Search results for: Black-Scholes model

Authors: Yiseyon Hosu, Joseph Akande

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Wheat is one of the most important staple food grains of human for centuries and is largely consumed in South Africa. It has a special place in the South African economy because of its significance in food security, trade, and industry. This paper modelled and forecast the production and consumption of wheat in South Africa in the time covid-19 and the ongoing Russia-Ukraine war by using annual time series data from 1940–2021 based on the ARIMA models. Both the averaging forecast and selected models forecast indicate that there is the possibility of an increase with respect to production. The minimum and maximum growth in production is projected to be between 3million and 10 million tons, respectively. However, the model also forecast a possibility of depression with respect to consumption in South Africa. Although Covid-19 and the war between Ukraine and Russia, two major producers and exporters of global wheat, are having an effect on the volatility of the prices currently, the wheat production in South African is expected to increase and meat the consumption demand and provided an opportunity for increase export with respect to domestic consumption. The forecasting of production and consumption behaviours of major crops play an important role towards food and nutrition security, these findings can assist policymakers and will provide them with insights into the production and pricing policy of wheat in South Africa.

Keywords: ARIMA, food security, price volatility, staple food, South Africa

Procedia PDF Downloads 105

Authors: Daniyar Seitenov, Nazim Mir-Nasiri

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Optimization of horizontal axis semi-exposed wind turbine has been performed using a shield protection that automatically protects the generator shaft at extreme wind speeds from over speeding, mechanical damage and continues generating electricity during the high wind speed conditions. A semi-exposed to wind generator has been designed and its structure has been described in this paper. The simplified point-force dynamic load model on the blades has been derived for normal and extreme wind conditions with and without shield involvement. Numerical simulation has been conducted at different values of wind speed to study the efficiency of shield application. The obtained results show that the maximum power generated by the wind turbine with shield does not exceed approximately the rated value of the generator, where shield serves as an automatic break for extreme wind speed values of 15 m/sec and above. Meantime the wind turbine without shield produced a power that is much larger than the rated value. The optimized horizontal axis semi-exposed wind turbine with shield protection is suitable for low and medium power generation when installed on the roofs of high rise buildings for harvesting wind energy. Wind shield works automatically with no power consumption. The structure of the generator with the protection, math simulation of kinematics and dynamics of power generation has been described in details in this paper.

Keywords: renewable energy, wind turbine, wind turbine optimization, high wind speed

Procedia PDF Downloads 180

Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

Procedia PDF Downloads 125

Authors: Salinthip Thipayang, Achara Chandrachai, Rath Pichyangkura, Sukree Sinthupinyo

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Most of the well-known frameworks and tools to measure and compare organisational innovation of the public or government agencies have been designed and used in the developed economies such as the EU, Nordic Region, Australia, and South Korea. This project is one of the very first attempts to develop a measurement tool to adequately measure the organisational (administrative) innovation of the government agencies in the developing economies in ASEAN. New measurement framework with the components including the intra and international collaborations of these government agencies to other private, public and academic sectors were added to the proposed measurement framework. Questionnaires and in-depth interviews with the experts and the middle to top executives of the participating public agencies in the ASEAN member states were conducted to determine the suitability and develop the indicators that should be included in the measurement model. The results showed that intra and international collaborations of these government organisations to other agencies in the public, private and academic sectors can lead to new changes and greatly impact the ways in which these government agencies in the ASEAN STI ecosystem are operated and administered. Government organisations in less developing countries in ASEAN are ready and willing to learn from their counterparts in other more advanced countries and adjust their internal management to be more innovative and to better handle international collaborative projects and commitments.

Keywords: organisational innovation, administrative innovation, government agencies, public agencies, ASEAN science technology and innovation ecosystem, international collaborations

Procedia PDF Downloads 387

Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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Authors: Oludare Olupemi Ezekiel

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This research examines the rhythmic structure of Sakara music by tracing its roots and analyzing the various rhythmic patterns of this neo-traditional genre, as well as the contributions of the major exponents and contemporary practitioners, using these as a model for understanding and establishing African rhythms. Biography of the major exponents and contemporary practitioners, interviews and participant observational methods were used to elicit information. Samples of the genre which were chosen at random were transcribed, notated and analyzed for academic use and documentation. The research affirmed that rhythms such as the Hemiola, Cross-rhythm, Clave or Bell rhythm, Percussive, Speech and Melodic rhythm and other relevant rhythmic theories were prevalent and applicable to Sakara music, while making important contributions to musical scholarship through its analysis of the music. The analysis and discussions carried out in the research pointed towards a conclusion that the Yoruba musicians are guided by some preconceptions and sound musical considerations in making their rhythmic patterns, used as compositional techniques and not mere incidental occurrence. These rhythmic patterns, with its consequential socio-cultural connotations, enhance musical values and national identity in Nigeria. The study concludes by recommending that musicologists need to carry out more research into this and other neo-traditional genres in order to advance the globalisation of African music.

Keywords: compositional techniques, globalisation, identity, neo-traditional, rhythmic theory, Sakara music

Procedia PDF Downloads 447

Authors: Sarayu Agarwal

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This paper aims to teach English (secondary language) by bridging the understanding between the Regional language (primary language) and the English Language (secondary language). Here primary language is the one a person has learned from birth or within the critical period, while secondary language would be any other language one learns or speaks. The paper also focuses on evolving old teaching methods to a contemporary participatory model of learning and teaching. Pilot studies were conducted to gauge an understanding of student’s knowledge of the English language. Teachers and students were interviewed and their academic curriculum was assessed as a part of the initial study. Extensive literature study and design thinking principles were used to devise a solution to the problem. The objective is met using a holistic learning kit/card game to teach children word recognition, word pronunciation, word spelling and writing words. Implication of the paper is a noticeable improvement in the understanding and grasping of English language. With increasing usage and applicability of English as a second language (ESL) world over, the paper becomes relevant due to its easy replicability to any other primary or secondary language. Future scope of this paper would be transforming the idea of participatory learning into self-regulated learning methods. With the upcoming govt. learning centres in rural areas and provision of smart devices such as tablets, the development of the card games into digital applications seems very feasible.

Keywords: English as a second language, vocabulary-building card games, learning through gamification, rural education

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Authors: Erdem Meriç

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Measuring total temperature of air flow accurately is a very important requirement in the development phases of many industrial products, including gas turbines and rockets. Thermocouples are very practical devices to measure temperature in such cases, but in high speed and high temperature flows, the temperature of thermocouple junction may deviate considerably from real flow total temperature due to the effects of heat transfer mechanisms of convection, conduction, and radiation. To avoid errors in total temperature measurement, special probe designs which are experimentally characterized are used. In this study, a validation case which is an experimental characterization of a specific class of total temperature probes is selected from the literature to develop a numerical conjugate heat transfer analysis methodology to study the total temperature probe flow field and solid temperature distribution. Validated conjugate heat transfer methodology is used to investigate flow structures inside and around the probe and effects of probe design parameters like the ratio between inlet and outlet hole areas and prob tip geometry on measurement accuracy. Lastly, a thermal model is constructed to account for errors in total temperature measurement for a specific class of probes in different operating conditions. Outcomes of this work can guide experimentalists to design a very accurate total temperature probe and quantify the possible error for their specific case.

Keywords: conjugate heat transfer, recovery factor, thermocouples, total temperature probes

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: Yun-Ru Tsai, Jo-Hui Lin

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The cultural interactions between tourists and destination communities have received increased attention. Tourists play an important role in constructing a rewarding intercultural experience and cultural understanding. Cultural literacy is the ability for tourists to negotiate different cultures, this research aimed to develop a measurement of Tourist Cultural Literacy (TCL), the result provides a theoretical framework to assess how tourists interact with different cultural destinations. A pilot qualitative research was conducted in order to generate the initial items. In this study, the procedure of developing the TCL scale was divided into two parts. First, an exploratory factor analysis was conducted, a 25-item TCL scale was developed and six factors were identified: cultural sensitivity, appreciation of the culture, respect for the culture, knowledge of the culture, participate in the culture, and empathy for the culture. Second, confirmatory factor analyses and structural equation modeling were employed, the six-factor model was verified, and was proven to have good fit, reliability, convergent validity, discriminant validity, and criterion-related validity. The study provides managerial implications for tourist management and education, the popularization of TCL might increase the respect and understanding between tourists and local societies as well as decrease the cultural shocks and negative social-cultural impacts derived from tourism activities, thereby reducing the maintenance cost of management and allowing tourists to obtain a better cultural experience. Future research suggestions are also provided.

Keywords: cultural literacy, cultural tourism, scale development, tourism contact

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Authors: Masih Moore, Saeed Ziaei-Rad

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In this study, the stability characteristics of a bi-stable composite plate with different asymmetric composition are considered. The interest in bi-stable structures comes from their ability that these structures can have two different stable equilibrium configurations to define a discrete set of stable shapes. The structures can easily change the first stable shape to the second one by a simple snap action. The main purpose of the current research is to consider the effect of including resin layers on the stability characteristics of bi-stable laminates. To this end and In order to determine the magnitude of the loads that are responsible for snap through and snap back phenomena between two stable shapes of the laminate, a non-linear finite element method (FEM) is utilized. An experimental investigation was also carried out to study the critical loads that caused snapping between two different stable shapes. Several specimens were manufactured from T300/5208 graphite-epoxy with [0/90]T, [-30/60]T, [-20/70]T asymmetric stacking sequence. In order to create an accurate finite element model, different thickness of resin layers created during the manufacturing process of the laminate was measured and taken into account. The geometry of each lamina and the resin layers was characterized by optical microscopy from different locations of the laminates thickness. The exact thickness of each lamina and the resin layer in all specimens with [0/90]T,[-30/60]T, [-20/70]T stacking sequence were determined by using image processing technique.

Keywords: bi-stable laminates, finite element method, graphite-epoxy plate, snap behavior

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Authors: Nima Mahmoudi, Hamzeh Khazaei

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Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

Procedia PDF Downloads 181

Authors: Yansong Gao, Damith C.Ranasinghe, Siad F. Al-Sarawi, Omid Kavehei, Derek Abbott

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Passive crossbar arrays is in principle the simplest functional electrical circuit, together with memristive device in cross-point, holding great promise in future high-density, non-volatile memories. However, the greatest problem of crossbar array is the sneak path current. In this paper, we investigate one type of memristive device with intrinsic rectification behavior to address the sneak path currents. Firstly, a SPICE behavior model written in Verilog-A language of the memristive device is presented to fit experimental data published in literature. Next, systematic performance simulations including read margin and power consumption of crossbar array, which uses the self-rectifying memristive device as storage element at cross-point, with respect to different crossbar sizes, interconnect resistance, ratio of HRS/LRS (High Resistance State/ Low Resistance State), rectification ratio and different read schemes are conducted. Subsequently, Trade-offs among reading margin, power consumption, and reading schemes are analyzed to provide guidelines for circuit design. Finally, performance comparison between the memristive device with/without intrinsic rectification behavior is given to show the worthiness of this intrinsic rectification behavior.

Keywords: memristive device, memristor, crossbar, RRAM, read margin, power consumption

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Authors: Ahmed M. Jihad

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The paper presents the concept of sustainable development, and the role of geographic techniques in the design, planning and presentation of maps of smart cities with geographical vision, and the identification of programs and tools, and models of maps of Arab cities, is the problem of research in how to apply, process and experience these programs? What is the role of geographic techniques in planning and mapping the optimal place for these cities? The paper proposes an addition to the designs of Iraqi cities, as it can be developed in the future to serve as a model for interactive smart cities by developing its services. The importance of this paper stems from the concept of sustainable development dynamic which has become a method of development imposed by the present era in rapid development to achieve social balance and specialized programs in draw paper argues that ensuring sustainable development is achieved through the use of information technology. The paper will follow the theoretical presentation of the importance of the concept of development, design tools and programs. The paper follows the method of analysis of modern systems (System Analysis Approach) through the latest programs will provide results can be said that the new Iraqi cities can be developed with smart technologies, like some of the Arab and European cities that were newly created through the introduction of international investment, and therefore Plans can be made to select the best programs in manufacturing and producing maps and smart cities in the future.

Keywords: geographic techniques, planning the cities, smart cities, sustainable development

Procedia PDF Downloads 211

Authors: Umar Shehu Umar

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Contract farming is a viable strategy agribusinesses rely on to strengthen vertical coordination. However, low contract compliance remains a significant setback to agribusinesses' contract performance. The present study aims to understand what drives smallholder farmers’ contract compliance behaviour. Qualitative information was collected through Focus Group Discussions to enrich the design of the survey questionnaire administered on a sample of 300 randomly selected farmers contracted by the Dangote Tomato Processing Plant (DTPP) in four regions of northern Nigeria. Novel transaction level data of tomato sales covering one season were collected in addition to socio-economic information of the sampled farmers. Binary logistic model results revealed that open fresh market tomato prices and payment delays negatively affect farmers' compliance behaviour while quantity harvested, education level and input provision correlated positively with compliance. The study suggests that contract compliance will increase if contracting firms devise a reliable and timely payment plan (e.g., digital payment), continue input and service provisions (e.g., improved seeds, extension services) and incentives (e.g., loyalty rewards, bonuses) in the contract.

Keywords: contract farming, compliance, farmers and processors., smallholder

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Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

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Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

Procedia PDF Downloads 668

Authors: Ivy Jumao-As, Randy Lupango, Clifford Villaflores, Marites Khanser

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Alongside inadequate implementation of ecotourism standards and other pressing issues on sustainable development is the lack of business plans and formal business structures of various ecotourism sites in the Central Visayas, Philippines, and other parts of the country. Addressing these issues plays a key role to boost ecotourism which is a sustainability tool to the country’s economic development. A three-phase research is designed to investigate the green business practices of selected ecotourism sites in the region in order to propose a business model for ecotourism destinations in the region and outside. This paper reports the initial phase of the study which described the sites’ profile as well as operators of the following selected destinations: Cebu City Protected Landscape and Olango Island Wildlife Bird Sanctuary in Cebu, Rajah Sikatuna Protected Landscape in Bohol. Interview, Self-Administered Questionnaire with key informants and Data Mining were employed in the data collection. Findings highlighted similarities and differences in terms of eco-tourism products, type and number of visitors, manpower composition, cultural and natural resources, complementary services and products, awards and accreditation, peak and off peak seasons, among others. Recommendations based from common issues initially identified in this study are also highlighted.

Keywords: ecotourism, ecotourism sites, green business, sustainability

Procedia PDF Downloads 276

Authors: Hsu Kuo-Wei, Tan Roon Fang, Chao Jen-chih

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Cities face environmental challenges, including over-urbanization issues, air and water quality issues, lack of green space, excess heat capture, polluted storm water runoff and lack of ecological biodiversity. The vertical farming holds the condition of technology addressing these issues by enabling more food to be produced with finite less resources use and space. Most of the existing research regarding to technology Industry of agriculture between plant factory and vertical greening, which with high costs and high-technology. Relative research developed a sustainable model for construction and operation of the vertical farm in urban housing which aims to revolutionize our daily life of food production and urban development. However, those researches focused on quantitative analysis. This study utilized relative research for key variables of benefits of vertical farming. In the second stage, utilizes Fuzzy Delphi Method to obtain the critical factors of benefits of vertical farming using in Urban Renewal by interviewing the foregoing experts. Then, Analytic Hierarchy Process is applied to find the importance degree of each criterion as the measurable indices of the vertical farming method in urban renewal within the older city of Taichung.

Keywords: urban renewal, vertical farming, urban agriculture, benefit analysis, the older city of Taichung

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Authors: Shuofen Hsu, Ya-Yi Chao, Chao-Wei Li

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This paper investigates the factors of whether firms’ quarterly consolidated financial statements to be voluntary reviewed by auditor. To promote the information transparency, the Financial Supervisory Commission of Executive Yuan in Taiwan ruled the Taiwanese listed companies should announce the first and third quarterly consolidated financial statements since 2008 to 2012, while the Commission didn’t require the consolidated financial statements should be reviewed by auditors. This is a very special practice in emerging market, especially in Taiwan. The valuable data of this period is suitable for us to research the determinants of firms’ voluntary review decision in emerging markets. We collected the auditors' report of each company and each year of Taiwanese listed companies since 2008 to 2012 for our research samples. We use probit model to test and analyze the determinants of voluntary review decision of the first and third quarterly consolidated financial statements. Our empirical result shows that the firms whose first and third quarterly consolidated financial statements are voluntary to be reviewed by auditors have better ranking of information transparency, higher audit quality, and better corporate governance, suggesting that voluntary review is a good signal to firms’ better information and corporate governance quality.

Keywords: voluntary review, information transparency, audit quality, quarterly consolidated financial statements

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

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The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

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Authors: Ali Hojati Najafabadi, Mohamad Hosein Rahmati, Seyed Ali Madanizadeh

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Governments execute energy subsidy reforms by either increasing energy prices or reducing energy price dispersion. These policies make less use of energy per plant (intensive margin), vary the total number of firms (extensive margin), promote technological progress (technology channel), and make additional resources to redistribute (resource channel). We estimate a structural dynamic firm model with endogenous technology adaptation using data from the manufacturing firms in Iran and a country ranked the second-largest energy subsidy plan by the IMF. The findings show significant dynamics and distributional effects due to an energy reform plan. The price elasticity of energy consumption in the industrial sector is about -2.34, while it is -3.98 for large firms. The dispersion elasticity, defined as the amounts of changes in energy consumption by a one-percent reduction in the standard error of energy price distribution, is about 1.43, suggesting significant room for a distributional policy. We show that the intensive margin is the main driver of energy price elasticity, whereas the other channels mostly offset it. In contrast, the labor response is mainly through the extensive margin. Total factor productivity slightly improves in light of the reduction in energy consumption if, at the same time, the redistribution policy boosts the aggregate demands.

Keywords: energy reform, firm dynamics, structural estimation, subsidy policy

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Authors: Elena Tkachenko, Vladimir Kokh, Alina Osipenko, Vladislav Surkov

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The modern period of development of Russian economy is fraught with a number of problems related to limitations in the use of traditional planning and financial management tools. Restrictions in the use of foreign software when performing an order of the Russian Government, on the one hand, and sanctions limiting the support of the major ERP and MRP II systems in the Russian Federation, on the other hand, entail the necessity to appeal to the basics of developing budgeting and analysis systems for industrial enterprises. Thus, cost calculation theory becomes the theoretical foundation for the development of industrial cost management systems. Based on the foregoing, it would be fair to make an assumption that the development of a working managerial accounting model on an industrial enterprise using an automated enterprise resource management system should rest upon the concept of the inevitability of alterations of business processes. On the other hand, optimized business processes make the architecture of financial analytics more transparent and permit the use of all the benefits of data cubes. The metrics and indicator slices provide online assessment of the state of key business processes at a given moment of time, which improves the quality of managerial decisions considerably. Therefore, the bilateral sanctions situation boosted the development of corporate business analytics and took industrial companies to the next level of understanding of business processes.

Keywords: cost culculation, ERP, OLAP, modern Russian economy

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Authors: Moustafa Ahmed, Fumio Koyama

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Directly-modulated semiconductor lasers, including edge-emitting and vertical-cavity surface-emitting lasers, have received considerable interest recently for use in data transmitters in cost-effective high-speed data centers, metro, and access networks. Optical feedback has been proved as an efficient technique to boost the modulation bandwidth and enhance the speed of the semiconductor laser. However, both the laser linewidth and frequency chirping in directly-modulated lasers are sensitive to both intensity modulation and optical feedback. These effects along width fiber dispersion affect the transmission bit rate and distance in single-mode fiber links. In this work, we continue our recent research on directly-modulated semiconductor lasers with modulation bandwidth in the millimeter-wave band by introducing simultaneous modeling and simulations on both the frequency chirping and lineshape broadening. The lasers are operating under strong optical feedback. The model takes into account the multiple reflections of laser reflections of laser radiation in the external cavity. The analyses are given in terms of the chirp-to-modulated power ratio, and the results are shown for the possible dynamic states of continuous wave, period-1 oscillation, and chaos.

Keywords: chirp, linewidth, optical feedback, semiconductor laser

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

Procedia PDF Downloads 243

Authors: A.Chen Chao-Chang, Phong Pham-Quoc

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Chemical-mechanical polishing (CMP) process has been widely applied on fabricating integrated circuits (IC) with a soft polishing pad combined with slurry composed of micron or nano-scaled abrasives for generating chemical reaction to remove substrate or film materials from wafer. During CMP process, pad uniformity usually works as a datum surface of wafer planarization and pad asperities can dominate the microscopic pad-slurry-wafer interaction. However, pad topography can be changed by related mechanism factors of CMP and it needs to be re-conditioned or dressed by a diamond dresser of well-distributed diamond grits on a disc surface. It is still very complicated to analyze and understand kinematic of diamond dressing process under the effects of input variables including oscillatory of diamond dresser and rotation speed ratio between the pad and the diamond dresser. This paper has developed a generic geometric model to clarify the kinematic modeling of diamond dressing processes such as dresser/pad motion, pad cutting locus, the relative velocity of the diamond abrasive grits on pad surface, and overlap of cutting for prediction of pad surface topography. Simulation results focus on comparing and analysis kinematics of the diamond dressing on certain CMP tools. Results have shown the significant parameters for diamond dressing process and also discussed. Future study can apply on diamond dresser design and experimental verification of pad dressing process.

Keywords: kinematic modeling, diamond dresser, pad cutting locus, CMP

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Jie Liu, Wei Wei, Chun-Ping Chang

Abstract:

Using a sample of 110 countries over the period 1984-2013, this paper examines the impacts of country risks on choosing a specific exchange rate regime (first by utilizing the Levy-Yeyati and Sturzenegger de facto classification and then robusting it by the IMF de jure measurement) relative to other regimes via the panel multinomial logit approach. Empirical findings are as follows. First, in the full samples case we provide evidence that government is more likely to implement a flexible regime, but less likely to adopt a fixed regime, under a low level of composite and financial risk. Second, we find that Eurozone countries are more likely to choose a fixed exchange rate regime with a decrease in the level of country risk and favor a flexible regime in response to a shock from an increase of risk, which is opposite to non-Eurozone countries. Third, we note that high-risk countries are more likely to choose a fixed regime with a low level of composite and political risk in the government, but do not adjust the exchange rate regime as a shock absorber when facing economic and financial risks. It is interesting to see that those countries with relatively low risk display almost opposite results versus high-risk economies. Overall, we believe that it is critically important to account for political economy variables in a government’s exchange rate policy decisions, especially for country risks. All results are robust to the panel ordered probit model.

Keywords: country risk, political economy, exchange rate regimes, shock absorber

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Authors: Y. J. Zhou, G. Lu

Abstract:

In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: analytical method, mechanical responses, spherical wave propagation, traumatic brain injury

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Authors: Luis Marquez, Ge Zhu, Vikas Srivastava

Abstract:

High-density polyethylene (HDPE) is one of the most commonly used thermoplastic polymer materials for water and gas pipelines. Slow crack growth failure is a well-known phenomenon in high-density polyethylene material and causes brittle failure well below the yield point with no obvious sign. The failure of transportation pipelines can cause catastrophic environmental and economic consequences. Using the non-destructive testing method to predict slow crack growth failure behavior is the primary preventative measurement employed by the pipeline industry but is often costly and time-consuming. Phenomenological slow crack growth models are useful to predict the slow crack growth behavior in the polymer material due to their ability to evaluate slow crack growth under different temperature and loading conditions. We developed a quantitative method to assess the slow crack growth behavior in the high-density polyethylene pipeline material under different thermal conditions based on existing physics-based phenomenological models. We are also working on developing an experimental protocol and quantitative model that can address slow crack growth behavior under different chemical exposure conditions to improve the safety, reliability, and resilience of HDPE-based pipeline infrastructure.

Keywords: mechanics of materials, physics-based modeling, civil engineering, fracture mechanics

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Authors: Khaled Suleiman Mohammed Al-Mashrafi

Abstract:

A compositional plume is a fluid flow in a directional channel of finite width in another fluid of different material composition. The study of the dynamics of compositional plumes plays an essential role in many real-life applications like industrial applications (e.g., iron casting), environmental applications (e.g., salt fingers and sea ice), and geophysical applications (e.g., solidification at the inner core boundary (ICB) of the Earth, and mantle plumes). The dynamics of compositional plumes have been investigated experimentally and theoretically. The experimental works observed that the plume flow seems to be stable, although some experiments showed that it can be unstable. At the same time, the theoretical investigations showed that the plume flow is unstable. This is found to be true even if the plume is subject to rotation or/and in the presence of a magnetic field and even if another plume of different composition is also present. It is noticeable that all the theoretical studies on the dynamics of compositional plumes are conducted in unbounded domains. The present work is to investigate theoretically the influence of vertical walls (boundaries) on the dynamics of compositional plumes in the absence/presence of a rotation field. The mathematical model of the dynamics of compositional plumes used the equations of continuity, motion, heat, concentration of light material, and state. It is found that the presence of boundaries has a strong influence on the basic state solution as well as the stability of the plume, particularly when the plume is close to the boundary, but the compositional plume remains unstable.

Keywords: compositional plumes, stability, bounded domain, vertical boundaries

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