Search results for: loss models
9127 Post Harvest Losses and Food Security in Northeast Nigeria What Are the Key Challenges and Concrete Solutions
Authors: Adebola Adedugbe
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The challenge of post-harvest losses poses serious threats for food security in Nigeria and the north-eastern part with the country losing about $9billion annually due to postharvest losses in the sector. Post-harvest loss (PHL) is the quantitative and qualitative loss of food in various post-harvest operations. In Nigeria, post-harvest losses (PHL) have been a major challenge to food security and improved farmer’s income. In 2022, the Nigerian government had said over 30 percent of food produced by Nigerian farmers perish during post-harvest. For many in northeast Nigeria, agriculture is the predominant source of livelihood and income. The persistent communal conflicts, flood, decade-old attacks by boko haram and insurgency in this region have disrupted farming activities drastically, with farmlands becoming insecure and inaccessible as communities are forced to abandon ancestral homes, The impact of climate change is also affecting agricultural and fishing activities, leading to shortage of food supplies, acute hunger and loss of livelihood. This has continued to impact negatively on the region and country’s food production and availability making it loose billions of US dollars annually in income in this sector. The root cause of postharvest losses among others in crops, livestock and fisheries are lack of modern post-harvest equipment, chemical and lack of technologies used for combating losses. The 2019 Global Hunger Index showed Nigeria’s case was progressing from a ‘serious to alarming level’. As part of measures to address the problem of post-harvest losses experienced by farmers, the federal government of Nigeria concessioned 17 silos with 6000 metric tonne storage space to private sector to enable farmers to have access to storage facilities. This paper discusses the causes, effects and solutions in handling post-harvest losses and optimize returns on food security in northeast Nigeria.Keywords: farmers, food security, northeast Nigeria, postharvest loss
Procedia PDF Downloads 719126 Modeling and Shape Prediction for Elastic Kinematic Chains
Authors: Jiun Jeon, Byung-Ju Yi
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This paper investigates modeling and shape prediction of elastic kinematic chains such as colonoscopy. 2D and 3D models of elastic kinematic chains are suggested and their behaviors are demonstrated through simulation. To corroborate the effectiveness of those models, experimental work is performed using a magnetic sensor system.Keywords: elastic kinematic chain, shape prediction, colonoscopy, modeling
Procedia PDF Downloads 6039125 A Low-Power, Low-Noise and High Linearity 60 GHz LNA for WPAN Applications
Authors: Noha Al Majid, Said Mazer, Moulhime El Bekkali, Catherine Algani, Mahmoud Mehdi
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A low noise figure (NF) and high linearity V-band Low Noise Amplifier (LNA) is reported in this article. The LNA compromises a three-stage cascode configuration. This LNA will be used as a part of a WPAN (Wireless Personal Area Network) receiver in the millimeter-wave band at 60 GHz. It is designed according to the MMIC technology (Monolithic Microwave Integrated Circuit) in PH 15 process from UMS foundry and uses a 0.15 μm GaAs PHEMT (Pseudomorphic High Electron Mobility Transistor). The particularity of this LNA compared to other LNAs in literature is its very low noise figure which is equal to 1 dB and its high linearity (IIP3 is about 22 dB). The LNA consumes 0.24 Watts, achieving a high gain which is about 23 dB, an input return loss better than -10 dB and an output return loss better than -8 dB.Keywords: low noise amplifier, V-band, MMIC technology, LNA, amplifier, cascode, pseudomorphic high electron mobility transistor (PHEMT), high linearity
Procedia PDF Downloads 5109124 The Models of Character Development Bali Police to Improve Quality of Moral Members in Bali Police Headquarters
Authors: Agus Masrukhin
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This research aims to find and analyze the model of character building in the Police Headquarters in Bali with a case study of Muslim members in improving the quality of the morality of its members. The formation of patterns of thinking, behavior, mentality, and police officers noble character, later can be used as a solution to reduce the hedonistic nature of the challenges in the era of globalization. The benefit of this study is expected to be a positive recommendation to find a constructive character building models of police officers in the Republic of Indonesia, especially Bali Police. For the long term, the discovery of the character building models can be developed for the entire police force in Indonesia. The type of research that would apply in this study researchers mix the qualitative research methods based on the narrative between the subject and the concrete experience of field research and quantitative research methods with 92 respondents from the police regional police Bali. This research used a descriptive analysis and SWOT analysis then it is presented in the FGD (focus group discussion). The results of this research indicate that the variable modeling the leadership of the police and variable police offices culture have significant influence on the implementation of spiritual development.Keywords: positive constructive, hedonistic, character models, morality
Procedia PDF Downloads 3659123 Analysis and Experimental Research on the Influence of Lubricating Oil on the Transmission Efficiency of New Energy Vehicle Gearbox
Authors: Chen Yong, Bi Wangyang, Zang Libin, Li Jinkai, Cheng Xiaowei, Liu Jinmin, Yu Miao
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New energy vehicle power transmission systems continue to develop in the direction of high torque, high speed, and high efficiency. The cooling and lubrication of the motor and the transmission system are integrated, and new requirements are placed on the lubricants for the transmission system. The effects of traditional lubricants and special lubricants for new energy vehicles on transmission efficiency were studied through experiments and simulation methods. A mathematical model of the transmission efficiency of the lubricating oil in the gearbox was established. The power loss of each part was analyzed according to the working conditions. The relationship between the speed and the characteristics of different lubricating oil products on the power loss of the stirring oil was discussed. The minimum oil film thickness was required for the life of the gearbox. The accuracy of the calculation results was verified by the transmission efficiency test conducted on the two-motor integrated test bench. The results show that the efficiency increases first and then decreases with the increase of the speed and decreases with the increase of the kinematic viscosity of the lubricant. The increase of the kinematic viscosity amplifies the transmission power loss caused by the high speed. New energy vehicle special lubricants have less attenuation of transmission efficiency in the range above mid-speed. The research results provide a theoretical basis and guidance for the evaluation and selection of transmission efficiency of gearbox lubricants for new energy vehicles.Keywords: new energy vehicles, lubricants, transmission efficiency, kinematic viscosity, test and simulation
Procedia PDF Downloads 1309122 Comparative Mesh Sensitivity Study of Different Reynolds Averaged Navier Stokes Turbulence Models in OpenFOAM
Authors: Zhuoneng Li, Zeeshan A. Rana, Karl W. Jenkins
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In industry, to validate a case, often a multitude of simulation are required and in order to demonstrate confidence in the process where users tend to use a coarser mesh. Therefore, it is imperative to establish the coarsest mesh that could be used while keeping reasonable simulation accuracy. To date, the two most reliable, affordable and broadly used advanced simulations are the hybrid RANS (Reynolds Averaged Navier Stokes)/LES (Large Eddy Simulation) and wall modelled LES. The potentials in these two simulations will still be developed in the next decades mainly because the unaffordable computational cost of a DNS (Direct Numerical Simulation). In the wall modelled LES, the turbulence model is applied as a sub-grid scale model in the most inner layer near the wall. The RANS turbulence models cover the entire boundary layer region in a hybrid RANS/LES (Detached Eddy Simulation) and its variants, therefore, the RANS still has a very important role in the state of art simulations. This research focuses on the turbulence model mesh sensitivity analysis where various turbulence models such as the S-A (Spalart-Allmaras), SSG (Speziale-Sarkar-Gatski), K-Omega transitional SST (Shear Stress Transport), K-kl-Omega, γ-Reθ transitional model, v2f are evaluated within the OpenFOAM. The simulations are conducted on a fully developed turbulent flow over a flat plate where the skin friction coefficient as well as velocity profiles are obtained to compare against experimental values and DNS results. A concrete conclusion is made to clarify the mesh sensitivity for different turbulence models.Keywords: mesh sensitivity, turbulence models, OpenFOAM, RANS
Procedia PDF Downloads 2609121 Power Efficiency Characteristics of Magnetohydrodynamic Thermodynamic Gas Cycle
Authors: Mahmoud Huleihil
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In this study, the performance of a thermodynamic gas cycle of magnetohydrodynamic (MHD) power generation is considered and presented in terms of power efficiency curves. The dissipation mechanisms considered include: fluid friction modeled by means of the isentropic efficiency of the compressor, heat transfer leakage directly from the hot reservoir to the cold heat reservoir, and constant velocity of the MHD generator. The study demonstrates that power and efficiency vanish at the extremes of both slow and fast operating conditions. These points are demonstrated on power efficiency curves and the locus of efficiency at maximum power and the locus of maximum efficiency. Qualitatively, the considered loss mechanisms have a similar effect on the efficiency at maximum power operation and on maximum efficiency operation, thus these efficiencies are reduced, even for small values of the loss mechanisms.Keywords: magnetohydrodynamic generator, electrical efficiency, maximum power, maximum efficiency, heat engine
Procedia PDF Downloads 2439120 Quantifying Uncertainties in an Archetype-Based Building Stock Energy Model by Use of Individual Building Models
Authors: Morten Brøgger, Kim Wittchen
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Focus on reducing energy consumption in existing buildings at large scale, e.g. in cities or countries, has been increasing in recent years. In order to reduce energy consumption in existing buildings, political incentive schemes are put in place and large scale investments are made by utility companies. Prioritising these investments requires a comprehensive overview of the energy consumption in the existing building stock, as well as potential energy-savings. However, a building stock comprises thousands of buildings with different characteristics making it difficult to model energy consumption accurately. Moreover, the complexity of the building stock makes it difficult to convey model results to policymakers and other stakeholders. In order to manage the complexity of the building stock, building archetypes are often employed in building stock energy models (BSEMs). Building archetypes are formed by segmenting the building stock according to specific characteristics. Segmenting the building stock according to building type and building age is common, among other things because this information is often easily available. This segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all buildings in a segment of the building stock is associated with loss of detail. Thermal characteristics are aggregated while other characteristics, which could affect the energy efficiency of a building, are disregarded. Thus, using a simplified representation of the building stock could come at the expense of the accuracy of the model. The present study evaluates the accuracy of a conventional archetype-based BSEM that segments the building stock according to building type- and age. The accuracy is evaluated in terms of the archetypes’ ability to accurately emulate the average energy demands of the corresponding buildings they were meant to represent. This is done for the buildings’ energy demands as a whole as well as for relevant sub-demands. Both are evaluated in relation to the type- and the age of the building. This should provide researchers, who use archetypes in BSEMs, with an indication of the expected accuracy of the conventional archetype model, as well as the accuracy lost in specific parts of the calculation, due to use of the archetype method.Keywords: building stock energy modelling, energy-savings, archetype
Procedia PDF Downloads 1539119 Vertebral Transverse Open Wedge Osteotomy in Correction of Thoracolumbar Kyphosis Resulting from Ankylosing Spondylitis
Authors: S. AliReza Mirghasemi, Amin Mohamadi, Zameer Hussain, Narges Rahimi Gabaran, Mir Mostafa Sadat, Shervin Rashidinia
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In progressive cases of Ankylosing Spondylitis, patients will have high degrees of kyphosis leading to severe disabilities. Several operative techniques have been used in this stage, but little knowledge exists on the indications for and outcome of these methods. In this study, we examined the efficacy of monosegmental transverse open wedge osteotomy of L3 in 11 patients with progressive spinal kyphosis. The average correction was 36̊ (20 to 42) with no loss of correction after operation. The average operating time was 120 minutes (100 to 130) and the mean blood loss was 1500 ml (1100 to 2000). Osteotomy corrected all patients sufficiently to allow them to see ahead and their posture was improved. There were no fatal complications but one patient had paraplegia after the operation.Keywords: ankylosing spondylitis, thoracolumbar kyphosis, open wedge osteotomy, L3 transverse open wedge osteotomy
Procedia PDF Downloads 3919118 Statistical Analysis and Impact Forecasting of Connected and Autonomous Vehicles on the Environment: Case Study in the State of Maryland
Authors: Alireza Ansariyar, Safieh Laaly
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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models
Procedia PDF Downloads 4429117 The Network Relative Model Accuracy (NeRMA) Score: A Method to Quantify the Accuracy of Prediction Models in a Concurrent External Validation
Authors: Carl van Walraven, Meltem Tuna
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Background: Network meta-analysis (NMA) quantifies the relative efficacy of 3 or more interventions from studies containing a subgroup of interventions. This study applied the analytical approach of NMA to quantify the relative accuracy of prediction models with distinct inclusion criteria that are evaluated on a common population (‘concurrent external validation’). Methods: We simulated binary events in 5000 patients using a known risk function. We biased the risk function and modified its precision by pre-specified amounts to create 15 prediction models with varying accuracy and distinct patient applicability. Prediction model accuracy was measured using the Scaled Brier Score (SBS). Overall prediction model accuracy was measured using fixed-effects methods that accounted for model applicability patterns. Prediction model accuracy was summarized as the Network Relative Model Accuracy (NeRMA) Score which ranges from -∞ through 0 (accuracy of random guessing) to 1 (accuracy of most accurate model in concurrent external validation). Results: The unbiased prediction model had the highest SBS. The NeRMA score correctly ranked all simulated prediction models by the extent of bias from the known risk function. A SAS macro and R-function was created to implement the NeRMA Score. Conclusions: The NeRMA Score makes it possible to quantify the accuracy of binomial prediction models having distinct inclusion criteria in a concurrent external validation.Keywords: prediction model accuracy, scaled brier score, fixed effects methods, concurrent external validation
Procedia PDF Downloads 2349116 Investigating the Factors Affecting Generalization of Deep Learning Models for Plant Disease Detection
Authors: Praveen S. Muthukumarana, Achala C. Aponso
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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis
Procedia PDF Downloads 1429115 Deep Learning Based, End-to-End Metaphor Detection in Greek with Recurrent and Convolutional Neural Networks
Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos
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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.Keywords: metaphor detection, deep learning, representation learning, embeddings
Procedia PDF Downloads 1529114 Mechanical and Micro-Structural Properties of Fly Ash Based Geopolymer with High-Temperature Exposure
Authors: Young-Cheol Choi, Joo-Hyung Kim, Gyu-Don Moon
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This paper discusses the effect of Na2O (alkali) content, SiO2/Na2O mole ratio, and elevated temperature on the mechanical performance of fly-ash-based inorganic green geopolymer composites. Fly-ash-based geopolymers, which were manufactured with varying alkali contents (4–8 % of fly ash weight) and SiO2/Na2O mole ratios (0.6–1.4), were subjected to elevated temperatures up to 900 ºC ; the geopolymer composites and their performance were evaluated on the basis of weight loss and strength loss after temperature exposure. In addition, mineralogical changes due to the elevated temperature exposure were studied using x-ray diffraction. Investigations of microstructures and microprobe analysis were performed using mercury intrusion porosimetry. The results showed that the fly-ash-based geopolymer responded significantly to high-temperature conditions.Keywords: fly ash, geopolymer, micro-structure, high-temperature, mechanical structural
Procedia PDF Downloads 5969113 Chemometric QSRR Evaluation of Behavior of s-Triazine Pesticides in Liquid Chromatography
Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević
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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis
Procedia PDF Downloads 3899112 Effect of Polymer Concentration on the Rheological Properties of Polyelectrolyte Solutions
Authors: Khaled Benyounes, Abderrahmane Mellak
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The rheology of aqueous solutions of polyelectrolyte (polyanionic cellulose, PAC) at high molecular weight was investigated using a controlled stress rheometer. Several rheological measurements; viscosity measurements, creep compliance tests at a constant low shear stress and oscillation experiments have been performed. The concentrations ranged by weight from 0.01 to 2.5% of PAC. It was found that the aqueous solutions of PAC do not exhibit a yield stress, the flow curves of PAC over a wide range of shear rate (0 to 1000 s-1) could be described by the cross model and the Williamson models. The critical concentrations of polymer c* and c** have been estimated. The dynamic moduli, i.e., storage modulus (G’) and loss modulus (G’’) of the polymer have been determined at frequency sweep from 0.01 to 10 Hz. At polymer concentration above 1%, the modulus G’ is superior to G’’. The relationships between the dynamic modulus and concentration of polymer have been established. The creep-recovery experiments demonstrated that polymer solutions show important viscoelastic properties of system water-PAC when the concentration of the polymer increases.Keywords: polyanionic cellulose, viscosity, creep, oscillation, cross model
Procedia PDF Downloads 3249111 Transition from Early Education to Pre-School Education in Children with Hearing Loss in Turkey: Problems and Recommendations
Authors: Şule Yanık, Emel Ertürk-Mustul, Zerrin Turan, Hasan Gürgür
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It is known that there are policies that will support the early special education (ESE) for children requiring special care including the children with hearing loss (CHL) in many countries that give importance to early childhood (0-6 years) education, accordingly ESE services have been gradually increasing and these services provide positive contributions to the child and family. These services begin with medical diagnostics, provision of the use of assistive technologies for hearing and the orientation of children towards early education program (EEP) for the CHL. In 0-3 years of age EEP, education and support services are provided to the children and their families. In 3-6 years of age, children are supported in a pre-school education program (PSE) in which their peers and teachers are present. Therefore, the children with hearing loss and their families are going through a series of medical, educational and social transition process after diagnosed with hearing loss. Depending on their age and development, CHL also go through a transition period from hospital to home, from home to EEP and from EEP to PSE. It is seen that there is no legal regulation regarding the transition process in Turkey and hence different processes have been carried out in the transition process from EEP to PSE. The aim of this study is to reveal the problems confronted by the CHL during the transition period from EEP to PSE and the solution proposals for these problems. In this study, a document review was made by reviewing the national and international studies about transition processes of the CHL in Turkey from EEP to PSE. Accordingly, in the study carried out in two stages, firstly, a review of the body of literature was performed by creating key words related to the subject. Secondly, the problems confronted by the CHL in Turkey during the transition period from EEP to PSE and the solution proposals for these problems were demonstrated by analyzing the obtained data. According to the body of literature, it is seen that there are no laws concerning the transition processes of the children who require special care including the CHL in Turkey from EEP (sending) to PSE (receiving), and correspondingly numerous problems have been experienced during the transition period. It seems that the EEP adopts family-centered approaches for strengthening the families of the CHL. However, PSE program aims to prepare the children to school life by focusing on their social and academical development rather with the adoption of children-centered approaches. Therefore, while the families feel an inseparable part of the team in EEP, they indicated that they felt like a stranger in the school team after their children have started to PSE. Therefore, families find the transition processes worrisome and state that they are not satisfied with the process. We discovered that in the process of transition from EEP to PSE, families are not informed, there is a limited number of PSE options available, children cannot adapt to the new educational environment and cannot benefit from the existing PSE.Keywords: early education program, early special education, children with hearing loss, transition
Procedia PDF Downloads 1439110 Dielectric Properties of Thalium Selenide Thin Films at Radio Wave Frequencies
Authors: Onur Potok, Deniz Deger, Kemal Ulutas, Sahin Yakut, Deniz Bozoglu
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Thalium Selenide (TlSe) is used for optoelectronic devices, pressure sensitive detectors, and gamma-ray detectors. The TlSe samples were grown as large single crystals using the Stockbarger-Bridgman method. The thin films, in the form of Al/TlSe/Al, were deposited on the microscope slide in different thicknesses (300-3000 Å) using thermal evaporation technique at 10-5 Torr. The dielectric properties of (TlSe) thin films, capacitance (C) and dielectric loss factor (tanδ), were measured in a frequency range of 10-105 Hz, and temperatures between 213K and 393K via Broadband Dielectric Spectroscopy analyzer. The dielectric constant (ε’) and the dielectric loss (ε’’) of the thin films were derived from measured parameters (C and tanδ). These results showed that the dielectric properties of TlSe thin films are frequency and temperature dependent. The capacitance and the dielectric constant decrease with increasing frequency and decreasing temperature. The dielectric loss of TlSe thin films decreases with increasing frequency, on the other hand, they increase with increasing temperature and increasing thicknesses. There is two relaxation region in the investigated frequency and temperature interval. These regions can be called as low and high-frequency dispersion regions. Low-frequency dispersion region can be attributed to the polarization of the main part of the chain structure of TlSe while high-frequency dispersion region can be attributed to the polarization of side parts of the structure.Keywords: thin films, thallium selenide, dielectric spectroscopy, binary compounds
Procedia PDF Downloads 1519109 Variable-Fidelity Surrogate Modelling with Kriging
Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans
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Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients
Procedia PDF Downloads 5569108 Measurement of CES Production Functions Considering Energy as an Input
Authors: Donglan Zha, Jiansong Si
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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.Keywords: bias of technical change, CES production function, elasticity of substitution, energy input
Procedia PDF Downloads 2789107 Analysis of Risk Factors Affecting the Motor Insurance Pricing with Generalized Linear Models
Authors: Puttharapong Sakulwaropas, Uraiwan Jaroengeratikun
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Casualty insurance business, the optimal premium pricing and adequate cost for an insurance company are important in risk management. Normally, the insurance pure premium can be determined by multiplying the claim frequency with the claim cost. The aim of this research was to study in the application of generalized linear models to select the risk factor for model of claim frequency and claim cost for estimating a pure premium. In this study, the data set was the claim of comprehensive motor insurance, which was provided by one of the insurance company in Thailand. The results of this study found that the risk factors significantly related to pure premium at the 0.05 level consisted of no claim bonus (NCB) and used of the car (Car code).Keywords: generalized linear models, risk factor, pure premium, regression model
Procedia PDF Downloads 4629106 Ontologies for Social Media Digital Evidence
Authors: Edlira Kalemi, Sule Yildirim-Yayilgan
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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.Keywords: criminal digital evidence, social media, ontologies, reasoning
Procedia PDF Downloads 3879105 Groundwater Pollution Models for Hebron/Palestine
Authors: Hassan Jebreen
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These models of a conservative pollutant in groundwater do not include representation of processes in soils and in the unsaturated zone, or biogeochemical processes in groundwater, These demonstration models can be used as the basis for more detailed simulations of the impacts of pollution sources at a local scale, but such studies should address processes related to specific pollutant species, and should consider local hydrogeology in more detail, particularly in relation to possible impacts on shallow systems which are likely to respond more quickly to changes in pollutant inputs. The results have demonstrated the interaction between groundwater flow fields and pollution sources in abstraction areas, and help to emphasise that wadi development is one of the key elements of water resources planning. The quality of groundwater in the Hebron area indicates a gradual increase in chloride and nitrate with time. Since the aquifers in Hebron districts are highly vulnerable due to their karstic nature, continued disposal of untreated domestic and industrial wastewater into the wadi will lead to unacceptably poor water quality in drinking water, which may ultimately require expensive treatment if significant health problems are to be avoided. Improvements are required in wastewater treatment at the municipal and domestic levels, the latter requiring increased public awareness of the issues, as well as improved understanding of the hydrogeological behaviour of the aquifers.Keywords: groundwater, models, pollutants, wadis, hebron
Procedia PDF Downloads 4389104 Modeling of Daily Global Solar Radiation Using Ann Techniques: A Case of Study
Authors: Said Benkaciali, Mourad Haddadi, Abdallah Khellaf, Kacem Gairaa, Mawloud Guermoui
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In this study, many experiments were carried out to assess the influence of the input parameters on the performance of multilayer perceptron which is one the configuration of the artificial neural networks. To estimate the daily global solar radiation on the horizontal surface, we have developed some models by using seven combinations of twelve meteorological and geographical input parameters collected from a radiometric station installed at Ghardaïa city (southern of Algeria). For selecting of best combination which provides a good accuracy, six statistical formulas (or statistical indicators) have been evaluated, such as the root mean square errors, mean absolute errors, correlation coefficient, and determination coefficient. We noted that multilayer perceptron techniques have the best performance, except when the sunshine duration parameter is not included in the input variables. The maximum of determination coefficient and correlation coefficient are equal to 98.20 and 99.11%. On the other hand, some empirical models were developed to compare their performances with those of multilayer perceptron neural networks. Results obtained show that the neural networks techniques give the best performance compared to the empirical models.Keywords: empirical models, multilayer perceptron neural network, solar radiation, statistical formulas
Procedia PDF Downloads 3449103 E-Consumers’ Attribute Non-Attendance Switching Behavior: Effect of Providing Information on Attributes
Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek
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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling
Procedia PDF Downloads 1389102 Modeling Water Resources Carrying Capacity, Optimizing Water Treatment, Smart Water Management, and Conceptualizing a Watershed Management Approach
Authors: Pius Babuna
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Sustainable water use is important for the existence of the human race. Water resources carrying capacity (WRCC) measures the sustainability of water use; however, the calculation and optimization of WRCC remain challenging. This study used a mathematical model (the Logistics Growth of Water Resources -LGWR) and a linear objective function to model water sustainability. We tested the validity of the models using data from Ghana. Total freshwater resources, water withdrawal, and population data were used in MATLAB. The results show that the WRCC remains sustainable until the year 2132 ±18, when half of the total annual water resources will be used. The optimized water treatment cost suggests that Ghana currently wastes GHȼ 1115.782± 50 cedis (~$182.21± 50) per water treatment plant per month or ~ 0.67 million gallons of water in an avoidable loss. Adopting an optimized water treatment scheme and a watershed management approach will help sustain the WRCC.Keywords: water resources carrying capacity, smart water management, optimization, sustainable water use, water withdrawal
Procedia PDF Downloads 859101 Mathematical Models for Drug Diffusion Through the Compartments of Blood and Tissue Medium
Authors: M. A. Khanday, Aasma Rafiq, Khalid Nazir
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This paper is an attempt to establish the mathematical models to understand the distribution of drug administration in the human body through oral and intravenous routes. Three models were formulated based on diffusion process using Fick’s principle and the law of mass action. The rate constants governing the law of mass action were used on the basis of the drug efficacy at different interfaces. The Laplace transform and eigenvalue methods were used to obtain the solution of the ordinary differential equations concerning the rate of change of concentration in different compartments viz. blood and tissue medium. The drug concentration in the different compartments has been computed using numerical parameters. The results illustrate the variation of drug concentration with respect to time using MATLAB software. It has been observed from the results that the drug concentration decreases in the first compartment and gradually increases in other subsequent compartments.Keywords: Laplace transform, diffusion, eigenvalue method, mathematical model
Procedia PDF Downloads 3329100 Off-Body Sub-GHz Wireless Channel Characterization for Dairy Cows in Barns
Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph
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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation
Procedia PDF Downloads 3179099 Deep Learning Approach for Chronic Kidney Disease Complications
Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia
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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis
Procedia PDF Downloads 1339098 Pressure Losses on Realistic Geometry of Tracheobronchial Tree
Authors: Michaela Chovancova, Jakub Elcner
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Real bronchial tree is very complicated piping system. Analysis of flow and pressure losses in this system is very difficult. Due to the complex geometry and the very small size in the lower generations is examination by CFD possible only in the central part of bronchial tree. For specify the pressure losses of lower generations is necessary to provide a mathematical equation. Determination of mathematical formulas for calculating the pressure losses in the real lungs is due to its complexity and diversity lengthy and inefficient process. For these calculations is necessary the lungs to slightly simplify (same cross-section over the length of individual generation) or use one of the models of lungs. The simplification could cause deviations from real values. The article compares the values of pressure losses obtained from CFD simulation of air flow in the central part of the real bronchial tree with the values calculated in a slightly simplified real lungs by using a mathematical relationship derived from the Bernoulli equation and continuity equation. Then, evaluate the desirability of using this formula to determine the pressure loss across the bronchial tree.Keywords: pressure gradient, airways resistance, real geometry of bronchial tree, breathing
Procedia PDF Downloads 319