Search results for: 3D plant data

Authors: A. Abdullah, S. Abushalmat, A. Bakshwain, A. Basuhail, A. Aslam

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GIS (Geographic Information System) applications require geo-referenced data, this data could be available as databases or in the form of digital or hard-copy agro-meteorological maps. These parameter maps are color-coded with different regions corresponding to different parameter values, converting these maps into a database is not very difficult. However, text and different planimetric elements overlaid on these maps makes an accurate image to database conversion a challenging problem. The reason being, it is almost impossible to exactly replace what was underneath the text or icons; thus, pointing to the need for inpainting. In this paper, we propose a probabilistic inpainting approach that uses the probability of spatial locality of colors in the map for replacing overlaid elements with underlying color. We tested the limits of our proposed technique using non-textual simulated data and compared text removing results with a popular image editing tool using public domain data with promising results.

Keywords: noise, image, GIS, digital map, inpainting

Procedia PDF Downloads 334

Authors: Noureddine Mahmoudi

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The use of natural fibers in the development of composite materials is a sector in full expansion. These fibers were used for their low cost, their availability and their renewable character. The fibers of the palm (palm tree) were used as reinforcement in polypropylene (PP). The date palm fibers have some potential because of their ecological and economic interest. Both unmodified and compatibilized fibers are used. Compatibilization was carried out with the use of maleic anhydride copolymers. The morphology and mechanical properties were characterized by electron microscopy scanning (SEM) and tensile tests. The influence of fiber content on mechanical properties of composite PP / date palm has been evaluated and demonstrated, that the maximum stress and elongation decreases with increasing fiber volume rate. On the other hand, an increase of the tensile modulus has been noticed, but after the fibers improvement, the maximum stress increases significantly up to 25% weight.

Keywords: plant fiber, palm, SEM, compatibilizer

Procedia PDF Downloads 439

Authors: Juanling Lin

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The construction of urban parks is an important part of eco-city construction, and the intervention of big data provides a more scientific and rational platform for the assessment of urban parks by identifying and correcting the irrationality of urban park planning from the macroscopic level and then promoting the rational planning of urban parks. The study builds an urban park assessment system based on urban road network data and POI data, taking Futian District of Shenzhen as the research object, and utilizes the GIS geographic information system to assess the park system of Futian District in five aspects: park spatial distribution, accessibility, service capacity, demand, and supply-demand relationship. The urban park assessment system can effectively reflect the current situation of urban park construction and provide a useful exploration for realizing the rationality and fairness of urban park planning.

Keywords: urban parks, assessment system, POI, supply and demand

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

Procedia PDF Downloads 56

Authors: C. R. Ríos-Soberanis, V. M. Moo-Huchin, R. J. Estrada-Leon, E. Perez-Pacheco

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Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.

Keywords: biomaterials, characterization techniques, natural resource, starch

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Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges faced by MLDB system at the piston foundry plant due to interruption in supply of water. For the MLDB system to work in Model, two sub-units must be connected to the robotic main unit. The system cannot function without robotics and water supply by the fan (WSF). Insufficient water supply is the cause of system failure. The system operates at top performance using two sub-units. If one sub-unit fails, the system capacity is reduced. Priority of repair is given to the main unit i.e. Robotic and WSF. To solve the problem, semi-Markov process and regenerative point technique are used. Relevant graphs are also included to particular case.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: Kayode Fatokun, Nozipho N. Motsa

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Field experiments were carried out during the summer/autumn (first trial) and winter/spring (second trial) seasons of 2019 and 2021 inDlangubo, Ngwelezane, and Mtubatubaareas of KwaZulu-Natal Province of South Africa to study the drought amelioration effects and impact of 2 locally available organic wastes [filter cake (FC) and macadamia husk compost (MHC)] on the productivity, and physiological responses of 4 orange-fleshed sweet potato cultivars (Buregard cv., Impilo, W-119 and 199062.1). The effects of FC and MHC were compared with that of inorganic fertilizer (IF) [2:3:2 (30)], FC+IF, MHC+IF, and control. The soil amendments were applied in the first trials only. Climatic data such as humidity, temperature, and rainfall were taken via remote sensing. The results of the first trial indicated that filter cake and IF significantly performed better than MHC. While the strength of filter cake may be attributable to its rich array of mineral nutrients such as calcium, magnesium, potassium, sodium, zinc, copper, manganese, iron, and phosphorus. The little performance from MHC may be attributable to its water holding capacity. Also, a positive correction occurred between the yield of the test OFSP cultivars and climatic factors such as rainfall, NDVI, and NDWI values. Whereas the inorganic fertilizer did not have any significant effect on the growth and productivity of any of the tested sweet potato cultivars in the second trial; FC, and MHC largely maintained their significant performances. In conclusion, the use of FC is highly recommended in the production of the test orange-fleshed sweet potato cultivars. Also, the study indicated that both FC and MHC may not only supply the needed plant nutrients but has the capacity to reduce the impact of drought on the growth of the test cultivars. These findings are of great value to farmers, especially the resource-poorones.

Keywords: amendments, drought, filter cake, macadamia husk compost, sweet potato

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Authors: F. T. Senberber, N. Tugrul, E. Moroydor Derun

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As a nutraceutical, sumac (Rhus Coriaria) was extracted by using different solvents of methanol, ethanol, and water. The DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) method of free radical scavenging capacity was used to determine the effects of solvent on antioxidant activities of the plant. The total phenolic content was studied by The Folin Ciocalteu Reagent method. The antioxidant activities of extracts exhibit minor changes in different solvents and varied in the range of 84.3–86.4 %. The total phenolic contents are affected by the selected solvent. The highest total phenolic content was determined at the liquid phase of water and it was estimated as 26.3 mg/g in gallic acid.

Keywords: DPPH, solvent, sumac, total phenolic content

Procedia PDF Downloads 137

Authors: Vaibhav Barve

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Reversible information hiding has drawn a lot of interest as of late. Being reversible, we can restore unique computerized data totally. It is a plan where mystery data is put away in digital media like image, video, audio to maintain a strategic distance from unapproved access and security reason. By and large JPEG bit stream is utilized to store this key data, first JPEG bit stream is encrypted into all around sorted out structure and then this secret information or key data is implanted into this encrypted region by marginally changing the JPEG bit stream. Valuable pixels suitable for information implanting are computed and as indicated by this key subtle elements are implanted. In our proposed framework we are utilizing RC4 algorithm for encrypting JPEG bit stream. Encryption key is acknowledged by framework user which, likewise, will be used at the time of decryption. We are executing enhanced least significant bit supplanting steganography by utilizing genetic algorithm. At first, the quantity of bits that must be installed in a guaranteed coefficient is versatile. By utilizing proper parameters, we can get high capacity while ensuring high security. We are utilizing logistic map for shuffling of bits and utilization GA (Genetic Algorithm) to find right parameters for the logistic map. Information embedding key is utilized at the time of information embedding. By utilizing precise picture encryption and information embedding key, the beneficiary can, without much of a stretch, concentrate the incorporated secure data and totally recoup the first picture and also the original secret information. At the point when the embedding key is truant, the first picture can be recouped pretty nearly with sufficient quality without getting the embedding key of interest.

Keywords: data embedding, decryption, encryption, reversible data hiding, steganography

Procedia PDF Downloads 278

Authors: Tyler T. Procko, Steve Collins

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New features in .NET (6 and above) permit streamlined access to information residing in JSON-capable relational databases, such as SQL Server (2016 and above). Traditional methods of data access now comparatively involve unnecessary steps which compromise system performance. This work posits that the established ORM (Object Relational Mapping) based methods of data access in applications and APIs result in common issues, e.g., object-relational impedance mismatch. Recent developments in C# and .NET Core combined with a framework of modern SQL Server coding conventions have allowed better technical solutions to the problem. As an amelioration, this work details the language features and coding conventions which enable this streamlined approach, resulting in an open-source .NET library implementation called Codeless Data Access (CODA). Canonical approaches rely on ad-hoc mapping code to perform type conversions between the client and back-end database; with CODA, no mapping code is needed, as JSON is freely mapped to SQL and vice versa. CODA streamlines API data access by improving on three aspects of immediate concern to web developers, database engineers and cybersecurity professionals: Simplicity, Speed and Security. Simplicity is engendered by cutting out the “middleman” steps, effectively making API data access a whitebox, whereas traditional methods are blackbox. Speed is improved because of the fewer translational steps taken, and security is improved as attack surfaces are minimized. An empirical evaluation of the speed of the CODA approach in comparison to ORM approaches ] is provided and demonstrates that the CODA approach is significantly faster. CODA presents substantial benefits for API developer workflows by simplifying data access, resulting in better speed and security and allowing developers to focus on productive development rather than being mired in data access code. Future considerations include a generalization of the CODA method and extension outside of the .NET ecosystem to other programming languages.

Keywords: API data access, database, JSON, .NET core, SQL server

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Authors: Bumjo Kim, Hyun Jin Kim, Joon Ha Kim

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The separate sewer system is that collects the wastewater as a sewer pipe and rainfall as a stormwater pipe separately, and then sewage is treated in the wastewater treatment plant, the stormwater is discharged to rivers or lakes through stormwater drainage pipes. Unfortunately, even for separate sewer systems, it is not possible to prevent Rainfall Driven Inflow/Infiltration(RDII) completely to the sewer pipe. Even if the sewerage line is renovated, there is an ineluctable RDII due to the combined sewer system in the house or the difficulty of sewage maintenance in private areas. The basic statistical analysis was performed using environmental data including rainfall, sewage, water qualities and groundwater level in the strict of Gwangju in ​South Korea. During rainfall in the target area, RDII showed an increased rate of 13.4 ~ 53.0% compared to that of a clear day and showed a rapid hydrograph response of 0.3 ~ 3.0 hr. As a result of water quality analysis, BOD5 concentration decreased by 17.3 % and salinity concentration decreased by 8.8 % at the representative spot in the project area compared to the sunny day during rainfall. In contrast to the seasonal fluctuation range of 0.38 m ~ 0.55 m in groundwater in Gwangju area and 0.58 m ~ 0.78 m in monthly fluctuation range, while the difference between groundwater level and the depth of sewer pipe laying was 2.70 m on average, which is larger than the range of fluctuation. Comprehensively, it can be concluded that the increasing of flowrate at sewer line is due to not infiltration water caused by groundwater level rise, construction failure, cracking due to joint failure or conduit deterioration, rainfall was directly inflowed into the sewer line rapidly. Acknowledgements: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: ground water, rainfall, rainfall driven inflow/infiltration, separate sewer system

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

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The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas, and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It's is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain. Then we try to describe various application areas, challenges, and future directions in the healthcare sector where blockchain platforms merge with IoT networks.

Keywords: IoT, blockchain, cryptocurrency, healthcare, consensus, data

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Authors: Şafak Aksoy, Ali Kurşun, Erhan Çetin, Mustafa Reşit Haboğlu

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In this study, thermo elastic stress analysis is performed on a cylinder made of laminated isotropic materials under thermomechanical loads. Laminated cylinders have many applications such as aerospace, automotive and nuclear plant in the industry. These cylinders generally performed under thermomechanical loads. Stress and displacement distribution of the laminated cylinders are determined using by analytical method both thermal and mechanical loads. Based on the results, materials combination plays an important role on the stresses distribution along the radius. Variation of the stresses and displacements along the radius are presented as graphs. Calculations program are prepared using MATLAB® by authors.

Keywords: isotropic materials, laminated cylinders, thermoelastic stress, thermomechanical load

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Authors: Oseyemi Omowunmi Olubomehin, Olufemi Michael Denton

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Diabetes mellitus is a disease that is related to the digestion of carbohydrates, proteins and fats and how this affects the blood glucose levels. Various synthetic drugs employed in the management of the disease work through different mechanisms. Keeping postprandial blood glucose levels within acceptable range is a major factor in the management of type 2 diabetes and its complications. Thus, the inhibition of carbohydrate-hydrolyzing enzymes such as α-amylase is an important strategy in lowering postprandial blood glucose levels, but synthetic inhibitors have undesirable side effects like flatulence, diarrhea, gastrointestinal disorders to mention a few. Therefore, it is necessary to identify and explore the α-amylase inhibitors from plants due to their availability, safety, and low costs. In the present study, extracts from the leaves of Rauvolfia vomitoria and seeds of Picralima nitida which are used in the Nigeria traditional system of medicine to treat diabetes were tested for their α-amylase inhibitory effect. The powdered plant samples were subjected to phytochemical screening using standard procedures. The leaves and seeds macerated successively using n-hexane, ethyl acetate and methanol resulted in the crude extracts which at different concentrations (0.1, 0.5 and 1 mg/mL) alongside the standard drug acarbose, were subjected to α-amylase inhibitory assay using the Benfield and Miller methods, with slight modification. Statistical analysis was done using ANOVA, SPSS version 2.0. The phytochemical screening results of the leaves of Rauvolfia vomitoria and the seeds of Picralima nitida showed the presence of alkaloids, tannins, saponins and cardiac glycosides while in addition Rauvolfia vomitoria had phenols and Picralima nitida had terpenoids. The α-amylase assay results revealed that at 1 mg/mL the methanol, hexane, and ethyl acetate extracts of the leaves of Rauvolfia vomitoria gave (15.74, 23.13 and 26.36 %) α-amylase inhibitions respectively, the seeds of Picralima nitida gave (15.50, 30.68, 36.72 %) inhibitions which were not significantly different from the control at p < 0.05, while acarbose gave a significant 56 % inhibition at p < 0.05. The presence of alkaloids, phenols, tannins, steroids, saponins, cardiac glycosides and terpenoids in these plants are responsible for the observed anti-diabetic activity. However, the low percentages of α-amylase inhibition by these plant samples shows that α-amylase inhibition is not the major way by which both plants exhibit their anti-diabetic effect.

Keywords: alpha-amylase, Picralima nitida, postprandial hyperglycemia, Rauvolfia vomitoria

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

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Authors: Zuzana Poborilova, Anna B. Ohlsson, Torkel Berglund, Anna Vildova, Petr Babula

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Lawsone is a pigment that occurs naturally in plants. It has been used as a skin and hair dye for a long time. Moreover, its different biological activities have been reported. The present study focused on the effect of lawsone on a plant cell model represented by tobacco BY-2 cell suspension culture, which is used as a model comparable with the HeLa cells. It has been shown that lawsone inhibits the cell growth in the concentration-dependent manner. In addition, changes in DNA methylation level have been determined. We observed decreasing level of DNA methylation in the presence of increasing concentrations of lawsone. These results were accompanied with overproduction of reactive oxygen species (ROS). Since epigenetic modifications can be caused by different stress factors, there could be a connection between the changes in the level of DNA methylation and ROS production caused by lawsone.

Keywords: DNA methylation, lawsone, naphthoquinone, reactive oxygen species

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Authors: Mayada Al Meghari

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Recently, grid middlewares have provided large integrated use of network resources as the shared data and the CPU to become a virtual supercomputer. In this work, we present the design and implementation of the middleware for Data Warehouse Signature, DWS Framework. The aim of using the middleware in our DWS framework is to achieve the high performance by the parallel computing. This middleware is developed on Alchemi.Net framework to increase the security among the network nodes through the authentication and group-key distribution model. This model achieves the key security and prevents any intermediate attacks in the middleware. This paper presents the flow process structures of the middleware design. In addition, the paper ensures the implementation of security for DWS middleware enhancement with the authentication and group-key distribution model. Finally, from the analysis of other middleware approaches, the developed middleware of DWS framework is the optimal solution of a complete covering of security issues.

Keywords: middleware, parallel computing, data warehouse, security, group-key, high performance

Procedia PDF Downloads 98

Authors: Swarnadip Ghosh

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Sentiment Analysis is the process of detecting the contextual polarity of text. In other words, it determines whether a piece of writing is positive, negative or neutral.Sentiment analysis of documents holds great importance in today's world, when numerous information is stored in databases and in the world wide web. An efficient algorithm to illicit such information, would be beneficial for social, economic as well as medical purposes. In this project, we have developed an algorithm to classify a document into positive or negative. Using our algorithm, we obtained a feature set from the data, and classified the documents based on this feature set. It is important to note that, in the classification, we have not used the independence assumption, which is considered by many procedures like the Naive Bayes. This makes the algorithm more general in scope. Moreover, because of the sparsity and high dimensionality of such data, we did not use empirical distribution for estimation, but developed a method by finding degree of close clustering of the data points. We have applied our algorithm on a movie review data set obtained from IMDb and obtained satisfactory results.

Keywords: sentiment, Run's Test, cross validation, higher dimensional pmf estimation

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Authors: Ayodele Ajayi, John Ajayi

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This paper investigates the effect of corporate governance with a view to determining the relationship between board size and bank performance. Data for the study were obtained from the audited financial statements of five sampled banks listed on the Nigerian Stock Exchange. Panel data technique was adopted and analysis was carried out with the use of multiple regression and pooled ordinary least square. Results from the study show that the larger the board size, the greater the profit implying that corporate governance is positively correlated with bank performance.

Keywords: corporate governance, banks performance, board size, pooled data

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

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Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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Authors: A. Adetutu, T. M. Awodugba, O. A. Owoade

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The development of resistance to currently known conventional anti-typhoid drugs has necessitated search into cheap, more potent and less toxic anti-typhoid drugs of plant origin. Therefore, this study investigated the anti-typhoid activity of fractions of A. indica in Salmonella typhi infected rats. Leaves of A. indica were extracted in methanol and fractionated into n-hexane, chloroform, ethyl-acetate, and aqueous fractions. The anti-salmonella potentials of fractions of A. indica were assessed via in-vitro inhibition of S. typhi using agar well diffusion, Minimum Inhibitory Concentration (MIC), Minimum Bactericidal Concentration (MBC) and biofilm assays. The biochemical and haematological parameters were determined by spectrophotometric methods. The histological analysis was performed using Haematoxylin and Eosin staining methods. Data analysis was performed by one-way ANOVA. Results of this study showed that S. typhi was sensitive to aqueous and chloroform fractions of A. indica, and the fractions showed biofilm inhibition at concentrations of 12.50, 1.562, and 0.39 mg/mL. In the in-vivo study, the extract and chloroform fraction had significant (p < 0.05) effects on the number of viable S. typhi recovered from the blood and stopped salmonellosis after 6 days of treatment of rats at 500 mg/kg b.w. Treatments of infected rats with chloroform and aqueous fractions of A. indica normalized the haematological parameters in the animals. Similarly, treatment with fractions of the plants sustained a normal antioxidant status when compared with the normal control group. Chloroform and ethyl-acetate fractions of A. indica reversed the liver and intestinal degeneration induced by S. typhi infection in rats. The present investigation indicated that the aqueous and chloroform fractions of A. indica showed the potential to provide an effective treatment for salmonellosis, including typhoid fever. The results of the study may justify the ethno-medicinal use of the extract in traditional medicine for the treatment of typhoid and salmonella infections.

Keywords: Azadirachta indica L, salmonella, typhoid, leave fractions

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Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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Authors: Sung Ho Ahn, Jintae Hong, Chang Young Joung, Tae Ho Yang, Sung Ho Heo, Seo Yun Jang

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The performances of nuclear fuels and materials are qualified at an irradiation system in research reactors operating under the commercial nuclear power plant conditions. Fuel centerline temperature, coolant temperature, neutron flux, deformations of fuel stack and swelling are important parameters needed to analyze the nuclear fuel performances. The dimensional stability of nuclear fuels is a key parameter measuring the fuel densification and swelling. In this study, the fuel stack elongation is measured using a LVDT. A mockup LVDT instrumented fuel rod is developed. The performances of mockup LVDT instrumented fuel rod is evaluated by experiments.

Keywords: axial deformation, elongation measurement, in-pile instrumentation, LVDT

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Authors: Toleen Alaqqad, Kadi Alshabramiy, Suad Zaafarany, Basma Musallam

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CADmapper is a significant tool of software for transforming geographic data into realistic CAD drawings. It speeds up and simplifies the conversion process by automating it. This allows architects, urban planners, engineers, and geographic information system (GIS) experts to solely concentrate on the imaginative and scientific parts of their projects. While the future incorporation of AI has the potential for further improvements, CADmapper's current capabilities make it an indispensable asset in the business. It covers a combination of 2D and 3D city and urban area models. The user can select a specific square section of the map to view, and the fee is based on the dimensions of the area being viewed. The procedure is straightforward: you choose the area you want, then pick whether or not to include topography. 3D architectural data (if available), followed by selecting whatever design program or CAD style you want to publish the document which contains more than 200 free broad town plans in DXF format. If you desire to specify a bespoke area, it's free up to 1 km2.

Keywords: cadmaper, gdata, 2d and 3d data conversion, automated cad drawing, urban planning software

Procedia PDF Downloads 47

Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

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In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

Procedia PDF Downloads 45

Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

Procedia PDF Downloads 566

Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

Abstract:

Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 190

Authors: Amriana Hifizah, Philip Edward Vercoe, Graeme Bruce Martin, Teuku Reza Ferasy, Muhammad Hambal

Abstract:

Many native forage plant species have been used in Indonesia as feed for ruminants. However, less information is available about how these plants affect productivity, let alone methane emissions. In the province of Aceh, where the traditional practice is to feed local forages to small ruminants, the farmers are not satisfied with the productivity of their livestock, and they attribute this problem to poor availability and too few options for good quality forages. Forage quality is reduced by high environmental temperatures which increase the amount of lignification. In addition to reducing productivity, these factors also increase enteric methane production. A preliminary survey about potential forage species was completed in three different districts, two of low elevation and one of high elevation: Syiah Kuala (05°30’5.08” N to 095°24’7.35” E), elevation 29 m MSL; Kajhu (05°32’34.6” N to 095°21’17.7” E), elevation 30 m MSL; Lembah Seulawah (05°28'06.4" N to 095°43' 14.2" E), elevation 254 m MSL. Information about local plants was collected in a semi-structured interview with scientists, government field officers and local farmers, in the city of Banda Aceh and in those three districts. The outcome was a list 40 species that could be useful, of which 21 were selected for further study. The selection process was based on several criteria: high availability, high protein content, low toxicity, and evidence of secondary metabolites (eg, history of medicinal plants for both human and animals). For some of the selected medicinal plants, there is experimental evidence of effects on methane production during rumen fermentation. Subsequently, the selected forages were tested for their effects on rumen fermentation in vitro, using batch culture. The data produced will be used to identify forages with the potential to reduce CH4 emissions. These candidates will then be assessed for their benefits (fermentability and productivity) and potential deleterious side-effects.

Keywords: batch culture, forage, methane, rumen

Procedia PDF Downloads 317