Search results for: export trade data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25196

Search results for: export trade data

24026 Effect of Discharge Pressure Conditions on Flow Characteristics in Axial Piston Pump

Authors: Jonghyuk Yoon, Jongil Yoon, Seong-Gyo Chung

Abstract:

In many kinds of industries which usually need a large amount of power, an axial piston pump has been widely used as a main power source of a hydraulic system. The axial piston pump is a type of positive displacement pump that has several pistons in a circular array within a cylinder block. As the cylinder block and pistons start to rotate, since the exposed ends of the pistons are constrained to follow the surface of the swashed plate, the pistons are driven to reciprocate axially and then a hydraulic power is produced. In the present study, a numerical simulation which has three dimensional full model of the axial piston pump was carried out using a commercial CFD code (Ansys CFX 14.5). In order to take into consideration motion of compression and extension by the reciprocating pistons, the moving boundary conditions were applied as a function of the rotation angle to that region. In addition, this pump using hydraulic oil as working fluid is intentionally designed as a small amount of oil leaks out in order to lubricate moving parts. Since leakage could directly affect the pump efficiency, evaluation of effect of oil-leakage is very important. In order to predict the effect of the oil leakage on the pump efficiency, we considered the leakage between piston-shoe and swash-plate by modeling cylindrical shaped-feature at the end of the cylinder. In order to validate the numerical method used in this study, the numerical results of the flow rate at the discharge port are compared with the experimental data, and good agreement between them was shown. Using the validated numerical method, the effect of the discharge pressure was also investigated. The result of the present study can be useful information of small axial piston pump used in many different manufacturing industries. Acknowledgement: This research was financially supported by the “Next-generation construction machinery component specialization complex development program” through the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT).

Keywords: axial piston pump, CFD, discharge pressure, hydraulic system, moving boundary condition, oil leaks

Procedia PDF Downloads 232
24025 Alternative Dispute Resolution Procedures for International Conflicts about Industrial Design

Authors: Moreno Liso Lourdes

Abstract:

The industrial design protects the appearance of part or all of a product resulting from the features of, in particular, the lines, contours, colors, shape, texture or materials of the product itself or its ornamentation. The industrial property offers a different answer depending on the characteristics of the shape object of protection possible, including the trademark and industrial design. There are certain cases where the trademark right invalidate the exclusive right of the industrial design. This can occur in the following situations: 1st) collected as a sign design and trademarked; and 2nd) you want to trademark and protected as a form design (either registered or unregistered). You can either get a trade mark or design right in the same sign or form, provided it meets the legal definition of brand and design and meets the requirements imposed for the protection of each of them, even able to produce an overlap of protection. However, this double protection does not have many advantages. It is, therefore, necessary to choose the best form of legal protection according to the most adequate ratios. The diversity of rights that can use the creator of an industrial design to protect your job requires you to make a proper selection to prevent others, especially their competitors, taking advantage of the exclusivity that guarantees the law. It is necessary to choose between defending the interests of the parties through a judicial or extrajudicial procedure when the conflict arises. In this paper, we opted for the defense through mediation.

Keywords: industrial design, ADR, Law, EUIPO

Procedia PDF Downloads 227
24024 Variance-Aware Routing and Authentication Scheme for Harvesting Data in Cloud-Centric Wireless Sensor Networks

Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

Abstract:

The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

Procedia PDF Downloads 56
24023 Quality of Age Reporting from Tanzania 2012 Census Results: An Assessment Using Whipple’s Index, Myer’s Blended Index, and Age-Sex Accuracy Index

Authors: A. Sathiya Susuman, Hamisi F. Hamisi

Abstract:

Background: Many socio-economic and demographic data are age-sex attributed. However, a variety of irregularities and misstatement are noted with respect to age-related data and less to sex data because of its biological differences between the genders. Noting the misstatement/misreporting of age data regardless of its significance importance in demographics and epidemiological studies, this study aims at assessing the quality of 2012 Tanzania Population and Housing Census Results. Methods: Data for the analysis are downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple’s index, Myers’ blended index, and Age-Sex Accuracy index. Results: The recorded Whipple’s index for both sexes was 154.43; male has the lowest index of about 152.65 while female has the highest index of about 156.07. For Myers’ blended index, the preferences were at digits ‘0’ and ‘5’ while avoidance were at digits ‘1’ and ‘3’ for both sexes. Finally, Age-sex index stood at 59.8 where sex ratio score was 5.82 and age ratio scores were 20.89 and 21.4 for males and female respectively. Conclusion: The evaluation of the 2012 PHC data using the demographic techniques has qualified the data inaccurate as the results of systematic heaping and digit preferences/avoidances. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.

Keywords: age heaping, digit preference/avoidance, summary indices, Whipple’s index, Myer’s index, age-sex accuracy index

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24022 A Proposal to Integrate Spatially Explicit Ecosystem Services with Urban Metabolic Modelling

Authors: Thomas Elliot, Javier Babi Almenar, Benedetto Rugani

Abstract:

The integration of urban metabolism (UM) with spatially explicit ecosystem service (ES) stocks has the potential to advance sustainable urban development. It will correct the lack of spatially specificity of current urban metabolism models. Furthermore, it will include into UM not only the physical properties of material and energy stocks and flows, but also the implications to the natural capital that provides and maintains human well-being. This paper presents the first stages of a modelling framework by which urban planners can assess spatially the trade-offs of ES flows resulting from urban interventions of different character and scale. This framework allows for a multi-region assessment which takes into account sustainability burdens consequent to an urban planning event occurring elsewhere in the environment. The urban boundary is defined as the Functional Urban Audit (FUA) method to account for trans-administrative ES flows. ES are mapped using CORINE land use within the FUA. These stocks and flows are incorporated into a UM assessment method to demonstrate the transfer and flux of ES arising from different urban planning implementations.

Keywords: ecological economics, ecosystem services, spatial planning, urban metabolism

Procedia PDF Downloads 316
24021 Women Entrepreneurship: An Era Facing Challenges

Authors: Neetika Mahajan, Awanish Shukla

Abstract:

Entrepreneurship is key a driver to economic development. It opens opportunities for business startups and has potential to expand employment opportunities for many. Entrepreneurship gives ‘Purpose thriving’ approach towards society with new technologies and zeal to develop and compete in the market. There are many more advantages of entrepreneurship like freedom to scope of work and independence in setting own goals. Women contribute to nearly 50 percent of India’s population, constitute nearly 10 percent of a total number of entrepreneurs in India. Women are found to be better risk calculators, more ambitious and less prone to self-confidence. However, It is a hard fact that life has not been easy for women aspiring professional success. Gender parity is the biggest threat faced by female aspirant seeking new businesses. More challenges like socio-cultural barriers, insufficient financial assistance, etc. have been faced by the women of our country. To uplift the status of women in the society, a number of initiatives have been taken up by the Government of India. Initiatives like National Mission for Empowerment of Women by (Ministry of Women And Child Development) and SKILL INDIA aim to increase the technical skills and knowledge of women for tapping employment opportunities and self-confidence. Trade Related Entrepreneurship Assistance and Development (TREAD) Scheme and Mahila Coir Yojana are proposed by the Ministry of MSMEs aiming to facilitate employment opportunities for women and entrepreneurship development. This paper will aim to bring out the gaps and barriers, which are still resisting the potential women come upfront and start a new business irrespective of a number of initiatives being put by government of India. The aim is also to identify focus areas where further intervention is required and proposing suitable interventions. The methodology to take forward this research will include primary and secondary data collection from on ground survey to track various kind of challenges faced by aspirant women entrepreneurs. Insight will be put towards initiations by the government of India towards women empowerment and assistance to entrepreneurship. Scientific quantitative tools will be used to analyze collected information. The final output of the research shall focus on achieving the respective aims and objectives.

Keywords: women entrepreneurship, government programs and schemes, key challenges, economic development

Procedia PDF Downloads 235
24020 The Islamic Advertising Standardisation Revisited of Food Products

Authors: Nurzahidah Haji Jaapar, Anis Husna Abdul Halim, Mohd Faiz Mohamed Yusof, Mohd Dani Muhamad, Sharifah Fadylawaty Syed Abdullah

Abstract:

The growing size of Muslim is recognised with significant increasing of purchasing power in the market. The realm of trade and business has embedded religious values as the new market segments are emerging in offering food products to meet needs and demands of Muslim consumer. The emergence of new market in food industry, advertising is charged with all sort of negative effects includes promoting controversial unsafety and harmful products, wasteful spending and exploiting women and kids. Therefore, this research attempts to examine between previous examinations of advertising standardisation in ancient era and current practices in the market. This paper is based on content analysis of the literature. The results show that there are a bridge gap between the implementation of practices as the advent in industrial 4.0 in using digital advertising by food industry. Thus, this paper is able to recognize the differences between two era and significant in determining the best practices in advertising by following Islamic principles.

Keywords: Islamic advertising, unethical advertising, ethical advertising, Islamic principles

Procedia PDF Downloads 137
24019 Technological Development of a Biostimulant Bioproduct for Fruit Seedlings: An Engineering Overview

Authors: Andres Diaz Garcia

Abstract:

The successful technological development of any bioproduct, including those of the biostimulant type, requires to adequately completion of a series of stages allied to different disciplines that are related to microbiological, engineering, pharmaceutical chemistry, legal and market components, among others. Engineering as a discipline has a key contribution in different aspects of fermentation processes such as the design and optimization of culture media, the standardization of operating conditions within the bioreactor and the scaling of the production process of the active ingredient that it will be used in unit operations downstream. However, all aspects mentioned must take into account many biological factors of the microorganism such as the growth rate, the level of assimilation to various organic and inorganic sources and the mechanisms of action associated with its biological activity. This paper focuses on the practical experience within the Colombian Corporation for Agricultural Research (Agrosavia), which led to the development of a biostimulant bioproduct based on native rhizobacteria Bacillus amyloliquefaciens, oriented mainly to plant growth promotion in cape gooseberry nurseries and fruit crops in Colombia, and the challenges that were overcome from the expertise in the area of engineering. Through the application of strategies and engineering tools, a culture medium was optimized to obtain concentrations higher than 1E09 CFU (colony form units)/ml in liquid fermentation, the process of biomass production was standardized and a scale-up strategy was generated based on geometric (H/D of bioreactor relationships), and operational criteria based on a minimum dissolved oxygen concentration and that took into account the differences in the capacity of control of the process in the laboratory and pilot scales. Currently, the bioproduct obtained through this technological process is in stages of registration in Colombia for cape gooseberry fruits for export.

Keywords: biochemical engineering, liquid fermentation, plant growth promoting, scale-up process

Procedia PDF Downloads 103
24018 Model for Introducing Products to New Customers through Decision Tree Using Algorithm C4.5 (J-48)

Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

Abstract:

This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

Procedia PDF Downloads 412
24017 SWOT Analysis on the Prospects of Carob Use in Human Nutrition: Crete, Greece

Authors: Georgios A. Fragkiadakis, Antonia Psaroudaki, Theodora Mouratidou, Eirini Sfakianaki

Abstract:

Research: Within the project "Actions for the optimal utilization of the potential of carob in the Region of Crete" which is financed-supervised by the Region, with collaboration of Crete University and Hellenic Mediterranean University, a SWOT (strengths, weaknesses, opportunities, threats) survey was carried out, to evaluate the prospects of carob in human nutrition, in Crete. Results and conclusions: 1). Strengths: There exists a local production of carob for human consumption, based on international reports, and local-product reports. The data on products in the market (over 100 brands of carob food), indicates a sufficiency of carob materials offered in Crete. The variety of carob food products retailed in Crete indicates a strong demand-production-consumption trend. There is a stable number (core) of businesses that invest significantly (Creta carob, Cretan mills, etc.). The great majority of the relevant food stores (bakery, confectionary etc.) do offer carob products. The presence of carob products produced in Crete is strong on the internet (over 20 main professionally designed websites). The promotion of the carob food-products is based on their variety and on a few historical elements connected with the Cretan diet. 2). Weaknesses: The international prices for carob seed affect the sector; the seed had an international price of €20 per kg in 2021-22 and fell to €8 in 2022, causing losses to carob traders. The local producers do not sort the carobs they deliver for processing, causing 30-40% losses of the product in the industry. The occasional high price triggers the collection of degraded raw material; large losses may emerge due to the action of insects. There are many carob trees whose fruits are not collected, e.g. in Apokoronas, Chania. The nutritional and commercial value of the wild carob fruits is very low. Carob trees-production is recorded by Greek statistical services as "other cultures" in combination with prickly pear i.e., creating difficulties in retrieving data. The percentage of carob used for human nutrition, in contrast to animal feeding, is not known. The exact imports of carob are not closely monitored. We have no data on the recycling of carob by-products in Crete. 3). Opportunities: The development of a culture of respect for carob trade may improve professional relations in the sector. Monitoring carob market and connecting production with retailing-industry needs may allow better market-stability. Raw material evaluation procedures may be implemented to maintain carob value-chain. The state agricultural services may be further involved in carob-health protection. The education of farmers on carob cultivation/management, can improve the quality of the product. The selection of local productive varieties, may improve the sustainability of the culture. Connecting the consumption of carob with health-food products, may create added value in the sector. The presence and extent of wild carob threes in Crete, represents, potentially, a target for grafting. 4). Threats: The annual fluctuation of carob yield challenges the programming of local food industry activities. Carob is a forest species also - there is danger of wrong classification of crops as forest areas, where land ownership is not clear.

Keywords: human nutrition, carob food, SWOT analysis, crete, greece

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24016 Analysis of the Potential of Biomass Residues for Energy Production and Applications in New Materials

Authors: Sibele A. F. Leite, Bernno S. Leite, José Vicente H. D´Angelo, Ana Teresa P. Dell’Isola, Julio CéSar Souza

Abstract:

The generation of bioenergy is one of the oldest and simplest biomass applications and is one of the safest options for minimizing emissions of greenhouse gasses and replace the use of fossil fuels. In addition, the increasing development of technologies for energy biomass conversion parallel to the advancement of research in biotechnology and engineering has enabled new opportunities for exploitation of biomass. Agricultural residues offer great potential for energy use, and Brazil is in a prominent position in the production and export of agricultural products such as banana and rice. Despite the economic importance of the growth prospects of these activities and the increasing of the agricultural waste, they are rarely explored for energy and production of new materials. Brazil products almost 10.5 million tons/year of rice husk and 26.8 million tons/year of banana stem. Thereby, the aim of this study was to analysis the potential of biomass residues for energy production and applications in new materials. Rice husk (specify the type) and banana stem (specify the type) were characterized by physicochemical analyses using the following parameters: organic carbon, nitrogen (NTK), proximate analyses, FT-IR spectroscopy, thermogravimetric analyses (TG), calorific values and silica content. Rice husk and banana stem presented attractive superior calorific (from 11.5 to 13.7MJ/kg), and they may be compared to vegetal coal (21.25 MJ/kg). These results are due to the high organic matter content. According to the proximate analysis, biomass has high carbon content (fixed and volatile) and low moisture and ash content. In addition, data obtained by Walkley–Black method point out that most of the carbon present in the rice husk (50.5 wt%) and in banana stalk (35.5 wt%) should be understood as organic carbon (readily oxidizable). Organic matter was also detected by Kjeldahl method which gives the values of nitrogen (especially on the organic form) for both residues: 3.8 and 4.7 g/kg of rice husk and banana stem respectively. TG and DSC analyses support the previous results, as they can provide information about the thermal stability of the samples allowing a correlation between thermal behavior and chemical composition. According to the thermogravimetric curves, there were two main stages of mass-losses. The first and smaller one occurred below 100 °C, which was suitable for water losses and the second event occurred between 200 and 500 °C which indicates decomposition of the organic matter. At this broad peak, the main loss was between 250-350 °C, and it is because of sugar decomposition (components readily oxidizable). Above 350 °C, mass loss of the biomass may be associated with lignin decomposition. Spectroscopic characterization just provided qualitative information about the organic matter, but spectra have shown absorption bands around 1030 cm-1 which may be identified as species containing silicon. This result is expected for the rice husk and deserves further investigation to the stalk of banana, as it can bring a different perspective for this biomass residue.

Keywords: rice husk, banana stem, bioenergy, renewable feedstock

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24015 Exploring the Role of Data Mining in Crime Classification: A Systematic Literature Review

Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

Abstract:

This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

Procedia PDF Downloads 46
24014 Researching the Impact of Entrepreneurship on Economic Growth: Making Traditional Products Suitable for Our Age with E-Commerce

Authors: GüLcan Keskin

Abstract:

In a globalizing world, it is more difficult for developing counties to gain a competitive advantage compared to developed countries. Entrepreneurship is an important factor for economic growth in developing countries. Entrepreneurship is not only in the success of an entrepreneur’s own businesses, but also plays an important role in regional and national development. Entrepreneurship is the factor that triggers change for the country to accelerate the creation, dissemination, and implementation of new thoughts, leading to the emergence of industries that supports economic growth and development as it increases productivity by creating a competitive advantage. Therefore, it is an important factor for countries to develop economically and socially in a global world. As the know-how of the local products belongs to the region, it is a value that should not be lost. Having know-how provides a competitive advantage to the region. On the other hand, traditional products can be tailored to today’s trade understanding to appeal to more audiences. The primary aim of the study is to examine the interaction mechanism between traditional products and innovation in the context of related literature. The second aim of the study is to show the effect the traditional products to competitive advantage.

Keywords: e-commerce, economic growth, entrepreneurship, traditional products

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24013 Assessing Supply Chain Performance through Data Mining Techniques: A Case of Automotive Industry

Authors: Emin Gundogar, Burak Erkayman, Nusret Sazak

Abstract:

Providing effective management performance through the whole supply chain is critical issue and hard to applicate. The proper evaluation of integrated data may conclude with accurate information. Analysing the supply chain data through OLAP (On-Line Analytical Processing) technologies may provide multi-angle view of the work and consolidation. In this study, association rules and classification techniques are applied to measure the supply chain performance metrics of an automotive manufacturer in Turkey. Main criteria and important rules are determined. The comparison of the results of the algorithms is presented.

Keywords: supply chain performance, performance measurement, data mining, automotive

Procedia PDF Downloads 497
24012 Multimodal Data Fusion Techniques in Audiovisual Speech Recognition

Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

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In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

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24011 Potentials for Change in the MENA Region: A Socioeconomic Perspective

Authors: Shaira Karishma Sheriff, Zarinah Hamid

Abstract:

The Arab Spring, which commenced during the end of 2010 and accelerated during 2011, was caused primarily due to poverty, unemployment and a general recession in the Middle East and North African (MENA) region. The core motivation of this revolution could be said to be the need for political, economic and social reforms that the region desires to experience. Though GDP growth has been significant in the region, the income distribution mechanism in MENA countries has been ineffective. This results in low levels of education, substandard health care facilities, unemployment, and poverty. This paper argues that MENA countries have great potential for experiencing socioeconomic development by being less dependent on oil exports and enhancing their services sector through better education which would eventually lead to job creation. Furthermore, the region can encourage better trade and political integration by forming transparent and accountable governments. The notion of Nation-State needs to be addressed and the countries in the region need to look for ways to develop effective supra-national institutions for better political and economic integration that goes beyond geographical borders.

Keywords: political reforms, social reforms, economic development, nation-state, economic integration

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24010 Knowledge-Driven Decision Support System Based on Knowledge Warehouse and Data Mining by Improving Apriori Algorithm with Fuzzy Logic

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

Procedia PDF Downloads 316
24009 The Study of Dengue Fever Outbreak in Thailand Using Geospatial Techniques, Satellite Remote Sensing Data and Big Data

Authors: Tanapat Chongkamunkong

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The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

Procedia PDF Downloads 179
24008 Model of Optimal Centroids Approach for Multivariate Data Classification

Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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24007 Study of Inhibition of the End Effect Based on AR Model Predict of Combined Data Extension and Window Function

Authors: Pan Hongxia, Wang Zhenhua

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In this paper, the EMD decomposition in the process of endpoint effect adopted data based on AR model to predict the continuation and window function method of combining the two effective inhibition. Proven by simulation of the simulation signal obtained the ideal effect, then, apply this method to the gearbox test data is also achieved good effect in the process, for the analysis of the subsequent data processing to improve the calculation accuracy. In the end, under various working conditions for the gearbox fault diagnosis laid a good foundation.

Keywords: gearbox, fault diagnosis, ar model, end effect

Procedia PDF Downloads 353
24006 Exploring the Intersection Between the General Data Protection Regulation and the Artificial Intelligence Act

Authors: Maria Jędrzejczak, Patryk Pieniążek

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The European legal reality is on the eve of significant change. In European Union law, there is talk of a “fourth industrial revolution”, which is driven by massive data resources linked to powerful algorithms and powerful computing capacity. The above is closely linked to technological developments in the area of artificial intelligence, which has prompted an analysis covering both the legal environment as well as the economic and social impact, also from an ethical perspective. The discussion on the regulation of artificial intelligence is one of the most serious yet widely held at both European Union and Member State level. The literature expects legal solutions to guarantee security for fundamental rights, including privacy, in artificial intelligence systems. There is no doubt that personal data have been increasingly processed in recent years. It would be impossible for artificial intelligence to function without processing large amounts of data (both personal and non-personal). The main driving force behind the current development of artificial intelligence is advances in computing, but also the increasing availability of data. High-quality data are crucial to the effectiveness of many artificial intelligence systems, particularly when using techniques involving model training. The use of computers and artificial intelligence technology allows for an increase in the speed and efficiency of the actions taken, but also creates security risks for the data processed of an unprecedented magnitude. The proposed regulation in the field of artificial intelligence requires analysis in terms of its impact on the regulation on personal data protection. It is necessary to determine what the mutual relationship between these regulations is and what areas are particularly important in the personal data protection regulation for processing personal data in artificial intelligence systems. The adopted axis of considerations is a preliminary assessment of two issues: 1) what principles of data protection should be applied in particular during processing personal data in artificial intelligence systems, 2) what regulation on liability for personal data breaches is in such systems. The need to change the regulations regarding the rights and obligations of data subjects and entities processing personal data cannot be excluded. It is possible that changes will be required in the provisions regarding the assignment of liability for a breach of personal data protection processed in artificial intelligence systems. The research process in this case concerns the identification of areas in the field of personal data protection that are particularly important (and may require re-regulation) due to the introduction of the proposed legal regulation regarding artificial intelligence. The main question that the authors want to answer is how the European Union regulation against data protection breaches in artificial intelligence systems is shaping up. The answer to this question will include examples to illustrate the practical implications of these legal regulations.

Keywords: data protection law, personal data, AI law, personal data breach

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24005 A Method for Identifying Unusual Transactions in E-commerce Through Extended Data Flow Conformance Checking

Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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24004 A General Iterative Nonlinear Programming Method to Synthesize Heat Exchanger Network

Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

Abstract:

The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

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24003 Pharmaceutical Evaluation of Five Different Generic Brands of Prednisolone

Authors: Asma A. Ben Ahmed, Hajer M. Alborawy, Alaa A. Mashina, Pradeep K. Velautham, Abdulmonem Gobassa, Emhemmed Elgallal, Mohamed N. El Attug

Abstract:

Generic medicines are those where patent protection has expired, and which may be produced by manufacturers other than the innovator company. Use of generic medicines has been increasing in recent years, primarily as a cost saving measure in healthcare provision. Generic medicines are typically 20 – 90 % cheaper than originator equivalents. Physicians often continue to prescribe brand-name drugs to their patients even when less expensive pharmacologically equivalent generic drugs are available. Because generics are less expensive than their brand-name counterparts, the cost-savings to the patient is not the only factor that physicians consider when choosing between generic and brand-name drugs. Unfortunately Physicians in general and Libyan Physicians in particular tend to prescribe brand-name drugs, even without evidence of their therapeutic superiority, because neither they nor their insured patients bear these drugs’ increased cost with respect to generic substitutes. This study is to compare the quality of five different prednisolone tablets of the same strength from different companies under different trade names: Julphar, October pharma, Akums, Actavis, Pfizer compared them with pure prednisolone reference (BPCRS).

Keywords: quality control, pharmaceutical analysis, generic medicines, prednisolone

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24002 Advanced Analytical Competency Is Necessary for Strategic Leadership to Achieve High-Quality Decision-Making

Authors: Amal Mohammed Alqahatni

Abstract:

This paper is a non-empirical analysis of existing literature on digital leadership competency, data-driven organizations, and dealing with AI technology (big data). This paper will provide insights into the importance of developing the leader’s analytical skills and style to be more effective for high-quality decision-making in a data-driven organization and achieve creativity during the organization's transformation to be digitalized. Despite the enormous potential that big data has, there are not enough experts in the field. Many organizations faced an issue with leadership style, which was considered an obstacle to organizational improvement. It investigates the obstacles to leadership style in this context and the challenges leaders face in coaching and development. The leader's lack of analytical skill with AI technology, such as big data tools, was noticed, as was the lack of understanding of the value of that data, resulting in poor communication with others, especially in meetings when the decision should be made. By acknowledging the different dynamics of work competency and organizational structure and culture, organizations can make the necessary adjustments to best support their leaders. This paper reviews prior research studies and applies what is known to assist with current obstacles. This paper addresses how analytical leadership will assist in overcoming challenges in a data-driven organization's work environment.

Keywords: digital leadership, big data, leadership style, digital leadership challenge

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24001 A Simulation-Based Study of Dust Ingression into Microphone of Indoor Consumer Electronic Devices

Authors: Zhichao Song, Swanand Vaidya

Abstract:

Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

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24000 Analysis of Operating Speed on Four-Lane Divided Highways under Mixed Traffic Conditions

Authors: Chaitanya Varma, Arpan Mehar

Abstract:

The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

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23999 Accurate HLA Typing at High-Digit Resolution from NGS Data

Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang

Abstract:

Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.

Keywords: human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing

Procedia PDF Downloads 649
23998 Early Childhood Education: Teachers Ability to Assess

Authors: Ade Dwi Utami

Abstract:

Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

Procedia PDF Downloads 237
23997 Statistical Analysis for Overdispersed Medical Count Data

Authors: Y. N. Phang, E. F. Loh

Abstract:

Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling over-dispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling over-dispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling over-dispersed medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling over-dispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian, and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling over-dispersed medical count data when ZIP and ZINB are inadequate.

Keywords: zero inflated, inverse trinomial distribution, Poisson inverse Gaussian distribution, strict arcsine distribution, Pearson’s goodness of fit

Procedia PDF Downloads 523