Search results for: international standard industrial classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12845

Search results for: international standard industrial classification

12815 Classification of Attacks Over Cloud Environment

Authors: Karim Abouelmehdi, Loubna Dali, Elmoutaoukkil Abdelmajid, Hoda Elsayed, Eladnani Fatiha, Benihssane Abderahim

Abstract:

The security of cloud services is the concern of cloud service providers. In this paper, we will mention different classifications of cloud attacks referred by specialized organizations. Each agency has its classification of well-defined properties. The purpose is to present a high-level classification of current research in cloud computing security. This classification is organized around attack strategies and corresponding defenses.

Keywords: cloud computing, classification, risk, security

Procedia PDF Downloads 506
12814 Global Differences in Job Satisfaction of Healthcare Professionals

Authors: Jonathan H. Westover, Ruthann Cunningham, Jaron Harvey

Abstract:

Purpose: Job satisfaction is one of the most critical attitudes among employees. Understanding whether employees are satisfied with their jobs and what is driving that satisfaction is important for any employer, but particularly for healthcare organizations. This study looks at the question of job satisfaction and drivers of job satisfaction among healthcare professionals at a global scale, looking for trends that generalize across 37 countries. Study: This study analyzed job satisfaction responses to the 2015 Work Orientations IV wave of the International Social Survey Programme (ISSP) to understand differences in antecedents for and levels of job satisfaction among healthcare professionals. A total of 18,716 respondents from 37 countries participated in the annual survey. Findings: Respondents self-identified their occupational category based on corresponding International Standard Classification of Occupations (ISCO-08) codes. Results suggest that mean overall job satisfaction was highest among health service managers and generalist medical practitioners and lowest among environmental hygiene professionals and nursing professionals. Originality: Many studies have addressed the issue of job satisfaction in healthcare, examining small samples of specific healthcare workers. In this study, using a large international dataset, we are able to examine questions of job satisfaction across large groups of healthcare workers in different occupations within the healthcare field.

Keywords: job satisfaction, healthcare industry, global comparisons, workplace

Procedia PDF Downloads 118
12813 Classification of Poverty Level Data in Indonesia Using the Naïve Bayes Method

Authors: Anung Style Bukhori, Ani Dijah Rahajoe

Abstract:

Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

Procedia PDF Downloads 29
12812 International Tourists’ Travel Motivation by Push-Pull Factors and Decision Making for Selecting Thailand as Destination Choice

Authors: Siripen Yiamjanya, Kevin Wongleedee

Abstract:

This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: decision making, destination choice, international tourist, pull factor, push factor, Thailand, travel motivation

Procedia PDF Downloads 366
12811 The Historical Framework of International Crime in International Criminal Law

Authors: Tahraoui Boualem

Abstract:

Researching the historical framework of international crime means examining the historical facts that have contributed to uncovering this serious crime affecting international interests, and the law by which the study of the subject of international crime is determined is international criminal law, which is a branch of public international law. In this context, the historical study of international crime means recognizing the existence of an international community governed by international law, which makes us acknowledge that ancient societies lacked such stable and recurring international relations. Therefore, an attempt to monitor international crime in those ancient societies is only to demonstrate a historical fact that those societies have known some features of this crime, and have contributed in one way or another to the development of international criminal law without defining its concept or legal nature. The international community has affirmed the principle of establishing peace, achieving security, and respecting human rights. As a basis for friendly relations between the people of the international community and in case of prejudice, such as the aggressors breaching the obligations imposed on them, whether in time of peace or war.

Keywords: historical framework, of international crime, peace or war., international law

Procedia PDF Downloads 64
12810 Fundamentals of Theorizing Power in International Relations

Authors: Djehich Mohamed Yousri

Abstract:

The field of political science is one of the sciences in which there is much controversy, in terms of the multiplicity of schools, trends, and goals. This overlap and complexity in the interpretation of the political phenomenon in political science has been linked to other disciplines associated with it, and the science of international relations and the huge amount of theories that have found a wide range and a decisive position after the national tide in the history of Western political thought, especially after the Westphalia Conference 1648, and as a result was approved The new foundations of international politics, the most important of which is respect for state sovereignty. Historical events continued and coincided with scientific, intellectual, and economic developments following the emergence of the industrial revolution, followed by the technological revolutions in all their contents, which led to the rooting and establishment of a comprehensive political system that is more complex and overlapping than it was in the past during the First and Second World Wars. The international situation has become dependent on the digital revolution and its aspirations in The comprehensive transformation witnessed by international political relations after the Cold War.

Keywords: theorizing, international relations, approaches to international relations, political science, the political system

Procedia PDF Downloads 72
12809 New Formula for Revenue Recognition Likely to Change the Prescription for Pharma Industry

Authors: Shruti Hajirnis

Abstract:

In May 2014, FASB issued Accounting Standards Update (ASU) 2014-09, Revenue from Contracts with Customers (Topic 606), and the International Accounting Standards Board (IASB) issued International Financial Reporting Standards (IFRS) 15, Revenue from Contracts with Customers that will supersede virtually all revenue recognition requirements in IFRS and US GAAP. FASB and the IASB have basically achieved convergence with these standards, with only some minor differences such as collectability threshold, interim disclosure requirements, early application and effective date, impairment loss reversal and nonpublic entity requirements. This paper discusses the impact of five-step model prescribed in new revenue standard on the entities operating in Pharma industry. It also outlines the considerations for these entities while implementing the new standard.

Keywords: revenue recognition, pharma industry, standard, requirements

Procedia PDF Downloads 419
12808 Improved Classification Procedure for Imbalanced and Overlapped Situations

Authors: Hankyu Lee, Seoung Bum Kim

Abstract:

The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

Procedia PDF Downloads 276
12807 Quality Culture Framework Proposal for Libyan Industrial Companies

Authors: Mostafa Ahmed Shokshok

Abstract:

Libyan industrial companies face many challenges in today's competitive market. Quality management culture approaches is one of these challenges which may furnish the road to the Libyan industrial companies to effectively empower their employees and improve their ability to respond to the international competition. The primary objective of this paper is to design a practical approach to guide Libyan industrial companies toward successful quality culture implementation.

Keywords: TQM, quality culture, Libyan manufacturing industries, quality framework

Procedia PDF Downloads 387
12806 Review and Comparison of Associative Classification Data Mining Approaches

Authors: Suzan Wedyan

Abstract:

Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

Procedia PDF Downloads 507
12805 Meta-Learning for Hierarchical Classification and Applications in Bioinformatics

Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

Procedia PDF Downloads 281
12804 Methods Used to Achieve Airtightness of 0.07 Ach@50Pa for an Industrial Building

Authors: G. Wimmers

Abstract:

The University of Northern British Columbia needed a new laboratory building for the Master of Engineering in Integrated Wood Design Program and its new Civil Engineering Program. Since the University is committed to reducing its environmental footprint and because the Master of Engineering Program is actively involved in research of energy efficient buildings, the decision was made to request the energy efficiency of the Passive House Standard in the Request for Proposals. The building is located in Prince George in Northern British Columbia, a city located at the northern edge of climate zone 6 with an average low between -8 and -10.5 in the winter months. The footprint of the building is 30m x 30m with a height of about 10m. The building consists of a large open space for the shop and laboratory with a small portion of the floorplan being two floors, allowing for a mezzanine level with a few offices as well as mechanical and storage rooms. The total net floor area is 1042m² and the building’s gross volume 9686m³. One key requirement of the Passive House Standard is the airtight envelope with an airtightness of < 0.6 ach@50Pa. In the past, we have seen that this requirement can be challenging to reach for industrial buildings. When testing for air tightness, it is important to test in both directions, pressurization, and depressurization, since the airflow through all leakages of the building will, in reality, happen simultaneously in both directions. A specific detail or situation such as overlapping but not sealed membranes might be airtight in one direction, due to the valve effect, but are opening up when tested in the opposite direction. In this specific project, the advantage was the overall very compact envelope and the good volume to envelope area ratio. The building had to be very airtight and the details for the windows and doors installation as well as all transitions from walls to roof and floor, the connections of the prefabricated wall panels and all penetrations had to be carefully developed to allow for maximum airtightness. The biggest challenges were the specific components of this industrial building, the large bay door for semi-trucks and the dust extraction system for the wood processing machinery. The testing was carried out in accordance with EN 132829 (method A) as specified in the International Passive House Standard and the volume calculation was also following the Passive House guideline resulting in a net volume of 7383m3, excluding all walls, floors and suspended ceiling volumes. This paper will explore the details and strategies used to achieve an airtightness of 0.07 ach@50Pa, to the best of our knowledge the lowest value achieved in North America so far following the test protocol of the International Passive House Standard and discuss the crucial steps throughout the project phases and the most challenging details.

Keywords: air changes, airtightness, envelope design, industrial building, passive house

Procedia PDF Downloads 123
12803 A Review of Effective Gene Selection Methods for Cancer Classification Using Microarray Gene Expression Profile

Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

Abstract:

Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

Procedia PDF Downloads 420
12802 A Quantitative Evaluation of Text Feature Selection Methods

Authors: B. S. Harish, M. B. Revanasiddappa

Abstract:

Due to rapid growth of text documents in digital form, automated text classification has become an important research in the last two decades. The major challenge of text document representations are high dimension, sparsity, volume and semantics. Since the terms are only features that can be found in documents, selection of good terms (features) plays an very important role. In text classification, feature selection is a strategy that can be used to improve classification effectiveness, computational efficiency and accuracy. In this paper, we present a quantitative analysis of most widely used feature selection (FS) methods, viz. Term Frequency-Inverse Document Frequency (tfidf ), Mutual Information (MI), Information Gain (IG), CHISquare (x2), Term Frequency-Relevance Frequency (tfrf ), Term Strength (TS), Ambiguity Measure (AM) and Symbolic Feature Selection (SFS) to classify text documents. We evaluated all the feature selection methods on standard datasets like 20 Newsgroups, 4 University dataset and Reuters-21578.

Keywords: classifiers, feature selection, text classification

Procedia PDF Downloads 423
12801 Factors of Adoption of the International Financial Reporting Standard for Small and Medium Sized Entities

Authors: Uyanga Jadamba

Abstract:

Globalisation of the world economy has necessitated the development and implementation of a comparable and understandable reporting language suitable for use by all reporting entities. The International Accounting Standard Board (IASB) provides an international reporting language that lets all users understand the financial information of their business and potentially allows them to have access to finance at an international level. The study is based on logistic regression analysis to investigate the factors for the adoption of theInternational Financial Reporting Standard for Small and Medium sized Entities (IFRS for SMEs). The study started with a list of 217 countries from World Bank data. Due to the lack of availability of data, the final sample consisted of 136 countries, including 60 countries that have adopted the IFRS for SMEs and 76 countries that have not adopted it yet. As a result, the study included a period from 2010 to 2020 and obtained 1360 observations. The findings confirm that the adoption of the IFRS for SMEs is significantly related to the existence of national reporting standards, law enforcement quality, common law (legal system), and extent of disclosure. It means that the likelihood of adoption of the IFRS for SMEs decreases if the country already has a national reporting standard for SMEs, which suggests that implementation and transitional costs are relatively high in order to change the reporting standards. The result further suggests that the new standard adoption is easier in countries with constructive law enforcement and effective application of laws. The finding also shows that the adoption increases if countries have a common law system which suggests that efficient reportingregulations are more widespread in these countries. Countries with a high extent of disclosing their financial information are more likely to adopt the standard than others. The findings lastly show that the audit qualityand primary education levelhave no significant impact on the adoption.One possible explanation for this could be that accounting professionalsfrom in developing countries lacked complete knowledge of the international reporting standards even though there was a requirement to comply with them. The study contributes to the literature by providing factors that impact the adoption of the IFRS for SMEs. It helps policymakers to better understand and apply the standard to improve the transparency of financial statements. The benefit of adopting the IFRS for SMEs is significant due to the relaxed and tailored reporting requirements for SMEs, reduced burden on professionals to comply with the standard, and provided transparent financial information to gain access to finance.The results of the study are useful toemerging economies where SMEs are dominant in the economy in informing its evaluation of the adoption of the IFRS for SMEs.

Keywords: IFRS for SMEs, international financial reporting standard, adoption, institutional factors

Procedia PDF Downloads 50
12800 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 225
12799 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 207
12798 Research on Ultrafine Particles Classification Using Hydrocyclone with Annular Rinse Water

Authors: Tao Youjun, Zhao Younan

Abstract:

The separation effect of fine coal can be improved by the process of pre-desliming. It was significantly enhanced when the fine coal was processed using Falcon concentrator with the removal of -45um coal slime. Ultrafine classification tests using Krebs classification cyclone with annular rinse water showed that increasing feeding pressure can effectively avoid the phenomena of heavy particles passing into overflow and light particles slipping into underflow. The increase of rinse water pressure could reduce the content of fine-grained particles while increasing the classification size. The increase in feeding concentration had a negative effect on the efficiency of classification, meanwhile increased the classification size due to the enhanced hindered settling caused by high underflow concentration. As a result of optimization experiments with response indicator of classification efficiency which based on orthogonal design using Design-Expert software indicated that the optimal classification efficiency reached 91.32% with the feeding pressure of 0.03MPa, the rinse water pressure of 0.02MPa and the feeding concentration of 12.5%. Meanwhile, the classification size was 49.99 μm which had a good agreement with the predicted value.

Keywords: hydrocyclone, ultrafine classification, slime, classification efficiency, classification size

Procedia PDF Downloads 138
12797 Disaster Adaptation Mechanism and Disaster Prevention Adaptation Planning Strategies for Industrial Parks in Response to Climate Change and Different Socio-Economic Disasters

Authors: Jen-Te Pai, Jao-Heng Liu, Shin-En Pai

Abstract:

The impact of climate change has intensified in recent years, causing Taiwan to face higher frequency and serious natural disasters. Therefore, it is imperative for industrial parks manufacturers to promote adaptation policies in response to climate change. On the other hand, with the rise of the international anti-terrorism situation, once a terrorist attack occurs, it will attract domestic and international media attention, especially the strategic and economic status of the science park. Thus, it is necessary to formulate adaptation and mitigation strategies under climate change and social economic disasters. After reviewed the literature about climate change, urban disaster prevention, vulnerability assessment, and risk communication, the study selected 62 industrial parks compiled by the Industrial Bureau of the Ministry of Economic Affairs of Taiwan as the research object. This study explored the vulnerability and disaster prevention and disaster relief functional assessment of these industrial parks facing of natural and socio-economic disasters. Furthermore, this study explored planned adaptation of industrial parks management section and autonomous adaptation of corporate institutions in the park. The conclusion of this study is that Taiwan industrial parks with a higher vulnerability to natural and socio-economic disasters should employ positive adaptive behaviours.

Keywords: adaptive behaviours, analytic network process, vulnerability, industrial parks

Procedia PDF Downloads 111
12796 Design and Implementation of Generative Models for Odor Classification Using Electronic Nose

Authors: Kumar Shashvat, Amol P. Bhondekar

Abstract:

In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

Procedia PDF Downloads 354
12795 Engagement Analysis Using DAiSEE Dataset

Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

Procedia PDF Downloads 91
12794 Radical Web Text Classification Using a Composite-Based Approach

Authors: Kolade Olawande Owoeye, George R. S. Weir

Abstract:

The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

Procedia PDF Downloads 119
12793 European Refugee Camps and the Right to an Adequate Standard of Living: Advancing Accountability under International Human Rights Law

Authors: Genevieve Zingg

Abstract:

Since the onset of the 2015 ‘refugee crisis’ in the European Union (EU), migrant deaths have overwhelmingly occurred in the Mediterranean Sea. However, far less attention has been paid to the startling number of injuries, deaths, and allegations of systematic human rights violations occurring within European refugee camps. Most troubling is the assertion that injuries and deaths in EU refugee camps have occurred as a result of negligent management and poor access to healthcare, food, water and sanitation, and other elements that comprise an adequate standard of living under international human rights law. Using available evidence and documentation, this paper will conduct a thorough examination of the causes of death and injury in EU refugee camps, with a specific focus on Greece, in order to identify instances of negligence or conditions that amount to potential breaches of human rights law. Based on its analysis, this paper will subsequently explore potential legal avenues to achieving justice and accountability under international human rights law in order to effectively address and remedy inadequate standards of living causing wrongful death or injury in European refugee camps.

Keywords: European Union, Greece, human rights, international human rights law, migration, refugees

Procedia PDF Downloads 167
12792 Role of International Organizations towards Good Governance: Recent Trends

Authors: E. Prema Shyam

Abstract:

The role of international organizations has contributed in various ways for the good governance in the world at large. Since the beginning of the 1990s international organizations, particularly those active in the areas of human rights, trade and economic etc., have embraced a 'good governance'. It is also pertinent to mention that the application of the concept of good governance to international organizations themselves and not exclusively to national or regional polities is a more recent phenomenon. Especially since the second half of the 1990s, a number of international organizations have carried out major governance reforms, assuming that their calls for governments to heed higher standards of good governance will be all the more credible provided that they develop a good governance standard for themselves. In addition to this number of organizations such as the United Nations (UN), Organisation for Economic Co-operation and Development (OECD), European Union (EU), International Committee of the Red Cross and World Trade Organization (WTO). OECD has been specifically mobilized to fight corruption. The World Bank was the first international organization to address the issue of good governance when it attributed the African development crisis to a crisis of governance in a 1989 report. International organizations are often denounced for their lack of transparency and democracy. However, in the last few years, a number of them have pushed through impressive reforms aimed at enhancing good governance standards within their own organizations, especially in the light of their long-standing secrecy. This is a remnant of the traditional conception of international organizations, which renders them merely answerable to their Members. International organizations have already gone quite some way in the areas of good management and opening up to the public. However, as far as participatory governance is concerned, lot to be done for the larger interest of society. In this paper, an attempt has been made to focus the issues on international organisations with regard to good governance.

Keywords: good governance, World Trade Organisation, international organisation, governance reforms

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12791 Islamic Financial Instrument, Standard Parallel Salam as an Alternative to Conventional Derivatives

Authors: Alireza Naserpoor

Abstract:

Derivatives are the most important innovation which has happened in the past decades. When it comes to financial markets, it has changed the whole way of operations of stock, commodities and currency market. Beside a lot of advantages, Conventional derivatives contracts have some disadvantages too. Some problems have been caused by derivatives contain raising Volatility, increasing Bankruptcies and causing financial crises. Standard Parallel Salam contract as an Islamic financial product meanwhile is a financing instrument can be used for risk management by investors. Standard Parallel Salam is a Shari’ah-Compliant contract. Furthermore, it is an alternative to conventional derivatives. Despite the fact that the unstructured types of that, has been used in several Islamic countries, This contract as a structured and standard financial instrument introduced in Iran Mercantile Exchange in 2014. In this paper after introducing parallel Salam, we intend to examine a collection of international experience and local measure regarding launching standard parallel Salam contract and proceed to describe standard scenarios for trading this instrument and practical experience in Iran Mercantile Exchange about this instrument. Afterwards, we make a comparison between SPS and Futures contracts as a conventional derivative. Standard parallel salam contract as an Islamic financial product, can be used for risk management by investors. SPS is a Shariah-Compliant contract. Furthermore it is an alternative to conventional derivatives. This contract as a structured and standard financial instrument introduced in Iran Mercantile Exchange in 2014. despite the fact that the unstructured types of that, has been used in several Islamic countries. In this article after introducing parallel salam, we intend to examine a collection of international experience and local measure regarding launching standard parallel salam contract and proceed to describe standard scenarios for trading this instrument containing two main approaches in SPS using, And practical experience in IME about this instrument Afterwards, a comparison between SPS and Futures contracts as a conventional derivatives.

Keywords: futures contracts, hedging, shari’ah compliant instruments, standard parallel salam

Procedia PDF Downloads 351
12790 A Research Analysis on the Source Technology and Convergence Types

Authors: Kwounghee Choi

Abstract:

Technological convergence between the various sectors is expected to have a very large impact on future industrial and economy. This study attempts to do empirical approach between specific technologies’ classification. For technological convergence classification, it is necessary to set the target technology to be analyzed. This study selected target technology from national research and development plan. At first we found a source technology for analysis. Depending on the weight of source technology, NT-based, BT-based, IT-based, ET-based, CS-based convergence types were classified. This study aims to empirically show the concept of convergence technology and convergence types. If we use the source technology to classify convergence type, it will be useful to make practical strategies of convergence technology.

Keywords: technology convergence, source technology, convergence type, R&D strategy, technology classification

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12789 A Comparative Analysis of E-Government Quality Models

Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

Many quality models have been used to measure e-government portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.

Keywords: e-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126

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12788 Hyperspectral Image Classification Using Tree Search Algorithm

Authors: Shreya Pare, Parvin Akhter

Abstract:

Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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12787 Pose Normalization Network for Object Classification

Authors: Bingquan Shen

Abstract:

Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

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12786 Applicable Law to Intellectual and Industrial Property Agreements According to Turkish Private International Law and Rome I Regulation

Authors: Sema Cortoglu Koca

Abstract:

Intellectual and industrial property rules, have a substantial effect on the sustainable development. Intellectual and industrial property rights, as temporary privileges over the products of intellectual activity, determine the supervision of information and technology. The level and scope of intellectual property protection thus influence the flow of technology between developed and developing countries. In addition, intellectual and industrial property rights are based on the notion of balance. Since they are time-limited rights, they reconcile private and public benefits. That is, intellectual and industrial property rights respond to both private interests and public interests by rewarding innovators and by promoting the dissemination of ideas, respectively. Intellectual and industrial property rights can, therefore, be a tool for sustainable development. If countries can balance their private and public interests according to their particular context and circumstances, they can ensure the intellectual and industrial property which promotes innovation and technology transfer relevant for them. People, enterprises and countries who need technology, can transfer developed technology which is acquired by people, enterprises and countries so as to decrease their technological necessity and improve their technology. Because of the significance of intellectual and industrial property rights on the technology transfer law as mentioned above, this paper is confined to intellectual and industrial property agreements especially technology transfer contracts. These are license contract, know-how contract, franchise agreement, joint venture agreement, management agreement, research and development agreement. In Turkey, technology transfer law is still a developing subject. For developing countries, technology transfer regulations are very important for their private international law because these countries do not know which technology transfer law is applicable when conflicts arise. In most technology transfer contracts having international elements, the parties choose a law to govern their contracts. Where the parties do not choose a law, either expressly or impliedly, and matters which is not excluded in party autonomy, the court has to determine the applicable law to contracts in a matter of capacity, material, the formal and essential validity of contracts. For determining the proper law of technology transfer contracts, it is tried to build a rule for applying all technology transfer contracts. This paper is confined to the applicable law to intellectual and industrial property agreements according to ‘5718 Turkish Act on Private International Law and Civil Procedure’ and ‘Regulation (EC) No 593/2008 of the European Parliament and of the Council of 17 June 2008 on the law applicable to contractual obligations (Rome I)’. Like these complex contracts, to find a rule can be really difficult. We can arrange technology transfer contracts in groups, and we can determine the rule and connecting factors to these groups. For the contracts which are not included in these groups, we can determine a special rule considering the characteristics of the contract.

Keywords: intellectual and industrial property agreements, Rome I regulation, technology transfer, Turkish act on private international law and civil procedure

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