Search results for: twin delayed deep deterministic policy gradient.
Commenced in January 2007
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Edition: International
Paper Count: 1662

Search results for: twin delayed deep deterministic policy gradient.

1332 Investigation of Buoyant Parameters of k-ε Turbulence Model in Gravity Stratified Flows

Authors: A. Majid Bahari, Kourosh Hejazi

Abstract:

Different variants for buoyancy-affected terms in k-ε turbulence model have been utilized to predict the flow parameters more accurately, and investigate applicability of alternative k-ε turbulence buoyant closures in numerical simulation of a horizontal gravity current. The additional non-isotropic turbulent stress due to buoyancy has been considered in production term, based on Algebraic Stress Model (ASM). In order to account for turbulent scalar fluxes, general gradient diffusion hypothesis has been used along with Boussinesq gradient diffusion hypothesis with a variable turbulent Schmidt number and additional empirical constant c3ε.To simulate buoyant flow domain a 2D vertical numerical model (WISE, Width Integrated Stratified Environments), based on Reynolds- Averaged Navier-Stokes (RANS) equations, has been deployed and the model has been further developed for different k-ε turbulence closures. Results are compared against measured laboratory values of a saline gravity current to explore the efficient turbulence model.

Keywords: Buoyant flows, Buoyant k-ε turbulence model, saline gravity current.

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1331 Study on Compressive Strength and Setting Times of Fly Ash Concrete after Slump Recovery Using Superplasticizer

Authors: Chaiyakrit Raoupatham, Ram Hari Dhakal, Chalermchai Wanichlamlert

Abstract:

Fresh concrete has one of dynamic properties known as slump. Slump of concrete is design to compatible with placing method. Due to hydration reaction of cement, the slump of concrete is loss through time. Therefore, delayed concrete probably get reject because slump is unacceptable. In order to recover the slump of delayed concrete the second dose of superplasticizer (naphthalene based type F) is added into the system, the slump recovery can be done as long as the concrete is not setting. By adding superplasticizer as solution for recover unusable slump loss concrete may affects other concrete properties. Therefore, this paper was observed setting times and compressive strength of concrete after being re-dose with chemical admixture type F (superplasticizer, naphthalene based) for slump recovery. The concrete used in this study was fly ash concrete with fly ash replacement of 0%, 30% and 50% respectively. Concrete mix designed for test specimen was prepared with paste content (ratio of volume of cement to volume of void in the aggregate) of 1.2 and 1.3, water-to-binder ratio (w/b) range of 0.3 to 0.58, initial dose of superplasticizer (SP) range from 0.5 to 1.6%. The setting times of concrete were tested both before and after re-dosed with different amount of second dose and time of dosing. The research was concluded that addition of second dose of superplasticizer would increase both initial and final setting times accordingly to dosage of addition. As for fly ash concrete, the prolongation effect was higher as the replacement of fly ash increase. The prolongation effect can reach up to maximum about 4 hours. In case of compressive strength, the re-dosed concrete has strength fluctuation within acceptable range of ±10%.

Keywords: Compressive strength, Fly ash concrete, Second dose of superplasticizer, Slump recovery, Setting times.

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1330 Landowners' Willingness to Participate in the Green Forestation Plan in Taiwan

Authors: Wan-Yu Liu, Jiunn-Cheng Lin, Chun-Cheng Lin

Abstract:

Green Forestation Plan (GFP) was expected to promote the reforestation of plains totaling 60,000 has within the first 8 years. Annual subsidies were budgeted at $120,000 per ha, and $2.4 million for 20 years. In this research we have surveyed landlords- opinions toward the GFP in an attempt to understand landlords- incentives for participating in the GFP and their levels of concern and agreement toward the policy design. Based our analysis of landlords- opinions on the policy design, we expect to derive appropriate complementary measures, establish effective promotional schemes, and raise the policy effectiveness of the GFP. According to the results of this research, there was still a relatively high proportion of population who were not aware of GFP; more than 50% of landlords were neutral or willing to participate given high reforestation subsidies; approximately 30% of landlords were unwilling to participate. In terms of the designs of GFP, more than 50% of respondents were concerned and agreed with the policy design. In terms of the period of this policy, 52.7% of respondents indicated that it should be shortened to 15 years or lower. In terms of the amount of the subsidy, 41.7% of respondents showed that it should be raised to approximately $250,000/ha. In terms of land area restrictions, 88.0% of respondents believed that the minimum should be lowered to 0.4 ha. More than 70% of respondents owned less than 0.4 has of land, and since they do not own enough land to be eligible for the program, more than 80% of landlords wished to lower the minimum requirements of land area. In addition, 59.3% of respondents were reluctant to participate in reforestation because their lands were too small to be eligible; 15.0% of respondents were reluctant because the duration was too long. Responses to the question about “how the policy can be adjusted to provide incentives for landlords- participation" revealed that almost 40% of respondents desired higher subsidies. Some policy suggestions are provided as follows: (1) many landlords are still unaware of the GFP so the government should enhance the promotion of the policy; (2) many landlords are unwilling to participate in GFP mainly because they do not own enough lands to be eligible, hence the government should consider adjusting its requirements for minimum agricultural land area; (3) for subsequent promotions on GFP, the government may consider targeting on the landlords with high income and high level of education; (4) because the subsidy of this policy alone provides limited help to landlords, the government should help the landlords to explore other revenue possibilities from afforestation in addition to the existing subsidies and raise the participation incentives.

Keywords: Green Forestation Plan (GFP), Landlord, Willingness to Participate.

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1329 Characterizing Multivariate Thresholds in Industrial Engineering

Authors: Ali E. Abbas

Abstract:

This paper highlights some of the normative issues that might result by setting independent thresholds in risk analyses and particularly with safety regions. A second objective is to explain how such regions can be specified appropriately in a meaningful way. We start with a review of the importance of setting deterministic trade-offs among target requirements. We then show how to determine safety regions for risk analysis appropriately using utility functions.

Keywords: Decision analysis, thresholds, risk, reliability.

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1328 Soft Real-Time Fuzzy Task Scheduling for Multiprocessor Systems

Authors: Mahdi Hamzeh, Sied Mehdi Fakhraie, Caro Lucas

Abstract:

All practical real-time scheduling algorithms in multiprocessor systems present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in multiprocessor systems with real-time constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. The practical scheduling algorithms in real-time systems have not deterministic response time. Deterministic timing behavior is an important parameter for system robustness analysis. The intrinsic uncertainty in dynamic real-time systems increases the difficulties of scheduling problem. To alleviate these difficulties, we have proposed a fuzzy scheduling approach to arrange real-time periodic and non-periodic tasks in multiprocessor systems. Static and dynamic optimal scheduling algorithms fail with non-critical overload. In contrast, our approach balances task loads of the processors successfully while consider starvation prevention and fairness which cause higher priority tasks have higher running probability. A simulation is conducted to evaluate the performance of the proposed approach. Experimental results have shown that the proposed fuzzy scheduler creates feasible schedules for homogeneous and heterogeneous tasks. It also and considers tasks priorities which cause higher system utilization and lowers deadline miss time. According to the results, it performs very close to optimal schedule of uni-processor systems.

Keywords: Computational complexity, Deadline, Feasible scheduling, Fuzzy scheduling, Priority, Real-time multiprocessor systems, Robustness, System utilization.

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1327 Using Partnerships to Achieve National Goals

Authors: Pamela L. Eddy

Abstract:

Ireland developed a National Strategy 2030 that argued for the creation of a new form of higher education institution, a Technological University. The research reported here reviews the first stage of this partnership development. The study found that national policy can create system capacity and change, but that individual partners may have more to gain or lose in collaborating. When presented as a zero-sum activity, fear among partners is high. The level of knowledge and networking within the higher education system possessed by each partner contributed to decisions to participate or not in a joint proposal for collaboration. Greater success resulted when there were gains for all partners. This research concludes that policy mandates can provide motivation to collaborate, but that the partnership needs to be built more on shared values versus coercion by mandates.

Keywords: Leadership, Partnerships, Policy, Strategic Planning.

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1326 Financial Regulations in the Process of Global Financial Crisis and Macroeconomics Impact of Basel III

Authors: M. Okan Tasar

Abstract:

Basel III (or the Third Basel Accord) is a global regulatory standard on bank capital adequacy, stress testing and market liquidity risk agreed upon by the members of the Basel Committee on Banking Supervision in 2010-2011, and scheduled to be introduced from 2013 until 2018. Basel III is a comprehensive set of reform measures. These measures aim to; (1) improve the banking sector-s ability to absorb shocks arising from financial and economic stress, whatever the source, (2) improve risk management and governance, (3) strengthen banks- transparency and disclosures. Similarly the reform target; (1) bank level or micro-prudential, regulation, which will help raise the resilience of individual banking institutions to periods of stress. (2) Macro-prudential regulations, system wide risk that can build up across the banking sector as well as the pro-cyclical implication of these risks over time. These two approaches to supervision are complementary as greater resilience at the individual bank level reduces the risk system wide shocks. Macroeconomic impact of Basel III; OECD estimates that the medium-term impact of Basel III implementation on GDP growth is in the range -0,05 percent to -0,15 percent per year. On the other hand economic output is mainly affected by an increase in bank lending spreads as banks pass a rise in banking funding costs, due to higher capital requirements, to their customers. Consequently the estimated effects on GDP growth assume no active response from monetary policy. Basel III impact on economic output could be offset by a reduction (or delayed increase) in monetary policy rates by about 30 to 80 basis points. The aim of this paper is to create a framework based on the recent regulations in order to prevent financial crises. Thus the need to overcome the global financial crisis will contribute to financial crises that may occur in the future periods. In the first part of the paper, the effects of the global crisis on the banking system examine the concept of financial regulations. In the second part; especially in the financial regulations and Basel III are analyzed. The last section in this paper explored the possible consequences of the macroeconomic impacts of Basel III.

Keywords: Banking Systems, Basel III, Financial regulation, Global Financial Crisis.

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1325 Principles of Sustainable and Affordable Housing Policy for Afghan Refugees Returning to Afghanistan

Authors: Mohammad Saraj Sharifzai, Keisuke Kitagawa, Mohammad Kamil Halimee, Javid Habib, Daishi Sakaguchi

Abstract:

The overall goal of this paper is to examine the suitability and potential of the policies addressing the sustainability and affordability of housing for returnees, and to determine the impact of this policy on housing delivery for Afghan refugees. Housing is a central component of the settlement experience of refugees. A positive housing situation can facilitate many aspects of integration. Unaffordable, and unsafe housing, however, can cause disruptions in the entire settlement process. This paper aims to identify a suite of built forms for housing that is both affordable and environmentally sustainable for Afghan refugees. The result was the development of a framework that enables the assessment of the overall performance of various types of housing development in all zones of the country. There is very little evidence that the present approach of housing provision to the vagaries of market forces has provided affordable housing, especially for Afghan refugees. There is a need to incorporate social housing into the policy to assist people who cannot afford to have their own houses.

Keywords: Afghan refugees, housing policy, affordability, social housing, housing provision, environmental sustainability principles, resettlement.

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1324 A Survey of Field Programmable Gate Array-Based Convolutional Neural Network Accelerators

Authors: Wei Zhang

Abstract:

With the rapid development of deep learning, neural network and deep learning algorithms play a significant role in various practical applications. Due to the high accuracy and good performance, Convolutional Neural Networks (CNNs) especially have become a research hot spot in the past few years. However, the size of the networks becomes increasingly large scale due to the demands of the practical applications, which poses a significant challenge to construct a high-performance implementation of deep learning neural networks. Meanwhile, many of these application scenarios also have strict requirements on the performance and low-power consumption of hardware devices. Therefore, it is particularly critical to choose a moderate computing platform for hardware acceleration of CNNs. This article aimed to survey the recent advance in Field Programmable Gate Array (FPGA)-based acceleration of CNNs. Various designs and implementations of the accelerator based on FPGA under different devices and network models are overviewed, and the versions of Graphic Processing Units (GPUs), Application Specific Integrated Circuits (ASICs) and Digital Signal Processors (DSPs) are compared to present our own critical analysis and comments. Finally, we give a discussion on different perspectives of these acceleration and optimization methods on FPGA platforms to further explore the opportunities and challenges for future research. More helpfully, we give a prospect for future development of the FPGA-based accelerator.

Keywords: Deep learning, field programmable gate array, FPGA, hardware acceleration, convolutional neural networks, CNN.

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1323 Evaluating per-user Fairness of Goal-Oriented Parallel Computer Job Scheduling Policies

Authors: Sangsuree Vasupongayya

Abstract:

Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.

Keywords: deviation, fair share, discrepancy search, priority scheduling.

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1322 Efficient HAAR Wavelet Transform with Embedded Zerotrees of Wavelet Compression for Color Images

Authors: S. Piramu Kailasam

Abstract:

This study is expected to compress true color image with compression algorithms in color spaces to provide high compression rates. The need of high compression ratio is to improve storage space. Alternative aim is to rank compression algorithms in a suitable color space. The dataset is sequence of true color images with size 128 x 128. HAAR Wavelet is one of the famous wavelet transforms, has great potential and maintains image quality of color images. HAAR wavelet Transform using Set Partitioning in Hierarchical Trees (SPIHT) algorithm with different color spaces framework is applied to compress sequence of images with angles. Embedded Zerotrees of Wavelet (EZW) is a powerful standard method to sequence data. Hence the proposed compression frame work of HAAR wavelet, xyz color space, morphological gradient and applied image with EZW compression, obtained improvement to other methods, in terms of Compression Ratio, Mean Square Error, Peak Signal Noise Ratio and Bits Per Pixel quality measures.

Keywords: Color Spaces, HAAR Wavelet, Morphological Gradient, Embedded Zerotrees Wavelet Compression.

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1321 Adaptive PID Controller based on Reinforcement Learning for Wind Turbine Control

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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1320 Assessment of Climate Policy and Sustainability in Hungary

Authors: M. Csete, G. Szendrö

Abstract:

The last Assessment Report of the Intergovernmental Panel on Climate Change, stating that the greatest risk in climate change affects sustainability is now widely known and accepted. However, it has not provoked substantial reaction and attention in Hungary, while international and national efforts have also not achieved expected results so far. Still, there are numerous examples on different levels (national, regional, local, household) making considerable progress in limiting their own emissions and making steps toward mitigation of and adaptation to climate change. The local level is exceptionally important in sustainability adaptation, as local communities are often able to adapt more flexibly to changes in the natural environment.The aim of this paper is to attempt a review of the national climate policy and the local climate change strategies in Hungary considering sustainable development.

Keywords: adaptation, climate policy, mitigation, localsustainability.

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1319 Satellite Imagery Classification Based on Deep Convolution Network

Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

Abstract:

Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: Satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization.

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1318 The Need for Selective Credit Policy Implementation: Case of Croatia

Authors: Drago Jakovcevic, Mihovil Andelinovic, Igor Husak

Abstract:

The aim of this paper is to explore the economic circumstances in which the selective credit policy, the least used instrument of four types of instruments on disposal to central banks, should be used. The most significant example includes the use of selective credit policies in response to the emergence of the global financial crisis by the FED. Specifics of the potential use of selective credit policies as the instigator of economic growth in Croatia, a small open economy, are determined by high euroization of financial system, fixed exchange rate and long-term trend growth of external debt that is related to the need to maintain high levels of foreign reserves. In such conditions, the classic forms of selective credit policies are unsuitable for the introduction. Several alternative approaches to implement selective credit policies are examined in this paper. Also, thorough analysis of distribution of selective monetary policy loans among economic sectors in Croatia is conducted in order to minimize the risk of investing funds and maximize the return, in order to influence the GDP growth.

Keywords: Global crisis, Selective credit policy, Small open economy.

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1317 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line

Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

Abstract:

Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: Deep-learning, image classification, image identification, industrial engineering.

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1316 The Effects of an Immigration Policy on the Economic Integration of Migrants and on Natives’ Attitudes: The Case of Syrian Refugees in Turkey

Authors: S. Zeynep Siretioglu Girgin, Gizem Turna Cebeci

Abstract:

Turkey’s immigration policy is a controversial issue considering its legal, economic, social, and political and human rights dimensions. Formulation of an immigration policy goes hand in hand with political processes, where natives’ attitudes play a significant role. On the other hand, as was the case in Turkey, radical changes made in immigration policy or policies lacking transparency may cause severe reactions by the host society. The underlying discussion paper aims to analyze quantitatively the effects of the existing ‘open door’ immigration policy on the economic integration of Syrian refugees in Turkey, and on the perception of the native population of refugees. For the analysis, semi-structured in-depth interviews and focus group interviews have been conducted. After the introduction, a literature review is provided, followed by theoretical background on the explanation of natives’ attitudes towards immigrants. In the next section, a qualitative analysis of natives’ attitudes towards Syrian refugees is presented with the subtopics of (i) awareness, general opinions and expectations, (ii) open-door policy and management of the migration process, (iii) perception of positive and negative impacts of immigration, (iv) economic integration, and (v) cultural similarity. Results indicate that, natives concurrently have social, economic and security concerns regarding refugees, while difficulties regarding security and economic integration of refugees stand out. Socio-economic characteristics of the respondents, such as the educational level and employment status, are not sufficient to explain the overall attitudes towards refugees, while they can be used to explain the awareness of the respondents and the priority of the concerns felt.

Keywords: Economic integration, immigration policy, integration policies, migrants, natives’ attitudes, perception, Syrian refugees, Turkey.

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1315 Investigation of Tearing in Hydroforming Process with Analytical Equations and Finite Element Method

Authors: H.Seidi, M.Jalali Azizpour, S.A.Zahedi

Abstract:

Today, Hydroforming technology provides an attractive alternative to conventional matched die forming, especially for cost-sensitive, lower volume production, and for parts with irregular contours. In this study the critical fluid pressures which lead to rupture in the workpiece has been investigated by theoretical and finite element methods. The axisymmetric analysis was developed to investigate the tearing phenomenon in cylindrical Hydroforming Deep Drawing (HDD). By use of obtained equations the effect of anisotropy, drawing ratio, sheet thickness and strain hardening exponent on tearing diagram were investigated.

Keywords: Hydroforming deep drawing, Pressure path, Axisymmetric analysis, Finite element simulation.

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1314 Fine-Grained Sentiment Analysis: Recent Progress

Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

Abstract:

Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially the fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, ma-chine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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1313 Does the Polysemic Nature of Energy Security Make it a 'Wicked' Problem?

Authors: Lynne Chester

Abstract:

Governments around the world are expending considerable time and resources framing strategies and policies to deliver energy security. The term 'energy security' has quietly slipped into the energy lexicon without any meaningful discourse about its meaning or assumptions. An examination of explicit and inferred definitions finds that the concept is inherently slippery because it is polysemic in nature having multiple dimensions and taking on different specificities depending on the country (or continent), timeframe or energy source to which it is applied. But what does this mean for policymakers? Can traditional policy approaches be used to address the problem of energy security or does its- polysemic qualities mean that it should be treated as a 'wicked' problem? To answer this question, the paper assesses energy security against nine commonly cited characteristics of wicked policy problems and finds strong evidence of 'wickedness'.

Keywords: Energy security, policy making, wicked problems.

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1312 Relationship of Arm Acupressure Points and Thai Traditional Massage

Authors: Boonyarat Chaleephay

Abstract:

The purpose of this research paper was to describe the relationship of acupressure points on the anterior surface of the upper limb in accordance with Applied Thai Traditional Massage (ATTM) and the deep structures located at those acupressure points. There were 2 population groups; normal subjects and cadaver specimens. Eighteen males with age ranging from 20-40 years old and seventeen females with ages ranging from 30-97 years old were studies. This study was able to obtain a fundamental knowledge concerning acupressure point and the deep structures that related to those acupressure points. It might be used as the basic knowledge for clinically applying and planning treatment as well as teaching in ATTM.

Keywords: Acupressure point (AP), Applie Thai Traditional Medicine (ATTM), Paresthesia, Numbness.

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1311 Deep Learning Based, End-to-End Metaphor Detection in Greek with Recurrent and Convolutional Neural Networks

Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

Abstract:

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: Metaphor detection, deep learning, representation learning, embeddings.

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1310 Zhou Enlai’s Impact to the Foreign Folicy of China

Authors: Nazira B. Boldurukova

Abstract:

The main aim of this article is to give the information about life and social and diplomatic work of Zhou Enlai, to prove his identity in his impact to the history of the world; to show his place in the organization of internal and foreign policy and in the peaceful international relationships of China with other countries.

Keywords: China, foreign policy of China, identity, politician, diplomacy, Zhou Enlai.

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1309 Determination and Comparison of Fabric Pills Distribution Using Image Processing and Spatial Data Analysis Tools

Authors: Lenka Techniková, Maroš Tunák, Jiří Janáček

Abstract:

This work deals with the determination and comparison of pill patterns in 2 sets of fabric samples which differ in way of pill creation. The first set contains fabric samples with the pills created by simulation on a Martindale abrasion machine, while pills in the second set originated during normal wearing and maintenance. The goal of the study is to determine whether the pattern of the fabric pills created by simulation is the same as the pattern of naturally occurring pills. The system of determination and comparison of the pills is based on image processing and spatial data analysis tools. Firstly, 3D reconstruction of the fabric surfaces with the pills is realized with using a gradient fields method. The gradient fields method creates a 3D fabric surface from a set of 4 images. Thereafter, the pills are detected in 3D fabric surfaces using image-processing tools in the MATLAB software. Determination and comparison of the pills patterns of two sets of fabric samples is based on spatial data analysis using tools in R software.

Keywords: 3D reconstruction of the surface, image analysis tools, distribution of the pills, spatial data analysis tools.

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1308 Comparison of Machine Learning and Deep Learning Algorithms for Automatic Classification of 80 Different Pollen Species

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinié

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. In this context, the automation of this task is urgent. In this work, we compare classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN and Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches.

Keywords: Image segmentation, stuck particles separation, Sobel operator, thresholding.

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1307 The Relationship between Fugacity and Stress Intensity Factor for Corrosive Environment in Presence of Hydrogen Embrittlement

Authors: A. R. Shahani, E. Mahdavi, M. Amidpour

Abstract:

Hydrogen diffusion is the main problem for corrosion fatigue in corrosive environment. In order to analyze the phenomenon, it is needed to understand their behaviors specially the hydrogen behavior during the diffusion. So, Hydrogen embrittlement and prediction its behavior as a main corrosive part of the fractions, needed to solve combinations of different equations mathematically. The main point to obtain the equation, having knowledge about the source of causing diffusion and running the atoms into materials, called driving force. This is produced by either gradient of electrical or chemical potential. In this work, we consider the gradient of chemical potential to obtain the property equation. In diffusion of atoms, some of them may be trapped but, it could be ignorable in some conditions. According to the phenomenon of hydrogen embrittlement, the thermodynamic and chemical properties of hydrogen are considered to justify and relate them to fracture mechanics. It is very important to get a stress intensity factor by using fugacity as a property of hydrogen or other gases. Although, the diffusive behavior and embrittlement event are common and the same for other gases but, for making it more clear, we describe it for hydrogen. This considering on the definite gas and describing it helps us to understand better the importance of this relation.

Keywords: Hydrogen embrittlement, Fracture mechanics, Thermodynamic, Stress intensity factor.

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1306 Productivity Effect of Urea Deep Placement Technology: An Empirical Analysis from Irrigation Rice Farmers in the Northern Region of Ghana

Authors: Shaibu Baanni Azumah, Ignatius Tindjina, Stella Obanyi, Tara N. Wood

Abstract:

This study examined the effect of Urea Deep Placement (UDP) technology on the output of irrigated rice farmers in the northern region of Ghana. Multi-stage sampling technique was used to select 142 rice farmers from the Golinga and Bontanga irrigation schemes, around Tamale. A treatment effect model was estimated at two stages; firstly, to determine the factors that influenced farmers’ decision to adopt the UDP technology and secondly, to determine the effect of the adoption of the UDP technology on the output of rice farmers. The significant variables that influenced rice farmers’ adoption of the UPD technology were sex of the farmer, land ownership, off-farm activity, extension service, farmer group participation and training. The results also revealed that farm size and the adoption of UDP technology significantly influenced the output of rice farmers in the northern region of Ghana. In addition to the potential of the technology to improve yields, it also presents an employment opportunity for women and youth, who are engaged in the deep placement of Urea Super Granules (USG), as well as in the transplantation of rice. It is recommended that the government of Ghana work closely with the IFDC to embed the UDP technology in the national agricultural programmes and policies. The study also recommends an effective collaboration between the government, through the Ministry of Food and Agriculture (MoFA) and the International Fertilizer Development Center (IFDC) to train agricultural extension agents on UDP technology in the rice producing areas of the country.

Keywords: Northern Ghana, output, irrigation rice farmers, treatment effect model, urea deep placement.

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1305 Evaluation of Energy and Environmental Aspects of Reduced Tillage Systems Applied in Maize Cultivation

Authors: E. Sarauskis, L. Masilionyte, Z. Kriauciuniene, K. Romaneckas, S. Buragiene

Abstract:

In maize growing technologies, tillage technological operations are the most time-consuming and require the greatest fuel input. Substitution of conventional tillage, involving deep ploughing, by other reduced tillage methods can reduce technological production costs, diminish soil degradation and environmental pollution from greenhouse gas emissions, as well as improve economic competitiveness of agricultural produce.

Experiments designed to assess energy and environmental aspects associated with different reduced tillage systems, applied in maize cultivation were conducted at Aleksandras Stulginskis University taking into account Lithuania’s economic and climate conditions. The study involved 5 tillage treatments: deep ploughing (DP, control), shallow ploughing (SP), deep cultivation (DC), shallow cultivation (SC) and no-tillage (NT).

Our experimental evidence suggests that with the application of reduced tillage systems it is feasible to reduce fuel consumption by 13-58% and working time input by 8.4% to nearly 3-fold, to reduce the cost price of maize cultivation technological operations, decrease environmental pollution with CO2 gas by 30 to 146 kg ha-1, compared with the deep ploughing.

Keywords: Reduced tillage, energy and environmental assessment, fuel consumption, CO2 emission, maize.

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1304 An Empirical Study on Switching Activation Functions in Shallow and Deep Neural Networks

Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

Abstract:

Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs – Sigmoid, ReLU, and Tanh – have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment on multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLU-ReLU) combination. Our results show that on using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: Activation Function, Universal Approximation function, Neural Networks, convergence.

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1303 Small Entrepreneurship Supporting Economic Policy in Georgia

Authors: G. Erkomaishvili

Abstract:

This paper discusses small entrepreneurship development strategy in Georgia and the tools and regulations that will encourage development of small entrepreneurship. The current situation in the small entrepreneurship sector, as well as factors affecting growth and decline in the sector and the priorities of state support, are studied and analyzed. The objective of this research is to assess the current situation of the sector to highlight opportunities and reveal the gaps. State support of small entrepreneurship should become a key priority in the country’s economic policy, as development of the sector will ensure social, economic and political stability. Based on the research, a small entrepreneurship development strategy is presented; corresponding conclusions are made and recommendations are developed.

Keywords: Economic policy for small entrepreneurship development, small entrepreneurship, regulations, small entrepreneurship development strategy.

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