Search results for: plant data

Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Jose Manuel Rodriguez-Dominguez, Rodrigo Barba-Gonzalez, Ernesto Tapia-Campos

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Sprekelia formosissima (L.) Herbert is a bulbous ornamental species of the monocotyledonous Amaryllidaceae family, and it is a perennial, herbaceous monotypic plant commonly known as ‘Aztec Lily’ or ‘Jacobean Lily’; it is distributed through Mexico and Guatemala. Its scarlet flowers with curved petals have made it an exceptional ornamental pot plant. Cytogenetic studies in this species have shown differences in chromosome number (2n=60, 120, 150, 180) with a basic number x=30. Different reports have shown a variable ploidy level (diploid, tetraploid, pentaploid and hexaploid); however, triploid plants have not been reported. In this work, triploid plants of S. formosissima were obtained by crossing tetraploid (2n=4x=120) with diploid (2n=2x=60) genotypes of this species; the seeds obtained from the crosses were placed in pots with a moist substrate made of Peat Moss: Vermiculite (7:3) for germination. Root tips were collected, and metaphasic chromosome preparations were performed. For chromosome counting, the best five metaphases obtained were photographed with a Leica DMRA2 microscope (Leica Microsystems, Germany) microscopy coupled to an Evolution QEI camera under phase contrast (Media-Cybernetics). Chromosomes counting in root-tip cells showed that 100% of the plants were triploid (2n=3x=90). Although tetraploid or pentaploid plants of S. formosissima are highly appreciated, they usually have lower growth rates than related diploid ones. For this reason, it is important to obtain triploid plants, which have advantages such as higher growth rates than tetraploid and pentaploid, larger flowers than those of the diploid plants and they are expected to not be able to produce seeds because their gametes are aneuploids. Furthermore, triploids may become very important for genomic research in the future, creating opportunities for discovering and monitoring genomic and transcriptomic changes in unbalanced genomes, hence the importance of this work.

Keywords: Amaryllidaceae, cytogenetics, ornamental, ploidy level

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Authors: Ph. Fauquet-Alekhine

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Decision-making occurs several times an hour when working in high risk industry and an erroneous choice might have undesirable outcomes for people and the environment surrounding the industrial plant. Industrial decisions are very often made in a context of acute stress. Time pressure is a crucial stressor leading decision makers sometimes to boost up the decision-making process and if it is not possible then shift to the simplest strategy. We thus found it interesting to update the characterization of the stress factors impairing decision-making at Chinon Nuclear Power Plant (France) in order to optimize decision making contexts and/or associated processes. The investigation was based on the analysis of reports addressing safety events over the last 3 years. Among 93 reports, those explicitly addressing decision-making issues were identified. Characterization of each event was undertaken in terms of three criteria: stressors, biases impairing decision making and weaknesses of the decision-making process. The statistical analysis showed that biases were distributed over 10 possibilities among which the hypothesis confirmation bias was clearly salient. No significant correlation was found between criteria. The analysis indicated that the main stressor was time pressure and highlights an unexpected form of stressor: the trust asymmetry principle of the expert. The analysis led to the conclusion that this stressor impaired decision-making from a psychological angle rather than from a physiological angle: it induces defensive bias of self-esteem, self-protection associated with a bias of confirmation. This leads to the hypothesis that this stressor can intervene in some cases without being detected, and to the hypothesis that other stressors of the same kind might occur without being detected too. Further investigations addressing these hypotheses are considered. The analysis also led to the conclusion that dealing with these issues implied i) decision-making methods being well known to the workers and automated and ii) the decision-making tools being well known and strictly applied. Training was thus adjusted.

Keywords: bias, expert, high risk industry, stress.

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Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

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The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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Authors: Jayesh M. Patel, Bharat P. Modi

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The availability of on mobile devices that can invoke the demonstrated that the total data demand from users is far higher than previously articulated by measurements based solely on a cellular-centric view of smart-phone usage. The ratio of Wi-Fi to cellular traffic varies significantly between countries, This paper is shown the compression between the cellular data usage and Wi-Fi data usage by the user. This strategy helps operators to understand the growing importance and application of yield management strategies designed to squeeze maximum returns from their investments into the networks and devices that enable the mobile data ecosystem. The transition from unlimited data plans towards tiered pricing and, in the future, towards more value-centric pricing offers significant revenue upside potential for mobile operators, but, without a complete insight into all aspects of smartphone customer behavior, operators will unlikely be able to capture the maximum return from this billion-dollar market opportunity.

Keywords: cellular, Wi-Fi, mobile, smart phone

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Authors: Isha Saxena, Behzad Kazemtabrizi, Matthias C. M. Troffaes, Christopher Crabtree

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The calculations done at the beginning of the life of a wind farm are rarely reliable, which makes it important to conduct research and study the failure and repair rates of the wind turbines under various conditions. This miscalculation happens because the current models make a simplifying assumption that the failure/repair rate remains constant over time. This means that the reliability function is exponential in nature. This research aims to create a more accurate model using sensory data and a data-driven approach. The data cleaning and data processing is done by comparing the Power Curve data of the wind turbines with SCADA data. This is then converted to times to repair and times to failure timeseries data. Several different mathematical functions are fitted to the times to failure and times to repair data of the wind turbine components using Maximum Likelihood Estimation and the Posterior expectation method for Bayesian Parameter Estimation. Initial results indicate that two parameter Weibull function and exponential function produce almost identical results. Further analysis is being done using the complex system analysis considering the failures of each electrical and mechanical component of the wind turbine. The aim of this project is to perform a more accurate reliability analysis that can be helpful for the engineers to schedule maintenance and repairs to decrease the downtime of the turbine.

Keywords: reliability, bayesian parameter inference, maximum likelihood estimation, weibull function, SCADA data

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Authors: Muhammad Shafiq

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In accelerated life testing approaches life time data is obtained under various conditions which are considered more severe than usual condition. Classical techniques are based on obtained precise measurements, and used to model variation among the observations. In fact, there are two types of uncertainty in data: variation among the observations and the fuzziness. Analysis techniques, which do not consider fuzziness and are only based on precise life time observations, lead to pseudo results. This study was aimed to examine the behavior of empirical acceleration functions using fuzzy lifetimes data. The results showed an increased fuzziness in the transformed life times as compare to the input data.

Keywords: acceleration function, accelerated life testing, fuzzy number, non-precise data

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Authors: Neha Bhadauria, Indu Gaur, Shilpi Shilpi, Susmita Goswami, Prabir K. Paul

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The aerial surface of plants colonized by Human Enteric Pathogens ()has been implicated in outbreaks of enteric diseases in humans. Practice of organic farming primarily using animal dung as manure and sewage water for irrigation are the most significant source of enteric pathogens on the surface of leaves, fruits and vegetables. The present work aims to have an insight into the molecular mechanism of interaction of Human Enteric Pathogens or their metabolites with cell wall receptors in plants. Tomato plants grown under aseptic conditions at 12 hours L/D photoperiod, 25±1°C and 75% RH were inoculated individually with S. fonticola and K. pneumonia. The leaves from treated plants were sampled after 24 and 48 hours of incubation. The cell wall and cytoplasmic proteins were extracted and isocratically separated on 1D SDS-PAGE. The sampled leaves were also subjected to formaldehyde treatment prior to isolation of cytoplasmic proteins to study protein-protein interactions induced by Human Enteric Pathogens. Protein bands extracted from the gel were subjected to MALDI-TOF-TOF MS analysis. The foremost interaction of Human Enteric Pathogens on the plant surface was found to be cell wall bound receptors which possibly set ups a wave a critical protein-protein interaction in cytoplasm. The study revealed the expression and suppression of specific cytoplasmic and cell wall-bound proteins, some of them being important components of signaling pathways. The results also demonstrated HEP induced rearrangement of signaling pathways which possibly are crucial for adaptation of these pathogens to plant surface. At the end of the study, it can be concluded that controlling the over-expression or suppression of these specific proteins rearrange the signaling pathway thus reduces the outbreaks of food-borne illness.

Keywords: cytoplasmic protein, cell wall-bound protein, Human Enteric Pathogen (HEP), protein-protein interaction

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Authors: E. A. Krasikov

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As the service life of an operating nuclear power plant (NPP) increases, the potential misunderstanding of the degradation of aging components must receive more attention. Integrity assurance analysis contributes to the effective maintenance of adequate plant safety margins. In essence, the reactor pressure vessel (RPV) is the key structural component determining the NPP lifetime. Environmentally induced cracking in the stainless steel corrosion-preventing cladding of RPV’s has been recognized to be one of the technical problems in the maintenance and development of light-water reactors. Extensive cracking leading to failure of the cladding was found after 13000 net hours of operation in JPDR (Japan Power Demonstration Reactor). Some of the cracks have reached the base metal and further penetrated into the RPV in the form of localized corrosion. Failures of reactor internal components in both boiling water reactors and pressurized water reactors have increased after the accumulation of relatively high neutron fluences (5´1020 cm–2, E>0,5MeV). Therefore, in the case of cladding failure, the problem arises of hydrogen (as a corrosion product) embrittlement of irradiated RPV steel because of exposure to the coolant. At present when notable progress in plasma physics has been obtained practical energy utilization from fusion reactors (FR) is determined by the state of material science problems. The last includes not only the routine problems of nuclear engineering but also a number of entirely new problems connected with extreme conditions of materials operation – irradiation environment, hydrogenation, thermocycling, etc. Limiting data suggest that the combined effect of these factors is more severe than any one of them alone. To clarify the possible influence of the in-service synergistic phenomena on the FR structural materials properties we have studied hydrogen-irradiated steel interaction including alternating hydrogenation and heat treatment (annealing). Available information indicates that the life of the first wall could be expanded by means of periodic in-place annealing. The effects of neutron fluence and irradiation temperature on steel/hydrogen interactions (adsorption, desorption, diffusion, mechanical properties at different loading velocities, post-irradiation annealing) were studied. Experiments clearly reveal that the higher the neutron fluence and the lower the irradiation temperature, the more hydrogen-radiation defects occur, with corresponding effects on the steel mechanical properties. Hydrogen accumulation analyses and thermal desorption investigations were performed to prove the evidence of hydrogen trapping at irradiation defects. Extremely high susceptibility to hydrogen embrittlement was observed with specimens which had been irradiated at relatively low temperature. However, the susceptibility decreases with increasing irradiation temperature. To evaluate methods for the RPV’s residual lifetime evaluation and prediction, more work should be done on the irradiated metal–hydrogen interaction in order to monitor more reliably the status of irradiated materials.

Keywords: hydrogen, radiation, stability, structural steel

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Authors: Feras Hanandeh, Izzat Alsmadi, Muhammad M. Kwafha

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Prefix trees or tries are data structures that are used to store data or index of data. The goal is to be able to store and retrieve data by executing queries in quick and reliable manners. In principle, the structure of the trie depends on having letters in nodes at the different levels to point to the actual words in the leafs. However, the exact structure of the trie may vary based on several aspects. In this paper, we evaluated different structures for building tries. Using datasets of words of different sizes, we evaluated the different forms of trie structures. Results showed that some characteristics may impact significantly, positively or negatively, the size and the performance of the trie. We investigated different forms and structures for the trie. Results showed that using an array of pointers in each level to represent the different alphabet letters is the best choice.

Keywords: data structures, indexing, tree structure, trie, information retrieval

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Authors: Elizaveta Petelina, Anton Sizo

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Environmental remediation projects deal with a wide spectrum of data, including data collected during site assessment, execution of remediation activities, and environmental monitoring. Therefore, an appropriate data management is required as a key factor for well-grounded decision making. The Environmental Data Management System (EDMS) was developed to address all necessary data management aspects, including efficient data handling and data interoperability, access to historical and current data, spatial and temporal analysis, 2D and 3D data visualization, mapping, and data sharing. The system focuses on support of well-grounded decision making in relation to required mitigation measures and assessment of remediation success. The EDMS is a combination of enterprise and desktop level data management and Geographic Information System (GIS) tools assembled to assist to environmental remediation, project planning, and evaluation, and environmental monitoring of mine sites. EDMS consists of seven main components: a Geodatabase that contains spatial database to store and query spatially distributed data; a GIS and Web GIS component that combines desktop and server-based GIS solutions; a Field Data Collection component that contains tools for field work; a Quality Assurance (QA)/Quality Control (QC) component that combines operational procedures for QA and measures for QC; Data Import and Export component that includes tools and templates to support project data flow; a Lab Data component that provides connection between EDMS and laboratory information management systems; and a Reporting component that includes server-based services for real-time report generation. The EDMS has been successfully implemented for the Project CLEANS (Clean-up of Abandoned Northern Mines). Project CLEANS is a multi-year, multimillion-dollar project aimed at assessing and reclaiming 37 uranium mine sites in northern Saskatchewan, Canada. The EDMS has effectively facilitated integrated decision-making for CLEANS project managers and transparency amongst stakeholders.

Keywords: data management, environmental remediation, geographic information system, GIS, decision making

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Authors: Bharat Singh Om Prakash Vyas

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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.

Keywords: ALS, NMF, high dimensional data, RMSE

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Authors: Khaled Mawardi

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Bay laurel (Laurus nobilis L.) is an evergreen of the Laurus genus of the Lauraceae Family. It is a plant native to the southern Mediterranean and widespread in Syria. It is a plant with enormous industrial applications. For instance, they are used as platform chemicals in food, pharmaceutical and cosmetic applications. Herein, we report an efficient extraction of Bay laurel oil from Bay laurel fruits via a comparative investigation of boiled water conventional extraction technique and microwave-assisted extraction (MAE) by microwave heating at atmospheric pressure. In order to optimize the extraction efficiency, we investigated several extraction parameters, such as extraction time and microwave power. In addition, to demonstrate the feasibility of the method, oil obtained under optimal conditions by method (MAE) was compared quantitatively and qualitatively with that obtained by the conventional method. After 1h of microwave-assisted extraction (power of 600W), an oil yield of 9.8% with identified lauric acid content of 22.7%. In comparison, an extended extraction of up to 4h was required to obtain a 9.7% yield of oil extraction with 21.2% of lauric acid content. The change in microwave power impacts the fatty acids profile and also the quality parameters of Laurel Oil. It was found that the profile of fatty acids changed with the power, where the lauric acid content increased from 22.7% at 600W to 30.5% at 1200W owing to a decrease of oleic acid content from 32.8% at 600W to 28.3% at 1200W and linoleic acid content from 22.3% at 600W to 20.6% at 1200W. In addition, we observed a decrease in oil yield from 9.8% at 600W to 5.1% at 1200W. Summarily, the overall results indicated that the extraction of laurel fruit oils could be successfully performed using (MAE) at a short extraction time and lower energy compared with the fixed oil obtained by conventional processes of extraction. Microwave heating exerted more aggressive effects on the oil. Indeed, microwave heating inflicted changes in the fatty acids profile of oil; the most affected fraction was the unsaturated fatty acids, with higher susceptibility to oxidation.

Keywords: microwaves, extraction, Laurel oil, solvent-free

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Authors: Anna Bohers, Emília Hroncová, Juraj Ladomerský

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Oil sludge with its main characteristic of high acidity is a waste product generated from the operation of refinery and petrochemical plants. Former refinery and petrochemical plant - Petrochema Dubová is present in Slovakia as well. Its activities was to process the crude oil through sulfonation and adsorption technology for production of lubricating and special oils, synthetic detergents and special white oils for cosmetic and medical purposes. Seventy years ago – period, when this historical acid sludge burden has been created – comparing to the environmental awareness the production was in preference. That is the reason why, as in many countries, also in Slovakia a historical environmental burden is present until now – 229 211 m3 of oil sludge in the middle of the National Park of Nízke Tatry mountain chain. Neither one of tried treatment methods – bio or non-biologic one - was proved as suitable for processing or for recovery in the reason of different factors admission: i.e. strong aggressivity, difficulty with handling because of its sludgy and liquid state et sim. As a potential solution, also incineration was tested, but it was not proven as a suitable method, as the concentration of SO2 in combustion gases was too high, and it was not possible to decrease it under the acceptable value of 2000 mg.mn-3. That is the reason why the operation of incineration plant has been terminated, and the acid sludge landfills are present until nowadays. The objective of this paper is to present a new possibility of processing and valorization of acid sludgy-waste. The processing of oil sludge was performed through the effective separation - thermal desorption technology, through which it is possible to split the sludgy material into the matrix (soil, sediments) and organic contaminants. In order to boost the efficiency in the processing of acid sludge through thermal desorption, the work will present the possibility of application of an original technology – Method of Blowing Decomposition for recovering of organic matter into technological lubricating oil.

Keywords: hazardous waste, oil sludge, remediation, thermal desorption

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Sulaiman A. Alrumman, Abd El-Latif Hesham

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Despite medical progress worldwide, dental caries are still widespread. Miswak is derived from the plant arak (Salvadora persica). It is used by Muslim people as a natural product for the cleansing of teeth, to ensure oral and dental hygiene. This study was designed to evaluate the antimicrobial effects of ethanol, methanol, and ethanol/methanol extracts of miswak against three bacterial pathogens of the oral cavity. The pathogens were isolated from the oral cavity of volunteers/patients and were identified on the basis of 16S rRNA gene amplification data. Sequence comparisons were made with 16S rRNA gene sequences available in the GenBank database. The results of sequence alignment and phylogenetic analysis identified the three pathogens as being Staphylococcus aureus strain KKU-020, Enterococcus faecalis strain KKU-021 and Klebsiella pneumoniae strain KKU-022. All miswak extracts showed powerful antimicrobial activity against the three pathogens. The maximum zone of inhibition (40.67±0.88 mm) was observed against E. faecalis with ethanolic extracts whilst methanolic extracts showed the minimum zone of inhibition (10.33±0.88 mm) against K. pneumonia KKU-022. Based on the significant effects of the miswak extracts against the oral cavity pathogens in our study, we recommend that miswak is to be used as a dental hygiene method to prevent tooth caries.

Keywords: antibacterial, miswak, Salvadora persica, oral cavity pathogens

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Authors: Wang Lin, Li Zhiqiang

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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

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Authors: Jamilah Syafawati Yaacob, Muhammad Aiman Ramli

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Cili padi or Capsicum frutescens is one of capsicum species from nightshade family, Solanaceae. It is famous in Malaysia and is widely used as a food ingredient. Capsicum frutescens also possess vast medicinal properties. The objectives of this study are to determine the most optimum 2,4-D hormone concentration for callus induction from stem explants C. frutescens and the effects of different 2,4-D concentrations on expression of compounds from C. frutescens. Seeds were cultured on MS media without hormones (MS basal media) to yield aseptic seedlings of this species, which were then used to supply explant source for subsequent tissue culture experiments. Stem explants were excised from aseptic seedlings and cultured on MS media supplemented with various concentrations (0.1, 0.3 and 0.5 mg/L) of 2,4-D to induce formation of callus. Fresh weight, dry weight and callus growth percentage in all samples were recorded. The highest mean of dry weight was observed in MS media supplemented with 0.5 mg/L 2,4-D, where 0.4499 ± 0.106 g of callus was produced. The highest percentage of callus growth (16.4%) was also observed in cultures supplemented with 0.5 mg/L 2,4-D. The callus samples were also subjected to HPLC-MS to evaluate the effect of hormone concentration on expression of bio active compounds in different samples. Results showed that caffeoylferuloylquinic acids were present in all samples, but was most abundant in callus cells supplemented with 0.3 & 0.5 mg/L 2,4-D. Interestingly, there was an unknown compound observed to be highly expressed in callus cells supplemented with 0.1 mg/L 2,4-D, but its presence was less significant in callus cells supplemented with 0.3 and 0.5 mg/L 2,4-D. Furthermore, there was also a compound identified as octadecadienoic acid, which was uniquely expressed in callus supplemented with 0.5 mg/L 2,4-D, but absent in callus cells supplemented with 0.1 and 0.3 mg/L 2,4-D. The results obtained in this study indicated that plant growth regulators played a role in expression of secondary metabolites in plants. The increase or decrease of these growth regulators may have triggered a change in the secondary metabolite biosynthesis pathways, thus causing differential expression of compounds in this plant.

Keywords: callus, in vitro, secondary metabolite, 2, 4-Dichlorophenoxyacetic acid

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

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With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: cloud storage security, sharing storage, attributes, Hash algorithm

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Authors: Kazam Ali, Muhammad Sagheer, Mansoor-Ul- Hasan, Abdul Rashid, Chaudhary Muhammad Shahid Hanif, Fawad Zafar Ahmad Khan, Hafiz Muhammad Aatif

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Natural extracts of two medicinal plants Nicotiana tabacum and Eucalyptus globulus were tested for their toxic and enzyme inhibition effects against three insects species of stored grains Tribolium castaneum, Trogoderma granarium and Sitophilus granarius. Responses of insects varied with exposure periods and dilution levels of acetone extracts of plants. Both plant extracts were lethal to insects but the crude leaf extract of N. tabacum evidenced strong toxic action against three tested insect species. Maximum mortality 36.30% in S. granarius, 25.96% in T. castaneum, and 21.88% in T. granarium were found at 20% dilution level, after 10 days exposure to botanical extract of N. tabacum. The impact of N. tabacum and E. globulus on the activity of esterases; acetylcholinesterase (AChE), α-carboxylesterase (α-CE), β-carboxylesterase (β-CE) and phosphatses; acid phosphatase (AcP), alkaline phosphatase (AlP) of three stored grain insect species were also studied in the survivors of toxicity assay. Whole body homogenates of insects were used for enzyme determination and consumption of high dose rate N. tabacum extract containing diet resulted in maximum 55.33% inhibition of AChE and 26.17% AlP inhibition in T. castaneum, while 44.17% of α-CE and 31.67% inhibition of β-CE activity were noted in S. granarius. Maximum inhibition 23.44% of AcP activity was found in T. granarium exposed to diet treated with the extract of E. globulus. The findings indicate that acetone extracts of N. tabacum and E. globulus are naturally occurring pesticide and facts of the enzyme inhibition relations specify that their effect changes with the insect species.

Keywords: natural extract, medicinal plant, toxic effects, enzyme inhibition, acetone extract

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Authors: Binjuan Xu, Qian Zhao, Ping Jiang, Bo Guo, Zhijun Cheng, Xiaoyue Wu

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Astronautical valves are key units in engine systems of astronautical products; their reliability will influence results of rocket or missile launching, even lead to damage to staff and devices on the ground. Besides failure in engine system may influence the hitting accuracy and flight shot of missiles. Therefore high reliability is quite essential to astronautical products. There are quite a few literature doing research based on few failure test data to estimate valves’ reliability, thus this paper proposed a new method to estimate valves’ reliability, according to the corresponding tests of different failure modes, this paper takes advantage of tests data which acquired from temperature, vibration, and action tests to estimate reliability in every failure modes, then this paper has regarded these three kinds of tests as three stages in products’ process to integrate these results to acquire valves’ reliability. Through the comparison of results achieving from tests data and simulated data, the results have illustrated how to obtain valves’ reliability based on the few failure data with failure modes and prove that the results are effective and rational.

Keywords: censored data, temperature tests, valves, vibration tests

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Authors: Malgorzata Krysiak, Anna Wegrzyn, Maciej Garstka, Radoslaw Mazur

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Under constantly fluctuating environmental conditions, the thylakoid membrane protein network evolved the ability to dynamically respond to changing biotic and abiotic factors. One of the most important protective mechanism is rearrangement of the chlorophyll-protein (CP) complexes, induced by protein phosphorylation. In a temperate climate, low temperature is one of the abiotic stresses that heavily affect plant growth and productivity. The aim of this study was to determine the role of LHCII antenna complex phosphorylation in the dark-chilling response. The study included an experimental model based on dark-chilling at 4 °C of detached chilling sensitive (CS) runner bean (Phaseolus coccineus L.) and chilling tolerant (CT) garden pea (Pisum sativum L.) leaves. This model is well described in the literature as used for the analysis of chilling impact without any additional effects caused by light. We examined changes in thylakoid membrane protein phosphorylation, interactions between phosphorylated LHCII (P-LHCII) and CP complexes, and their impact on the dynamics of photosystem II (PSII) under dark-chilling conditions. Our results showed that the dark-chilling treatment of CS bean leaves induced a substantial increase of phosphorylation of LHCII proteins, as well as changes in CP complexes composition and their interaction with P-LHCII. The PSII photochemical efficiency measurements showed that in bean, PSII is overloaded with light energy, which is not compensated by CP complexes rearrangements. On the contrary, no significant changes in PSII photochemical efficiency, phosphorylation pattern and CP complexes interactions were observed in CT pea. In conclusion, our results indicate that different responses of the LHCII phosphorylation to chilling stress take place in CT and CS plants, and that kinetics of LHCII phosphorylation and interactions of P-LHCII with photosynthetic complexes may be crucial to chilling stress response. Acknowledgments: presented work was financed by the National Science Centre, Poland grant No.: 2016/23/D/NZ3/01276

Keywords: LHCII, phosphorylation, chilling stress, pea, runner bean

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Authors: Berat Krasniqi, Shpëtim Thaçi, Miribane Dërmaku-Sopjani, Sokol Abazi, Mentor Sopjani

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The Mediterranean native plant, Sideritis raeseri Boiss. & Heldr. (Lamiaceae), also known as "mountain tea," has a long history of use in traditional medicine. The effects of an ethanol extract of Sideritis raeseri (SR) on uterus smooth muscle activity are evaluated in this study, and the underlying mechanism is identified. S. raeseri extract (SRE) was made from air-dried components of the SR shoot system. At 37°C, the SRE (0.5-2 mg/mL) was tested on isolated rabbit uterus rings that were suspended in a Krebs solution-filled organ bath and bubbled with a mixture of 95% O₂ and 5% CO₂. The SRE alone relaxed the muscle contraction in a concentration-dependent manner in uterine rings in in vitro tests. SRE also decreased Ca²⁺-induced contractions in the uterus by a large amount when the uterus was depolarized with carbachol (CCh, 1µM), K⁺ (80 mM), or contracted by oxytocin (5 nM). The potential involvement of NO-dependent or independent cGMP mechanisms in the uterine actions of SR was investigated. For this purpose, L-NAME (NO synthase inhibitor, 100 M) or bradykinin (NO synthase stimulator, 100 nM), or indomethacin (cyclooxygenase inhibitor, 10µM) decreased the impact of SRE. These results suggest that NO-dependent signaling is involved in SRE's mediated uterine relaxant effect. Data suggests that SRE could be a powerful tocolytic agent that reduces uterine activity and could be used to treat a number of uterine conditions.

Keywords: Sideritis raeseri, uterus, alternative medicine, intracellular mechanisms

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

Procedia PDF Downloads 298

Authors: Grazia Disciglio, Annalisa Tarantino, Emanuele Tarantino

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The production system of Foggia province (Apulia, Southern Italy) is characterized by the presence of numerous agro-food industries whose activities include the processing of vegetables products that release large quantities of wastewater. The reuse in agriculture of these wastewaters offers the opportunity to reduce the costs of their disposal and minimizing their environmental impact. In addition, in this area, which suffers from water shortage, the use of agro-industrial wastewater is essential in the very intensive irrigation cropping systems. The present investigation was carried out in years 2009 and 2010 to monitor the physico-chemical and microbiological characteristics of the industrial wastewater (IWW) from the secondary treatment plant of the 'Industrial Area of Foggia'. The treatment plant released on average about 567,000 m3y-1 of IWW, which distribution was not uniform over the year. The monthly values were about 250,000 m3 from November to June and about 90,000 m3 from July to October. The obtained results revealed that IWW was characterized by low values of Total Suspended Solids (TSS), Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Electrical Conductivity (EC) and Sodium Absorption Rate (SAR). An occasional presence of heavy metal and high concentration of total phosphorus, total nitrogen, ammoniacal nitrogen and microbial organisms (Escherichia coli and Salmonella) were observed. Due to the presence of this pathogenic microorganisms and sometimes of heavy metals, which may raise sanitary and environmental problems in order to the possible irrigation reuse of this IWW, a tertiary treatment of wastewater based on filtration and disinfection in line are recommended. Researches on the reuse of treated IWW on crops (olive, artichoke, industrial tomatoes, fennel, lettuce etc.) did not show significant differences among the irrigated plots for most of the soil and yield characteristics.

Keywords: agroindustrial wastewater, irrigation, microbiological characteristic, physico-chemical characteristics

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Authors: Hamideh Nouri, Sattar Chavoshi Borujeni

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Grey infrastructure is an unavoidable part of urbanisation that is threatening the local microclimates. Sustainable urbanisation requires more green infrastructure in cities such as green roofs to minimise urbanisation impacts. The environmental, social and economic benefits of green roofs are widely deliberated. However, there is still a lack of assessment of the water management for green roofs. This paper aimed to assess the irrigation management of green roofs in a semi-arid region where blue water scarcity is one of the primary challenges in urban water management. To determine the appropriate water source and growing media for green roofs, an experiment was established at the University of South Australia, Australia. This study compared the performance of two growing media and three water sources on the drainage quality, medium weight and survival rate of potted Tussock grass (Poa labillardieral), an endemic plant to Australia and recommended for green roofs. Three irrigation sources were tap water, mixed of wastewater-stormwater, and rainwater. The growing media were natural sandy loam soil and Scoria - one of the most used commercial growing media for green roofs. The drainage quality of these media was tested by analysing leachate samples. Medium weight was measured before and after watering, and all pots were monitored for their survival rates. Results showed that although plant growing development was significantly higher in Scoria, the survival rate was lower. For all three water sources, EC and pH of the leachate were significantly lower from Scoria than the sandy loam soil. However, the mixed of wastewater-stormwater had the highest EC, and rainwater had the lowest EC. Results did not present a significant difference between pH of different water resources in the same media. Our experimental results found the scoria and rainwater as the best sources of medium and water for green roofs.

Keywords: green smart cities, urban water, green roofs, green walls, wastewater, stormwater

Procedia PDF Downloads 156

Authors: Zhen Peng, Baifeng Wu

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Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability

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Authors: Z. Nourmohammadi, F. Farahani, M. Shaker

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Aloe is an important commercial crop available in a wide range of species and varieties in international markets. The applications of this plant have been recorded in the ancient cultures of India, Egypt, Greece, Rome and China. Aloe has been used for centuries and is currently being actively studied for medicinal purposes. Aloe is propagated through lateral buds, which is slow, very expensive and low income practice. Nowadays, it has been cultured by in vitro propagation for rapid multiplication of plants, genetic improvement of crops, obtaining disease-free clones and for progressive valuable germplasm. The present study focused on the influence of different phytohormones on rapid in vitro propagation of Aloe plants. We also investigated the effect of gamma radiation on biochemical characters as well as genetic changes. Shoot tip of 2-3 cm were collected from offshoot of Aloe barbadensis and Aloe littoralis, and were inoculated with MS medium containing various concentrations of BA (0.5, 1, 2 mg/l), IAA (0.5, 1 mg/l). The best treatment for a highest shoot number and bud proliferation was MS medium containing 2 mg/l BAP and 0.5 mg/l IAA in A. barbadensis and A. littoralis. Maximum percentage of proliferated shoot buds (90% and 95%) from a single explant were obtained in MS medium after 4-5 weeks of the second and the first subcultures, respectively. Different genome sizes were also indicated among treatments and subcultures. The mixoploids identified in flow cytometery histograms in different treatments. The effect of gamma radiation on A. littoralis showed that by increasing the dose of gamma radiation, amounts of chlorophyll A, B, carotenoids, total protein content and superoxide dismutase were significantly increased compared to control plants. Genetic variation analysis also revealed significant genetic differences between control and gamma radiation treated regenerated plants by AMOVA test. Higher genetic heterozygocity was observed in radiation treated plants. Our findings may provide useful method for improving of Aloe plant proliferation with increasing of useful material such as antioxidant enzymes.

Keywords: aloe, antioxidant enzyme, micropropagation, gamma radiation, genetic variation

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Authors: Hiesik Kim, Yong-Beom Kim, Jaheon Gu

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to rate up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group (SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with a different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as open source hardware, gas sensor, and Bluetooth module and algorithm controlling transmission rate is demonstrated. Experiment controlling transmission rate also is progressed by developing Android application receiving measured data, and controlling this rate is available at the experiment result. It is important that in the future, improvement for communication algorithm be needed because a few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, IoT, transmission

Procedia PDF Downloads 273