Search results for: arrhythmia database

Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

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An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Nguyen Van Anh Le, Mafuyu Kitahara

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In several languages, it is widely acknowledged that vowels are longer before voiced consonants than before voiceless ones such as English. However, in Mandarin Chinese, Vietnamese, Japanese, and Korean, the distribution of voiced-voiceless stop contrasts and long-short vowel differences are vastly different from English. The purpose of this study is to determine whether these targeted learners' L2 English production and perception change in terms of vowel duration as a function of stop voicing. The production measurements in the database of Asian learners revealed a distinct effect than the one observed in native speakers. There was no evident vowel lengthening patterns. The results of the perceptual experiment with 24 participants indicated that individuals tended to prefer voiceless stops when preceding vowels were shortened, but there was no statistically significant difference between intermediate, upper-intermediate, and advanced-level learners. However, learners demonstrated distinct perceptual patterns for various vowels and stops. The findings have valuable implications for L2 English speech acquisition. Keywords: voiced/voiceless stops, preceding vowel duration, voiced/voiceless perception, L2 English, L1 Mandarin Chinese, L1 Vietnamese, L1 Japanese, L1 Korean

Keywords: voiced/voiceless stops, preceding vowel duration, voiced/voiceless perception, L2 english

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Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

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Authors: Zhichao Jiao, Craig Farnham, Jihui Yuan, Kazuo Emura

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It is common to use the outdoor design weather data to select the air-conditioning capacity in the building design stage. The outdoor design weather data are usually comprised of multiple meteorological elements for a 24-hour period separately, but the dependency between the elements is not well considered, which may cause an overestimation of selecting air-conditioning capacity. Considering the dependency between the air temperature and global solar radiation, we used the copula approach to model the joint distributions of those two weather elements and suggest a new method of selecting more credible outdoor design conditions based on the specific simultaneous occurrence probability of air temperature and global solar radiation. In this paper, the 10-year period hourly weather data from 2001 to 2010 in Osaka, Japan, was used to analyze the dependency structure and joint distribution, the result shows that the Joe-Frank copula fit for almost all hourly data. According to calculating the simultaneous occurrence probability and the common exceeding probability of air temperature and global solar radiation, the results have shown that the maximum difference in design air temperature and global solar radiation of the day is about 2 degrees Celsius and 30W/m2, respectively.

Keywords: energy conservation, design weather database, HVAC, copula approach

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Authors: Wipada Chaiwchan, Patcharee Klinhom

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This research is aimed to develop the online-class scheduling management system and improve as a complex problem solution, this must take into consideration in various conditions and factors. In addition to the number of courses, the number of students and a timetable to study, the physical characteristics of each class room and regulations used in the class scheduling must also be taken into consideration. This system is developed to assist management in the class scheduling for convenience and efficiency. It can provide several instructors to schedule simultaneously. Both lecturers and students can check and publish a timetable and other documents associated with the system online immediately. It is developed in a web-based application. PHP is used as a developing tool. The database management system was MySQL. The tool that is used for efficiency testing of the system is questionnaire. The system was evaluated by using a Black-Box testing. The sample was composed of 2 groups: 5 experts and 100 general users. The average and the standard deviation of results from the experts were 3.50 and 0.67. The average and the standard deviation of results from the general users were 3.54 and 0.54. In summary, the results from the research indicated that the satisfaction of users was in a good level. Therefore, this system could be implemented in an actual workplace and satisfy the users’ requirement effectively

Keywords: timetable, schedule, management system, online

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Authors: Muhammad Jawad Hashmi

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The idea of nuclear terrorism is as old as nuclear weapons but the global concerns of likelihood of nuclear terrorism are uncertain. Post 9/11 trends manifest that terrorists are believers of massive causalities. Innovation in terrorist’s tactics, sophisticated weaponry, vulnerability, theft and smuggling of nuclear/radiological material, connections between terrorists, black market and rough regimes are signaling seriousness of upcoming challenges as well as global trends of “terror-transnationalism.” Furthermore, the International-Atomic-Energy-Agency’s database recorded 2734 incidents regarding misuse, unauthorized possession, trafficking of nuclear material etc. Since, this data also includes incidents from south Asia, so, there is every possibility to claim that such illicit activities may increase in future, mainly due to expansion of nuclear industry in South Asia. Moreover, due to such mishaps the region is vulnerable to threats of nuclear terrorism. This is also a reason that the region is in limelight along with issues such as rapidly growing nuclear arsenals, nuclear safety and security, terrorism and political instability. With this backdrop, this study is aimed to investigate the prevailing threats and challenges in South Asia vis a vis nuclear safety and security. A comparative analysis of the overall capabilities would be done to identify the areas of cooperation to eliminate the probability of nuclear/radiological terrorism in the region.

Keywords: nuclear terrorism, safety, security, South Asia, india, Pakistan

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Clara Inés Pardo Martínez

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In emerging economies, recycling is an opportunity for the cities to increase the lifespan of sanitary landfills, reduce the costs of the solid waste management, decrease the environmental problems of the waste treatment through reincorporate waste in the productive cycle and protect and develop people’s livelihoods of informal waste pickers. However, few studies have analysed the possibilities and strategies to integrate formal and informal sectors in the solid waste management for the benefit of both. This study seek to make a strength, weakness, opportunity, and threat (SWOT) analysis in three recycling associations of Bogotá with the aim to understand and determine the situation of recycling from perspective of informal sector in its transition to enter as authorized waste providers. Data used in the analysis are derived from multiple strategies such as literature review, the Bogota’s recycling database, focus group meetings, governmental reports, national laws and regulations and specific interviews with key stakeholders. Results of this study show as the main stakeholders of formal and informal sector of waste management can identify the internal and internal conditions of recycling in Bogotá. Several strategies were designed based on the SWOTs determined, could be useful for Bogotá to advance and promote recycling as a key strategy for integrated sustainable waste management in the city.

Keywords: Bogotá, recycling, solid waste management, SWOT analysis

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Authors: Zahra Tolou-Ghamari

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Objective: Health care associated with multiresistant pathogens is rising globally. It is well known that nosocomial infections increase hospital stay, morbidity, mortality, and disability. Therefore, the aim of this study was to define the occurrence of nosocomial infections in a tertiary hospital in Isfahan/Iran. Materials and Methods: The data were extracted from the official database of hospital nosocomial infections records that included 9152 vertical rows. For each patient, the reported infections were coded by number as UTI-SUTI; Code 55, VAE-PVAP; Code 56, BSI-LCBI Code 19, SSI-DIP; Code 14, and so on. For continuous variables, mean ± standard deviation and for categorical variables, the frequency was used. Results: The study population was 5542 patients, comprised of males (n=3282) and females (n=2260). With a minimum of 15 and a maximum of 99, the mean age in 5313 patients was 58.5 ± 19.1 years old. The highest reported nosocomial infections (n= 77%) were associated with the ages 30-80 years old. Sites of nosocomial infections in 87% were as: VAE-PVAP; 27.3%, VAE-IVAC; 7.7, UTI-SUTI; 29.5%, BSI-LCBI; 12.9%, SSI-DIP; 9.5% and other individual infection (13%) with the main pathogens klebsiella pneumonia, acinetobacter baumannii and staphylococcus. Conclusions: For an efficient surveillance system, adopting pharmacotherapy used antibiotics in terms of monotherapy or polypharmacy control policy, in addition to advanced infection control programs at regional and national levels in Iran recommended.

Keywords: infection, nosocomial, ventilator, blood stream, Isfahan, Iran

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Authors: Uzoma Emmanuel Igboji

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This paper examines the influence of public debts (external and internal) on economic growth and development in Nigeria from (1980-2015). The study uses aggregate GDP as a proxy for economic growth, per capital income as a proxy for standard of living and Government expenditure on health as a proxy for human capital development, while Foreign Direct Investment, Unemployment rate, and Oil revenue were used as control variables. The study made use of ex-post facto research design with the data extracted from the Central Bank of Nigeria (CBN) Statistical Bulletin and the World Bank database. It adopted a multiple regression analysis of the ordinary least square (OLS) method with the help of E-View version 3.0. The results revealed that external debt has a negative and insignificant effect on GDP, per capital income and human capital development. The study concluded that external debts were being channeled to meet the recurrent expenditures of the nation’s economy at the expense of productive investment that could stimulate growth and poverty alleviation. It, however, recommended that government should ensure that the bulk of the total borrowings are mostly sourced from within the domestic economy so that the repayment of the principal and interest will serve as a crowd in-effect rather that crowd out-effect which in turn further accelerates the country’s economic growth and development.

Keywords: economic growth, external debt, internal debt, Nigeria

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Authors: Gabriela Wasileski, Debra L. Stanley

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Maryland efforts to decrease the juvenile criminality and recidivism shifts towards evidence based sentencing. While in theory the evidence based sentencing has an impact on the reduction of juvenile delinquency and drug abuse; the assessment of juveniles’ risk and needs usually lacks crucial information about juvenile’s prior victimization. The Maryland Comprehensive Assessment and Service Planning (MCASP) Initiative is the primary tool for developing and delivering a treatment service plan for juveniles at risk. Even though it consists of evidence-based screening and assessment instruments very little is currently known regarding the effectiveness and the impact of the assessment in general. In keeping with Maryland’s priority to develop successful evidence-based recidivism reduction programs, this study examined results of assessments based on MCASP using a representative sample of the juveniles at risk and their assessment results. Specifically, it examined: (1) the results of the assessments in an electronic database (2) areas of need that are more frequent among delinquent youth in a system/agency, (3) the overall progress of youth in an agency’s care (4) the impact of child victimization and trauma experiences reported in the assessment. The project will identify challenges regarding the use of MCASP in Maryland, and will provide a knowledge base to support future research and practices.

Keywords: Juvenile Justice, assessment of risk and need, victimization and crime, recidivism

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Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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Authors: David A. Swanson, Lucky M. Tedrow

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Taylor’s Law is a widely observed empirical pattern that relates variances to means in sets of non-negative measurements via an approximate power function, which has found application to human mortality. This study adds to this research by showing that Taylor’s Law leads to a model that reasonably describes the relationship between life expectancy at birth (e0, which also is equal to mean age at death in a life table) and variance at age of death in seven World Bank regional life tables measured at two points in time, 1970 and 2000. Using as a benchmark a non-random sample of four Japanese female life tables covering the period from 1950 to 2004, the study finds that the simple linear model provides reasonably accurate estimates of variance in age at death in a life table from e0, where the latter range from 60.9 to 85.59 years. Employing 2017 life tables from the Human Mortality Database, the simple linear model is used to provide estimates of variance at age in death for six countries, three of which have high e0 values and three of which have lower e0 values. The paper provides a substantive interpretation of Taylor’s Law relative to e0 and concludes by arguing that reasonably accurate estimates of variance in age at death in a period life table can be calculated using this approach, which also can be used where e0 itself is estimated rather than generated through the construction of a life table, a useful feature of the model.

Keywords: empirical pattern, mean age at death in a life table, mean age of a stationary population, stationary population

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Authors: Sanchali Das, Swapan Debbarma

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Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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Authors: Haitao Yang, Zhenjiang Ruan, Fei Xu, Lanting Xia

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Industry data centers often need to sync data changes reliably and instantly from a large-scale of heterogeneous autonomous relational databases accessed via the not-so-reliable Internet, for which a practical universal sync middle of low maintenance and operation costs is most wanted, but developing such a product and adapting it for various scenarios are a very sophisticated and continuous practice. The authors have been devising, applying, and optimizing a generic sync middleware system, named GSMS since 2006, holding the principles or advantages that the middleware must be SyncML-compliant and transparent to data application layer logic, need not refer to implementation details of databases synced, does not rely on host computer operating systems deployed, and its construction is light weighted and hence, of low cost. A series of ultimate experiments with GSMS sync performance were conducted for a persuasive example of a source relational database that underwent a broad range of write loads, say, from one thousand to one million intensive writes within a few minutes. The tests proved that GSMS has achieved an instant sync level of well below a fraction of millisecond per record sync, and GSMS’ smooth performances under ultimate write loads also showed it is feasible and competent.

Keywords: heterogeneous massive data, instantly sync intensive writes, Internet generic middleware design, optimization

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Authors: Sérgio J. Teixeira, João J. Ferreira

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Tourism frequently gets identified as one of the sectors with the greatest potential for expansion on a global scale and hence conveying the importance of attempting to better understand the regional factors of competitiveness prevailing in this sector. This study’s objective essentially strives to provide a mapping of the scientific publications and the intellectual knowledge therein contained while conveying past research trends and identifying potential future lines of research in the fields of regional competitiveness and tourism innovation. This correspondingly deploys a systematic review of the literature in keeping with the bibliometric approach based upon VOSviewer software, with a particular focus on drafting maps for visualising the underlying intellectual structure. This type of analysis encapsulates the number of articles published and their annual number of citations for the period between 1900 and 2016 as registered by the Web of Science database. The results demonstrate how the intellectual structure on regional competitiveness divides essentially into three major categories: regional competitiveness, tourism innovation, and tourism clusters. Thus, the main contribution of this study arises out of identifying the main research trends in this field and the respective shortcomings and specific needs for future scientific research in the field of regional competitiveness and innovation in tourism.

Keywords: regional competitiveness, tourism cluster, bibliometric studies, tourism innovation, systematic review

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Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: automatic detection, defects, fracture lines, wavelets

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Authors: Sulaiman A. Alrumman, Abd El-Latif Hesham

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Despite medical progress worldwide, dental caries are still widespread. Miswak is derived from the plant arak (Salvadora persica). It is used by Muslim people as a natural product for the cleansing of teeth, to ensure oral and dental hygiene. This study was designed to evaluate the antimicrobial effects of ethanol, methanol, and ethanol/methanol extracts of miswak against three bacterial pathogens of the oral cavity. The pathogens were isolated from the oral cavity of volunteers/patients and were identified on the basis of 16S rRNA gene amplification data. Sequence comparisons were made with 16S rRNA gene sequences available in the GenBank database. The results of sequence alignment and phylogenetic analysis identified the three pathogens as being Staphylococcus aureus strain KKU-020, Enterococcus faecalis strain KKU-021 and Klebsiella pneumoniae strain KKU-022. All miswak extracts showed powerful antimicrobial activity against the three pathogens. The maximum zone of inhibition (40.67±0.88 mm) was observed against E. faecalis with ethanolic extracts whilst methanolic extracts showed the minimum zone of inhibition (10.33±0.88 mm) against K. pneumonia KKU-022. Based on the significant effects of the miswak extracts against the oral cavity pathogens in our study, we recommend that miswak is to be used as a dental hygiene method to prevent tooth caries.

Keywords: antibacterial, miswak, Salvadora persica, oral cavity pathogens

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Malik Abdul Jabbar Zen, Wiwik Misaco Yuniarti, Azisya Amalia Karimasari, Novita Priandini

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Zoonos is as an infectiontransmitted froma nimals to human sand vice versa currently having increased in the last 20 years. The experts/scientists predict that zoonosis will be a threat to the community in the future since it leads on 70% emerging infectious diseases (EID) and the high mortality of 50%-90%. The zoonosis’ spread from animal to human is caused by contaminated food known as foodborne disease. One World One Health, as the conceptual prevention toward zoonosis, requires the crossed disciplines cooperation to accelerate and streamlinethe handling ofanimal-based disease. E-Vet Smart Rapid System is an integrated innovation in the veterinary expertise application is able to facilitate the prevention, treatment, and educationagainst pandemic diseases and zoonosis. This system is constructed by Decision Support System (DSS) method provides a database of knowledge that is expected to facilitate the identification of disease rapidly, precisely, and accurately as well as to identify the deduction. The testingis conducted through a black box test case and questionnaire (N=30) by validity and reliability approach. Based on the black box test case reveals that E-Vet Rapid System is able to deliver the results in accordance with system design, and questionnaire shows that this system is valid (r > 0.361) and has a reliability (α > 0.3610).

Keywords: diagnosis, disease, expert systems, livestock, zoonosis

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Authors: Chen-Fu Wang, Lin-Ya Kung

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For traditional painting materials, the artisan used to combine the pigments with different binders to create colors. As time goes by, the materials used for painting evolved from natural to chemical materials. The vast variety of ingredients used in chemical materials has complicated restoration work; it makes conservation work more difficult. Conservation work also becomes harder when the materials cannot be easily identified; therefore, it is essential that we take a more scientific approach to assist in conservation work. Paintings materials are high molecular weight polymer, and their analysis is very complicated as well other contamination such as smoke and dirt can also interfere with the analysis of the material. The current methods of composition analysis of painting materials include Fourier transform infrared spectroscopy (FT-IR), mass spectrometer, Raman spectroscopy, X-ray diffraction spectroscopy (XRD), each of which has its own limitation. In this study, FT-IR was used to analyze the components of the paint coating. We have taken the most commonly seen materials as samples and deteriorated it. The aged information was then used for the database to exam the temple painting materials. By observing the FT-IR changes over time, we can tell all of the painting materials will be deteriorated by the UV light, but only the speed of its degradation had some difference. From the deterioration experiment, the acrylic resin resists better than the others. After collecting the painting materials aging information on FT-IR, we performed some test on the paintings on the temples. It was found that most of the artisan used tune-oil for painting materials, and some other paintings used chemical materials. This method is now working successfully on identifying the painting materials. However, the method is destructive and high cost. In the future, we will work on the how to know the painting materials more efficiently.

Keywords: temple painting, painting material, conservation, FT-IR

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Authors: Chang Li-Yu

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Purposes: The present research focuses on exploring the latent growth model of psychological capital in disadvantaged adolescents and assessing its relationship with subjective well-being. Methods: Longitudinal study design was utilized and the data was from Taiwan Database of Children and Youth in Poverty (TDCYP), using the student questionnaires from 2009, 2011, and 2013. Data analysis was conducted using both univariate and multivariate latent growth curve models. Results: This study finds that: (1) The initial state and growth rate of individual factors such as parent-child relationships, psychological capital, and subjective wellbeing in economically disadvantaged adolescents have a predictive impact; (2) There are positive interactive effects in the development among factors like parentchild relationships, psychological capital, and subjective well-being in economically disadvantaged adolescents; and (3) The initial state and growth rate of parent-child relationships and psychological capital in economically disadvantaged adolescents positively affect the initial state and growth rate of their subjective well-being. Recommendations: Based on these findings, this study concretely discusses the significance of psychological capital and family cohesion for the mental health of economically disadvantaged youth and offers suggestions for counseling, psychological therapy, and future research.

Keywords: economically disadvantaged adolescents, psychological capital, parent-child relationships, subjective well-beings

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Authors: Uzma Saqib, Mirza S. Baig

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Myeloid differentiation primary response protein 88 (MYD88) has long been considered a central player in the inflammatory pathway. Recent studies clearly suggest that it is an important therapeutic target in inflammation. On the other hand, a recent study on the interaction between the orphan nuclear receptor (Nur77) and p38α, leading to increased lipopolysaccharide-induced hyperinflammatory response, suggests this binary complex as a therapeutic target. In this study, we have designed inhibitors that can inhibit both MYD88 and Nur77 at the same time. Since both MYD88 and Nur77 are an integral part of the pathways involving lipopolysaccharide-induced activation of NF-κB-mediated inflammation, we tried to target both proteins with the same library in order to retrieve compounds having dual inhibitory properties. To perform this, we developed a homodimeric model of MYD88 and, along with the crystal structure of Nur77, screened a virtual library of compounds from the traditional Chinese medicine database containing ~61,000 compounds. We analyzed the resulting hits for their efficacy for dual binding and probed them for developing a common pharmacophore model that could be used as a prototype to screen compound libraries as well as to guide combinatorial library design to search for ideal dual-target inhibitors. Thus, our study explores the identification of novel leads having dual inhibiting effects due to binding to both MYD88 and Nur77 targets.

Keywords: drug design, Nur77, MYD88, inflammation

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Authors: Bolin Hua

Abstract:

In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

Abstract:

The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

Procedia PDF Downloads 365

Authors: Mohammad Izadkhah, Mojtaba Hoseini, Alireza Khalili Tehrani

Abstract:

In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation.

Keywords: video tracking, particle filter, greedy snake, neural network

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Authors: Afshin Moazami, Andrea Schiffauerova

Abstract:

The objective of this work is to investigate the development and the role of collaboration networks in the creation of knowledge and innovations in the US and Canada, with a special focus on Quebec. In order to create scientific networks, the data on journal articles were extracted from SCOPUS, and the networks were built based on the co-authorship of the journal papers. For innovation networks, the USPTO database was used, and the networks were built on the patent co-inventorship. Various indicators characterizing the evolution of the network structure and the positions of the researchers and inventors in the networks were calculated. The comparison between the United States, Canada, and Quebec was then carried out. The preliminary results show that the nature of scientific collaboration networks differs from the one seen in innovation networks. Scientists work in bigger teams and are mostly interconnected within one giant network component, whereas the innovation network is much more clustered and fragmented, the inventors work more repetitively with the same partners, often in smaller isolated groups. In both Canada and the US, an increasing tendency towards collaboration was observed, and it was found that networks are getting bigger and more centralized with time. Moreover, a declining share of knowledge transfers per scientist was detected, suggesting an increasing specialization of science. The US collaboration networks tend to be more centralized than the Canadian ones. Quebec shares a lot of features with the Canadian network, but some differences were observed, for example, Quebec inventors rely more on the knowledge transmission through intermediaries.

Keywords: Canada, collaboration, innovation network, scientific network, Quebec, United States

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Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

Abstract:

Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

Procedia PDF Downloads 375