Search results for: semi-quantitative analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27823

Search results for: semi-quantitative analysis

27823 Superparamagnetic Sensor with Lateral Flow Immunoassays as Platforms for Biomarker Quantification

Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

Abstract:

Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

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27822 A Review of Spatial Analysis as a Geographic Information Management Tool

Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

Abstract:

Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

Procedia PDF Downloads 318
27821 Application of Subversion Analysis in the Search for the Causes of Cracking in a Marine Engine Injector Nozzle

Authors: Leszek Chybowski, Artur Bejger, Katarzyna Gawdzińska

Abstract:

Subversion analysis is a tool used in the TRIZ (Theory of Inventive Problem Solving) methodology. This article introduces the history and describes the process of subversion analysis, as well as function analysis and analysis of the resources, used at the design stage when generating possible undesirable situations. The article charts the course of subversion analysis when applied to a fuel injection nozzle of a marine engine. The work describes the fuel injector nozzle as a technological system and presents principles of analysis for the causes of a cracked tip of the nozzle body. The system is modelled with functional analysis. A search for potential causes of the damage is undertaken and a cause-and-effect analysis for various hypotheses concerning the damage is drawn up. The importance of particular hypotheses is evaluated and the most likely causes of damage identified.

Keywords: complex technical system, fuel injector, function analysis, importance analysis, resource analysis, sabotage analysis, subversion analysis, TRIZ (Theory of Inventive Problem Solving)

Procedia PDF Downloads 617
27820 Effects of Wind Load on the Tank Structures with Various Shapes and Aspect Ratios

Authors: Doo Byong Bae, Jae Jun Yoo, Il Gyu Park, Choi Seowon, Oh Chang Kook

Abstract:

There are several wind load provisions to evaluate the wind response on tank structures such as API, Euro-code, etc. the assessment of wind action applying these provisions is made by performing the finite element analysis using both linear bifurcation analysis and geometrically nonlinear analysis. By comparing the pressure patterns obtained from the analysis with the results of wind tunnel test, most appropriate wind load criteria will be recommended.

Keywords: wind load, finite element analysis, linear bifurcation analysis, geometrically nonlinear analysis

Procedia PDF Downloads 637
27819 The Role of Environmental Analysis in Managing Knowledge in Small and Medium Sized Enterprises

Authors: Liu Yao, B. T. Wan Maseri, Wan Mohd, B. T. Nurul Izzah, Mohd Shah, Wei Wei

Abstract:

Effectively managing knowledge has become a vital weapon for businesses to survive or to succeed in the increasingly competitive market. But do they perform environmental analysis when managing knowledge? If yes, how is the level and significance? This paper established a conceptual framework covering the basic knowledge management activities (KMA) to examine their contribution towards organizational performance (OP). Environmental analysis (EA) was then investigated from both internal and external aspects, to identify its effects on that contribution. Data was collected from 400 Chinese SMEs by questionnaires. Cronbach's α and factor analysis were conducted. Regression results show that the external analysis presents higher level than internal analysis. However, the internal analysis mediates the effects of external analysis on the KMA-OP relation and plays more significant role in the relation comparing with the external analysis. Thus, firms shall improve environmental analysis especially the internal analysis to enhance their KM practices.

Keywords: knowledge management, environmental analysis, performance, mediating, small sized enterprises, medium sized enterprises

Procedia PDF Downloads 614
27818 Improving Taint Analysis of Android Applications Using Finite State Machines

Authors: Assad Maalouf, Lunjin Lu, James Lynott

Abstract:

We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

Procedia PDF Downloads 178
27817 The Documentary Analysis of Meta-Analysis Research in Violence of Media

Authors: Proud Arunrangsiwed

Abstract:

The part of “future direction” in the findings of meta-analysis could provide the great direction to conduct the future studies. This study, “The Documentary Analysis of Meta-Analysis Research in Violence of Media” would conclude “future directions” out of 10 meta-analysis papers. The purposes of this research are to find an appropriate research design or an appropriate methodology for the future research related to the topic, “violence of media”. Further research needs to explore by longitudinal and experimental design, and also needs to have a careful consideration about age effects, time spent effects, enjoyment effects, and ordinary lifestyle of each media consumer.

Keywords: aggressive, future direction, meta-analysis, media, violence

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27816 Data Transformations in Data Envelopment Analysis

Authors: Mansour Mohammadpour

Abstract:

Data transformation refers to the modification of any point in a data set by a mathematical function. When applying transformations, the measurement scale of the data is modified. Data transformations are commonly employed to turn data into the appropriate form, which can serve various functions in the quantitative analysis of the data. This study addresses the investigation of the use of data transformations in Data Envelopment Analysis (DEA). Although data transformations are important options for analysis, they do fundamentally alter the nature of the variable, making the interpretation of the results somewhat more complex.

Keywords: data transformation, data envelopment analysis, undesirable data, negative data

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27815 Considering Partially Developed Artifacts in Change Impact Analysis Implementation

Authors: Nazri Kama, Sufyan Basri, Roslina Ibrahim

Abstract:

It is important to manage the changes in the software to meet the evolving needs of the customer. Accepting too many changes causes delay in the completion and it incurs additional cost. One type of information that helps to make the decision is through change impact analysis. Current impact analysis approaches assume that all classes in the class artifact are completely developed and the class artifact is used as a source of analysis. However, these assumptions are impractical for impact analysis in the software development phase as some classes in the class artifact are still under development or partially developed that leads to inaccuracy. This paper presents a novel impact analysis approach to be used in the software development phase. The significant achievements of the approach are demonstrated through an extensive experimental validation using three case studies.

Keywords: software development, impact analysis, traceability, static analysis.

Procedia PDF Downloads 608
27814 On the Analysis of Pseudorandom Partial Quotient Sequences Generated from Continued Fractions

Authors: T. Padma, Jayashree S. Pillai

Abstract:

Random entities are an essential component in any cryptographic application. The suitability of a number theory based novel pseudorandom sequence called Pseudorandom Partial Quotient Sequence (PPQS) generated from the continued fraction expansion of irrational numbers, in cryptographic applications, is analyzed in this paper. An approach to build the algorithm around a hard mathematical problem has been considered. The PQ sequence is tested for randomness and its suitability as a cryptographic key by performing randomness analysis, key sensitivity and key space analysis, precision analysis and evaluating the correlation properties is established.

Keywords: pseudorandom sequences, key sensitivity, correlation, security analysis, randomness analysis, sensitivity analysis

Procedia PDF Downloads 590
27813 Impact on the Results of Sub-Group Analysis on Performance of Recommender Systems

Authors: Ho Yeon Park, Kyoung-Jae Kim

Abstract:

The purpose of this study is to investigate whether friendship in social media can be an important factor in recommender system through social scientific analysis of friendship in popular social media such as Facebook and Twitter. For this purpose, this study analyzes data on friendship in real social media using component analysis and clique analysis among sub-group analysis in social network analysis. In this study, we propose an algorithm to reflect the results of sub-group analysis on the recommender system. The key to this algorithm is to ensure that recommendations from users in friendships are more likely to be reflected in recommendations from users. As a result of this study, outcomes of various subgroup analyzes were derived, and it was confirmed that the results were different from the results of the existing recommender system. Therefore, it is considered that the results of the subgroup analysis affect the recommendation performance of the system. Future research will attempt to generalize the results of the research through further analysis of various social data.

Keywords: sub-group analysis, social media, social network analysis, recommender systems

Procedia PDF Downloads 363
27812 Sentiment Analysis: Comparative Analysis of Multilingual Sentiment and Opinion Classification Techniques

Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

Abstract:

Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

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27811 Sentiment Analysis in Social Networks Sites Based on a Bibliometrics Analysis: A Comprehensive Analysis and Trends for Future Research Planning

Authors: Jehan Fahim M. Alsulami

Abstract:

Academic research about sentiment analysis in sentiment analysis has obtained significant advancement over recent years and is flourishing from the collection of knowledge provided by various academic disciplines. In the current study, the status and development trend of the field of sentiment analysis in social networks is evaluated through a bibliometric analysis of academic publications. In particular, the distributions of publications and citations, the distribution of subject, predominant journals, authors, countries are analyzed. The collaboration degree is applied to measure scientific connections from different aspects. Moreover, the keyword co-occurrence analysis is used to find out the major research topics and their evolutions throughout the time span. The area of sentiment analysis in social networks has gained growing attention in academia, with computer science and engineering as the top main research subjects. China and the USA provide the most to the area development. Authors prefer to collaborate more with those within the same nation. Among the research topics, newly risen topics such as COVID-19, customer satisfaction are discovered.

Keywords: bibliometric analysis, sentiment analysis, social networks, social media

Procedia PDF Downloads 218
27810 Vibrations of Springboards: Mode Shape and Time Domain Analysis

Authors: Stefano Frassinelli, Alessandro Niccolai, Riccardo E. Zich

Abstract:

Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain.

Keywords: springboard analysis, modal analysis, time domain analysis, vibrations

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27809 Stable Isotope Analysis of Faunal Remains of Ancient Kythnos Island for Paleoenvironmental Reconstruction

Authors: M. Tassi, E. Dotsika, P. Karalis, A. Trantalidou, A. Mazarakis Ainian

Abstract:

The Kythnos Island in Greece is of particular archaeological interest, as it has been inhabited from the 12th BC until the 7th AD. From island excavations, numerous faunal and human skeletal remains have been recovered. This work is the first attempt at the paleoenvironmental reconstruction of the island via stable isotope analysis. Specifically, we perform 13C and 18O isotope analysis in faunal bone apatite in order to investigate the climate conditions that prevailed in the area. Additionally, we conduct 13C and 15N isotope analysis in faunal bone collagen, which will constitute the baseline for the subsequent diet reconstruction of the ancient Kythnos population.

Keywords: stable isotopes analysis, bone collagen stable isotope analysis, bone apatite stable isotope analysis, paleodiet, palaeoclimate

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27808 Relevancy Measures of Errors in Displacements of Finite Elements Analysis Results

Authors: A. B. Bolkhir, A. Elshafie, T. K. Yousif

Abstract:

This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation.

Keywords: finite element analysis (FEA), discretization error, round-off error, mesh refinement, richardson extrapolation, monotonic convergence

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27807 One Plus One is More than Two: Why Nurse Recruiters Need to Use Various Multivariate Techniques to Understand the Limitations of the Concept of Emotional Intelligence

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

Procedia PDF Downloads 466
27806 A Survey of the Applications of Sentiment 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

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27805 Spatial and Temporal Analysis of Violent Crime in Washington, DC

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
27804 Fine-Grained Sentiment Analysis: Recent Progress

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
27803 Analysis Customer Loyalty Characteristic and Segmentation Analysis in Mobile Phone Category in Indonesia

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

Abstract:

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
27802 One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents

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

Procedia PDF Downloads 517
27801 3D Finite Element Analysis of Yoke Hybrid Electromagnet

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

Abstract:

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

Procedia PDF Downloads 727
27800 After-Cooling Analysis of RC Structural Members Exposed to High Temperature by Using Numerical Approach

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

Procedia PDF Downloads 414
27799 Fuzzy Approach for Fault Tree Analysis of Water Tube Boiler

Authors: Syed Ahzam Tariq, Atharva Modi

Abstract:

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
27798 Overview and Future Opportunities of Sarcasm Detection on Social Media Communications

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

Abstract:

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 457
27797 A Critical Genre Analysis of Negative Parts in CSR Reports

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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27796 BingleSeq: A User-Friendly R Package for Single-Cell RNA-Seq Data Analysis

Authors: Quan Gu, Daniel Dimitrov

Abstract:

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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27795 Value Chain Analysis and Enhancement Added Value in Palm Oil Supply Chain

Authors: Juliza Hidayati, Sawarni Hasibuan

Abstract:

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

Procedia PDF Downloads 371
27794 Data and Spatial Analysis for Economy and Education of 28 E.U. Member-States for 2014

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