Search results for: plant data

Authors: Akshay Agrawal, Anand K. Srivastava

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The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

Procedia PDF Downloads 370

Authors: Hiesik Kim, YongBeum Kim

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed 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 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 speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

Procedia PDF Downloads 479

Authors: Sreejith Gopinath, Aspen Olmsted

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This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

Procedia PDF Downloads 128

Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

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Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

Procedia PDF Downloads 163

Authors: Michael Gidey Gebru

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Most DEA models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp DEA into DEA with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the DEA model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units’ efficiency. Finally, the developed DEA model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

Procedia PDF Downloads 43

Authors: M. Achemo, O. Saito

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Jefoure land use system is one of the traditional landscape human settlement patterns, and it is a cultural design and peculiar art of the people of Gurage in Ethiopia via which houses and trees flank roads left and right. Assessment of the multiple benefits of the traditional road that benefit society and development could enhance the understanding of the land use planners and decision makers to pay attention while planning and managing the land use system. Recent trend shows that the Jefoure land use is on the threshold of change as a result of flourishing road networks, overgrazing, and agricultural expansion. This study aimed to evaluate the multiple ecosystem services provided by the Jefoure land use system after characterization of the socio-ecological landscape. Information was compiled from existing data sources such as ordnance survey maps, aerial photographs, recent high resolution satellite imageries, designated questionnaires and interviews, and local authority contacts. The result generated scientific data on the characteristics, ecosystem services provision, and drivers of changes. The cultural landscape has novel characteristics and providing multiple ecosystem services to the community for long period of time. It is serving as road for humans, livestock and vehicles, habitat for plant species, regulating local temperature, climate, runoff and infiltration, and place for meeting, conducting religious and spiritual activities, holding social events such as marriage and mourning, playing station for children and court for football and other traditional games. As a result of its aesthetic quality and scenic beauty, it is considered as recreational place for improving mental and physical health. The study draws relevant land use planning and management solution in the improvement of socio-ecological resilience in the Jefoure land use system. The study suggests the landscape needs to be registrar as heritage site for recognizing the wisdom of the community and enhancing the conservation mechanisms.

Keywords: cultural landscape, ecosystem services, Gurage, Jefoure

Procedia PDF Downloads 117

Authors: Burmansyah Muhammad, Supriyoto Supriyoto

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Crop yield, quality and food safety are three important components that all estate and food crops must put into consideration to lifting the economic value. These measurements should be evaluated because marketplace demand is simultaneously changing and farmers must adapt quickly to remain competitive. The increase in economic value could be done by producing high quality product that aligns with harvest collector preferences. The purpose of this study is to examine the causal effects of value added farming in agriculture economic aspects towards crop yield, quality and food security. This research is using descriptive survey research by employing data from small-scale cocoa farmers listed to off-taker company, located on Sulawesi area of Indonesia. The questionnaire was obtained from 650 cocoa farmers, selected randomly. Major findings of the study indicate that 78% of respondents agree that agriculture inputs have positive effect on crop yield, quality and food safety. The study recommended that cocoa stakeholders should ensure access to agriculture inputs in first priority and then followed by ensuring access to cocoa supply chain trader and micro-financing. Value Added Farming refers to lifting the economic value of a commodity through particular intervention. Regarding access to agriculture inputs, one of significant intervention is fertilization and plant nutrition management, both organic and inorganic fertilizer. Small-scale cocoa farmers can get access to fertilizer intervention through establishment of demo farm. Ordinary demo farm needs large area, selective requirements, lots of field resources and centralization impact. On the contrary, satellite demo farm is developing to wide-spread the impact of agriculture economic aspects and also the involvement in number of farmers. In Sulawesi Project, we develop leveling strata of small-scale demo farm with group of farmers and local cooperative. With this methodology, all of listed small-scale farmers can get access to agriculture input, micro-financing and how to deliver quality output. PT Pupuk Kaltim is member firm of holding company PT Pupuk Indonesia, private company belongs to the government of Indonesia. The company listed as Indonesia's largest producer of urea fertilizers, besides ammonia, Compound Fertilizer (NPK) and biological fertilizers. To achieve strategic objectives, the company has distinguished award such as SNI Platinum, SGS Award IFA Protect and Sustain Stewardship and Gold Rank of Environment Friendly Company. This achievement has become the strategic foundation for our company to energize value added farming in sustaining food security program. Moreover, to ensure cocoa sustainability farming the company has developed partnership with international companies and Non-Government Organization (NGO).

Keywords: fertilizer and plant nutrition management, good agriculture practices, agriculture economic aspects, value-added farming

Procedia PDF Downloads 93

Authors: Denise Hexom, Judith Menoher

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Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

Procedia PDF Downloads 379

Authors: Yaeji Lim, Hee-Seok Oh

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The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

Procedia PDF Downloads 383

Authors: Shiva Mardani, Mehdi Nasr-Esfahani, Majid Olia, Hamid Molahosseini, Hamed Hassanzadeh Khankahdani

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Plant-parasitic nematodes cause serious diseases on plants and effectively reduce food production in quality and quantity worldwide, with at least 17 nematode species in the three important and major genera, including Meloidogyne, Heterodera, and Pratylenchus. Root-knot nematodes (RKN), Meloidogyne spp. with the dominant species, Meloidogynejavanica, are considered as the important plant pathogens of agricultural products globally. The hosts range can be vegetables, bedding plants, grasses, shrubs, numerous weeds, and trees, including forests. In this study, chemical management was carried out on RKN, M. javanica, to investigate the efficacy of Iranian Abamectin insecticide product [acaricide Abamectin (Vermectin® 2% EC, Gyah Corp., Iran)] verses imported normal Abamectin available in the Iran markets [acaricide Abamectin (Vermectin® 1.8% EC, Cropstar Chemical Industry Co., Ltd.)] each of which at the rate of 8 L./ha, on Tomatoes, Solanumlycopersicum L., (No. 29-41, Dutch company Siemens) as a test plant, and the controls (infested to RKN and without any chemical pesticides treatments); and (sterile soil without any RKN and chemical pesticides treatments) at the greenhouse in Isfahan, Iran. The trails were repeated thrice. The results indicated a highly significant reduction in RKN population and an increase in biomass parameters at 1% level of significance, respectively. Relatively similar results were obtained in all the three experiments conducted on tomato root-knot nematodes. The treatments of Gyah-Abamectin (51.6%) and external Abamectin (40.4%) had the highest to least effect on reducing the number of larvae in the soil compared to the infected controls, respectively. Gyah-Abamectin by 44.1% and then external one by 31.9% had the highest effect on reducing the number of larvae and eggs in the root and 31.4% and 24.1% reduction in the number of galls compared to the infected controls, respectively. Based on priority, Gyah-Abamectin (47.4 % ) and external Abamectin (31.1 %) treatments had the highest effect on reducing the number of egg- masses in the root compared to the infected controls, with no significant difference between Gyah-Abamectin and external Abamectin. The highest reproduction of larvae and egg in the root was observed in the infected controls (75.5%) and the lowest in the healthy controls (0.0%). The highest reduction in the larval and egg reproduction in the roots compared to the infected controls was observed in Gyah-Abamectin and the lowest in the external one. Based on preference, Gyah-Abamectin (37.6%) and external Abamectin (26.9%) had the highest effect on the reduction of the larvae and egg reproduction in the root compared to the infected controls, respectively. Regarding growth parameters factors, the lowest stem length was observed in external Abamectin (51.9 cm), with nosignificantly different from Gyah-Abamectin and healthy controls. The highest root fresh weight was recorded in the infected controls (19.81 gr.) and the lowest in the healthy ones (9.81 gr.); the highest root length in the healthy controls (22.4 cm), and the lowest in the infected controls and external Abamectin (12.6 and 11.9 cm), respectively. Conclusively, the results of these three tests on tomato plants revealed that Gyah-Abamectin 2% compared to external Abamectin 1.8% is competitive in the chemical management of the root nematodes of these types of products and is a suitable alternative in this regard.

Keywords: solanum lycopersicum, vermectin, biomass, tomato

Procedia PDF Downloads 87

Authors: Danielle C. B. Honorato, Rafael H. Carvalho, Adriana L. Soares, Ana Paula F. R. L. Bracarense, Paulo D. Guarnieri, Massami Shimokomaki, Elza I. Ida

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Over the past decade, the Brazilian production of turkey meat increased by more than 50%, indicating that the turkey meat is considered a great potential for the Brazilian economy contributing to the growth of agribusiness at the marketing international scenario. However, significant color changes may occur during its processing leading to the pale, soft and exudative (PSE) appearance on the surface of breast meat due to the low water holding capacity (WHC). Changes in PSE meat functional properties occur due to the myofibrils proteins denaturation caused by a rapid postmortem glycolysis resulting in a rapid pH decline while the carcass temperature is still warm. The aim of this study was to analyze the physical, chemical and histological characteristics of PSE turkey meat obtained from a Brazilian commercial processing plant. The turkey breasts samples were collected (n=64) at the processing line and classified as PSE at L* ≥ 53 value. The pH was also analyzed after L* measurement. In sequence, PSE meat samples were evaluated for WHC, cooking loss (CL), shear force (SF), myofibril fragmentation index (MFI), protein denaturation (PD) and histological evaluation. The abnormal color samples presented lower pH values, 16% lower fiber diameter, 11% lower SF and 2% lower WHC than those classified as normal. The CL, PD and MFI were, respectively, 9%, 18% and 4% higher in PSE samples. The Pearson correlation between the L* values and CL, PD and MFI was positive, while that SF and pH values presented negative correlation. Under light microscopy, a shrinking of PSE muscle cell diameter was approximately 16% shorter in relation to normal samples and an extracellular enlargement of endomysium and perimysium sheaths as the consequence of higher water contents lost as observed previously by lower WHC values. Thus, the results showed that PSE turkey breast meat presented significant changes in their physical, chemical and histological characteristics that may impair its functional properties.

Keywords: functional properties, histological evaluation, meat quality, PSE

Procedia PDF Downloads 451

Authors: Lazlo Fauth, Andreas Ligocki

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For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper, three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester, and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

Keywords: predictive maintenance, condition monitoring, forest harvesting, forest engineering, oil data, hydraulic data

Procedia PDF Downloads 132

Authors: Federico Pittino, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

Procedia PDF Downloads 118

Authors: H. Y. Jung, Ju H. Park, S. M. Lee

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A sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The sector bounded nonlinear systems, which have a feedback connection with a linear dynamical system and nonlinearity satisfying certain sector type constraints. Also, the sampled-data control scheme is very useful since it is possible to handle digital controller and increasing research efforts have been devoted to sampled-data control systems with the development of modern high-speed computers. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: sampled-data control, fuel cell, linear matrix inequalities, nonlinear control

Procedia PDF Downloads 562

Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

Procedia PDF Downloads 67

Authors: Guo Wenyu, Qu Youli

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A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA

Procedia PDF Downloads 247

Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

Procedia PDF Downloads 83

Authors: Fernando Vega, Esmeralda Portillo, Sara Camino, Benito Navarrete, Elena Montavez

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The European Union aims at strongly reducing their CO₂ emissions from energy and industrial sector by 2030. The energy sector contributes with more than two-thirds of the CO₂ emission share derived from anthropogenic activities. Although efforts are mainly focused on the use of renewables by energy production sector, carbon capture and storage (CCS) remains as a frontline option to reduce CO₂ emissions from industrial process, particularly from fossil-fuel power plants and cement production. Among the most feasible and near-to-market CCS technologies, namely post-combustion and oxy-combustion, partial oxy-combustion is a novel concept that can potentially reduce the overall energy requirements of the CO₂ capture process. This technology consists in the use of higher oxygen content in the oxidizer that should increase the CO₂ concentration of the flue gas once the fuel is burnt. The CO₂ is then separated from the flue gas downstream by means of a conventional CO₂ chemical absorption process. The production of a higher CO₂ concentrated flue gas should enhance the CO₂ absorption into the solvent, leading to further reductions of the CO₂ separation performance in terms of solvent flow-rate, equipment size, and energy penalty related to the solvent regeneration. This work evaluates a portfolio of CCS technologies applied to fossil-fuel power plants. For this purpose, an economic evaluation methodology was developed in detail to determine the main economical parameters for CO₂ emission removal such as the levelized cost of electricity (LCOE) and the CO₂ captured and avoided costs. ASPEN Plus™ software was used to simulate the main units of power plant and solve the energy and mass balance. Capital and investment costs were determined from the purchased cost of equipment, also engineering costs and project and process contingencies. The annual capital cost and operating and maintenance costs were later obtained. A complete energy balance was performed to determine the net power produced in each case. The baseline case consists of a supercritical 500 MWe coal-fired power plant using anthracite as a fuel without any CO₂ capture system. Four cases were proposed: conventional post-combustion capture, oxy-combustion and partial oxy-combustion using two levels of oxygen-enriched air (40%v/v and 75%v/v). CO₂ chemical absorption process using monoethanolamine (MEA) was used as a CO₂ separation process whereas the O₂ requirement was achieved using a conventional air separation unit (ASU) based on Linde's cryogenic process. Results showed a reduction of 15% of the total investment cost of the CO₂ separation process when partial oxy-combustion was used. Oxygen-enriched air production also reduced almost half the investment costs required for ASU in comparison with oxy-combustion cases. Partial oxy-combustion has a significant impact on the performance of both CO₂ separation and O₂ production technologies, and it can lead to further energy reductions using new developments on both CO₂ and O₂ separation processes.

Keywords: carbon capture, cost methodology, economic evaluation, partial oxy-combustion

Procedia PDF Downloads 140

Authors: Wanjiku Karanja

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Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 117

Authors: Adel A. Ghoneim

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Desalination using solar energy is an interesting option specifically at regions with abundant solar radiation since such areas normally have scarcity of clean water resources. Desalination is the procedure of eliminating dissolved minerals from seawater or brackish water to generate fresh water. In this work, a simulation program is developed to determine the performance of reverse osmosis (RO) water desalination plant powered by high concentrated photovoltaic (HCPV) panels in Kuwait climate conditions. The objective of such a photovoltaic thermal system is to accomplish a double output, i.e., co-generation of both electricity and fresh water that is applicable for rural regions with high solar irradiation. The suggested plan enables to design an RO plant that does not depend on costly batteries or additional land and significantly reduce the government costs to subsidize the water generation cost. Typical weather conditions for Kuwait is employed as input to the simulation program. The simulation program is utilized to optimize the system efficiency as well as the distillate water production. The areas and slopes of HCPV modules are varied to attain maximum yearly power production. Maximum yearly distillate production and HCPV energy generation are found to correspond to HCPV facing south with tilt of 27° (Kuwait latitude-3°). The power needed to produce 1 l of clean drinking water ranged from 2 to 8 kW h/m³, based on the salinity of the feed water and the system operating conditions. Moreover, adapting HCPV systems achieve an avoided greenhouse gases emission by about 1128 ton CO₂ annually. Present outcomes certainly illustrate environmental advantages of water desalination system powered by high concentrated photovoltaic systems in Kuwait climate conditions.

Keywords: desalination, high concentrated photovoltaic systems, reverse osmosis, solar radiation

Procedia PDF Downloads 137

Authors: Abdelmoniem A. Attaelmanan, Ahmed A. H. Siddig

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This study was conducted in light of continual global climate changes that projected increasing aridity, changes in soil fertility, and pollution. Plant growth and development largely depend on the combination of availing water and nutrients in the soil. Changes in the climate and atmospheric chemistry can cause serious effects on these growth factors. Plant carbon (C), nitrogen (N), and hydrogen (H) play a fundamental role in the maintenance of ecosystem structure and function. Hashab (Acacia senegal), which produces gum Arabic, supports dryland ecosystems in tropical zones by its potentiality to restore degraded soils; hence it is ecologically and economically important for the dry areas of sub-Saharan Africa. The study aims at investigating the effects of water stress (simulated drought) and poor soil type on Acacia senegal C, N, and H contents. Seven days old seedlings were assigned to the treatments in Split- plot design for four weeks. The main plot is irrigation interval (well-watered and water-stressed), and the subplot is soil types (silt and sand soils). Seedling's C%, N%, and H% were measured using CHNS-O Analyzer and applying Standard Test Method. Irrigation intervals and soil types had no effects on seedlings and leaves C%, N%, and H%, irrigation interval had affected stem C and H%, both irrigation intervals and soil types had affected root N% and interaction effect of water and soil was found on leaves and root's N%. Synthesis application of well-watered irrigation with soil that is rich in N and other nutrients would result in the greatest seedling C, N, and H content which will enhance growth and biomass accumulation and can play a crucial role in ecosystem productivity and services in the dryland regions.

Keywords: Acacia senegal, Africa, climate change, drylands, nutrients biomass, Sub-Saharan, Sudan

Procedia PDF Downloads 109

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 193

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

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Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 312

Authors: Parvaneh Mahmoudi, Ahmad Moeni, Seyed Mojtaba Khayam Nekoei, Mohsen Mardi, Mehrshad Zeinolabedini, Ghasem Hosseini Salekdeh

Abstract:

Saffron (Crocus sativus L.) is one of the most important spice and medicinal plants. The three-branch style of C. sativus flowers are the most important economic part of the plant and known as saffron, which has several medicinal properties. Despite the economic and biological significance of this plant, knowledge about its molecular characteristics is very limited. In the present study, we, for the first time, constructed a comprehensive dataset for C. sativus stigma through de novo transcriptome sequencing. We performed de novo transcriptome sequencing of C. sativus stigma using the Illumina paired-end sequencing technology. A total of 52075128 reads were generated and assembled into 118075 unigenes, with an average length of 629 bp and an N50 of 951 bp. A total of 66171unigenes were identified, among them, 66171 (56%) were annotated in the non-redundant National Center for Biotechnology Information (NCBI) database, 30938 (26%) were annotated in the Swiss-Prot database, 10273 (8.7%) unigenes were mapped to 141 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, while 52560 (44%) and 40756 (34%) unigenes were assigned to Gen Ontology (GO) categories and Eukaryotic Orthologous Groups of proteins (KOG), respectively. In addition, 65 candidate genes involved in three stages of crocin biosynthesis were identified. Finally, transcriptome sequencing of saffron stigma was used to identify 6779 potential microsatellites (SSRs) molecular markers. High-throughput de novo transcriptome sequencing provided a valuable resource of transcript sequences of C. sativus in public databases. In addition, most of candidate genes potentially involved in crocin biosynthesis were identified which could be further utilized in functional genomics studies. Furthermore, numerous obtained SSRs might contribute to address open questions about the origin of this amphiploid spices with probable little genetic diversity.

Keywords: saffron, transcriptome, NGS, bioinformatic

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Authors: N. Manjunatha, K. T. Rangswamy, N. Nagaraju, H. A. Prameela, P. Rudraswamy, M. Krishnareddy

Abstract:

The identification of virus in cowpea especially potyviruses is confusing. Even though there are several studies on viruses causing diseases in cowpea, difficult to distinguish based on symptoms and serological detection. The differentiation of potyviruses considering as a constraint, the present study is initiated for molecular characterization, host plant resistance and epidemiology of the BCMV infecting cowpea. The etiological agent causing cowpea mosaic was identified as Bean Common Mosaic Virus (BCMV) on the basis of RT-PCR and electron microscopy. An approximately 750bp PCR product corresponding to coat protein (CP) region of the virus and the presence of long flexuous filamentous particles measuring about 952 nm in size typical to genus potyvirus were observed under electron microscope. The characterized virus isolate genome had 10054 nucleotides, excluding the 3’ terminal poly (A) tail. Comparison of polyprotein of the virus with other potyviruses showed similar genome organization with 9 cleavage sites resulted in 10 functional proteins. The pairwise sequence comparison of individual genes, P1 showed most divergent, but CP gene was less divergent at nucleotide and amino acid level. A phylogenetic tree constructed based on multiple sequence alignments of the polyprotein nucleotide and amino acid sequences of cowpea BCMV and potyviruses showed virus is closely related to BCMV-HB. Whereas, Soybean variant of china (KJ807806) and NL1 isolate (AY112735) showed 93.8 % (5’UTR) and 94.9 % (3’UTR) homology respectively with other BCMV isolates. This virus transmitted to different leguminous plant species and produced systemic symptoms under greenhouse conditions. Out of 100 cowpea genotypes screened, three genotypes viz., IC 8966, V 5 and IC 202806 showed immune reaction in both field and greenhouse conditions. Single marker analysis (SMA) was revealed out of 4 SSR markers linked to BCMV resistance, M135 marker explains 28.2 % of phenotypic variation (R2) and Polymorphic information content (PIC) value of these markers was ranged from 0.23 to 0.37. The correlation and regression analysis showed rainfall, and minimum temperature had significant negative impact and strong relationship with aphid population, whereas weak correlation was observed with disease incidence. Path coefficient analysis revealed most of the weather parameters exerted their indirect contributions to the aphid population and disease incidence except minimum temperature. This study helps to identify specific gaps in knowledge for researchers who may wish to further analyse the science behind complex interactions between vector-virus and host in relation to the environment. The resistant genotypes identified are could be effectively used in resistance breeding programme.

Keywords: cowpea, epidemiology, genotypes, virus

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Authors: Salam Khalifa, Naveed Ahmed

Abstract:

We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

Procedia PDF Downloads 367

Authors: Kiwon Yeom

Abstract:

Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

Procedia PDF Downloads 161

Authors: Puja Sharma, S. R. Dhiman, Bhararti Kashyap, Y. C. Gupta, Shabnam Pangtu

Abstract:

The experiments were carried out for mass multiplication and domestication of an endangered native tree spp, an orchid and an ornamental shrub having high medicinal value. Floriculture industry is novelty driven, hence the potential of these native ornamentals was assessed for their utilization as a novelty in the industry. For the mass propagation of endangered tree Oroxylum indicum, seed propagation and vegetative propagation techniques were successfully utilized. Highest seed germination was recorded in a medium containing cocopeat and perlite (1:1 v/v). Semi hard wood cuttings treated with IBA 2000 ppm planted in cocopeat+ sand+ perlite medium and maintained at 80% RH has resulted in about 90% rooting. The low growing tree was successfully domestication and has potential to be utilized in landscape industry. In the present study, cutting propagation and division of clump were used as methods for multiplication of Aerides multiflora, a native orchid spp. Soft wood cuttings treated with IBA 500 ppm planted in cocopeat medium was found to be the most suitable vegetative method resulting in 90 % rooting. It was domesticated as pot plant and for making hanging baskets. Propagation through seeds and cuttings was carried out for Pyracantha crenulata, a native ornamental shrub which is a cardiovascular medicine. For vegetative propagation, treatment of basal end of semi- hardwood cuttings of Pyracantha with IBA 3000 ppm (quick dip) and planting in cocopeat under mist chamber maintained at a relative humidity of 70-80% resulted in about 90% rooting out of all applied treatments in the study. For seed propagation, treatment of seeds in boiling water for 20 minutes and planting in cocopeat resulted in 82.55 % germination. The shrub was domesticated for its use as pot plant, protective hedge and for making bonsai.

Keywords: native, endangered, multiplication, domestication, oroxylum, aerides, pyracantha

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Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

Abstract:

This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

Procedia PDF Downloads 434

Authors: Rodrigo Calili, Anna Carolina Sermarini, João Henrique Azevedo, Vanessa Cardoso de Albuquerque, Felipe Gonçalves, Gilberto Jannuzzi

Abstract:

The diffusion of Distributed Energy Resources (DER) has caused structural changes in the relationship between consumers and electrical systems. The Photovoltaic Distributed Generation (PVDG), in particular, is an essential strategy for achieving the 2030 Agenda goals, especially SDG 7 and SDG 13. However, it is observed that most projects involving this technology in Brazil are restricted to the wealthiest classes of society, not yet reaching the low-income population, aligned with theories of energy justice. Considering the research for energy equality, one of the policies adopted by governments is the social electricity tariff (SET), which provides discounts on energy tariffs/bills. However, just granting this benefit may not be effective, and it is possible to merge it with DER technologies, such as the PVDG. Thus, this work aims to evaluate the economic viability of the policy to replace the social electricity tariff (the current policy aimed at the low-income population in Brazil) by PVDG projects. To this end, a proprietary methodology was developed that included: mapping the stakeholders, identifying critical variables, simulating policy options, and carrying out an analysis in the Brazilian context. The simulation answered two key questions: in which municipalities low-income consumers would have lower bills with PVDG compared to SET; which consumers in a given city would have increased subsidies, which are now provided for solar energy in Brazil and for the social tariff. An economic model was created for verifying the feasibility of the proposed policy in each municipality in the country, considering geographic issues (tariff of a particular distribution utility, radiation from a specific location, etc.). To validate these results, four sensitivity analyzes were performed: variation of the simultaneity factor between generation and consumption, variation of the tariff readjustment rate, zeroing CAPEX, and exemption from state tax. The behind-the-meter modality of generation proved to be more promising than the construction of a shared plant. However, although the behind-the-meter modality presents better results than the shared plant, there is a greater complexity in adopting this modality due to issues related to the infrastructure of the most vulnerable communities (e.g., precarious electrical networks, need to reinforce roofs). Considering the shared power plant modality, many opportunities are still envisaged since the risk of investing in such a policy can be mitigated. Furthermore, this modality can be an alternative due to the mitigation of the risk of default, as it allows greater control of users and facilitates the process of operation and maintenance. Finally, it was also found, that in some regions of Brazil, the continuity of the SET presents more economic benefits than its replacement by PVDG. However, the proposed policy offers many opportunities. For future works, the model may include other parameters, such as cost with low-income populations’ engagement, and business risk. In addition, other renewable sources of distributed generation can be studied for this purpose.

Keywords: low income, subsidy policy, distributed energy resources, energy justice

Procedia PDF Downloads 107