Search results for: Text watermarking.
159 Using Multi-Linguistic Techniques for Thailand Herb and Traditional Medicine Registration Systems
Authors: Thanapol Wisuttikul, Choochart Haruechaiyasak, Santipong Thaiprayoon
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Thailand has evolved many unique culture and knowledge, and the leading is the Thai traditional medicine (TTM). Recently, a number of researchers have tried to save this indigenous knowledge. However, the system to do so has still been scant. To preserve this ancient knowledge, we therefore invented and integrated multi-linguistic techniques to create the system of the collected all of recipes. This application extracted the medical recipes from antique scriptures then normalized antiquarian words, primitive grammar and antiquated measurement of them to the modern ones. Then, we applied ingredient-duplication-calculation, proportion-similarity-calculation and score-ranking to examine duplicate recipes. We collected the questionnaires from registrants and people to investigate the users’ satisfaction. The satisfactory results were found. This application assists not only registrants to validating the copyright violation in TTM registration process but also people to cure their illness that aids both Thai people and all mankind to fight for intractable diseases.
Keywords: Medicine Registration, Search Engine, Text Approximation, Traditional Medicine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1991158 Automatic Extraction of Features and Opinion-Oriented Sentences from Customer Reviews
Authors: Khairullah Khan, Baharum B. Baharudin, Aurangzeb Khan, Fazal_e_Malik
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Opinion extraction about products from customer reviews is becoming an interesting area of research. Customer reviews about products are nowadays available from blogs and review sites. Also tools are being developed for extraction of opinion from these reviews to help the user as well merchants to track the most suitable choice of product. Therefore efficient method and techniques are needed to extract opinions from review and blogs. As reviews of products mostly contains discussion about the features, functions and services, therefore, efficient techniques are required to extract user comments about the desired features, functions and services. In this paper we have proposed a novel idea to find features of product from user review in an efficient way. Our focus in this paper is to get the features and opinion-oriented words about products from text through auxiliary verbs (AV) {is, was, are, were, has, have, had}. From the results of our experiments we found that 82% of features and 85% of opinion-oriented sentences include AVs. Thus these AVs are good indicators of features and opinion orientation in customer reviews.Keywords: Classification, Customer Reviews, Helping Verbs, Opinion Mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2083157 N-Grams: A Tool for Repairing Word Order Errors in Ill-formed Texts
Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou, Konstantinos Mamouras
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This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. A possible way for reordering the words is to use all the permutations. The problem is that for a sentence with length N words the number of all permutations is N!. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The confusion matrix technique has been designed in order to reduce the search space among permuted sentences. The limitation of search space is succeeded using the statistical inference of N-grams. The results of this technique are very interesting and prove that the number of permuted sentences can be reduced by 98,16%. For experimental purposes a test set of TOEFL sentences was used and the results show that more than 95% can be repaired using the proposed method.
Keywords: Permutations filtering, Statistical language model N-grams, Word order errors, TOEFL
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1659156 Comparative Analysis of DTC Based Switched Reluctance Motor Drive Using Torque Equation and FEA Models
Authors: P. Srinivas, P. V. N. Prasad
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Since torque ripple is the main cause of noise and vibrations, the performance of Switched Reluctance Motor (SRM) can be improved by minimizing its torque ripple using a novel control technique called Direct Torque Control (DTC). In DTC technique, torque is controlled directly through control of magnitude of the flux and change in speed of the stator flux vector. The flux and torque are maintained within set hysteresis bands.
The DTC of SRM is analyzed by two methods. In one method, the actual torque is computed by conducting Finite Element Analysis (FEA) on the design specifications of the motor. In the other method, the torque is computed by Simplified Torque Equation. The variation of peak current, average current, torque ripple and speed settling time with Simplified Torque Equation model is compared with FEA based model.
Keywords: Direct Toque Control, Simplified Torque Equation, Finite Element Analysis, Torque Ripple.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3494155 Topic Modeling Using Latent Dirichlet Allocation and Latent Semantic Indexing on South African Telco Twitter Data
Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro
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Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.
Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 433154 Teachers’ and Students’ Causal Explanations for Classroom Misbehavior: Similarities and Differences
Authors: Rachel C. F. Sun
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This study aimed to examine the similarities and differences between teachers’ and students’ causal explanations of classroom misbehavior. In-depth semi-structured interviews were conducted with twelve teachers and eighteen Grade 7-9 students. The qualitative data were analyzed, in which the attributed causes of classroom misbehavior were categorized into student, family, school and peer factors. Findings showed that both interviewed teachers and students shared similarity in attributing to student factors, such as ‘fun and pleasure seeking’ and ‘attention seeking’ as the leading causes of misbehavior. However, the students accounted to school factors, particularly ‘boring lessons’ as the next attributed causes, while the teachers accounted to family factors, such as ‘lack of parent demandingness’. By delineating the factors at student, family, school, and peer levels, these findings help drawing corresponding implications for preventing and mitigating misbehavior in school.
Keywords: Causal explanation, misbehavior, student, teacher.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5280153 Classification of Political Affiliations by Reduced Number of Features
Authors: Vesile Evrim, Aliyu Awwal
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By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.Keywords: Politics, machine learning, feature selection, LIWC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2352152 Investigation of Maritime Accidents with Exploratory Data Analysis in the Strait of Çanakkale (Dardanelles)
Authors: Gizem Kodak
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The Strait of Çanakkale (Dardanelles), together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.
Keywords: Maritime Accidents, EDA, Strait of Çanakkale, navigational safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 106151 On Developing a Core Guideline for English Language Training Programs in Business Settings
Authors: T. Ito, K. Kawaguchi, R. Ohta
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The purpose of this study is to provide a guideline to assist globally-minded companies in developing task-based English- language programs for their employees. After conducting an online self-assessment questionnaire comprised of 45 job-related tasks, we analyzed responses received from 3,000 Japanese company employees and developed a checklist that considered three areas; i) the percentage of those who need to accomplish English-language tasks in their workplace (need for English), ii) a five-point self-assessment score (task performance level), and iii) the impact of previous task experience on perceived performance (experience factor). The 45 tasks were graded according to five proficiency levels. Our results helped us to create a core guideline that may assist companies in two ways: first, in helping determine which tasks employees with a certain English proficiency should be able to satisfactorily carry out, and secondly, to quickly prioritize which business-related English skills they would need in future English language programs.
Keywords: Business settings, Can-do statements, English language training programs, Self-assessment, Task experience.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1439150 Defining Human Resources “Bundles” and Its’ Correlation with Companies’ Financial Performances
Authors: Ivana Tadić, Snježana Pivac
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Although human resources are recognized as the crucial companies’ resources and their positive influence on companies’ performances has been confirmed through different researches, scientists are still debating it. In order to contribute this debate, this paper firstly discusses the most important human resource management elements and practices and its influence on companies’ success. Afterwards it defines human resource “bundles” – interrelated and internally consistent human resource practices, complementary to each other, or the most important human resource practices and elements regarding Croatian companies and its human resource management activities. Finally, the paper provides empirical results; more precisely it reveals the relation of the level of development of human resource management function (“bundles”) and companies’ financial performances (using profitability ratios, liquidity ratios, solvency ratios and a group of additional ratios related to employees’ indicators).
Keywords: Companies’ performances, human resource bundles, multivariate statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8788149 Low Cost Real-Time Communication Braille Hand-Glove for Visually Impaired Using Slot Sensors and Vibration Motors
Authors: Mukul Bandodkar, Virat Chourasia
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Visually impaired people find it extremely difficult to acquire basic and vital information necessary for their living. Therefore, they are at a very high risk of being socially excluded as a result of poor access to information. In recent years, several attempts have been made in improving the communication methods for visually impaired people which involve tactile sensation such as finger Braille, manual alphabets and the print on palm method and several other electronic devices. But, there are some problems which arise in such methods such as lack of privacy and lack of compatibility to computer environment. This paper describes a low cost Braille hand glove for blind people using slot sensors and vibration motors with the help of which they can read and write emails, text messages and read e-books. This glove allows the person to type characters based on different Braille combination using six slot sensors. The vibration in six different positions of the glove which matches to the Braille code allows them to read characters.
Keywords: Braille, Braille Hand-Glove, Slot sensors, Vibration motors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4175148 Feature-Based Summarizing and Ranking from Customer Reviews
Authors: Dim En Nyaung, Thin Lai Lai Thein
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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.
Keywords: Opinion Mining, Opinion Summarization, Sentiment Analysis, Text Mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2926147 Post-Modernist Tragi-Comedy: A Study of Tom Stoppard’s Rosencrantz and Guildenstern Are Dead
Authors: Azza Taha Zaki
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The death of tragedy is probably one of the most distinctive literary controversies of the twentieth century. There is common critical consent that tragedy in the classical sense of the word is no longer possible. Thinkers, philosophers and critics such as Nietzsche, Durrenmatt and George Steiner have all agreed that the decline of the genre in the modern age is due to the total lack of a unified world image and the absence of a shared vision in a fragmented and ideologically diversified world. The production of Rosencrantz and Guildenstern Are Dead in 1967 marked the rise of the genre of tragi-comedy as a more appropriate reflection of the spirit of the age. At the hands of such great dramatists as Tom Stoppard (1937- ), the revived genre was not used as an extra comic element to give some comic relief to an otherwise tragic text, but it was given a postmodernist touch to serve the interpretation of the dilemma of man in the postmodernist world. This paper will study features of postmodernist tragi-comedy in Rosencrantz and Guildenstern Are Dead as one of the most important plays in the modern British theatre and investigate Stoppard’s vision of man and life as influenced by postmodernist thought and philosophy.
Keywords: British, drama, postmodernist, Stoppard, tragi-comedy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 402146 Operation Parameters of Vacuum Cleaned Filters
Authors: Wilhelm Hoeflinger, Thomas Laminger, Johannes Wolfslehner
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For vacuum cleaned dust filters there exist no calculation methods to determine design parameters (e.g. traverse velocity of the nozzle, filter area…). In this work a method to calculate the optimum traverse velocity of the nozzle of an industrial-size flat dust filter at a given mean pressure drop and filter face velocity was elaborated. Well-known equations for the design of a cleanable multi-chamber bag-house-filter were modified in order to take into account a continuously regeneration of a dust filter by a nozzle. Thereby, the specific filter medium resistance and the specific cake resistance values are needed which can be derived from filter tests under constant operation conditions.
A lab-scale filter test rig was used to derive the specific filter media resistance value and the specific cake resistance value for vacuum cleaned filter operation. Three different filter media were tested and the determined parameters were compared to each other.
Keywords: Design of dust filter, Dust removing, Filter regeneration, Operation parameters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1923145 Optimization of Shear Frame Structures Applying Various Forms of Wavelet Transforms
Authors: Seyed Sadegh Naseralavi, Sohrab Nemati, Ehsan Khojastehfar, Sadegh Balaghi
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In the present research, various formulations of wavelet transform are applied on acceleration time history of earthquake. The mentioned transforms decompose the strong ground motion into low and high frequency parts. Since the high frequency portion of strong ground motion has a minor effect on dynamic response of structures, the structure is excited by low frequency part. Consequently, the seismic response of structure is predicted consuming one half of computational time, comparing with conventional time history analysis. Towards reducing the computational effort needed in seismic optimization of structure, seismic optimization of a shear frame structure is conducted by applying various forms of mentioned transformation through genetic algorithm.
Keywords: Time history analysis, wavelet transform, optimization, earthquake.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 785144 Existence of Nano-Organic Carbon Particles below the Size Range of 10 nm in the Indoor Air Environment
Authors: Bireswar Paul, Amitava Datta
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Indoor air environment is a big concern in the last few decades in the developing countries, with increased focus on monitoring the air quality. In this work, an experimental study has been conducted to establish the existence of carbon nanoparticles below the size range of 10 nm in the non-sooting zone of a LPG/air partially premixed flame. Mainly, four optical techniques, UV absorption spectroscopy, fluorescence spectroscopy, dynamic light scattering and TEM have been used to characterize and measure the size of carbon nanoparticles in the sampled materials collected from the inner surface of the flame front. The existence of the carbon nanoparticles in the sampled material has been confirmed with the typical nature of the absorption and fluorescence spectra already reported in the literature. The band gap energy shows that the particles are made up of three to six aromatic rings. The size measurement by DLS technique also shows that the particles below the size range of 10 nm. The results of DLS are also corroborated by the TEM image of the same material.
Keywords: Indoor air, carbon nanoparticles, LPG, partially premixed flame, optical techniques.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 870143 Multi-Modal Visualization of Working Instructions for Assembly Operations
Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger
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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.Keywords: Assembly, assistive technologies, augmented reality, manufacturing, visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 905142 Effect of Different Moisture States of Surface-Treated Recycled Concrete Aggregate on Properties of Fresh and Hardened Concrete
Authors: Sallehan Ismail, Mahyuddin Ramli
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This study examined the properties of fresh and hardened concretes as influenced by the moisture state of the coarse recycled concrete aggregates (RCA) after surface treatment. Surface treatment was performed by immersing the coarse RCA in a calcium metasilicate (CM) solution. The treated coarse RCA was maintained in three controlled moisture states, namely, air-dried, oven-dried, and saturated surface-dried (SSD), prior to its use in a concrete mix. The physical properties of coarse RCA were evaluated after surface treatment during the first phase of the experiment to determine the density and the water absorption characteristics of the RCA. The second phase involved the evaluation of the slump, slump loss, density, and compressive strength of the concretes that were prepared with different proportions of natural and treated coarse RCA. Controlling the moisture state of the coarse RCA after surface treatment was found to significantly influence the properties of the fresh and hardened concretes.
Keywords: Moisture state, recycled concrete aggregate, surface treatment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3237141 Humanoid Personalized Avatar Through Multiple Natural Language Processing
Authors: Jin Hou, Xia Wang, Fang Xu, Viet Dung Nguyen, Ling Wu
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There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.
Keywords: personalized avatar, mutiple natural luanguage processing, social backgrounds, anmimation, human computer interaction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1958140 Multimedia Data Fusion for Event Detection in Twitter by Using Dempster-Shafer Evidence Theory
Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan
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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.Keywords: Data fusion, Dempster-Shafer theory, data mining, event detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1790139 Towards an Intelligent Ontology Construction Cost Estimation System: Using BIM and New Rules of Measurement Techniques
Authors: F. H. Abanda, B. Kamsu-Foguem, J. H. M. Tah
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Construction cost estimation is one of the most important aspects of construction project design. For generations, the process of cost estimating has been manual, time-consuming and error-prone. This has partly led to most cost estimates to be unclear and riddled with inaccuracies that at times lead to over- or underestimation of construction cost. The development of standard set of measurement rules that are understandable by all those involved in a construction project, have not totally solved the challenges. Emerging Building Information Modelling (BIM) technologies can exploit standard measurement methods to automate cost estimation process and improve accuracies. This requires standard measurement methods to be structured in ontological and machine readable format; so that BIM software packages can easily read them. Most standard measurement methods are still text-based in textbooks and require manual editing into tables or Spreadsheet during cost estimation. The aim of this study is to explore the development of an ontology based on New Rules of Measurement (NRM) commonly used in the UK for cost estimation. The methodology adopted is Methontology, one of the most widely used ontology engineering methodologies. The challenges in this exploratory study are also reported and recommendations for future studies proposed.
Keywords: BIM, Construction projects, Cost estimation, NRM, Ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4421138 An Empirical Analysis of the Impact of Selected Macroeconomic Variables on Capital Formation in Libya (1970–2010)
Authors: Khaled Ramadan Elbeydi
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This study is carried out to provide an insight into the analysis of the impact of selected macro-economic variables on gross fixed capital formation in Libya using annual data over the period (1970-2010). The importance of this study comes from the ability to show the relative important factors that impact the Libyan gross fixed capital formation. This understanding would give indications to decision makers on which policy they must focus to stimulate the economy. An Autoregressive Distributed Lag (ARDL) modeling process is employed to investigate the impact of the Gross Domestic Product, Monetary Base and Trade Openness on Gross Fixed Capital Formation in Libya. The results of this study reveal that there is an equilibrium relationship between capital formation and its determinants. The results also indicate that GDP and trade openness largely explain the pattern of capital formation in Libya. The findings and recommendations provide vital information relevant for policy formulation and implementation aimed to improve capital formation in Libya.
Keywords: ARDL, Bounds test, capital formation, Cointegration, Libya.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1715137 Automatic Reusability Appraisal of Software Components using Neuro-fuzzy Approach
Authors: Parvinder S. Sandhu, Hardeep Singh
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Automatic reusability appraisal could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this paper, we have mentioned two-tier approach by studying the structural attributes as well as usability or relevancy of the component to a particular domain. Latent semantic analysis is used for the feature vector representation of various software domains. It exploits the fact that FeatureVector codes can be seen as documents containing terms -the idenifiers present in the components- and so text modeling methods that capture co-occurrence information in low-dimensional spaces can be used. Further, we devised Neuro- Fuzzy hybrid Inference System, which takes structural metric values as input and calculates the reusability of the software component. Decision tree algorithm is used to decide initial set of fuzzy rules for the Neuro-fuzzy system. The results obtained are convincing enough to propose the system for economical identification and retrieval of reusable software components.Keywords: Clustering, ID3, LSA, Neuro-fuzzy System, SVD
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1651136 Hydraulic Studies on Core Components of PFBR
Authors: G. K. Pandey, D. Ramadasu, I. Banerjee, V. Vinod, G. Padmakumar, V. Prakash, K. K. Rajan
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Detailed thermal hydraulic investigations are very essential for safe and reliable functioning of liquid metal cooled fast breeder reactors. These investigations are further more important for components with complex profile, since there is no direct correlation available in literature to evaluate the hydraulic characteristics of such components directly. In those cases available correlations for similar profile or geometries may lead to significant uncertainty in the outcome. Hence experimental approach can be adopted to evaluate these hydraulic characteristics more precisely for better prediction in reactor core components. Prototype Fast Breeder Reactor (PFBR), a sodium cooled pool type reactor is under advanced stage of construction at Kalpakkam, India. Several components of this reactor core require hydraulic investigation before its usage in the reactor. These hydraulic investigations on full scale models, carried out by experimental approaches using water as simulant fluid are discussed in the paper.
Keywords: Fast Breeder Reactor, Cavitation, pressure drop, Reactor components.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2924135 Supply Chain Decarbonisation – A Cost-Based Decision Support Model in Slow Steaming Maritime Operations
Authors: Eugene Y. C. Wong, Henry Y. K. Lau, Mardjuki Raman
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CO2 emissions from maritime transport operations represent a substantial part of the total greenhouse gas emission. Vessels are designed with better energy efficiency. Minimizing CO2 emission in maritime operations plays an important role in supply chain decarbonisation. This paper reviews the initiatives on slow steaming operations towards the reduction of carbon emission. It investigates the relationship and impact among slow steaming cost reduction, carbon emission reduction, and shipment delay. A scenario-based cost-driven decision support model is developed to facilitate the selection of the optimal slow steaming options, considering the cost on bunker fuel consumption, available speed, carbon emission, and shipment delay. The incorporation of the social cost of cargo is reviewed and suggested. Additional measures on the effect of vessels sizes, routing, and type of fuels towards decarbonisation are discussed.
Keywords: Slow steaming, carbon emission, maritime logistics, sustainability, green supply chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2665134 Digital Preservation in Nigeria Universities Libraries: A Comparison between University of Nigeria Nsukka and Ahmadu Bello University Zaria
Authors: Suleiman Musa, Shuaibu Sidi Safiyanu
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This study examined the digital preservation in Nigeria university libraries. A comparison between the university of Nigeria Nsukka (UNN) and Ahmadu Bello University Zaria (ABU, Zaria). The study utilized primary source of data obtained from two selected institution librarians. Finding revealed varying results in terms of skills acquired by librarians before and after digitization of the two institutions. The study reports that journals publication, text book, CD-ROMS, conference papers and proceedings, theses, dissertations and seminar papers are among the information resources available for digitization. The study further documents that copyright issue, power failure, and unavailability of needed materials are among the challenges facing the digitization of library of the institution. On the basis of the finding, the study concluded that digitization of library enhances efficiency in organization and retrieval of information services. The study therefore recommended that software should be upgraded with backup, training of the librarians on digital process, installation of antivirus and enhancement of technical collaboration between the library and MIS.Keywords: Digitalization, preservation, libraries, comparison.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1715133 AI-based Radio Resource and Transmission Opportunity Allocation for 5G-V2X HetNets: NR and NR-U networks
Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard A. Jorswieck
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The capacity of fifth-generation (5G)vehicle-to-everything (V2X) networks poses significant challenges.To address this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a vehicular heterogeneous network (HetNet). We propose a framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles, while guarantying the WiFi users throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.
Keywords: Vehicle-to-everything, resource allocation, BS assignment, new radio, new radio unlicensed, coexistence NR-U and WiFi, deep deterministic policy gradient, Deep Q-network, Duty cycle mechanism.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 286132 Speech Recognition Using Scaly Neural Networks
Authors: Akram M. Othman, May H. Riadh
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This research work is aimed at speech recognition using scaly neural networks. A small vocabulary of 11 words were established first, these words are “word, file, open, print, exit, edit, cut, copy, paste, doc1, doc2". These chosen words involved with executing some computer functions such as opening a file, print certain text document, cutting, copying, pasting, editing and exit. It introduced to the computer then subjected to feature extraction process using LPC (linear prediction coefficients). These features are used as input to an artificial neural network in speaker dependent mode. Half of the words are used for training the artificial neural network and the other half are used for testing the system; those are used for information retrieval. The system components are consist of three parts, speech processing and feature extraction, training and testing by using neural networks and information retrieval. The retrieve process proved to be 79.5-88% successful, which is quite acceptable, considering the variation to surrounding, state of the person, and the microphone type.Keywords: Feature extraction, Liner prediction coefficients, neural network, Speech Recognition, Scaly ANN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1725131 An Ontology Based Question Answering System on Software Test Document Domain
Authors: Meltem Serhatli, Ferda N. Alpaslan
Abstract:
Processing the data by computers and performing reasoning tasks is an important aim in Computer Science. Semantic Web is one step towards it. The use of ontologies to enhance the information by semantically is the current trend. Huge amount of domain specific, unstructured on-line data needs to be expressed in machine understandable and semantically searchable format. Currently users are often forced to search manually in the results returned by the keyword-based search services. They also want to use their native languages to express what they search. In this paper, an ontology-based automated question answering system on software test documents domain is presented. The system allows users to enter a question about the domain by means of natural language and returns exact answer of the questions. Conversion of the natural language question into the ontology based query is the challenging part of the system. To be able to achieve this, a new algorithm regarding free text to ontology based search engine query conversion is proposed. The algorithm is based on investigation of suitable question type and parsing the words of the question sentence.Keywords: Description Logics, ontology, question answering, reasoning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2139130 Empirical Process Monitoring Via Chemometric Analysis of Partially Unbalanced Data
Authors: Hyun-Woo Cho
Abstract:
Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.
Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1739