Search results for: solar–climatic data

Authors: Temitayo Tosin Alawiye

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Plant disease control is important in maintaining plant vigour, grain quantity, abundance of food, feed, and fibre produced by farmers all over the world. Farmers make use of different methods in controlling these diseases but one of the commonly used method is the use of chemicals. However, the continuous and excessive usages of these agrochemicals pose a danger to the environment, man and wildlife. The more the population growth the more the food security challenge which leads to more pressure on agronomic growth. Agricultural waste also known as green waste are the residues from the growing and processing of raw agricultural products such as fruits, vegetables, rice husk, corn cob, mushroom growth medium waste, coconut husk. They are widely used in land bioremediation, crop production and protection which include disease control. These agricultural wastes help the crop by improving the soil fertility, increase soil organic matter and reduce in many cases incidence and severity of disease. The objective was to review the agricultural waste that has worked effectively against certain soil-borne diseases such as Fusarium oxysporum, Pythiumspp, Rhizoctonia spp so as to help minimize the use of chemicals. Climate change is a major problem of agriculture and vice versa. Climate change and agriculture are interrelated. Change in climatic conditions is already affecting agriculture with effects unevenly distributed across the world. It will increase the risk of food insecurity for some vulnerable groups such as the poor in Sub Saharan Africa. The food security challenge will become more difficult as the world will need to produce more food estimated to feed billions of people in the near future with Africa likely to be the biggest hit. In order to surmount this hurdle, smallholder farmers in Africa must embrace climate-smart agricultural techniques and innovations which includes the use of green waste in agriculture, conservative agriculture, pasture and manure management, mulching, intercropping, etc. Training and retraining of smallholder farmers on the use of green energy to mitigate the effect of climate change should be encouraged. Policy makers, academia, researchers, donors, and farmers should pay more attention to the use of green energy as a way of reducing incidence and severity of soilborne plant diseases to solve looming food security challenges.

Keywords: agricultural waste, climate change, green energy, soil borne plant disease

Procedia PDF Downloads 269

Authors: Rebecca Oakes

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In the New Zealand public health system, work has been taking place to use electronic systems to convey data from the ‘floor to the board’ that makes patient needs, and therefore nursing work, visible. For nurses, these developments in health information technology puts us in a very new and exciting position of being able to articulate the work of nursing through a language understood at all levels of an organisation, the language of acuity. Nurses increasingly have a considerable stake-hold in patient acuity data. Patient acuity systems, when used well, can assist greatly in demonstrating how much work is required, the type of work, and when it will be required. The New Zealand Safe Staffing Unit is supporting New Zealand nurses to create a culture of shared governance, where nursing data is informing policies, staffing methodologies and forecasting within their organisations. Assisting organisations to understand their acuity data, strengthening user confidence in using electronic patient acuity systems, and ensuring nursing and midwifery workload is accurately reflected is critical to the success of the safe staffing programme. Nurses and midwives have the capacity via an acuity tool to become key informers of organisational planning. Quality patient care, best use of health resources and a quality work environment are essential components of a safe, resilient and well resourced organisation. Nurses are the key informers of this information. In New Zealand a national level approach is paving the way for significant changes to the understanding and use of patient acuity and nursing workload information.

Keywords: nursing workload, patient acuity, safe staffing, New Zealand

Procedia PDF Downloads 382

Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

Procedia PDF Downloads 142

Authors: Wen-Jay Lee, Kuo-Ning Chiang

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The graphene binding with silicon substrate has apparently Schottky barriers property, which can be used in the application of solar cell and light source. Because graphene has only one atom layer, the atomistic structure of graphene binding with the silicon surface plays an important role to affect the properties of graphene. In this work, temperature effect on the morphology of graphene sheet attached on different crystal planes of silicon substrates are investigated by Molecular dynamics (MD) (LAMMPS, developed by Sandia National Laboratories). The results show that the covered graphene sheet would cause the structural deformation of the surface Si atoms of stubtrate. To achieve a stable state in the binding process, the surface Si atoms would adjust their position and fit the honeycomb structure of graphene after the graphene attaches to the Si surface. The height contour of graphene on different plane of silicon surfaces presents different pattern, leading the local residual stress at the interface. Due to the high density of dangling bond on the Si (111)7x7 surface, the surface of Si(111)7x7 is not matching with the graphene so well in contrast with Si(100)2x1and Si(111)2x1. Si(111)7x7 is found that only partial silicon adatoms are rearranged on surface after the attachment when the temperature is lower than 200K, As the temperature gradually increases, the deformation of surface structure becomes significant, as well as the residue stress. With increasing temperature till the 815K, the graphene sheet begins to destroy and mixes with the silicon atoms. For the Si(100)2x1 and Si(111)2x1, the silicon surface structure keep its structural arrangement with a higher temperature. With increasing temperature, the residual stress gradually decrease till a critical temperatures. When the temperature is higher than the critical temperature, the residual stress gradually increases and the structural deformation is found on the surface of the Si substrates.

Keywords: molecular dynamics, graphene, silicon, Schottky barriers, interface

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Authors: Arshad Alfoqaha, Seth Bard, Dustin Demetriou

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A new multi-physics acoustic modeling approach using ANSYS Mechanical FEA and FLUENT CFD methods is developed for modeling servers mounted to racks, such as IBM Z and IBM Power Systems, in data centers. This new approach allows users to determine the thermal and acoustic conditions that people are exposed to within the data center. The sound pressure level (SPL) exposure for a human working inside a hot aisle containment system inside the data center is studied. The SPL is analyzed at the noise source, at the human body, on the rack walls, on the containment walls, and on the ceiling and flooring plenum walls. In the acoustic CFD simulation, it is assumed that a four-inch diameter sphere with monopole acoustic radiation, placed in the middle of each rack, provides a single-source representation of all noise sources within the rack. Ffowcs Williams & Hawkings (FWH) acoustic model is employed. The target frequency is 1000 Hz, and the total simulation time for the transient analysis is 1.4 seconds, with a very small time step of 3e-5 seconds and 10 iterations to ensure convergence and accuracy. A User Defined Function (UDF) is developed to accurately simulate the acoustic noise source, and a Dynamic Mesh is applied to ensure acoustic wave propagation. Initial validation of the acoustic CFD simulation using a closed-form solution for the spherical propagation of an acoustic point source is performed.

Keywords: data centers, FLUENT, acoustics, sound pressure level, SPL, hot aisle containment, IBM

Procedia PDF Downloads 176

Authors: Ashagrie Getnet Flattie

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Line-of-sight (LOS) information, data rates, good quality, and flexible network service are limited by the fact that, for the duration of any given connection, they experience severe variation in signal strength due to fading and path loss. Wireless system faces major challenges in achieving wide coverage and capacity without affecting the system performance and to access data everywhere, all the time. In this paper, the cell coverage and edge rate of different Multiple-input multiple-output (MIMO) schemes in 20 MHz Long Term Evolution (LTE) system under Unmanned Air Vehicles (UAV) platform are investigated. After some background on the enormous potential of UAV, MIMO, and LTE in wireless links, the paper highlights the presented system model which attempts to realize the various benefits of MIMO being incorporated into UAV platform. The performances of the three MIMO LTE schemes are compared with the performance of 4x4 MIMO LTE in UAV scheme carried out to evaluate the improvement in cell radius, BER, and data throughput of the system in different morphology. The results show that significant performance gains such as bit error rate (BER), data rate, and coverage can be achieved by using the presented scenario.

Keywords: LTE, MIMO, path loss, UAV

Procedia PDF Downloads 279

Authors: Sorin Valcan, Mihail Gaianu

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Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need for labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to an algorithm used for the generation of ground truth data for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher, which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual label adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: labeling automation, infrared camera, driver monitoring, eye detection, convolutional neural networks

Procedia PDF Downloads 117

Authors: Jaemoon Lim

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To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME

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Authors: Joanne Moyer

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El Paso, Texas is a southwest border city that has experienced continuous growth within the last 15-years. Understanding the urban growth trends and patterns using data from the National Land Cover Database (NLCD) and landscape metrics, provides a quantitative description of growth. Past urban growth provided a basis to predict 2031 future land-use for El Paso using the CA-Markov model. As a consequence of growth, an increase in demand of resources follows. Using panel data analysis, an understanding of the relation between landscape metrics and electricity consumption is further analyzed. The studies’ findings indicate that past growth focused within three districts within the City of El Paso. The landscape metrics suggest as the city has grown, fragmentation has decreased. Alternatively, the landscape metrics for the projected 2031 land-use indicates possible fragmentation within one of these districts. Panel data suggests electricity consumption and mean patch area landscape metric are positively correlated. The study provides local decision makers to make informed decisions for policies and urban planning to ensure a future sustainable community.

Keywords: landscape metrics, CA-Markov, El Paso, Texas, panel data

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Authors: M. S. Mousavi-Daramoroudi, H. Yousefnia, S. Zolghadri, F. Abbasi-Davani

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Dosimetry is an indispensable and precious factor in patient treatment planning; to minimize the absorbed dose in vital tissues. In this study, In accordance with the proper characteristics of DOTATOC and ¹⁷⁷Lu, after preparing ¹⁷⁷Lu-DOTATOC at the optimal conditions for the first time in Iran, radionuclidic and radiochemical purity of the solution was investigated using an HPGe spectrometer and ITLC method, respectively. The biodistribution of the compound was assayed for treatment of adenocarcinoma breast cancer in bearing BALB/c mice. The results have demonstrated that ¹⁷⁷Lu-DOTATOC is a profitable selection for therapy of the tumors. Because of the vital role of internal dosimetry before and during therapy, the effort to improve the accuracy and rapidity of dosimetric calculations is necessary. For this reason, a new method was accomplished to calculate the absorbed dose through mixing between compartmental model, animal dosimetry and extrapolated data from animal to human and using MIRD method. Despite utilization of compartmental model based on the experimental data, it seems this approach may increase the accuracy of dosimetric data, confidently.

Keywords: ¹⁷⁷Lu-DOTATOC, biodistribution modeling, compartmental model, internal dosimetry

Procedia PDF Downloads 219

Authors: Yuntao Liu, Lei Wang, Haoran Xia

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Machine learning has shown extensive applications in the development of classification models for autism spectrum disorder (ASD) using neural image data. This paper proposes a fusion multi-modal classification network based on a graph neural network. First, the brain is segmented into 116 regions of interest using a medical segmentation template (AAL, Anatomical Automatic Labeling). The image features of sMRI and the signal features of fMRI are extracted, which build the node and edge embedding representations of the brain map. Then, we construct a dynamically updated brain map neural network and propose a method based on a dynamic brain map adjacency matrix update mechanism and learnable graph to further improve the accuracy of autism diagnosis and recognition results. Based on the Autism Brain Imaging Data Exchange I dataset(ABIDE I), we reached a prediction accuracy of 74% between ASD and TD subjects. Besides, to study the biomarkers that can help doctors analyze diseases and interpretability, we used the features by extracting the top five maximum and minimum ROI weights. This work provides a meaningful way for brain disorder identification.

Keywords: autism spectrum disorder, brain map, supervised machine learning, graph network, multimodal data, model interpretability

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Authors: K. Abuzayan, H. Alabed

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The objectives of this study (baseline study, n = 20) were to implement Matlab procedures for quantifying selected static balance variables, establish baseline data of selected variables which characterize static balance activities in a population of healthy young adult males, and to examine any trial effects on these variables. The results indicated that the implementation of Matlab procedures for quantifying selected static balance variables was practical and enabled baseline data to be established for selected variables. There was no significant trial effect. Recommendations were made for suitable tests to be used in later studies. Specifically it was found that one foot-tiptoes tests either in static balance is too challenging for most participants in normal circumstances. A one foot-flat eyes open test was considered to be representative and challenging for static balance.

Keywords: static balance, base of support, baseline data, young adults

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Authors: Sandip Mitra

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Studies on Governance and Accountability has often stressed the need to release Data in public domain to increase transparency ,which otherwise act as an evidence of performance. However, inefficient handling, lack of capacity and the dynamics of transfers (especially fund transfers) are important issues which need appropriate attention. E-Governance alone can not serve as a measure of transparency as long as a comprehensive planning is instituted. Studies on Governance and public exposure has often triggered public opinion in favour or against any government. The root of the problem (especially in local governments) lies in the management of the governance. The participation of the people in the local government functioning, the networks within and outside the locality, synergy with various layers of Government are crucial in understanding the activities of any government. Unfortunately, data on such issues are not released in the public domain .If they are at all released , the extraction of information is often hindered for complicated designs. A Study has been undertaken with a few local Governments in India. The data has been analysed to substantiate the views.

Keywords: accountability, e-governance, transparency, local government

Procedia PDF Downloads 436

Authors: Eusèbe Gnonlonfoun, Xavier Framboisier, Michel Fick, Emmanuel Rondags

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Pathogenic fungi represent a generic problem for cereals, including barley, as they can produce a number of thermostable toxic metabolites such as mycotoxins that contaminate plants and food products, leading to serious health issues for humans and animals and causing significant losses in global food production. In addition, mycotoxins represent a significant technological concern for the malting and brewing industries, as they may affect the quality and safety of raw materials (barley and malt) and final products (beer). Moreover, this situation is worsening due to the highly variable climatic conditions that favor microbial development and the societal desire to reduce the use of phytosanitary products, including fungicides. In this complex environmental, regulatory and economic context for the French barley-malt-beer industry, this project aims to develop an innovative biocontrol process by using technological bacteria, isolated from infection-resistant barley cultures, that are able to reduce the development of spoilage fungi and the associated mycotoxin production. The experimental approach consists of i) coculturing bacterial and pathogenic fungal strains in solid and liquid media to access the growth kinetics of these microorganisms and to evaluate the impact of these bacteria on fungal growth and mycotoxin production; then ii) the results will be used to carry out a micro-malting process in order to develop the aforementioned process, and iii) the technological and sanitary properties of the generated barley malts will finally be evaluated in order to validate the biocontrol process developed. The process is expected to make it possible to guarantee, with controlled costs, an irreproachable hygienic and technological quality of the malt, despite the increasingly complex and variable conditions for barley production. Thus, the results will not only make it possible to maintain the dominant world position of the French barley-malt chain but will also allow it to conquer emerging markets, mainly in Africa and Asia. The use of this process will also contribute to the reduction of the use of phytosanitary products in the field for barley production while reducing the level of contamination of malting plant effluents. Its environmental impact would therefore be significant, especially considering that barley is the fourth most-produced cereal in the world.

Keywords: barley, pathogenic fungi, mycotoxins, malting, bacterial biocontrol

Procedia PDF Downloads 177

Authors: A. Ikusika, O. I. Poppola

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This study was carried out to delineate possible structures that may favour the accumulation of tantalite, a magnetic mineral. A ground based technique was employed using proton precision magnetometer G-856 AX. A total of ten geophysical traverses were established in the study area. The acquired magnetic field data were corrected for drift. The trend analysis was adopted to remove the regional gradient from the observed data and the resulting results were presented as profiles. Quantitative interpretation only was adopted to obtain the depth to basement using Peter half slope method. From the geological setting of the area and the information obtained from the magnetic survey, a conclusion can be made that the study area is underlain by a rock unit of accumulated minerals. It is therefore suspected that the overburden is relatively thin within the study area and the metallic minerals are in disseminated quantity and at a shallow depth.

Keywords: basement, drift, magnetic field data, tantalite, traverses

Procedia PDF Downloads 475

Authors: Rajarshi Motilal

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The birth of the Internet and the rise of social media marked an important chapter in the history of humankind. Often termed the fourth scientific revolution, the Internet has changed human lives and cognisance. The birth of Web 2.0, followed by the launch of social media and social networking sites, added another milestone to these technological advancements where connectivity and influx of information became dominant. With billions of individuals using the internet and social media sites in the 21st century, “users” became “consumers”, and orthodox marketing reshaped itself to digital marketing. Furthermore, organisations started using sophisticated algorithms to predict consumer purchase behaviour and manipulate it to sustain themselves in such a competitive environment. The rampant storage and analysis of individual data became the new normal, raising many questions about data privacy. The excessive usage of the Internet among individuals brought in other problems of them becoming addicted to it, scavenging for societal approval and instant gratification, subsequently leading to a collective dualism, isolation, and finally, depression. This study aims to determine the relationship between social media usage in the modern age and the rise of psychological and cognitive imbalances in human minds. The literature review is positioned timely as an addition to the existing work at a time when the world is constantly debating on whether social media resignation is the only way to protect user data and restore the decaying cognitive balance.

Keywords: social media, digital marketing, consumer behaviour, internet addiction, data privacy

Procedia PDF Downloads 76

Authors: Janne Engblom, Elias Oikarinen

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The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

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Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón

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The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.

Keywords: AD0, ALICE, DCS, LHC

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Authors: Mohammed Sharaf, Alireza Shokri, Adrian Small, Toby Bridges

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This paper investigates digital transformation challenges in SMEs within the automotive supply chain. A case study approach and participant observation revealed significant data management and process optimization barriers, corroborated by a conceptual model. Stakeholder feedback, visualized through a pie chart, emphasized data management and process efficiency as primary concerns. Recommended strategies include implementing advanced data systems, process simplification, and enhancing digital skills. Despite the single-case study limitation, the findings offer actionable insights for SMEs to leverage Industry 4.0 technologies effectively. This research contributes to the strategic roadmap necessary for SMEs to achieve competitive digital transformation.

Keywords: automotive supply chain, digital transformation, industry 4.0

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Authors: Vito Telesca, Giuseppina A. Giorgio, M. Ragosta

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The effects of extreme heat events are increasing in recent years. Humans are forced to adjust themselves to adverse climatic conditions. The impact of weather on human health has become public health significance, especially in light of climate change and rising frequency of devasting weather events (e.g., heat waves and floods). The interest of scientific community is widely known. In particular, the associations between temperature and mortality are well studied. Weather conditions are natural factors that affect the human organism. Recent works show that the temperature threshold at which an impact is seen varies by geographic area and season. These results suggest heat warning criteria should consider local thresholds to account for acclimation to local climatology as well as the seasonal timing of a forecasted heat wave. Therefore, it is very important the problem called ‘local warming’. This is preventable with adequate warning tools and effective emergency planning. Since climate change has the potential to increase the frequency of these types of events, improved heat warning systems are urgently needed. This would require a better knowledge of the full impact of extreme heat on morbidity and mortality. The majority of researchers who analyze the associations between human health and weather variables, investigate the effect of air temperature and bioclimatic indices. These indices combine air temperature, relative humidity, and wind speed and are very important to determine the human thermal comfort. Health impact studies of weather events showed that the prevention is an essential element to dramatically reduce the impact of heat waves. The summer Italian of 2012 was characterized with high average temperatures (con un +2.3°C in reference to the period 1971-2000), enough to be considered as the second hottest summer since 1800. Italy was the first among countries in Europe which adopted tools for to predict these phenomena with 72 hours in advance (Heat Health Watch Warning System - HHWWS). Furthermore, in Italy heat alert criteria relies on the different Indexes, for example Apparent temperature, Scharlau index, Thermohygrometric Index, etc. This study examines the importance of developing public health policies that protect the most vulnerable people (such as the elderly) to extreme temperatures, highlighting the factors that confer susceptibility.

Keywords: heat waves, Italy, local warming, temperature

Procedia PDF Downloads 243

Authors: Agastya Pratap Singh

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Generative Adversarial Networks (GANs) have emerged as powerful tools in the fields of image recognition and anomaly detection due to their ability to model complex data distributions and generate realistic images. This systematic review explores recent advancements and applications of GANs in both image recognition and anomaly detection tasks. We discuss various GAN architectures, such as DCGAN, CycleGAN, and StyleGAN, which have been tailored to improve accuracy, robustness, and efficiency in visual data analysis. In image recognition, GANs have been used to enhance data augmentation, improve classification models, and generate high-quality synthetic images. In anomaly detection, GANs have proven effective in identifying rare and subtle abnormalities across various domains, including medical imaging, cybersecurity, and industrial inspection. The review also highlights the challenges and limitations associated with GAN-based methods, such as instability during training and mode collapse, and suggests future research directions to overcome these issues. Through this review, we aim to provide researchers with a comprehensive understanding of the capabilities and potential of GANs in transforming image recognition and anomaly detection practices.

Keywords: generative adversarial networks, image recognition, anomaly detection, DCGAN, CycleGAN, StyleGAN, data augmentation

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Authors: M. Y. Bakeir

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Rough set theory is a recent approach for reasoning about data. It has achieved a large amount of applications in various real-life fields. The main idea of rough sets corresponds to the lower and upper set approximations. These two approximations are exactly the interior and the closure of the set with respect to a certain topology on a collection U of imprecise data acquired from any real-life field. The base of the topology is formed by equivalence classes of an equivalence relation E defined on U using the available information about data. The theory of generalized topology was studied by Cs´asz´ar. It is well known that generalized topology in the sense of Cs´asz´ar is a generalization of the topology on a set. On the other hand, many important collections of sets related with the topology on a set form a generalized topology. The notion of Nano topology was introduced by Lellis Thivagar, which was defined in terms of approximations and boundary region of a subset of an universe using an equivalence relation on it. The purpose of this paper is to introduce a new generalized topology in terms of rough set called nano generalized topology

Keywords: rough sets, topological space, generalized topology, nano topology

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Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: C. Romero, R. Ortega, P. Sánchez-Camacho, P. Aguilar, V. Segur, J. Ruiz, G. Gutiérrez

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Introduction: Breast cancer is a leading cause of death in CLM. (2.8% of all deaths in women and 13,8% of deaths from tumors in womens). It is the most tumor incidence in CLM region with 26.1% from all tumours, except nonmelanoma skin (Cancer Incidence in Five Continents, Volume X, IARC). Cancer registries are a good information source to estimate cancer incidence, however the data are usually available with a lag which makes difficult their use for health managers. By contrast, mortality and survival statistics have less delay. In order to serve for resource planning and responding to this problem, a method is presented to estimate the incidence of mortality and survival data. Objectives: To estimate the incidence of breast cancer by age group in CLM in the period 1991-2013. Comparing the data obtained from the model with current incidence data. Sources: Annual number of women by single ages (National Statistics Institute). Annual number of deaths by all causes and breast cancer. (Mortality Registry CLM). The Breast cancer relative survival probability. (EUROCARE, Spanish registries data). Methods: A Weibull Parametric survival model from EUROCARE data is obtained. From the model of survival, the population and population data, Mortality and Incidence Analysis MODel (MIAMOD) regression model is obtained to estimate the incidence of cancer by age (1991-2013). Results: The resulting model is: Ix,t = Logit [const + age1*x + age2*x2 + coh1*(t – x) + coh2*(t-x)2] Where: Ix,t is the incidence at age x in the period (year) t; the value of the parameter estimates is: const (constant term in the model) = -7.03; age1 = 3.31; age2 = -1.10; coh1 = 0.61 and coh2 = -0.12. It is estimated that in 1991 were diagnosed in CLM 662 cases of breast cancer (81.51 per 100,000 women). An estimated 1,152 cases (112.41 per 100,000 women) were diagnosed in 2013, representing an increase of 40.7% in gross incidence rate (1.9% per year). The annual average increases in incidence by age were: 2.07% in women aged 25-44 years, 1.01% (45-54 years), 1.11% (55-64 years) and 1.24% (65-74 years). Cancer registries in Spain that send data to IARC declared 2003-2007 the average annual incidence rate of 98.6 cases per 100,000 women. Our model can obtain an incidence of 100.7 cases per 100,000 women. Conclusions: A sharp and steady increase in the incidence of breast cancer in the period 1991-2013 is observed. The increase was seen in all age groups considered, although it seems more pronounced in young women (25-44 years). With this method you can get a good estimation of the incidence.

Keywords: breast cancer, incidence, cancer registries, castilla-la mancha

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Authors: Islam Elsayed Hussein

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The aim of this paper is to discover the impact of students’ attitude towards social media and the skills required to adopt social media as a university e-learning (2.0) platform. In addition, it measures the effect of social media adoption on interactive learning effectiveness. The population of this study was students at Faculty of tourism and Hotels, Fayoum University. A questionnaire was used as a research instrument to collect data from respondents, which had been selected randomly. Data had been analyzed using quantitative data analysis method. Findings showed that the students have a positive attitude towards adopting social networking in the learning process and they have also good skills for effective use of social networking tools. In addition, adopting social media is effectively affecting the interactive learning environment.

Keywords: attitude, skills, e-learning 2.0, interactive learning, Egypt

Procedia PDF Downloads 524

Authors: Hyehyeon Lee, Jiwon Yu, Juwon Kim, Raquel Kristina Leoni Tumiar, Taewon Kim, Juae Kim, Hongsuk Suh

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Photovoltaics, which have many advantages in cost, easy processing, and light-weight, have attracted attention. We synthesized pyrimidine-based conjugated polymers with 2-{4-[4,6-bis-(4-hexyl-thiophen-2-yl)-pyrimidin-2-yl]-phenyl}-thiazolo[5,4-b]pyridine (pPTP) which have an ability of powerful electron withdrawing and introduced into the PSCs. By Stille polymerization, we designed the conjugated polymers, pPTPBDT-12, pPTPBDT-EH, pPTPBDTT-EH and pPTPTTI. The HOMO energy levels of four polymers (pPTPBDT-12, pPTPBDT-EH, pPTPBDTT-EH and pPTPTTI) were at -5.61 ~ -5.89 eV, their LUMO (Lowest Unoccupied Molecular Orbital) energy levels were at -3.95 ~ -4.09 eV. The device including pPTPBDT-12 and PC71BM (1:2) indicated a V_oc of 0.67 V, a J_sc of 1.33 mA/cm², and a fill factor (FF) of 0.25, giving a power conversion efficiency (PCE) of 0.23%. The device including pPTPBDT-EH and PC71BM (1:2) indicated a V_oc of 0.72 V, a J_sc of 2.56 mA/cm², and a fill factor (FF) of 0.30, giving a power conversion efficiency of 0.56%. The device including pPTPBDTT-EH and PC71BM (1:2) indicated a V_oc of 0.72 V, a J_sc of 3.61 mA/cm², and a fill factor (FF) of 0.29, giving a power conversion efficiency of 0.74%. The device including pPTPTTI and PC71BM (1:2) indicated a V_oc of 0.83 V, a J_sc of 4.41 mA/cm², and a fill factor (FF) of 0.31, giving a power conversion efficiency of 1.13%. Therefore, pPTPBDT-12, pPTPBDT-EH, pPTPBDTT-EH, and pPTPTTI were synthesized by Stille polymerization. And We find one of the best efficiency for these polymers, called pPTPTTI. Their optical properties were measured and the results show that pyrimidine-based polymers especially like pPTPTTI have a great promise to act as the donor of the active layer.

Keywords: polymer solar cells, pyrimidine-based polymers, photovoltaics, conjugated polymer

Procedia PDF Downloads 198

Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

Procedia PDF Downloads 82

Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

Procedia PDF Downloads 311

Authors: Sathapath Kilaso

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Nowadays, Today, wireless sensor networks are an important technology that works with Internet of Things. It is receiving various data from many sensor. Then sent to processing or storing. By wireless network or through the Internet. The devices around us are intelligent, can receiving/transmitting and processing data and communicating through the system. There are many applications of wireless sensor networks, such as smart city, smart farm, environmental management, weather. This article will explore the use of wireless sensor networks in Thailand and collect data from Thai Thesis database in 2012-2017. How to Implementing Wireless Sensor Network Technology. Advantage from this study To know the usage wireless technology in many fields. This will be beneficial for future research. In this study was found the most widely used wireless sensor network in agriculture field. Especially for smart farms. And the second is the adoption of the environment. Such as weather stations and water inspection.

Keywords: wireless sensor network, smart city, survey, Adhoc Network

Procedia PDF Downloads 207

Authors: Jaturong Som-ard

Abstract:

The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

Procedia PDF Downloads 192