Search results for: bioinformatics analysis

Authors: Eric Bang

Abstract:

Interactions between receptors and ligands are crucial for many essential biological processes, including neurotransmission and metabolism. Ligand-receptor analyses that examine cell behavior and interactions often utilize cell type-specific RNA expressions from single-cell RNA sequencing (scRNA-seq) data. Using CellPhoneDB, a public repository consisting of ligands, receptors, and ligand-receptor interactions, the cell-cell interactions were explored in a specific scRNA-seq dataset from kidney tissue and portrayed the results with dot plots and heat maps. Depending on the type of cell, each ligand-receptor pair was aligned with the interacting cell type and calculated the positori probabilities of these associations, with corresponding P values reflecting average expression values between the triads and their significance. Using single-cell data (sample kidney cell references), genes in the dataset were cross-referenced with ones in the existing CellPhoneDB dataset. For example, a gene such as Pleiotrophin (PTN) present in the single-cell data also needed to be present in the CellPhoneDB dataset. Using the single-cell transcriptomics data via slide-seq and reference data, the CellPhoneDB program defines cell types and plots them in different formats, with the two main ones being dot plots and heat map plots. The dot plot displays derived measures of the cell to cell interaction scores and p values. For the dot plot, each row shows a ligand-receptor pair, and each column shows the two interacting cell types. CellPhoneDB defines interactions and interaction levels from the gene expression level, so since the p-value is on a -log10 scale, the larger dots represent more significant interactions. By performing an interaction analysis, a significant interaction was discovered for myeloid and T-cell ligand-receptor pairs, including those between Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1), which is consistent with previous findings. It was proposed that an effective protocol would involve a filtration step where cell types would be filtered out, depending on which ligand-receptor pair is activated in that part of the tissue, as well as the incorporation of the CellPhoneDB data in a streamlined workflow pipeline. The filtration step would be in the form of a Python script that expedites the manual process necessary for dataset filtration. Being in Python allows it to be integrated with the CellPhoneDB dataset for future workflow analysis. The manual process involves filtering cell types based on what ligand/receptor pair is activated in kidney cells. One limitation of this would be the fact that some pairings are activated in multiple cells at a time, so the manual manipulation of the data is reflected prior to analysis. Using the filtration script, accurate sorting is incorporated into the CellPhoneDB database rather than waiting until the output is produced and then subsequently applying spatial data. It was envisioned that this would reveal wherein the cell various ligands and receptors are interacting with different cell types, allowing for easier identification of which cells are being impacted and why, for the purpose of disease treatment. The hope is this new computational method utilizing spatially explicit ligand-receptor association data can be used to uncover previously unknown specific interactions within kidney tissue.

Keywords: bioinformatics, Ligands, kidney tissue, receptors, spatial transcriptome

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Authors: Austyn Snowden

Abstract:

Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

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Authors: Pingping Lin, Xudong Luo

Abstract:

Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: application, natural language processing, online comments, sentiment analysis

Procedia PDF Downloads 263

Authors: Pallavi Roe

Abstract:

Violent crime is a significant public safety concern in urban areas across the United States, and Washington, DC, is no exception. This research discusses the prevalence and types of crime, particularly violent crime, in Washington, DC, along with the factors contributing to the high rate of violent crime in the city, including poverty, inequality, access to guns, and racial disparities. The organizations working towards ensuring safety in neighborhoods are also listed. The proposal to perform spatial and temporal analysis on violent crime and the use of guns in crime analysis is presented to identify patterns and trends to inform evidence-based interventions to reduce violent crime and improve public safety in Washington, DC. The stakeholders for crime analysis are also discussed, including law enforcement agencies, prosecutors, judges, policymakers, and the public. The anticipated result of the spatial and temporal analysis is to provide stakeholders with valuable information to make informed decisions about preventing and responding to violent crimes.

Keywords: crime analysis, spatial analysis, temporal analysis, violent crime

Procedia PDF Downloads 320

Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

Abstract:

Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

Procedia PDF Downloads 262

Authors: Sonika Raj, Amarjeet Singh, Vijay Lakshmi Sharma

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Introduction: In 21st century, due to revolution in Information and Communication Technologies (ICTs), there has been phenomenal development in quality and quantity of knowledge in the field of medical science. So, the access to relevant information to physicians is critical to the delivery of effective healthcare services to patients. The study was conducted to assess the information needs and attitudes of the medical professionals; to determine the sources and channels of information used by them; to ascertain the current usage of ICTs and the barriers faced by them in utilization of ICTs in health information access. Methodology: This descriptive cross-sectional study was carried in 2015 on hundred medical professionals working in public and private sectors of Chandigarh. The study used both quantitative and qualitative method for data collection. A semi structured questionnaire and interview schedule was used to collect data on information seeking needs, access to ICTs and barriers to healthcare information access. Five Data analysis was done using SPSS-16 and qualitative data was analyzed using thematic approach. Results: The most preferred sources to access healthcare information were internet (85%), trainings (61%) and communication with colleagues (57%). They wanted information on new drug therapy and latest developments in respective fields. All had access to computer with but almost half assessed their computer knowledge as average and only 3% had received training regarding usage. Educational status (p=0.004), place of work (p=0.004), number of years in job (p=0.004) and sector of job (p=0.04) of doctors were found to be significantly associated with their active search for information. The major themes that emerged from in-views were need; types and sources of healthcare information; exchange of information among different levels of healthcare providers; usage of ICTs to obtain and share information; barriers to access of healthcare information and quality of health information materials and involvement in their development process Conclusion and Recommendations: The medical professionals need information in their in their due course of work. However, information needs of medical professionals were not being adequately met. There should be training of professional regarding internet skills and the course on bioinformatics should be incorporated in the curricula of medical students. The policy framework must be formulated that will encourage and promote the use of ICTs as tools for health information access and dissemination.

Keywords: health information, ICTs, medical professionals, qualitative

Procedia PDF Downloads 349

Authors: A. B. Robert, Adam Pramadia, Calvin Andika

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The main purpose of this study is to explore consumer loyalty characteristic of mobile phone category in Indonesia. Second, this research attempts to identify consumer segment and to explore their profile in each segment as the basis of marketing strategy formulation. This study used some tools of multivariate analysis such as discriminant analysis and cluster analysis. Discriminate analysis used to discriminate consumer loyal and not loyal by using particular variables. Cluster analysis used to reveal various segment in mobile phone category. In addition to having better customer understanding in each segment, this study used descriptive analysis and cross tab analysis in each segment defined by cluster analysis. This study expected several findings. First, consumer can be divided into two large group of loyal versus not loyal by set of variables. Second, this study identifies customer segment in mobile phone category. Third, exploring customer profile in each segment that has been identified. This study answer a call for additional empirical research into different product categories. Therefore, a replication research is advisable. By knowing the customer loyalty characteristic, and deep analysis of their consumption behavior and profile for each segment, this study is very advisable for high impact marketing strategy development. This study contributes body of knowledge by adding empirical study of consumer loyalty, segmentation analysis in mobile phone category by multiple brand analysis.

Keywords: customer loyalty, segmentation, marketing strategy, discriminant analysis, cluster analysis, mobile phone

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Authors: Roslina Che Soh

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Best interest of the child has been the prevailing principle of the custody legislations of most nations in the world. The tremendous shift from parental rights to parental responsibilities throughout the centuries had made the principle of best interests of the child as the utmost matter which parents must uphold in child upbringing. Despite the commitment to this principle is significantly enshrined in the United Nation Convention on Rights of the Child, the content and application of the principle differs across borders. Differences persist notwithstanding many countries have experienced a substantial shift over the last several decades in the types of custodial arrangements that are thought to best serve children’s interests. The laws in Malaysia similarly uphold this principle but do not provide further deliberation on the principle itself. The principle is entirely developed by the courts through decided cases. Thus, this paper seeks to discuss the extent of the application of best interest of the child principle in custody disputes. In doing so, it attempts to provide an overview of the current laws and the approach of the Civil and the Shariah courts in Malaysia in applying the principle in determining custody disputes. For purposes of comparison, it briefly examines the legislations and the courts practices in Australia and England on this matter. The purpose is to determine the best standard to be adopted by Malaysia and to propose improvement to the laws whenever appropriate.

Keywords: child custody, best interest, Malaysian law, bioinformatics, biomedicine

Procedia PDF Downloads 275

Authors: Chothmal, Basant Agarwal

Abstract:

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Xiao Zhou, Jianlin Cheng

Abstract:

A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

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Authors: Hasan Fatih Ertuğrul, Beytullah Okur, Huseyin Üvet, Kadir Erkan

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The objective of this paper is to analyze a 4-pole hybrid magnetic levitation system by using 3D finite element and analytical methods. The magnetostatic analysis of the system is carried out by using ANSYS MAXWELL-3D package. An analytical model is derived by magnetic equivalent circuit (MEC) method. The purpose of magnetostatic analysis is to determine the characteristics of attractive force and rotational torques by the change of air gap clearances, inclination angles and current excitations. The comparison between 3D finite element analysis and analytical results are presented at the rest of the paper.

Keywords: yoke hybrid electromagnet, 3D finite element analysis, magnetic levitation system, magnetostatic analysis

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Syed Ahzam Tariq, Atharva Modi

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This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

Procedia PDF Downloads 127

Authors: Srijoni Banerjee

Abstract:

Sequences of some of the candidate genes (e.g., CPE, CDKAL1, GCKR, HSD11B1, IGF2BP2, IRS1, LPIN1, PKLR, TNF, PPARG) implicated in some of the complex disease, e.g. Type II diabetes in man has been compared with other species to investigate phylogenetic affinity. Based on mRNA sequence of these genes of 7 to 8 species, using bioinformatics tools Mega 5, Bioedit, Clustal W, distance matrix was obtained. Phylogenetic trees were obtained by NJ and UPGMA clustering methods. The results of the phylogenetic analyses show that of the species compared: Xenopus l., Danio r., Macaca m., Homo sapiens s., Rattus n., Mus m. and Gallus g., Bos taurus, both NJ and UPGMA clustering show close affinity between clustering of Homo sapiens s. (Man) with Rattus n. (Rat), Mus m. species for the candidate genes, except in case of Lipin1 gene. The results support the functional similarity of these genes in physiological and biochemical process involving man and mouse/rat. Therefore, in understanding the complex etiology and treatment of the complex disease mouse/rate model is the best laboratory choice for experimentation.

Keywords: phylogeny, candidate gene of type-2 diabetes, CPE, CDKAL1, GCKR, HSD11B1, IGF2BP2, IRS1, LPIN1, PKLR, TNF, PPARG

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Authors: Muhammad Sollehhuddin A. Jalil, Mohd Ibrahim Shapiai, Rubiyah Yusof

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Nowadays, ontology is common in many areas like artificial intelligence, bioinformatics, e-commerce, education and many more. Ontology is one of the focus areas in the field of Information Retrieval. The purpose of an ontology is to describe a conceptual representation of concepts and their relationships within a particular domain. In other words, ontology provides a common vocabulary for anyone who needs to share information in the domain. There are several ontology domains in various fields including engineering and non-engineering knowledge. However, there are only a few available ontology for engineering knowledge. Fuzzy logic as engineering knowledge is still not available as ontology domain. In general, fuzzy logic requires step-by-step guidelines and instructions of lab experiments. In this study, we presented domain ontology for Fuzzy Logic Control (FLC) knowledge. We give Table of Content (ToC) with middle strategy based on the Uschold and King method to develop FLC ontology. The proposed framework is developed using Protégé as the ontology tool. The Protégé’s ontology reasoner, known as the Pellet reasoner is then used to validate the presented framework. The presented framework offers better performance based on consistency and classification parameter index. In general, this ontology can provide a platform to anyone who needs to understand FLC knowledge.

Keywords: engineering knowledge, fuzzy logic control ontology, ontology development, table of content

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Authors: Yahia I. Mohamed, Ahmed I. Marzouk, Mohamed A. Yacout

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Aim of this work was to study the genetic basis for oil accumulation in olive fruit via tracking DGAT2 (Diacylglycerol acyltransferase type-2) gene in three Egyptian Origen Olive cultivars namely Toffahi, Hamed and Maraki using molecular marker techniques and bioinformatics tools. Results illustrate that, firstly: specific genomic band of Maraki cultivars was identified as DGAT2 (Diacylglycerol acyltransferase type-2) and identical for this gene in Olea europaea with 100 % of similarity. Secondly, differential genomic band of Maraki cultivars which produced from RAPD fingerprinting technique reflected predicted distinguished sequence which identified as DGAT2 (Diacylglycerol acyltransferase type-2) in Fragaria vesca subsp. Vesca with 76% of sequential similarity. Third and finally, specific genomic specific band of Hamed cultivars was indentified as two fragments, 1-Olea europaea cultivar Koroneiki diacylglycerol acyltransferase type 2 mRNA, complete cds with two matches regions with 99% or 2-PREDICTED: Fragaria vesca subsp. vesca diacylglycerol O-acyltransferase 2-like (LOC101313050), mRNA with 86% of similarity.

Keywords: Olea europaea, fingerprinting, diacylglycerol acyltransferase type-2 (DGAT2), Egypt

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Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

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Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

Procedia PDF Downloads 458

Authors: Jingyuan Hu, Zhandong Liu

Abstract:

CRISPR genome editing technology has transformed molecular biology by accurately targeting and altering an organism’s DNA. Despite the state-of-art precision of CRISPR genome editing, the imprecise mutation outcome and off-target effects present considerable risk, potentially leading to unintended genetic changes. Targeted deep sequencing, combined with bioinformatics sequence alignment, can detect such unwanted mutations. Nevertheless, the classical method, Needleman-Wunsch (NW) algorithm may produce false alignment outcomes, resulting in inaccurate mutation identification. The key to precisely identifying CRISPR-induced mutations lies in determining optimal parameters for the sequence alignment algorithm. Hidden Markov models (HMM) are ideally suited for this task, offering flexibility across CRISPR systems by leveraging forward-backward algorithms for parameter estimation. In this study, we introduce CRISPR-HMM, a statistical software to precisely call CRISPR-induced mutations. We demonstrate that the software significantly improves precision in identifying CRISPR-induced mutations compared to NW-based alignment, thereby enhancing the overall understanding of the CRISPR gene-editing process.

Keywords: CRISPR, HMM, sequence alignment, gene editing

Procedia PDF Downloads 52

Authors: Shuai Liu

Abstract:

In corporate social responsibility (CSR) reporting, companies are expected to present both the positive and negative parts of the social and environmental impacts of their performance. This study investigates how the companies that listed in fortune 500 respond to this challenge by analyzing the representations of negative part especially the safety performance. It has found that in the level of genre analysis, it presented 3 major moves and 11 steps in terms of the interdiscursivity analysis. It was made up of three dominant discourse.. The study calls for greater focus on the internal and external analysis of the negative aspect of aspects of companies’ self-disclosure.

Keywords: CSR reports, negative parts, critical genre analysis, interdiscursivity

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Authors: Juliza Hidayati, Sawarni Hasibuan

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PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

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Authors: Alexiou Dimitra, Fragkaki Maria

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The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables.

Keywords: Multiple Factorial Correspondence Analysis, Principal Component Analysis, Factor Analysis, E.U.-28 countries, Statistical package IBM SPSS 20, CHIC Analysis V 1.1 Software, Eurostat.eu Statistics

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Authors: J. R. Wang, W. Y. Cheng, J. S. Yeh, S. W. Chen, Y. M. Ferng, J. H. Yang, W. S. Hsu, C. Shih

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To understand the risk for dry storage concrete casks in the cask loading, transfer, and storage phase, the purpose of this research is to establish the probabilistic risk assessment (PRA) analysis methodology for dry storage concrete casks by using SAPHIRE 8 code. This analysis methodology is used to perform the study of Taiwan nuclear power plants (NPPs) dry storage system. The process of research has three steps. First, the data of the concrete casks and Taiwan NPPs are collected. Second, the PRA analysis methodology is developed by using SAPHIRE 8. Third, the PRA analysis is performed by using this methodology. According to the analysis results, the maximum risk is the multipurpose canister (MPC) drop case.

Keywords: PRA, dry storage, concrete cask, SAPHIRE

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Authors: Jeong-Hyun Park, Young-Sik Park, Hyo-Teag Jung

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This paper presents static analysis deployment model for code quality on R&D Projects of SW Development. The proposed model includes the scope of R&D projects and index for static analysis of source code, operation model and execution process, environments and infrastructure system for R&D projects of SW development. There is the static analysis result of pilot project as case study based on the proposed deployment model and environment, and strategic considerations for success operation of the proposed static analysis deployment model for R&D Projects of SW Development. The proposed static analysis deployment model in this paper will be adapted and improved continuously for quality upgrade of R&D projects, and customer satisfaction of developed source codes and products.

Keywords: static analysis, code quality, coding rules, automation tool

Procedia PDF Downloads 520

Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

Procedia PDF Downloads 368

Authors: Mrigakshi Das

Abstract:

The private sector investments and quantum of money required in this sector critically hinges on the financial risk and returns the sector offers to providers of capital. Therefore, it becomes important to understand financial performance of hospitals. Financial Analysis is useful for decision makers in a variety of settings. Consider the small proprietary hospitals, say, Physicians Clinic. The managers of such clinic need the information that financial statements provide. Attention to Financial Statements of healthcare Organizations can provide answers to questions like: How are they doing? What is their rate of profit? What is their solvency and liquidity position? What are their sources and application of funds? What is their Operational Efficiency? The researcher has studied Financial Statements of 5 Private Healthcare Organizations in Guwahati City.

Keywords: not-for-profit organizations, financial analysis, ratio analysis, profitability analysis, liquidity analysis, operational efficiency, capital structure analysis

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Authors: D. Beziakina, E. Bulgakova

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This study continues the research on Tuvinian intonation and presents a general cross-dialect analysis of intonation of Tuvinian declarative utterances, specifically the character of the tone movement in order to test the hypothesis about the prevalence of level tone in some Tuvinian dialects. The results of the analysis of basic pitch characteristics of Tuvinian speech (in general and in comparison with two other Turkic languages - Uzbek and Azerbaijani) are also given in this paper. The goal of our work was to obtain the ranges of pitch parameter values typical for Tuvinian speech. Such language-specific values can be used in speaker identification systems in order to get more accurate results of ethnic speech analysis. We also present the results of a cross-dialect analysis of declarative intonation in the poorly studied Tuvinian language.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Chengcao Sun, Shujun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, Dejia Li

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Recently, the long non-coding RNA (lncRNA) NEAT1 has been identified as an oncogenic gene in multiple cancer types and elevated expression of NEAT1 was tightly linked to tumorigenesis and cancer progression. However, the molecular basis for this observation has not been characterized in progression of non-small cell lung cancer (NSCLC). In our studies, we identified NEAT1 was highly expressed in NSCLC patients and was a novel regulator of NSCLC progression. Patients whose tumors had high NEAT1 expression had a shorter overall survival than patients whose tumors had low NEAT1 expression. Further, NEAT1 significantly accelerates NSCLC cell growth and metastasis in vitro and tumor growth in vivo. Additionally, by using bioinformatics study and RNA pull down combined with luciferase reporter assays, we demonstrated that NEAT1 functioned as a competing endogenous RNA (ceRNA) for has-miR-377-3p, antagonized its functions and led to the de-repression of its endogenous targets E2F3, which was a core oncogene in promoting NSCLC progression. Taken together, these observations imply that the NEAT1 modulated the expression of E2F3 gene by acting as a competing endogenous RNA, which may build up the missing link between the regulatory miRNA network and NSCLC progression.

Keywords: long non-coding RNA NEAT1, hsa-miRNA-377-3p, E2F3, non-small cell lung cancer, tumorigenesis

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Authors: Dong Wook Lee, Adrian Mistreanu

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The authors have studied a method for analyzing containment and penetration using an explicit nonlinear Finite Element Analysis. This method may be used in the stage of concept design for the protection of external configurations or components of aircraft engines and nuclear power plant structures. This paper consists of the modeling method, the results obtained from the method and the comparison of the results with those calculated from simple analytical method. It shows that the containment capability obtained by proposed method matches well with analytically calculated containment capability.

Keywords: computer aided engineering, containment analysis, finite element analysis, impact analysis, penetration analysis

Procedia PDF Downloads 138

Authors: Niamh Higgins, Dawn Howard

Abstract:

The Irish agri-food sector is of major importance to Ireland’s manufacturing sector and to the Irish economy through employment and the exporting of animal products worldwide. Infectious diseases and parasites have an impact on farm animal health causing profitability and productivity to be affected. For the sustainability of Irish dairy farming, there must be the highest standard of animal health. There can be a lack of information in accounting for > 1% of complete microbial diversity in an environment. There is the tendency of culture-based methods of microbial identification to overestimate the prevalence of species which grow easily on an agar surface. There is a need for new technologies to address these issues to assist with animal health. Metagenomic approaches provide information on both the whole genome and transcriptome present through DNA sequencing of total DNA from environmental samples producing high determination of functional and taxonomic information. Nanopore Next Generation Technologies have the ability to be powerful sequencing technologies. They provide high throughput, low material requirements and produce ultra-long reads, simplifying the experimental process. The aim of this study is to use a metagenomics approach to analyze dairy cattle faecal samples using the Oxford Nanopore MinION Next Generation Sequencer and to establish an in-house pipeline for metagenomic characterization of complex samples. Faecal samples will be obtained from Irish dairy farms, DNA extracted and the MinION will be used for sequencing, followed by bioinformatics analysis. Of particular interest, will be the parasite Buxtonella sulcata, which there has been little research on and which there is no research on its presence on Irish dairy farms. Preliminary results have shown the ability of the MinION to produce hundreds of reads in a relatively short time frame of eight hours. The faecal samples were obtained from 90 dairy cows on a Galway farm. The results from Oxford Nanopore ‘What’s in my pot’ (WIMP) using the Epi2me workflow, show that from a total of 926 classified reads, 87% were from the Kingdom Bacteria, 10% were from the Kingdom Eukaryota, 3% were from the Kingdom Archaea and < 1% were from the Kingdom Viruses. The most prevalent bacteria were those from the Genus Acholeplasma (71 reads), Bacteroides (35 reads), Clostridium (33 reads), Acinetobacter (20 reads). The most prevalent species present were those from the Genus Acholeplasma and included Acholeplasma laidlawii (39 reads) and Acholeplasma brassicae (26 reads). The preliminary results show the ability of the MinION for the identification of microorganisms to species level coming from a complex sample. With ongoing optimization of the pipe-line, the number of classified reads are likely to increase. Metagenomics has the potential in animal health for diagnostics of microorganisms present on farms. This would support wprevention rather than a cure approach as is outlined in the DAFMs National Farmed Animal Health Strategy 2017-2022.

Keywords: animal health, buxtonella sulcata, infectious disease, irish dairy cattle, metagenomics, minION, next generation sequencing

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