Search results for: DNA database

Authors: Osamu Komori, Shinto Eguchi, Hiroshi Okamura, Momoko Ichinokawa

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The long time-series data on population assessments are essential for global ecosystem assessment because the temporal change of biomass in such a database reflects the status of global ecosystem properly. However, the available assessment data usually have limited sample sizes and the ratio of populations with low abundance of biomass (collapsed) to those with high abundance (non-collapsed) is highly imbalanced. To allow for the imbalance and uncertainty involved in the ecological data, we propose a binary regression model with mixed effects for inferring ecosystem status through an asymmetric logistic model. In the estimation equation, we observe that the weights for the non-collapsed populations are relatively reduced, which in turn puts more importance on the small number of observations of collapsed populations. Moreover, we extend the asymmetric logistic regression model using propensity score to allow for the sample biases observed in the labeled and unlabeled datasets. It robustified the estimation procedure and improved the model fitting.

Keywords: double robust estimation, ecological binary data, mixed effect logistic regression model, propensity score

Procedia PDF Downloads 268

Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

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One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: energy-efficient buildings, energy management systems, government buildings, JENOSYS

Procedia PDF Downloads 175

Authors: Mahmoud Mabrok, Channarong Rodkhum

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Flavobacterium columanre is one of the devastating pathogen that causes noticeable economic losses in freshwater cultured fish. Like other filamentous bacteria, F. columanre tends to aggregate and fluctuate to all kind of media, thus revealing obstacles in recognition of its colonies. Since the molecular typing is the only fundamental tool for rapid and precise detection of this pathgen. The present study developed a species-specific PCR assay based on cslA unique gene of F. columnare. The cslA gene sequences of 13 F. columnare, strains retrieved from gene bank database, were aligned to identify a conserved homologous segment prior to primers design. The new primers yielded amplicons of 287 bp from F. columnare strains but not from relevant or other pathogens, unlike to other published set that showed no specificity and cross-reactivity with F. indicum. The primers were sensitive and detected as few as 7 CFUs of bacteria and 3 pg of gDNA template. The sensitivity was reduced ten times when using tissue samples. These primers precisely defined all field isolates in a double-blind study, proposing their applicable use for field detection.

Keywords: Columnaris infection, cslA gene, Flavobacterium columnare, PCR

Procedia PDF Downloads 128

Authors: Javad Sadoghi Yazdi, Robb Eric S. Moss

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This paper utilizes a probabilistic liquefaction triggering method for modeling post-liquefaction ground deformation. This cone penetration test CPT-based liquefaction triggering is employed to estimate the factor of safety against liquefaction (FSL) and compute the maximum cyclic shear strain (γmax). The study identifies a maximum PL value of 90% across various relative densities, which challenges the decrease from 90% to 70% as relative density decreases. It reveals that PL ranges from 5% to 50% for volumetric strain (εvol) less than 1%, while for εvol values between 1% and 3.2%, PL spans from 50% to 90%. The application of the CPT-based simplified liquefaction triggering procedures has been employed in previous researches to estimate liquefaction ground-failure indices, such as the Liquefaction Potential Index (LPI) and Liquefaction Severity Number (LSN). However, several studies have been conducted to highlight the variability in liquefaction probability calculations, suggesting a more accurate depiction of liquefaction likelihood. Consequently, the utilization of these simplified methods may not offer practical efficiency. This paper further investigates the efficacy of various established liquefaction vulnerability parameters, including LPI and LSN, in explaining the observed liquefaction-induced damage within residential zones of Christchurch, New Zealand using results from CPT database.

Keywords: cone penetration test (CPT), liquefaction, postliquefaction, ground failure

Procedia PDF Downloads 73

Authors: Salvador Treviño-Martinez, Christian Reich-Lopez

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This paper investigates the relationship between website appeal and brand value outcomes (brand attraction, brand loyalty, brand relationship, and brand experience), considering the mediating effect of emotional attractiveness. Data were collected from 221 customers of a quick-service restaurant in Culiacan, Mexico, using an online survey distributed via WhatsApp, following the clients' navigation of the restaurant's website. The study employed PLS-SEM to test the proposed hypotheses and performed 5,000 bootstrapping subsamples to obtain results. The findings indicate that consistent image, a key component of website appeal, has a statistically significant direct and mediated effect (through emotional attractiveness) on the aforementioned brand outcomes. The study's limitations include the convenience sampling method and the single company client database used for the sample composition. This research contributes to the branding and website quality literature by testing nine hypotheses using the Stimuli-Organism-Response theoretical approach in an underexplored context: quick-service restaurants in Latin America.

Keywords: website appeal, branding, emotional attractiveness, consistent image, website quality

Procedia PDF Downloads 93

Authors: Emi Yuda, Yutaka Yoshida, Junichiro Hayano

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Distinct circadian rhythm of activity, i.e., high activity during the day and deep rest at night are a typical feature of a healthy lifestyle. Exposure to the skylight is thought to be an important factor to increase arousal level and maintain normal circadian rhythm. To examine whether sunshine hours influence the day-night contract of activity, we analyzed the relationship between 24-hour heart rate (HR) and weather data of the recording day. We analyzed data in 36,500 males and 49,854 females of Allostatic State Mapping by Ambulatory ECG Repository (ALLSTAR) database in Japan. Median (IQR) sunshine duration was 5.3 (2.8-7.9) hr. While sunshine hours had only modest effects of increasing 24-hour average HR in either gender (P=0.0282 and 0.0248 for male and female) and no significant effects on nighttime HR in either gender, it increased daytime HR (P = 0.0007 and 0.0015) and day-night HF difference in both genders (P < 0.0001 for both) even after adjusting for the effects of average temperature, atmospheric pressure, and humidity. Our observations support for the hypothesis that longer sunshine hours enhance circadian rhythm of activity.

Keywords: big data, circadian rhythm, heart rate, sunshine

Procedia PDF Downloads 165

Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

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The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

Procedia PDF Downloads 86

Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

Procedia PDF Downloads 642

Authors: Hasan Ashkanani

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Pottery assemblages from the site of Al-Khidr on Failaka Island, Kuwait, were analysed in order to reconstruct the chemical composition of Bronze Age wares and to build a mineralogical database of Bronze Age pottery dated from Failaka Periods 1–3B (2000–1650 BCE). A total of 145 ceramic sherds from Al-Khidr, as well as reference groups, were analysed by non-destructive portable X-ray fluorescence (pXRF) spectrometry. Preliminarily petrographic thin-section analysis was applied to four samples to reconstruct possible clay paste recipes and to identify raw materials. The results indicate that geochemical analyses can successfully distinguish subgroups within a typological category of ceramic assemblages. The results identified two subgroups within the Al-Khidr typological category: the Dilmun Barbar tradition and the Mesopotamian tradition. Future comparative compositional studies can be conducted to explore other aspects of craft specialisation, such as ceramic technological choices and possibly the influence of sociopolitical units

Keywords: Kuwait archaeology, pottery, pXRF, Dilmun

Procedia PDF Downloads 141

Authors: Stephan P. Barkhuizen, Deon Greyling, Ryan J. Miller

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The accurate determination of the engineering parameters of soil is necessary for the design of geotechnical structures, such as Tailings Storage Facilities. The shear strength and saturated permeability of soil and tailings samples obtained from 14 sites located in the copper belt in the Democratic Republic of the Congo have been tested at six commercial soil laboratories in South Africa. This study compiles a database of the test results proved by the soil laboratories. The samples have been categorised into clay, silt, and sand, based on the Unified Soil Classification System, with tailings kept separate. The effective friction angle (Φ’) and cohesion (c’) were interpreted from the stress paths, in s’:t space, obtained from triaxial tests. The minimum, lower quartile, median, upper quartile, and maximum values for Φ’,c’, and saturated hydraulic conductivity (k) have been determined for the soil sample. The objective is to provide statistics of the measured values of the engineering properties for the TSF borrow material, foundation soils and tailings of this region.

Keywords: Democratic Republic of the Congo, laboratory test work, soil engineering parameter variation, tailings storage facilities

Procedia PDF Downloads 68

Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

Procedia PDF Downloads 304

Authors: Ahmed Hariri

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E-Learning has become a necessity in the advanced education. It is easier for the student and teacher communication also it speed up the process with less time and less effort. With the progress and the enormous development of distance education must keep up with this age of making a website that allows students and teachers to take all the advantages of advanced education. In this regards, we developed University Short courses web application which is specially designed for Faculty of computing and information technology, Rabigh, Kingdom of Saudi Arabia. After an elaborate review of the current state-of-the-art methods of teaching and learning, we found that instructors deliver extra short courses and workshop to students to enhance the knowledge of students. Moreover, this process is completely manual. The prevailing methods of teaching and learning consume a lot of time; therefore in this context, University Short courses web application will help to make process easy and user friendly. The site allows for students can view and register short courses online conducted by instructor also they can see courses starting dates, finishing date and locations. It also allows the instructor to put things on his courses on the site and see the students enrolled in the study material. Finally, student can print the certificate after finished the course online. ASP.NET, SQLSERVER, JavaScript SQL SERVER Database will use to develop the University Short Courses web application.

Keywords: e-learning, short courses, ASP.NET, SQL SERVER

Procedia PDF Downloads 135

Authors: Kehinde Adeyeye Adelabu

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Computer applications has completely revolutionized the way of life of people which does not exclude the field of sport education. There are computer technologies which help to enhance teaching in every field of education. Invention of computers has done great to the field of education. This study was therefore carried out to examine the effects and merits of computer operations in Human Kinetics Education and Sports. The study was able to identify the component of computer, uses of computer in Human Kinetics education (sports), computer applications in some branches of human kinetics education. A qualitative research method was employed by the author in gathering experts’ views and used to analyze the effects and merits of computer applications in the field of human kinetics education. No experiment was performed in the cause of carrying out the study. The source of information for the study was text-books, journal, articles, past project reports, internet i.e. Google search engine. Computer has significantly helped to improve Education (Human Kinetic), it has complemented the basic physical fitness testing and gave a more scientific basis to the testing. The use of the software and packages has made cost projections, database applications, inventory control, management of events, word processing, electronic mailing and record keeping easier than the pasts.

Keywords: application, computer operation, education, human kinetics

Procedia PDF Downloads 186

Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

Procedia PDF Downloads 411

Authors: Mohamed Wahba

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Objective: To build a comparative arm for product (X) in specific gene mutated advanced gastrointestinal cancer using real world evidence to fulfill HTA requirements in drug evaluation. Methods: Data for product (X) were collected from phase II clinical trial while real world data for (Y) and (Z) were collected from US database. Real-world (RW) cohorts were matched to clinical trial base line characteristics using weighting by odds method. Outcomes included progression-free survival (PFS) and overall survival (OS) rates. Study location and participants: Internationally (product X, n=80) and from USA (Product Y and Z, n=73) Results: Two comparisons were made: trial cohort 1 (X) versus real-world cohort 1 (Z), trial cohort 2 (X) versus real-world cohort 2 (Y). For first line, the median OS was 9.7 months (95% CI 8.6- 11.5) and the median PFS was 5.2 months (95% CI 4.7- not reached) for real-world cohort 1. For second line, the median OS was 10.6 months (95% CI 4.7- 27.3) for real-world cohort 2 and the median PFS was 5.0 months (95% CI 2.1- 29.3). For OS analysis, results were statistically significant but not for PFS analysis. Conclusion: This study provided the clinical comparative outcomes needed for HTA evaluation.

Keywords: real world evidence, pharmacoeconomics, HTA agencies, oncology

Procedia PDF Downloads 90

Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad

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In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.

Keywords: reliability, availability Gumbel-Hougaard family copula, MTTF, internet data centre

Procedia PDF Downloads 532

Authors: Kai Qian, Lixin Tao

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Mobile devices such as smartphones are getting more and more popular in our daily lives. The security vulnerability and threat attacks become a very emerging and important research and education topic in computing security discipline. There is a need to have an innovative mobile security hands-on laboratory to provide students with real world relevant mobile threat analysis and protection experience. This paper presents an authentic teaching and learning mobile security approach with smartphone devices which covers most important mobile threats in most aspects of mobile security. Each lab focuses on one type of mobile threats, such as mobile messaging threat, and conveys the threat analysis and protection in multiple ways, including lectures and tutorials, multimedia or app-based demonstration for threats analysis, and mobile app development for threat protections. This authentic learning approach is affordable and easily-adoptable which immerse students in a real world relevant learning environment with real devices. This approach can also be applied to many other mobile related courses such as mobile Java programming, database, network, and any security relevant courses so that can learn concepts and principles better with the hands-on authentic learning experience.

Keywords: mobile computing, Android, network, security, labware

Procedia PDF Downloads 407

Authors: Etta Conteh, Tracy Macintosh

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Introduction: Restraints are often used in the Emergency Department when it is necessary for a patient to be restrained in order to decrease their agitation and better treat them. Chemical and physical restraints may be used on these patients at the discretion of the medical provider. Racism and injustice are rampant within our country, and medicine and healthcare are not spared. While racism and racial bias in medicine and healthcare have been studied, information on the differences in the use of restraints by race are scarce. Objective: The objective of this study is to determine if African Americans and Hispanic-American patients are restrained at higher rates compared to their White counterparts. Methods: This study will be carried out through a retrospective analysis utilizing the Hospital Corporation of America (HCA) national Emergency Department (ED) and inpatient database with patient visits from 2016-2019. All patient visits, with patients aged 18 years or older, will be reviewed, looking specifically for the race and the use and type of restraints. Other factors, such a pre-existing psychiatric condition, will be used for sub-analysis. Rationale: The outcome of this project will demonstrate the absence or presence of a racial disparity in the use of restraints in the Emergency Department. These results can be used as a foundation for improving racial equity in healthcare treatment.

Keywords: emergency medicine, public health, racism, restraint use

Procedia PDF Downloads 279

Authors: Anna Kizinska

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The research aims at discussing Polish and British incongruent terms that refer to company law. The Polish terms under analysis appear in the Polish Code of Commercial Partnerships and Companies and constitute legal terms or factual terms. The English equivalents of each Polish term under research appear in two Polish Code of Commercial Partnerships and Companies translations into English. The theoretical part of the paper includes the presentation of the definitions of a system-bound term and incongruity of terms. The aim of the analysis is to check if the classification of translation methods used in civil law terms translation comprehends the translation methods applied while translating company law terms into English. The translation procedures are defined according to Newmark. The stages of the research include 1) presentation of a definition of a Polish term, 2) enumerating the so-far published English equivalents of a given Polish term and comparing their definitions (as long as they appear in English law dictionaries ) with the definition of a given Polish term under analysis, 3) checking whether an English equivalent appears or not in, among others, the sources of the British law (legislation.gov.uk database) , 4) identifying the translation method that was applied while forming a given English equivalent.

Keywords: translation, legal terms, equivalence, company law, incongruency

Procedia PDF Downloads 90

Authors: Tamas Madl

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Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 236

Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: energy production, meteorological data, irradiance decomposition, solar photovoltaic system

Procedia PDF Downloads 143

Authors: H. Chassaigne, S. Gioria, J. Lobo Vicente, D. Carpi, P. Barboro, G. Tomasi, A. Kinsner-Ovaskainen, F. Rossi

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Emerging approaches in the area of exposure to nanomaterials and assessment of human health effects combine the use of in vitro systems and analytical techniques to study the perturbation of the proteome and/or the metabolome. We investigated the modification in the cytoplasmic compartment of the Balb/3T3 cell line exposed to gold nanoparticles. On one hand, the proteomic approach is quite standardized even if it requires precautions when dealing with in vitro systems. On the other hand, metabolomic analysis is challenging due to the chemical diversity of cellular metabolites that complicate data elaboration and interpretation. Differentially expressed proteins were found to cover a range of functions including stress response, cell metabolism, cell growth and cytoskeleton organization. In addition, de-regulated metabolites were annotated using the HMDB database. The "omics" fields hold huge promises in the interaction of nanoparticles with biological systems. The combination of proteomics and metabolomics data is possible however challenging.

Keywords: data processing, gold nanoparticles, in vitro systems, metabolomics, proteomics

Procedia PDF Downloads 503

Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

Procedia PDF Downloads 302

Authors: Adnan A. Y. Mustafa

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Image matching is a fundamental problem that arises frequently in many aspects of robot and computer vision. It can become a time-consuming process when matching images to a database consisting of hundreds of images, especially if the images are big. One approach to reducing the time complexity of the matching process is to reduce the search space in a pre-matching stage, by simply removing dissimilar images quickly. The Probabilistic Matching Model for Binary Images (PMMBI) showed that dissimilarity detection between binary images can be accomplished quickly by random pixel mapping and is size invariant. The model is based on the gamma binary similarity distance that recognizes an image and its inverse as containing the same scene and hence considers them to be the same image. However, in many applications, an image and its inverse are not treated as being the same but rather dissimilar. In this paper, we present a comparative analysis of dissimilarity detection between PMMBI based on the gamma binary similarity distance and a modified PMMBI model based on a similarity distance that does distinguish between an image and its inverse as being dissimilar.

Keywords: binary image, dissimilarity detection, probabilistic matching model for binary images, image mapping

Procedia PDF Downloads 155

Authors: Ming Lu, Xiaojun Li, Bodi Lu, Juehui Xing

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Earthquake damage phenomenon of each large earthquake gives comprehensive and profound real test to the dynamic performance and failure mechanism of different engineering structures. Cognitive engineering structure characteristics through seismic damage phenomenon are often far superior to expensive shaking table experiments. After the earthquake, people will record a variety of different types of engineering damage photos. However, a large number of earthquake damage photographs lack sufficient information and reduce their using value. To improve the research value and the use efficiency of engineering seismic damage photographs, this paper objects to explore and show seismic damage background information, which includes the earthquake magnitude, earthquake intensity, and the damaged structure characteristics. From the research requirement in earthquake engineering field, the authors use the 2008 China Wenchuan M8.0 earthquake photographs, and provide four kinds of attribute indexes and classification, which are seismic information, structure types, earthquake damage parts and disaster causation factors. The final object is to set up an engineering structural seismic damage database based on these four attribute indicators and classification, and eventually build a website providing seismic damage photographs.

Keywords: attribute index, classification method, earthquake damage picture, engineering structure

Procedia PDF Downloads 765

Authors: Ehsan Mehryaar, Reza Bushehri

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One of the principal parameters defining the clay soil dynamic response is the strain-shear modulus relation. Predicting the strain and, subsequently, shear modulus reduction of the soil is essential for performance analysis of structures exposed to earthquake and dynamic loadings. Many soil properties affect soil’s dynamic behavior. In order to capture those effects, in this study, a database containing 1193 data points consists of maximum shear modulus, strain, moisture content, initial void ratio, plastic limit, liquid limit, initial confining pressure resulting from dynamic laboratory testing of 21 clays is collected for predicting the shear modulus vs. strain curve of soil. A model based on an extreme gradient boosting technique is proposed. A tree-structured parzan estimator hyper-parameter tuning algorithm is utilized simultaneously to find the best hyper-parameters for the model. The performance of the model is compared to the existing empirical equations using the coefficient of correlation and root mean square error.

Keywords: XGBoost, hyper-parameter tuning, soil shear modulus, dynamic response

Procedia PDF Downloads 203

Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici

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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic

Procedia PDF Downloads 336

Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 336

Authors: Gigih Supriyatno

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SQL injection is one of the most common types of attacks and has a very critical impact on web servers. In the worst case, an attacker can perform post-exploitation after a successful SQL injection attack. In the case of forensics web servers, web server analysis is closely related to log file analysis. But sometimes large file sizes and different log types make it difficult for investigators to look for traces of attackers on the server. The purpose of this paper is to help investigator take appropriate steps to investigate when the web server gets attacked. We use attack scenarios using SQL injection attacks including PHP backdoor injection as post-exploitation. We perform post-mortem analysis of web server logs based on Hypertext Transfer Protocol (HTTP) POST and HTTP GET method approaches that are characteristic of SQL injection attacks. In addition, we also propose structured analysis method between the web server application log file, database application, and other additional logs that exist on the webserver. This method makes the investigator more structured to analyze the log file so as to produce evidence of attack with acceptable time. There is also the possibility that other attack techniques can be detected with this method. On the other side, it can help web administrators to prepare their systems for the forensic readiness.

Keywords: web forensic, SQL injection, investigation, web shell

Procedia PDF Downloads 148

Authors: Lisnawati Hutagalung

Abstract:

Background: Low birth weight (LBW) is one cause of newborn death. Babies with low birth weight tend to have slower cognitive development, growth retardation, more at risk of infectious disease event at risk of death. Objective: Identifying risk factors and dominant factors that influence the incidence of LBW in Indonesia. Method: This research used some database of public health such as Google Scholar, UGM journals, UI journals and UNAND journals in 2012-2015. Data were filtered using keywords ‘Risk Factors’ AND ‘Cause LBW’ with amounts 2757 study. The filtrate obtained 5 public health research that meets the criteria. Results: Risk factors associated with LBW, among other environment factors (exposure to cigarette smoke and residence), social demographics (age and socio-economic) and maternal factors (anemia, placental abnormal, nutritional status of mothers, examinations antenatal, preeclampsia, parity, and complications in pregnancy). Anemia and nutritional status become the dominant factor affecting LBW. Conclusions: The risk factors that affect LBW, most commonly found in the maternal factors. The dominant factors are a big effect on LBW is anemia and nutritional status of the mother during pregnancy.

Keywords: low birth weight, anemia, nutritional status, the dominant factor

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