Search results for: plant data

Authors: Aswini M. S.

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Tomato (Solanum lycopersicum L.) is one of the most significant vegetable crops in terms of its economic benefits. Both fresh and processed tomatoes are consumed. Tomatoes have a limited genetic base, which makes breeding extremely challenging. Plant breeding has become much simpler and more effective with genome editing tools of CRISPR and CRISPR-associated 9 protein (CRISPR/Cas9), which address the problems with traditional breeding, chemical/physical mutagenesis, and transgenics. With the use of CRISPR/Cas9, a number of tomato traits have been functionally distinguished and edited. These traits include plant architecture as well as flower characters (leaf, flower, male sterility, and parthenocarpy), fruit ripening, quality and nutrition (lycopene, carotenoid, GABA, TSS, and shelf-life), disease resistance (late blight, TYLCV, and powdery mildew), tolerance to abiotic stress (heat, drought, and salinity) and resistance to herbicides. This study explores the potential of CRISPR/Cas9 genome editing for enhancing yield in tomato plants. The study utilized the CRISPR/Cas9 genome editing technology to functionally edit various traits in tomatoes. The de novo domestication of elite features from wild cousins to cultivated tomatoes and vice versa has been demonstrated by the introgression of CRISPR/Cas9. The CycB (Lycopene beta someri) gene-mediated Cas9 editing increased the lycopene content in tomato. Also, Cas9-mediated editing of the AGL6 (Agamous-like 6) gene resulted in parthenocarpic fruit development under heat-stress conditions. The advent of CRISPR/Cas has rendered it possible to use digital resources for single guide RNA design and multiplexing, cloning (such as Golden Gate cloning, GoldenBraid, etc.), creating robust CRISPR/Cas constructs, and implementing effective transformation protocols like the Agrobacterium and DNA free protoplast method for Cas9-gRNAs ribonucleoproteins (RNPs) complex. Additionally, homologous recombination (HR)-based gene knock-in (HKI) via geminivirus replicon and base/prime editing (Target-AID technology) remains possible. Hence, CRISPR/Cas facilitates fast and efficient breeding in the improvement of tomatoes.

Keywords: CRISPR-Cas, biotic and abiotic stress, flower and fruit traits, genome editing, polygenic trait, tomato and trait introgression

Procedia PDF Downloads 63

Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

Procedia PDF Downloads 160

Authors: Valentin P. Velikov

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Automatic program generation saves time, human resources, and allows receiving syntactically clear and logically correct modules. The 4-th generation programming languages are related to drawing the data and the processes of the subject area, as well as, to obtain a frame of the respective information system. The application can be separated in interface and business logic. That means, for an interactive generation of the needed system to be used an already existing toolkit or to be created a new one.

Keywords: computer science, graphical user interface, user dialog interface, dialog frames, data modeling, subject area modeling

Procedia PDF Downloads 298

Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

Procedia PDF Downloads 279

Authors: Marwa Abida, Florian Gehring, Jamel Mars, Alexandre Vivet, Fakhreddine Dammak, Mohamed Haddar

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The demand for bio-based materials in semi-structural and structural applications is constantly growing to conform to new environmental policies. Among them, Plant Fiber Reinforced Composites (PFRC) are attractive for the scientific community as well as the industrial world. Due to their relatively low densities and low environmental impact, vegetal fibers appear to be suitable as reinforcing materials for polymers. However, the major issue of plant fibers and PFRC in general is their hydrophilic behavior (high affinity to water molecules). Indeed, when absorbed, water causes fiber swelling and a loss of mechanical properties. Thus, the environmental loadings (moisture, temperature, UV) can strongly affect their mechanical properties and therefore play a critical role in the service life of PFRC. In order to analyze the influence of conditioning at relative humidity on the behavior of flax fiber reinforced composites, a preliminary study on flax fabrics has been conducted. The conditioning of the fabrics in different humid atmospheres made it possible to study the influence of the water content on the hygro-mechanical behavior of flax reinforcement through mechanical tensile tests. This work shows that increasing the relative humidity of the atmosphere induces an increase of the water content in the samples. It also brings up the significant influence of water content on the stiffness and elongation at break of the fabric, while no significant change of the breaking load is detected. Non-linear decrease of flax fabric rigidity and increase of its elongation at maximal force with the increase of water content are observed. It is concluded that water molecules act as a softening agent on flax fabrics. Two kinds of typical tensile curves are identified. Most of the tensile curves of samples show one unique linear region where the behavior appears to be linear prior to the first yarn failure. For some samples in which water content is between 2.7 % and 3.7 % (regardless the conditioning atmosphere), the emergence of a two-linear region behavior is pointed out. This phenomenon could be explained by local heterogeneities of water content which could induce premature local plasticity in some regions of the flax fabric sample behavior.

Keywords: hygro-mechanical behavior, hygroscopy, flax fabric, relative humidity, mechanical properties

Procedia PDF Downloads 183

Authors: Teo Hao Jing, Shane Ho Ken Wae, Lee Jin Yu, Burra Venkata Durga Kumar

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Current distributed healthcare systems face the challenge of interoperability of health data. Storing electronic health records (EHR) in local databases causes them to be fragmented. This problem is aggravated as patients visit multiple healthcare providers in their lifetime. Existing solutions are unable to solve this issue and have caused burdens to healthcare specialists and patients alike. Blockchain technology was found to be able to increase the interoperability of health data by implementing digital access rules, enabling uniformed patient identity, and providing data aggregation. Consortium blockchain was found to have high read throughputs, is more trustworthy, more secure against external disruptions and accommodates transactions without fees. Therefore, this paper proposes a blockchain-based model for data management applications. In this model, a consortium blockchain is implemented by using a delegated proof of stake (DPoS) as its consensus mechanism. This blockchain allows collaboration between users from different organizations such as hospitals and medical bureaus. Patients serve as the owner of their information, where users from other parties require authorization from the patient to view their information. Hospitals upload the hash value of patients’ generated data to the blockchain, whereas the encrypted information is stored in a distributed cloud storage.

Keywords: blockchain technology, data management applications, healthcare, interoperability, delegated proof of stake

Procedia PDF Downloads 131

Authors: P. Javid, A. Aeenmehr, J. Taghavifar

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In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.

Keywords: air conditioning system, GPC, dead time, air supply control

Procedia PDF Downloads 523

Authors: Saeed Hosseini, Ali Reza Tahavvor

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Sound processing is one the subjects that newly attracts a lot of researchers. It is efficient and usually less expensive than other methods. In this paper the flow generated sound is used to estimate the flow speed of free flows. Many sound samples are gathered. After analyzing the data, a parameter named wave power is chosen. For all samples, the wave power is calculated and averaged for each flow speed. A curve is fitted to the averaged data and a correlation between the wave power and flow speed is founded. Test data are used to validate the method and errors for all test data were under 10 percent. The speed of the flow can be estimated by calculating the wave power of the flow generated sound and using the proposed correlation.

Keywords: the flow generated sound, free stream, sound processing, speed, wave power

Procedia PDF Downloads 407

Authors: Shengnan Chen, Shuhua Wang

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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

Procedia PDF Downloads 280

Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

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Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

Procedia PDF Downloads 442

Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 123

Authors: S. Cichosz, A. Masek

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A new cellulose hybrid modification approach, which is undoubtedly a scientific novelty, is introduced. The study reports the properties of cellulose (Arbocel UFC100 – Ultra Fine Cellulose) and characterizes cellulose filled polymer composites based on an ethylene-norbornene copolymer (TOPAS Elastomer E-140). Moreover, the approach of physicochemical two-stage cellulose treatment is introduced: solvent exchange (to ethanol or hexane) and further chemical modification with maleic anhydride (MA). Furthermore, the impact of the drying process on cellulose properties was investigated. Suitable measurements were carried out to characterize cellulose fibers: spectroscopic investigation (Fourier Transform Infrared Spektrofotometer-FTIR, Near InfraRed spectroscopy-NIR), thermal analysis (Differential scanning calorimetry, Thermal gravimetric analysis ) and Karl Fischer titration. It should be emphasized that for all UFC100 treatments carried out, a decrease in moisture content was evidenced. FT-IR reveals a drop in absorption band intensity at 3334 cm-1, the peak is associated with both –OH moieties and water. Similar results were obtained with Karl Fischer titration. Based on the results obtained, it may be claimed that the employment of ethanol contributes greatly to the lowering of cellulose water absorption ability (decrease of moisture content to approximately 1.65%). Additionally, regarding polymer composite properties, crucial data has been obtained from the mechanical and thermal analysis. The highest material performance was noted in the case of the composite sample that contained cellulose modified with MA after a solvent exchange with ethanol. This specimen exhibited sufficient tensile strength, which is almost the same as that of the neat polymer matrix – in the region of 40 MPa. Moreover, both the Payne effect and filler efficiency factor, calculated based on dynamic mechanical analysis (DMA), reveal the possibility of the filler having a reinforcing nature. What is also interesting is that, according to the Payne effect results, fibers dried before the further chemical modification are assumed to allow more regular filler structure development in the polymer matrix (Payne effect maximum at 1.60 MPa), compared with those not dried (Payne effect in the range 0.84-1.26 MPa). Furthermore, taking into consideration the data gathered from DSC and TGA, higher thermal stability is obtained in case of the materials filled with fibers that were dried before the carried out treatments (degradation activation energy in the region of 195 kJ/mol) in comparison with the polymer composite samples filled with unmodified cellulose (degradation activation energy of approximately 180 kJ/mol). To author’s best knowledge this work results in the introduction of a novel, new filler hybrid treatment approach. Moreover, valuable data regarding the properties of composites filled with cellulose fibers of various moisture contents have been provided. It should be emphasized that plant fiber-based polymer bio-materials described in this research might contribute significantly to polymer waste minimization because they are more readily degraded.

Keywords: cellulose fibers, solvent exchange, moisture content, ethylene-norbornene copolymer

Procedia PDF Downloads 109

Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method Web-App auto-generated twin data structure replication. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi" has been developed. A special login form has been developed with a special instance of data validation; this verification process secures the web application from its early stages. The system has been tested and validated, up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database

Procedia PDF Downloads 144

Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in diverse domains has created an urgent need for effective utilization of mathematical and statistical sciences in data analytics. This abstract explores the journey from theory to practice, emphasizing the importance of harnessing mathematical and statistical innovations to unlock the full potential of data analytics. Drawing on a comprehensive review of existing literature and research, this study investigates the fundamental theories and principles underpinning mathematical and statistical sciences in the context of data analytics. It delves into key mathematical concepts such as optimization, probability theory, statistical modeling, and machine learning algorithms, highlighting their significance in analyzing and extracting insights from complex datasets. Moreover, this abstract sheds light on the practical applications of mathematical and statistical sciences in real-world data analytics scenarios. Through case studies and examples, it showcases how mathematical and statistical innovations are being applied to tackle challenges in various fields such as finance, healthcare, marketing, and social sciences. These applications demonstrate the transformative power of mathematical and statistical sciences in data-driven decision-making. The abstract also emphasizes the importance of interdisciplinary collaboration, as it recognizes the synergy between mathematical and statistical sciences and other domains such as computer science, information technology, and domain-specific knowledge. Collaborative efforts enable the development of innovative methodologies and tools that bridge the gap between theory and practice, ultimately enhancing the effectiveness of data analytics. Furthermore, ethical considerations surrounding data analytics, including privacy, bias, and fairness, are addressed within the abstract. It underscores the need for responsible and transparent practices in data analytics, and highlights the role of mathematical and statistical sciences in ensuring ethical data handling and analysis. In conclusion, this abstract highlights the journey from theory to practice in harnessing mathematical and statistical sciences in data analytics. It showcases the practical applications of these sciences, the importance of interdisciplinary collaboration, and the need for ethical considerations. By bridging the gap between theory and practice, mathematical and statistical sciences contribute to unlocking the full potential of data analytics, empowering organizations and decision-makers with valuable insights for informed decision-making.

Keywords: data analytics, mathematical sciences, optimization, machine learning, interdisciplinary collaboration, practical applications

Procedia PDF Downloads 87

Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

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Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

Procedia PDF Downloads 153

Authors: Lu Zhao, Yanrong Kang, Lili Guo, Yuan Long, Guidong Xing

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Smart watches, as a handy device with rich functionality, has become one of the most popular wearable devices all over the world. Among the various function, the most basic is health monitoring. The monitoring data can be provided as an effective evidence or a clue for the detection of crime cases. For instance, the step counting data can help to determine whether the watch wearer was quiet or moving during the given time period. There is, however, still quite few research on the analysis of human character based on these data. The purpose of this research is to analyze the health monitoring data to distinguish the drinking state from normal state. The analysis result may play a role in cases involving drinking, such as drunk driving. The experiment mainly focused on finding the figures of smart watch health monitoring data that change with drinking and figuring up the change scope. The chosen subjects are mostly in their 20s, each of whom had been wearing the same smart watch for a week. Each subject drank for several times during the week, and noted down the begin and end time point of the drinking. The researcher, then, extracted and analyzed the health monitoring data from the watch. According to the descriptive statistics analysis, it can be found that the heart rate change when drinking. The average heart rate is about 10% higher than normal, the coefficient of variation is less than about 30% of the normal state. Though more research is needed to be carried out, this experiment and analysis provide a thought of the application of the data from smart watches.

Keywords: character analysis, descriptive statistics analysis, drink state, heart rate, smart watch

Procedia PDF Downloads 162

Authors: Sabin Aslam, Sultan Habibullah Khan, James G. Thomson, Abhaya M. Dandekar

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Losses due to viral diseases are posing a serious threat to crop production. A quick breakdown of resistance to viruses like Cotton Leaf Curl Virus (CLCuV) demands the application of a proficient technology to engineer durable resistance. Gene stacking has recently emerged as a potential approach for integrating multiple genes in crop plants. In the present study, recombinase technology has been used for site-specific gene stacking. A target vector (pG-Rec) was designed for engineering a predetermined specific site in the plant genome whereby genes can be stacked repeatedly. Using Agrobacterium-mediated transformation, the pG-Rec was transformed into Coker-312 along with Nicotiana tabacum L. cv. Xanthi and Nicotiana benthamiana. The transgene analysis of target lines was conducted through junction PCR. The transgene positive target lines were used for further transformations to site-specifically stack two genes of interest using Bxb1 and PhiC31 recombinases. In the first instance, Cas9 driven by multiplex gRNAs (for Rep gene of CLCuV) was site-specifically integrated into the target lines and determined by the junction PCR and real-time PCR. The resulting plants were subsequently used to stack the second gene of interest (AVP3 gene from Arabidopsis for enhancing cotton plant growth). The addition of the genes is simultaneously achieved with the removal of marker genes for recycling with the next round of gene stacking. Consequently, transgenic marker-free plants were produced with two genes stacked at the specific site. These transgenic plants can be potential germplasm to introduce resistance against various strains of cotton leaf curl virus (CLCuV) and abiotic stresses. The results of the research demonstrate gene stacking in crop plants, a technology that can be used to introduce multiple genes sequentially at predefined genomic sites. The current climate change scenario highlights the use of such technologies so that gigantic environmental issues can be tackled by several traits in a single step. After evaluating virus resistance in the resulting plants, the lines can be a primer to initiate stacking of further genes in Cotton for other traits as well as molecular breeding with elite cotton lines.

Keywords: cotton, CRISPR/Cas9, gene stacking, genome editing, recombinases

Procedia PDF Downloads 147

Authors: Sara Sallam, Mohamed Taqi, Naoual Belouaggadia

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Solar thermal power plants using parabolic trough collectors (PTC) are currently a powerful technology for generating electricity. Most of these solar power plants use thermal oils as heat transfer fluid. The latter is heated in the solar field and transfers the heat absorbed in an oil-water heat exchanger for the production of steam driving the turbines of the power plant. Currently, we are seeking to develop PTCs with direct steam generation (DSG). This process consists of circulating water under pressure in the receiver tube to generate steam directly into the solar loop. This makes it possible to reduce the investment and maintenance costs of the PTCs (the oil-water exchangers are removed) and to avoid the environmental risks associated with the use of thermal oils. The pressure drops in these systems are an important parameter to ensure their proper operation. The determination of these losses is complex because of the presence of the two phases, and most often we limit ourselves to describing them by models using empirical correlations. A comparison of these models with experimental data was performed. Our calculations focused on the evolution of the pressure of the liquid-vapor mixture along the receiver tube of a PTC-DSG for pressure values and inlet flow rates ranging respectively from 3 to 10 MPa, and from 0.4 to 0.6 kg/s. The comparison of the numerical results with experience allows us to demonstrate the validity of some models according to the pressures and the flow rates of entry in the PTC-DSG receiver tube. The analysis of these two parameters’ effects on the evolution of the pressure along the receiving tub, shows that the increase of the inlet pressure and the decrease of the flow rate lead to minimal pressure losses.

Keywords: direct steam generation, parabolic trough collectors, Ppressure drop, empirical models

Procedia PDF Downloads 134

Authors: Jun Byung Joon, Seo Seok Hyun, Lee Seo Young

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As carbon dioxide emissions increase due to rapid industrialization and reckless development, abnormal climates such as floods and droughts are occurring. In order to respond to such climate change, the use of existing fossil fuels is reduced, and the proportion of eco-friendly renewable energy is gradually increasing. Korea is an energy resource-poor country that depends on imports for 93% of its total energy. As the global energy supply chain instability experienced due to the Russia-Ukraine crisis increases, countries around the world are resetting energy policies to minimize energy dependence and strengthen security. Seawater thermal energy is a renewable energy that replaces the existing air heat energy. It uses the characteristic of having a higher specific heat than air to cool and heat main spaces of buildings to increase heat transfer efficiency and minimize power consumption to generate electricity using fossil fuels, and Carbon dioxide emissions can be minimized. In addition, the effect on the marine environment is very small by using only the temperature characteristics of seawater in a limited way. K-water carried out a demonstration project of supplying cooling and heating energy to spaces such as the central control room and presentation room in the management building by acquiring the heat source of seawater circulated through the power plant's waterway by using the characteristics of the tidal power plant. Compared to the East Sea and the South Sea, the main system was designed in consideration of the large tidal difference, small temperature difference, and low-temperature characteristics, and its performance was verified through operation during the demonstration period. In addition, facility improvements were made for major deficiencies to strengthen monitoring functions, provide user convenience, and improve facility soundness. To spread these achievements, the basic concept was to expand the seawater heating and cooling system with a scale of 200 USRT at the Tidal Culture Center. With the operational experience of the demonstration system, it will be possible to establish an optimal seawater heat cooling and heating system suitable for the characteristics of the west coast ocean. Through this, it is possible to reduce operating costs by KRW 33,31 million per year compared to air heat, and through industry-university-research joint research, it is possible to localize major equipment and materials and develop key element technologies to revitalize the seawater heat business and to advance into overseas markets. The government's efforts are needed to expand the seawater heating and cooling system. Seawater thermal energy utilizes only the thermal energy of infinite seawater. Seawater thermal energy has less impact on the environment than river water thermal energy, except for environmental pollution factors such as bottom dredging, excavation, and sand or stone extraction. Therefore, it is necessary to increase the sense of speed in project promotion by innovatively simplifying unnecessary licensing/permission procedures. In addition, support should be provided to secure business feasibility by dramatically exempting the usage fee of public waters to actively encourage development in the private sector.

Keywords: seawater thermal energy, marine energy, tidal power plant, energy consumption

Procedia PDF Downloads 97

Authors: Boris Nemzer, Tania Reyes-Izquierdo, Zbigniew Pietrzkowski

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Glucosinolate is a family of glucosides that can be found in a family of brassica vegetables. Upon the damage of the plant, glucosinolate breakdown by an internal enzyme myrosinase (thioglucosidase; EC 3.2.3.1) into isothiocyanates, such as sulforaphane. Sulforaphane is formed by glucoraphanin cleaving the sugar off by myrosinase and rearranged. Sulforaphane nitrile is formed in the same reaction as sulforaphane with the active of epithiospecifier protein (ESP). Most common food processing procedure would break the plant and mix the glucoraphanin and myrosinase together, and the formed sulforaphane would be further degraded. The purpose of this study is to understand the glucoraphanin/sulforaphane and the myrosinase activity of broccoli seeds germinated at a different time and technological processing conditions that keep the activity of the enzyme to form sulforaphane. Broccoli seeds were germinated in the house. Myrosinase activities were tested as the glucose content using glucose assay kit and measured UV-Vis spectrophotometer. Glucosinolates were measured by HPLC/DAD. Sulforaphane was measured using HPLC-DAD and GC/MS. The 6 hr germinated sprouts have a myrosinase activity 32.2 mg glucose/g, which is comparable with 12 and 24 hour germinated seeds and higher than dry seeds. The glucoraphanin content in 6 hour germinated sprouts is 13935 µg/g which is comparable to 24 hour germinated seeds and lower than the dry seeds. GC/MS results show that the amount of sulforaphane is higher than the amount of sulforaphane nitrile in seeds, 6 hour and 24 hour germinated seeds. The ratio of sulforaphane and sulforaphane nitrile is high in 6 hour germinated seeds, which indicates the inactivated ESP in the reaction. After evaluating the results, the short time germinated seeds can be used as the source of glucoraphanin and myrosinase supply to form potential higher sulforaphane content. Broccoli contains glucosinolates, glucoraphanin (4-methylsulfinylbutyl glucosinolate), which is an important metabolite with health-promoting effects. In the pilot clinical study, we observed the effects of a glucosinolates/glucoraphanin-rich extract from short time germinated broccoli seeds on blood adenosine triphosphate (ATP), reactive oxygen species (ROS) and lactate levels. A single dose of 50 mg of broccoli sprouts extract increased blood levels of ATP up to 61% (p=0.0092) during the first 2 hours after the ingestion. Interestingly, this effect was not associated with an increase in blood ROS or lactate. When compared to the placebo group, levels of lactate were reduced by 10% (p=0.006). These results indicate that broccoli germinated seed extract may positively affect the generation of ATP in humans. Due to the preliminary nature of this work and promising results, larger clinical trials are justified.

Keywords: broccoli glucosinolates, glucoraphanin, germinated seeds, myrosinase, adenosine triphosphate

Procedia PDF Downloads 287

Authors: Necati Içer

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Crop-hail insurance plays a vital role in managing risks and reducing the financial consequences of hail damage on crop production. Predicting insurance premium rates with short-term data is a major difficulty in numerous nations because of the unique characteristics of hailstorms. This study aims to suggest a feasible approach for establishing equitable premium rates in crop-hail insurance for nations with short-term insurance data. The primary goal of the rate-making process is to determine premium rates for high and zero loss costs of villages and enhance their credibility. To do this, a technique was created using the author's practical knowledge of crop-hail insurance. With this approach, the rate-making method was developed using a range of temporal and spatial factor combinations with both hypothetical and real data, including extreme cases. This article aims to show how to incorporate the temporal and spatial elements into determining fair premium rates using short-term insurance data. The article ends with a suggestion on the ultimate premium rates for insurance contracts.

Keywords: crop-hail insurance, premium rate, short-term insurance data, spatial and temporal parameters

Procedia PDF Downloads 42

Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

Procedia PDF Downloads 93

Authors: Doron Markel

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Water availability in most of the Middle East (especially in Jordan) is among the lowest in the world and has been even further exacerbated by the regional climatic change and the reduced rainfall. The Araba Valley in Israel is disconnected from the national water system. On the other hand, the Araba Valley, both in Israel and Jordan, is an excellent area for solar energy gaining. The Dead Sea (Israel and Jordan) is a hypersaline lake which its level declines at a rate of more than 1 m/y. The decline stems from the increasing use of all available freshwater resources that discharge into the Dead Sea and decreasing natural precipitation due to climate change in the Middle East. As an adaptation tool for this humanmade and Climate Change results, a comprehensive water-energy and environmental project were suggested: The Red Sea-Dead Sea Conveyance. It is planned to desalinate the Red Sea water, supply the desalinated water to both Israel and Jordan, and convey the desalination brine to the Dead Sea to stabilize its water level. Therefore, the World Bank had led a multi-discipline feasibility study between 2008 and 2013, that had mainly dealt with the mixing of seawater and Dead Sea Water. The possible consequences of such mixing were precipitation and possible suspension of secondary Gypsum, as well as blooming of Dunaliella red algae. Using a comprehensive hydrodynamic-geochemical model for the Dead Sea, it was predicted that while conveying up to 400 Million Cubic Meters per year of seawater or desalination brine to the Dead Sea, the latter would not be stratified as it was until 1979; hence Gypsum precipitation and algal blooms would be neglecting. Using another hydrodynamic-biological model for the Red Sea, it was predicted the Seawater pump from the Gulf of Eilat would not harm the ecological system of the gulf (including the sensitive coral reef), giving a pump depth of 120-160 m. Based on these studies, a pipeline conveyance was recommended to convey desalination brine to the Dead Sea with the use of a hydropower plant, utilizing the elevation difference of 400 m between the Red Sea and the Dead Sea. The complementary energy would come from solar panels coupled with innovative storage technology, needed to produce a continuous energy production for an appropriate function of the desalination plant. The paper will describe the proposed project as well as the feasibility study results. The possibility to utilize this water-energy-environmental project as a climate change adaptation strategy for both Israel and Jordan will also be discussed.

Keywords: Red Sea, Dead Sea, water supply, hydro-power, Gypsum, algae

Procedia PDF Downloads 108

Authors: Eric Spruth, Lindsey Herbert, Danielle DiCristofano, Isis Violet Spruth, Drake Von Spruth

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Turning dreams into reality, the lifelong passion of Mr. Spruth and the company is to transform garbage-filled courtyards into flourishing flower and vegetable gardens, bringing light, hope, and wellness to not just the space but to the populations served within these public and private spaces. As an Expressive Art Therapist at Cook County Jail, Eric Spruth has implemented gardening projects, mobile radish carts, plant fostering systems, and large-scale murals. Lindsey Herbert, the Manager of Operations and Events at the International Museum of Surgical Science, supports gardening projects with Mr. Spruth along the front lawn of the museum, which will eventually accumulate into a community wellness garden. Mr. Spruth and Ms. Herbert both have dedicated efforts towards fostering awareness of hope and help and accountability for physical and mental wellbeing. Medicinal plants can rightfully be called one of nature’s wonderful healing tools with therapeutic powers. They can inhibit and kill bacteria, lower blood pressure, blood cholesterol, and blood sugar, prevent blood clotting, boost the immune system, and serve as a digestive aid. Some plants have the ability to stimulate the lymphatic system, which expedites the removal of waste products from the body to fight off evil toxins. Many plants are considered effective antioxidants to protect cells against free radical damage, serving to prevent some forms of cancer, heart disease, strokes, and viral infections. Garlic alone can provide us with over two hundred unusual chemicals that have the capability of protecting the human body from a wide variety of diseases. Besides the medicinal qualities of plants, plant and vegetable gardens also have an echoing effect on non-participants to look at something beautiful rather than a concrete courtyard or an unkempt lawn in front of a beautiful building. Plants also purify spaces and affect mood with color therapy. Collective gardening can foster a sense of community and purpose. Additionally, by recognizing the ever-evolving planet with global warming, horticulture therapy teaches important lessons in responsibility, accountability, and sustainability. Growing local food provides an opportunity to be involved in your own mental and physical health and gives you a chance for your own self-resilience, combating depression and a lack of nutrition. In adolescents, the process of watering and caring for plants can teach important life lessons that transcend beyond the garden by providing knowledge on how to care for yourself and how to be an active member of society. It also gives a sense of purpose and pride in transforming a small seed into a plant that can be consumed or enjoyed by others. Mr. Spruth and Ms. Herbert recognize the importance of bringing more green spaces to urban areas, both to serve a nutritional benefit and provide a beautiful transformation to underutilized areas. Gardens can bring beauty, wellness, and hope to dark spaces and provide immeasurable benefits for all.

Keywords: growth, hope, mental health, sustainability, transformation, wellness

Procedia PDF Downloads 87

Authors: Ali Hosseini

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Paralleling is a mechanism to decrease the time necessary to execute the programs. Sorting is one of the important operations to be used in different systems in a way that the proper function of many algorithms and operations depend on sorted data. CRCW_SORT algorithm executes ‘N’ elements sorting in O(1) time on SIMD (Single Instruction Multiple Data) computers with n^2/2-n/2 number of processors. In this article having presented a mechanism by dividing the input string by the hinge element into two less strings the number of the processors to be used in sorting ‘N’ elements in O(1) time has decreased to n^2/8-n/4 in the best state; by this mechanism the best state is when the hinge element is the middle one and the worst state is when it is minimum. The findings from assessing the proposed algorithm by other methods on data collection and number of the processors indicate that the proposed algorithm uses less processors to sort during execution than other methods.

Keywords: CRCW, SIMD (Single Instruction Multiple Data) computers, parallel computers, number of the processors

Procedia PDF Downloads 303

Authors: Chris Ewe, Naoum Jamous, Holger Schrödl

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Like most entrepreneurs, data center operators pursue goals such as profit-maximization, improvement of the company’s reputation or basically to exist on the market. Part of those aims is to guarantee a given quality of service. Quality characteristics are specified in a contract called the service level agreement. Central part of this agreement is non-functional properties of an IT service. The system availability is one of the most important properties as it will be shown in this paper. To comply with availability requirements, data center operators can use virtualization technologies. A clear model to assess the effect of virtualization functions on the parts of a data center in relation to the system availability is still missing. This paper aims to introduce a basic model that shows these connections, and consider if the identified effects are positive or negative. Thus, this work also points out possible disadvantages of the technology. In consequence, the paper shows opportunities as well as risks of data center virtualization in relation to system availability.

Keywords: availability, cloud computing IT service, quality of service, service level agreement, virtualization

Procedia PDF Downloads 528

Authors: Alvin Chun Man Kwok, Wai Sun Chan, Wei Yuan, Joseph Tin Yum Wong

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Cellulose, the most abundant biopolymer, is the major constituent of plant and dinoflagellate cell walls. Thecate dinoflagellates, in particular, are renowned for their remarkable capacity to synthesize intricate cellulosic thecal plates (CTPs). Unlike the extracellular two-dimensional structure of plant cell walls, these CTPs are three-dimensional and reside within the cellular structure itself. The deposition of CTPs occurs with remarkable precision, and their arrangement serves as crucial taxonomic markers. It is noteworthy that these plates possess the hardness of wood, despite the absence of lignin. Partial and prolonged hydrolysis of CTPs results in the formation of uniform long bundles and lowdimensional, modular crystalline whiskers. This observation aligns with the consistent nanomechanical properties, suggesting a CTPboard structure. The unique composition and structural characteristics of CTPs distinguish them from other cellulose-based materials in the natural world. Spectroscopic studies using Raman and FTIR methods indicate a clear low crystallinity index, with the OH shift becoming more distinct following SDS treatment. Birefringence imaging confirms the highly organized structure of CTPs, demonstrating varying degrees of anisotropy in different regions, including both seaward and cytosolic passages. The knockdown of a cellulose synthase enzyme in dinoflagellates resulted in severe malformation of CTPs and hindered the life-cycle transition. Unlike certain other microalgal groups, these unique circum-spherical depositions of CTPs were not pre-fabricated and transported "to site," but synthesized within alveolar sacs at the specific site. Our research is particularly focused on unraveling the mechanisms underlying the biodeposition of CTPs and exploring their potential biotechnological applications. Understanding the processes involved in CTP formation can pave the way for harnessing their unique properties for various practical applications. Dinoflagellates play a crucial role as major agents of algal blooms and are also known for producing anti-greenhouse sulfur compounds such as DMS/DMSP, highlighting the significance of CTPs as a carbon-neutral source of cellulose. Grant acknowledgement: Research in the laboratory are supported by GRF16104523 from Research Grant Council to JTYW.

Keywords: cellulosic thecal plates, dinoflagellates, cellulose, cell wall

Procedia PDF Downloads 87

Authors: Thabiso M. Sebolai, Victor Mlambo, Solomon Tefera, Othusitse R. Madibela

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In some tree species, sustained herbivory can induce changes in biosynthetic pathways resulting in overproduction of anti-nutritional secondary plant compounds. This inductive mechanism, which has not been demonstrated in semi-arid rangelands of South Africa, may result in browse leaves of lower nutritive value. In this study we investigate the interactive effect of browsing pressure and tree species on chemical composition, buffer nitrogen solubility index (NSI), in vitro ruminal dry matter degradability (IVDMD) and in vitro ruminal N degradability (IVND) of leaves. Leaves from Maytenus capitata, Olea africana, Coddia rudis, Carissa macrocarpa, Rhus refracta, Ziziphus mucronata, Boscia oliedes, Grewia robusta, Phyllanthus vessucosus and Ehretia rigida trees growing in a communal grazing area were harvested at two heights: browsable ( < 1.5 m) and non-browsable ( > 1.5 m), representing high and low browsing pressure, respectively. The type of animals utilizing the communal rangeland includes cattle at 1 livestock unit (450kg)/12 to 15 hectors and goats at 1 livestock unit/4 ha. Harvested leaves were dried, milled and analysed for proximate components, soluble phenolics, condensed tannins, minerals and in vitro ruminal fermentation. A significant plant species and harvesting height interaction effect (P < 0.05) was observed for total nitrogen (N) and soluble phenolics concentration. Tree species and harvesting height affected (P < 0.05) condensed tannin (CTs) content where samples harvested from the non-browsable height had higher (0.61 AU550 nm/200 mg) levels than those harvested at browsable height (0.55 AU550 nm/200 mg) while their interaction had no effects. Macro and micro-minerals were only influenced (P < 0.05) by browse species but not harvesting height. Species and harvesting height interacted (P < 0.05) to influence IVDMD and IVND of leaves at 12, 24 and 36 hours of incubation. The different browse leaves contained moderate to high protein, moderate level of phenolics and minerals, suggesting that they have the potential to provide supplementary nutrients for ruminants during the dry seasons.

Keywords: browse plants, chemical composition, harvesting heights, phenolics

Procedia PDF Downloads 141

Authors: Nilda Ersoy, Sevinç Şener, Ayşe Yalçın Elidemir, Ebru Evcil, Ergün Döğen

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In this study, pesticide residues were investigated in black cumin (Nigella orientalis L.) seeds which grown in Turkey. GC-MS and LC-MS/MS analytical instruments are used in high precision, when determining residue limits. A total of 100 pesticide active ingredients in LC-MS/MS devices have been performed in Nigella orientalis L. seeds samples. Moreover, for same aim, 103 pesticide active ingredients were analyzed in GC-MS. This study conducted in 2012 and 2013. Samples residues were not found in detectable levels for two years.

Keywords: pesticide, residue, black cumin, Nigella orientalis L.

Procedia PDF Downloads 327

Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

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Crowd-sourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowd-sourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is -to our best knowledge- the first to develop safety performance functions using crowd-sourced data by adopting a negative binomial structure model and the Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

Procedia PDF Downloads 31