Search results for: cytometry analysis

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 261

Authors: Alsulami H., Alghamdi N., Alasker A., Almohen N., Shome D.

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Most conventional chemotherapeutic agents which are used for the treatment of cancers not only eradicate cancer cells but also affect normal hematopoietic Stem cells (HSCs) that leads to severe pancytopenia during treatment. Therefore, a need exists for novel approaches to treat cancer without or with minimum effect on normal HSCs. Parthenolide (PTL), a herbal product occurring naturally in the plant Feverfew, is a potential new chemotherapeutic agent for the treatment of many cancers such as acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL). In this study we investigated the effect of different PTL concentrations on the viability of normal HSCs and also on the ability of these cells to form colonies after they have been treated with PTL in vitro. Methods: In this study, 24 samples of bone marrow and cord blood were collected with consent, and mononuclear cells were separated using density gradient separation. These cells were then exposed to various concentrations of PTL for 24 hours. Cell viability after culture was determined using 7ADD in a flow cytometry test. Additionally, the impact of PTL on hematopoietic stem cells (HSCs) was evaluated using a colony forming unit assay (CFU). Furthermore, the levels of NFҝB expression were assessed by using a PE-labelled anti-pNFκBP65 antibody. Results: this study showed that there was no statistically significant difference in the percentage of cell death between untreated and PTL treated cells with 5 μM PTL (p = 0.7), 10 μM PTL (p = 0.4) and 25 μM (p = 0.09) respectively. However, at higher doses, PTL caused significant increase in the percentage of cell death. These results were significant when compared to untreated control (p < 0.001). The response of cord blood cells (n=4) on the other hand was slightly different from that for bone marrow cells in that the percentage of cell death was significant at 100 μM PTL. Therefore, cord blood cells seemed more resistant than bone marrow cells. Discussion &Conclusion: At concentrations ≤25 μM PTL has a minimum or no effect on HSCs in vitro. Cord blood HSCs are more resistant to PTL compared to bone marrow HSCs. This could be due to the higher percentage of T-lymphocytes, which are resistant to PTL, in CB samples (85% in CB vs. 56% in BM. Additionally, CB samples contained a higher proportion of CD34+ cells, with 14.5% of brightly CD34+ cells compared to only 1% in normal BM. These bright CD34+ cells in CB were mostly negative for early-stage stem cell maturation antigens, making them young and resilient to oxidative stress and high concentrations of PTL.

Keywords: stem cell, parthenolide, NFKB, CLL

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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

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Authors: Gema Gómez-Casado, Alba Rodríguez-Muñoz, Virginia Mela-Rivas, Pallavi Kompella, Francisco José Tinahones-Madueña, Isabel Moreno-Indias, Almudena Ortega-Gómez

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Obesity is a high-priority health problem worldwide due to its high prevalence. The proportion of obese and overweight subjects in industrialized countries exceeds half of the population in most cases. Beyond the metabolic problem, obesity boosts inflammation levels in the organism. The gut microbiota, considered an organ by itself, controls a high variety of processes at a systemic level. In fact, the microbiota interacts closely with the immune system, being crucial in determining the maturation state of neutrophils, key effectors of the innate immune response. It is known that changes in the diet exert strong effects on the variety and activity of the gut microbiota. The effect that those changes have on the axis microbiota-immune response is an unexplored field. In this study, 10 patients with obesity (weight 114,3 ± 14,5Kg, BMI 40,47±3,66) followed a Mediterranean-hypocaloric diet for 3 months, reducing their initial weight by 12,71 ± 3%. A transplant of microbiota from these patients before and after the diet was performed into wild type “germ-free” mice (n=10/group), treated with antibiotics. Six weeks after the transplant, mice were euthanized, and the presence of cells from the innate immune system were analysed in different organs (bone marrow, blood, spleen, visceral adipose tissue, and intestine) by flow cytometry. No differences were observed in the number of myeloid cells in bone marrow, blood, spleen, or visceral adipose tissue of mice transplanted with patient’s microbiota before and after following the Mediterranean diet. However, the intestine of mice that received post-diet microbiota presented a marked decrease in the number of neutrophils (whose presence is associated with tissue inflammation), as well as macrophages. In line with these findings, intestine monocytes from mice with post-diet microbiota showed a less inflammatory profile (lower Ly6Gˡᵒʷ proportion of cells). These results point toward a decrease in the inflammatory state of the intestinal tissue, derived from changes in the gut microbiota, which occurred after a 3-month Mediterranean diet.

Keywords: obesity, nutrition, Mediterranean diet, gut microbiota, immune system

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

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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

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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

Procedia PDF Downloads 596

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: 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: Manali Jain, Neeta Singh, Raunaq Fatima, Soniya Nityanand, Mandakini Pradhan, Chandra Prakash Chaturvedi

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Isolated Congenital Heart Defect (ICHD) is the major cause of neonatal death worldwide among all forms of CHDs. A significant proportion of fetuses with ICHD die in the neonatal period if no treatment is provided. Recently, stem cell therapies have emerged as a potential approach to ameliorate ICHD in children. ICHD is characterized by cardiac structural abnormalities during embryogenesis due to alterations in the cardiomyogenic properties of a pool of cardiac progenitors/ stem cells associated with fetal heart development. The stem cells present in the amniotic fluid (AF) are of fetal origin and may reflect the physiological and pathological changes in the fetus during embryogenesis. Therefore, in the present study, the cardiomyogenic potential of AF-MSCs derived from fetuses with ICHD (ICHD AF-MSCs) has been evaluated and compared with that of AF-MSCs of structurally normal fetuses (normal AF-MSCs). Normal and ICHD AF-MSC were analyzed for the expression of cardiac progenitor markers viz., stage-specific embryonic antigen-1 (SSEA-1), vascular endothelial growth factor 2 (VEGFR-2) and platelet-derived growth factor receptor-alpha (PDGFR-α) by flow cytometry. The immunophenotypic characterization revealed that ICHD AF-MSCs have significantly lower expression of cardiac progenitor markers VEGFR-2 (0.14% ± 0.6 vs.48.80% ± 0.9; p <0.01), SSEA-1 (70.86% ± 2.4 vs. 88.36% ±2.7; p <0.01), and PDGFR-α (3.92% ± 1.8 vs. 47.59% ± 3.09; p <0.01) in comparison to normal AF-MSCs. Upon induction with 5’-azacytidine for 21 days, ICHD AF-MSCs showed a significantly down-regulated expression of cardiac transcription factors such as GATA-4 (0.4 ± 0.1 vs. 6.8 ± 1.2; p<0.01), ISL-1 (2.3± 0.6 vs. 14.3 ± 1.12; p<0.01), NK-x 2-5 (1.1 ± 0.3 vs. 14.1 ±2.8; p<0.01), TBX-5 (0.4 ± 0.07 vs. 4.4 ± 0.3; p<0.001), and TBX-18 (1.3 ± 0.2 vs. 4.19 ± 0.3; p<0.01) when compared with the normal AF-MSCs. Furthermore, immunocytochemical staining revealed that both types of AF-MSCs could differentiate into cardiovascular lineages and express cardiomyogenic, endothelial, and smooth muscle actin markers, viz., cardiac troponin (cTNT), CD31, and alpha-smooth muscle actin (α-SMA). However, normal AF-MSCs showed an enhanced expression of cTNT (p<0.001), CD31 (p<0.01), and α-SMA (p<0.05), compared to ICHD AF-MSCs. Overall, these results suggest that the ICHD-AF-MSCs have a defective cardiomyogenic differentiation potential and that the defects in these stem cells may have a role in the pathogenesis of ICHD.

Keywords: amniotic fluid, cardiomyogenic potential, isolated congenital heart defect, mesenchymal stem cells

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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

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Authors: Shuai Liu

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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: Quan Gu, Daniel Dimitrov

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BingleSeq was developed as a shiny-based, intuitive, and comprehensive application that enables the analysis of single-Cell RNA-Sequencing count data. This was achieved via incorporating three state-of-the-art software packages for each type of RNA sequencing analysis, alongside functional annotation analysis and a way to assess the overlap of differential expression method results. At its current state, the functionality implemented within BingleSeq is comparable to that of other applications, also developed with the purpose of lowering the entry requirements to RNA Sequencing analyses. BingleSeq is available on GitHub and will be submitted to R/Bioconductor.

Keywords: bioinformatics, functional annotation analysis, single-cell RNA-sequencing, transcriptomics

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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

Abstract:

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

Procedia PDF Downloads 511

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 367

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: Dong Wook Lee, Adrian Mistreanu

Abstract:

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

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Authors: Anuta Mukherjee, Saswati Mukherjee

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Data is growing everyday. Social networking sites such as Twitter are becoming an integral part of our daily lives, contributing a large increase in the growth of data. It is a rich source especially for sentiment detection or mining since people often express honest opinion through tweets. However, although sentiment analysis is a well-researched topic in text, this analysis using Twitter data poses additional challenges since these are unstructured data with abbreviations and without a strict grammatical correctness. We have employed collision theory to achieve sentiment analysis in Twitter data. We have also incorporated discourse analysis in the collision theory based model to detect accurate sentiment from tweets. We have also used the retweet field to assign weights to certain tweets and obtained the overall weightage of a topic provided in the form of a query. Hadoop has been exploited for speed. Our experiments show effective results.

Keywords: sentiment analysis, twitter, collision theory, discourse analysis

Procedia PDF Downloads 535

Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

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In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

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Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Komon Paisal

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The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: constructivism, learning management, mathematics analysis courses, learning activity

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Authors: Tais Basaco, Stefanie Pektor, Josue A. Moreno, Matthias Miederer, Andreas Türler

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Radiopharmaceuticals based in monoclonal anti-body (mAb) via chemical linkers have become a potential tool in nuclear medicine because of their specificity and the large variability and availability of therapeutic radiometals. It is important to identify the conjugation sites and number of attached chelator to mAb to obtain radioimmunoconjugates with required immunoreactivity and radiostability. Girentuximab antibody (G250) is a potential candidate for radioimmunotherapy of clear cell carcinomas (RCCs) because it is reactive with CAIX antigen, a transmembrane glycoprotein overexpressed on the cell surface of most ( > 90%) (RCCs). G250 was conjugated with the bifunctional chelating agent DOTA (1,4,7,10-Tetraazacyclododecane-N,N’,N’’,N’’’-tetraacetic acid) via a benzyl-thiocyano group as a linker (p-SCN-Bn-DOTA). DOTA-G250 conjugates were analyzed by size exclusion chromatography (SE-HPLC) and by electrophoresis (SDS-PAGE). The potential site-specific conjugation was identified by liquid chromatography–mass spectrometry (LC/MS-MS) and the number of linkers per molecule of mAb was calculated using the molecular weight (MW) measured by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). The average number obtained in the conjugates in non-reduced conditions was between 8-10 molecules of DOTA per molecule of mAb. The average number obtained in the conjugates in reduced conditions was between 1-2 and 3-4 molecules of DOTA per molecule of mAb in the light chain (LC) and heavy chain (HC) respectively. Potential DOTA modification sites of the chelator were identified in lysine residues. The biological activity of the conjugates was evaluated by flow cytometry (FACS) using CAIX negative (SKRC-18) and CAIX positive (SKRC-52). The DOTA-G250 conjugates were labelled with 177Lu with a radiochemical yield > 95% reaching specific activities of 12 MBq/µg. The stability in vitro of different types of radioconstructs was analyzed in human serum albumin (HSA). The radiostability of 177Lu-DOTA-G250 at high specific activity was increased by addition of sodium ascorbate after the labelling. The immunoreactivity was evaluated in vitro and in vivo. Binding to CAIX positive cells (SK-RC-52) at different specific activities was higher for conjugates with less DOTA content. Protein dose was optimized in mice with subcutaneously growing SK-RC-52 tumors using different amounts of 177Lu- DOTA-G250.

Keywords: mass spectrometry, monoclonal antibody, radiopharmaceuticals, radioimmunotheray, renal cancer

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Authors: Felipe Magalhaes Lemos

Abstract:

Functional behavior analysis is a procedure that has been studied for several decades by behavior analysts. In Brazil, we still have few studies in the area, so it was decided to carry out a systematic review of the articles published in the area by Brazilians. A search was done on the following scientific article registration sites: PsycINFO, ERIC, ISI Web of Science, Virtual Health Library. The research includes (a) peer-reviewed studies that (b) have been carried out in Brazil containing (c) functional assessment as a pre-treatment through (d) experimental procedures, direct or indirect observation and measurement of behavior problems (e) demonstrating a relationship between environmental events and behavior. During the review, 234 papers were found; however, only 9 were included in the final analysis. Of the 9 articles extracted, only 2 presented functional analysis procedures with manipulation of environmental variables, while the other 7 presented different procedures for a descriptive behavior assessment. Only the two studies using "functional analysis" used graphs to demonstrate the prevalent function of the behavior. Other studies described procedures and did not make clear the causal relationship between environment and behavior. There is still confusion in Brazil regarding the terms "functional analysis", "descriptive assessment" and "contingency analysis," which are generally treated in the same way. This study shows that few articles are published with a focus on functional analysis in Brazil.

Keywords: behavior, contingency, descriptive assessment, functional analysis

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Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

Abstract:

The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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