Search results for: proposed drought severity index
Commenced in January 2007
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Edition: International
Paper Count: 12795

Search results for: proposed drought severity index

12555 An Association between Stock Index and Macro Economic Variables in Bangladesh

Authors: Shamil Mardi Al Islam, Zaima Ahmed

Abstract:

The aim of this article is to explore whether certain macroeconomic variables such as industrial index, inflation, broad money, exchange rate and deposit rate as a proxy for interest rate are interlinked with Dhaka stock price index (DSEX index) precisely after the introduction of new index by Dhaka Stock Exchange (DSE) since January 2013. Bangladesh stock market has experienced rapid growth since its inception. It might not be a very well-developed capital market as compared to its neighboring counterparts but has been a strong avenue for investment and resource mobilization. The data set considered consists of monthly observations, for a period of four years from January 2013 to June 2018. Findings from cointegration analysis suggest that DSEX and macroeconomic variables have a significant long-run relationship. VAR decomposition based on VAR estimated indicates that money supply explains a significant portion of variation of stock index whereas, inflation is found to have the least impact. Impact of industrial index is found to have a low impact compared to the exchange rate and deposit rate. Policies should there aim to increase industrial production in order to enhance stock market performance. Further reasonable money supply should be ensured by authorities to stimulate stock market performance.

Keywords: deposit rate, DSEX, industrial index, VAR

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12554 Identifying and Quantifying Factors Affecting Traffic Crash Severity under Heterogeneous Traffic Flow

Authors: Praveen Vayalamkuzhi, Veeraragavan Amirthalingam

Abstract:

Studies on safety on highways are becoming the need of the hour as over 400 lives are lost every day in India due to road crashes. In order to evaluate the factors that lead to different levels of crash severity, it is necessary to investigate the level of safety of highways and their relation to crashes. In the present study, an attempt is made to identify the factors that contribute to road crashes and to quantify their effect on the severity of road crashes. The study was carried out on a four-lane divided rural highway in India. The variables considered in the analysis includes components of horizontal alignment of highway, viz., straight or curve section; time of day, driveway density, presence of median; median opening; gradient; operating speed; and annual average daily traffic. These variables were considered after a preliminary analysis. The major complexities in the study are the heterogeneous traffic and the speed variation between different classes of vehicles along the highway. To quantify the impact of each of these factors, statistical analyses were carried out using Logit model and also negative binomial regression. The output from the statistical models proved that the variables viz., horizontal components of the highway alignment; driveway density; time of day; operating speed as well as annual average daily traffic show significant relation with the severity of crashes viz., fatal as well as injury crashes. Further, the annual average daily traffic has significant effect on the severity compared to other variables. The contribution of highway horizontal components on crash severity is also significant. Logit models can predict crashes better than the negative binomial regression models. The results of the study will help the transport planners to look into these aspects at the planning stage itself in the case of highways operated under heterogeneous traffic flow condition.

Keywords: geometric design, heterogeneous traffic, road crash, statistical analysis, level of safety

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12553 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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12552 Prediction of Index-Mechanical Properties of Pyroclastic Rock Utilizing Electrical Resistivity Method

Authors: İsmail İnce

Abstract:

The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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12551 Overweight and Neurocognitive Functioning: Unraveling the Antagonistic Relationship in Adolescents

Authors: Swati Bajpai, S. P. K Jena

Abstract:

Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

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12550 Forecasting Models for Steel Demand Uncertainty Using Bayesian Methods

Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method

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12549 A Particle Swarm Optimal Control Method for DC Motor by Considering Energy Consumption

Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

Abstract:

In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control

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12548 Investigating Acute and Chronic Pain after Bariatric Surgery

Authors: Patti Kastanias, Wei Wang, Karyn Mackenzie, Sandra Robinson, Susan Wnuk

Abstract:

Obesity is a worldwide epidemic and is recognized as a chronic disease. Pain in the obese individual is a multidimensional issue. An increase in BMI is positively correlated with pain incidence and severity, especially in central obesity where individuals are twice as likely to have chronic pain. Both obesity and chronic pain are also associated with mood disorders. Pain is worse among obese individuals with depression and anxiety. Bariatric surgery provides patients with an effective solution for long-term weight loss and associated health problems. However, not much is known about acute and chronic pain after bariatric surgery and its contributing factors, including mood disorders. Nurse practitioners (NPs) at one large multidisciplinary bariatric surgery centre led two studies to examine acute and chronic pain and pain management over time after bariatric surgery. The purpose of the initial study was to examine the incidence and severity of acute and chronic pain after bariatric surgery. The aim of the secondary study was to further examine chronic pain, specifically looking at psychological factors that influence severity or incidence of both neuropathic and somatic pain as well as changes in opioid use. The initial study was a prospective, longitudinal study where patients having bariatric surgery at one surgical center were followed up to 6 months postop. Data was collected at 7 time points using validated instruments for pain severity, pain interference, and patient satisfaction. In the second study, subjects were followed longitudinally starting preoperatively and then at 6 months and 1 year postoperatively to capture changes in chronic pain and influencing variables over time. Valid and reliable instruments were utilized for all major study outcomes. In the first study, there was a trend towards decreased acute post-operative pain over time. The incidence and severity of chronic pain was found to be significantly reduced at 6 months post bariatric surgery. Interestingly, interference of chronic pain in daily life such as normal work, mood, and walking ability was significantly improved at 6 months postop however; this was not the case with sleep. Preliminary results of the secondary study indicate that pain severity, pain interference, anxiety and depression are significantly improved at 6 months postoperatively. In addition, preoperative anxiety, depression and emotional regulation were predictive of pain interference, but not pain severity. The results of our regression analyses provide evidence for the impact of pre-existing psychological factors on pain, particularly anxiety in obese populations.

Keywords: bariatric surgery, mood disorders, obesity, pain

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12547 Correlation between the Sowing Date and Yield of Maize on Chernozem Soil, in Connection with the Leaf Area Index and Photosynthesis

Authors: Enikő Bene

Abstract:

Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012-2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields

Keywords: sowing date, hybrid, leaf area index, photosynthetic capacity

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12546 Compact Low Loss Design of SOI 1x2 Y-Branch Optical Power Splitter with S-Bend Waveguide and Study on the Variation of Transmitted Power with Various Waveguide Parameters

Authors: Nagaraju Pendam, C. P. Vardhani

Abstract:

A simple technology–compatible design of silicon-on-insulator based 1×2 optical power splitter is proposed. For developing large area Opto-electronic Silicon-on-Insulator (SOI) devices, the power splitter is a key passive device. The SOI rib- waveguide dimensions (height, width, and etching depth, refractive indices, length of waveguide) leading simultaneously to single mode propagation. In this paper a low loss optical power splitter is designed by using R Soft cad tool and simulated by Beam propagation method, here s-bend waveguides proposed. We concentrate changing the refractive index difference, branching angle, width of the waveguide, free space wavelength of the waveguide and observing transmitted power, effective refractive index in the designed waveguide, and choosing the best simulated results to be fabricated on silicon-on insulator platform. In this design 1550 nm free spacing are used.

Keywords: beam propagation method, insertion loss, optical power splitter, rib waveguide, transmitted power

Procedia PDF Downloads 639
12545 Parenting a Child with Mental Health Problems: The Role of Self-compassion

Authors: Vered Shenaar-Golan, Nava Wald, Uri Yatzkar

Abstract:

Background: Parenting children with mental health problems poses multiple challenges, including coping with difficult behavior and negative child emotions. The impact on parents includes financial strain, negative social stigma, and negative feelings of guilt or blame, resulting in significant stress and lower levels of well-being. Given findings that self-compassion plays a significant role in reducing stress and improving well-being, the current study examined the role of self-compassion in the experience of parents raising a child with mental health problems. The study tested (1) whether child behavioral/emotional problem severity is associated with higher parental stress and lower parental well-being; (2) whether self-compassion is associated with lower parental stress and higher parental well-being; and (3) whether self-compassion is a stronger predictor of parental stress and well-being than child behavioral/emotional problem severity. Methods: Three hundred and six mothers and two hundred and fifty-six fathers of children attending a hospital child and adolescent psychiatric center were assessed at admission. Consenting parents completed four questionnaires: Child Strength and Difficulty – parent version, Self-compassion, Parent Feeling Inventory, and Well-Being. Results: Child behavioral/emotional problem severity was associated with higher parental stress and lower parental well-being, and self-compassion was a stronger predictor of parental stress and well-being levels than child behavioral/emotional problem severity. For children with internalizing but not externalizing behavioral/emotional problems, parental self-compassion was the only predictor of parental well-being beyond the severity of child behavioral/emotional problems. Conclusions: Cultivating self-compassion is important in reducing parental stress and increasing parental well-being, particularly with internalizing presentations, and should be considered when designing therapeutic interventions for parents.

Keywords: parenting children with mental health problems, self-compassion, parental stress, feelings, well-being

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12544 Development of Sleep Quality Index Using Heart Rate

Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

Abstract:

Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: sleep, sleep quality, heart rate, statistical analysis

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12543 Market Index Trend Prediction using Deep Learning and Risk Analysis

Authors: Shervin Alaei, Reza Moradi

Abstract:

Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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12542 A Basic Understanding of Viral Disease and Education Level Influences Disease Risk Perception, Disease Severity Perception, and Mask Wearing Behavior During the COVID-19 Pandemic

Authors: Ilse Kreme

Abstract:

To the best of this author’s knowledge, no studies have been identified on the connection between a refusal to engage in health-protective behaviors and a basic understanding of viral biology among community college students, faculty, and staff during the COVID-19 pandemic. Lack of scientific knowledge could prevent understanding of why these behaviors are important to prevent the community spread of COVID-19, even when they are not shown to offer much individual protection. In this study, a possible correlation was examined between a basic knowledge level of viral disease that comes from having taken a college biology course and disease perceptions of COVID-19. In particular, disease risk perception, disease severity percept and mask-wearing behaviors were examined as they correlated with having taken an undergraduate biology course. The effect of covariates of age, gender, and education level were investigated along with the main dependent variables. A representative sample of the population included students, faculty, and staff at Paradise Valley Community College (PVCC) in Phoenix, Arizona. Participants were recruited by an email sent to all students, faculty, and staff at PVCC using an all-college email distribution. Disease risk and severity perception were assessed with the Brief Illness Perception Questionnaire 5 (BIP-Q5), which was modified to include questions measuring participant age, education level, and whether they took or ever took a college biology course. Two additional questions measured compliance of willingness to wear a face mask. The results showed an effect of gender on mask-wearing behavior and a correlation between having taken a biology course and disease severity perception. No differences were seen in mask-wearing behavior and disease risk perception as a result of having taken a biology course. These findings suggest that taking an undergraduate biology course leads to a greater awareness of COVID-19 disease severity through an understanding of the basic biological principles of viral disease transmission. The results can be used to modify existing health education strategies. Further research is needed on how to best reach target audiences in all education brackets.

Keywords: COVID-19, education, gender, mask wearing, disease risk perception, disease severity perception

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12541 Pavement Maintenance and Rehabilitation Scheduling Using Genetic Algorithm Based Multi Objective Optimization Technique

Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

Abstract:

This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

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12540 Application of Benford's Law in Analysis of Frankfurt Stock Exchange Index (DAX) Percentage Changes

Authors: Mario Zgela

Abstract:

Application of Benford’s Law is very rarely covered in the field of stock market analysis, especially in percentage change of stock market indices. Deutscher Aktien IndeX (DAX) is very important stock market index of Frankfurt Deutsche Börse which serves as underlying basis for large number of financial instruments. It is calculated for selected 30 German blue chips stocks. In this paper, Benford's Law first digit test is applied on 10 year DAX daily percentage changes in order to check compliance. Deviations of 10 year DAX percentage changes set as well as distortions of certain subsets from Benford's Law distribution are detected. It is possible that deviations are the outcome of speculations; and psychological influence should not be eliminated.

Keywords: Benford's Law, DAX, index percentage changes, stock market

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12539 Measuring Development through Extreme Observations: An Archetypal Analysis Approach to Index Construction

Authors: Claudeline D. Cellan

Abstract:

Development is multifaceted, and efforts to hasten growth in all these facets have been gaining traction in recent years. Thus, producing a composite index that is reflective of these multidimensional impacts captures the interests of policymakers. The problem lies in going through a mixture of theoretical, methodological and empirical decisions and complexities which, when done carelessly, can lead to inconsistent and unreliable results. This study looks into index computation from a different and less complex perspective. Borrowing the idea of archetypes or ‘pure types’, archetypal analysis looks for points in the convex hull of the multivariate data set that captures as much information in the data as possible. The archetypes or 'pure types' are estimated such that they are convex combinations of all the observations, which in turn are convex combinations of the archetypes. This ensures that the archetypes are realistically observable, therefore achievable. In the sense of composite indices, we look for the best among these archetypes and use this as a benchmark for index computation. Its straightforward and simplistic approach does away with aggregation and substitutability problems which are commonly encountered in index computation. As an example of the application of archetypal analysis in index construction, the country data for the Human Development Index (HDI 2017) of the United Nations Development Programme (UNDP) is used. The goal of this exercise is not to replicate the result of the UNDP-computed HDI, but to illustrate the usability of archetypal analysis in index construction. Here best is defined in the context of life, education and gross national income sub-indices. Results show that the HDI from the archetypal analysis has a linear relationship with the UNDP-computed HDI.

Keywords: archetypes, composite index, convex combination, development

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12538 Predicting COVID-19 Severity Using a Simple Parameters in Resource-Limited Settings

Authors: Sireethorn Nimitvilai, Ussanee Poolvivatchaikarn, Nuchanart Tomeun

Abstract:

Objective: To determine the simple laboratory parameters to predict disease severity among COVID-19 patients in resource-limited settings. Material and methods: A retrospective cohort study was conducted at Nakhonpathom Hospital, a 722-bed tertiary care hospital, with an average of 50,000 admissions per year, during April 15 and May 15, 2021. Eligible patients were adults aged ≥ 15 years who were hospitalized with COVID-19. Baseline characteristics, comorbid conditions ad laboratory findings at admission were collected. Predictive factors for severe COVID-19 infection were analyzed. Result: There were 207 patients (79 male and 128 female) and the mean age was 46.7 (16.8) years. Of these, 39 cases (18.8%) were severe and 168 (81.2%) cases were non-severe. Factors associated with severe COVID-19 were neutrophil to lymphocyte ratio ≥ 4 (OR 8.1, 95%CI 2.3-20.3, P < 0.001) and C-reactive protein to albumin ratio ≥ 10 (OR 3.49, 95%CI 1.3-9.1, p 0.01). Conclusions: Complete blood counts, C-reactive protein and albumin are simple, inexpensive, widely available tests and can be used to predict severe COVID-19 in resource-limited settings.

Keywords: COVID-19, predictor of severity, resource-limiting settings, simple laboratory parameters

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12537 Some Conjectures and Programs about Computing the Detour Index of Molecular Graphs of Nanotubes

Authors: Shokofeh Ebrtahimi

Abstract:

Let G be the chemical graph of a molecule. The matrix D = [dij ] is called the detour matrix of G, if dij is the length of longest path between atoms i and j. The sum of all entries above the main diagonal of D is called the detour index of G.Chemical graph theory is the topology branch of mathematical chemistry which applies graph theory to mathematical modelling of chemical phenomena.[1] The pioneers of the chemical graph theory are Alexandru Balaban, Ante Graovac, Ivan Gutman, Haruo Hosoya, Milan Randić and Nenad TrinajstićLet G be the chemical graph of a molecule. The matrix D = [dij ] is called the detour matrix of G, if dij is the length of longest path between atoms i and j. The sum of all entries above the main diagonal of D is called the detour index of G. In this paper, a new program for computing the detour index of molecular graphs of nanotubes by heptagons is determineded. Some Conjectures about detour index of Molecular graphs of nanotubes is included.

Keywords: chemical graph, detour matrix, Detour index, carbon nanotube

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12536 Efficacy and Safety of Electrical Vestibular Stimulation on Adults with Symptoms of Insomnia: A Double-Blind, Randomized, Sham-Controlled Trial

Authors: Teris Cheung, Joyce Yuen Ting Lam, Kwan Hin Fong, Calvin Pak-Wing Cheng, Julie Sittlington, Yu-Tao Xiang, Tim Man Ho Li

Abstract:

Insomnia is one of the most common health problems in the general population. Insomnia can be acute, intermittent, and become chronic, often due to comorbidity with other physical and mental health conditions. Although there are conventional pharmaceutical and psychotherapeutic treatments to treat symptoms of insomnia, however; there is no robust and novel randomized controlled trial (RCT) using transdermal neurostimulation on individuals with insomnia symptoms. This gives us the impetus to execute the first nationwide RCT. Aim: To evaluate the efficacy of Electrical Vestibular Stimulation (VeNS) on individuals with insomnia in Hong Kong. Design: This study was a two-armed, double blinded, randomized, sham-controlled trial. Sampling: 60 community-dwelling adults aged 18 and 60 years with moderate insomnia symptoms or above (Insomnia Severity Index > 14) were recruited. All subjects were computerized randomized into either the active VeNS group or the sham VeNS group on a 1:1 ratio. Intervention: All participants received a home-use VeNS device and used 30-min VeNS sessions during five consecutive days across a 4-week period (total treatment hours: 10). Baseline measurements and post-VeNS evaluation of the psychological outcomes, including 1) insomnia severity, 2) sleep quality, and 3) quality of life were investigated. The short-and long-term sustainability of the VeNS intervention was assessed immediately after poststim and at a 1-month and 3-month follow-up period. Data analysis: A mixed GEE model was used to analyze the repeated measures data. Missing data were managed by multiple imputations. The level of significance was set to p < 0.05. Significance of the study: This is the first trial to examine the efficacy and safety of VeNS among adults with insomnia symptoms in Hong Kong. Findings that emerged were used to determine whether this VeNS device can be considered a self-help technological device to reduce the severity of insomnia in the community setting and to reduce the global disease burden. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT04452981.

Keywords: adults, insomnia, neuromodulation, rct, vestibular stimulation

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12535 Semantic Indexing Improvement for Textual Documents: Contribution of Classification by Fuzzy Association Rules

Authors: Mohsen Maraoui

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In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

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12534 Bystander Perceived Severity on Traditional versus Cyber Bullying

Authors: C. Smith, T. Goga, T. Hancock

Abstract:

Bullying has been an increasingly prevalent problem among society for decades. Approximately one out of every four students report being bullied at least once during the school year. Additionally, these instances of bullying are often witnessed but not reported by the bystanders, which could be dependent on the type of bullying situation. Thus, the present study aims to investigate any possible perceptual differences which may exist between traditional bullying (i.e., face to face) and cyberbullying from the bystander’s point of view. Undergraduate students were given a bullying scenario to read from either the traditional condition or the cyber condition. They were then asked to rate how severe they perceived this behavior on a Likert based scale. Participants were also asked if they would intervene (yes or no) and what their individual response would be to the witnessed behavior (report/ignore/confront/other). Results indicated that, while there was no significant difference in perceived severity between the two bullying conditions, there was a significant difference in whether or not participants would intervene between the two types of scenarios. A significant effect was also found between the scenarios for response type. Together, these findings suggest that even though individuals may not be aware of how severe they perceive certain bullying behaviors, the responses they exhibit might suggest otherwise.

Keywords: bullying, bystander, cyber, severity, traditional

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12533 Critical Thinking Index of College Students

Authors: Helen Frialde-Dupale

Abstract:

Critical thinking Index (CTI) of 150 third year college students from five State Colleges and Universities (SUCs) in Region I were determined. Only students with Grade Point Average (GPA) of at least 2.0 from four general classification of degree courses, namely: Education, Arts and Sciences, Engineering and Agriculture were included. Specific problem No.1 dealt with the profile variables, namely: age, sex, degree course, monthly family income, number of siblings, high school graduated from, grade point average, personality type, highest educational attainment of parents, and occupation of parents. Problem No. 2 determined the critical thinking index among the respondents. Problem No. 3 investigated whether or not there are significant differences in the critical thinking index among the respondents across the profile variables. While problem No.4 determined whether or not there are significant relationship between the critical thinking index and selected profile variables, namely: age, monthly family income, number of siblings, and grade point average of the respondents. Finally, on problem No. 5, the critical thinking instrument which obtained the lowest rates, were used as basis for outlining an intervention program for enhancing critical thinking index (CTI) of students. The following null hypotheses were tested at 0.05 level of significance: there are no significant differences in the critical thinking index of the third college students across the profile variables; there are no significant relationships between the critical thinking index of the respondents and selected variables, namely: age, monthly family income, number of siblings, and grade point average.

Keywords: attitude as critical thinker, critical thinking applied, critical thinking index, self-perception as critical thinker

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12532 Determining a Bilingualism Index: Evidence From Lebanese Control Bilinguals

Authors: Rania Kassir, Christophe Dos Santos, Halim Abboud, Olivier Godefroy

Abstract:

The ability to communicate in at least two different languages is shared by a growing number of humans. Recently, many researchers have been studying the elderly bilingual population around the world in neuroscience, and yet, until today there’s no accurate nor universal measure or methodology used to examine bilingualism across these studies which constitute a real challenge for results generalization. This study contributes to the quest of a multidimensional bilingualism index and language proficiency literature by investigating a new bilingualism index from a reliable subjective questionnaire the Language Experience and Proficiency Questionnaire (LEAP-Q), multi-linguistic tests, and a diverse bilingual population all featured in one analysis and one index. One hundred Lebanese subjects aged between 55 and 92 years old divided into three different bilingualism subgroups (Arabic prominent, balanced, and French prominent) were recruited and underwent the LEAP-Q with a set of linguistic and cognitive tests. The analysis of the collected data led to the creation of a robust bilingualism index from speaking and oral understanding scores that underline specifically bilingualism subtype according to cutoffs scored. The practice implications of this index, particularly its use within bilingual populations, are addressed in the conclusion of this work.

Keywords: bilingualism, language dominance, bilingualism index, balanced bilingualism, Arabic first language, Lebanese, Arabic-French bilingualism

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12531 Vegetation Index-Deduced Crop Coefficient of Wheat (Triticum aestivum) Using Remote Sensing: Case Study on Four Basins of Golestan Province, Iran

Authors: Hoda Zolfagharnejad, Behnam Kamkar, Omid Abdi

Abstract:

Crop coefficient (Kc) is an important factor contributing to estimation of evapotranspiration, and is also used to determine the irrigation schedule. This study investigated and determined the monthly Kc of winter wheat (Triticum aestivum L.) using five vegetation indices (VIs): Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Soil Adjusted Vegetation Index (SAVI), Infrared Percentage Vegetation Index (IPVI), and Ratio Vegetation Index (RVI) of four basins in Golestan province, Iran. 14 Landsat-8 images according to crop growth stage were used to estimate monthly Kc of wheat. VIs were calculated based on infrared and near infrared bands of Landsat 8 images using Geographical Information System (GIS) software. The best VIs were chosen after establishing a regression relationship among these VIs with FAO Kc and Kc that was modified for the study area by the previous research based on R² and Root Mean Square Error (RMSE). The result showed that local modified SAVI with R²= 0.767 and RMSE= 0.174 was the best index to produce monthly wheat Kc maps.

Keywords: crop coefficient, remote sensing, vegetation indices, wheat

Procedia PDF Downloads 377
12530 Sensitive Analysis of the ZF Model for ABC Multi Criteria Inventory Classification

Authors: Makram Ben Jeddou

Abstract:

The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

Procedia PDF Downloads 477
12529 Comparative Germination Studies in Mature Seeds of Haloxylon Salicornicum

Authors: Laila Almulla

Abstract:

As native plants are better adapted to the local environment, can endure long spells of drought, withstand high soil salinity levels and provide a more natural effect to landscape projects, their use in landscape projects are gaining popularity. Standardization of seed germination methods and raising the hardened plants of selected native plants for their use in landscape projects will both conserve natural resources and produce sustainable greenery. In the present study, Haloxylon salicornicum, a perennial herb with a potential use for urban greenery was selected for seed germination tests as there is an urgent need to mass multiply them for their large-scale use. Among the nine treatments tried with different concentrations of gibberelic acid (GA3) and dry heat, the seeds responded with treatments when the wings were removed. The control as well as 250 GA3 treatments produced the maximum germination of 86%.

Keywords: dormancy, gibberelic acid, germination trays , vigor index

Procedia PDF Downloads 374
12528 Molecular Diagnosis of a Virus Associated with Red Tip Disease and Its Detection by Non Destructive Sensor in Pineapple (Ananas comosus)

Authors: A. K. Faizah, G. Vadamalai, S. K. Balasundram, W. L. Lim

Abstract:

Pineapple (Ananas comosus) is a common crop in tropical and subtropical areas of the world. Malaysia once ranked as one of the top 3 pineapple producers in the world in the 60's and early 70's, after Hawaii and Brazil. Moreover, government’s recognition of the pineapple crop as one of priority commodities to be developed for the domestics and international markets in the National Agriculture Policy. However, pineapple industry in Malaysia still faces numerous challenges, one of which is the management of disease and pest. Red tip disease on pineapple was first recognized about 20 years ago in a commercial pineapple stand located in Simpang Renggam, Johor, Peninsular Malaysia. Since its discovery, there has been no confirmation on its causal agent of this disease. The epidemiology of red tip disease is still not fully understood. Nevertheless, the disease symptoms and the spread within the field seem to point toward viral infection. Bioassay test on nucleic acid extracted from the red tip-affected pineapple was done on Nicotiana tabacum cv. Coker by rubbing the extracted sap. Localised lesions were observed 3 weeks after inoculation. Negative staining of the fresh inoculated Nicotiana tabacum cv. Coker showed the presence of membrane-bound spherical particles with an average diameter of 94.25nm under transmission electron microscope. The shape and size of the particles were similar to tospovirus. SDS-PAGE analysis of partial purified virions from inoculated N. tabacum produced a strong and a faint protein bands with molecular mass of approximately 29 kDa and 55 kDa. Partial purified virions of symptomatic pineapple leaves from field showed bands with molecular mass of approximately 29 kDa, 39 kDa and 55kDa. These bands may indicate the nucleocapsid protein identity of tospovirus. Furthermore, a handheld sensor, Greenseeker, was used to detect red tip symptoms on pineapple non-destructively based on spectral reflectance, measured as Normalized Difference Vegetation Index (NDVI). Red tip severity was estimated and correlated with NDVI. Linear regression models were calibrated and tested developed in order to estimate red tip disease severity based on NDVI. Results showed a strong positive relationship between red tip disease severity and NDVI (r= 0.84).

Keywords: pineapple, diagnosis, virus, NDVI

Procedia PDF Downloads 762
12527 Mine Production Index (MPi): New Method to Evaluate Effectiveness of Mining Machinery

Authors: Amol Lanke, Hadi Hoseinie, Behzad Ghodrati

Abstract:

OEE has been used in many industries as measure of performance. However due to limitations of original OEE, it has been modified by various researchers. OEE for mining application is special version of classic equation, carries these limitation over. In this paper it has been aimed to modify the OEE for mining application by introducing the weights to the elements of it and termed as Mine Production index (MPi). As a special application of new index MPi shovel has been developed by team of experts and researchers for evaluating the shovel effectiveness. Based on analysis, utilization followed by performance and availability were ranked in this order. To check the applicability of this index, a case study was done on four electrical and one hydraulic shovel in a Swedish mine. The results shows that MPishovelcan properly evaluate production effectiveness of shovels and determine effectiveness values in optimistic view compared to OEE. MPi with calculation not only give the effectiveness but also can predict which elements should be focused for improving the productivity.

Keywords: mining, overall equipment efficiency (OEE), mine production index, shovels

Procedia PDF Downloads 434
12526 Multistage Data Envelopment Analysis Model for Malmquist Productivity Index Using Grey's System Theory to Evaluate Performance of Electric Power Supply Chain in Iran

Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

Abstract:

Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain

Procedia PDF Downloads 120