Search results for: plant data

Authors: Abubakar Bello Usman, Alhassan Muhammad Gani, Kolo Ibrahim

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The use of botanical raw materials to produce pharmaceuticals, herbal remedies, teas, spirits, cosmetics, sweets, dietary supplements, special industrial compounds and crude materials constitute an important global resource in terms of healthcare and economy. In Nigeria and other developing countries, the indigenous knowledge on the uses of plants lies with the older generation and the traditional healers. However, these custodians are decreasing in number due to death and other unforeseen occurrences. An Ethno-botanical survey was carried out to obtain information on the ethno medical values of wide range of plants used by the people of Gombe State, North-Eastern Nigeria, in the practice of healing and cure of typhoid (enteric) fever. Oral interviews were conducted so as to consider those with low literacy level who are involved in the practice of traditional medicine and thirty four (34) informants availed themselves for the interview and were consulted. All relevant information obtained from the respondents was recorded. A recent and valid nomenclature, along with local names, family names, part of the plant(s) used, methods of preparation and administration and fifty four (54) plant species belonging to 27 families as well as 7 unidentified species that are commonly used by the people of the state in ethnomedical treatment of the ailment were tabulated. Those interviewed included traditional practitioners, local herb sellers, traditional rulers, hunters, farmers and patients. Specific questions were asked and information supplied by informants was promptly documented. Results showed that the people of Gombe State are knowledgeable on herbal medicine in the treatment of diseases and ailments. Furthermore, the aqueous leaf extracts of Senna siamea, the plant species with the highest PPK (percentage of people who have knowledge about the use of a species for treating typhoid fever) in this ethnobotanical survey, was tested for its activity against clinical isolates of Salmonella typhi using the agar well diffusion method. The aqueous extracts showed some activity (zones of inhibition 11, 9, 7.5, 3.5, 1.3 mm) at 2000, 1800, 1600, 1400, 1200 µg/ml concentrations respectively. Preliminary phytochemical studies of the aqueous leaf extracts of the plant revealed the presence of secondary metabolites such as alkaloids, saponins, tannins, flavonoids and cardiac glycosides. Though a large number of traditionally used plants for the treatment of enteric fever were identified, further scientific validation of the traditional claims of anti-typhoid properties is imperative. This would establish their candidature for any possible future research for active principles and the possible development of new cheaper and more effective anti-typhoid drugs, as well as in the conservation of this rich diversity of medicinal plants.

Keywords: antimicrobial activities, ethnobotany, gombe state, north-eastern Nigeria, phytochemical screening, senna siamea, typhoid fever

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Authors: Rafael Alvarenga, Hubert Herbaux, Laurent Linguet

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The uncertainty concerning the power production of intermittent renewable energy is one of the main barriers to the integration of such assets into the power grid. Efforts have thus been made to develop methods to quantify this uncertainty, allowing producers to ensure more reliable and profitable engagements related to their future power delivery. Even though a diversity of probabilistic approaches was proposed in the literature giving promising results, the added value of adopting such methods for scheduling intermittent power plants is still unclear. In this study, the profits obtained by a decision-making model used to optimally schedule an existing PV power plant connected to batteries are compared when the model is fed with deterministic and probabilistic forecasts generated with two of the most recent methods proposed in the literature. Moreover, deterministic forecasts with different accuracy levels were used in the experiments, testing the utility and the capability of probabilistic methods of modeling the progressively increasing uncertainty. Even though probabilistic approaches are unquestionably developed in the recent literature, the results obtained through a study case show that deterministic forecasts still provide the best performance if accurate, ensuring a gain of 14% on final profits compared to the average performance of probabilistic models conditioned to the same forecasts. When the accuracy of deterministic forecasts progressively decreases, probabilistic approaches start to become competitive options until they completely outperform deterministic forecasts when these are very inaccurate, generating 73% more profits in the case considered compared to the deterministic approach.

Keywords: PV power forecasting, uncertainty quantification, optimal scheduling, power systems

Procedia PDF Downloads 76

Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian Murray

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The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: interoperabilty, medical data exchange, health data standards, case study, Saudi Arabia

Procedia PDF Downloads 333

Authors: Pulcherie Matsodoum Nguemte, Adrien Wanko Ngnien, Guy Valerie Djumyom Wafo, Ives Magloire Kengne Noumsi, Pierre Francois Djocgoue

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The identification of plant species with the capacity to grow on hydrocarbon-polluted soils is an essential step for phytoremediation. In view of developing phytoremediation in Cameroon, floristic surveys have been conducted in 4 cities (Douala, Yaounde, Limbe, and Kribi). In each city, 13 hydrocarbon-polluted, as well as unpolluted sites (control), have been investigated using quadrat method. 106 species belonging to 76 genera and 30 families have been identified on hydrocarbon-polluted sites, unlike the control sites where floristic diversity was much higher (166 species contained in 125 genera and 50 families). Poaceae, Cyperaceae, Asteraceae and Amaranthaceae have higher taxonomic richness on polluted sites (16, 15,10 and 8 taxa, respectively). Shannon diversity index of the hydrocarbon-polluted sites (1.6 to 2.7 bits/ind.) were significantly lower than the control sites (2.7 to 3.2 bits/ind.). Based on a relative frequency > 10% and abundance > 7%, this study highlights more than ten plants predisposed to be effective in the cleaning-up attempts of soils contaminated by hydrocarbons. Based on the floristic indicators, 6 species (Eleusine indica (L.) Gaertn., Cynodon dactylon (L.) Pers., Alternanthera sessilis (L.) R. Br. ex DC †, Commelinpa benghalensis L., Cleome ciliata Schum. & Thonn. and Asystasia gangetica (L.) T. Anderson) were selected for a study to determine their capacity to remediate a soil contaminated with fuel oil (82.5 ml/ kg of soil). The experiments lasting 150 days takes into account three modalities - Tn: uncontaminated soils planted (6) To contaminated soils unplanted (3) and Tp: contaminated soil planted (18) – randomized arranged. 3 on 6 species (Eleusine indica, Cynodon dactylon, and Alternanthera sessilis) survived the climatic and soil conditions. E. indica presents a significantly higher growth rate for density and leaf area while C. dactylon had a significantly higher growth rate for stem size and leaf numbers. A. sessilis showed stunted growth and development throughout the experimental period. The species Eleusine indica (L.) Gaertn. and Cynodon dactylon (L.) Pers. can be qualified as polluo-tolerant plant species; polluo-tolerance being the ability of a species to survive and develop in the midst subject to extreme physical and chemical disturbances.

Keywords: Cameroon, cleaning-up, floristic surveys, phytoremediation

Procedia PDF Downloads 237

Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

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Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

Procedia PDF Downloads 398

Authors: Rafeza Begum, Mohammad Mokhlesur Rahman, Safikul Moula, Rafiqul Islam

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Potassium (K) is crucial for healthy soil and plant growth. However, K fertilization is either disregarded or poorly underutilized in Bangladesh agriculture, despite the great demand for crops. This could eventually result in a significant depletion of the soil's potassium reserves, irreversible alteration of the minerals that contain potassium, and detrimental effects on crop productivity. Soil K mining in Bangladesh is a worrying problem, and we need to evaluate it thoroughly and find remedies. A pot culture experiment was conducted in the greenhouse of Bangladesh Institute of Nuclear Agriculture (BINA) using eleven soil series of Bangladesh in order to see the depletion behaviour of potassium (K) by continuous cropping using rice (var. Iratom-24) as the test crop. The soil series were Ranishankhail, Kaonia. Sonatala, Silmondi, Gopalpur, Ishurdi, Sara, Kongsha, Nunni, Lauta and Amnura on which four successive rice plants (45 days duration) were raised with (100 ppm K) or without addition of potassium. Nitrogen, phosphorus, sulfur and zinc were applied as basal to all pots. Potassium application resulted in higher dry matter yield, increased K concentration and uptake in all the soils compared with no K treatment; which gradually decreased in the subsequent harvests. Furthermore, plant takes up K not only from exchangeable pool but also from non-exchangeable sites and a minimum replenishment of K from the soil reserve was observed. Continuous cropping has resulted in the depletion of available K of the soil. The result indicated that in order to sustain higher crop yield under intensive cultivation, the addition of potash fertilizer is necessary.

Keywords: potassium, exchangeable pool, depletion behavior., Soil series

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Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

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In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

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Authors: Anusha Konduru, Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

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Mobile applications are increasing in a significant amount, each to address the requirements of many users. However, the quick developments and enhancements are resulting in many underlying defects. Android apps create and handle a large variety of 'instance' data that has to persist across runs, such as the current navigation route, workout results, antivirus settings, or game state. Due to the nature of Android, an app can be paused, sent into the background, or killed at any time. If the instance data is not saved and restored between runs, in addition to data loss, partially-saved or corrupted data can crash the app upon resume or restart. However, it is difficult for the programmer to manually test this issue for all the activities. This results in the issue of data loss that the data entered by the user are not saved when there is any interruption. This issue can degrade user experience because the user needs to reenter the information each time there is an interruption. Automated testing to detect such data loss is important to improve the user experience. This research proposes a tool, DroidDL, a data loss detector for Android, which detects the instance data loss from a given android application. We have tested 395 applications and found 12 applications with the issue of data loss. This approach is proved highly accurate and reliable to find the apps with this defect, which can be used by android developers to avoid such errors.

Keywords: Android, automated testing, activity, data loss

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Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

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FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: compression properties, uncertainty, uncertain time series, mining technique, weather prediction

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Authors: Muccifora S., Rinallo C., Bellani L.

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Calcium (Ca²+) is an element essential to the plant being involved in plant growth and development. At high concentrations, it is toxic and can influence every stage, process and cellular activity of plant life. Given its toxicity, cells implement mechanisms to compartmentalize calcium in a vacuole, endoplasmic reticulum, mitochondria, plastids and cell wall. One of the most effective mechanisms to reduce the excess of calcium, thus avoiding cellular damage, is its complexation with oxalic acid to form calcium oxalate crystals that are no longer osmotically or physiologically active. However, the sequestered calcium can be mobilized when the plant needs it. Calcium crystals can be accumulated in the vacuole of specialized sink-cells called idioblasts, with different crystalline forms (druse, raphyde and styloid) of diverse physiological meanings. Actinidia deliciosa cv. Hayward presents raphydes and styloid localized in idioblasts in cells of photosynthetic and non-photosynthetic tissues. The purpose of this work was to understand if there is a relationship between the age of Actinidia leaves and the presence, distribution, dimension and shape of oxalate crystals by means of light, fluorescent, polarized and transmission electron microscopy. Three vines from female plants were chosen at the beginning of the season and used throughout the study. The leaves with petioles were collected at various stages of development from the bottom to the shoot of the plants monthly from April to July. The samples were taken in corresponding areas of the central and lateral parts of the leaves and of the basal portion of the petiole. The results showed that in the leaves, the number of raphyde idioblasts decreased with the progress of the growing season, while the styloid idioblasts increased progressively, becoming very numerous in the upper nodes of July. In June and in July samples, in the vacuoles of the highest nodes, a portion regular in shape strongly stained with rubeanic acid was present. Moreover, the chlortetracycline (CTC) staining for localization of free calcium marked the wall of the idioblasts and the wall of the cells near vascular bundles. In April petiole samples, moving towards the youngest nodes, the raphydes idioblast decreased in number and in the length of the single raphydes. Besides, crystals stained with rubeanic acid appeared in the vacuoles of some cells. In June samples, numerous raphyde idioblasts oriented parallel to vascular bundles were evident. Under the electron microscope, numerous idioblasts presented not homogeneous electrondense aggregates of material, in which a few crystals (styloids) in the form of regular holes were scattered. In July samples, an increase in the number of styloid idioblasts in the youngest nodes and little masses stained with CTC near styloids were observed. Peculiar cells stained with rubeanic acid were detected and hypothesized to be involved in the formation of the idioblasts. In conclusion, in Actinidia leaves and petioles, it seems to confirm the hypothesis that the formation of styloid idioblasts can be correlated to increasing calcium levels in growing tissues.

Keywords: calcium oxalate crystals, actinidia deliciosa, light and electron microscopy, idioblasts

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Thangavelu Muthukumar, Thotapalli Parvathaleswara Sastry

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Collagen is the most abundantly available connective tissue protein, which is being used as a biomaterial for various biomedical applications. Presently, fish wastes are disposed improperly which is causing serious environmental pollution resulting in offensive odour. Fish scales are promising source of Type I collagen. Medicinal plants have been used since time immemorial for treatment of various ailments of skin and dermatological disorders especially cuts, wounds, and burns. Developing biomaterials from the natural sources which are having wound healing properties within the search of a common man is the need of hour, particularly in developing and third world countries. With these objectives in view we have developed a wound dressing material containing fish scale collagen (FSC) incorporated with Macrotyloma uniflorum plant extract (PE). The wound dressing composite was characterized for its physiochemical properties using conventional methods. SEM image revealed that the composite has fibrous and porous surface which helps in transportation of oxygen as well as absorbing wound fluids. The biomaterial has shown 95% biocompatibility with required mechanical strength and has exhibited antimicrobial properties. This biomaterial has been used as a wound dressing material in experimental wounds of rats. The healing pattern was evaluated by macroscopic observations, panimetric studies, biochemical, histopathological observations. The results showed faster healing pattern in the wounds treated with CSPE compared to the other composites used in this study and untreated control. These experiments clearly suggest that CSPE can be used as wound/burn dressing materials.

Keywords: collagen, wound dressing, Macrotyloma uniflorum, burn dressing

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Authors: Murat Yazici

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Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

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Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Noel Dogonyara

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This paper describes the problem of building secure computational services for encrypted information in the Cloud. Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy or confidentiality, availability and integrity of the data and user’s security. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory that is derivable from abstract algebra which can easily be integrated and leveraged in the Cloud computing interface with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based on cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, Fully Homomorphic Encryption Scheme

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Authors: Mustapha Saidu, Bilyaminu Mohammed

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The study was conducted in Udubo Grazing Reserve between July 2019 and October 2019 to assess forage utilization for pasture-based livestock production in reserve. The grazing land was cross-divided into grids, where 15 coordinates were selected as the sample points. Grids of one-kilometer interval were made. The grids were systematically selected 1 grid after 7 grids. 1 × 1-meter quadrat was made at the coordinate of the selected grids for measurement, estimation, and sample collection. The results of the study indicated that Zornia glochidiatah has the highest percent of species composition (42%), while Mitracarpus hirtus has the lowest percent (0.1%). Urochloa mosambicensis has 48 percent of height removed and 27 percent used by weight, Zornia glochidiata 60 percent of height removed and 57 percent used by weight, Alysicapus veginalis has 55 percent of height removed, and 40 percent used by weight, and Cenchrus biflorus has 40 percent of height removed and 28 percent used by weight. The target is 50 percent utilization of forage by weight during a grazing period as well as at the end of the grazing season. The study found that Orochloa mosambicensis, Alysicarpus veginalis, and Cenchrus biflorus had lower percent by weight which is normal, while Zornia glochidiata had a higher percent by weight which is an indication of danger. The study recommends that the identification of key plant species in pasture and rangeland is critical to implementing a successful grazing management plan. There should be collective action and promotion of historically generated grazing knowledge through public and private advocacies.

Keywords: forage, grazing reserve, live stock, pasture, plant species

Procedia PDF Downloads 80

Authors: Mohammad Abdollahi

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Tomato (Lycopersicon esculentum Mill.) is one of the most popular, widely grown and the second most important vegetable crop, after potatoes. Nematodes have been identified as one of the major pests affecting tomato production throughout the world. The most destructive nematodes are the genus Meloidogyne. Most widespread and devastating species of this genus are M. incognita, M. javanica, and M. arenaria. These species can cause complete crop loss under adverse growing conditions. There are several potential methods for management of the root knot nematodes. Although the chemicals are widely used against the phytonematodes, because of hazardous effects of these compounds on non-target organisms and on the environment, there is a need to develop other control strategies. Nowadays, non-chemical measures are widely used to control the plant parasitic nematodes. Biocontrol of phytonematodes is an important method among environment-friendly measures of nematode management. There are some soil-inhabiting fungi that have biocontrol potential on phytonematodes, which can be used in nematode management program. The fungus Metarhizium anisopliae, originally is an entomopathogenic bioagent. Biocontrol potential of this fungus on some phytonematodes has been reported earlier. Recently, use of organic soil amendments as well as the use of bioagents is under special attention in sustainable agriculture. This research aimed to reduce the pesticide use in control of root-knot nematode, Meloidogyne javanica in tomato. The effects of M. anisopliae IMI 330189 and different levels of oak tree debris on M. javanica were determined. The combination effect of the fungus as well as the different rates of soil amendments was determined. Pots were filled with steam pasteurized soil mixture and the six leaf tomato seedlings were inoculated with 3000 second stage larvae of M. javanica/kg of soil. After eight weeks, plant growth parameters and nematode reproduction factors were compared. Based on the results of our experiment, combination of M. anisopliae IMI 330189 and oak debris caused more than 90% reduction in reproduction factor of nematode, at the rates of 100 and 150 g/kg soil (P ≤ 0.05). As compared to control, the reduction in number of galls was 76%. It was 86% for nematode reproduction factor, showing the significance of combined effect of both tested agents. Our results showed that plant debris can increase the biological activity of the tested bioagent. It was also proved that there was no adverse effect of oak debris, which potentially has antimicrobial activity, on antagonistic power of applied bioagent.

Keywords: biological control, nematode management, organic soil, Quercus branti, root knot nematode, soil amendment

Procedia PDF Downloads 169

Authors: O. U. Nwosu, C. O. Osuagwu, N. Nnawugwu, C. T. Amanze

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Phytoremediation is a green and sustainable approach to decontaminate and restore contaminated sites while maintaining the biological activity and physical structure of soils. A pot experiment was conducted for a period of 70 days to evaluate the remediation potentials of Vetiveira zizanioides, Heianthus annuus L., Zea mays, and Glycine max in concurrent removal of anthracene and Pb in co-contaminated soil. Sandy loam soils were polluted with Pb chloride salt and anthracene at three different levels (50mg/kg of Pb, 100mg/kg of Pb, and 100mg/kg of Pb+100mg/kg of anthracene) and laid out in a completely randomized design with three replicates. Shoot dry matter weight was significantly reduced (p≤0.05) in comparison to control treatments by 33%, 32%, 40%, and 6.7% when exposed to 100mg kg⁻¹ of Pb, respectively in G.max, H.annuus, Z.mays, and vetiver. There was 42%, 41%, 48%, and 7.1% growth inhibition of shoot dry matter weight of G.max, H.annuus, Z.mays, and vetiver relative to control treatments when 100 mg Pb kg⁻¹ was mixed with 100 mgkg⁻¹ anthracene. Root and shoot metal concentration in G.max, H.annuus, Z.mays, and vetiver increased with increasing concentration of Pb. Translocation factor (TF < 1) obtained for G.max, Z.mays, and vetiver suggests that these plant species predominantly retain Pb in the root portion, while the TF value (TF≥1) obtained for H.annuus suggests that it predominantly retains Pb in the shoot portion. The extractable anthracene decreased significantly (p ≤ 0.05) in soil planted with G.max, H.annuus, Z.mays, and vetiver, as well as in pots without plants. This accounted for 53% to 71% of anthracene dissipation in planted soil and 40% dissipation in unplanted soil. This result suggested that the plant species used are a promising candidate for phytoremediation.

Keywords: phytoremediation, heavy metals, polyaromatic hydrocarbon, co-contaminated soil

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Authors: Sarisa Pinkham, Kanyarat Bussaban

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The research aims to approximate the amount of daily rainfall by using a pixel value data approach. The daily rainfall maps from the Thailand Meteorological Department in period of time from January to December 2013 were the data used in this study. The results showed that this approach can approximate the amount of daily rainfall with RMSE=3.343.

Keywords: daily rainfall, image processing, approximation, pixel value data

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Authors: Pawitchaya Srijaiwong, Surin Khomfoi

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There are several solutions to supply electricity to an island in Thailand such as diesel generation, submarine power cable, and renewable energy power generation. However, each alternative has its own limitation like fuel and pollution of diesel generation, submarine power cable length resulting in loss of cable and cost of investment, and potential of renewable energy in the local area. This paper shows microgrid system which is a new alternative for power supply to an island. It integrates local power plant from renewable energy, energy storage system, and microgrid controller. The suitable renewable energy power generation on an island is selected from geographic location and potential evaluation. Thus, photovoltaic system and hydro power plant are taken into account. The capacity of energy storage system is also estimated by transient stability study in order to supply electricity demand sufficiently under normal condition. Microgrid controller plays an important role in conducting, communicating and operating for both sources and loads on an island so that its functions are discussed in this study. The conceptual design of microgrid operation is investigated in order to analyze the reliability and power quality. The result of this study shows that microgrid is able to operate in parallel with the main grid and in case of islanding. It is applicable for electricity supply to an island and a remote area. The advantages of operating microgrid on an island include the technical aspect like improving reliability and quality of power system and social aspects like outage cost saving and CO₂ reduction.

Keywords: energy storage, islanding, microgrid, renewable energy

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Authors: E. Kayitesi, S. Moyo, V. Mavumengwana

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Cleome gynandra (spider plant) is an African green leafy vegetable categorized as an indigenous, underutilized and has been reported to contain essential phenolic compounds. Phenolic compounds play a significant role in human diets due to their proposed health benefits. These compounds however may be affected by different processing methods such as cooking and drying. Cleome gynandra was subjected to boiling, steam blanching, and drying processes and analysed for Total Phenolic Content (TPC), Total Flavonoid Content (TFC), antioxidant activity and flavonoid composition. Cooking and drying significantly (p < 0.05) increased the levels of phenolic compounds and antioxidant activity of the vegetable. The boiled sample filtrate exhibited the lowest TPC followed by the raw sample while the steamed sample depicted the highest TPC levels. Antioxidant activity results showed that steamed sample showed the highest DPPH, FRAP and ABTS with mean values of 499.38 ± 2.44, 578.68 ± 5.19, and 214.39 ± 12.33 μM Trolox Equivalent/g respectively. An increase in quercetin-3-rutinoside, quercetin-rhamnoside and kaempferol-3-rutinoside occurred after all the cooking and drying methods employed. Cooking and drying exerted positive effects on the vegetable’s phenolic content, antioxidant activity as a whole, but with varied effects on the individual flavonoid molecules. The results obtained help in defining the importance of African green leafy vegetable and resultant processed products as functional foods and their potential to exert health promoting properties.

Keywords: Cleome gynandra, phenolic compounds, cooking, drying, health promoting properties

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

Procedia PDF Downloads 503

Authors: Jaya Mathew

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Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

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Authors: Sven Gehrke, Johannes Ruhland

Abstract:

Data is the oil of our time, without them progress would come to a hold [1]. On the other hand, the mistrust of data mining is increasing [2]. The paper at hand shows different aspects of the concept of trust and describes the information asymmetry of the typical stakeholders of a data mining project using the CRISP-DM phase model. Based on the identified influencing factors in relation to trust, problematic aspects of the current approach are verified using various interviews with the stakeholders. The results of the interviews confirm the theoretically identified weak points of the phase model with regard to trust and show potential research areas.

Keywords: trust, data mining, CRISP DM, stakeholder management

Procedia PDF Downloads 90

Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha

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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.

Keywords: big data, two-hop transmission, physical layer wireless security, cooperative jamming, energy balance

Procedia PDF Downloads 482

Authors: Piyush V. Surjagade, Jiamei Deng, Paul Doney, S. R. Shimjith, A. John Arul

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In sophisticated and complex systems such as nuclear power plants, maintaining the system's stability in the presence of uncertainties and disturbances and obtaining a fast dynamic response are the most challenging problems. Thus, to ensure the satisfactory and safe operation of nuclear power plants, this work proposes a new fast, robust optimal switching control strategy for pressurized water reactor-type nuclear power plants. The proposed control strategy guarantees a substantial degree of robustness, fast dynamic response over the entire operational envelope, and optimal performance during the nominal operation of the plant. To improve the robustness, obtain a fast dynamic response, and make the system optimal, a bank of controllers is designed. Various controllers, like a baseline proportional-integral-derivative controller, an optimal linear quadratic Gaussian controller, and a robust adaptive L1 controller, are designed to perform distinct tasks in a specific situation. At any instant of time, the most suitable controller from the bank of controllers is selected using the switching logic unit that designates the controller by monitoring the health of the nuclear power plant or transients. The proposed switching control strategy optimizes the overall performance and increases operational safety and efficiency. Simulation studies have been performed considering various uncertainties and disturbances that demonstrate the applicability and effectiveness of the proposed switching control strategy over some conventional control techniques.

Keywords: switching control, robust control, optimal control, nuclear power control

Procedia PDF Downloads 121

Authors: I. Hilia, C. Hange, F. Hakala, M. Matheus, C. Jansen, J. Hidinwa, O. Awofolu

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The article reports on the occurrences, level, and mobility of selected trace metals in environmental samples. The conceptual basis was to examine the possible influence of anthropogenic activities and the impact on human and environmental health. Environmental samples (soil, plant and lower animal) were randomly collected from stratified study/sampling areas, preserved and pre-treated before analysis. Mineral acid digestion procedure was employed for the isolation of metallic contents in samples, and elemental qualitative and quantitative analysis was by ICP-OES. Analytical protocol was validated through the quality assurance process and was found acceptable with quantitative metallic recoveries in the range of 85-90%; hence considered applicable for the analyses of environmental samples. The mean concentration of analysed metals in soil samples ranged from 53.2- 2532.8 mg/kg (Cu); 59.5- 2020.1 mg/kg (Zn); 1.80 – 21.26 mg/kg (Cd) and 19.6- 140.9 mg/kg (Pb). The mean level in grass samples ranged from 9.33 – 38.63 mg/kg (Cu); 64.20-105.18 mg/kg (Zn); 0.28–0.73 mg/kg (Cd) and 0.53 -16.26 mg/kg (Pb) while the mean level in lower animal sample (beetle) varied from 9.6 - 105.3 mg/kg (Cu); 134.1-297.2 mg/kg (Zn); 0.63 – 3.78 (Cd) and 8.0 – 29.1 mg/kg (Pb) across sample collection points (SCPs) 1-4 respectively. Metallic transfer factors (TFs) were in the order Zn >Cd > Cu > Pb with metal Pollution Indices (MPIs) in the order SCP1 > SCP2 > SCP3 > SCP4. About 60-70 % of analysed metals were above the maximum allowable limits (MALs) in soil and plant samples. Results obtained revealed the general prevalence of analysed metals at all sampled sites with indication of metallic mobility across the food chain which portrayed dire consequences for environmental and human health. Systematic environmental remediation and pollution abatement strategies are recommended.

Keywords: trace metals, pollution, human health, Incidences, ICP-OES

Procedia PDF Downloads 156

Authors: Romeo Botes, Imelda Smit

Abstract:

In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

Procedia PDF Downloads 237