Search results for: physiological data extraction

Authors: Namik Kemal Sonmez

Abstract:

Based passive remote sensing technologies have been widely used in many plant species. However, use of these techniques in orange trees is limited. In this study, the relationships between chlorophyll content (Chl) and calculated red edge (RE) and vegetation index values of the citrus leave at different growth stages were formed the basis for the analysis. Canopy reflectance by hand-held spectroradiometer and total Chl analysis at the lab were measured simultaneously, from the random samples taken from four different parts of an orange orchard. Plant materials consisted of four different age groups of 15, 20, 25, and 30 years old orange trees. Reflectance measurements were conducted between 450 and 900 nanometer (nm) wavelength at four different bands (3 visible bands and 1 near-infrared band) at the four basic physiological periods (flowering, fruit setting, fruit maturity, and dormancy) of orange trees. According to the statistical analysis conducted, there was a strong relationship between the chlorophyll content and calculated indexes (p ≤ 0.01; R²= 0.925 at red edge and R²= 0.986 at vegetation index) at the fruit setting stage of 20 years old trees. Again at this stage, fruit setting, total Chl content values among all orange trees were significantly correlated at the RE and VI with the R² values of 0.672 and 0.635 at the 0.001 level, respectively. This indicated that the relationships between Chl content and index values were very strong at this stage, in comparison to the other stages.

Keywords: spectroradiometer, citrus, chlorophyll, reflectance, index

Procedia PDF Downloads 368

Authors: Hamd Rezaeifar, Hamid Reza Sahriari

Abstract:

Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.

Keywords: accident, data mining, neural network, GIS

Procedia PDF Downloads 43

Authors: Buse A. Ataç, Doğan K. Cenan, Arda Çetinkaya, Naz D. Şahin, Köksal Sanlı, Zeynep Koç, Akın Kısa

Abstract:

With its spatial data reliability, interpretation and questioning capabilities, Geographical Information Systems make significant contributions to scientists, planners and practitioners. Geographic information systems have received great attention in today's digital world, growing rapidly, and increasing the efficiency of use. Access to and use of current and accurate geographical data, which are the most important components of the Geographical Information System, has become a necessity rather than a need for sustainable and economic development. This project aims to enable sharing of data collected by public institutions and organizations on a web-based platform. Within the scope of the project, INSPIRE (Infrastructure for Spatial Information in the European Community) data specifications are considered as a road-map. In this context, Turkey's National Geographic Information System (TUCBS) Integration Project supports sharing spatial data within 61 pilot public institutions as complied with defined national standards. In this paper, which is prepared by the project team members in the TUCBS Integration Project, the technical process with a detailed methodology is explained. In this context, the main technical processes of the Project consist of Geographic Data Analysis, Geographic Data Harmonization (Standardization), Web Service Creation (WMS, WFS) and Metadata Creation-Publication. In this paper, the integration process carried out to provide the data produced by 61 institutions to be shared from the National Geographic Data Portal (GEOPORTAL), have been trying to be conveyed with a detailed methodology.

Keywords: data specification, geoportal, GIS, INSPIRE, Turkish National Geographic Information System, TUCBS, Turkey's national geographic information system

Procedia PDF Downloads 137

Authors: Reut Lanyado, David Mendlovic

Abstract:

Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

Procedia PDF Downloads 121

Authors: Syed Umair Aziz, Muhammad Faheem, Sameer Hussain, Faraz Idris

Abstract:

Content centric network is the network based on the mechanism of sending and receiving the data based on the interest and data request to the specified node (which has cached data). In this network, the security is bind with the content not with the host hence making it host independent and secure. In this network security is applied by taking content’s MAC (message authentication code) and encrypting it with the public key of the receiver. On the receiver end, the message is first verified and after verification message is saved and decrypted using the receiver's private key.

Keywords: content centric network, client-server, host security threats, message authentication code, named data network, network caching, peer-to-peer

Procedia PDF Downloads 637

Authors: Jamal Al-Zain, O. El Hajjaji, T. El Bardouni

Abstract:

A (Th-U) O2 fuel pin benchmark made up of 25 w/o U and 75 w/o Th was used. In order to analyze the depletion and inventory of the fuel for the pressurized water reactor pin-cell model. The new version VIII.0 of the ENDF/B nuclear data library was used to create a data set in ACE format at various temperatures and process the data using the MAKXSF6.2 and NJOY2016 programs to process the data at the various temperatures in order to conduct this study and analyze cross-section data. The infinite multiplication factor, the concentrations and activities of the main fission products, the actinide radionuclides accumulated in the pin cell, and the total radioactivity were all estimated and compared in this study using the Monte Carlo N-Particle 6 (MCNP6.2) and DRAGON5 programs. Additionally, the behavior of the Pressurized Water Reactor (PWR) thorium pin cell that is dependent on burn-up (BU) was validated and compared with the reference data obtained using the Massachusetts Institute of Technology (MIT-MOCUP), Idaho National Engineering and Environmental Laboratory (INEEL-MOCUP), and CASMO-4 codes. The results of this study indicate that all of the codes examined have good agreements.

Keywords: PWR thorium pin cell, ENDF/B-VIII.0, MAKXSF6.2, NJOY2016, MCNP6.2, DRAGON5, fuel burn-up.

Procedia PDF Downloads 87

Authors: Bastian Haarmann, Likas Sikorski

Abstract:

In this paper, we introduce an NLG application for the automatic creation of ready-to-publish texts from big data. The fully automatic generated stories have a high resemblance to the style in which the human writer would draw up a news story. Topics may include soccer games, stock exchange market reports, weather forecasts and many more. The generation of the texts runs according to the human language production. Each generated text is unique. Ready-to-publish stories written by a computer application can help humans to quickly grasp the outcomes of big data analyses, save time-consuming pre-formulations for journalists and cater to rather small audiences by offering stories that would otherwise not exist.

Keywords: big data, natural language generation, publishing, robotic journalism

Procedia PDF Downloads 425

Authors: Aswathi Thrivikraman, S. Advaith

Abstract:

The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

Procedia PDF Downloads 145

Authors: Thaís T. Valério Caetano, João Máximo De Siqueira, Carlos Alexandre Carollo, Arthur Ladeira Macedo, Vanessa C. Stein

Abstract:

Nicotiana glauca, commonly known as wild tobacco or tobacco bush, belongs to the Solanaceae family. It is native to South America but has become naturalized in various regions, including Australia, California, Africa, and the Mediterranean. N. glauca is listed in the Global Invasive Species Database (GISD) and the Invasive Species Compendium (CABI). It is known for producing pyridine alkaloids, including anabasine, which is highly toxic. Anabasine is predominantly found in the leaves and can cause severe health issues such as neuromuscular blockade, respiratory arrest, and cardiovascular problems when ingested. Mistaken identity with edible plants like spinach has resulted in food poisoning cases in Israel and Brazil. Anabasine, a minor alkaloid constituent of tobacco, may contribute to tobacco addiction by mimicking or enhancing the effects of nicotine. Therefore, it is essential to investigate the production pattern of anabasine and its relationship to the developmental stages of the plant. This study aimed to establish the relationship between the phenological plant age, cultivation place, and the increase in anabasine concentration, which can lead to human intoxication cases. In this study, N. glauca plants were collected from three different rural areas in Brazil for a year to examine leaves at various stages of development. Samples were also obtained from cultivated plants in Marilândia, Minas Gerais, Brazil, as well as from Divinópolis, Minas Gerais, Brazil, and Arraial do Cabo, Rio de Janeiro, Brazil. In vitro cultivated plants on MS medium were included in the study. The collected leaves were dried, powdered, and stored. Alkaloid extraction was performed using a methanol and water mixture, followed by liquid-liquid extraction with chloroform. The anabasine content was determined using HPLC-DAD analysis with nicotine as a standard. The results indicated that anabasine production increases with the plant's development, peaking in adult leaves during the reproduction phase and declining afterward. In vitro, plants showed similar anabasine production to young leaves. The successful adaptation of N. glauca in new environments poses a global problem, and the correlation between anabasine production and the plant's developmental stages has been understudied. The presence of substances produced by the plant can pose a risk to other species, especially when mistaken for edible plants. The findings from this study shed light on the pattern of anabasine production and its association with plant development, contributing to a better understanding of the potential risks associated with N. glauca and the importance of accurate identification.

Keywords: nicotiana glauca graham, global invasive species database, alkaloids, toxic

Procedia PDF Downloads 78

Authors: M. Sari Yilmaz, N. Karamahmut Mermer

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Coal fly ash is formed as a solid waste product from the combustion of coal in coal fired power stations. Huge amounts of fly ash are produced globally every year and are predicted to increase. Nowadays, less than half of the fly ash is used as a raw material for cement manufacturing, construction and the rest of it is disposed as a waste causing yet another environmental concern. For this reason, the recycling of this kind of slurries into useful materials is quite important in terms of economical and environmental aspects. The purpose of this study is to evaluate the Orhaneli and Tuncbilek coal fly ashes for utilization in some industrial applications. Therefore the mineralogical and chemical compositions of these fly ashes were analyzed by X-ray fluorescence (XRF) spectroscopy and X-ray diffraction (XRD). The silicon (Si) and aluminum (Al) in the fly ashes were activated by alkali fusion technique with sodium hydroxide. The obtained extracts were analyzed for Si and Al content by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: extraction, fly ash, fusion, XRD

Procedia PDF Downloads 317

Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

Abstract:

With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

Procedia PDF Downloads 149

Authors: Ali. Marjani, M. Farsi, M. Rahimizadeh

Abstract:

Chickpea (Cicer arietinum L.) is one of the important grain legume crops in the world. However, drought stress is a serious threat to chickpea production, and development of drought-resistant varieties is a necessity. Field experiments were conducted to evaluate the response of 8 chickpea genotypes (MCC* 696, 537, 80, 283, 392, 361, 252, 397) and drought stress (S1: non-stress, S2: stress at vegetative growth stage, S3: stress at early bloom, S4: stress at early pod visible) at different growth stages. Experiment was arranged in split plot design with four replications. Difference among the drought stress time was found to be significant for investigated traits except biological yield. Differences were observed for genotypes in flowering time, pod information time, physiological maturation time and yield. Plant height reduced due to drought stress in vegetative growth stage. Stem dry weight reduced due to drought stress in pod visibly. Flowering time, maturation time, pod number, number of seed per plant and yield cause of drought stress in flowering was also reduced. The correlation between yield and number of seed per plant and biological yield was positive. The MCC283 and MCC696 were the high-tolerance genotypes. These results demonstrated that drought stress delayed phonological growth in chickpea and that flowering stage is sensitive.

Keywords: chickpea, drought stress, growth stage, tolerance

Procedia PDF Downloads 255

Authors: Ewa M. Laskowska, Jorn Vatn

Abstract:

Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

Procedia PDF Downloads 87

Authors: James Newman

Abstract:

Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

Procedia PDF Downloads 89

Authors: Thaís T. Valério Caetano, Lívia de Carvalho Ferreira, João Máximo De Siqueira, Carlos Alexandre Carollo, Arthur Ladeira Macedo, Vanessa C. Stein

Abstract:

Nicotiana glauca, commonly known as wild tobacco or tobacco bush, belongs to the Solanaceae family. It is native to South America but has become naturalized in various regions, including Australia, California, Africa, and the Mediterranean. N. glauca is listed in the Global Invasive Species Database (GISD) and the Invasive Species Compendium (CABI). It is known for producing pyridine alkaloids, including anabasine, which is highly toxic. Anabasine is predominantly found in the leaves and can cause severe health issues such as neuromuscular blockade, respiratory arrest, and cardiovascular problems when ingested. Mistaken identity with edible plants like spinach has resulted in food poisoning cases in Israel and Brazil. Anabasine, a minor alkaloid constituent of tobacco, may contribute to tobacco addiction by mimicking or enhancing the effects of nicotine. Therefore, it is essential to investigate the production pattern of anabasine and its relationship to the developmental stages of the plant. This study aimed to establish the relationship between the phenological plant age, cultivation place, and the increase in anabasine concentration, which can lead to human intoxication cases. In this study, N. glauca plants were collected from three different rural areas in Brazil during a year to examine leaves at various stages of development. Samples were also obtained from cultivated plants in Marilândia, Minas Gerais, Brazil, as well as from Divinópolis, Minas Gerais, Brazil, and Arraial do Cabo, Rio de Janeiro, Brazil. In vitro cultivated plants on MS medium were included in the study. The collected leaves were dried, powdered, and stored. Alkaloid extraction was performed using a methanol and water mixture, followed by liquid-liquid extraction with chloroform. The anabasine content was determined using HPLC-DAD analysis with nicotine as a standard. The results indicated that anabasine production increases with the plant's development, peaking in adult leaves during the reproduction phase and declining afterward. In vitro, plants showed similar anabasine production to young leaves. The successful adaptation of N. glauca in new environments poses a global problem, and the correlation between anabasine production and the plant's developmental stages has been understudied. The presence of substances produced by the plant can pose a risk to other species, especially when mistaken for edible plants. The findings from this study shed light on the pattern of anabasine production and its association with plant development, contributing to a better understanding of the potential risks associated with N. glauca and the importance of accurate identification.

Keywords: alkaloid production, invasive species, nicotiana glauca, plant phenology

Procedia PDF Downloads 73

Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

Abstract:

Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

Procedia PDF Downloads 202

Authors: Niharika Kaushal, Minni Singh

Abstract:

Fruit crops are widely cultivated throughout the World, with citrus being one of the most common. Mandarins, oranges, grapefruits, lemons, and limes are among the most frequently grown varieties. Citrus cultivars are industrially processed into juice, resulting in approx. 25-40% by wt. of biomass in the form of peels and seeds, generally considered as waste. In consequence, a significant amount of this nutraceutical-enriched biomass goes to waste, which, if utilized wisely, could revolutionize the functional food industry, as this biomass possesses a wide range of bioactive compounds, mainly within the class of polyphenols and terpenoids, making them an abundant source of functional bioactive. Mandarin is a potential source of bioflavonoids with putative antioxidative properties, and its potential application for developing value-added products is obvious. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was studied for its flavonoid profile. For this, dried and pulverized peels were subjected to green and sustainable extraction techniques, namely, supercritical fluid extraction carried out under conditions pressure: 330 bar, temperature: 40 ̊ C and co-solvent: 10% ethanol. The obtained extract was observed to contain 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the prevalence of polymethoxyflavones (PMFs), chiefly tangeretin and nobiletin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which was estimated to be at an IC₅₀ of 0.55μg/ml. The pre-systemic metabolism of flavonoids limits their functionality, as was observed in this study through in vitro gastrointestinal studies where nearly 50.0% of the flavonoids were degraded within 2 hours of gastric exposure. We proposed nanoencapsulation as a means to overcome this problem, and flavonoids-laden polylactic-co-glycolic acid (PLGA) nano encapsulates were bioengineered using solvent evaporation method, and these were furnished to a particle size between 200-250nm, which exhibited protection of flavonoids in the gastric environment, allowing only 20% to be released in 2h. A further step involved impregnating the nano encapsulates within alginate hydrogels which were fabricated by ionic cross-linking, which would act as delivery vehicles within the gastrointestinal (GI) tract. As a result, 100% protection was achieved from the pre-systemic release of bioflavonoids. These alginate hydrogels had key significant features, i.e., less porosity of nearly 20.0%, and Cryo-SEM (Cryo-scanning electron microscopy) images of the composite corroborate the packing ability of the alginate hydrogel. As a result of this work, it is concluded that the waste can be used to develop functional biomaterials while retaining the functionality of the bioactive itself.

Keywords: bioflavonoids, gastrointestinal, hydrogels, mandarins

Procedia PDF Downloads 74

Authors: Xianjia Meng, Chuanyong Qu

Abstract:

Compact bone produces fatigue damage under the inevitable physiological load. The accumulation of fatigue damage can change the bone’s micro-structure at different scales and cause the catastrophic failure eventually. However, most tests were limited to the macroscopic modulus of bone and there is a need to assess the microscopic modulus during fatigue progress. In this paper, nano-identation was used to investigate the bone specimen subjected to four point bending. The microscopic modulus of the same area were measured at different degrees of damage including fracture. So microscopic damage can be divided into three stages: first, the modulus decreased rapidly and then They fell slowly, before fracture the decline became fast again. After fracture, the average modulus decreased by 20%. The results of inner and outer planes explained the influence of compressive and tensile loads on modulus. Both the compressive and tensile moduli decreased with the accumulation of damage. They reached the minimum at ending and increased after fracture. The modulus evolution under different strains were revealed by the side. They all fell slowly and then fast with the accumulation of damage. The fractured results indicated that the elastic modulus decreased obviously at the high strain while decreased less at the low strain. During the fatigue progress, there was a significant difference in modulus at low degree of damage. However, the dispersed modulus tended to be similar at high degree of damage, but they became different again after the failure.

Keywords: fatigue damage, fracture, microscopic modulus, bone, nano-identation

Procedia PDF Downloads 155

Authors: Tonderai Muchenje, Xolani Mkhwanazi

Abstract:

Precision agriculture uses a number of technologies, devices, protocols, and computing paradigms to optimize agricultural processes. Big data, artificial intelligence, cloud computing, and edge computing are all used to handle the huge amounts of data generated by precision agriculture. However, precision agriculture is still emerging and has a low level of security features. Furthermore, future solutions will demand data availability and accuracy as key points to help farmers, and security is important to build robust and efficient systems. Since precision agriculture comprises a wide variety and quantity of resources, security addresses issues such as compatibility, constrained resources, and massive data. Moreover, conventional protection schemes used in the traditional internet may not be useful for agricultural systems, creating extra demands and opportunities. Therefore, this paper aims at reviewing state of the art of precision agriculture security, particularly in open field agriculture, discussing its architecture, describing security issues, and presenting the major challenges and future directions.

Keywords: precision agriculture, security, IoT, EIDE

Procedia PDF Downloads 84

Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

Abstract:

The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

Procedia PDF Downloads 73

Authors: Francisco Domingos Francisco

Abstract:

Tropical forests are key providers of many Ecosystem Services (ES), contributing to human wellbeing on a global and local scale. Communities around and within Moribane Forest Reserve (MFR), Manica Province - Mozambique, benefit from ES through the exploitation of non-wood and wood forest products. The objective was to assess the provisioning capacity of the MFR in woody forest products in species and profiles of interest to local communities in the main sources of extraction. Social data relating to the basic needs of local communities for these products were captured through an exploratory study before this one. From that study, it became known about the most collected wood species, the sources of collection, and their availability in the profiles of greatest interest to them. A field survey through 39 rectangular 50mx20m plots was conducted with 13 plots established in each of the three land-use types (LUT), namely Restricted Forest, Unrestricted Forest, and Disturbed areas. The results show that 89 species were identified, of which 28 (31.4%) are assumed to be the most used by the communities. The number of species of local interest does not vary across the LUT (p>0.05). The most used species (MUS) is distributed in 82% in Restricted Forest, 75% in Unrestricted, and also 75% in Disturbed. Most individuals of both general and MUS found in Unrestricted Forest, and Degraded areas have lower end profiles (5-7 cm), representing 0.77 and 0.26%, respectively. The profile of individuals of species of local interest varies by LUT (p<0.05), and their greatest proportion (0.51%) outside the lower end is found in Restricted Forest. There were no similarities between the LUT for the species in general (JCI <0.5) but between the MUS (JCI >0.5). Conclusion, the areas authorized for the exploitation of wood forest products in the MFR tend to reduce their ability to provide local communities with forest products in species and profiles of their interest. This reduction item is a serious threat to the biodiversity of the Restricted Forest. The study can help the academic community in future studies by replicating the methodology used for monitoring purposes or conducting studies in other similar areas, and the results may support decision-makers in designing better strategies for sustainability.

Keywords: ecosystem services, land-use types, local communities, species profile, wellbeing, wood forest product

Procedia PDF Downloads 127

Authors: Bounmediene Farida, Nouani Abdelouahab, Bellal Mouloud

Abstract:

The present study examined the influence of two production parameters namely genetic factor (race) and physiological factors (stage of lactation) on the composition of the traditional goat cheese made using the enzyme extract of caprine origin and commercial rennet. The results obtained show that the goat cheese of the Alpine race is richer in fat and protein than Saanen and Local breeds. Similar variations were observed depending on the stage of lactation for the third stage. Thus, analysis of the products obtained show that there is no difference in quality between the cheeses obtained with rennet and those obtained with goat coagulase. In addition, principal component analysis (PCA) made from individuals (races and stages of lactation) and variables (physicochemical parameters goat cheese) divides people into two groups: The first group includes cheeses races Alpine, Saanen and local third stages of lactation. This group corresponds to samples of the richest cheese in a useful matter. The second group includes cheeses from the three races in the second stage of lactation. This group corresponds to cheeses that have low contents in a useful matter.

Keywords: goat cheese, goat coagulase, rennet, coagulation

Procedia PDF Downloads 315

Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

Abstract:

The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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Authors: Ching-Ju Hsiao, Mao-Chen Huang, Pei-Fan Chen, Ruo-Yun Chung, Jiun-Hua Chou, Chih-Hui Yang, Keng-Shiang Huang, Jei-Fu Shaw

Abstract:

Chlorophyll has many benefits for human body. It is known to improve the health of the circulatory, digestive, immune and detoxification systems of the body. However, Chl can’t be preserved at the environment of high temperature and light exposure for a long time due to it is chemical structure is easily degradable. This characteristic causes that human body is difficult to absorb Chl effective components. In order to solve this problem, we utilize polycaprolactone (PCL) polymer encapsulation technology to increase the stability of Chl. In particular, we also established a microfluidic platform provide the control of composite beads diameter. The new composite beads is potential to be a health food. Result show that Chl effective components via the microfludic platform can be encapsulated effectively and still preserve its effective components.

Keywords: chlorophyll, PCL, PVA, microfluidic

Procedia PDF Downloads 543

Authors: Manh-Dung Ho, Van-Giap Pham, Van-Doanh Ho, Quang-Thien Tran, Tuan-Anh Tran

Abstract:

The k0-factors and related nuclear data, i.e. the Q0-factors and effective resonance energies (Ēr) of the selected radionuclides which are used in the k0-based neutron activation analysis (k0-NAA), were critically reviewed to be integrated in the “k0-DALAT” software. The k0- and Q0-factors of some short-lived radionuclides: 46mSc, 110Ag, 116m2In, 165mDy, and 183mW, were experimentally determined at the Dalat research reactor. The other radionuclides selected are: 20F, 36S, 49Ca, 60mCo, 60Co, 75Se, 77mSe, 86mRb, 115Cd, 115mIn, 131Ba, 134mCs, 134Cs, 153Gd, 153Sm, 159Gd, 170Tm, 177mYb, 192Ir, 197mHg, 239U and 239Np. The reviewed data as compared with the literature data were biased within 5.6-7.3% in which the experimental re-determined factors were within 6.1 and 7.3%. The NIST standard reference materials: Oyster Tissue (1566b), Montana II Soil (2711a) and Coal Fly Ash (1633b) were used to validate the new reviewed data showing that the new data gave an improved k0-NAA using the “k0-DALAT” software with a factor of 4.5-6.8% for the investigated radionuclides.

Keywords: neutron activation analysis, k0-based method, k0 factor, Q0 factor, effective resonance energy

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Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

Abstract:

Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

Procedia PDF Downloads 183

Authors: R. Shamsi, F. Sharifi

Abstract:

In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

Procedia PDF Downloads 101

Authors: Ali M. Mutlag, Yang Zhiqiang, Meng Jiaren, Zhang Jingyan, Li Jianxi

Abstract:

The object of this study was to investigate several hormones correlated to the reproduction and Inhibin A, Inhibin B and NO levels in the infertile dairy cows as attempt to illustrate the physiological causes of dairy cows infertility. 40 Holstein cows (21 infertile and 19 fertile) were used at estrous phase of the cycle, Hormones FSH, LH, E2, Testosterone, Were measured using ELISA method. Inhibin A and B also estimated by ELISA method, Nitric oxide was measured by Greiss reagent method. The results showed different concentrations of the hormone in which FSH illustrated significantly higher concentration in the infertile cows than fertile cows (P<0.05). LH and E2 showed significant decrease in the infertile cows than the fertile cows (P<0.05), No significant difference appeared in testosterone concentrations in the fertile cows and infertile cows (P>0.05). The both inhibins A and B showed significant P<0.05 decrease concentrations in the infertile cows also NO showed clearly significant decrease P<0.05 in the infertile cows. In conclusion, The present study approved the poorly ovarian activities and reproduction disturbance of infertile cows in spite of trigger estrous signs, The study confirmed a positive correlation between inhibins and NO to regulate the ovarian physiology. These inhibins represent effective markers of dairy cows infertility.

Keywords: cows, inhibins A and B, infertility, nitric oxide (NO)

Procedia PDF Downloads 280

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 351

Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

Abstract:

In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

Procedia PDF Downloads 463