination among individuals with intellectual disability. The study also reveals that the training received on transition planning by the special educators found to be effective because they were able to practice the concept by imparting and training the individuals with intellectual disability to if determined. The results show that there was a significant difference at 1% level in the pre and post tests mean scores (t-16.61) of self-determination among individuals with intellectual disability. Conclusion: To conclude it can be said that the training has a remarkable impact on the performance of the individuals with intellectual disability on self-determination.

Keywords: experiment, individuals with intellectual disability, self-determination, special educators

Procedia PDF Downloads 311
4579 Thermally Stable Nanocrystalline Aluminum Alloys Processed by Mechanical Alloying and High Frequency Induction Heat Sintering

Authors: Hany R. Ammar, Khalil A. Khalil, El-Sayed M. Sherif

Abstract:

The as-received metal powders were used to synthesis bulk nanocrystalline Al; Al-10%Cu; and Al-10%Cu-5%Ti alloys using mechanical alloying and high frequency induction heat sintering (HFIHS). The current study investigated the influence of milling time and ball-to-powder (BPR) weight ratio on the microstructural constituents and mechanical properties of the processed materials. Powder consolidation was carried out using a high frequency induction heat sintering where the processed metal powders were sintered into a dense and strong bulk material. The sintering conditions applied in this process were as follow: heating rate of 350°C/min; sintering time of 4 minutes; sintering temperature of 400°C; applied pressure of 750 Kgf/cm2 (100 MPa); cooling rate of 400°C/min and the process was carried out under vacuum of 10-3 Torr. The powders and the bulk samples were characterized using XRD and FEGSEM techniques. The mechanical properties were evaluated at various temperatures of 25°C, 100°C, 200°C, 300°C and 400°C to study the thermal stability of the processed alloys. The bulk nanocrystalline Al; Al-10%Cu; and Al-10%Cu-5%Ti alloys displayed extremely high hardness values even at elevated temperatures. The Al-10%Cu-5%Ti alloy displayed the highest hardness values at room and elevated temperatures which are related to the presence of Ti-containing phases such as Al3Ti and AlCu2Ti, these phases are thermally stable and retain the high hardness values at elevated temperatures up to 400ºC.

Keywords: nanocrystalline aluminum alloys, mechanical alloying, hardness, elevated temperatures

Procedia PDF Downloads 434
4578 Supply Chain Decarbonisation – A Cost-Based Decision Support Model in Slow Steaming Maritime Operations

Authors: Eugene Y. C. Wong, Henry Y. K. Lau, Mardjuki Raman

Abstract:

CO2 emissions from maritime transport operations represent a substantial part of the total greenhouse gas emission. Vessels are designed with better energy efficiency. Minimizing CO2 emission in maritime operations plays an important role in supply chain decarbonisation. This paper reviews the initiatives on slow steaming operations towards the reduction of carbon emission. It investigates the relationship and impact among slow steaming cost reduction, carbon emission reduction, and shipment delay. A scenario-based cost-driven decision support model is developed to facilitate the selection of the optimal slow steaming options, considering the cost on bunker fuel consumption, available speed, carbon emission, and shipment delay. The incorporation of the social cost of cargo is reviewed and suggested. Additional measures on the effect of vessels sizes, routing, and type of fuels towards decarbonisation are discussed.

Keywords: slow steaming, carbon emission, maritime logistics, sustainability, green supply chain

Procedia PDF Downloads 438
4577 Deployment of Beyond 4G Wireless Communication Networks with Carrier Aggregation

Authors: Bahram Khan, Anderson Rocha Ramos, Rui R. Paulo, Fernando J. Velez

Abstract:

With the growing demand for a new blend of applications, the users dependency on the internet is increasing day by day. Mobile internet users are giving more attention to their own experiences, especially in terms of communication reliability, high data rates and service stability on move. This increase in the demand is causing saturation of existing radio frequency bands. To address these challenges, researchers are investigating the best approaches, Carrier Aggregation (CA) is one of the newest innovations, which seems to fulfill the demands of the future spectrum, also CA is one the most important feature for Long Term Evolution - Advanced (LTE-Advanced). For this purpose to get the upcoming International Mobile Telecommunication Advanced (IMT-Advanced) mobile requirements (1 Gb/s peak data rate), the CA scheme is presented by 3GPP, which would sustain a high data rate using widespread frequency bandwidth up to 100 MHz. Technical issues such as aggregation structure, its implementations, deployment scenarios, control signal techniques, and challenges for CA technique in LTE-Advanced, with consideration of backward compatibility, are highlighted in this paper. Also, performance evaluation in macro-cellular scenarios through a simulation approach is presented, which shows the benefits of applying CA, low-complexity multi-band schedulers in service quality, system capacity enhancement and concluded that enhanced multi-band scheduler is less complex than the general multi-band scheduler, which performs better for a cell radius longer than 1800 m (and a PLR threshold of 2%).

Keywords: component carrier, carrier aggregation, LTE-advanced, scheduling

Procedia PDF Downloads 171
4576 Microbial Fuel Cells in Waste Water Treatment and Electricity Generation

Authors: Rajalaxmi N., Padma Bhat, Pooja Garag, Pooja N. M., V. S. Hombalimath

Abstract:

Microbial fuel cell (MFC) is the advancement of science that aims at utilizing the oxidizing potential of bacteria for wastewater treatment and production of bio-hydrogen and bio-electricity. Salt-bridge is the economic alternative to highly priced proton-exchange membrane in the construction of a microbial fuel cell. This paper studies the electricity generating capacity of E.coli and Clostridium sporogenes in microbial fuel cells (MFCs). Unlike most of MFC research, this targets the long term goals of renewable energy production and wastewater treatment. In present study the feasibility and potential of bioelectricity production from different wastewater was observed. Different wastewater was primarily treated which were confirmed by the COD tests which showed reduction of COD. We observe that the electricity production of MFCs decreases almost linearly after 120 hrs. The sewage wastewater containing Clostridium sporogenes showed bioelectricity production up to 188mV with COD removal of 60.52%. Sewage wastewater efficiently produces bioelectricity and this also helpful to reduce wastewater pollution load.

Keywords: microbial fuel cell, bioelectricity, wastewater, salt bridge, COD

Procedia PDF Downloads 503
4575 Simulation of Internal Flow Field of Pitot-Tube Jet Pump

Authors: Iqra Noor, Ihtzaz Qamar

Abstract:

Pitot-tube Jet pump, single-stage pump with low flow rate and high head, consists of a radial impeller that feeds water to rotating cavity. Water then enters stationary pitot-tube collector (diffuser), which discharges to the outside. By means of ANSYS Fluent 15.0, the internal flow characteristics for Pitot-tube Jet pump with standard pitot and curved pitot are studied. Under design condition, realizable k-e turbulence model and SIMPLEC algorithm are used to calculate 3D flow field inside both pumps. The simulation results reveal that energy is imparted to the flow by impeller and inside the rotor, forced vortex type flow is observed. Total pressure decreases inside pitot-tube whereas static pressure increases. Changing pitot-tube from standard to curved shape results in minimum flow circulation inside pitot-tube and leads to a higher pump performance.

Keywords: CFD, flow circulation, high pressure pump, impeller, internal flow, pickup tube pump, rectangle channels, rotating casing, turbulence

Procedia PDF Downloads 140
4574 Cache Analysis and Software Optimizations for Faster on-Chip Network Simulations

Authors: Khyamling Parane, B. M. Prabhu Prasad, Basavaraj Talawar

Abstract:

Fast simulations are critical in reducing time to market in CMPs and SoCs. Several simulators have been used to evaluate the performance and power consumed by Network-on-Chips. Researchers and designers rely upon these simulators for design space exploration of NoC architectures. Our experiments show that simulating large NoC topologies take hours to several days for completion. To speed up the simulations, it is necessary to investigate and optimize the hotspots in simulator source code. Among several simulators available, we choose Booksim2.0, as it is being extensively used in the NoC community. In this paper, we analyze the cache and memory system behaviour of Booksim2.0 to accurately monitor input dependent performance bottlenecks. Our measurements show that cache and memory usage patterns vary widely based on the input parameters given to Booksim2.0. Based on these measurements, the cache configuration having least misses has been identified. To further reduce the cache misses, we use software optimization techniques such as removal of unused functions, loop interchanging and replacing post-increment operator with pre-increment operator for non-primitive data types. The cache misses were reduced by 18.52%, 5.34% and 3.91% by employing above technology respectively. We also employ thread parallelization and vectorization to improve the overall performance of Booksim2.0. The OpenMP programming model and SIMD are used for parallelizing and vectorizing the more time-consuming portions of Booksim2.0. Speedups of 2.93x and 3.97x were observed for the Mesh topology with 30 × 30 network size by employing thread parallelization and vectorization respectively.

Keywords: cache behaviour, network-on-chip, performance profiling, vectorization

Procedia PDF Downloads 174
4573 Combining Multiscale Patterns of Weather and Sea States into a Machine Learning Classifier for Mid-Term Prediction of Extreme Rainfall in North-Western Mediterranean Sea

Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

Abstract:

Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

Procedia PDF Downloads 112
4572 Salicylic Acid Signalling in Relation to Root Colonization in Rice

Authors: Seema Garcha, Sheetal Chopra, Navraj Sarao

Abstract:

Plant hormones play a role in internal colonization by beneficial microbes and also systemic acquired resistance. They define qualitative and quantitative nature of root microbiome and also influence dynamics of root rhizospheric soil. The present study is an attempt to relate salicylic acid (signal molecule) content and qualitative nature of root endophytes at various stages in the growth of rice varieties of commercial value- Parmal 121 and Basmati 1121. Root seedlings of these varieties were raised using tissue culture techniques and then they were transplanted in the fields. Cultivation was done using conventional methods in agriculture. Field soil contained 0.39% N, 75.12 Kg/hectare of phosphorus and 163.0 Kg/hectare of potassium. Microfloral profiling of the root tissue was done using the selective microbiological medium. The salicylic acid content was estimated using HPLC-Agilent 1100 HPLC Series. Salicylic acid level of Basmati 1121 remained relatively low at the time of transplant and 90 days after transplant. It increased marginally at 60 days. A similar trend was observed with Parmal 121 as well. However, Parmal variety recorded 0.935 ug/g of salicylic acid at 60 days after transplant. Salicylic acid content decreased after 90 days as both the rice varieties remained disease free. The endophytic root microflora was established by 60 days after transplant in both the varieties after which their population became constant. Rhizobium spp dominated over Azotobacter spp. Genetic profiling of endophytes for nitrogen-fixing ability is underway.

Keywords: plant-microbe interaction, rice, root microbiome, salicylic acid

Procedia PDF Downloads 176
4571 Multisymplectic Geometry and Noether Symmetries for the Field Theories and the Relativistic Mechanics

Authors: H. Loumi-Fergane, A. Belaidi

Abstract:

The problem of symmetries in field theory has been analyzed using geometric frameworks, such as the multisymplectic models by using in particular the multivector field formalism. In this paper, we expand the vector fields associated to infinitesimal symmetries which give rise to invariant quantities as Noether currents for classical field theories and relativistic mechanic using the multisymplectic geometry where the Poincaré-Cartan form has thus been greatly simplified using the Second Order Partial Differential Equation (SOPDE) for multi-vector fields verifying Euler equations. These symmetries have been classified naturally according to the construction of the fiber bundle used.  In this work, unlike other works using the analytical method, our geometric model has allowed us firstly to distinguish the angular moments of the gauge field obtained during different transformations while these moments are gathered in a single expression and are obtained during a rotation in the Minkowsky space. Secondly, no conditions are imposed on the Lagrangian of the mechanics with respect to its dependence in time and in qi, the currents obtained naturally from the transformations are respectively the energy and the momentum of the system.

Keywords: conservation laws, field theories, multisymplectic geometry, relativistic mechanics

Procedia PDF Downloads 184
4570 Porous Ni Electrodes Modified with Au Nanoparticles for Hydrogen Production

Authors: V. Pérez-Herranz, C. González-Buch, E. M. Ortega, S. Mestre

Abstract:

In this work new macroporous Ni electrodes modified with Au nanoparticles for hydrogen production have been developed. The supporting macroporous Ni electrodes have been obtained by means of the electrodeposition at high current densities. Then, the Au nanoparticles were synthesized and added to the electrode surface. The electrocatalytic behaviour of the developed electrocatalysts was studied by means of pseudo-steady-state polarization curves, electrochemical impedance spectroscopy (EIS) and hydrogen discharge curves. The size of the Au synthetized nanoparticles shows a monomodal distribution, with a very sharp band between 10 and 50 nm. The characteristic parameters d10, d50 and d90 were 14, 20 and 31 nm respectively. From Tafel polarization data has been concluded that the Au nanoparticles improve the catalytic activity of the developed electrodes towards the HER respect to the macroporous Ni electrodes. EIS permits to obtain the electrochemically active area by means of the roughness factor value. All the developed electrodes show roughness factor values in the same order of magnitude. From the activation energy results it can be concluded that the Au nanoparticles improve the intrinsic catalytic activity of the macroporous Ni electrodes.

Keywords: Au nano particles, hydrogen evolution reaction, porous Ni electrodes, electrochemical impedance spectroscopy

Procedia PDF Downloads 600
4569 Introducing New and Less Known Sources of Geomorphosites for Geotourism Development, with Examples from Misho-dagh Mountain in Northwestern Iran

Authors: Davoud Mokhtari

Abstract:

One of the factors behind the increasing development of geotourism is the identification and introduction of new facets of amazing geosphere phenomena. The Misho-Dagh Mountains in northwestern Iran are one of the rich geodiversity areas. The presence of some rare and interesting phenomena in this mountain has increased the potential of this region for geotourism development. Active pressure ridges, arcuate valleys, sag Ponds, granite complexes, glacial rock springs, and displaced habitats due to tectonic activity are among the most significant phenomena in the study area. The research is based on the literature review of geotourism and personal research experiences on geomorphosites of the northwest of Iran. Monitoring the changes of geomorphosites and evaluation of corresponding changes in the geomorphosite̕s location and their capabilities using satellite images and fieldwork is done. In this study, six geomorphosite were introduced, each with special characteristics and with one of the geotourism topics. Selection of this location of northwestern Iran is due to the focus of author of this paper is on this part of the country, and there is no doubt that such places, even with higher values of geotourism, there are in various parts of Iran and the world that could be interested in this field of emerging science. From in situ observations taken in the field and estimating a level of impact, employing assessment techniques, and then finally extrapolating the resultant factors across all case studies, we have been able to generate a geotourism map for future planning purposes. Accordingly, it should be noted that we are not just part of the landscape of the geomorphosites. The geomorphosites are also part of our landscape. It is hoped that the findings of this paper can open a new world of geotourism that, if is not associated with geomorphological processes, will be very short.

Keywords: geotourism, sources of geotourism, geotouristic areas, mishow_dagh, northwest of Iran

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4568 Using Business Intelligence Capabilities to Improve the Quality of Decision-Making: A Case Study of Mellat Bank

Authors: Jalal Haghighat Monfared, Zahra Akbari

Abstract:

Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: business intelligence, business intelligence capability, decision making, decision quality

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4567 Transgression, Resistance and Independent Art in Russia

Authors: Oxana Vasilyeva

Abstract:

This paper draws on research in progress focusing on independent art in the Russian Federation. I am using the concept of independent art to mean art free from state control and established restrictive narratives. The Russian state pursues its interests by supporting or forbidding certain forms of art, and art that promotes values in opposition to the official political course is often forbidden. Arguments presented below draw from fieldwork carried out in Russian cities of Moscow and Saint Petersburg in June – August 2019, which included in-depth interviews with artists. This research explores socially engaged artistic works and their effect on socio-political state of affairs. It argues that artistic works entering public places have a potential to challenge autocratic system and inspire civil society to be critically engaged and to be capable to resist state propaganda. I am focusing on those artists who have a critical stance towards the current Russian political regime and analyzing their works in terms of transgression. By using the framework of transgression I aim to demonstrate how artists step across existing norms with their art influencing political and social order. To show the connection between the factors mentioned above, I will turn to two examples of transgressive aesthetics; one is individual and another is collective. The first example is Konstantin Benkovich, an artist who makes his works out of steel rebar, which is considered to be a symbol of the lack of freedom, as it is usually encountered in prison settings. The second example is a collective art practice called Monstration. It combines techniques of a demonstration and a carnival atmosphere. In 2019 Monstration was held in 30 Russian cities, despite the dissatisfaction of the authorities.

Keywords: art, culture, resistance, Russia

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4566 Performance Study of Classification Algorithms for Consumer Online Shopping Attitudes and Behavior Using Data Mining

Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

Abstract:

With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

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4565 Business Model Innovation and Firm Performance: Exploring Moderation Effects

Authors: Mohammad-Ali Latifi, Harry Bouwman

Abstract:

Changes in the business environment accelerated dramatically over the last decades as a result of changes in technology, regulation, market, and competitors’ behavior. Firms need to change the way they do business in order to survive or maintain their growth. Innovating business model (BM) can create competitive advantages and enhance firm performance. However, many companies fail to achieve expected outcomes in practice, mostly due to irreversible fundamental changes in key components of the company’s BM. This leads to more ambiguity, uncertainty, and risks associated with business performance. However, the relationship among BM Innovation, moderating factors, and the firm’s overall performance is by and large ignored in the current literature. In this study, we identified twenty moderating factors from our comprehensive literature review. We categorized these factors based on two criteria regarding the extent to which: the moderating factors can be controlled and managed by firms, and they are generic or specific changes to the firms. This leads to four moderation groups. The first group is BM implementation, which includes management support, employees’ commitment, employees’ skills, communication, detailed plan. The second group is called BM practices, which consists of BM tooling, BM experimentation, the scope of change, speed of change, degree of novelty. The third group is Firm characteristics, including firm size, age, and ownership. The last group is called Industry characteristics, which considers the industry sector, competitive intensity, industry life cycle, environmental dynamism, high-tech vs. low-tech industry. Through collecting data from 508 European small and medium-sized enterprises (SMEs) and using the structural equation modeling technique, the developed moderation model was examined. Results revealed that all factors highlighted through these four groups moderate the relation between BMI and firm performance significantly. Particularly, factors related to BM-Implementation and BM-Practices are more manageable and would potentially improve firm overall performance. We believe that this result is more important for researchers and practitioners since the possibility of working on factors in Firm characteristics and Industry characteristics groups are limited, and the firm can hardly control and manage them to improve the performance of BMI efforts.

Keywords: business model innovation, firm performance, implementation, moderation

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4564 Assessment of the Impact of Trawling Activities on Marine Bottoms of Moroccan Atlantic

Authors: Rachida Houssa, Hassan Rhinane, Fadoumo Ali Malouw, Amina Oulmaalem

Abstract:

Since the early 70s, the Moroccan Atlantic sea was subjected to the pressure of the bottom trawling, one of the most destructive techniques seabed that cause havoc on fishing catch, nonselective, and responsible for more than half of all releases of fish around the world. The present paper aims to map and assess the impact of the activity of the bottom trawling of the Moroccan Atlantic coast. For this purpose, a dataset of thirty years, between 1962 and 1999, from foreign fishing vessels using bottom trawling, has been used and integrated in a GIS. To estimate the extent and the importance of the geographical distribution of the trawling effort, the Moroccan Atlantic area was divided into a grid of cells of 25 km2 (5x5 km). This grid was joined to the effort trawling data, creating a new entity with a table containing spatial overlay grid with the polygon of swept surfaces. This mapping model allowed to quantify the used fishing effort versus time and to generate the trace indicative of trawling efforts on the seabed. Indeed, for a given year, a grid cell may have a swept area equal to 0 (never been touched by the trawl) or 25 km2 (the trawled area is similar to the cell size) or may be 100 km2 indicating that for this year, the scanned surface is four times the cell area. The results show that the total cumulative sum of trawled area is approximately 28,738,326 km2, scattered throughout the Atlantic coast. 95% of the overall trawling effort is located in the southern zone, between 29°N and 20°30'N. Nearly 5% of the trawling effort is located in the northern coastal region, north of 33°N. The center area between 33°N and 29°N is the least swept by Russian commercial vessels because in this region the majority of the area is rocky, and non trawlable.

Keywords: GIS, Moroccan Atlantic Ocean, seabed, trawling

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4563 Plant Identification Using Convolution Neural Network and Vision Transformer-Based Models

Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

Abstract:

Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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4562 Comparative Study Using WEKA for Red Blood Cells Classification

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

Abstract:

Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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4561 Development of a Tilt-Rotor Aircraft Model Using System Identification Technique

Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

Abstract:

The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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4560 A Case Study on the Condition Monitoring of a Critical Machine in a Tyre Manufacturing Plant

Authors: Ramachandra C. G., Amarnath. M., Prashanth Pai M., Nagesh S. N.

Abstract:

The machine's performance level drops down over a period of time due to the wear and tear of its components. The early detection of an emergent fault becomes very vital in order to obtain uninterrupted production in a plant. Maintenance is an activity that helps to keep the machine's performance at an anticipated level, thereby ensuring the availability of the machine to perform its intended function. At present, a number of modern maintenance techniques are available, such as preventive maintenance, predictive maintenance, condition-based maintenance, total productive maintenance, etc. Condition-based maintenance or condition monitoring is one such modern maintenance technique in which the machine's condition or health is checked by the measurement of certain parameters such as sound level, temperature, velocity, displacement, vibration, etc. It can recognize most of the factors restraining the usefulness and efficacy of the total manufacturing unit. This research work is conducted on a Batch Mill in a tire production unit located in the Southern Karnataka region. The health of the mill is assessed using amplitude of vibration as a parameter of measurement. Most commonly, the vibration level is assessed using various points on the machine bearing. The normal or standard level is fixed using reference materials such as manuals or catalogs supplied by the manufacturers and also by referring vibration standards. The Rio-Vibro meter is placed in different locations on the batch-off mill to record the vibration data. The data collected are analyzed to identify the malfunctioning components in the batch off the mill, and corrective measures are suggested.

Keywords: availability, displacement, vibration, rio-vibro, condition monitoring

Procedia PDF Downloads 58