Search results for: multivariate statistical
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4403

Search results for: multivariate statistical

3983 Statistical Optimization and Production of Rhamnolipid by P. aeruginosa PAO1 Using Prickly Pear Peel as a Carbon Source

Authors: Mostafa M. Abo Elsoud, Heba I. Elkhouly, Nagwa M. Sidkey

Abstract:

Production of rhamnolipids by Pseudomonas aeruginosa has attracted a growing interest during the last few decades due to its high productivity compared with other microorganisms. In the current work, rhamnolipids production by P. aeruginosa PAO1 was statistically modeled using Taguchi orthogonal array, numerically optimized and validated. Prickly Pear Peel (Opuntia ficus-indica) has been used as a carbon source for production of rhamnolipid. Finally, the optimum conditions for rhamnolipid production were applied in 5L working volume bioreactors at different aerations, agitation and controlled pH for maximum rhamnolipid production. In addition, kinetic studies of rhamnolipids production have been reported. At the end of the batch bioreactor optimization process, rhamnolipids production by P. aeruginosa PAO1 has reached the worldwide levels and can be applied for its industrial production.

Keywords: rhamnolipids, pseudomonas aeruginosa, statistical optimization, tagushi, opuntia ficus-indica

Procedia PDF Downloads 166
3982 Factors Influencing the Enjoyment and Performance of Students in Statistics Service Courses: A Mixed-Method Study

Authors: Wilma Coetzee

Abstract:

Statistics lecturers experience that many students who are taking a service course in statistics do not like statistics. Students in these courses tend to struggle and do not perform well. This research takes a look at the student’s perspective, with the aim to determine how to change the teaching of statistics so that students will enjoy it more and perform better. Questionnaires were used to determine the perspectives of first year service statistics students at a South African university. Factors addressed included motivation to study, attitude toward statistics, statistical anxiety, mathematical abilities and tendency to procrastinate. Logistic regression was used to determine what contributes to students performing badly in statistics. The results show that the factors that contribute the most to students performing badly are: statistical anxiety, not being motivated and having had mathematical literacy instead of mathematics in secondary school. Two open ended questions were included in the questionnaire: 'I will enjoy statistics more if…' and 'I will perform better in statistics if…'. The answers to these questions were analyzed using qualitative methods. Frequent themes were identified for each of the questions. A simulation study incorporating bootstrapping was done to determine the saturation of the themes. The majority of the students indicated that they would perform better in statistics if they studied more, managed their time better, had a flare for mathematics and if the lecturer was able to explain difficult concepts better. They also want more active learning. To ensure that students enjoy statistics more, they want an active learning experience. They want fun activities, more interaction with the lecturer and with one another, more computer based problems, and more challenges. They want a better understanding of the subject, want to understand the relevance of statistics to their future career and want excellent lecturers. These findings can be used to direct the improvement of the tuition of statistics.

Keywords: active learning, performance in statistics, statistical anxiety, statistics education

Procedia PDF Downloads 140
3981 Time-Domain Analysis of Pulse Parameters Effects on Crosstalk in High-Speed Circuits

Authors: Loubna Tani, Nabih Elouzzani

Abstract:

Crosstalk among interconnects and printed-circuit board (PCB) traces is a major limiting factor of signal quality in high-speed digital and communication equipments especially when fast data buses are involved. Such a bus is considered as a planar multiconductor transmission line. This paper will demonstrate how the finite difference time domain (FDTD) method provides an exact solution of the transmission-line equations to analyze the near end and the far end crosstalk. In addition, this study makes it possible to analyze the rise time effect on the near and far end voltages of the victim conductor. The paper also discusses a statistical analysis, based upon a set of several simulations. Such analysis leads to a better understanding of the phenomenon and yields useful information.

Keywords: multiconductor transmission line, crosstalk, finite difference time domain (FDTD), printed-circuit board (PCB), rise time, statistical analysis

Procedia PDF Downloads 422
3980 Object-Oriented Multivariate Proportional-Integral-Derivative Control of Hydraulic Systems

Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

Abstract:

This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation

Procedia PDF Downloads 337
3979 An Investigation into the Correlation between Music Preferences and Emotional Regulation in Military Cadets

Authors: Chiu-Pin Wei

Abstract:

This research aims to explore the impact of music preferences on the emotional well-being of military academy students, recognizing the potential long-term implications for their high-stress careers post-graduation. Given the significance of positive emotion regulation in military personnel, this study focuses on understanding the types of music preferred by military cadets and analyzing how these preferences correlate with their emotional states. The study employs a quantitative approach, utilizing the Music Category Scale and Mood Scale to collect data. Statistical tools, such as Statistical Product and Service Solutions (SPSS), are employed for inferential analysis, including t-tests for emotional responses to instrumental and vocal music, one-way variance analysis for different demographic factors (grades, genders, and music listening frequencies), and Pearson's correlation to examine the relationship between music preferences and moods of military students.

Keywords: music preference, emotional regulation, military academic students, SPASS

Procedia PDF Downloads 54
3978 Curve Fitting by Cubic Bezier Curves Using Migrating Birds Optimization Algorithm

Authors: Mitat Uysal

Abstract:

A new met heuristic optimization algorithm called as Migrating Birds Optimization is used for curve fitting by rational cubic Bezier Curves. This requires solving a complicated multivariate optimization problem. In this study, the solution of this optimization problem is achieved by Migrating Birds Optimization algorithm that is a powerful met heuristic nature-inspired algorithm well appropriate for optimization. The results of this study show that the proposed method performs very well and being able to fit the data points to cubic Bezier Curves with a high degree of accuracy.

Keywords: algorithms, Bezier curves, heuristic optimization, migrating birds optimization

Procedia PDF Downloads 323
3977 Efficient Internal Generator Based on Random Selection of an Elliptic Curve

Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

Abstract:

The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

Procedia PDF Downloads 433
3976 Soil Salinity from Wastewater Irrigation in Urban Greenery

Authors: H. Nouri, S. Chavoshi Borujeni, S. Anderson, S. Beecham, P. Sutton

Abstract:

The potential risk of salt leaching through wastewater irrigation is of concern for most local governments and city councils. Despite the necessity of salinity monitoring and management in urban greenery, most attention has been on agricultural fields. This study was defined to investigate the capability and feasibility of monitoring and predicting soil salinity using near sensing and remote sensing approaches using EM38 surveys, and high-resolution multispectral image of WorldView3. Veale Gardens within the Adelaide Parklands was selected as the experimental site. The results of the near sensing investigation were validated by testing soil salinity samples in the laboratory. Over 30 band combinations forming salinity indices were tested using image processing techniques. The outcomes of the remote sensing and near sensing approaches were compared to examine whether remotely sensed salinity indicators could map and predict the spatial variation of soil salinity through a potential statistical model. Statistical analysis was undertaken using the Stata 13 statistical package on over 52,000 points. Several regression models were fitted to the data, and the mixed effect modelling was selected the most appropriate one as it takes to account the systematic observation-specific unobserved heterogeneity. Results showed that SAVI (Soil Adjusted Vegetation Index) was the only salinity index that could be considered as a predictor for soil salinity but further investigation is needed. However, near sensing was found as a rapid, practical and realistically accurate approach for salinity mapping of heterogeneous urban vegetation.

Keywords: WorldView3, remote sensing, EM38, near sensing, urban green spaces, green smart cities

Procedia PDF Downloads 151
3975 Estimation of PM2.5 Emissions and Source Apportionment Using Receptor and Dispersion Models

Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

Abstract:

Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM2.5, while the AERMOD dispersion model has been used to account for missing sources of PM2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM₂.₅, fugitive, emission inventory

Procedia PDF Downloads 325
3974 A Statistical Study on Young UAE Driver’s Behavior towards Road Safety

Authors: Sadia Afroza, Rakiba Rouf

Abstract:

Road safety and associated behaviors have received significant attention in recent years, reflecting general public concern. This paper portrays a statistical scenario of the young drivers in UAE with emphasis on various concern points of young driver’s behavior and license issuance. Although there are many factors contributing to road accidents, statistically it is evident that age plays a major role in road accidents. Despite ensuring strict road safety laws enforced by the UAE government, there is a staggering correlation among road accidents and young driver’s at UAE. However, private organizations like BMW and RoadSafetyUAE have extended its support on conducting surveys on driver’s behavior with an aim to ensure road safety. Various strategies such as road safety law enforcement, license issuance, adapting new technologies like safety cameras and raising awareness can be implemented to improve the road safety concerns among young drivers.

Keywords: driving behavior, Graduated Driver Licensing System (GLDS), road safety, UAE drivers, young drivers

Procedia PDF Downloads 247
3973 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features

Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

Procedia PDF Downloads 364
3972 Applications of Analytical Probabilistic Approach in Urban Stormwater Modeling in New Zealand

Authors: Asaad Y. Shamseldin

Abstract:

Analytical probabilistic approach is an innovative approach for urban stormwater modeling. It can provide information about the long-term performance of a stormwater management facility without being computationally very demanding. This paper explores the application of the analytical probabilistic approach in New Zealand. The paper presents the results of a case study aimed at development of an objective way of identifying what constitutes a rainfall storm event and the estimation of the corresponding statistical properties of storms using two selected automatic rainfall stations located in the Auckland region in New Zealand. The storm identification and the estimation of the storm statistical properties are regarded as the first step in the development of the analytical probabilistic models. The paper provides a recommendation about the definition of the storm inter-event time to be used in conjunction with the analytical probabilistic approach.

Keywords: hydrology, rainfall storm, storm inter-event time, New Zealand, stormwater management

Procedia PDF Downloads 330
3971 Assessment of Marine Diversity on Rocky Shores of Triporti, Vlore, Albania

Authors: Ina Nasto, Denada Sota, Kerol Sacaj, Brunilda Veshaj, Hajdar Kicaj

Abstract:

Rocky shores are often used as models to describe the dynamics of biodiversity around the world, making them one of the most studied marine habitats and their communities. The variability in the number of species and the abundance of hard-bottom benthic animal communities on the coast of Triporti, north of the Bay of Vlora, Albania is described in relation to environmental variables using multivariate analysis. The purpose of this study is to monitor the species composition, quantitative characteristics, and seasonal variations of the benthic macroinvertebrate populations of the shallow rocky shores of the Triportit-Vlora area, as well as the assessment of the ecological condition of these populations. The rocky coast of Triport, with a length of 7 km, was divided into three sampling stations, with three transects each of 50m. The monitoring of benthic macroinvertebrates in these areas was carried out in two seasons, spring and summer (June and August 2021). In each station and sampling season, estimates of the total and average density for each species, the presence constant, and the assessment of biodiversity were calculated using the Shannon–Wiener and the Simpson index. The species composition, the quantitative characteristics of the populations, and the indicators mentioned above were analyzed in a comparative way, both between the seasons within one station and between the three stations with each other. Statistical processing of the data was carried out to analyze the changes between the seasons and between the sampling stations for the species composition, population density, as well as correlation between them. A total of 105 benthic macroinvertebrate taxa were found, dominated by Molluscs, Annelids, and Arthropods. The small density of species and the low degree of stability of the macrozoobenthic community are indicators of the poor ecological condition and environmental impact in the studied areas. Algal cover, the diversity of coastal microhabitats, and the degree of coastal exposure to waves play an important role in the characteristics of macrozoobenthos populations in the studied areas. Also, the rocky shores are of special interest because, in the infralittoral of these areas, there are dense kelp forests with Gongolaria barbata, Ericaria crinita as well as fragmented areas with Posidonia oceanica that reach the coast, priority habitats of special conservation importance in the Mediterranean.

Keywords: Macrozoobenthic communities, Shannon–Wiener, Triporti, Vlore, rocky shore

Procedia PDF Downloads 85
3970 Distinguishing between Bacterial and Viral Infections Based on Peripheral Human Blood Tests Using Infrared Microscopy and Multivariate Analysis

Authors: H. Agbaria, A. Salman, M. Huleihel, G. Beck, D. H. Rich, S. Mordechai, J. Kapelushnik

Abstract:

Viral and bacterial infections are responsible for variety of diseases. These infections have similar symptoms like fever, sneezing, inflammation, vomiting, diarrhea and fatigue. Thus, physicians may encounter difficulties in distinguishing between viral and bacterial infections based on these symptoms. Bacterial infections differ from viral infections in many other important respects regarding the response to various medications and the structure of the organisms. In many cases, it is difficult to know the origin of the infection. The physician orders a blood, urine test, or 'culture test' of tissue to diagnose the infection type when it is necessary. Using these methods, the time that elapses between the receipt of patient material and the presentation of the test results to the clinician is typically too long ( > 24 hours). This time is crucial in many cases for saving the life of the patient and for planning the right medical treatment. Thus, rapid identification of bacterial and viral infections in the lab is of great importance for effective treatment especially in cases of emergency. Blood was collected from 50 patients with confirmed viral infection and 50 with confirmed bacterial infection. White blood cells (WBCs) and plasma were isolated and deposited on a zinc selenide slide, dried and measured under a Fourier transform infrared (FTIR) microscope to obtain their infrared absorption spectra. The acquired spectra of WBCs and plasma were analyzed in order to differentiate between the two types of infections. In this study, the potential of FTIR microscopy in tandem with multivariate analysis was evaluated for the identification of the agent that causes the human infection. The method was used to identify the infectious agent type as either bacterial or viral, based on an analysis of the blood components [i.e., white blood cells (WBC) and plasma] using their infrared vibrational spectra. The time required for the analysis and evaluation after obtaining the blood sample was less than one hour. In the analysis, minute spectral differences in several bands of the FTIR spectra of WBCs were observed between groups of samples with viral and bacterial infections. By employing the techniques of feature extraction with linear discriminant analysis (LDA), a sensitivity of ~92 % and a specificity of ~86 % for an infection type diagnosis was achieved. The present preliminary study suggests that FTIR spectroscopy of WBCs is a potentially feasible and efficient tool for the diagnosis of the infection type.

Keywords: viral infection, bacterial infection, linear discriminant analysis, plasma, white blood cells, infrared spectroscopy

Procedia PDF Downloads 210
3969 Analysis on Prediction Models of TBM Performance and Selection of Optimal Input Parameters

Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

Procedia PDF Downloads 298
3968 Investigated Optimization of Davidson Path Loss Model for Digital Terrestrial Television (DTTV) Propagation in Urban Area

Authors: Pitak Keawbunsong, Sathaporn Promwong

Abstract:

This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

Procedia PDF Downloads 326
3967 The Principle Probabilities of Space-Distance Resolution for a Monostatic Radar and Realization in Cylindrical Array

Authors: Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk

Abstract:

In conjunction with the problem of the target selection on a clutter background, the analysis of the scanning rate influence on the spatial-temporal signal structure, the generalized multivariate correlation function and the quality of the resolution with the increase pulse repetition frequency is made. The possibility of the object space-distance resolution, which is conditioned by the range-to-angle conversion with an increased scanning rate, is substantiated. The calculations for the real cylindrical array at high scanning rate are presented. The high scanning rate let to get the signal to noise improvement of the order of 10 dB for the space-time signal processing.

Keywords: antenna pattern, array, signal processing, spatial resolution

Procedia PDF Downloads 168
3966 Mixed Integer Programming-Based One-Class Classification Method for Process Monitoring

Authors: Younghoon Kim, Seoung Bum Kim

Abstract:

One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

Procedia PDF Downloads 165
3965 Wind Power Forecast Error Simulation Model

Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

Abstract:

One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: wind power, uncertainty, stochastic process, Monte Carlo simulation

Procedia PDF Downloads 470
3964 Assessing Basic Computer Applications’ Skills of College-Level Students in Saudi Arabia

Authors: Mohammed A. Gharawi, Majed M. Khoja

Abstract:

This paper is a report on the findings of a study conducted at the Institute of Public Administration (IPA) in Saudi Arabia. The paper applied both qualitative and quantitative research methods to assess the levels of basic computer applications’ skills among students enrolled in the preparatory programs of the institution. qualitative data have been collected from semi-structured interviews with the instructors who have previously been assigned to teach Introduction to information technology courses. Quantitative data were collected by executing a self-report questionnaire and a written statistical test. 380 enrolled students responded to the questionnaire and 142 accomplished the statistical test. The results indicate the lack of necessary skills to deal with computer applications among most of the students who are enrolled in the IPA’s preparatory programs.

Keywords: assessment, computer applications, computer literacy, Institute of Public Administration, Saudi Arabia

Procedia PDF Downloads 298
3963 Acoustic Emission Techniques in Monitoring Low-Speed Bearing Conditions

Authors: Faisal AlShammari, Abdulmajid Addali, Mosab Alrashed

Abstract:

It is widely acknowledged that bearing failures are the primary reason for breakdowns in rotating machinery. These failures are extremely costly, particularly in terms of lost production. Roller bearings are widely used in industrial machinery and need to be maintained in good condition to ensure the continuing efficiency, effectiveness, and profitability of the production process. The research presented here is an investigation of the use of acoustic emission (AE) to monitor bearing conditions at low speeds. Many machines, particularly large, expensive machines operate at speeds below 100 rpm, and such machines are important to the industry. However, the overwhelming proportion of studies have investigated the use of AE techniques for condition monitoring of higher-speed machines (typically several hundred rpm, or even higher). Few researchers have investigated the application of these techniques to low-speed machines ( < 100 rpm). This paper addressed this omission and has established which, of the available, AE techniques are suitable for the detection of incipient faults and measurement of fault growth in low-speed bearings. The first objective of this paper program was to assess the applicability of AE techniques to monitor low-speed bearings. It was found that the measured statistical parameters successfully monitored bearing conditions at low speeds (10-100 rpm). The second objective was to identify which commonly used statistical parameters derived from the AE signal (RMS, kurtosis, amplitude and counts) could identify the onset of a fault in the out race. It was found that these parameters effectually identify the presence of a small fault seeded into the outer races. Also, it is concluded that rotational speed has a strong influence on the measured AE parameters but that they are entirely independent of the load under such load and speed conditions.

Keywords: acoustic emission, condition monitoring, NDT, statistical analysis

Procedia PDF Downloads 239
3962 Statistical Modeling of Mobile Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes

Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

Procedia PDF Downloads 363
3961 Investigating the Factors Affecting on One Time Passwords Technology Acceptance: A Case Study in Banking Environment

Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

Abstract:

According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

Procedia PDF Downloads 436
3960 Chemical Composition of Volatiles Emitted from Ziziphus jujuba Miller Collected during Different Growth Stages

Authors: Rose Vanessa Bandeira Reidel, Bernardo Melai, Pier Luigi Cioni, Luisa Pistelli

Abstract:

Ziziphus jujuba Miller is a common species of the Ziziphus genus (Rhamnaceae family) native to the tropics and subtropics known for its edible fruits, fresh consumed or used in healthy food, as flavoring and sweetener. Many phytochemicals and biological activities are described for this species. In this work, the aroma profiles emitted in vivo by whole fresh organs (leaf, bud flower, flower, green and red fruits) were analyzed separately by mean of solid phase micro-extraction (SPME) coupled with gas chromatography mass spectrometry (GC-MS). The emitted volatiles from different plant parts were analysed using Supelco SPME device coated with polydimethylsiloxane (PDMS, 100µm). Fresh plant material was introduced separately into a glass conical flask and allowed to equilibrate for 20 min. After the equilibration time, the fibre was exposed to the headspace for 15 min at room temperature, the fibre was re-inserted into the needle and transferred to the injector of the CG and CG-MS system, where the fibre was desorbed. All the data were submitted to multivariate statistical analysis, evidencing many differences amongst the selected plant parts and their developmental stages. A total of 144 compounds were identified corresponding to 94.6-99.4% of the whole aroma profile of jujube samples. Sesquiterpene hydrocarbons were the main chemical class of compounds in leaves also present in similar percentage in flowers and bud flowers where (E, E)-α-farnesene was the main constituent in all cited plant parts. This behavior can be due to a protection mechanism against pathogens and herbivores as well as resistance to abiotic factors. The aroma of green fruits was characterized by high amount of perillene while the red fruits release a volatile blend mainly constituted by different monoterpenes. The terpenoid emission of flesh fruits has important function in the interaction with animals including attraction of seed dispersers and it is related to a good quality of fruits. This study provides for the first time the chemical composition of the volatile emission from different Ziziphus jujuba organs. The SPME analyses of the collected samples showed different patterns of emission and can contribute to understand their ecological interactions and fruit production management.

Keywords: Rhamnaceae, aroma profile, jujube organs, HS-SPME, GC-MS

Procedia PDF Downloads 238
3959 Effect of Food Supplies Holstein Calves Supplemented with Bacillus Subtilis PB6 in Morbidity and Mortality

Authors: Banca Patricia Pena Revuelta, Ramiro Gonzalez Avalos, Juan Leonardo Rocha Valdez, Jose Gonzalez Avalos, Karla Rodriguez Hernandez

Abstract:

Probiotics are a promising alternative to improve productivity and animals' health. In addition, they can be part of the composition of different types of products, including foods (functional foods), medicines, and dietary supplements. The objective of the present work was to evaluate the effect of the feeding of Holstein calves supplemented with bacillus subtilis PB6 in morbidity and mortality. 60 newborn animals were used, randomly included in 1 of 3 treatments. The treatments were as follows: T1 = control, T2 = 10 g / calf / day. The first takes within 20 min after birth, T3 = 10 g / calf/day. The first takes between 12 and 24 h after birth. In all the treatments, 432 L of pasteurized whole milk divided into two doses/day 07:00 and 15:00, respectively, were given for 60 days. The addition of bacillus subtilis PB6 was carried out in the milk tub at the time of feeding them. The first colostrum intake (2 L • intake) was given within 2 h after birth, after which they were given a second 6 h after the first one. The diseases registered to monitor the morbidity and mortality of the calves were: diarrhea and pneumonia. The registry was carried out from birth to 60 days of life. The parameter evaluated was food consumption. The variable statistical analysis was performed using analysis of variance, and comparison of means was performed using the Tukey test. The value of P < 0.05 was used to consider the statistical difference. The results of the present study in relation to the consumption of food show no statistical difference P < 0.05 between treatments (14,762, 11,698, and 12,403 kg of food average, respectively). Calves group to which they were not provided Bacillus subtilis PB6 obtained higher feed intake. The addition of Bacillus subtilis PB6 in feeding calves does not increase feed intake.

Keywords: feeding, development, milk, probiotic

Procedia PDF Downloads 130
3958 Sleep Apnea Hypopnea Syndrom Diagnosis Using Advanced ANN Techniques

Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

Abstract:

Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

Procedia PDF Downloads 109
3957 Statistical Modeling for Permeabilization of a Novel Yeast Isolate for β-Galactosidase Activity Using Organic Solvents

Authors: Shweta Kumari, Parmjit S. Panesar, Manab B. Bera

Abstract:

The hydrolysis of lactose using β-galactosidase is one of the most promising biotechnological applications, which has wide range of potential applications in food processing industries. However, due to intracellular location of the yeast enzyme, and expensive extraction methods, the industrial applications of enzymatic hydrolysis processes are being hampered. The use of permeabilization technique can help to overcome the problems associated with enzyme extraction and purification of yeast cells and to develop the economically viable process for the utilization of whole cell biocatalysts in food industries. In the present investigation, standardization of permeabilization process of novel yeast isolate was carried out using a statistical model approach known as Response Surface Methodology (RSM) to achieve maximal b-galactosidase activity. The optimum operating conditions for permeabilization process for optimal β-galactosidase activity obtained by RSM were 1:1 ratio of toluene (25%, v/v) and ethanol (50%, v/v), 25.0 oC temperature and treatment time of 12 min, which displayed enzyme activity of 1.71 IU /mg DW.

Keywords: β-galactosidase, optimization, permeabilization, response surface methodology, yeast

Procedia PDF Downloads 242
3956 Eating Behavior and Nutritional Status of Pregnant Women Living in Keserwan Lebanon

Authors: Cynthia Zgheib, Yonna Sacre

Abstract:

Pregnancy, this particular moment in the life of a woman, requires monitoring of eating behavior changes. However, the food choices during pregnancy should be varied and healthy, including the consumption of different food groups. Nutritional status is the process of acquisition and consumption of food. Therefore, a varied diet is associated with good nutritional status. This is why the nutrition education is a strategy commonly applied to improve maternal nutrition during pregnancy. Thus, it is crucial to assess 'The eating behavior and nutritional status of pregnant women living in Keserwan Lebanon.' In order to evaluate the association of different persona, socioeconomic and sociodemographic factors with the eating behavior and nutrition in the concerned study category, a cross-sectional descriptive study was conducted on a sample of 150 pregnant women aging between 18 and 40 years randomly selected from the hospitals and clinics located in Keserwan area and equally distributed between different cities and villages of the area according to altitude. The purpose of this study was to evaluate the eating behavior of the concerned population and to compare it to the recommendation of the food guide pyramid, their level of food awareness and finally to analyze their blood tests in order to detect any nutrients deficiency that they may face during the course of their pregnancy. Sociodemographic, lifestyle, eating behaviour, health, eating patterns, awareness, and food frequency questionnaire (FFQ) were collected through a validated questionnaire specifically adapted for the purpose of the study. Statistical analysis was carried out, and multivariate models were used in order to evaluate the association between several independent variables and the eating behaviour and nutritional status of Lebanese pregnant women The final analysis has shown that 48.7% of pregnant women were aged between 30 and 40 years old, 56% had a normal BMI between 18.5 and 24.9, thus age affects the eating behavior, so the older are the pregnant women, and the healthier is their eating behavior. In fact, 80.7% had acceptable food behavior which is based on an equilibrium between both quantity and quality of food, although the recommended foods are foods found in the food pyramid and available in the Lebanese diet. In addition, 68% had an acceptable level of awareness concerning the health importance of good eating habits, therefore, it is positively affecting their food choices. Moreover, 50 % have an acceptable nutritional status which is confirmed by their biological tests. Future governmental or national studies and programs could be settled aiming to increase the awareness about the good eating behaviors and nutritional status of Lebanese pregnant women.

Keywords: eating behavior, nutritional status, level of awareness, pregnant woman

Procedia PDF Downloads 247
3955 Using Statistical Significance and Prediction to Test Long/Short Term Public Services and Patients' Cohorts: A Case Study in Scotland

Authors: Raptis Sotirios

Abstract:

Health and social care (HSc) services planning and scheduling are facing unprecedented challenges due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven can help to improve policies, plan and design services provision schedules using algorithms assist healthcare managers’ to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as CART, random forests (RF), and logistic regression (LGR). The significance tests Chi-Squared test and Student test are used on data over a 39 years span for which HSc services data exist for services delivered in Scotland. The demands are probabilistically associated through statistical hypotheses that assume that the target service’s demands are statistically dependent on other demands as a NULL hypothesis. This linkage can be confirmed or not by the data. Complementarily, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus groups of services. Statistical tests confirm ML couplings making the prediction also statistically meaningful and prove that a target service can be matched reliably to other services, and ML shows these indicated relationships can also be linear ones. Zero paddings were used for missing years records and illustrated better such relationships both for limited years and in the entire span offering long term data visualizations while limited years groups explained how well patients numbers can be related in short periods or can change over time as opposed to behaviors across more years. The prediction performance of the associations is measured using Receiver Operating Characteristic(ROC) AUC and ACC metrics as well as the statistical tests, Chi-Squared and Student. Co-plots and comparison tables for RF, CART, and LGR as well as p-values and Information Exchange(IE), are provided showing the specific behavior of the ML and of the statistical tests and the behavior using different learning ratios. The impact of k-NN and cross-correlation and C-Means first groupings is also studied over limited years and the entire span. It was found that CART was generally behind RF and LGR, but in some interesting cases, LGR reached an AUC=0 falling below CART, while the ACC was as high as 0.912, showing that ML methods can be confused padding or by data irregularities or outliers. On average, 3 linear predictors were sufficient, LGR was found competing RF well, and CART followed with the same performance at higher learning ratios. Services were packed only if when significance level(p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, birth weights, alcoholism, drug abuse, and emergency admissions. The work found that different HSc services can be well packed as plans of limited years, across various services sectors, learning configurations, as confirmed using statistical hypotheses.

Keywords: class, cohorts, data frames, grouping, prediction, prob-ability, services

Procedia PDF Downloads 215
3954 The Effectiveness of Energy Index Technique in Bearing Condition Monitoring

Authors: Faisal Alshammari, Abdulmajid Addali, Mosab Alrashed, Taihiret Alhashan

Abstract:

The application of acoustic emission techniques is gaining popularity, as it can monitor the condition of gears and bearings and detect early symptoms of a defect in the form of pitting, wear, and flaking of surfaces. Early detection of these defects is essential as it helps to avoid major failures and the associated catastrophic consequences. Signal processing techniques are required for early defect detection – in this article, a time domain technique called the Energy Index (EI) is used. This article presents an investigation into the Energy Index’s effectiveness to detect early-stage defect initiation and deterioration, and compares it with the common r.m.s. index, Kurtosis, and the Kolmogorov-Smirnov statistical test. It is concluded that EI is a more effective technique for monitoring defect initiation and development than other statistical parameters.

Keywords: acoustic emission, signal processing, kurtosis, Kolmogorov-Smirnov test

Procedia PDF Downloads 348