Search results for: time series regression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22472

Search results for: time series regression

21422 Effects of Handheld Video Games on Interpersonal Relationships: A Two-Wave Panel Study on Elementary School Students

Authors: Kanae Suzuki

Abstract:

Handheld video games are popular communication tools among Japanese elementary school students today. This study aims to examine the effects of the use of handheld video games on interpersonal relationships of the students in real and virtual worlds. A two-wave panel survey was conducted for students of ten elementary schools at an interval of approximately six months. The survey questionnaire included questions about the average amount of time spent playing a handheld video game during the past one month, the frequency of communication with players during game play, and the interpersonal relationships, such as the number of real and virtual friends the students have. A multiple regression model was constructed for 324 students to examine causal relationships. The results indicated that the more frequently the students communicated with other players while playing games, the number of the real friends tended to increase. In contrast, no significant effect of the total time spent playing games was found on interpersonal relationships. The findings suggested that communication during game play is an important factor for improving interpersonal relationships of this age group.

Keywords: communication, real friend, social adjustment, virtual friend

Procedia PDF Downloads 494
21421 A Case Comparative Study of Infant Mortality Rate in North-West Nigeria

Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

Abstract:

This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

Procedia PDF Downloads 335
21420 Stability Analysis and Experimental Evaluation on Maxwell Model of Impedance Control

Authors: Le Fu, Rui Wu, Gang Feng Liu, Jie Zhao

Abstract:

Normally, impedance control methods are based on a model that connects a spring and damper in parallel. The series connection, namely the Maxwell model, has emerged as a counterpart and draw the attention of robotics researchers. In the theoretical analysis, it turns out that the two pattern are both equivalents to some extent, but notable differences of response characteristics exist, especially in the effect of damping viscosity. However, this novel impedance control design is lack of validation on realistic robot platforms. In this study, stability analysis and experimental evaluation are achieved using a 3-fingered Barrett® robotic hand BH8-282 endowed with tactile sensing, mounted on a torque-controlled lightweight and collaborative robot KUKA® LBR iiwa 14 R820. Object handover and incoming objects catching tasks are executed for validation and analysis. Experimental results show that the series connection pattern has much better performance in natural impact or shock absorption, which indicate promising applications in robots’ safe and physical interaction with humans and objects in various environments.

Keywords: impedance control, Maxwell model, force control, dexterous manipulation

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21419 Evaluation of Mechanical Properties and Analysis of Rapidly Heat Treated M-42 High Speed Steel

Authors: R. N. Karthik Babu, R. Sarvesh, A. Rajendra Prasad, G. Swaminathan

Abstract:

M42 is a molybdenum-series high-speed alloy steel widely used because of its better hot-hardness and wear resistance. These steels are conventionally heat treated in a salt bath furnace with up to three stages of preheating with predetermined soaking and holding periods. Such methods often involve long periods of processing with a large amount of energy consumed. In this study, the M42 steel samples were heat-treated by rapidly heating the specimens to the austenising temperature of 1260 °C and cooled conventionally by quenching in a neutral salt bath at a temperature of 550 °C with the aid of a hybrid microwave furnace. As metals reflect microwaves, they cannot directly be heated up when placed in a microwave furnace. The technology used herein requires the specimens to be placed in a crucible lined with SiC which is a good absorber of microwaves and the SiC lining heats the metal through radiation which facilitates the volumetric heating of the metal. A sample of similar dimensions was heat treated conventionally and cooled in the same manner. Conventional tempering process was then carried out on both these samples and analysed for various parameters such as micro-hardness, processing time, etc. Microstructure analysis and scanning electron microscopy was also carried out. The objective of the study being that similar or better properties, with substantial time and energy saving and cost cutting are achievable by rapid heat treatment through hybrid microwave furnaces. It is observed that the heat treatment is done with substantial time and energy savings, and also with minute improvement in mechanical properties of the tool steel heat treated.

Keywords: rapid heating, heat treatment, metal processing, microwave heating

Procedia PDF Downloads 288
21418 Investigating the Effect of Study Plan and Homework on Student's Performance by Using Web Based Learning MyMathLab

Authors: Mohamed Chabi, Mahmoud I. Syam, Sarah Aw

Abstract:

In Summer 2012, the Foundation Program Unit of Qatar University has started implementing new ways of teaching Math by introducing MML (MyMathLab) as an innovative interactive tool to support standard teaching. In this paper, we focused on the effect of proper use of the Study Plan component of MML on student’s performance. Authors investigated the results of students of pre-calculus course during Fall 2013 in Foundation Program at Qatar University. The results showed that there is a strong correlation between study plan results and final exam results, also a strong relation between homework results and final exam results. In addition, the attendance average affected on the student’s results in general. Multiple regression is determined between passing rate dependent variable and study plan, homework as independent variable.

Keywords: MyMathLab, study plan, assessment, homework, attendance, correlation, regression

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21417 Mediterranean Diet, Duration of Admission and Mortality in Elderly, Hospitalized Patients: A Cross-Sectional Study

Authors: Christos Lampropoulos, Maria Konsta, Ifigenia Apostolou, Vicky Dradaki, Tamta Sirbilatze, Irini Dri, Christina Kordali, Vaggelis Lambas, Kostas Argyros, Georgios Mavras

Abstract:

Objectives: Mediterranean diet has been associated with lower incidence of cardiovascular disease and cancer. The purpose of our study was to examine the hypothesis that Mediterranean diet may protect against mortality and reduce admission duration in elderly, hospitalized patients. Methods: Sample population included 150 patients (78 men, 72 women, mean age 80±8.2). The following data were taken into account in analysis: anthropometric and laboratory data, dietary habits (MedDiet score), patients’ nutritional status [Mini Nutritional Assessment (MNA) score], physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission, compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and admission duration difference respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 30% per each unit increase of MedDiet score (OR=0.7, 95% CI:0.6-0.8, p < 0.0001). Patients with cancer-related admission were 37.7 times more likely to die, compared to those with infection (OR=37.7, 95% CI:4.4-325, p=0.001). According to multivariate linear regression analysis, admission duration was inversely related to Mediterranean diet, since it is decreased 0.18 days on average for each unit increase of MedDiet score (b:-0.18, 95% CI:-0.33 - -0.035, p=0.02). Additionally, the duration of current admission increased on average 0.83 days for each previous hospital admission (b:0.83, 95% CI:0.5-1.16, p<0.0001). The admission duration of patients with cancer was on average 4.5 days higher than the patients who admitted due to infection (b:4.5, 95% CI:0.9-8, p=0.015). Conclusion: Mediterranean diet adequately protects elderly, hospitalized patients against mortality and reduces the duration of hospitalization.

Keywords: Mediterranean diet, malnutrition, nutritional status, prognostic factors for mortality

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21416 A Data Driven Approach for the Degradation of a Lithium-Ion Battery Based on Accelerated Life Test

Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

Abstract:

Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

Procedia PDF Downloads 173
21415 Data Recording for Remote Monitoring of Autonomous Vehicles

Authors: Rong-Terng Juang

Abstract:

Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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21414 Scalable UI Test Automation for Large-scale Web Applications

Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

Abstract:

This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

Procedia PDF Downloads 111
21413 Can Exams Be Shortened? Using a New Empirical Approach to Test in Finance Courses

Authors: Eric S. Lee, Connie Bygrave, Jordan Mahar, Naina Garg, Suzanne Cottreau

Abstract:

Marking exams is universally detested by lecturers. Final exams in many higher education courses often last 3.0 hrs. Do exams really need to be so long? Can we justifiably reduce the number of questions on them? Surprisingly few have researched these questions, arguably because of the complexity and difficulty of using traditional methods. To answer these questions empirically, we used a new approach based on three key elements: Use of an unusual variation of a true experimental design, equivalence hypothesis testing, and an expanded set of six psychometric criteria to be met by any shortened exam if it is to replace a current 3.0-hr exam (reliability, validity, justifiability, number of exam questions, correspondence, and equivalence). We compared student performance on each official 3.0-hr exam with that on five shortened exams having proportionately fewer questions (2.5, 2.0, 1.5, 1.0, and 0.5 hours) in a series of four experiments conducted in two classes in each of two finance courses (224 students in total). We found strong evidence that, in these courses, shortening of final exams to 2.0 hrs was warranted on all six psychometric criteria. Shortening these exams by one hour should result in a substantial one-third reduction in lecturer time and effort spent marking, lower student stress, and more time for students to prepare for other exams. Our approach provides a relatively simple, easy-to-use methodology that lecturers can use to examine the effect of shortening their own exams.

Keywords: exam length, psychometric criteria, synthetic experimental designs, test length

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21412 Value Relevance of Accounting Information: A Study of Steel Sector in India

Authors: Pradyumna Mohanty

Abstract:

The paper aims to explore whether accounting information of Indian companies in the Steel sector are value relevant or not. Ohlson’s model which usually takes into consideration book value per share (BV) and earnings per share (EARN) has been used and the same has been expanded to include two more variables such as cash flow from operations (CFO) and return on equity (ROE). The data were collected from CMIE-Prowess data base in respect of BSE-listed steel companies and the time frame spans from 2010 to 2014. OLS regression has been used to test the value relevance of these accounting numbers. Results indicate that both CFO and BV are having significant influence on the stock price in two out of five years of study. But, BV is emerging as the most significant and highly value relevant of all the four variables during the entire period of study.

Keywords: value relevance, accounting information, book value per share, earnings per share

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21411 Impact of Trade Cooperation of BRICS Countries on Economic Growth

Authors: Svetlana Gusarova

Abstract:

The essential role in the recent development of world economy has led to the developing countries, notably to BRICS countries (Brazil, Russia, India, China, South Africa). Over the next 50 years the BRICS countries are expected to be the engines of global trade and economic growth. Trade cooperation of BRICS countries can enhance their economic development. BRICS countries were among Top 10 world exporters of office and telecom equipment, of textiles, of clothing, of iron and steel, of chemicals, of agricultural products, of automotive products, of fuel and mining products. China was one of the main trading partners of all BRICS countries, maintaining close relationship with all BRICS countries in the development of trade. Author analyzed trade complementarity of BRICS countries and revealed the high level of complementarity of their trade flows in connection with availability of specialization in different types of goods. The correlation and regression analysis of communication of Intra-BRICS merchandise turnover and their GDP (PPP) revealed very strong impact on the development of their economies.

Keywords: BRICS countries, trade cooperation, complementarity, regression analysis

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21410 Manufacturing Process and Cost Estimation through Process Detection by Applying Image Processing Technique

Authors: Chalakorn Chitsaart, Suchada Rianmora, Noppawat Vongpiyasatit

Abstract:

In order to reduce the transportation time and cost for direct interface between customer and manufacturer, the image processing technique has been introduced in this research where designing part and defining manufacturing process can be performed quickly. A3D virtual model is directly generated from a series of multi-view images of an object, and it can be modified, analyzed, and improved the structure, or function for the further implementations, such as computer-aided manufacturing (CAM). To estimate and quote the production cost, the user-friendly platform has been developed in this research where the appropriate manufacturing parameters and process detections have been identified and planned by CAM simulation.

Keywords: image processing technique, feature detections, surface registrations, capturing multi-view images, Production costs and Manufacturing processes

Procedia PDF Downloads 253
21409 Thermoregulatory Responses of Holstein Cows Exposed to Intense Heat Stress

Authors: Rodrigo De A. Ferrazza, Henry D. M. Garcia, Viviana H. V. Aristizabal, Camilla De S. Nogueira, Cecilia J. Verissimo, Jose Roberto Sartori, Roberto Sartori, Joao Carlos P. Ferreira

Abstract:

Environmental factors adversely influence sustainability in livestock production system. Dairy herds are the most affected by heat stress among livestock industries. This clearly implies in development of new strategies for mitigating heat, which should be based on physiological and metabolic adaptations of the animal. In this study, we incorporated the effect of climate variables and heat exposure time on the thermoregulatory responses in order to clarify the adaptive mechanisms for bovine heat dissipation under intense thermal stress induced experimentally in climate chamber. Non-lactating Holstein cows were contemporaneously and randomly assigned to thermoneutral (TN; n=12) or heat stress (HS; n=12) treatments during 16 days. Vaginal temperature (VT) was measured every 15 min with a microprocessor-controlled data logger (HOBO®, Onset Computer Corporation, Bourne, MA, USA) attached to a modified vaginal controlled internal drug release insert (Sincrogest®, Ourofino, Brazil). Rectal temperature (RT), respiratory rate (RR) and heart rate (HR) were measured twice a day (0700 and 1500h) and dry matter intake (DMI) was estimated daily. The ambient temperature and air relative humidity were 25.9±0.2°C and 73.0±0.8%, respectively for TN, and 36.3± 0.3°C and 60.9±0.9%, respectively for HS. Respiratory rate of HS cows increased immediately after exposure to heat and was higher (76.02±1.70bpm; P<0.001) than TN (39.70±0.71bpm), followed by rising of RT (39.87°C±0.07 for HS versus 38.56±0.03°C for TN; P<0.001) and VT (39.82±0.10°C for HS versus 38.26±0.03°C for TN; P<0.001). A diurnal pattern was detected, with higher (P<0.01) afternoon temperatures than morning and this effect was aggravated for HS cows. There was decrease (P<0.05) of HR for HS cows (62.13±0.99bpm) compared to TN (66.23±0.79bpm), but the magnitude of the differences was not the same over time. From the third day, there was a decrease of DMI for HS in attempt to maintain homeothermy, while TN cows increased DMI (8.27kg±0.33kg d-1 for HS versus 14.03±0.29kg d-1 for TN; P<0.001). By regression analysis, RT and RR better reflected the response of cows to changes in the Temperature Humidity Index and the effect of climate variables from the previous day to influence the physiological parameters and DMI was more important than the current day, with ambient temperature the most important factor. Comparison between acute (0 to 3 days) and chronic (13 to 16 days) exposure to heat stress showed decreasing of the slope of the regression equations for RR and DMI, suggesting an adaptive adjustment, however with no change for RT. In conclusion, intense heat stress exerted strong influence on the thermoregulatory mechanisms, but the acclimation process was only partial.

Keywords: acclimation, bovine, climate chamber, hyperthermia, thermoregulation

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21408 Fast High Voltage Solid State Switch Using Insulated Gate Bipolar Transistor for Discharge-Pumped Lasers

Authors: Nur Syarafina Binti Othman, Tsubasa Jindo, Makato Yamada, Miho Tsuyama, Hitoshi Nakano

Abstract:

A novel method to produce a fast high voltage solid states switch using Insulated Gate Bipolar Transistors (IGBTs) is presented for discharge-pumped gas lasers. The IGBTs are connected in series to achieve a high voltage rating. An avalanche transistor is used as the gate driver. The fast pulse generated by the avalanche transistor quickly charges the large input capacitance of the IGBT, resulting in a switch out of a fast high-voltage pulse. The switching characteristic of fast-high voltage solid state switch has been estimated in the multi-stage series-connected IGBT with the applied voltage of several tens of kV. Electrical circuit diagram and the mythology of fast-high voltage solid state switch as well as experimental results obtained are presented.

Keywords: high voltage, IGBT, solid state switch, bipolar transistor

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21407 Multilayer Perceptron Neural Network for Rainfall-Water Level Modeling

Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

Abstract:

Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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21406 Investigation of Complexity Dynamics in a DC Glow Discharge Magnetized Plasma Using Recurrence Quantification Analysis

Authors: Vramori Mitra, Bornali Sarma, Arun K. Sarma

Abstract:

Recurrence is a ubiquitous feature of any real dynamical system. The states in phase space trajectory of a system have an inherent tendency to return to the same state or its close state after certain time laps. Recurrence quantification analysis technique, based on this fundamental feature of a dynamical system, detects evaluation of state under variation of control parameter of the system. The paper presents the investigation of nonlinear dynamical behavior of plasma floating potential fluctuations obtained by using a Langmuir probe in different magnetic field under the variation of discharge voltages. The main measures of recurrence quantification analysis are considered as determinism, linemax and entropy. The increment of the DET and linemax variables asserts that the predictability and periodicity of the system is increasing. The variable linemax indicates that the chaoticity is being diminished with the slump of magnetic field while increase of magnetic field enhancing the chaotic behavior. Fractal property of the plasma time series estimated by DFA technique (Detrended fluctuation analysis) reflects that long-range correlation of plasma fluctuations is decreasing while fractal dimension is increasing with the enhancement of magnetic field which corroborates the RQA analysis.

Keywords: detrended fluctuation analysis, chaos, phase space, recurrence

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21405 One-Hit Multiple Instance Logistic Regression for Binary Classification and Its Application to Atomic Force Microscopy Images for Bladder Cancer Determination

Authors: Eugene Demidenko, John Seigne, Igor Sokolov

Abstract:

Multiple instance classification is a known machine learning tech-nique when only a bag of features is labeled. The method of binary multiple instance classification, termed multiple instance logistic regression (LR), received the most attention as a well-defined statistical model. This algorithm is realized in several computer languages, including R (milr) and MATLAB. This work suggests improving this model, which is called the one-hit multiple instance LR. Unlike the existing ap-proach, where unknown labels are treated as missing observations, our model directly implements the ML approach. As such, it is methodologically straightforward and computationally stable, especially when features are highly correlated and/or bags are heterogeneous. Since the one-hit LR admits a closed form for the log-likelihood function, an efficient Fisher scoring algorithm applies with the variances of the regres-sion coefficients computed through the inverse of the Fisher information matrix at the final iteration. Numerical experiments demonstrate the superiority of the one-hit LR in terms of regression coefficients and classification accuracy. Another advantage of our approach is developing the optimal probability threshold for classification (the traditional threshold equals 0 5). The one-hit LR is illustrated with a noninvasive bladder cancer identification where each patient, in the multiple instance terminol-ogy ’bag,’ contains feature images of multiple cells from a urine sample of the same individual. We show that the one-hit LR with two Atomic Force Microscopy (AFM) image features leads to a perfect (AUC=1) or almost perfect (AUC=0.978) classifica-tion of normal and cancer patients among 20 individuals. The -value 0.0018 confirms that the latter AUC is unlikely to be obtained by chance.

Keywords: AUC, classification accuracy, classification p-value, Fisher information, ML, ROC curve

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21404 Discrete State Prediction Algorithm Design with Self Performance Enhancement Capacity

Authors: Smail Tigani, Mohamed Ouzzif

Abstract:

This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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21403 Life in Bequia in the Era of Climate Change: Societal Perception of Adaptation and Vulnerability

Authors: Sherry Ann Ganase, Sandra Sookram

Abstract:

This study examines adaptation measures and factors that influence adaptation decisions in Bequia by using multiple linear regression and a structural equation model. Using survey data, the results suggest that households are knowledgeable and concerned about climate change but lack knowledge about the measures needed to adapt. The findings from the SEM suggest that a positive relationship exist between vulnerability and adaptation, vulnerability and perception, along with a negative relationship between perception and adaptation. This suggests that being aware of the terms associated with climate change and knowledge about climate change is insufficient for implementing adaptation measures; instead the risk and importance placed on climate change, vulnerability experienced with household flooding, drainage and expected threat of future sea level are the main factors that influence the adaptation decision. The results obtained in this study are beneficial to all as adaptation requires a collective effort by stakeholders.

Keywords: adaptation, Bequia, multiple linear regression, structural equation model

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21402 Switching of Series-Parallel Connected Modules in an Array for Partially Shaded Conditions in a Pollution Intensive Area Using High Powered MOSFETs

Authors: Osamede Asowata, Christo Pienaar, Johan Bekker

Abstract:

Photovoltaic (PV) modules may become a trend for future PV systems because of their greater flexibility in distributed system expansion, easier installation due to their nature, and higher system-level energy harnessing capabilities under shaded or PV manufacturing mismatch conditions. This is as compared to the single or multi-string inverters. Novel residential scale PV arrays are commonly connected to the grid by a single DC–AC inverter connected to a series, parallel or series-parallel string of PV panels, or many small DC–AC inverters which connect one or two panels directly to the AC grid. With an increasing worldwide interest in sustainable energy production and use, there is renewed focus on the power electronic converter interface for DC energy sources. Three specific examples of such DC energy sources that will have a role in distributed generation and sustainable energy systems are the photovoltaic (PV) panel, the fuel cell stack, and batteries of various chemistries. A high-efficiency inverter using Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs) for all active switches is presented for a non-isolated photovoltaic and AC-module applications. The proposed configuration features a high efficiency over a wide load range, low ground leakage current and low-output AC-current distortion with no need for split capacitors. The detailed power stage operating principles, pulse width modulation scheme, multilevel bootstrap power supply, and integrated gate drivers for the proposed inverter is described. Experimental results of a hardware prototype, show that not only are MOSFET efficient in the system, it also shows that the ground leakage current issues are alleviated in the proposed inverter and also a 98 % maximum associated driver circuit is achieved. This, in turn, provides the need for a possible photovoltaic panel switching technique. This will help to reduce the effect of cloud movements as well as improve the overall efficiency of the system.

Keywords: grid connected photovoltaic (PV), Matlab efficiency simulation, maximum power point tracking (MPPT), module integrated converters (MICs), multilevel converter, series connected converter

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21401 Finite Element Analysis of Hollow Structural Shape (HSS) Steel Brace with Infill Reinforcement under Cyclic Loading

Authors: Chui-Hsin Chen, Yu-Ting Chen

Abstract:

Special concentrically braced frames is one of the seismic load resisting systems, which dissipates seismic energy when bracing members within the frames undergo yielding and buckling while sustaining their axial tension and compression load capacities. Most of the inelastic deformation of a buckling bracing member concentrates in the mid-length region. While experiencing cyclic loading, the region dissipates most of the seismic energy being input into the frame. Such a concentration makes the braces vulnerable to failure modes associated with low-cycle fatigue. In this research, a strategy to improve the cyclic behavior of the conventional steel bracing member is proposed by filling the Hollow Structural Shape (HSS) member with reinforcement. It prevents the local section from concentrating large plastic deformation caused by cyclic loading. The infill helps spread over the plastic hinge region into a wider area hence postpone the initiation of local buckling or even the rupture of the braces. The finite element method is introduced to simulate the complicated bracing member behavior and member-versus-infill interaction under cyclic loading. Fifteen 3-D-element-based models are built by ABAQUS software. The verification of the FEM model is done with unreinforced (UR) HSS bracing members’ cyclic test data and aluminum honeycomb plates’ bending test data. Numerical models include UR and filled HSS bracing members with various compactness ratios based on the specification of AISC-2016 and AISC-1989. The primary variables to be investigated include the relative bending stiffness and the material of the filling reinforcement. The distributions of von Mises stress and equivalent plastic strain (PEEQ) are used as indices to tell the strengths and shortcomings of each model. The result indicates that the change of relative bending stiffness of the infill is much more influential than the change of material in use to increase the energy dissipation capacity. Strengthen the relative bending stiffness of the reinforcement results in additional energy dissipation capacity to the extent of 24% and 46% in model based on AISC-2016 (16-series) and AISC-1989 (89-series), respectively. HSS members with infill show growth in 𝜂Local Buckling, normalized energy cumulated until the happening of local buckling, comparing to UR bracing members. The 89-series infill-reinforced members have more energy dissipation capacity than unreinforced 16-series members by 117% to 166%. The flexural rigidity of infills should be less than 29% and 13% of the member section itself for 16-series and 89-series bracing members accordingly, thereby guaranteeing the spread over of the plastic hinge and the happening of it within the reinforced section. If the parameters are properly configured, the ductility, energy dissipation capacity, and fatigue-life of HSS SCBF bracing members can be improved prominently by the infill-reinforced method.

Keywords: special concentrically braced frames, HSS, cyclic loading, infill reinforcement, finite element analysis, PEEQ

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21400 An Assessment of Self-Perceived Health after the Death of a Spouse among the Elderly

Authors: Shu-Hsi Ho

Abstract:

The problems of aging and number of widowed peers gradually rise in Taiwan. It is worth to concern the related issues for elderly after the death of a spouse. Hence, this study is to examine the impact of spousal death on the surviving spouse’s self-perceived health and mental health for the elderly in Taiwan. A cross section data design and ordered logistic regression models are applied to investigate whether marriage is associated significantly to self-perceived health and mental health for the widowed older Taiwanese. The results indicate that widowed marriage shows significant negative effects on self-perceived health and mental health regardless of widows or widowers. Among them, widows might be more likely to show worse mental health than widowers. The belief confirms that marriage provides effective sources to promote self-perceived health and mental health, particularly for females. In addition, since the social welfare system is not perfect in Taiwan, the findings also suggest that family and social support reveal strongly association with the self-perceived health and mental health for the widows and widowers elderly.

Keywords: logistic regression models, self-perceived health, widow, widower

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21399 Disrupted or Discounted Cash Flow: Impact of Digitisation on Business Valuation

Authors: Matthias Haerri, Tobias Huettche, Clemens Kustner

Abstract:

This article discusses the impact of digitization on business valuation. In order to become and remain ‘digital’, investments are necessary whose return on investment (ROI) often remains vague. This uncertainty is contradictory for a valuation, that rely on predictable cash flows, fixed capital structures and the steady state. However digitisation does not make a company valuation impossible, but traditional approaches must be reconsidered. The authors identify four areas that are to be changing: (1) Tools instead of intuition - In the future, company valuation will neither be art nor science, but craft. This does not require intuition, but experience and good tools. Digital evaluation tools beyond Excel will therefore gain in importance. (2) Real-time instead of deadline - At present, company valuations are always carried out on a case-by-case basis and on a specific key date. This will change with the digitalization and the introduction of web-based valuation tools. Company valuations can thus not only be carried out faster and more efficiently, but can also be offered more frequently. Instead of calculating the value for a previous key date, current and real-time valuations can be carried out. (3) Predictive planning instead of analysis of the past - Past data will also be needed in the future, but its use will not be limited to monovalent time series or key figure analyses. With pictures of ‘black swans’ and the ‘turkey illusion’ it was made clear to us that we build forecasts on too few data points of the past and underestimate the power of chance. Predictive planning can help here. (4) Convergence instead of residual value - Digital transformation shortens the lifespan of viable business models. If companies want to live forever, they have to change forever. For the company valuation, this means that the business model valid on the valuation date only has a limited service life.

Keywords: business valuation, corporate finance, digitisation, disruption

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21398 Study of Suezmax Shuttle Tanker Energy Efficiency for Operations at the Brazilian Pre-Salt Region

Authors: Rodrigo A. Schiller, Rubens C. Da Silva, Kazuo Nishimoto, Claudio M. P. Sampaio

Abstract:

The need to reduce fossil fuels consumption due to the current scenario of trying to restrain global warming effects and reduce air pollution is dictating a series of transformations in shipping. This study introduces, at first, the changes of the regulatory framework concerning gas emissions control and fuel consumption efficiency on merchant ships. Secondly, the main operational procedures with high potential reduction of fuel consumption are discussed, with focus on existing vessels, using ship speed reduction procedure. This procedure shows the positive impacts on both operating costs reduction and also on energy efficiency increase if correctly applied. Finally, a numerical analysis of the fuel consumption variation with the speed was carried out for a Suezmax class oil tanker, which has been adapted to oil offloading operations for FPSOs in Brazilian offshore oil production systems. In this analysis, the discussions about the variations of vessel energy efficiency from small speed rate reductions and the possible applications of this improvement, taking into account the typical operating profile of the vessel in such a way to have significant economic impacts on the operation. This analysis also evaluated the application of two different numerical methods: one based only on regression equations produced by existing data, semi-empirical method, and another using a CFD simulations for estimating the hull shape parameters that are most relevant for determining fuel consumption, analyzing inaccuracies and impact on the final results.

Keywords: energy efficiency, offloading operations, speed reduction, Suezmax oil tanker

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21397 Assesment of Financial Performance: An Empirical Study of Crude Oil and Natural Gas Companies in India

Authors: Palash Bandyopadhyay

Abstract:

Background and significance of the study: Crude oil and natural gas is of crucial importance due to its increasing demand in India. The demand has been increased because of change of lifestyle overtime. Since India has poor utilization of oil production capacity, constantly the import of it has been increased progressively day by day. This ultimately hit the foreign exchange reserves of India, however it negatively affect the Indian economy as well. The financial performance of crude oil and natural gas companies in India has been trimmed down year after year because of underutilization of production capacity, enhancement of demand, change in life style, and change in import bill and outflows of foreign currencies. In this background, the current study seeks to measure the financial performance of crude oil and natural gas companies of India in the post liberalization period. Keeping in view of this, this study assesses the financial performance in terms of liquidity management, solvency, efficiency, financial stability, and profitability of the companies under study. Methodology: This research work is encircled on yearly ratio data collected from Centre for Monitoring Indian Economy (CMIE) Prowess database for the periods between 1993-94 and 2012-13 with 20 observations using liquidity, solvency and efficiency indicators, profitability indicators and financial stability indicators of all the major crude oil and natural gas companies in India. In the course of analysis, descriptive statistics, correlation statistics, and linear regression test have been utilized. Major findings: Descriptive statistics indicate that liquidity position is satisfactory in case of three crude oil and natural gas companies (Oil and Natural Gas Companies Videsh Limited, Oil India Limited and Selan exploration and transportation Limited) out of selected companies under study but solvency position is satisfactory only for one company (Oil and Natural Gas Companies Videsh Limited). However, efficiency analysis points out that Oil and Natural Gas Companies Videsh Limited performs effectively the management of inventory, receivables, and payables, but the overall liquidity management is not well. Profitability position is very much satisfactory in case of all the companies except Tata Petrodyne Limited, but profitability management is not satisfactory for all the companies under study. Financial stability analysis shows that all the companies are more dependent on debt capital, which bears a financial risk. Correlation and regression test results illustrates that profitability is positively and negatively associated with liquidity, solvency, efficiency, and financial stability indicators. Concluding statement: Management of liquidity and profitability of crude oil and natural gas companies in India should have been improved through controlling unnecessary imports in spite of the heavy demand of crude oil and natural gas in India and proper utilization of domestic oil reserves. At the same time, Indian government has to concern about rupee depreciation and interest rates.

Keywords: financial performance, crude oil and natural gas companies, India, linear regression

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21396 Air Access Liberalisation and Tourism Trade Evidence from a Sids

Authors: Seetanah Boopen, R. V. Sannassee

Abstract:

The objective of the present study is two-fold. Firstly, to assess the impact of air access liberalization on tourism demand for Mauritius and secondly to analyses the dual impact of the interplay between air access liberalization and marketing promotion efforts on tourism demand. Using an Autoregressive Distributed Lag model, the results suggest that air access liberalization is an important ingredient, albeit to a lesser extent as compared to other classical explanatory variables, of tourism demand. The results also highlight the fact that Mauritius is perceived as a luxurious destination and tourists are deemed price sensitive. Moreover, our dynamic approach interestingly confirms the presence of repeat tourism in the island. Finally, the findings also uncover the positive impact of the interplay between air access liberalization and marketing promotion efforts on fostering tourism demand.

Keywords: air access liberalization, ARDL, SIDS, time series

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21395 Circadian Clock and Subjective Time Perception: A Simple Open Source Application for the Analysis of Induced Time Perception in Humans

Authors: Agata M. Kołodziejczyk, Mateusz Harasymczuk, Pierre-Yves Girardin, Lucie Davidová

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Subjective time perception implies connection to cognitive functions, attention, memory and awareness, but a little is known about connections with homeostatic states of the body coordinated by circadian clock. In this paper, we present results from experimental study of subjective time perception in volunteers performing physical activity on treadmill in various phases of their circadian rhythms. Subjects were exposed to several time illusions simulated by programmed timing systems. This study brings better understanding for further improvement of of work quality in isolated areas. 

Keywords: biological clock, light, time illusions, treadmill

Procedia PDF Downloads 342
21394 Examining the Cognitive Abilities and Financial Literacy Among Street Entrepreneurs: Evidence From North-East, India

Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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21393 Calculation of Pressure-Varying Langmuir and Brunauer-Emmett-Teller Isotherm Adsorption Parameters

Authors: Trevor C. Brown, David J. Miron

Abstract:

Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

Procedia PDF Downloads 237