Search results for: geographically weighted regressions
515 Energy Efficient Massive Data Dissemination Through Vehicle Mobility in Smart Cities
Authors: Salman Naseer
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One of the main challenges of operating a smart city (SC) is collecting the massive data generated from multiple data sources (DS) and to transmit them to the control units (CU) for further data processing and analysis. These ever-increasing data demands require not only more and more capacity of the transmission channels but also results in resource over-provision to meet the resilience requirements, thus the unavoidable waste because of the data fluctuations throughout the day. In addition, the high energy consumption (EC) and carbon discharges from these data transmissions posing serious issues to the environment we live in. Therefore, to overcome the issues of intensive EC and carbon emissions (CE) of massive data dissemination in Smart Cities, we propose an energy efficient and carbon reduction approach by utilizing the daily mobility of the existing vehicles as an alternative communications channel to accommodate the data dissemination in smart cities. To illustrate the effectiveness and efficiency of our approach, we take the Auckland City in New Zealand as an example, assuming massive data generated by various sources geographically scattered throughout the Auckland region to the control centres located in city centre. The numerical results show that our proposed approach can provide up to 5 times lower delay as transferring the large volume of data by utilizing the existing daily vehicles’ mobility than the conventional transmission network. Moreover, our proposed approach offers about 30% less EC and CE than that of conventional network transmission approach.Keywords: smart city, delay tolerant network, infrastructure offloading, opportunistic network, vehicular mobility, energy consumption, carbon emission
Procedia PDF Downloads 141514 Indicator-Based Approach for Assessing Socio Economic Vulnerability of Dairy Farmers to Impacts of Climate Variability and Change in India
Authors: Aparna Radhakrishnan, Jancy Gupta, R. Dileepkumar
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This paper aims at assessing the Socio Economic Vulnerability (SEV) of dairy farmers to Climate Variability and Change (CVC) in 3 states of Western Ghat region in India. For this purpose, a composite SEV index has been developed on the basis of functional relationships amongst sensitivity, exposure and adaptive capacity using 30 indicators related to dairy farming underlying the principles of Intergovernmental Panel on Climate Change and Fussel framework for nomenclature of vulnerable situation. Household level data were collected through Participatory Rural Appraisal and personal interviews of 540 dairy farmers of nine taluks, three each from a district selected from Kerala, Karnataka and Maharashtra, complemented by thirty years of gridded weather data. The data were normalized and then combined into three indices for sensitivity, exposure and adaptive capacity, which were then averaged with weights given using principal component analysis, to obtain the overall SEV index. Results indicated that the taluks of Western Ghats are vulnerable to CVC. The dairy farmers of Pulpally taluka were most vulnerable having the SEV score +1.24 and 42.66% farmers under high-level vulnerability category. Even though the taluks are geographically closer, there is wide variation in SEV components. Policies for incentivizing the ‘climate risk adaptation’ costs for small and marginal farmers and livelihood infrastructure for mitigating risks and promoting grass root level innovations are necessary to sustain dairy farming of the region.Keywords: climate change, dairy, vulnerability, livelihoods, adaptation strategies
Procedia PDF Downloads 418513 Probabilistic Approach to the Spatial Identification of the Environmental Sources behind Mortality Rates in Europe
Authors: Alina Svechkina, Boris A. Portnov
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In line with a rapid increase in pollution sources and enforcement of stricter air pollution regulation, which lowers pollution levels, it becomes more difficult to identify actual risk sources behind the observed morbidity patterns, and new approaches are required to identify potential risks and take preventive actions. In the present study, we discuss a probabilistic approach to the spatial identification of a priori unidentified environmental health hazards. The underlying assumption behind the tested approach is that the observed adverse health patterns (morbidity, mortality) can become a source of information on the geographic location of environmental risk factors that stand behind them. Using this approach, we analyzed sources of environmental exposure using data on mortality rates available for the year 2015 for NUTS 3 (Nomenclature of Territorial Units for Statistics) subdivisions of the European Union. We identified several areas in the southwestern part of Europe as primary risk sources for the observed mortality patterns. Multivariate regressions, controlled by geographical location, climate conditions, GDP (gross domestic product) per capita, dependency ratios, population density, and the level of road freight revealed that mortality rates decline as a function of distance from the identified hazard location. We recommend the proposed approach an exploratory analysis tool for initial investigation of regional patterns of population morbidity patterns and factors behind it.Keywords: mortality, environmental hazards, air pollution, distance decay gradient, multi regression analysis, Europe, NUTS3
Procedia PDF Downloads 167512 Groundwater Recharge Suitability Mapping Using Analytical Hierarchy Process Based-Approach
Authors: Aziza Barrek, Mohamed Haythem Msaddek, Ismail Chenini
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Excessive groundwater pumping due to the increasing water demand, especially in the agricultural sector, causes groundwater scarcity. Groundwater recharge is the most important process that contributes to the water's durability. This paper is based on the Analytic Hierarchy Process multicriteria analysis to establish a groundwater recharge susceptibility map. To delineate aquifer suitability for groundwater recharge, eight parameters were used: soil type, land cover, drainage density, lithology, NDVI, slope, transmissivity, and rainfall. The impact of each factor was weighted. This method was applied to the El Fahs plain shallow aquifer. Results suggest that 37% of the aquifer area has very good and good recharge suitability. The results have been validated by the Receiver Operating Characteristics curve. The accuracy of the prediction obtained was 89.3%.Keywords: AHP, El Fahs aquifer, empirical formula, groundwater recharge zone, remote sensing, semi-arid region
Procedia PDF Downloads 121511 Determining of Importance Level of Factors Affecting Job Selection with the Method of AHP
Authors: Nurullah Ekmekci, Ömer Akkaya, Kazım Karaboğa, Mahmut Tekin
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Job selection is one of the most important decisions that affect their lives in the name of being more useful to themselves and the society. There are many criteria to consider in the job selection. The amount of criteria in the job selection makes it a multi-criteria decision-making (MCDM) problem. In this study; job selection has been discussed as multi-criteria decision-making problem and has been solved by Analytic Hierarchy Process (AHP), one of the multi-criteria decision making methods. A survey, contains 5 different job selection criteria (finding a job friendliness, salary status, job , social security, work in the community deems reputation and business of the degree of difficulty) within many job selection criteria and 4 different job alternative (being academician, working at the civil service, working at the private sector and working at in their own business), has been conducted to the students of Selcuk University Faculty of Economics and Administrative Sciences. As a result of pairwise comparisons, the highest weighted criteria in the job selection and the most coveted job preferences were identified.Keywords: analytical hierarchy process, job selection, multi-criteria, decision making
Procedia PDF Downloads 399510 Mapping of Potential Areas for Groundwater Storage in the Sais Plateau and Its Middle Atlas Borders, Morocco
Authors: Abdelghani Qadem, Zohair Qadem, Mohamed Lasri
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At the level of the Moroccan Sais Plateau, groundwater constitutes strategic natural resources for agricultural, industrial, and domestic use. Today, due to climate change and population growth, the pressure on groundwater has increased considerably. This contribution aims to delineate and map potential areas for groundwater storage in the area in question using GIS and remote sensing. The methodology adopted is based on the identification of the thematic layers used to assess the potential recharge of the aquifer. The mapping of potential areas for groundwater storage is developed through the method of modeling and weighted overlay using the spatial analysis tool on the Geographic Information System. The results obtained can be used for the planning of future artificial recharge projects in the study area in order to ensure the good sustainable use of this underground gift.Keywords: Morocco, climate change, groundwater, mapping, recharge
Procedia PDF Downloads 83509 Mapping the Suitable Sites for Food Grain Crops Using Geographical Information System (GIS) and Analytical Hierarchy Process (AHP)
Authors: Md. Monjurul Islam, Tofael Ahamed, Ryozo Noguchi
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Progress continues in the fight against hunger, yet an unacceptably large number of people still lack food they need for an active and healthy life. Bangladesh is one of the rising countries in the South-Asia but still lots of people are food insecure. In the last few years, Bangladesh has significant achievements in food grain production but still food security at national to individual levels remain a matter of major concern. Ensuring food security for all is one of the major challenges that Bangladesh faces today, especially production of rice in the flood and poverty prone areas. Northern part is more vulnerable than any other part of Bangladesh. To ensure food security, one of the best way is to increase domestic production. To increase production, it is necessary to secure lands for achieving optimum utilization of resources. One of the measures is to identify the vulnerable and potential areas using Land Suitability Assessment (LSA) to increase rice production in the poverty prone areas. Therefore, the aim of the study was to identify the suitable sites for food grain crop rice production in the poverty prone areas located at the northern part of Bangladesh. Lack of knowledge on the best combination of factors that suit production of rice has contributed to the low production. To fulfill the research objective, a multi-criteria analysis was done and produced a suitable map for crop production with the help of Geographical Information System (GIS) and Analytical Hierarchy Process (AHP). Primary and secondary data were collected from ground truth information and relevant offices. The suitability levels for each factor were ranked based on the structure of FAO land suitability classification as: Currently Not Suitable (N2), Presently Not Suitable (N1), Marginally Suitable (S3), Moderately Suitable (S2) and Highly Suitable (S1). The suitable sites were identified using spatial analysis and compared with the recent raster image from Google Earth Pro® to validate the reliability of suitability analysis. For producing a suitability map for rice farming using GIS and multi-criteria analysis tool, AHP was used to rank the relevant factors, and the resultant weights were used to create the suitability map using weighted sum overlay tool in ArcGIS 10.3®. Then, the suitability map for rice production in the study area was formed. The weighted overly was performed and found that 22.74 % (1337.02 km2) of the study area was highly suitable, while 28.54% (1678.04 km2) was moderately suitable, 14.86% (873.71 km2) was marginally suitable, and 1.19% (69.97 km2) was currently not suitable for rice farming. On the other hand, 32.67% (1920.87 km2) was permanently not suitable which occupied with settlements, rivers, water bodies and forests. This research provided information at local level that could be used by farmers to select suitable fields for rice production, and then it can be applied to other crops. It will also be helpful for the field workers and policy planner who serves in the agricultural sector.Keywords: AHP, GIS, spatial analysis, land suitability
Procedia PDF Downloads 241508 Understanding Factors that Affect the Prior Knowledge of Deaf and Hard of Hearing Students and their Relation to Reading Comprehension
Authors: Khalid Alasim
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The reading comprehension levels of students who are deaf or hard of hearing (DHH) are low compared to those of their hearing peers. One possible reason for this low reading levels is related to the students’ prior knowledge. This study investigated the potential factors that might affected DHH students’ prior knowledge, including their degree of hearing loss, the presence or absence of family members with a hearing loss, and educational stage (elementary–middle school). The study also examined the contribution of prior knowledge in predicting DHH students’ reading comprehension levels, and investigated the differences in the students’ scores based on the type of questions, including text-explicit (TE), text-implicit (TI), and script-implicit (SI) questions. Thirty-one elementary and middle-school students completed a demographic form and assessment, and descriptive statistics and multiple and simple linear regressions were used to answer the research questions. The findings indicated that the independent variables—degree of hearing loss, presence or absence of family members with hearing loss, and educational stage—explained little of the variance in DHH students’ prior knowledge. Further, the results showed that the DHH students’ prior knowledge affected their reading comprehension. Finally, the result demonstrated that the participants were able to answer more of the TI questions correctly than the TE and SI questions. The study concluded that prior knowledge is important in these students’ reading comprehension, and it is also important for teachers and parents of DHH children to use effective ways to increase their students’ and children’s prior knowledge.Keywords: reading comprehension, prior knowledge, metacognition, elementary, self-contained classrooms
Procedia PDF Downloads 104507 Administrative Determinants of Students' Sports Participation in Private and Public Secondary Schools in Kwara State, Nigeria
Authors: Danjuma Moudu Momoh
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Participation in sports is of immense benefit to the soundness of individual mental and social wellness, particularly among youngsters. The 1980’s and 1990’s compared to 2000’s witnessed great involvement of youngsters in school games arising from the high administrative supports attached to sports. Previous studies in an attempt to increase youngster’s participation in sports had focused more on other factors rather than on administrative factors. This study, therefore, investigated the importance of administrative factors (availability of facilities, availability of equipment, funding, scheduling of sports programme and administrative style of school principals) on students’ sports participation in private and public secondary schools in Kwara State, Nigeria. Descriptive survey research design using validated and structured questionnaire, was adopted. Stratified random sampling technique was used to pick the students both male and female. A total of two thousand five hundred and sixty participants were involved in the study. A reliable coefficient of r=0.82 was obtained for the instruments using Cronbach Alpha. Data were analyzed using multiple regressions to test the hypotheses at 00.5 significant levels. At the end of the study, it was discovered that the relative contributions of administrative factors among the students were: availability of facilities (β=0.314), availability of equipment (β=0.444), funding (β=0.301), scheduling of sports programme (β=0.447), made relative contributions to the dependent variable, administrative style of school principal (β=0.077) did not make significant but minimal contribution to the student’s sports participation.Keywords: administrative determinants, secondary school students, physical activity, sports participation
Procedia PDF Downloads 550506 A Semiparametric Approach to Estimate the Mode of Continuous Multivariate Data
Authors: Tiee-Jian Wu, Chih-Yuan Hsu
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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method
Procedia PDF Downloads 284505 Obesity, Leptin Levels and Leptin Receptor Gene Polymorphisms in Afro-Caribbean Subjects
Authors: Lydia Foucan, Christine Rambhojan, Rachel Billy, Christophe Armand, Carl-Thony Michel, Jean-Marc Lacorte, Laurent Larifla
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Leptin, an adipocyte-derived hormone, modulates insulin secretion and action via the leptin receptor (LEPR) that is expressed in pancreatic beta cells, adipose tissue, and muscle. Several polymorphisms have been described in the human LEPR gene including p.K109R (rs1137100), p.Q223R (rs1137101) and p.K656N (rs1805094) polymorphisms. The role of these polymorphisms is not yet studied in Guadeloupian population. Our aim was to explore the association of LEPR polymorphisms (K109R, Q223R and K656N) with leptin levels and obesity in non-diabetic Afro-Caribbean subjects. Genotypic analysis of the three polymorphisms was performed in 425 subjects using TaqMan and KASPar Assays. Serum leptin was measured with ELISA kits Biovendor® (RD191001100). Logistic regressions were used for assessment of statistical associations. Mean age was 47.6 ± 12.7 years. Among the participants, 238 (56 %) were women, 124 (30%) were obese and 155 (36.5%) had abdominal obesity. Carriers of LEPR K656N rs1805094 rare allele had significant higher frequencies of obesity (P = 0.007), abdominal obesity (P = 0.004) and metabolic syndrome (P = 0.021) but mean leptin level was not significantly different between both groups (P = 0.075). Odds ratios, adjusted for age and sex associated with presence of rs1805094 rare allele were 1.8 (1.1-2.9), P = 0.012 for obesity, 2.0 (1.2-3.3), P = 0.008 for abdominal obesity and 1.8 (1.1-3.0), P = 0.031 for MetS. No significant association was found with K109R, Q223R. These findings suggest that the K656N polymorphism (but not the K109R or Q223R polymorphism) of LEPR is associated with obesity, abdominal obesity and metabolic syndrome in this Afro-Caribbean non-diabetic population.Keywords: Afro-Caribbean, leptin levels, leptin receptor gene polymorphisms, obesity
Procedia PDF Downloads 377504 Machine Learning Approach for Lateralization of Temporal Lobe Epilepsy
Authors: Samira-Sadat JamaliDinan, Haidar Almohri, Mohammad-Reza Nazem-Zadeh
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Lateralization of temporal lobe epilepsy (TLE) is very important for positive surgical outcomes. We propose a machine learning framework to ultimately identify the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Unlike most studies that use classification algorithms, we propose an effective clustering approach to distinguish between normal and TLE cases. We apply the famous Minkowski weighted K-Means (MWK-Means) technique as the clustering framework. To overcome the problem of poor initialization of K-Means, we use particle swarm optimization (PSO) to effectively select the initial centroids of clusters prior to applying MWK-Means. We demonstrate that compared to K-means and MWK-means independently, this approach is able to improve the result of a benchmark data set.Keywords: temporal lobe epilepsy, machine learning, clustering, magnetoencephalography
Procedia PDF Downloads 154503 Security in Resource Constraints Network Light Weight Encryption for Z-MAC
Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy
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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC
Procedia PDF Downloads 143502 Major Constraints to Adoption of Improved Post-harvest Technologies among Smallholder Farmers in Developing Countries: A Systematic Review
Authors: Muganyizi Jonas Bisheko, G. Rejikumar
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Reducing post-harvest losses could be a sustainable solution to enhance the food and income security of smallholder farmers in developing countries. While various research institutions have come up with a number of innovative post-harvest technologies for reducing post-harvest losses, most of them have not been extensively adopted by smallholder farmers. Despite this gap, the synthesized information about the major constraints of post-harvest technology is scarce. This study has been conducted to fill this gap and show the implications of the findings for future post-harvest research. The developed search strategy retrieved 2201 studies. However, after excluding duplicates, title, abstract and full article screening, a total of 41 documents were identified. The major findings are: (i) there is an outstanding deficiency of systematic evidence of the effect of climate change, off-farm income and sources of post-harvest information on the adoption of improved post-harvest technologies; (ii) there is very limited information on adoption constraints pertaining to matters of policy, rules and regulations; (iii) there is very thin literature on behavioral constraints associated with limited adoption of improved post-harvest technologies; (iv) most of the studies focused on post-harvest storage technologies (47%) followed by overall post-harvest management practices (25%), processing technologies (19%) and packaging technologies (3%). Much of the information was found on Cereals (58%), especially maize (44%); (v) geographically, Sub-Saharan Africa accounted for 79% of the reviewed interventions, while South Asia occupied only 21%. The findings of this review are intended to guide various post-harvest technologists and decision-makers in addressing the challenge of huge post-harvest losses.Keywords: constraints, post-harvest loss, post-harvest technology , smallholder farmer
Procedia PDF Downloads 235501 Improving Fault Tolerance and Load Balancing in Heterogeneous Grid Computing Using Fractal Transform
Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry
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The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems
Procedia PDF Downloads 490500 Nonparametric Estimation of Risk-Neutral Densities via Empirical Esscher Transform
Authors: Manoel Pereira, Alvaro Veiga, Camila Epprecht, Renato Costa
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This paper introduces an empirical version of the Esscher transform for risk-neutral option pricing. Traditional parametric methods require the formulation of an explicit risk-neutral model and are operational only for a few probability distributions for the returns of the underlying. In our proposal, we make only mild assumptions on the pricing kernel and there is no need for the formulation of the risk-neutral model for the returns. First, we simulate sample paths for the returns under the physical distribution. Then, based on the empirical Esscher transform, the sample is reweighted, giving rise to a risk-neutralized sample from which derivative prices can be obtained by a weighted sum of the options pay-offs in each path. We compare our proposal with some traditional parametric pricing methods in four experiments with artificial and real data.Keywords: esscher transform, generalized autoregressive Conditional Heteroscedastic (GARCH), nonparametric option pricing
Procedia PDF Downloads 489499 Leveraging Multimodal Neuroimaging Techniques to in vivo Address Compensatory and Disintegration Patterns in Neurodegenerative Disorders: Evidence from Cortico-Cerebellar Connections in Multiple Sclerosis
Authors: Efstratios Karavasilis, Foteini Christidi, Georgios Velonakis, Agapi Plousi, Kalliopi Platoni, Nikolaos Kelekis, Ioannis Evdokimidis, Efstathios Efstathopoulos
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Introduction: Advanced structural and functional neuroimaging techniques contribute to the study of anatomical and functional brain connectivity and its role in the pathophysiology and symptoms’ heterogeneity in several neurodegenerative disorders, including multiple sclerosis (MS). Aim: In the present study, we applied multiparametric neuroimaging techniques to investigate the structural and functional cortico-cerebellar changes in MS patients. Material: We included 51 MS patients (28 with clinically isolated syndrome [CIS], 31 with relapsing-remitting MS [RRMS]) and 51 age- and gender-matched healthy controls (HC) who underwent MRI in a 3.0T MRI scanner. Methodology: The acquisition protocol included high-resolution 3D T1 weighted, diffusion-weighted imaging and echo planar imaging sequences for the analysis of volumetric, tractography and functional resting state data, respectively. We performed between-group comparisons (CIS, RRMS, HC) using CAT12 and CONN16 MATLAB toolboxes for the analysis of volumetric (cerebellar gray matter density) and functional (cortico-cerebellar resting-state functional connectivity) data, respectively. Brainance suite was used for the analysis of tractography data (cortico-cerebellar white matter integrity; fractional anisotropy [FA]; axial and radial diffusivity [AD; RD]) to reconstruct the cerebellum tracts. Results: Patients with CIS did not show significant gray matter (GM) density differences compared with HC. However, they showed decreased FA and increased diffusivity measures in cortico-cerebellar tracts, and increased cortico-cerebellar functional connectivity. Patients with RRMS showed decreased GM density in cerebellar regions, decreased FA and increased diffusivity measures in cortico-cerebellar WM tracts, as well as a pattern of increased and mostly decreased functional cortico-cerebellar connectivity compared to HC. The comparison between CIS and RRMS patients revealed significant GM density difference, reduced FA and increased diffusivity measures in WM cortico-cerebellar tracts and increased/decreased functional connectivity. The identification of decreased WM integrity and increased functional cortico-cerebellar connectivity without GM changes in CIS and the pattern of decreased GM density decreased WM integrity and mostly decreased functional connectivity in RRMS patients emphasizes the role of compensatory mechanisms in early disease stages and the disintegration of structural and functional networks with disease progression. Conclusions: In conclusion, our study highlights the added value of multimodal neuroimaging techniques for the in vivo investigation of cortico-cerebellar brain changes in neurodegenerative disorders. An extension and future opportunity to leverage multimodal neuroimaging data inevitably remain the integration of such data in the recently-applied mathematical approaches of machine learning algorithms to more accurately classify and predict patients’ disease course.Keywords: advanced neuroimaging techniques, cerebellum, MRI, multiple sclerosis
Procedia PDF Downloads 140498 Heuristic for Scheduling Correlated Parallel Machine to Minimize Maximum Lateness and Total Weighed Completion Time
Authors: Yang-Kuei Lin, Yun-Xi Zhang
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This research focuses on the bicriteria correlated parallel machine scheduling problem. The two objective functions considered in this problem are to minimize maximum lateness and total weighted completion time. We first present a mixed integer programming (MIP) model that can find the entire efficient frontier for the studied problem. Next, we have proposed a bicriteria heuristic that can find non-dominated solutions for the studied problem. The performance of the proposed bicriteria heuristic is compared with the efficient frontier generated by solving the MIP model. Computational results indicate that the proposed bicriteria heuristic can solve the problem efficiently and find a set of diverse solutions that are uniformly distributed along the efficient frontier.Keywords: bicriteria, correlated parallel machines, heuristic, scheduling
Procedia PDF Downloads 141497 The Effect of Chitosan and Mycorrhization on Some Growth-Physiological Indices of Salvia leriifolia Benth.
Authors: Marzieh Fotovvat, Farzaneh Najafi, Ramazan Ali Khavari-Nejad, Daryush Talei, Farhad Rejali
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Salvia leriifolia Benth. is one of the valuable and perennial medicinal plants of the Lamiaceae family, geographically growing in the south and tropical regions of Khorassan and Semnan provinces in Iran. In recent years, several medicinal properties such as antimicrobial, antifungal, anti-diabetic, analgesic, and anti-inflammatory effects have been reported from this plant. The use of elicitors such as chitosan and Arbuscular mycorrhizal fungi (AMF) symbiosis are the main methods for increasing the production of secondary metabolites, growth, and physiological factors in plants. The main aim of this study was to investigate the effects of foliar spraying applications by chitosan and/or the contribution of AMF (Glomus interaradices) on some growth factors and chlorophyll content of S. leriifolia under glasshouse conditions. The sterilized seeds were germinated by placing them into a cocopeat. After one month, seedlings that were in the 2-4 leaf stage were transferred to plastic pots (garden soil and pumice at 2:1) with or without mycorrhizal fungi. Chitosan (0, 50, 100, 200, and 400 mg L-1) was sprayed four times in the fourth month of the vegetative period. The results showed that fresh leaf weight, fresh root weight, root height, and chlorophyll content could change in the plant treated with chitosan and AMF symbiosis. So that the highest chlorophyll content and fresh weight of roots and leaves were observed in the interaction of chitosan and G. interaradices. In general, by optimizing the chitosan concentration and the use of appropriate AMF symbiosis, it is possible to improve the growth and quality of the medicinal plant S. leriifolia.Keywords: chitosan, chlorophyll, growth factors, mycorrhiza
Procedia PDF Downloads 81496 Land Suitability Analysis for Rice Production in a Typical Watershed of Southwestern Nigeria: A Sustainability Pathway
Authors: Oluwagbenga O. Isaac Orimoogunje, Omolola Helen Oshosanya
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The study examined land management in a typical watershed in southwestern Nigeria with a view to ascertaining its impact on land suitability analysis for rice cultivation and production. The study applied the analytical hierarchy process (AHP), weighted overlay analysis (WOA), multi-criteria decision-making techniques, and suitability map calculations within a Geographic Information System environment. Five main criteria were used, and these include climate, topography, soil fertility, macronutrients, and micronutrients. A consistency ratio (CR) of 0.067 was obtained for rice cultivation. The results showed that 95% of the land area is suitable for rice cultivation, with pH units ranging between 4.6 and 6.0, organic matter of 1.4–2.5 g kg-1 and base saturation of more than 80%. The study concluded that the Ofiki watershed is a potential site for large-scale rice cultivation in a sustainable capacity.Keywords: land management, land characteristics, land suitability, rice production, watershed
Procedia PDF Downloads 77495 Forthcoming Big Data on Smart Buildings and Cities: An Experimental Study on Correlations among Urban Data
Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin
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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.Keywords: big data, machine learning, ontology model, urban data model
Procedia PDF Downloads 418494 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features
Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim
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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction
Procedia PDF Downloads 380493 Polarisation in Latin America: Examining the Role of Social Media in Ideological Positioning Based on 2018 Census Data
Authors: Sarah Ledoux
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This paper analyses the quantitative effects of political content consumption in social media platforms on self-reported ideological preference across the Latin American region. Initially praising the democratic potential of the internet and its social networking websites, digital politics scholars have transitioned their discourse to warning against the undemocratic side-effects it cultivates, such as hate speech, filter bubbles, and ideological polarisation. Holding technology solely responsible for political trends worldwide is an oversimplification of the factors influencing social change. Nonetheless, widespread use of social media in new democracies raises questions on the reproduction of recent trends that have been observed in the US and Western Europe. Through the analysis of ordered logistic regressions on data from the 2018 AmericasBarometer survey, this study examines the extent to which the relationship between the consumption of political content on social media is related to ideological polarisation in Latin America. The findings indicate that there is a close link between consumption of political information on social media, specifically on Facebook and WhatsApp, and ideological positioning on the extremes of the political left- and right-wings. This relation holds when controlling for individual-level demographic and attitudinal factors, as well as country-level effects. These results demonstrate with empirical evidence that viewing political content on social media has a significant positive effect on the likelihood that citizens position themselves on the extreme ends of the left-right ideological spectrum and implies that political polarisation is a phenomenon that accompanies politically driven social media use.Keywords: Latin America, polarisation, political consumption, political ideology, social media, survey
Procedia PDF Downloads 146492 Production and Distribution Network Planning Optimization: A Case Study of Large Cement Company
Authors: Lokendra Kumar Devangan, Ajay Mishra
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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.Keywords: production planning, mixed integer optimization, network model, network optimization
Procedia PDF Downloads 66491 The Effect of Conservative Tillage on Physical Properties of Soil and Yield of Rainfed Wheat
Authors: Abolfazl Hedayatipoor, Mohammad Younesi Alamooti
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In order to study the effect of conservative tillage on a number of physical properties of soil and the yield of rainfed wheat, an experiment in the form of a randomized complete block design (RCBD) with three replications was conducted in a field in Aliabad County, Iran. The study treatments included: T1) Conventional method, T2) Combined moldboard plow method, T3) Chisel-packer method, and T4) Direct planting method. During early October, the study soil was prepared based on these treatments in a field which was used for rainfed wheat farming in the previous year. The apparent specific gravity of soil, weighted mean diameter (WMD) of soil aggregates, soil mechanical resistance, and soil permeability were measured. Data were analyzed in MSTAT-C. Results showed that the tillage practice had no significant effect on grain yield (p < 0.05). Soil permeability was 10.9, 16.3, 15.7 and 17.9 mm/h for T1, T2, T3 and T4, respectively.Keywords: rainfed agriculture, conservative tillage, energy consumption, wheat
Procedia PDF Downloads 206490 Functionalized SPIO Conjugated with Doxorubicin for Tumor Diagnosis and Chemotherapy Enhanced by Applying Magnetic Fields
Authors: Po-Chin Liang, Yung-Chu Chen, Chi-Feng Chiang, Yun-Ping Lin, Wen-Yuan Hsieh, Win-Li Lin
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The aim of this study was to develop super paramagnetic iron oxide (SPIO) nano-particles comprised of a magnetic Fe3O4 core and a shell of aqueous stable self-doped polyethylene glycol (PEG) with a high loading of doxorubicin (SPIO-PEG-D) for tumor theranostics. The in-vivo MRI study showed that there was a stronger T2-weighted signal enhancement for the group under a magnetic field, and hence it indicated that this group had a better accumulation of SPIO-PEG than the group without a magnetic field. In the anticancer evaluation of SPIO-PEG-D, the group with a magnetic field displayed a significantly smaller tumor size than the group without. The overall results show that SPIO-PEG-D nanoparticles have the potential for the application of MRI/monitoring chemotherapy and the therapy can be locally enhanced by applying an external magnetic field.Keywords: super paramagnetic iron oxide nano particles, doxorubicin, chemotherapy, MRI, magnetic fields
Procedia PDF Downloads 599489 Ensemble-Based SVM Classification Approach for miRNA Prediction
Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam
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In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data
Procedia PDF Downloads 349488 An Accelerated Stochastic Gradient Method with Momentum
Authors: Liang Liu, Xiaopeng Luo
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In this paper, we propose an accelerated stochastic gradient method with momentum. The momentum term is the weighted average of generated gradients, and the weights decay inverse proportionally with the iteration times. Stochastic gradient descent with momentum (SGDM) uses weights that decay exponentially with the iteration times to generate the momentum term. Using exponential decay weights, variants of SGDM with inexplicable and complicated formats have been proposed to achieve better performance. However, the momentum update rules of our method are as simple as that of SGDM. We provide theoretical convergence analyses, which show both the exponential decay weights and our inverse proportional decay weights can limit the variance of the parameter moving directly to a region. Experimental results show that our method works well with many practical problems and outperforms SGDM.Keywords: exponential decay rate weight, gradient descent, inverse proportional decay rate weight, momentum
Procedia PDF Downloads 162487 Attribution of Strategic Motive, Business Efficiencies, Firm Economies, and Market Factors as Motivations of Restaurant Industry Vertical Integration Adoption: A Structural Equation Model
Authors: Sy, Melecio Jr
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The decision to adopt vertical integration (VI) is firm-specific, but there is a common practice among businesses in an industry to maximize the massive potential benefits of VI. This study aims to determine VI adoption in the restaurant industry in Davao City. Using a two-step sampling process, the study used a validated survey questionnaire among 264 restaurant owners and managers randomly selected and geographically classified. It is a quantitative study where the data were subjected to a structural equation model (SEM). The results revealed that VI is present but limited to procurement, production, restaurant services, and online marketing. Raw materials were outsourced while delivery to customers through third-party delivery services. VI slowly increased over ten years except for online marketing, which has grown significantly in a few years. The endogenous and exogenous variables were correlated and established the linear regression model. The SEM's best fit model revealed that strategic motives (SMOT) and market factors (MFAC) influenced VI adoption while MFAC is the best predictor. Favorable market factors may lead restaurants to adopt VI. It is, thus, recommended for restaurants to institutionalize strategic management, quantify the impact of double marginalization in future studies as a reason for VI and conduct this study during the new normal to see the influence of business efficiencies and firm economies on VI adoption.Keywords: business efficiencies, business management, davao city, firm economies, market factors, philippines, strategic motives, structural equation model, supply chain, vertical integration adoption
Procedia PDF Downloads 70486 Assessment of Work-Related Stress and Its Predictors in Ethiopian Federal Bureau of Investigation in Addis Ababa
Authors: Zelalem Markos Borko
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Work-related stress is a reaction that occurs when the work weight progress toward becoming excessive. Therefore, unless properly managed, stress leads to high employee turnover, decreased performance, illness and absenteeism. Yet, little has been addressed regarding work-related stress and its predictors in the study area. Therefore, the objective of this study was to assess stress prevalence and its predictors in the study area. To that effect, a cross-sectional study design was conducted on 281 employees from the Ethiopian Federal Bureau of Investigation by using stratified random sampling techniques. Survey questionnaire scales were employed to collect data. Data were analyzed by percentage, Pearson correlation coefficients, simple linear regression, multiple linear regressions, independent t-test and one-way ANOVA statistical techniques. In the present study13.9% of participants faced high stress, whereas 13.5% of participants faced low stress and the rest 72.6% of officers experienced moderate stress. There is no significant group difference among workers due to age, gender, marital status, educational level, years of service and police rank. This study concludes that factors such as role conflict, performance over-utilization, role ambiguity, and qualitative and quantitative role overload together predict 39.6% of work-related stress. This indicates that 60.4% of the variation in stress is explained by other factors, so other additional research should be done to identify additional factors predicting stress. To prevent occupational stress among police, the Ethiopian Federal Bureau of Investigation should develop strategies based on factors that will help to develop stress reduction management.Keywords: work-related stress, Ethiopian federal bureau of investigation, predictors, Addis Ababa
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