Search results for: export trade data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25190

Search results for: export trade data

24440 Design of a Low Cost Motion Data Acquisition Setup for Mechatronic Systems

Authors: Baris Can Yalcin

Abstract:

Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

Procedia PDF Downloads 568
24439 Stochastic Pi Calculus in Financial Markets: An Alternate Approach to High Frequency Trading

Authors: Jerome Joshi

Abstract:

The paper presents the modelling of financial markets using the Stochastic Pi Calculus model. The Stochastic Pi Calculus model is mainly used for biological applications; however, the feature of this model promotes its use in financial markets, more prominently in high frequency trading. The trading system can be broadly classified into exchange, market makers or intermediary traders and fundamental traders. The exchange is where the action of the trade is executed, and the two types of traders act as market participants in the exchange. High frequency trading, with its complex networks and numerous market participants (intermediary and fundamental traders) poses a difficulty while modelling. It involves the participants to seek the advantage of complex trading algorithms and high execution speeds to carry out large volumes of trades. To earn profits from each trade, the trader must be at the top of the order book quite frequently by executing or processing multiple trades simultaneously. This would require highly automated systems as well as the right sentiment to outperform other traders. However, always being at the top of the book is also not best for the trader, since it was the reason for the outbreak of the ‘Hot – Potato Effect,’ which in turn demands for a better and more efficient model. The characteristics of the model should be such that it should be flexible and have diverse applications. Therefore, a model which has its application in a similar field characterized by such difficulty should be chosen. It should also be flexible in its simulation so that it can be further extended and adapted for future research as well as be equipped with certain tools so that it can be perfectly used in the field of finance. In this case, the Stochastic Pi Calculus model seems to be an ideal fit for financial applications, owing to its expertise in the field of biology. It is an extension of the original Pi Calculus model and acts as a solution and an alternative to the previously flawed algorithm, provided the application of this model is further extended. This model would focus on solving the problem which led to the ‘Flash Crash’ which is the ‘Hot –Potato Effect.’ The model consists of small sub-systems, which can be integrated to form a large system. It is designed in way such that the behavior of ‘noise traders’ is considered as a random process or noise in the system. While modelling, to get a better understanding of the problem, a broader picture is taken into consideration with the trader, the system, and the market participants. The paper goes on to explain trading in exchanges, types of traders, high frequency trading, ‘Flash Crash,’ ‘Hot-Potato Effect,’ evaluation of orders and time delay in further detail. For the future, there is a need to focus on the calibration of the module so that they would interact perfectly with other modules. This model, with its application extended, would provide a basis for researchers for further research in the field of finance and computing.

Keywords: concurrent computing, high frequency trading, financial markets, stochastic pi calculus

Procedia PDF Downloads 60
24438 Signal On-Off Ratio and Output Frequency Analysis of Semiconductor Electron-Interference Device

Authors: Tomotaka Aoki, Isao Tomita

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We examined the on-off ratio and frequency components of output signals from an electron-interference device made of GaAs/AlₓGa₁₋ₓAs by solving the time-dependent Schrödinger's equation on conducting electrons in the channel waveguide of the device. For electron-wave modulation, a periodic voltage of frequency f was applied to the channel. Furthermore, we examined the voltage-amplitude dependence of the signals in time and frequency domains and found that large applied voltage deformed the output-signal waveform and created additional side modes (frequencies) near the modulation frequency f and that there was a trade-off between on-off ratio and side-mode creation.

Keywords: electrical conduction, electron interference, frequency spectrum, on-off ratio

Procedia PDF Downloads 110
24437 Speed Characteristics of Mixed Traffic Flow on Urban Arterials

Authors: Ashish Dhamaniya, Satish Chandra

Abstract:

Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85th and 50th percentile speed to the difference in 50th and 15th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

Procedia PDF Downloads 401
24436 An Exploratory Analysis of Brisbane's Commuter Travel Patterns Using Smart Card Data

Authors: Ming Wei

Abstract:

Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

Procedia PDF Downloads 269
24435 Analysis of Supply Chain Risk Management Strategies: Case Study of Supply Chain Disruptions

Authors: Marcelo Dias Carvalho, Leticia Ishikawa

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Supply Chain Risk Management refers to a set of strategies used by companies to avoid supply chain disruption caused by damage at production facilities, natural disasters, capacity issues, inventory problems, incorrect forecasts, and delays. Many companies use the techniques of the Toyota Production System, which in a way goes against a better management of supply chain risks. This paper studies key events in some multinationals to analyze the trade-off between the best supply chain risk management techniques and management policies designed to create lean enterprises. The result of a good balance of these actions is the reduction of losses, increased customer trust in the company and better preparedness to face the general risks of a supply chain.

Keywords: just in time, lean manufacturing, supply chain disruptions, supply chain management

Procedia PDF Downloads 324
24434 Pattern Recognition Using Feature Based Die-Map Clustering in the Semiconductor Manufacturing Process

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

Procedia PDF Downloads 385
24433 Spatial Integrity of Seismic Data for Oil and Gas Exploration

Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

Procedia PDF Downloads 202
24432 Research and Innovation Centre

Authors: Krasimir Ivanov, Tonyo Tonev, Nguyen Nguyen, Alexander Peltekov, Anyo Mitkov

Abstract:

Maize is among the most economically important crops and at the same time one of the most sensitive to soil deficiency in zinc. In this paper, the impact of the foliar zinc application in the form of zinc hydroxy nitrate suspension on the micro and macro elements partitioning in maize leaves and grain was studied during spring maize season, 2017. The impact of the foliar zinc fertilization on the grain yield and quality was estimated too. The experiment was performed by the randomized block design with 8 variants in 3 replications. Seven suspension solutions whit different Zn concentration were used, including ZnO suspension and zinc hydroxyl nitrate alone or nixed with other nutrients. Fertilization and irrigation were the same for all variants. The Zn content and the content of selected micro (Cu, Fe) and macro (Ca, Mg, P and K) elements in maize leaves were determined two weeks after the first spraying (5-6 sheets), two weeks after the second spraying (9-10 sheets) and after harvesting. It was concluded that the synthesized zinc hydroxy nitrate demonstrates potential as the long-term foliar fertilizer. A significant (p < 0.05) effect of zinc accumulation in maize leaves by foliar zinc application during the first growth stage was found, followed by its reutilization to other plants organs during the second growth stage. Significant export of Cu, P, and K from lower and middle leaves was observed. The content of Ca and Mg remains constant in the whole longevity period, while the content of Fe decreases sharply.

Keywords: foliar fertilization, zinc hydroxy nitrate, maize, zinc

Procedia PDF Downloads 143
24431 Labor Productivity and Organization Performance in Specialty Trade Construction: The Moderating Effect of Safety

Authors: Shalini Priyadarshini

Abstract:

The notion of performance measurement has held great appeal for the industry and research communities alike. This idea is also true for the construction sector, and some propose that performance measurement and productivity analysis are two separate management functions, where productivity is a subset of performance, the latter requiring comprehensive analysis of comparable factors. Labor productivity is considered one of the best indicators of production efficiency. The construction industry continues to account for a disproportionate share of injuries and illnesses despite adopting several technological and organizational interventions that promote worker safety. Specialty trades contractors typically complete a large fraction of work on any construction project, but insufficient body of work exists that address subcontractor safety and productivity issues. Literature review has revealed the possibility of a relation between productivity, safety and other factors and their links to project, organizational, task and industry performance. This research posits that there is an association between productivity and performance at project as well as organizational levels in the construction industry. Moreover, prior exploration of the importance of safety within the performance-productivity framework has been anecdotal at best. Using structured questionnaire survey and organization- and project level data, this study, which is a combination of cross-sectional and longitudinal research designs, addresses the identified research gap and models the relationship between productivity, safety, and performance with a focus on specialty trades in the construction sector. Statistical analysis is used to establish a correlation between the variables of interest. This research identifies the need for developing and maintaining productivity and safety logs for smaller businesses. Future studies can design and develop research to establish causal relationships between these variables.

Keywords: construction, safety, productivity, performance, specialty trades

Procedia PDF Downloads 262
24430 Single-Cell Visualization with Minimum Volume Embedding

Authors: Zhenqiu Liu

Abstract:

Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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24429 Cloud Data Security Using Map/Reduce Implementation of Secret Sharing Schemes

Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

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Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

Procedia PDF Downloads 284
24428 Analyzing the Support to Fisheries in the European Union: Modelling Budgetary Transfers in Wild Fisheries

Authors: Laura Angulo, Petra Salamon, Martin Banse, Frederic Storkamp

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Fisheries subsidies are focus on reduce management costs or deliver income benefits to fishers. In 2015, total fishery budgetary transfers in 31 OECD countries represented 35% of their total landing value. However, subsidies to fishing have adverse effects on trade and it has been claimed that they may contribute directly to overfishing. Therefore, this paper analyses to what extend fisheries subsidies may 1) influence capture production facing quotas and 2) affect price dynamics. The study uses the fish module in AGMEMOD (Agriculture Member States Modelling, details see Chantreuil et al. (2012)) which covers eight fish categories (cephalopods; crustaceans; demersal marine fish; pelagic marine fish; molluscs excl. cephalopods; other marine finfish species; freshwater and diadromous fish) for EU member states and other selected countries developed under the SUCCESS project. This model incorporates transfer payments directly linked to fisheries operational costs. As aquaculture and wild fishery are not included within the WTO Agreement on Agriculture, data on fisheries subsidies is obtained from the OECD Fisheries Support Estimates (FSE) database, which provides statistics on budgetary transfers to the fisheries sector. Since support has been moving from budgetary transfers to General Service Support Estimate the last years, subsidies in capture production may not present substantial effects. Nevertheless, they would still show the impact across countries and fish categories within the European Union.

Keywords: AGMEMOD, budgetary transfers, EU Member States, fish model, fisheries support estimate

Procedia PDF Downloads 227
24427 A Review on Trends in Measurement of Port Performance

Authors: J. Racedo, J. Torres

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Globalization has led to a worldwide competition for participation in markets of goods and productive factors, with significant effects on transports requirements. The port industry has not been an exception to this event, in fact, it has received increasing attention in recent years due to its crucial role on international trade. Because of this, the measurement of port performance has become an important issue in transport policy. Port performance and port efficiency has been widely studied in the last decades, resulting in noteworthy contributions to improving the industry competitiveness. In this paper, we aim to present a review of the literature on port performance and the relation between this concept and transport policies. This study has the objective to describe the approaches that have been developed in recent years, and especially those that include the modeling of public policies. Finally, we highlight existing gaps in this field, as well as possible directions for future research.

Keywords: port performance, port efficiency, transport, policy

Procedia PDF Downloads 313
24426 A Modular Framework for Enabling Analysis for Educators with Different Levels of Data Mining Skills

Authors: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

Procedia PDF Downloads 308
24425 The Impact of Vertical Product Differentiation on Exchange Rate Pass-Through: An Empirical Investigation of IRON and Steel Industry between Thailand and Vietnam

Authors: Santi Termprasertsakul, Jakkrich Jearviriyaboonya

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This paper studies the market power and pricing behavior of products in iron and steel industry by investigating the impact of vertical product differentiation (VPD) on exchange rate pass-through (ERPT). Vietnam has become one of the major trading partners of Thailand since 2017. The iron and steel export value to Vietnam is more than $300 million a year. Particularly, the average growth rate of importing iron and steel is approximately 30% per year. The VPD is applied to analyze the quality difference of iron and steel between Thailand and Vietnam. The 20 products in iron and steel industry are investigated. The monthly pricing behavior of Harmonized Commodity Description and Coding System 4-digit products is observed from 2010 to 2019. The Nonlinear Autoregressive Distributed Lag is also used to analyze the asymmetry of ERPT in this paper. The empirical results basically reveal an incomplete pass-through between Thai Baht and Vietnamese Dong. The ERPT also varies with the degree of VPD. The product with higher VPD, indicating higher unit values, has higher ERPT. This result suggests the higher market power of the Thai iron and steel industry. In addition, the asymmetry of ERPT exists.

Keywords: exchange rate pass-through, iron and steel industry, pricing behavior, vertical product differentiation

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24424 Using Audit Tools to Maintain Data Quality for ACC/NCDR PCI Registry Abstraction

Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

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Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

Procedia PDF Downloads 88
24423 Artificial Intelligence Based Comparative Analysis for Supplier Selection in Multi-Echelon Automotive Supply Chains via GEP and ANN Models

Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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24422 The Moderation Effect of Financial Distress on the Relationship Between Market Power and Earnings Management of Firms

Authors: Shazia Ali, Yves Mard, Éric Severin

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To the best of our knowledge, this is the first study to have analyzed the impact of a) firm-specific product-market power and b) industry competition on earnings management behavior of European firms in distress versus healthy years while controlling for firm-level characteristics. We predicted a significant relationship between firms’ product market power and earnings management tools and their trade-off under the moderation effect of financial distress. We found that the firm-level market power hereinafter referred to as MP (proxied by the industry-adjusted Lerner Index) is positively associated with both real and accrual earnings management. However, MP is associated with a higher level of real earnings management compared to accrual earnings management in distress years compared to healthy years. On the other hand, industry product market power (representing low competition and proxied by the inverse of the total number of firms in an industry hereinafter referred to as NUMB) and firms product market power (proxied by firm market share hereinafter referred to as MS) are associated with lower inflationary accruals and higher deflationary accruals respectively. On the other hand, they are found to be linked with higher real earnings management in distress versus healthy years. When we divided the sample into small and big firms based on their respective industry-year median total assets, we found that all three measures of industry competition (Industry Median Lerner Index (hereinafter referred to as IMLI), NUMB, and Herfindahl–Hirschman Index (hereinafter referred to as HHI) indicate that small firms in low-competitive industries in financial distress are more likely to inflate their earnings through discretionary accruals. While big firms in this situation are more likely to lower the use of both inflationary and deflationary discretionary accruals as indicated by IMLI and HHI and trade-off accruals earnings management for real earnings management as indicated by NUMB. Moreover, IMLI and HHI did not show any interesting results when we divided the sample based on the firm Lerner Index/Market Power. However, the distressed firms with high market power (MP>industry median) are found to engage in income-decreasing discretionary accruals in low-competitive industries (high NUMB). Whereas firms with low market power in the same industry use downward discretionary accruals but inflate income using real activities (abnCFO). Our findings are robust across alternate measures of discretionary accruals and financial distress, such as the Altman Z-Score. The finding of the study is valuable for accounting standard setters, competition authorities, policymakers, and investors alike to help in informed decision-making.

Keywords: financial distress, earnings management, market competition

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24421 Negotiating Increased Food Production with African Indigenous Agricultural Knowledge: The Ugandan Case

Authors: Harriet Najjemba, Simon Peter Rutabajuuka, Deo Katono Nzarwa

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Scientific agricultural knowledge was introduced in Africa, including Uganda, during colonial rule. While this form of knowledge was introduced as part of Western scientific canon, African indigenous knowledge was not destroyed and has remained vital in food production. Modern scientific methods were devoted to export crops while food crop production was left to Africans who continued to use indigenous knowledge. Today, indigenous agricultural knowledge still provides farming skills and practices, more than a century since modern scientific agricultural knowledge was introduced in Uganda. It is evident that there is need to promote the still useful and more accessible indigenous agricultural practices in order to sustain increased food production. It is also important to have a tailor made agricultural knowledge system that combines practical indigenous practices with financially viable western scientific agricultural practices for sustained food production. The proposed paper will explain why the African indigenous agricultural knowledge has persisted and survived for over a century after colonial introduction of western scientific agricultural knowledge. The paper draws on research findings for a PhD study at Makerere University, Uganda. The study uses both written and oral sources, including colonial and postcolonial archival documents, and interviews. It critiques the parameters within which Western farming methods were introduced to African farmers.

Keywords: food production, food shortage, indigenous agricultural knowledge, western scientific agricultural practices

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24420 The Recognition of Exclusive Choice of Court Agreements: United Arab Emirates Perspective and the 2005 Hague Convention on Choice of Court Agreements

Authors: Hasan Alrashid

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The 2005 Hague Convention seeks to ensure legal certainty and predictability between parties in international business transactions. It harmonies exclusive choice of court agreements at the international level between parties to commercial transactions and to govern the recognition and enforcement of judgments resulting from proceedings based on such agreements to promote international trade and investment. Although the choice of court agreements is significant in international business transactions, the United Arab Emirates refuse to recognise it by Article 24 of the Federal Law No. 11 of 1992 of the Civil Procedure Code. A review of judicial judgments in United Arab Emirates up to the present day has revealed that several cases appeared before the Court in different states of United Arab Emirates regarding the recognition of exclusive choice of court agreements. In all the cases, the courts regarded the exclusive choice of court agreements as a direct assault on state authority and sovereignty and refused categorically to recognize choice of court agreements by refusing to stay proceedings in favor of the foreign chosen court. This has created uncertainty and unpredictability in international business transaction in the United Arab Emirates. In June 2011, the first Gulf Judicial Seminar on Cross-Frontier Legal Cooperation in Civil and Commercial Matters was held in Doha, Qatar. The Permanent Bureau of the Hague Conference attended the conference and invited the states of the Gulf Cooperation Council (GCC) namely, The United Arab Emirates, Bahrain, Saudi Arabia, Oman, Qatar and Kuwait to adopt some of the Hague Conventions, one of which was the Hague Convention on Choice of Court Agreements. One of the recommendations of the conference was that the GCC states should research ‘the benefits of predictability and legal certainty provided by the 2005 Convention on Choice of Court Agreements and its resulting advantages for cross-border trade and investment’ for possible adoption of the Hague Convention. Up to today, no further step has been taken by the any of the GCC states to adapt the Hague Convention nor did they conduct research on the benefits of predictability and legal certainty in international business transactions. This paper will argue that the approach regarding the recognition of choice of court agreements in United Arab Emirates states can be improved in order to help the parties in international business transactions avoid parallel litigation and ensure legal certainty and predictability. The focus will be the uncertainty and gaps regarding the choice of court agreements in the United Arab Emirates states. The Hague Convention on choice of court agreements and the importance of harmonisation of the rules of choice of court agreements at international level will also be discussed. Finally, The feasibility and desirability of recognizing choice of court agreements in United Arab Emirates legal system by becoming a party to the Hague Convention will be evaluated.

Keywords: choice of court agreements, party autonomy, public authority, sovereignty

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24419 Increasing the Apparent Time Resolution of Tc-99m Diethylenetriamine Pentaacetic Acid Galactosyl Human Serum Albumin Dynamic SPECT by Use of an 180-Degree Interpolation Method

Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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24418 Identifying the Determinants of Compliance with Maritime Environmental Legislation in the North and Baltic Sea Area: A Model Developed from Exploratory Qualitative Data Collection

Authors: Thea Freese, Michael Gille, Andrew Hursthouse, John Struthers

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Ship operators on the North and Baltic Sea have been experiencing increased political interest in marine environmental protection and cleaner vessel operations. Stricter legislation on SO2 and NOx emissions, ballast water management and other measures of protection are currently being phased in or will come into force in the coming years. These measures benefit the health of the marine environment, while increasing company’s operational costs. In times of excess shipping capacity and linked consolidation in the industry non-compliance with environmental rules is one way companies might hope to stay competitive with both intra- and inter-modal trade. Around 5-15% of industry participants are believed to neglect laws on vessel-source pollution willingly or unwillingly. Exploratory in-depth interviews conducted with 12 experts from various stakeholder groups informed the researchers about variables influencing compliance levels, including awareness and apprehension, willingness to comply, ability to comply and effectiveness of controls. Semi-structured expert interviews were evaluated using qualitative content analysis. A model of determinants of compliance was developed and is presented here. While most vessel operators endeavour to achieve full compliance with environmental rules, a lack of availability of technical solutions, expediency of implementation and operation and economic feasibility might prove a hindrance. Ineffective control systems on the other hand foster willing non-compliance. With respect to motivations, lacking time, lacking financials and the absence of commercial advantages decrease compliance levels. These and other variables were inductively developed from qualitative data and integrated into a model on environmental compliance. The outcomes presented here form part of a wider research project on economic effects of maritime environmental legislation. Research on determinants of compliance might inform policy-makers about actual behavioural effects of shipping companies and might further the development of a comprehensive legal system for environmental protection.

Keywords: compliance, marine environmental protection, exploratory qualitative research study, clean vessel operations, North and Baltic Sea area

Procedia PDF Downloads 367
24417 Genetic Data of Deceased People: Solving the Gordian Knot

Authors: Inigo de Miguel Beriain

Abstract:

Genetic data of deceased persons are of great interest for both biomedical research and clinical use. This is due to several reasons. On the one hand, many of our diseases have a genetic component; on the other hand, we share genes with a good part of our biological family. Therefore, it would be possible to improve our response considerably to these pathologies if we could use these data. Unfortunately, at the present moment, the status of data on the deceased is far from being satisfactorily resolved by the EU data protection regulation. Indeed, the General Data Protection Regulation has explicitly excluded these data from the category of personal data. This decision has given rise to a fragmented legal framework on this issue. Consequently, each EU member state offers very different solutions. For instance, Denmark considers the data as personal data of the deceased person for a set period of time while some others, such as Spain, do not consider this data as such, but have introduced some specifically focused regulations on this type of data and their access by relatives. This is an extremely dysfunctional scenario from multiple angles, not least of which is scientific cooperation at the EU level. This contribution attempts to outline a solution to this dilemma through an alternative proposal. Its main hypothesis is that, in reality, health data are, in a sense, a rara avis within data in general because they do not refer to one person but to several. Hence, it is possible to think that all of them can be considered data subjects (although not all of them can exercise the corresponding rights in the same way). When the person from whom the data were obtained dies, the data remain as personal data of his or her biological relatives. Hence, the general regime provided for in the GDPR may apply to them. As these are personal data, we could go back to thinking in terms of a general prohibition of data processing, with the exceptions provided for in Article 9.2 and on the legal bases included in Article 6. This may be complicated in practice, given that, since we are dealing with data that refer to several data subjects, it may be complex to refer to some of these bases, such as consent. Furthermore, there are theoretical arguments that may oppose this hypothesis. In this contribution, it is shown, however, that none of these objections is of sufficient substance to delegitimize the argument exposed. Therefore, the conclusion of this contribution is that we can indeed build a general framework on the processing of personal data of deceased persons in the context of the GDPR. This would constitute a considerable improvement over the current regulatory framework, although it is true that some clarifications will be necessary for its practical application.

Keywords: collective data conceptual issues, data from deceased people, genetic data protection issues, GDPR and deceased people

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24416 Steps towards the Development of National Health Data Standards in Developing Countries

Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian Murray

Abstract:

The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: interoperabilty, medical data exchange, health data standards, case study, Saudi Arabia

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24415 A Proposal for U-City (Smart City) Service Method Using Real-Time Digital Map

Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

Abstract:

Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City

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24414 A Two Stage Stochastic Mathematical Model for the Tramp Ship Routing with Time Windows Problem

Authors: Amin Jamili

Abstract:

Nowadays, the majority of international trade in goods is carried by sea, and especially by ships deployed in the industrial and tramp segments. This paper addresses routing the tramp ships and determining the schedules including the arrival times to the ports, berthing times at the ports, and the departure times in an operational planning level. In the operational planning level, the weather can be almost exactly forecasted, however in some routes some uncertainties may remain. In this paper, the voyaging times between some of the ports are considered to be uncertain. To that end, a two-stage stochastic mathematical model is proposed. Moreover, a case study is tested with the presented model. The computational results show that this mathematical model is promising and can represent acceptable solutions.

Keywords: routing, scheduling, tram ships, two stage stochastic model, uncertainty

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24413 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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24412 Identifying Model to Predict Deterioration of Water Mains Using Robust Analysis

Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

Abstract:

In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

Procedia PDF Downloads 725
24411 Automated Testing to Detect Instance Data Loss in Android Applications

Authors: Anusha Konduru, Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

Abstract:

Mobile applications are increasing in a significant amount, each to address the requirements of many users. However, the quick developments and enhancements are resulting in many underlying defects. Android apps create and handle a large variety of 'instance' data that has to persist across runs, such as the current navigation route, workout results, antivirus settings, or game state. Due to the nature of Android, an app can be paused, sent into the background, or killed at any time. If the instance data is not saved and restored between runs, in addition to data loss, partially-saved or corrupted data can crash the app upon resume or restart. However, it is difficult for the programmer to manually test this issue for all the activities. This results in the issue of data loss that the data entered by the user are not saved when there is any interruption. This issue can degrade user experience because the user needs to reenter the information each time there is an interruption. Automated testing to detect such data loss is important to improve the user experience. This research proposes a tool, DroidDL, a data loss detector for Android, which detects the instance data loss from a given android application. We have tested 395 applications and found 12 applications with the issue of data loss. This approach is proved highly accurate and reliable to find the apps with this defect, which can be used by android developers to avoid such errors.

Keywords: Android, automated testing, activity, data loss

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