Search results for: geographic data streams

Authors: Eka Maulana, Sholeh Hadi Pramono, Dody Fanditya, M. Julius

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In this paper, extract of papaya leaves are used as a natural dye and combined by variations of solvent concentration applied on DSSC (Dye-Sensitized Solar Cell). Indonesian geographic located on the equator line occasions the magnitude of the potential to develop organic solar cells made from extracts of chlorophyll as a substitute for inorganic materials or synthetic dye on DSSC material. Dye serves as absorbing photons which are then converted into electrical energy. A conductive coated glass layer called TCO (Transparent Conductive Oxide) is used as a substrate of electrode. TiO2 nanoparticles as binding dye molecules, redox couple iodide/ tri-iodide as the electrolyte and carbon as the counter electrode in the DSSC are used. TiO2 nanoparticles, organic dyes, electrolytes and counter electrode are arranged and combined with the layered structure of the photo-catalyst absorption layer. Dye absorption measurements using a spectrophotometer at 200-800 nm light spectrum produces a total amount of chlorophyll 80.076 mg/l. The test cell at 7 watt LED light with 5000 lux luminescence were obtained Voc and Isc of 235.5 mV and 14 μA, respectively.

Keywords: DSSC (Dye-Sensitized Solar Cell), natural dye, chlorophyll, absorption

Procedia PDF Downloads 502

Authors: Jitka Rychtarikova

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Regional differences in mortality in the Czech Republic (CR) may be moderate from a broader European perspective, but important discrepancies in life expectancy can be found between smaller territorial units. In this study territorial units are based on Administrative Districts of Municipalities with Extended Powers (MEP). This definition came into force January 1, 2003. There are 205 units and the city of Prague. MEP represents the smallest unit for which mortality patterns based on life tables can be investigated and the Czech Statistical Office has been calculating such life tables (every five-years) since 2004. MEP life tables from 2009-2013 for males and females allowed the investigation of three main life cycles with the use of temporary life expectancies between the exact ages of 0 and 35; 35 and 65; and the life expectancy at exact age 65. The results showed regional survival inequalities primarily in adult and older ages. Consequently, only mortality indicators for adult and elderly population were related to census 2011 unlinked data for the same age groups. The most relevant socio-economic factors taken from the census are: having a partner, educational level and unemployment rate. The unemployment rate was measured for adults aged 35-64 completed years. Exploratory spatial data analysis methods were used to detect regional patterns in spatially contiguous units of MEP. The presence of spatial non-stationarity (spatial autocorrelation) of mortality levels for male and female adults (35-64), and elderly males and females (65+) was tested using global Moran’s I. Spatial autocorrelation of mortality patterns was mapped using local Moran’s I with the intention to depict clusters of low or high mortality and spatial outliers for two age groups (35-64 and 65+). The highest Moran’s I was observed for male temporary life expectancy between exact ages 35 and 65 (0.52) and the lowest was among women with life expectancy of 65 (0.26). Generally, men showed stronger spatial autocorrelation compared to women. The relationship between mortality indicators such as life expectancies and socio-economic factors like the percentage of males/females having a partner; percentage of males/females with at least higher secondary education; and percentage of unemployed males/females from economically active population aged 35-64 years, was evaluated using multiple regression (OLS). The results were then compared to outputs from geographically weighted regression (GWR). In the Czech Republic, there are two broader territories North-West Bohemia (NWB) and North Moravia (NM), in which excess mortality is well established. Results of the t-test of spatial regression showed that for males aged 30-64 the association between mortality and unemployment (when adjusted for education and partnership) was stronger in NM compared to NWB, while educational level impacted the length of survival more in NWB. Geographic variation and relationships in mortality of the CR MEP will also be tested using the spatial Durbin approach. The calculations were conducted by means of ArcGIS 10.6 and SAS 9.4.

Keywords: Czech Republic, mortality, municipality, socio-economic factors, spatial analysis

Procedia PDF Downloads 123

Authors: Rahul Malhotra, Anurag Sharma

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: FTTH, quad play, play service, access networks, data rate

Procedia PDF Downloads 420

Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

Procedia PDF Downloads 186

Authors: Lingerew Nebere Kassie, Ping-Yu Chang, Hsin-Hua Huang, , Chaw-Son Chen

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Transient electromagnetic (TEM) data plays a crucial role in hydrogeological and environmental applications, providing valuable insights into geological structures and resistivity variations. However, the presence of noise often hinders the interpretation and reliability of these data. Our study addresses this issue by utilizing a FASTSNAP system for the TEM survey, which operates at different modes (low, medium, and high) with continuous adjustments to discretization, gain, and current. We employ a denoising approach that processes the raw data obtained from each acquisition mode to improve signal quality and enhance data reliability. We use a signal-averaging technique for each mode, increasing the signal-to-noise ratio. Additionally, we utilize wavelet transform to suppress noise further while preserving the integrity of the underlying signals. This approach significantly improves the data quality, notably suppressing severe noise at late times. The resulting denoised data exhibits a substantially improved signal-to-noise ratio, leading to increased accuracy in parameter estimation. By effectively denoising TEM data, our study contributes to a more reliable interpretation and analysis of underground structures. Moreover, the proposed denoising approach can be seamlessly integrated into existing ground-based TEM data processing workflows, facilitating the extraction of meaningful information from noisy measurements and enhancing the overall quality and reliability of the acquired data.

Keywords: data quality, signal averaging, transient electromagnetic, wavelet transform

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

Procedia PDF Downloads 134

Authors: Balazs Kulcsar

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Professional energy organizations perform analyses mainly on the global and national levels about the expected development of the share of renewables in electric power generation, heating, and cooling, as well as the transport sectors. There are just a few publications, research institutions, non-profit organizations, and national initiatives with a focus on studies in the individual towns, settlements. Issues concerning the self-supply of energy on the settlement level have not become too wide-spread. The goal of our energy geographic studies is to determine the share of local renewable energy sources in the settlement-based electricity supply across Hungary. The Hungarian energy supply system defines four categories based on the installed capacities of electric power generating units. From these categories, the theoretical annual electricity production of small-sized household power plants (SSHPP) featuring installed capacities under 50 kW and small power plants with under 0.5 MW capacities have been taken into consideration. In the above-mentioned power plant categories, the Hungarian Electricity Act has allowed the establishment of power plants primarily for the utilization of renewable energy sources since 2008. Though with certain restrictions, these small power plants utilizing renewable energies have the closest links to individual settlements and can be regarded as the achievements of the host settlements in the shift of energy use. Based on the 2017 data, we have ranked settlements to reflect the level of self-sufficiency in electricity production from renewable energy sources. The results show that the supply of all the energy demanded by settlements from local renewables is within reach now in small settlements, e.g., in the form of the small power plant categories discussed in the study, and is not at all impossible even in small towns and cities. In Hungary, 30 settlements produce more renewable electricity than their own annual electricity consumption. If these overproductive settlements export their excess electricity towards neighboring settlements, then full electricity supply can be realized on further 29 settlements from renewable sources by local small power plants. These results provide an opportunity for governmental planning of the realization of energy shift (legislative background, support system, environmental education), as well as framing developmental forecasts and scenarios until 2030.

Keywords: energy geography, Hungary, local small power plants, renewable energy sources, self-sufficiency settlements

Procedia PDF Downloads 152

Authors: Claudia Carbajal, Jija Dutt, Smriti Pahwa, Sumukhi Vaid, Karishma Vats

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ASER Centre, the research and assessment arm of Pratham Education Foundation sees measurement as the first stage of action. ASER uses primary research to push and give empirical foundations to policy discussions at a multitude of levels. At a household level, common citizens use a simple assessment (a floor-level test) to measure learning across rural India. This paper presents the evidence on the applicability of an ASER approach to the health sector. A citizen-led assessment was designed and executed that collected information from young mothers with children up to a year of age. The pilot assessments were rolled-out in two different models: Paid surveyors and student volunteers. The survey covered three geographic areas: 1,239 children in the Jaipur District of Rajasthan, 2,086 in the Rae Bareli District of Uttar Pradesh, and 593 children in the Bhuj Block in Gujarat. The survey tool was designed to study knowledge of health-related issues, daily practices followed by young mothers and access to relevant services and programs. It provides insights on behaviors related to infant and young child feeding practices, child and maternal nutrition and supplementation, water and sanitation, and health services. Moreover, the survey studies the reasons behind behaviors giving policy-makers actionable pathways to improve implementation of social sector programs. Although data on health outcomes are available, this approach could provide a rapid annual assessment of health issues with indicators that are easy to understand and act upon so that measurements do not become an exclusive domain of experts. The results give many insights into early childhood health behaviors and challenges. Around 98% of children are breastfed, and approximately half are not exclusively breastfed (for the first 6 months). Government established diet diversity guidelines are met for less than 1 out of 10 children. Although most households are satisfied with the quality of drinking water, most tested households had contaminated water.

Keywords: citizen-led assessment, rapid health assessment, Infant and Young Children Feeding, water and sanitation, maternal nutrition, supplementation

Procedia PDF Downloads 171

Authors: Margaret S. Wright

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Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

Procedia PDF Downloads 226

Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

Procedia PDF Downloads 125

Authors: Surabhi Maiti, Prajakta Tamhankar, Prachi Uttam Mehta

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Since the accomplishment of the Human Genome Project, there has been an unparalled escalation in the sequencing of genomic data. This project has been the first major vault in the field of medical research, especially in genomics. This project won accolades by using a concept called Bigdata which was earlier, extensively used to gain value for business. Bigdata makes use of data sets which are generally in the form of files of size terabytes, petabytes, or exabytes and these data sets were traditionally used and managed using excel sheets and RDBMS. The voluminous data made the process tedious and time consuming and hence a stronger framework called Hadoop was introduced in the field of genetic sciences to make data processing faster and efficient. This paper focuses on using SPARK which is gaining momentum with the advancement of BigData technologies. Cloud Storage is an effective medium for storage of large data sets which is generated from the genetic research and the resultant sets produced from SPARK analysis.

Keywords: human genome project, Bigdata, genomic data, SPARK, cloud storage, Hadoop

Procedia PDF Downloads 259

Authors: M. J. Matulino, Carissa Ganong, Mark Mills, Jazmine Harry

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Large Woody Debris (LWD), defined as wooden debris with a diameter of at least 10 cm and a length of 2 m, serves as a crucial resource and habitat for aquatic organisms. While research on the ecological impacts of LWD has been conducted in temperate streams, LWD's influence on tropical stream biodiversity remains understudied, making this investigation particularly valuable for future conservation efforts. The Sura River in La Selva Biological Station includes both LWD and open channel sites. We sampled paired LWD and open-channel sites using minnow traps, Promar traps, and dip nets. Vertebrates were identified as species, while macroinvertebrates were identified to order level. We quantified abundance, richness, and Shannon diversity at each. We captured a total of 467 individuals, including 2 turtles, 17 fishes, 1 freshwater crab, 39 shrimp, and 408 other macroinvertebrates. Total abundance was significantly higher in LWD sites. Species richness was marginally higher in LWD sites, but the Shannon diversity index did not differ significantly with habitat. Shrimp (Macrobrachium olfersi) length was significantly higher in LWD areas. Increased food resources and microhabitat availability could contribute to higher abundance, richness, and organismal size in LWD environments. This study fills a critical gap by investigating LWD effects in a tropical environment, providing valuable insights for conservation efforts and the preservation of aquatic biodiversity.

Keywords: large woody debris (LWD), aquatic organisms, ecological impacts, tropical stream biodiversity, conservation efforts

Procedia PDF Downloads 96

Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

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Authors: Fikile Xaki, Zendy Magayiyana

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The increasing population and urbanization, with the demand for land and development, has had adverse impacts on wetland areas which has resulted in changing the hydrology and water chemistry of wetlands, affecting the water supply and water quality in urban areas like the Highland View, a residential area in Mbizana, South Africa. The settlement development in Highland View has led to wetland degradation due to land uses like agriculture and conversion of wetland for settlement development. Interviews with the local community were conducted to show how settlement development on wetland affects them. The results indicated that the environmental rights of people as according to Section 24 of the South African Constitution are compromised, and sustainable development was not put into consideration during development. With the results from the survey - through questionnaires for the Mbizana Local Municipality and the community, it was clear that the community needs education and capacity building on wetland management and conservation. Geographic Information Systems (GIS) was used to map physical properties of the Highland View wetland and houses built on the wetland. With all the information gathered from the research, it was clear that local municipality, together with hydrologists, needs to develop an environmental management framework to protect the wetlands.

Keywords: sustainable development, wetlands, human settlement, water

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

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Authors: Regina Kulugomba, Richard Blanchard, Harold Mapoma, Gregory Gamula, Stanley Mlatho

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Malawi is a country with low energy access with only 10% of people having access to electricity and 97% of people relying on charcoal and fuel wood. The over dependence on the traditional biomass has brought in a number of negative consequences on people’s health and the environment. To curb the situation, the Government of Malawi (GoM), through its national policy of 2018 and charcoal strategies of 2007, identified biogas as a suitable alternative energy source for cooking. The GoM intends to construct tubular digesters across the country and one of the most crucial factors is the availability of livestock manure. The study was conducted to assess biogas potential from livestock manure by using Quantum Geographic information system (QGIS) software. Potential methane was calculated based on the population of livestock, amount of manure produced per capita and year, total solids, biogas yield and availability coefficient. The results of the study estimated biogas potential at 687 million m3 /year. Districts identified with highest biogas potential were Lilongwe, Ntcheu, Mangochi, Neno, Mwanza, Blantyre, Chiradzulu and Mulanje. The information will help investors and the Government of Malawi to locate potential sites for biogas plants installation.

Keywords: biogas, energy, feedstock, livestock

Procedia PDF Downloads 184

Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

Procedia PDF Downloads 123

Authors: Arash Kosari, Ali Araghi

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A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: absorption, data throughput, depolarization, optical fiber

Procedia PDF Downloads 289

Authors: K. Ali, M. F. Qamar, M. A. Zaman, M. Younus, I. Khan, S. Ehtisham-ul-Haque, R. Tamkeen, M. I. Rashid, Q. Ali

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This study centers on molecular identification of Haemonchus contortus and isolation of Benz-imidazoles (BZ) resistant strains. Different abattoirs’ of two geographic regions of Punjab (Pakistan) were frequently visited for the collection of worms. Out of 1500 (n=1500) samples that were morphologically confirmed as H. contortus, 30 worms were subjected to molecular procedures for isolation of resistant strains. Resistant worms (n=8) were further subjected to DNA gene sequencing. Bio edit sequence alignment editor software was used to detect the possible mutation, deletion, replacement of nucleotides. Genetic diversity was noticed and genetic variation existing in β-tubulin isotype 1 of the H. contortus population of small ruminants of different regions considered in this study. H. contortus showed three different type of genetic sequences. 75%, 37.5%, 25% and 12.5% of the studied samples showed 100% query cover and identity with isolates and clones of China, UK, Australia and other countries, respectively. Interestingly the neighbor countries such as India and Iran haven’t many similarities with the Pakistani isolates. Thus, it suggests that population density of same genetic makeup H. contortus is scattered worldwide rather than clustering in a single region.

Keywords: Haemonchus contortus, Benzimidazole resistant, β-tubulin-1 gene, abattoirs

Procedia PDF Downloads 179

Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Michelle J. Miller

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In recent year, there has been a rise of two emerging issues that impact the global employment and business market that the legal community must review closer: offshore outsourcing and data privacy. These two issues intersect because employment opportunities are shifting due to offshore outsourcing and some States, like the United States, anti-outsourcing legislation has been passed or presented to retain jobs within the country. In addition, the legal requirements to retain the privacy of data as a global employer extends to employees and third party service provides, including services outsourced to offshore locations. For this reason, this paper will review the intersection of these two issues with a specific focus on data privacy.

Keywords: outsourcing, data privacy, international compliance, multinational corporations

Procedia PDF Downloads 414

Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

Procedia PDF Downloads 263

Authors: Kazım Kaba, Erdem Erdi, M. Akif Erdoğan, H. Mustafa Kandırmaz

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Rainfall is crucial data source for very different discipline such as agriculture, hydrology and climate. Therefore rain rate should be known well both spatial and temporal for any area. Rainfall is measured by using rain-gauge at meteorological ground stations traditionally for many years. At the present time, rainfall products are acquired from radar and satellite images with a temporal and spatial continuity. In this study, we investigated the accuracy of these rainfall data according to rain-gauge data. For this purpose, we used Adana-Hatay radar hourly total precipitation product (RN1) and Meteosat convective rainfall rate (CRR) product over Seyhan plain. We calculated daily rainfall values from RN1 and CRR hourly precipitation products. We used the data of rainy days of four stations located within range of the radar from October 2013 to November 2015. In the study, we examined two rainfall data over Seyhan plain and the correlation between the rain-gauge data and two raster rainfall data was observed lowly.

Keywords: meteosat, radar, rainfall, rain-gauge, Turkey

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Authors: Sihem Oujdi, Hafida Belbachir

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Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

Procedia PDF Downloads 619

Authors: Kannapha Amaruchkul

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We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 138

Authors: Rania Khadim, Mohammed Erritali, Abdelhakim Maaden

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Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to those networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. In this paper we choose to evaluate the performance of two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing) for Wireless Sensor Network. The simulations were performed using NS2 simulator to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR). This work presents also a new scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost, the location query cost and the storage cost.

Keywords: location based-services, routing protocols, scalability, wireless sensor networks

Procedia PDF Downloads 378

Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Amornchai Challcharoenwattana, Chanathip Pharino

Abstract:

Rising amount of MSW every day, maximizing material diversions from landfills via recycling is a prefer method to land dumping. Characteristic of Thai MSW is classified as 40 -60 per cent compostable wastes while potentially recyclable materials in waste streams are composed of plastics, papers, glasses, and metals. However, rate of material recovery from MSW, excluding composting or biogas generation, in Thailand is still low. Thailand’s recycling rate in 2010 was only 20.5 per cent. Central government as well as local governments in Thailand have tried to curb this problem by charging some of MSW management fees at the users. However, the fee is often too low to promote MSW minimization. The objective of this paper is to identify levels of willingness-to-pay (WTP) for MSW recycling in different social structures with expected outcome of sustainable MSW managements for different town settlements to maximize MSW recycling pertaining to each town’s potential. The method of eliciting WTP is a payment card. The questionnaire was deployed using online survey during December 2012. Responses were categorized into respondents living in Bangkok, living in other municipality areas, or outside municipality area. The responses were analysed using descriptive statistics, and multiple linear regression analysis to identify relationships and factors that could influence high or low WTP. During the survey period, there were 168 filled questionnaires from total 689 visits. However, only 96 questionnaires could be usable. Among respondents in the usable questionnaires, 36 respondents lived in within the boundary of Bangkok Metropolitan Administration while 45 respondents lived in the chartered areas that were classified as other municipality but not in BMA. Most of respondents were well-off as 75 respondents reported positive monthly cash flow (77.32%), 15 respondents reported neutral monthly cash flow (15.46%) while 7 respondent reported negative monthly cash flow (7.22%). For WTP data including WTP of 0 baht with valid responses, ranking from the highest means of WTP to the lowest WTP of respondents by geographical locations for good MSW management were Bangkok (196 baht/month), municipalities (154 baht/month), and non-urbanized towns (111 baht/month). In-depth analysis was conducted to analyse whether there are additional room for further increase of MSW management fees from the current payment that each correspondent is currently paying. The result from multiple-regression analysis suggested that the following factors could impacts the increase or decrease of WTP: incomes, age, and gender. Overall, the outcome of this study suggests that survey respondents are likely to support improvement of MSW treatments that are not solely relying on landfilling technique. Recommendations for further studies are to obtain larger sample sizes in order to improve statistical powers and to provide better accuracy of WTP study.

Keywords: MSW, willingness to pay, payment card, waste seperation

Procedia PDF Downloads 296

Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

Abstract:

The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

Procedia PDF Downloads 91

Authors: Mohammed Sulaiman, Hexu Liu, Mohamed Binalhaj, William W. Liou, Osama Abudayyeh

Abstract:

Emerging technologies such as camera-equipped unmanned aerial vehicles (UAVs) are increasingly being applied in building fire rescue to provide real-time visualization and 3D reconstruction of the entire fireground. However, flight planning of camera-equipped UAVs is usually a manual process, which is not sufficient to fulfill the needs of emergency management. This research proposes a Geographic Information System (GIS)-based approach to automatic flight planning of camera-equipped UAVs for building fire emergency response. In this research, Haversine formula and lawn mowing patterns are employed to automate flight planning based on geometrical and spatial information from GIS. The resulting flight mission satisfies the requirements of 3D reconstruction purposes of the fireground, in consideration of flight execution safety and visibility of camera frames. The proposed approach is implemented within a GIS environment through an application programming interface. A case study is used to demonstrate the effectiveness of the proposed approach. The result shows that flight mission can be generated in a timely manner for application to fire emergency response.

Keywords: GIS, camera-equipped UAVs, automatic flight planning, fire emergency response

Procedia PDF Downloads 130