Search results for: relational processing
2201 Lithological Mapping and Iron Deposits Identification in El-Bahariya Depression, Western Desert, Egypt, Using Remote Sensing Data Analysis
Authors: Safaa M. Hassan; Safwat S. Gabr, Mohamed F. Sadek
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This study is proposed for the lithological and iron oxides detection in the old mine areas of El-Bahariya Depression, Western Desert, using ASTER and Landsat-8 remote sensing data. Four old iron ore occurrences, namely; El-Gedida, El-Haraa, Ghurabi, and Nasir mine areas found in the El-Bahariya area. This study aims to find new high potential areas for iron mineralization around El-Baharyia depression. Image processing methods such as principle component analysis (PCA) and band ratios (b4/b5, b5/b6, b6/b7, and 4/2, 6/7, band 6) images were used for lithological identification/mapping that includes the iron content in the investigated area. ASTER and Landsat-8 visible and short-wave infrared data found to help mapping the ferruginous sandstones, iron oxides as well as the clay minerals in and around the old mines area of El-Bahariya depression. Landsat-8 band ratio and the principle component of this study showed well distribution of the lithological units, especially ferruginous sandstones and iron zones (hematite and limonite) along with detection of probable high potential areas for iron mineralization which can be used in the future and proved the ability of Landsat-8 and ASTER data in mapping these features. Minimum Noise Fraction (MNF), Mixture Tuned Matched Filtering (MTMF), pixel purity index methods as well as Spectral Ange Mapper classifier algorithm have been successfully discriminated the hematite and limonite content within the iron zones in the study area. Various ASTER image spectra and ASD field spectra of hematite and limonite and the surrounding rocks are compared and found to be consistent in terms of the presence of absorption features at range from 1.95 to 2.3 μm for hematite and limonite. Pixel purity index algorithm and two sub-pixel spectral methods, namely Mixture Tuned Matched Filtering (MTMF) and matched filtering (MF) methods, are applied to ASTER bands to delineate iron oxides (hematite and limonite) rich zones within the rock units. The results are validated in the field by comparing image spectra of spectrally anomalous zone with the USGS resampled laboratory spectra of hematite and limonite samples using ASD measurements. A number of iron oxides rich zones in addition to the main surface exposures of the El-Gadidah Mine, are confirmed in the field. The proposed method is a successful application of spectral mapping of iron oxides deposits in the exposed rock units (i.e., ferruginous sandstone) and present approach of both ASTER and ASD hyperspectral data processing can be used to delineate iron-rich zones occurring within similar geological provinces in any parts of the world.Keywords: Landsat-8, ASTER, lithological mapping, iron exploration, western desert
Procedia PDF Downloads 1452200 Game Space Program: Therapy for Children with Autism Spectrum Disorder
Authors: Khodijah Salimah
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Game Space Program is the program design and development game for therapy the autistic child who had problems with sensory processing and integration. This program is the basic for game space to expand treatment therapy in many areas to help autistic's ability to think through visual perception. This problem can be treated with sensory experience and integration with visual experience to learn how to think and how to learn with visual perception. This perception can be accommodated through an understanding of visual thinking received from sensory exist in game space as virtual healthcare facilities are adjusted based on the sensory needs of children with autism. This paper aims to analyze the potential of virtual visual thinking for treatment autism with the game space program.Keywords: autism, game space program, sensory, virtual healthcare facilities, visual perception
Procedia PDF Downloads 3142199 Real-Time Neuroimaging for Rehabilitation of Stroke Patients
Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge
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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation
Procedia PDF Downloads 3872198 Coupling Large Language Models with Disaster Knowledge Graphs for Intelligent Construction
Authors: Zhengrong Wu, Haibo Yang
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In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.Keywords: large language model, knowledge graph, disaster, deep learning
Procedia PDF Downloads 562197 Far-Field Noise Prediction of Tandem Cylinders Using Incompressible Large Eddy Simulation
Authors: Jesus Ruano, Francesc Xavier Trias, Asensi Oliva
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A three-dimensional incompressible Large Eddy Simulation (LES) is performed to compute the hydrodynamic field around a pair of tandem cylinders. Symmetry-preserving schemes will be used during this simulation in conjunction with Finite Volume Method (FVM) to obtain the hydrodynamic field around the selected geometry. A set of results consisting of pressure and velocity and the combination of them will be stored at different surfaces near the cylinders as the initial input for the second part of the study. A post-processing of the obtained results based on Ffowcs-Williams and Hawkings (FWH) equation with a Fourier Transform of the acoustic sources will be used to compute noise at several probes located far away from the region where the hydrodynamics are computed. Directivities as well as spectral profile of the obtained acoustic field will be analyzed.Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, long-span bodies
Procedia PDF Downloads 3762196 Cereal Bioproducts Conversion to Higher Value Feed by Using Pediococcus Strains Isolated from Spontaneous Fermented Cereal, and Its Influence on Milk Production of Dairy Cattle
Authors: Vita Krungleviciute, Rasa Zelvyte, Ingrida Monkeviciene, Jone Kantautaite, Rolandas Stankevicius, Modestas Ruzauskas, Elena Bartkiene
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The environmental impact of agricultural bioproducts from the processing of food crops is an increasing concern worldwide. Currently, cereal bran has been used as a low-value ingredient for both human consumption and animal feed. The most popular bioprocessing technologies for cereal bran nutritional and technological functionality increasing are enzymatic processing and fermentation, and the most popular starters in fermented feed production are lactic acid bacteria (LAB) including pediococci. However, the ruminant digestive system is unique, there are billions of microorganisms which help the cow to digest and utilize nutrients in the feed. To achieve efficient feed utilization and high milk yield, the microorganisms must have optimal conditions, and the disbalance of this system is highly undesirable. Pediococcus strains Pediococcus acidilactici BaltBio01 and Pediococcus pentosaceus BaltBio02 from spontaneous fermented rye were isolated (by rep – PCR method), identified, and characterized by their growth (by Thermo Bioscreen C automatic turbidometer), acidification rate (2 hours in 2.5 pH), gas production (Durham method), and carbohydrate metabolism (by API 50 CH test ). Antimicrobial activities of isolated pediococcus against variety of pathogenic and opportunistic bacterial strains previously isolated from diseased cattle, and their resistance to antibiotics were evaluated (EFSA-FEEDAP method). The isolated pediococcus strains were cultivated in barley/wheat bran (90 / 10, m / m) substrate, and developed supplements, with high content of valuable pediococcus, were used for Lithuanian black and white dairy cows feeding. In addition, the influence of supplements on milk production and composition was determined. Milk composition was evaluated by the LactoScope FTIR” FT1.0. 2001 (Delta Instruments, Holland). P. acidilactici BaltBio01 and P. pentosaceus BaltBio02 demonstrated versatile carbohydrate metabolism, grown at 30°C and 37°C temperatures, and acidic tolerance. Isolated pediococcus strains showed to be non resistant to antibiotics, and having antimicrobial activity against undesirable microorganisms. By barley/wheat bran utilisation using fermentation with selected pediococcus strains, it is possible to produce safer (reduced Enterobacteriaceae, total aerobic bacteria, yeast and mold count) feed stock with high content of pediococcus. Significantly higher milk yield (after 33 days) by using pediococcus supplements mix for dairy cows feeding could be obtained, while similar effect by using separate strains after 66 days of feeding could be achieved. It can be stated that barley/wheat bran could be used for higher value feed production in order to increase milk production. Therefore, further research is needed to identify what is the main mechanism of the positive action.Keywords: barley/wheat bran, dairy cattle, fermented feed, milk, pediococcus
Procedia PDF Downloads 3072195 The Role of Emotion in Attention Allocation
Authors: Michaela Porubanova
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In this exploratory study to examine the effects of emotional significance on change detection using the flicker paradigm, three different categories of scenes were randomly presented (neutral, positive and negative) in three different blocks. We hypothesized that because of the different effects on attention, performance in change detection tasks differs for scenes with different effective values. We found the greatest accuracy of change detection was for changes occurring in positive and negative scenes (compared with neutral scenes). Secondly and most importantly, changes in negative scenes (and also positive scenes, though not with statistical significance) were detected faster than changes in neutral scenes. Interestingly, women were less accurate than men in detecting changes in emotionally significant scenes (both negative and positive), i.e., women detected fewer changes in emotional scenes in the time limit of 40s. But on the other hand, women were quicker to detect changes in positive and negative images than men. The study makes important contributions to the area of the role of emotions on information processing. The role of emotion in attention will be discussed.Keywords: attention, emotion, flicker task, IAPS
Procedia PDF Downloads 3542194 Efficient Manageability and Intelligent Classification of Web Browsing History Using Machine Learning
Authors: Suraj Gururaj, Sumantha Udupa U.
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Browsing the Web has emerged as the de facto activity performed on the Internet. Although browsing gets tracked, the manageability aspect of Web browsing history is very poor. In this paper, we have a workable solution implemented by using machine learning and natural language processing techniques for efficient manageability of user’s browsing history. The significance of adding such a capability to a Web browser is that it ensures efficient and quick information retrieval from browsing history, which currently is very challenging. Our solution guarantees that any important websites visited in the past can be easily accessible because of the intelligent and automatic classification. In a nutshell, our solution-based paper provides an implementation as a browser extension by intelligently classifying the browsing history into most relevant category automatically without any user’s intervention. This guarantees no information is lost and increases productivity by saving time spent revisiting websites that were of much importance.Keywords: adhoc retrieval, Chrome extension, supervised learning, tile, Web personalization
Procedia PDF Downloads 3762193 Thermoelectric Properties of Doped Polycrystalline Silicon Film
Authors: Li Long, Thomas Ortlepp
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The transport properties of carriers in polycrystalline silicon film affect the performance of polycrystalline silicon-based devices. They depend strongly on the grain structure, grain boundary trap properties and doping concentration, which in turn are determined by the film deposition and processing conditions. Based on the properties of charge carriers, phonons, grain boundaries and their interactions, the thermoelectric properties of polycrystalline silicon are analyzed with the relaxation time approximation of the Boltz- mann transport equation. With this approach, thermal conductivity, electrical conductivity and Seebeck coefficient as a function of grain size, trap properties and doping concentration can be determined. Experiment on heavily doped polycrystalline silicon is carried out and measurement results are compared with the model.Keywords: conductivity, polycrystalline silicon, relaxation time approximation, Seebeck coefficient, thermoelectric property
Procedia PDF Downloads 1242192 Analysing Environmental Licensing of Infrastructure Projects in Brazil
Authors: Ronaldo Seroa Da Motta, Gabriela Santiago
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The main contribution of this study is the identification of the factors influencing the environmental licensing process of infrastructure projects in Brazil. These factors will be those that reflect the technical characteristics of the project, the corporate governance of the entrepreneur, and the institutional and regulatory governance of the environmental agency, including the number of interventions by non-licensing agencies. The model conditions these variables to the licensing processing time of 34 infrastructure projects. Our results indicated that the conditions would be more sensitive to the type of enterprise, complexity as in gas pipelines and hydroelectric plants in the most vulnerable biome with a greater value of the enterprise or the entrepreneur's assets, together with the number of employees of the licensing agency. The number of external interventions by other non-licensing institutions does not affect the licensing time. Such results challenge the current criticism that environmental licensing has been often pointed out as a barrier to speed up investments in infrastructure projects in Brazil due to the participation of civil society and other non-licensing institutions.Keywords: environmental licensing, condionants, Brazil, timing process
Procedia PDF Downloads 1342191 An Improved C-Means Model for MRI Segmentation
Authors: Ying Shen, Weihua Zhu
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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy
Procedia PDF Downloads 2252190 A Narrative of Nationalism in Mainstream Media: The US, China, and COVID-19
Authors: Rachel Williams, Shiqi Yang
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Our research explores the influence nationalism has had on media coverage of the COVID-19 pandemic as it relates to China in the United States through an inclusive qualitative analysis of two US news networks, Fox News and CNN. In total, the transcripts of sixteen videos uploaded on YouTube, each with more than 100,000 views, were gathered for data processing. Co-occurrence networks generated by KH Coder illuminate the themes and narratives underpinning the reports from Fox News and CNN. The results of in-depth content analysis with keywords suggest that the pandemic has been framed in an ethnopopulist nationalist manner, although to varying degrees between networks. Specifically, the authors found that Fox News is more likely to report hypotheses or statements as a fact; on the contrary, CNN is more likely to quote data and statements from official institutions. Future research into how nationalist narratives have developed in China and in other US news coverage with a more systematic and quantitative method can be conducted to expand on these findings.Keywords: nationalism, media studies, us and china, COVID-19, social media, communication studies
Procedia PDF Downloads 562189 Networked Radar System to Increase Safety of Urban Railroad Crossing
Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto
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The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.Keywords: radar for safe mobility, railroad crossing, railway, transport safety
Procedia PDF Downloads 4802188 Comparison of Parallel CUDA and OpenMP Implementations of Memetic Algorithms for Solving Optimization Problems
Authors: Jason Digalakis, John Cotronis
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Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems
Procedia PDF Downloads 1012187 Linear Array Geometry Synthesis with Minimum Sidelobe Level and Null Control Using Taguchi Method
Authors: Amara Prakasa Rao, N. V. S. N. Sarma
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This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design.Keywords: array factor, beamforming, null placement, optimization method, orthogonal array, Taguchi method, smart antenna system
Procedia PDF Downloads 3942186 Sentiment Analysis on the East Timor Accession Process to the ASEAN
Authors: Marcelino Caetano Noronha, Vosco Pereira, Jose Soares Pinto, Ferdinando Da C. Saores
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One particularly popular social media platform is Youtube. It’s a video-sharing platform where users can submit videos, and other users can like, dislike or comment on the videos. In this study, we conduct a binary classification task on YouTube’s video comments and review from the users regarding the accession process of Timor Leste to become the eleventh member of the Association of South East Asian Nations (ASEAN). We scrape the data directly from the public YouTube video and apply several pre-processing and weighting techniques. Before conducting the classification, we categorized the data into two classes, namely positive and negative. In the classification part, we apply Support Vector Machine (SVM) algorithm. By comparing with Naïve Bayes Algorithm, the experiment showed SVM achieved 84.1% of Accuracy, 94.5% of Precision, and Recall 73.8% simultaneously.Keywords: classification, YouTube, sentiment analysis, support sector machine
Procedia PDF Downloads 1082185 The Use of Thermal Infrared Wavelengths to Determine the Volcanic Soils
Authors: Levent Basayigit, Mert Dedeoglu, Fadime Ozogul
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In this study, an application was carried out to determine the Volcanic Soils by using remote sensing. The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models.Keywords: Landsat 7, soil moisture index, temperature models, volcanic soils
Procedia PDF Downloads 3052184 Spatial Econometric Approaches for Count Data: An Overview and New Directions
Authors: Paula Simões, Isabel Natário
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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data
Procedia PDF Downloads 5932183 X-Corner Detection for Camera Calibration Using Saddle Points
Authors: Abdulrahman S. Alturki, John S. Loomis
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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.Keywords: camera calibration, corner detector, edge detector, saddle points
Procedia PDF Downloads 4062182 A TiO₂-Based Memristor Reliable for Neuromorphic Computing
Authors: X. S. Wu, H. Jia, P. H. Qian, Z. Zhang, H. L. Cai, F. M. Zhang
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A bipolar resistance switching behaviour is detected for a Ti/TiO2-x/Au memristor device, which is fabricated by a masked designed magnetic sputtering. The current dependence of voltage indicates the curve changes slowly and continuously. When voltage pulses are applied to the device, the set and reset processes maintains linearity, which is used to simulate the synapses. We argue that the conduction mechanism of the device is from the oxygen vacancy channel model, and the resistance of the device change slowly due to the reaction between the titanium electrode and the intermediate layer and the existence of a large number of oxygen vacancies in the intermediate layer. Then, Hopfield neural network is constructed to simulate the behaviour of neural network in image processing, and the accuracy rate is more than 98%. This shows that titanium dioxide memristor has a broad application prospect in high performance neural network simulation.Keywords: memristor fabrication, neuromorphic computing, bionic synaptic application, TiO₂-based
Procedia PDF Downloads 902181 Effects of Education on Farmers’ Productivity Outputs in Rural Nigeria
Authors: Thomas Ogilegwu Orohu
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This paper highlights the effect of education on farmers’ productivity in rural Nigeria which includes potential to obtain paid employment or generate income through self-help employment using skills learnt in school. The paper emphasizes that education help farmers’ in agro-processing units in production to reduce post harvest wastage. It highlights the benefits of schooling for farmers’ productivity, particularly in terms of efficiency gains and increased farm productivity. As technological innovation spread more widely within the country, the importance of formal education in farm production ought to become more apparent. Education help farmers to improve attitudes, beliefs and habits that may lead to greater willingness to accept risk, adopts innovation, save investment and generally to embrace productive practices. Finally factors affecting farmers’ education and appropriate recommendation were given with the hope that if resolutely implemented would bring the attainment of desired farm education to farmers to improve farm productivity outputs.Keywords: benefit, education, effect, productivity
Procedia PDF Downloads 3192180 Application of Phenol Degrading Microorganisms for the Treatment of Olive Mill Waste (OMW)
Authors: M. A. El-Khateeb
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The growth of the olive oil production in Saudi Arabia peculiarly in Al Jouf region in recent years has been accompanied by an increase in the discharge of associated processing waste. Olive mill waste is produced throughout the extraction of oil from the olive fruit using the traditional mill and press process. Deterioration of the environment due to olive mill disposal wastes is a serious problem. When olive mill waste disposed into the soil, it affects soil quality, soil micro flora, and also toxic to plants. The aim of this work is to isolate microorganism (bacterial or fungal strains) from OMW capable of degrading phenols. Olive mill wastewater, olive mill waste and soil (beside oil production mill) contaminated with olive waste were used for isolation of phenol tolerant microorganisms. Four strains (two fungal and two bacterial) were isolated from olive mill waste. The isolated strains were Candida tropicalis and Phanerochaete chrysosporium (fungal strains) and Bacillus sp. and Rhodococcus sp. (bacterial strains). These strains were able to degrade phenols and could be used for bioremediation of olive mill waste.Keywords: bioremediation, bacteria, fungi, Sakaka
Procedia PDF Downloads 3622179 Coal Mining Safety Monitoring Using Wsn
Authors: Somdatta Saha
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The main purpose was to provide an implementable design scenario for underground coal mines using wireless sensor networks (WSNs). The main reason being that given the intricacies in the physical structure of a coal mine, only low power WSN nodes can produce accurate surveillance and accident detection data. The work mainly concentrated on designing and simulating various alternate scenarios for a typical mine and comparing them based on the obtained results to arrive at a final design. In the Era of embedded technology, the Zigbee protocols are used in more and more applications. Because of the rapid development of sensors, microcontrollers, and network technology, a reliable technological condition has been provided for our automatic real-time monitoring of coal mine. The underground system collects temperature, humidity and methane values of coal mine through sensor nodes in the mine; it also collects the number of personnel inside the mine with the help of an IR sensor, and then transmits the data to information processing terminal based on ARM.Keywords: ARM, embedded board, wireless sensor network (Zigbee)
Procedia PDF Downloads 3402178 The Impact of Business Process Reengineering to the Company Performance through TQM and Enterprise Resource Planning Implementation on Manufacturing Companies in East Java, Indonesia
Authors: Widjojo Suprapto, Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana
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Business process reengineering can be conducted by some procedure rationalization for all related departments in a company so that all data and business processes are connected. The changing of any business process is used to set up the working standard so that it gives an impact to the implementation of ERP and the company performance. After collecting and processing the data from 77 manufacturing companies, it is obtained that BPR (Business Process Reengineering) has no direct impact on the implementation of ERP (Enterprise Resource Planning) in the companies and manufacturing performance; however, it influences the implementation of TQM. The implementation of TQM influences directly the implementation of ERP, but it does not influence directly the company performance. The implementation of ERP gives a significant increase in the work performance of the manufacturing companies in East Java.Keywords: enterprise resources planning, business process reengineering, TQM, company performance
Procedia PDF Downloads 2072177 Use of Cassava Flour in Cakes Processing
Authors: S. S. Silva, S. M. A. Souza, C. F. P. Oliveira
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Brazil's agriculture is a major economic base in the country; in addition, family farming is directly responsible for the production of most agricultural products in Brazil, such as cassava. The number of studies on the use of cassava and its derivatives in the food industry has been increased, which is the basis of this study. Sought to develop a food that take advantage the products from farmers, adding value to these products and to study its effects as a replacement for wheat flour. For such elaborated a gluten-free cake – aiming to meet the needs of the celiac public – containing cassava flour, cane sugar, honey, egg, soya oil, coconut desiccated, baking powder and water. For evaluation of their characteristics technological, physicochemical and texture characterizations were done. Cake showed similar characteristics of cake made with wheat flour and growth and aeration of the dough. In sum up, marketing the product is viable, in that it has a typical overall appearance of cake made of wheat flour, meet the needs of celiac people and value the family farming.Keywords: baking, cake, cassava flour, celiac disease
Procedia PDF Downloads 4252176 Performance and Pellet Quality in Broiler Fed with Different Levels of Fat and Pellet Binders
Authors: Reza Vakili
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To assess the effect of different levels of soybean oil (SO: 1, 2%) and different types of pellet binders (sodium bentonite (SB), calcium lignosulfonate (Ca-Ls), and plant compounds (PC) on the pellet quality, and broilers’ performance, 480 one-day-old male broiler chickens (Ross 308) were used. The results showed that in the starter diet, the 1-PC group had the highest pellet durability index (PDI) (P<0.05). The PDI of the grower diet containing SB and PC was higher than others (P<0.05). The highest pellet hardness was observed in groups 1-SB, 1-PC, 2-SB, and 2-PC for the starter diet (P<0.05). For the finisher diet, the hardness of pellets containing SB and PC was higher (P<0.05). During the starter phase, the best feed conversion ratio (FCR) was obtained in 1-SB (P<0.05). The lowest and highest daily feed intake was observed in groups 2-PC and 1-SB, respectively, during the finisher phase. During the finisher and whole phases, the most daily body weight gain was observed in the SB group (P<0.05).Keywords: bentonite, birds, body weight, feed processing, pellet durability, soybean oil
Procedia PDF Downloads 342175 Efficient Ground Targets Detection Using Compressive Sensing in Ground-Based Synthetic-Aperture Radar (SAR) Images
Authors: Gherbi Nabil
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Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.Keywords: compressive sensing, raw complex data, synthetic aperture radar, ADMM
Procedia PDF Downloads 182174 Unity in Diversity: Exploring the Psychological Processes and Mechanisms of the Sense of Community for the Chinese Nation in Ethnic Inter-embedded Communities
Authors: Jiamin Chen, Liping Yang
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In 2007, sociologist Putnam proposed a pessimistic forecast in the United States' "Social Capital Community Benchmark Survey," suggesting that "ethnic diversity would challenge social unity and undermine social cohesion." If this pessimistic assumption were proven true, it would indicate a risk of division in diverse societies. China, with 56 ethnic groups, is a multi-ethnic country. On May 26, 2014, General Secretary Xi Jinping proposed "building ethnically inter-embedded communities to promote deeper development in interactions, exchanges, and integration among ethnic groups." Researchers unanimously agree that ethnic inter-embedded communities can serve as practical arenas and pathways for solidifying the sense of the Chinese national community However, there is no research providing evidence that ethnic inter-embedded communities can foster the sense of the Chinese national community, and the influencing factors remain unclear. This study adopts a constructivist grounded theory research approach. Convenience sampling and snowball sampling were used in the study. Data were collected in three communities in Kunming City. Twelve individuals were eventually interviewed, and the transcribed interviews totaled 187,000 words. The research has obtained ethical approval from the Ethics Committee of Nanjing Normal University (NNU202310030). The research analyzed the data and constructed theories, employing strategies such as coding, constant comparison, and theoretical sampling. The study found that: firstly, ethnic inter-embedded communities exhibit characteristics of diversity, including ethnic diversity, cultural diversity, and linguistic diversity. Diversity has positive functions, including increased opportunities for contact, promoting self-expansion, and increasing happiness; negative functions of diversity include highlighting ethnic differences, causing ethnic conflicts, and reminding of ethnic boundaries. Secondly, individuals typically engage in interactions within the community using active embedding and passive embedding strategies. Active embedding strategies include maintaining openness, focusing on similarities, and pro-diversity beliefs, which can increase external group identification, intergroup relational identity, and promote ethnic integration. Individuals using passive embedding strategies tend to focus on ethnic stereotypes, perceive stigmatization of their own ethnic group, and adopt an authoritarian-oriented approach to interactions, leading to a perception of more identity threats and ultimately rejecting ethnic integration. Thirdly, the commonality of the Chinese nation is reflected in the 56 ethnic groups as an "identity community" and "interest community," and both active and passive embedding paths affect individual understanding of the commonality of the Chinese nation. Finally, community work and environment can influence the embedding process. The research constructed a social psychological process and mechanism model for solidifying sense of the Chinese national community in ethnic inter-embedded communities. Based on this theoretical model, future research can conduct more micro-level psychological mechanism tests and intervention studies to enhance Chinese national cohesion.Keywords: diversity, sense of the chinese national community, ethnic inter-embedded communities, ethnic group
Procedia PDF Downloads 382173 Solar Power Forecasting for the Bidding Zones of the Italian Electricity Market with an Analog Ensemble Approach
Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva
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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.Keywords: analog ensemble, electricity market, PV forecast, solar energy
Procedia PDF Downloads 1582172 Learning Object Interface Adapted to the Learner's Learning Style
Authors: Zenaide Carvalho da Silva, Leandro Rodrigues Ferreira, Andrey Ricardo Pimentel
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Learning styles (LS) refer to the ways and forms that the student prefers to learn in the teaching and learning process. Each student has their own way of receiving and processing information throughout the learning process. Therefore, knowing their LS is important to better understand their individual learning preferences, and also, understand why the use of some teaching methods and techniques give better results with some students, while others it does not. We believe that knowledge of these styles enables the possibility of making propositions for teaching; thus, reorganizing teaching methods and techniques in order to allow learning that is adapted to the individual needs of the student. Adapting learning would be possible through the creation of online educational resources adapted to the style of the student. In this context, this article presents the structure of a learning object interface adaptation based on the LS. The structure created should enable the creation of the adapted learning object according to the student's LS and contributes to the increase of student’s motivation in the use of a learning object as an educational resource.Keywords: adaptation, interface, learning object, learning style
Procedia PDF Downloads 406