Search results for: return prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3127

Search results for: return prediction

637 A Critical Analysis of the Creation of Geoparks in Brazil: Challenges and Possibilities

Authors: Isabella Maria Beil

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The International Geosciences and Geoparks Programme (IGGP) were officially created in 2015 by the United Nations Educational, Scientific and Cultural Organization (UNESCO) to enhance the protection of the geological heritage and fill the gaps on the World Heritage Convention. According to UNESCO, a Global Geopark is an unified area where sites and landscapes of international geological significance are managed based on a concept of sustainable development. Tourism is seen as a main activity to develop new sources of revenue. Currently (November 2022), UNESCO recognized 177 Global Geoparks, of which more than 50% are in Europe, 40% in Asia, 6% in Latin America, and the remaining 4% are distributed between Africa and Anglo-Saxon America. This picture shows the existence of a much uneven geographical distribution of these areas across the planet. Currently, there are three Geoparks in Brazil; however, the first of them was accepted by the Global Geoparks Network in 2006 and, just fifteen years later, two other Brazilian Geoparks also obtained the UNESCO title. Therefore, this paper aims to provide an overview of the current geopark situation in Brazil and to identify the main challenges faced by the implementation of these areas in the country. To this end, the Brazilian history and its main characteristics regarding the development of geoparks over the years will be briefly presented. Then, the results obtained from interviews with those responsible for each of the current 29 aspiring geoparks in Brazil will be presented. Finally, the main challenges related to the implementation of Geoparks in the country will be listed. Among these challenges, the answers obtained through the interviews revealed conflicts and problems that pose hindrances both to the start of the development of a Geopark project and to its continuity and implementation. It is clear that the task of getting multiple social actors, or stakeholders, to engage with the Geopark, one of UNESCO’s guidelines, is one of its most complex aspects. Therefore, among the main challenges, stand out the difficulty of establishing solid partnerships, what directly reflects divergences between the different social actors and their goals. This difficulty in establishing partnerships happens for a number of reasons. One of them is that the investment in a Geopark project can be high and investors often expect a short-term financial return. In addition, political support from the public sector is often costly as well, since the possible results and positive influences of a Geopark in a given area will only be experienced during future mandates. These results demonstrate that the research on Geoparks goes far beyond the geological perspective linked to its origins, and is deeply embedded in political and economic issues.

Keywords: Brazil, geoparks, tourism, UNESCO

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636 Early Gastric Cancer Prediction from Diet and Epidemiological Data Using Machine Learning in Mizoram Population

Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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635 Ordinal Regression with Fenton-Wilkinson Order Statistics: A Case Study of an Orienteering Race

Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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634 Ultra-deformable Drug-free Sequessome™ Vesicles (TDT 064) for the Treatment of Joint Pain Following Exercise: A Case Report and Clinical Data

Authors: Joe Collins, Matthias Rother

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Background: Oral non-steroidal anti-inflammatory drugs (NSAIDs) are widely used for the relief of joint pain during and post-exercise. However, oral NSAIDs increase the risk of systemic side effects, even in healthy individuals, and retard recovery from muscle soreness. TDT 064 (Flexiseq®), a topical formulation containing ultra-deformable drug-free Sequessome™ vesicles, has demonstrated equivalent efficacy to oral celecoxib in reducing osteoarthritis-associated joint pain and stiffness. TDT 064 does not cause NSAID-related adverse effects. We describe clinical study data and a case report on the effectiveness of TDT 064 in reducing joint pain after exercise. Methods: Participants with a pain score ≥3 (10-point scale) 12–16 hours post-exercise were randomized to receive TDT 064 plus oral placebo, TDT 064 plus oral ketoprofen, or ketoprofen in ultra-deformable phospholipid vesicles plus oral placebo. Results: In the 168 study participants, pain scores were significantly higher with oral ketoprofen plus TDT 064 than with TDT 064 plus placebo in the 7 days post-exercise (P = 0.0240) and recovery from muscle soreness was significantly longer (P = 0.0262). There was a low incidence of adverse events. These data are supported by clinical experience. A 24-year-old male professional rugby player suffered a traumatic lisfranc fracture in March 2014 and underwent operative reconstruction. He had no relevant medical history and was not receiving concomitant medications. He had undergone anterior cruciate ligament reconstruction in 2008. The patient reported restricted training due to pain (score 7/10), stiffness (score 9/10) and poor function, as well as pain when changing direction and running on consecutive days. In July 2014 he started using TDT 064 twice daily at the recommended dose. In November 2014 he noted reduced pain on running (score 2-3/10), decreased morning stiffness (score 4/10) and improved joint mobility and was able to return to competitive rugby without restrictions. No side effects of TDT 064 were reported. Conclusions: TDT 064 shows efficacy against exercise- and injury-induced joint pain, as well as that associated with osteoarthritis. It does not retard muscle soreness recovery after exercise compared with an oral NSAID, making it an alternative approach for the treatment of joint pain during and post-exercise.

Keywords: exercise, joint pain, TDT 064, phospholipid vesicles

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633 Theory of the Optimum Signal Approximation Clarifying the Importance in the Recognition of Parallel World and Application to Secure Signal Communication with Feedback

Authors: Takuro Kida, Yuichi Kida

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In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

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632 Predicting Foreign Direct Investment of IC Design Firms from Taiwan to East and South China Using Lotka-Volterra Model

Authors: Bi-Huei Tsai

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This work explores the inter-region investment behaviors of integrated circuit (IC) design industry from Taiwan to China using the amount of foreign direct investment (FDI). According to the mutual dependence among different IC design industrial locations, Lotka-Volterra model is utilized to explore the FDI interactions between South and East China. Effects of inter-regional collaborations on FDI flows into China are considered. Evolutions of FDIs into South China for IC design industry significantly inspire the subsequent FDIs into East China, while FDIs into East China for Taiwan’s IC design industry significantly hinder the subsequent FDIs into South China. The supply chain along IC industry includes IC design, manufacturing, packing and testing enterprises. I C manufacturing, packaging and testing industries depend on IC design industry to gain advanced business benefits. The FDI amount from Taiwan’s IC design industry into East China is the greatest among the four regions: North, East, Mid-West and South China. The FDI amount from Taiwan’s IC design industry into South China is the second largest. If IC design houses buy more equipment and bring more capitals in South China, those in East China will have pressure to undertake more FDIs into East China to maintain the leading position advantages of the supply chain in East China. On the other hand, as the FDIs in East China rise, the FDIs in South China will successively decline since capitals have concentrated in East China. Prediction of Lotka-Volterra model in FDI trends is accurate because the industrial interactions between the two regions are included. Finally, this work confirms that the FDI flows cannot reach a stable equilibrium point, so the FDI inflows into East and South China will expand in the future.

Keywords: Lotka-Volterra model, foreign direct investment, competitive, Equilibrium analysis

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631 Frequency of Alloimmunization in Sickle Cell Disease Patients in Africa: A Systematic Review with Meta-analysis

Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

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630 Totally Implantable Venous Access Device for Long Term Parenteral Nutrition in a Patient with High Output Enterocutaneous Fistula Due to Advanced Malignancy

Authors: Puneet Goyal, Aarti Agarwal

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Background and Objective: Nutritional support is an integral part of palliative care of advanced non-resectable abdominal malignancy patients, though is frequently neglected aspect. Non-Healing high output Entero-cutaneous fistulas sometimes require long term parenteral nutrition, to take care of catabolism and replacement of nutrients. We present a case of inoperable pancreatic malignancy with high output entero-cutaneous fistula, which was provided parenteral nutritional support with the use of Totally Implantable Venous Access Device (TIVAD). Method and Results: 55 year old man diagnosed with carcinoma pancreas had developed high entero-cutaneous fistula. His tumor was found to be inoperable and was on total parenteral nutrition through routine central line. This line was difficult to maintain as he required it for a long term TPN. He was planned to undergo Totally Implantable Venous Access Device (TIVAD) implantation. 8Fr single lumen catheter with Groshong non-return Valve (Bard Access Systems, Inc. USA) was inserted through right internal jugular vein, under fluoroscopic guidance. The catheter was tunneled subcutaneously and brought towards infraclavicular pocket, cut at appropriate length and connected to port and locked. Port was sutured in floor of pocket. Free flow of blood aspirated, flushed with heparinized saline. There was no kink observed in entire length of catheter under fluoroscopy. Skin over infraclavicular pocket was sutured. Long term catheter care and associated risks were explained to patient and relatives. Patient continued to receive total parenteral nutrition as well as other supportive therapy though TIVAD for next 6 weeks, till his demise. Conclusion: TIVADs are standard of care for long term venous access solutions in cancer patients requiring chemotherapy. In this case, we extended its use for providing parenteral nutrition and other supportive therapy. TIVADs can be implanted in advanced cancer patients for providing venous access solution required for various palliative treatments and medications. This will help in improving quality of life and satisfaction amongst terminally ill cancer patients.

Keywords: parenteral nutrition, totally implantable venous access device, long term venous access, interventions in anesthesiology

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629 Colorful Ethnoreligious Map of Iraq and the Current Situation of Minorities in the Country

Authors: Meszár Tárik

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The aim of the study is to introduce the minority groups living in Iraq and to shed light on their current situation. The Middle East is a rather heterogeneous region in ethnic terms. It includes many ethnic, national, religious, linguistic, or ethnoreligious groups. The relationship between the majority and minority is the main cause of various conflicts in the region. It seems that most of the post-Ottoman states have not yet developed a unified national identity capable of integrating their multi-ethnic societies. The issue of minorities living in the Middle East is highly politicized and controversial, as the various Arab states consider the treatment of minorities as their internal affair, do not recognize discrimination or even deny the existence of any kind of minorities on their territory. This attitude of the Middle Eastern states may also be due to the fact that the minority issue can be abused and can serve as a reference point for the intervention policies of Western countries at any time. Methodologically, the challenges of these groups are perceived through the manifestos of prominent individuals and organizations belonging to minorities. The basic aim is to present the minorities’ own history in dealing with the issue. It also introduces the different ethnic and religious minorities in Iraq and analyzes their situation during the operation of the terrorist organization „Islamic State” and in the aftermath. It is clear that the situation of these communities deteriorated significantly with the advance of ISIS, but it is also clear that even after the expulsion of the militant group, we cannot necessarily report an improvement in this area, especially in terms of the ability of minorities to assert their interests and physical security. The emergence of armed militias involved in the expulsion of ISIS sometimes has extremely negative effects on them. Until the interests of non-Muslims are adequately represented at the local level and in the legislature, most experts and advocates believe that little will change in their situation. When conflicts flare, many Iraqi citizens usually leave Iraq, but because of the poor public security situation (threats from terrorist organizations, interventions by other countries), emigration causes serious problems not only outside the country’s borders but also within the country. Another ominous implication for minorities is that their communities are very slow if ever, to return to their homes after fleeing their own settlements. An important finding of the study is that this phenomenon is changing the face of traditional Iraqi settlements and threatens to plunge groups that have lived there for thousands of years into the abyss of history. Therefore, we not only present the current situation of minorities living in Iraq but also discuss their future possibilities.

Keywords: Middle East, Iraq, Islamic State, minorities

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628 Impact of Economic Globalization on Ecological Footprint in India: Evidenced with Dynamic ARDL Simulations

Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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627 Remaining Useful Life Estimation of Bearings Based on Nonlinear Dimensional Reduction Combined with Timing Signals

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

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626 Nonlinear Aerodynamic Parameter Estimation of a Supersonic Air to Air Missile by Using Artificial Neural Networks

Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

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625 Parental Education on Early Childhood Development Using Mobile App and Website in China

Authors: Margo O'Sullivan, Xuefeng Chen, Qi Zhao, J. Jiang, Ning Fu

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Early childhood development, or ECD, is about the 'whole child' – the physical, social and emotional, cognitive thinking and language progression of each young individual. Overwhelming evidence is now available to support investment in Early Childhood Development internationally, attendance at ECD leads to: improved learning outcomes; improved completion and reduced less dropout rates; and most notably, Professor Heckman, Nobel Laureate’s, findings that for every dollar invested, there is an economic return of up to 17%. Notably, ECD has been included in the 2015-2030 Sustainable Development Goals. The Government of China (GOC) has embraced this research and in 2010, State Council, announced focus on ECD setting a target to provide access to ECD for 85% of 3-6 year olds by 2020; to date, the target has surpassed expectations and reached 70.4%. GoC is also increasingly focusing on the even more critical 0-3 age group, when the plasticity of the brain is at its peak and neurons form connections as fast as 1,000 per second. Key to ECD are parents and caregivers of young children, with parental education critical to fully exploiting the significant potential of the early years of children. In China, with such vast numbers, one in seven pre-school age children in the world live in China, the Ministry of Education (MoE) and the National Centre for Education Technology, explored how to best provide parental education and provide key child developmental related knowledge to parents and caregivers. In response, MoE and UNICEF created a resource for parenting information that began with a computer website in 2012, followed by piloting a kiosk service in 2013 for parents in remote areas without access to the internet, and then a mobile phone application in 2014. The resource includes 269 ECD messages and 200 micro-videos covering critical issues of early childhood development from birth to age 6 years: daily care, nutrition and feeding, disease prevention, immunization, development and education, and safety and protection. To date, there have been 397,599 unique views on the website, and data for the mobile app currently being analysed (Links: http://yuer.cbern.gov.cn/; App: https://appsto.re/cn/OiKPZ.i). This paper will explore the development of this resource, its use by parents and the public, efforts to assess the effectiveness in improving parenting and child development, and future plans to roll an updated version in 2016 to all parents.

Keywords: early childhood development, mobile apps for education, parental education, China

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624 Numerical Tools for Designing Multilayer Viscoelastic Damping Devices

Authors: Mohammed Saleh Rezk, Reza Kashani

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Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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623 Discrete PID and Discrete State Feedback Control of a Brushed DC Motor

Authors: I. Valdez, J. Perdomo, M. Colindres, N. Castro

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Today, digital servo systems are extensively used in industrial manufacturing processes, robotic applications, vehicles and other areas. In such control systems, control action is provided by digital controllers with different compensation algorithms, which are designed to meet specific requirements for a given application. Due to the constant search for optimization in industrial processes, it is of interest to design digital controllers that offer ease of realization, improved computational efficiency, affordable return rates, and ease of tuning that ultimately improve the performance of the controlled actuators. There is a vast range of options of compensation algorithms that could be used, although in the industry, most controllers used are based on a PID structure. This research article compares different types of digital compensators implemented in a servo system for DC motor position control. PID compensation is evaluated on its two most common architectures: PID position form (1 DOF), and PID speed form (2 DOF). State feedback algorithms are also evaluated, testing two modern control theory techniques: discrete state observer for non-measurable variables tracking, and a linear quadratic method which allows a compromise between the theoretical optimal control and the realization that most closely matches it. The compared control systems’ performance is evaluated through simulations in the Simulink platform, in which it is attempted to model accurately each of the system’s hardware components. The criteria by which the control systems are compared are reference tracking and disturbance rejection. In this investigation, it is considered that the accurate tracking of the reference signal for a position control system is particularly important because of the frequency and the suddenness in which the control signal could change in position control applications, while disturbance rejection is considered essential because the torque applied to the motor shaft due to sudden load changes can be modeled as a disturbance that must be rejected, ensuring reference tracking. Results show that 2 DOF PID controllers exhibit high performance in terms of the benchmarks mentioned, as long as they are properly tuned. As for controllers based on state feedback, due to the nature and the advantage which state space provides for modelling MIMO, it is expected that such controllers evince ease of tuning for disturbance rejection, assuming that the designer of such controllers is experienced. An in-depth multi-dimensional analysis of preliminary research results indicate that state feedback control method is more satisfactory, but PID control method exhibits easier implementation in most control applications.

Keywords: control, DC motor, discrete PID, discrete state feedback

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622 Cement Bond Characteristics of Artificially Fabricated Sandstones

Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

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The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

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621 Inverse Prediction of Thermal Parameters of an Annular Hyperbolic Fin Subjected to Thermal Stresses

Authors: Ashis Mallick, Rajeev Ranjan

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The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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620 Exploring Hydrogen Embrittlement and Fatigue Crack Growth in API 5L X52 Steel Pipeline Under Cyclic Internal Pressure

Authors: Omar Bouledroua, Djamel Zelmati, Zahreddine Hafsi, Milos B. Djukic

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Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure, mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines.

Keywords: hydrogen embrittlement, pipelines, transient flow, cyclic pressure, fatigue crack growth

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619 Off-Shore Wind Turbines: The Issue of Soil Plugging during Pile Installation

Authors: Mauro Iannazzone, Carmine D'Agostino

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Off-shore wind turbines are currently considered as a reliable source of renewable energy Worldwide and especially in the UK. Most of the operational off-shore wind turbines located in shallow waters (i.e. < 30 m) are supported on monopiles. Monopiles are open-ended steel tubes with diameter ranging between 4 to 6 m. It is expected that future off-shore wind farms will be located in water depths as high as 70 m. Therefore, alternative foundation arrangements are needed. Foundations for off-shore structures normally consist of open-ended piles driven into the soil by means of impact hammers. During pile installation, the soil inside the pile may be mobilized by the increasing shear strength such as to prevent more soil from entering the pile. This phenomenon is known as soil plugging, and represents an important issue as it may change significantly the driving resistance of open-ended piles. In fact, if the plugging formation is unexpected, the installation may require more powerful and more expensive hammers. Engineers need to estimate whether the driven pile will be installed in a plugged or unplugged mode. As a consequence, a prediction of the degree of soil plugging is required in order to correctly predict the drivability of the pile. This work presents a brief review of the state-of-the-art of pile driving and approaches used to predict formation of soil plugs. In addition, a novel analytical approach is proposed, which is based on the vertical equilibrium of a plugged pile. Differently from previous studies, this research takes into account the enhancement of the stress within the soil plug. Finally, the work presents and discusses a series of experimental tests, which are carried out on small-scale models piles to validate the analytical solution.

Keywords: off-shore wind turbines, pile installation, soil plugging, wind energy

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618 Cognitive Science Based Scheduling in Grid Environment

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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617 Parameters Identification and Sensitivity Study for Abrasive WaterJet Milling Model

Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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616 Quoting Jobshops Due Dates Subject to Exogenous Factors in Developing Nations

Authors: Idris M. Olatunde, Kareem B.

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In manufacturing systems, especially job shops, service performance is a key factor that determines customer satisfaction. Service performance depends not only on the quality of the output but on the delivery lead times as well. Besides product quality enhancement, delivery lead time must be minimized for optimal patronage. Quoting accurate due dates is sine quo non for job shop operational survival in a global competitive environment. Quoting accurate due dates in job shops has been a herculean task that nearly defiled solutions from many methods employed due to complex jobs routing nature of the system. This class of NP-hard problems possessed no rigid algorithms that can give an optimal solution. Jobshop operational problem is more complex in developing nations due to some peculiar factors. Operational complexity in job shops emanated from political instability, poor economy, technological know-how, and the non-promising socio-political environment. The mentioned exogenous factors were hardly considered in the previous studies on scheduling problem related to due date determination in job shops. This study has filled the gap created in the past studies by developing a dynamic model that incorporated the exogenous factors for accurate determination of due dates for varying jobs complexity. Real data from six job shops selected from the different part of Nigeria, were used to test the efficacy of the model, and the outcomes were analyzed statistically. The results of the analyzes showed that the model is more promising in determining accurate due dates than the traditional models deployed by many job shops in terms of patronage and lead times minimization.

Keywords: due dates prediction, improved performance, customer satisfaction, dynamic model, exogenous factors, job shops

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615 Design, Synthesis and Pharmacological Investigation of Novel 2-Phenazinamine Derivatives as a Mutant BCR-ABL (T315I) Inhibitor

Authors: Gajanan M. Sonwane

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Nowadays, the entire pharmaceutical industry is facing the challenge of increasing efficiency and innovation. The major hurdles are the growing cost of research and development and a concurrent stagnating number of new chemical entities (NCEs). Hence, the challenge is to select the most druggable targets and to search the equivalent drug-like compounds, which also possess specific pharmacokinetic and toxicological properties that allow them to be developed as drugs. The present research work includes the studies of developing new anticancer heterocycles by using molecular modeling techniques. The heterocycles synthesized through such methodology are much effective as various physicochemical parameters have been already studied and the structure has been optimized for its best fit in the receptor. Hence, on the basis of the literature survey and considering the need to develop newer anticancer agents, new phenazinamine derivatives were designed by subjecting the nucleus to molecular modeling, viz., GQSAR analysis and docking studies. Simultaneously, these designed derivatives were subjected to in silico prediction of biological activity through PASS studies and then in silico toxicity risk assessment studies. In PASS studies, it was found that all the derivatives exhibited a good spectrum of biological activities confirming its anticancer potential. The toxicity risk assessment studies revealed that all the derivatives obey Lipinski’s rule. Amongst these series, compounds 4c, 5b and 6c were found to possess logP and drug-likeness values comparable with the standard Imatinib (used for anticancer activity studies) and also with the standard drug methotrexate (used for antimitotic activity studies). One of the most notable mutations is the threonine to isoleucine mutation at codon 315 (T315I), which is known to be resistant to all currently available TKI. Enzyme assay planned for confirmation of target selective activity.

Keywords: drug design, tyrosine kinases, anticancer, Phenazinamine

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614 A Deep Learning Model with Greedy Layer-Wise Pretraining Approach for Optimal Syngas Production by Dry Reforming of Methane

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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613 Optimizing the Window Geometry Using Fractals

Authors: K. Geetha Ramesh, A. Ramachandraiah

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In an internal building space, daylight becomes a powerful source of illumination. The challenge therefore, is to develop means of utilizing both direct and diffuse natural light in buildings while maintaining and improving occupant's visual comfort, particularly at greater distances from the windows throwing daylight. The geometrical features of windows in a building have significant effect in providing daylight. The main goal of this research is to develop an innovative window geometry, which will effectively provide the daylight component adequately together with internal reflected component(IRC) and also the external reflected component(ERC), if any. This involves exploration of a light redirecting system using fractal geometry for windows, in order to penetrate and distribute daylight more uniformly to greater depths, minimizing heat gain and glare, and also to reduce building energy use substantially. Of late the creation of fractal geometrical window and the occurrence of daylight illuminance due to such windows is becoming an interesting study. The amount of daylight can change significantly based on the window geometry and sky conditions. This leads to the (i) exploration of various fractal patterns suitable for window designs, and (ii) quantification of the effect of chosen fractal window based on the relationship between the fractal pattern, size, orientation and glazing properties for optimizing daylighting. There are a lot of natural lighting applications able to predict the behaviour of a light in a room through a traditional opening - a regular window. The conventional prediction methodology involves the evaluation of the daylight factor, the internal reflected component and the external reflected component. Having evaluated the daylight illuminance level for a conventional window, the technical performance of a fractal window for an optimal daylighting is to be studied and compared with that of a regular window. The methodologies involved are highlighted in this paper.

Keywords: daylighting, fractal geometry, fractal window, optimization

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612 Recurrent Neural Networks for Complex Survival Models

Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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611 Nuclear Fuel Safety Threshold Determined by Logistic Regression Plus Uncertainty

Authors: D. S. Gomes, A. T. Silva

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Analysis of the uncertainty quantification related to nuclear safety margins applied to the nuclear reactor is an important concept to prevent future radioactive accidents. The nuclear fuel performance code may involve the tolerance level determined by traditional deterministic models producing acceptable results at burn cycles under 62 GWd/MTU. The behavior of nuclear fuel can simulate applying a series of material properties under irradiation and physics models to calculate the safety limits. In this study, theoretical predictions of nuclear fuel failure under transient conditions investigate extended radiation cycles at 75 GWd/MTU, considering the behavior of fuel rods in light-water reactors under reactivity accident conditions. The fuel pellet can melt due to the quick increase of reactivity during a transient. Large power excursions in the reactor are the subject of interest bringing to a treatment that is known as the Fuchs-Hansen model. The point kinetic neutron equations show similar characteristics of non-linear differential equations. In this investigation, the multivariate logistic regression is employed to a probabilistic forecast of fuel failure. A comparison of computational simulation and experimental results was acceptable. The experiments carried out use the pre-irradiated fuels rods subjected to a rapid energy pulse which exhibits the same behavior during a nuclear accident. The propagation of uncertainty utilizes the Wilk's formulation. The variables chosen as essential to failure prediction were the fuel burnup, the applied peak power, the pulse width, the oxidation layer thickness, and the cladding type.

Keywords: logistic regression, reactivity-initiated accident, safety margins, uncertainty propagation

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610 Sensitivity Analysis of the Thermal Properties in Early Age Modeling of Mass Concrete

Authors: Farzad Danaei, Yilmaz Akkaya

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In many civil engineering applications, especially in the construction of large concrete structures, the early age behavior of concrete has shown to be a crucial problem. The uneven rise in temperature within the concrete in these constructions is the fundamental issue for quality control. Therefore, developing accurate and fast temperature prediction models is essential. The thermal properties of concrete fluctuate over time as it hardens, but taking into account all of these fluctuations makes numerical models more complex. Experimental measurement of the thermal properties at the laboratory conditions also can not accurately predict the variance of these properties at site conditions. Therefore, specific heat capacity and the heat conductivity coefficient are two variables that are considered constant values in many of the models previously recommended. The proposed equations demonstrate that these two quantities are linearly decreasing as cement hydrates, and their value are related to the degree of hydration. The effects of changing the thermal conductivity and specific heat capacity values on the maximum temperature and the time it takes for concrete to reach that temperature are examined in this study using numerical sensibility analysis, and the results are compared to models that take a fixed value for these two thermal properties. The current study is conducted in 7 different mix designs of concrete with varying amounts of supplementary cementitious materials (fly ash and ground granulated blast furnace slag). It is concluded that the maximum temperature will not change as a result of the constant conductivity coefficient, but variable specific heat capacity must be taken into account, also about duration when a concrete's central node reaches its max value again variable specific heat capacity can have a considerable effect on the final result. Also, the usage of GGBFS has more influence compared to fly ash.

Keywords: early-age concrete, mass concrete, specific heat capacity, thermal conductivity coefficient

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609 Correlation between Neck Circumference and Other Anthropometric Indices as a Predictor of Obesity

Authors: Madhur Verma, Meena Rajput, Kamal Kishore

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Background: The general view that obesity is a problem of prosperous Western countries has been repealed with substantial evidence showing that middle-income countries like India are now at the heart of a fat explosion. Neck circumference has evolved as a promising index to measure obesity, because of the convenience of its use, even in culture sensitive population. Objectives: To determine whether neck circumference (NC) was associated with overweight and obesity and contributed to the prediction like other classical anthropometric indices. Methodology: Cross-sectional study consisting of 1080 adults (> 19 years) selected through Multi-stage random sampling between August 2013 and September 2014 using the pretested semi-structured questionnaire. After recruitment, the demographic and anthropometric parameters [BMI, Waist & Hip Circumference (WC, HC), Waist to hip ratio (WHR), waist to height ratio (WHtR), body fat percentage (BF %), neck circumference (NC)] were recorded & calculated as per standard procedures. Analysis was done using appropriate statistical tests. (SPSS, version 21.) Results: Mean age of study participants was 44.55+15.65 years. Overall prevalence of overweight & obesity as per modified criteria for Asian Indians (BMI ≥ 23 kg/m2) was 49.62% (Females-51.48%; Males-47.77%). Also, number of participants having high WHR, WHtR, BF%, WC & NC was 827(76.57%), 530(49.07%), 513(47.5%), 537(49.72%) & 376(34.81%) respectively. Variation of NC, BMI & BF% with age was non- significant. In both the genders, as per the Pearson’s correlational analysis, neck circumference was positively correlated with BMI (men, r=0.670 {p < 0.05}; women, r=0.564 {p < 0.05}), BF% (men, r=0.407 {p < 0.05}; women, r= 0.283 {p < 0.05}), WC (men, r=0.598{p < 0.05}; women, r=0.615 {p < 0.05}), HC (men, r=0.512{p < 0.05}; women, r=0.523{p < 0.05}), WHR (men, r= 0.380{p > 0.05}; women, r=0.022{p > 0.05}) & WHtR (men, r=0.318 {p < 0.05}; women, r=0.396{p < 0.05}). On ROC analysis, NC showed good discriminatory power to identify obesity with AUC (AUC for males: 0.822 & females: 0.873; p- value < 0.001) with maximum sensitivity and specificity at a cut-off value of 36.55 cms for males & 34.05cms for females. Conclusion: NC has fair validity as a community-based screener for overweight and obese individuals in the study context and has also correlated well with other classical indices.

Keywords: neck circumference, obesity, anthropometric indices, body fat percentage

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608 Executive Order as an Effective Tool in Combating Insecurities and Human Rights Violations: The Case of the Special Anti-Robbery Squad and Youths in Nigeria

Authors: Cita Ayeni

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Following countless violations of Human Rights in Nigeria by the various arms and agencies of government; from the Military to the Federal Police and other law enforcement agencies, Nigeria has been riddled with several reports of acts by these agencies against the citizens, ranging from illegal arrest and imprisonment, torture, disappearing, and extrajudicial killings, just to mention a few. This paper, focuses on SARS (Special Anti-Robbery Squad), a division of the Nigeria Police Force, and its reported threats to the people’s security, particularly the Nigerian youths, with continuous violence, extortion, illegal arrest and imprisonment, terror, and extrajudicial activities resulting in maiming and in most cases death, thus infringing on the human rights of the people it’s sworn to protect. This research further analyses how the activities of SARS has over the years instigated fear on the average Nigerian youth, preventing the free participation in daily life, education, job, and individual development, in turn impeding the realization of their full potentials for growth and participation in collective national development. This research analyzes the executive order by the then Acting President (Vice-President) of Nigeria, directing the overhauling of SARS, and its implementation by the Federal Police Force in determining if it’s enough to prevent or put a stop to the continuous Human Rights abuse and threat to the security of the individual citizen. Concluding that although the order by the Acting President was given with an intent to halt the various violations by SARS, and the Inspector General of Police’s (IGP) subsequent action by releasing a statement following the order, the bureaucracy in Nigeria, with a history of incompetency and a return to 'business as usual' after a reduced public outcry, it’s most likely that there will not be adequate follow up put in place and these violations would be slowly 'swept under the rug' with SARS officials not held accountable. It is recommended therefore that the Federal Government through the NPF, following the reforms made, in collaboration with the mentioned Independent Human Rights and civil societies organizations should periodically produce unbiased and publicly accessible reports on the implementation of these reforms and progress made. This will go a long way in assuring the public of actual fulfillment of the restructuring, reduce fear by the youths and restore some public faith in the government.

Keywords: special anti-robbery squad, youths in Nigeria, overhaul, insecurities, human rights violations

Procedia PDF Downloads 297