Search results for: statistical features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7663

Search results for: statistical features

5683 Wildlife Habitat Corridor Mapping in Urban Environments: A GIS-Based Approach Using Preliminary Category Weightings

Authors: Stefan Peters, Phillip Roetman

Abstract:

The global loss of biodiversity is threatening the benefits nature provides to human populations and has become a more pressing issue than climate change and requires immediate attention. While there have been successful global agreements for environmental protection, such as the Montreal Protocol, these are rare, and we cannot rely on them solely. Thus, it is crucial to take national and local actions to support biodiversity. Australia is one of the 17 countries in the world with a high level of biodiversity, and its cities are vital habitats for endangered species, with more of them found in urban areas than in non-urban ones. However, the protection of biodiversity in metropolitan Adelaide has been inadequate, with over 130 species disappearing since European colonization in 1836. In this research project we conceptualized, developed and implemented a framework for wildlife Habitat Hotspots and Habitat Corridor modelling in an urban context using geographic data and GIS modelling and analysis. We used detailed topographic and other geographic data provided by a local council, including spatial and attributive properties of trees, parcels, water features, vegetated areas, roads, verges, traffic, and census data. Weighted factors considered in our raster-based Habitat Hotspot model include parcel size, parcel shape, population density, canopy cover, habitat quality and proximity to habitats and water features. Weighted factors considered in our raster-based Habitat Corridor model include habitat potential (resulting from the Habitat Hotspot model), verge size, road hierarchy, road widths, human density, and presence of remnant indigenous vegetation species. We developed a GIS model, using Python scripting and ArcGIS-Pro Model-Builder, to establish an automated reproducible and adjustable geoprocessing workflow, adaptable to any study area of interest. Our habitat hotspot and corridor modelling framework allow to determine and map existing habitat hotspots and wildlife habitat corridors. Our research had been applied to the study case of Burnside, a local council in Adelaide, Australia, which encompass an area of 30 km2. We applied end-user expertise-based category weightings to refine our models and optimize the use of our habitat map outputs towards informing local strategic decision-making.

Keywords: biodiversity, GIS modeling, habitat hotspot, wildlife corridor

Procedia PDF Downloads 118
5682 Desert Houses of the Past: Green Buildings of Today

Authors: Baharak Shakeri, Seyed Hashem Hosseini

Abstract:

The weather in deserts is hot and dry in summers, and cold and dry in winters, and difference of temperature of nights and days sometimes reaches to 28°C. People of deserts have reached some solutions to cope with this climatic condition and to decrease its annoying features. Among these solutions are: constructing houses adjacent to each other, making tall walls, using mud brick and thatch cover, constructing domical arches, cellar, and wind catcher, which are together the devices to control the adversity of hot weather in summers and cold weather in winters. Using these solutions, the people of deserts have succeeded to make the best use with the least energy consumption, and to minimize the damage on the nature and environment, and in short, they are friends of the nature, which is a step toward the objectives of green buildings.

Keywords: desert house, green building, Iran, nature

Procedia PDF Downloads 339
5681 New Segmentation of Piecewise Moving-Average Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

This paper addresses the problem of the signal segmentation within a Bayesian framework by using reversible jump MCMC algorithm. The signal is modelled by piecewise constant Moving-Average (MA) model where the numbers of segments, the position of change-point, the order and the coefficient of the MA model for each segment are unknown. The reversible jump MCMC algorithm is then used to generate samples distributed according to the joint posterior distribution of the unknown parameters. These samples allow calculating some interesting features of the posterior distribution. The performance of the methodology is illustrated via several simulation results.

Keywords: piecewise, moving-average model, reversible jump MCMC, signal segmentation

Procedia PDF Downloads 228
5680 Detecting Rat’s Kidney Inflammation Using Real Time Photoacoustic Tomography

Authors: M. Y. Lee, D. H. Shin, S. H. Park, W.C. Ham, S.K. Ko, C. G. Song

Abstract:

Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Keywords: photoacoustic tomography, inflammation detection, rat, kidney, contrast agent, ultrasound

Procedia PDF Downloads 458
5679 Detect QOS Attacks Using Machine Learning Algorithm

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 62
5678 International Trends in Sustainability Reporting Using Global Reporting Initiatives

Authors: Ramona Zharfpeykan

Abstract:

This study analyses the trend and nature of sustainability key performance indicators (KPIs) reporting in firms globally. It presents both trend and panel data of sustainability reports of 798 firms in the Global Reporting Initiative (GRI) database from 2010 to 2014. The results show some fluctuations in the frequency of sustainability KPI reporting globally across the time while the major focus of reports in firms stayed almost the same. It made us further analyse this trend and found that there are some indicators, such as 'environmental protect expenses' and 'number of grievances', that was barely reported over this period along with some highly popular ones such as 'direct economic value' and 'employment rate'. We could not find any statistical correlation between the KPI reporting percentage and the firms’ industries generally and neither if they belong to environmentally sensitive industries.

Keywords: global reporting initiatives, sustainability reporting, sustainability KPI, trends of sustainability reporting

Procedia PDF Downloads 144
5677 Project and Module Based Teaching and Learning

Authors: Jingyu Hou

Abstract:

This paper proposes a new teaching and learning approach-project and Module Based Teaching and Learning (PMBTL). The PMBTL approach incorporates the merits of project/problem based and module based learning methods, and overcomes the limitations of these methods. The correlation between teaching, learning, practice, and assessment is emphasized in this approach, and new methods have been proposed accordingly. The distinct features of these new methods differentiate the PMBTL approach from conventional teaching approaches. Evaluation of this approach on practical teaching and learning activities demonstrates the effectiveness and stability of the approach in improving the performance and quality of teaching and learning. The approach proposed in this paper is also intuitive to the design of other teaching units.

Keywords: computer science education, project and module based, software engineering, module based teaching and learning

Procedia PDF Downloads 493
5676 Implementation of Achterbahn-128 for Images Encryption and Decryption

Authors: Aissa Belmeguenai, Khaled Mansouri

Abstract:

In this work, an efficient implementation of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written by MATLAB.7.5. At first two different original images are used for validate the proposed design. Then our developed program was used to transform the original images data into image digits file. Finally, we used our implemented program to encrypt and decrypt images data. Several tests are done for proving the design performance including visual tests and security analysis; we discuss the security analysis of the proposed image encryption scheme including some important ones like key sensitivity analysis, key space analysis, and statistical attacks.

Keywords: Achterbahn-128, stream cipher, image encryption, security analysis

Procedia PDF Downloads 533
5675 Assessing Pain Using Morbid Motion Monitor System in the Pain Management of Nurse Practitioner

Authors: Mohammad Reza Dawoudi

Abstract:

With the increasing rate of patients suffering from chronic pain, several methods for evaluating of chronic pain are suggested. Motion of morbid has been defined as the rate of pine and it is linked with various co-morbid conditions. This study provides a summary of procedure useful to statistics performing direct behavioral observation in hospital settings. We describe the need for and usefulness of comprehensive “morbid motions” observations; provide a primer on the identification, definition, and assessment of morbid behaviors; and outline and discuss specific statistical procedures, including formulating referral motions, describing and conducting the observation. We also provide practical devices for observing and analyzing the obtained information into a report that guides clinical intervention.

Keywords: assessing pain, DNA modeling, image matching technique, pain scale

Procedia PDF Downloads 414
5674 Emerging Technology for 6G Networks

Authors: Yaseein S. Hussein, Victor P. Gil Jiménez, Abdulmajeed Al-Jumaily

Abstract:

Due to the rapid advancement of technology, there is an increasing demand for wireless connections that are both fast and reliable, with minimal latency. New wireless communication standards are developed every decade, and the year 2030 is expected to see the introduction of 6G. The primary objectives of 6G network and terminal designs are focused on sustainability and environmental friendliness. The International Telecommunication Union-Recommendation division (ITU-R) has established the minimum requirements for 6G, with peak and user data rates of 1 Tbps and 10-100 Gbps, respectively. In this context, Light Fidelity (Li-Fi) technology is the most promising candidate to meet these requirements. This article will explore the various advantages, features, and potential applications of Li-Fi technology, and compare it with 5G networking, to showcase its potential impact among other emerging technologies that aim to enable 6G networks.

Keywords: 6G networks, artificial intelligence (AI), Li-Fi technology, Terahertz (THz) communication, visible light communication (VLC)

Procedia PDF Downloads 95
5673 The Gender Perspective Applied to the Analysis of Occupational Accidents

Authors: María Del Carmen Pardo Ferreira, Fernando Rodriguez Cortes, Juan Carlos Rubio Romero

Abstract:

According to the International Labor Organization, every day there is more presence of women in the labor market although inequality between women and men persists in world labor markets. In order to try to reduce this gender inequality in the work environment, the present study is proposed, which aims to analyze the occupational accidents suffered by women and occurred in Spain between 2015 and 2018. For this, the methodology used was based on a statistical analysis of the data provided by the Government of Spain. The results will allow to know in which jobs women suffer accidents, in what type of companies and the severity of the accident. Based on these results, specific intervention policies may be defined according to the needs detected in each sector.

Keywords: Injured women, Gender perspective, Occupational accidents, Occupational health and safety

Procedia PDF Downloads 180
5672 A Study on Big Data Analytics, Applications and Challenges

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 88
5671 A Study on Big Data Analytics, Applications, and Challenges

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 96
5670 Differences in Assessing Hand-Written and Typed Student Exams: A Corpus-Linguistic Study

Authors: Jutta Ransmayr

Abstract:

The digital age has long arrived at Austrian schools, so both society and educationalists demand that digital means should be integrated accordingly to day-to-day school routines. Therefore, the Austrian school-leaving exam (A-levels) can now be written either by hand or by using a computer. However, the choice of writing medium (pen and paper or computer) for written examination papers, which are considered 'high-stakes' exams, raises a number of questions that have not yet been adequately investigated and answered until recently, such as: What effects do the different conditions of text production in the written German A-levels have on the component of normative linguistic accuracy? How do the spelling skills of German A-level papers written with a pen differ from those that the students wrote on the computer? And how is the teacher's assessment related to this? Which practical desiderata for German didactics can be derived from this? In a trilateral pilot project of the Austrian Center for Digital Humanities (ACDH) of the Austrian Academy of Sciences and the University of Vienna in cooperation with the Austrian Ministry of Education and the Council for German Orthography, these questions were investigated. A representative Austrian learner corpus, consisting of around 530 German A-level papers from all over Austria (pen and computer written), was set up in order to subject it to a quantitative (corpus-linguistic and statistical) and qualitative investigation with regard to the spelling and punctuation performance of the high school graduates and the differences between pen- and computer-written papers and their assessments. Relevant studies are currently available mainly from the Anglophone world. These have shown that writing on the computer increases the motivation to write, has positive effects on the length of the text, and, in some cases, also on the quality of the text. Depending on the writing situation and other technical aids, better results in terms of spelling and punctuation could also be found in the computer-written texts as compared to the handwritten ones. Studies also point towards a tendency among teachers to rate handwritten texts better than computer-written texts. In this paper, the first comparable results from the German-speaking area are to be presented. Research results have shown that, on the one hand, there are significant differences between handwritten and computer-written work with regard to performance in orthography and punctuation. On the other hand, the corpus linguistic investigation and the subsequent statistical analysis made it clear that not only the teachers' assessments of the students’ spelling performance vary enormously but also the overall assessments of the exam papers – the factor of the production medium (pen and paper or computer) also seems to play a decisive role.

Keywords: exam paper assessment, pen and paper or computer, learner corpora, linguistics

Procedia PDF Downloads 172
5669 Sport and Exercise Behavior of Students in Suan Sunandha Rajabhat University

Authors: Pimporn Thongmuang

Abstract:

The purpose of this research is to study sport and exercise behavior of students in Suan Sunandha Rajabhat University in September of 2012. The sample group used in this research was a group of regular students in undergraduate school enrolled in faculty of science and technology. This sample group consisted of 1,858 students. The research tool used to collect result was the checklist. The data was calculated by statistical percentage. From the research, it was discovered that most students did exercise in previous month. 71.6% of students exercised by running. 61.1% of students exercised in their neighborhood. 60.4% of students exercised in order to keep fit. 60.2% of students agreed that the result from this research can be educational and inspirational for students in campus in terms of living healthily by exercise.

Keywords: exercise behavior, sport behavior, students, health

Procedia PDF Downloads 472
5668 Bundle Block Detection Using Spectral Coherence and Levenberg Marquardt Neural Network

Authors: K. Padmavathi, K. Sri Ramakrishna

Abstract:

This study describes a procedure for the detection of Left and Right Bundle Branch Block (LBBB and RBBB) ECG patterns using spectral Coherence(SC) technique and LM Neural Network. The Coherence function finds common frequencies between two signals and evaluate the similarity of the two signals. The QT variations of Bundle Blocks are observed in lead V1 of ECG. Spectral Coherence technique uses Welch method for calculating PSD. For the detection of normal and Bundle block beats, SC output values are given as the input features for the LMNN classifier. Overall accuracy of LMNN classifier is 99.5 percent. The data was collected from MIT-BIH Arrhythmia database.

Keywords: bundle block, SC, LMNN classifier, welch method, PSD, MIT-BIH, arrhythmia database

Procedia PDF Downloads 284
5667 Metallacyclodimeric Array Containing Both Suprachannels and Cages: Selective Reservoir and Recognition of Diiodomethane

Authors: Daseul Lee, Jeong Jun Lee, Ok-Sang Jung

Abstract:

Self-assembly of a series of ZnX2 (X- = Cl-, Br-, and I-) with 2,3-bis(4’-nicotinamidephenoxy)naphthalene (L) as a new bidentate pyridyl-donor ligand yields systematic metallacyclodimeric unit, [ZnX2L]2. The supramolecule constitutes a characteristically stacked forming both 1D suprachannels and cages. Weak C-H⋯π and inter-digitated π⋯π interactions are main driving forces in the formation of both suprachannels and cages. The slightly different features between the suprachannel and cage have been investigated by 1H NMR and TG analysis, which solvent quantitatively exchange within only suprachannels. Photo-unstable CH2I2 molecules are stabilized via capturing within suprachannels, which is monitored by UV-Vis spectroscopy. Furthermore, the photoluminescence intensity, from the chromophore naphthyl moiety of [ZnCl2L]2, gradually decreases with the addition of CH2I2. And washing off the CH2I2 by dichloromethane returned the PL intensity back to its approximately original signal.

Keywords: metallacyclodimer, suprachannel, π⋯π interaction, molecular recognition

Procedia PDF Downloads 323
5666 Investigation of Optical Requirements for Power System Assets Monitoring with Unmanned Aerial Vehicles

Authors: Ioana Pisica, Dimitrios Gkritzapis

Abstract:

The significance of UAS in scientific applications has been amply demonstrated in recent years. The combinations of portability and quasi-static positioning by means of flying in close loop path make them versatile and efficient in the inspection of power systems infrastructure. In this paper, we critically assess several platforms and sensor capabilities to identify their pros and cons in relation to the power systems assets to be monitored. In this respect, it is paramount the flights to be conducted by using UAS which bear certain suitable features, such as responsive and easy control, video capturing in real time, autonomous routing of pre-planned flight programming with differentiating payloads. The outcome of this research is a set of optimal requirements for power system assets monitoring with UAS.

Keywords: platforms, power system, sensors, UAVs

Procedia PDF Downloads 288
5665 Features of Annual Junior Men's Kayak Training Loads in China

Authors: Liu Haitao, Wang Hengyong

Abstract:

This paper attempts to kayak, Zhaoqing City, the annual training program for young men, the deconstruction and analysis, describe the characteristics of their training load, Young people to extract the key issues for training kayak, kayak training young people to clarify in Zhaoqing City, and the cause of the bottlenecks. On one hand, scientifically arranging for the coaches to adjust training load and provide the basis for periodic structure, for young people to provide practical reference kayak athletes. On the other hand, through their training load research, enrich the theoretical system kayak training project for junior kayak athletes to provide a theoretical basis.

Keywords: juniors, kayak, training programs, full year

Procedia PDF Downloads 591
5664 Impact of Graduates’ Quality of Education and Research on ICT Adoption at Workplace

Authors: Mohammed Kafaji

Abstract:

This paper aims to investigate the influence of quality of education and quality of research, provided by local educational institutions, on the adoption of Information and Communication Technology (ICT) in managing business operations for companies in Saudi market. A model was developed and tested using data collected from 138 CEO’s of foreign companies in diverse business sectors. The data is analysed and managed using multivariate approaches through standard statistical packages. The results showed that educational quality has little contribution to the ICT adoption while research quality seems to play a more prominent role. These results are analysed in terms of business environment and market constraints and further extended to the perceived effectiveness of applied pedagogical approaches in schools and universities.

Keywords: quality of education, quality of research, mediation, domestic competition, ICT adoption

Procedia PDF Downloads 458
5663 Defects Estimation of Embedded Systems Components by a Bond Graph Approach

Authors: I. Gahlouz, A. Chellil

Abstract:

The paper concerns the estimation of system components faults by using an unknown inputs observer. To reach this goal, we used the Bond Graph approach to physical modelling. We showed that this graphical tool is allowing the representation of system components faults as unknown inputs within the state representation of the considered physical system. The study of the causal and structural features of the system (controllability, observability, finite structure, and infinite structure) based on the Bond Graph approach was hence fulfilled in order to design an unknown inputs observer which is used for the system component fault estimation.

Keywords: estimation, bond graph, controllability, observability

Procedia PDF Downloads 415
5662 Nonstationarity Modeling of Economic and Financial Time Series

Authors: C. Slim

Abstract:

Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

Procedia PDF Downloads 424
5661 The Role of Identifications in Women Psychopathology

Authors: Mary Gouva, Elena Dragioti, Evangelia Kotrsotsiou

Abstract:

Family identification has the potential to play a very decisive role in psychopathology. In this study we aimed to investigate the impact of family identifications on female psychopathology. A community sample of 101 women (mean age 20.81 years, SD = 0.91 ranged 20-25) participated to the present study. The girls completed a) the Symptom Check-List Revised (SCL-90) and b) questionnaire concerning socio-demographic information and questions for family identifications. The majority of women reported that they matched to the father in terms of identifications (47.1%). Age and birth order were not contributed on family identifications (F(5) =2.188, p=.062 and F(3)=1.244, p=.299 respectively). Multivariate analysis by using MANCOVA found statistical significant associations between family identifications and domains of psychopathology as provided by SCL-90 (P<05). Our results highlight the role of identifications especially on father and female psychopathology as well as replicate the Freudian perception about the female Oedipus complex.

Keywords: family identification, psychoanalysis, psychopathology, women

Procedia PDF Downloads 327
5660 An Exploratory Study of Chinese Paper-Cut Art in Household Product Design

Authors: Ruining Wu, Na Song

Abstract:

Paper-cut, as one of the Chinese traditional folk decoration art, has become a unique visual aesthetic characteristics of the Chinese nation in the long-term evolution of cultural symbols. Chinese paper-cut art is the treasure-house for product design in natural resources. This paper first analyzed Chinese folk art of historical origin, cultural background, cultural values, aesthetic value, style features of Chinese paper cut art, then analyzed the design thought and design cases of paper-cut art application in different areas, such as clothing design, logo design and product design areas. Through the research of Chinese paper-cut art culture and design elements, this paper aims to build a household product design concept of Chinese traditional culture.

Keywords: paper-cut art, culture, household products, design

Procedia PDF Downloads 613
5659 A New Spell-Out Mechanism

Authors: Yusra Yahya

Abstract:

In this paper, a new spell-out mechanism is developed and defended. This mechanism builds on the role of phase heads as both the loci of spell-out features and the transfer triggers via either Phase Impenetrability Condition 1 (PIC1) and/or Phase Impenetrability Condition 2 (PIC2). The assumption here is that phase heads, mainly v*, can regulate the spell-out process by deciding both the type of spell-out applying and the timing of spell-out relevant. This paper also proposes a new form of the constraint Wrap call it Wrap-XP’ and it is assumed to apply to IP as a functional maximal projection. This extension is shown to fall as a natural result once we assume the new theory of phases and multiple spell-out. Moreover, it is proposed in this work that some forms of XP movement are not motivated by an EPP feature of a strong phase head mainly v*, but they are rather motivated by a last resort strategy to accomplish the spell-out instruction of this phase head.

Keywords: linguistics, syntax, phonology, phase theory, optimality theory

Procedia PDF Downloads 514
5658 Features Dimensionality Reduction and Multi-Dimensional Voice-Processing Program to Parkinson Disease Discrimination

Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

Abstract:

Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

Procedia PDF Downloads 280
5657 Enzymatic Hydrolysis of Sugar Cane Bagasse Using Recombinant Hemicellulases

Authors: Lorena C. Cintra, Izadora M. De Oliveira, Amanda G. Fernandes, Francieli Colussi, Rosália S. A. Jesuíno, Fabrícia P. Faria, Cirano J. Ulhoa

Abstract:

Xylan is the main component of hemicellulose and for its complete degradation is required cooperative action of a system consisting of several enzymes including endo-xylanases (XYN), β-xylosidases (XYL) and α-L-arabinofuranosidases (ABF). The recombinant hemicellulolytic enzymes an endoxylanase (HXYN2), β-xylosidase (HXYLA), and an α-L-arabinofuranosidase (ABF3) were used in hydrolysis tests. These three enzymes are produced by filamentous fungi and were expressed heterologously and produced in Pichia pastoris previously. The aim of this work was to evaluate the effect of recombinant hemicellulolytic enzymes on the enzymatic hydrolysis of sugarcane bagasse (SCB). The interaction between the three recombinant enzymes during SCB pre-treated by steam explosion hydrolysis was performed with different concentrations of HXYN2, HXYLA and ABF3 in different ratios in according to a central composite rotational design (CCRD) 23, including six axial points and six central points, totaling 20 assays. The influence of the factors was assessed by analyzing the main effects and interaction between the factors, calculated using Statistica 8.0 software (StatSoft Inc. Tulsa, OK, USA). The Pareto chart was constructed with this software and showed the values of the Student’s t test for each recombinant enzyme. It was considered as response variable the quantification of reducing sugars by DNS (mg/mL). The Pareto chart showed that the recombinant enzyme ABF3 exerted more significant effect during SCB hydrolysis, with higher concentrations and with the lowest concentration of this enzyme. It was performed analysis of variance according to Fisher method (ANOVA). In ANOVA for the release of reducing sugars (mg/ml) as the variable response, the concentration of ABF3 showed significance during hydrolysis SCB. The result obtained by ANOVA, is in accordance with those presented in the analysis method based on the statistical Student's t (Pareto chart). The degradation of the central chain of xylan by HXYN2 and HXYLA was more strongly influenced by ABF3 action. A model was obtained, and it describes the performance of the interaction of all three enzymes for the release of reducing sugars, and can be used to better explain the results of the statistical analysis. The formulation capable of releasing the higher levels of reducing sugars had the following concentrations: HXYN2 with 600 U/g of substrate, HXYLA with 11.5 U.g-1 and ABF3 with 0.32 U.g-1. In conclusion, the recombinant enzyme that has a more significant effect during SCB hydrolysis was ABF3. It is noteworthy that the xylan present in the SCB is arabinoglucoronoxylan, due to this fact debranching enzymes are important to allow access of enzymes that act on the central chain.

Keywords: experimental design, hydrolysis, recombinant enzymes, sugar cane bagasse

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5656 A Development of a Simulation Tool for Production Planning with Capacity-Booking at Specialty Store Retailer of Private Label Apparel Firms

Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

Abstract:

In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: capacity-booking, SPA, monthly production planning, linear programming

Procedia PDF Downloads 521
5655 Generalized Mean-Field Theory of Phase Unwrapping via Multiple Interferograms

Authors: Yohei Saika

Abstract:

On the basis of Bayesian inference using the maximizer of the posterior marginal estimate, we carry out phase unwrapping using multiple interferograms via generalized mean-field theory. Numerical calculations for a typical wave-front in remote sensing using the synthetic aperture radar interferometry, phase diagram in hyper-parameter space clarifies that the present method succeeds in phase unwrapping perfectly under the constraint of surface- consistency condition, if the interferograms are not corrupted by any noises. Also, we find that prior is useful for extending a phase in which phase unwrapping under the constraint of the surface-consistency condition. These results are quantitatively confirmed by the Monte Carlo simulation.

Keywords: Bayesian inference, generalized mean-field theory, phase unwrapping, multiple interferograms, statistical mechanics

Procedia PDF Downloads 480
5654 Big Data Analysis with RHadoop

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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