Search results for: deep deterministic policy gradient
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1513

Search results for: deep deterministic policy gradient

1093 SNR Classification Using Multiple CNNs

Authors: Thinh Ngo, Paul Rad, Brian Kelley

Abstract:

Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: Classification, classifier fusion, CNN, Deep Learning, prediction, SNR.

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1092 DocPro: A Framework for Processing Semantic and Layout Information in Business Documents

Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

Abstract:

With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: Document processing, framework, formal definition, machine learning.

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1091 Highlighting of the Factors and Policies Affecting CO2 Emissions Level in Malaysian Transportation Sector

Authors: M. S. Indati, H. A. Bekhet

Abstract:

Global CO2 emission and increasing fuel consumption to meet energy demand has become a threat in recent decades. Effort to reduce the CO2 emission is now a matter of priority in most countries of the world including Malaysia. Transportation has been identified as the most intensive sector of carbon-based fuels and achievement of the voluntary target to meet 40% carbon intensity reduction set at the 15th Conference of the Parties (COP15) means that the emission from the transport sector must be reduced accordingly. This posed a great challenge to Malaysia and effort has to be made to embrace suitable and appropriate energy policy for sustainable energy and emission reduction of this sector. The focus of this paper is to analyze the trends of Malaysia’s energy consumption and emission of four different transport sub-sectors (road, rail, aviation and maritime). Underlying factors influencing the growth of energy consumption and emission trends are discussed. Besides, technology status towards energy efficiency in transportation sub-sectors is presented. By reviewing the existing policies and trends of energy used, the paper highlights prospective policy options towards achieving emission reduction in the transportation sector.

Keywords: CO2 Emission, Energy policy, Fuel consumption, Transportation sector, Malaysia.

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1090 Evaluation of Research in the Field of Energy Efficiency and MCA Methods Using Publications Databases

Authors: Juan Sepúlveda

Abstract:

Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: Energy efficiency, MCA, Scientometrics, trends.

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1089 Haematology and Serum Biochemical Profile of Laying Chickens Reared on Deep Litter System with or without Access to Grass or Legume Pasture under Humid Tropical Climate

Authors: E. Oke, A. O. Ladokun, J. O. Daramola, O. M. Onagbesan

Abstract:

There has been a growing interest on the effects of access to pasture on poultry health status. However, there is a paucity of data on the relative benefits of grass and legume pastures. An experiment was conducted to determine the effects of rearing systems {deep litter system (DL), deep litter with access to legumes (LP) or grass (GP) pastures} haematology and serum chemistry of ISA Brown layers. The study involved the use of two hundred and forty 12 weeks old pullets. The birds were reared until 60 weeks of age. Eighty birds were assigned to each treatment; each treatment had four replicates of 20 birds each. Blood samples (2.5 ml) were collected from the wing vein of two birds per replicate and serum chemistry and haematological parameters were determined. The results showed that there were no significant differences between treatments in all the parameters considered at 18 weeks of age. At 24 weeks old, the percentage of heterophyl (HET) in DL and LP were similar but higher than that of GP. The ratio of H:L was higher (P<0.05) in DL than those of LP and GP while LP and GP were comparable. At week 38 of age, the percentage of PCV in the birds in LP and GP were similar but the birds in DL had significantly lower level than that of GP. In the early production phase, serum total protein of the birds in LP was similar to that of GP but higher (P<0.05) than that of DL. At the peak production phase (week 38), the total protein in GP and DL were similar but significantly lower than that of LP. The albumin level in LP was greater (P<0.05) than GP but similar to that of DL. In the late production phase, the total protein in LP was significantly higher than that of DL but similar to that of GP. It was concluded that rearing chickens in either grass or legume pasture did not have deleterious effects on the health of laying chickens but improved some parameters including blood protein and HET/lymphocyte.

Keywords: Rearing systems, Stylosanthes, Cynodon serum chemistry, haematology, hen.

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1088 Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network

Authors: Jia Xin Low, Keng Wah Choo

Abstract:

This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: Convolutional neural network, discrete wavelet transform, deep learning, heart sound classification.

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1087 The Role of ICT for Income Inequality: The Model and the Simulations

Authors: Shoji Katagiri

Abstract:

This paper is to clarify the relationship between ICT and income inequality. To do so, we develop the general equilibrium model with ICT investment, obtain the equilibrium solutions, and then simulate the model with these solutions for some OECD countries. As a result, generally, during the corresponding periods we confirm that the relationship between ICT investment and income inequality is positive. In this mode, the increment of the ratio of ICT investment to the aggregated investment in stock enhances the capital’s share of income, and finally leads to income inequality such as the increase of the share of the top decile income. Although we confirm the positive relationship between ICT investment and income inequality, the upward trend for that relationship depends on the values of parameters for the making use of the simulations and these parameters are not deterministic in the magnitudes on the calculated results for the simulations.

Keywords: ICT, inequality, capital accumulation, technology.

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1086 SEM Image Classification Using CNN Architectures

Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

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1085 Emergence of New Capitalist Class and Issues of Market, Merit and Social Justice: The Business and Economics of Higher Education in India

Authors: Subramaniam Chandran

Abstract:

This paper analyses the structural changes in education sector since the introduction of liberalization policy in India. This paper explains how the so-called non-profit trusts and societies appropriated the liberalization policy and enhanced themselves as new capitalist class in higher education sector. Over the decades, the policy witnessed the role of private sector in terms of maintaining market equilibrium. The state also witnessed the incompatibility of the private sector in inculcating the values of social justice. The most important consequence of the policy is to witness the rise of new capitalist class and academic capitalism. When the state came to realize that it no longer cope up with market demands, it opens the entry of private sector in higher education. Concessions and tax exemptions were provided to the trusts and societies to establish higher education institutions. There is a basic difference between western countries and India in providing higher education by the trusts and societies. In western countries the big business houses contributed their surplus revenues to promote higher education and research as a complementary service to society and nation. In India, several entrepreneurs came up with business motive using education sector. Over the period, they accumulated wealth at the cost of students and concessions from the government. Four major results can now be identified: production of manpower in view of market demands; reduction of standards in higher education; bypassing the values of social justice; and the rise of new capitalist class from the business of education. This paper tries to substantiate these issues with the inputs from case studies.

Keywords: New capitalism, market, social justice, higher education

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1084 The Problem of Using the Calculation of the Critical Path to Solver Instances of the Job Shop Scheduling Problem

Authors: Marco Antonio Cruz-Chávez, Juan Frausto-Solís, Fernando Ramos-Quintana

Abstract:

A procedure commonly used in Job Shop Scheduling Problem (JSSP) to evaluate the neighborhoods functions that use the non-deterministic algorithms is the calculation of the critical path in a digraph. This paper presents an experimental study of the cost of computation that exists when the calculation of the critical path in the solution for instances in which a JSSP of large size is involved. The results indicate that if the critical path is use in order to generate neighborhoods in the meta-heuristics that are used in JSSP, an elevated cost of computation exists in spite of the fact that the calculation of the critical path in any digraph is of polynomial complexity.

Keywords: Job Shop, CPM, critical path, neighborhood, meta-heuristic.

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1083 Bandwidth allocation in ATM Network for different QOS Requirements

Authors: H. El-Madbouly

Abstract:

For future Broad band ISDN, Asynchronous Transfer Mode (ATM) is designed not only to support a wide range of traffic classes with diverse flow characteristics, but also to guarantee the different quality of service QOS requirements. The QOS may be measured in terms of cell loss probability and maximum cell delay. In this paper, ATM networks in which the virtual path (VP) concept is implemented are considered. By applying the Markov Deterministic process method, an efficient algorithm to compute the minimum capacity required to satisfy the QOS requirements when multiple classes of on-off are multiplexed on to a single VP. Using the result, we then proposed a simple algorithm to determine different combinations of VP to achieve the optimum of the total capacity required for satisfying the individual QOS requirements (loss- delay).

Keywords: Bandwidth allocation, Quality of services, ATMNetwork, virtual path.

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1082 Image Authenticity and Perceptual Optimization via Genetic Algorithm and a Dependence Neighborhood

Authors: Imran Usman, Asifullah Khan, Rafiullah Chamlawi, Abdul Majid

Abstract:

Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the un-watermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantization and transplantation.

Keywords: Digital watermarking, fragile watermarking, geneticalgorithm, Image authentication.

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1081 Simulating Economic Order Quantity and Reorder Point Policy for a Repairable Items Inventory System

Authors: Mojahid F. Saeed Osman

Abstract:

Repairable items inventory system is a management tool used to incorporate all information concerning inventory levels and movements for repaired and new items. This paper presents development of an effective simulation model for managing the inventory of repairable items for a production system where production lines send their faulty items to a repair shop considering the stochastic failure behavior and repair times. The developed model imitates the process of handling the on-hand inventory of repaired items and the replenishment of the inventory of new items using Economic Order Quantity and Reorder Point ordering policy in a flexible and risk-free environment. We demonstrate the appropriateness and effectiveness of the proposed simulation model using an illustrative case problem. The developed simulation model can be used as a reliable tool for estimating a healthy on-hand inventory of new and repaired items, backordered items, and downtime due to unavailability of repaired items, and validating and examining Economic Order Quantity and Reorder Point ordering policy, which would further be compared with other ordering strategies as future work.

Keywords: Inventory system, repairable items, simulation, maintenance, economic order quantity, reorder point.

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1080 Economic Neoliberalism: Property Right and Redistribution Policy

Authors: Aleksandar Savanović

Abstract:

In this paper, we will analyze the relationship between the neo-liberal concept of property rights and redistribution policy. This issue is back in the focus of interest due to the crisis 2008. The crisis has reaffirmed the influence of the state on the free-market processes. The interference of the state with property relations reopened a classical question: is it legitimate to redistribute resources of a man in favor of another man with taxes? The dominant view is that the neoliberal philosophy of natural rights is incompatible with redistributive measures. In principle, this view can be accepted. However, when we look into the details of the theory of natural rights proposed by some coryphaei of neoliberal philosophy, such as Hayek, Nozick, Buchanan and Rothbard, we can see that it is not such an unequivocal view. 

Keywords: Economic neoliberalism, natural law, property, redistribution

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1079 An Exploration of Sense of Place as Informative for Spatial Planning Guidelines: A Case Study of the Vredefort Dome World Heritage Site, South Africa

Authors: Karen Puren, Ernst Drewes, Vera Roos

Abstract:

This paper explores the sense of place in the Vredefort Dome World Heritage site, South Africa, as an essential input for the formulation of spatial planning proposals for the area. Intangible aspects such as personal and symbolic meanings of sites are currently not integrated in spatial planning in South Africa. This may have a detrimental effect on local inhabitants who have a long history with the site and built up a strong place identity. Involving local inhabitants at an early stage of the planning process and incorporating their attitudes and opinions in future intervention in the area, may also contribute to the acceptance of the legitimacy of future policy. An interdisciplinary and mixed-method research approach was followed in this study in order to identify possible ways to anchor spatial planning proposals in the identity of the place. In essence, the qualitative study revealed that inhabitants reflect a deep and personal relationship with and within the area, which contributes significantly to their sense of emotional security and selfidentity. Results include a strong conservation-orientated attitude with regard to the natural rural character of the site, especially in the inner core.

Keywords: Place identity, Sense of Place, Spatial Planning, Vredefort Dome World Heritage Site.

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1078 Effect of Atmospheric Turbulence on AcquisitionTime of Ground to Deep Space Optical Communication System

Authors: Hemani Kaushal, V.K.Jain, Subrat Kar

Abstract:

The performance of ground to deep space optical communication systems is degraded by distortion of the beam as it propagates through the turbulent atmosphere. Turbulence causes fluctuations in the intensity of the received signal which ultimately affects the acquisition time required to acquire and locate the spaceborne target using narrow laser beam. In this paper, performance of free-space optical (FSO) communication system in atmospheric turbulence has been analyzed in terms of acquisition time for coherent and non-coherent modulation schemes. Numerical results presented in graphical and tabular forms show that the acquisition time increases with the increase in turbulence level. This is true for both schemes. The BPSK has lowest acquisition time among all schemes. In non-coherent schemes, M-PPM performs better than the other schemes. With the increase in M, acquisition time becomes lower, but at the cost of increase in system complexity.

Keywords: Atmospheric Turbulence, Acquisition Time, BinaryPhase Shift Keying (BPSK), Free-Space Optical (FSO)Communication System, M-ary Pulse Position Modulation (M-PPM), Coherent/Non-coherent Modulation Schemes.

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1077 A Multi-objective Fuzzy Optimization Method of Resource Input Based on Genetic Algorithm

Authors: Tao Zhao, Xin Wang

Abstract:

With the increasing complexity of engineering problems, the traditional, single-objective and deterministic optimization method can not meet people-s requirements. A multi-objective fuzzy optimization model of resource input is built for M chlor-alkali chemical eco-industrial park in this paper. First, the model is changed into the form that can be solved by genetic algorithm using fuzzy theory. And then, a fitness function is constructed for genetic algorithm. Finally, a numerical example is presented to show that the method compared with traditional single-objective optimization method is more practical and efficient.

Keywords: Fitness function, genetic algorithm, multi-objectivefuzzy optimization, satisfaction degree membership function.

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1076 Joint Use of Factor Analysis (FA) and Data Envelopment Analysis (DEA) for Ranking of Data Envelopment Analysis

Authors: Reza Nadimi, Fariborz Jolai

Abstract:

This article combines two techniques: data envelopment analysis (DEA) and Factor analysis (FA) to data reduction in decision making units (DMU). Data envelopment analysis (DEA), a popular linear programming technique is useful to rate comparatively operational efficiency of decision making units (DMU) based on their deterministic (not necessarily stochastic) input–output data and factor analysis techniques, have been proposed as data reduction and classification technique, which can be applied in data envelopment analysis (DEA) technique for reduction input – output data. Numerical results reveal that the new approach shows a good consistency in ranking with DEA.

Keywords: Effectiveness, Decision Making, Data EnvelopmentAnalysis, Factor Analysis

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1075 Using ε Value in Describe Regular Languages by Using Finite Automata, Operation on Languages and the Changing Algorithm Implementation

Authors: Abdulmajid Mukhtar Afat

Abstract:

This paper aims at introducing nondeterministic finite automata with ε value which is used to perform some operations on languages. a program is created to implement the algorithm that converts nondeterministic finite automata with ε value (ε-NFA) to deterministic finite automata (DFA).The program is written in c++ programming language. The program inputs are FA 5-tuples from text file and then classifies it into either DFA/NFA or ε -NFA. For DFA, the program will get the string w and decide whether it is accepted or rejected. The tracking path for an accepted string is saved by the program. In case of NFA or ε-NFA automation, the program changes the automation to DFA to enable tracking and to decide if the string w exists in the regular language or not.

Keywords: Finite automata, DFA, NFA, ε-NFA, Eclose, operations on languages.

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1074 An Efficient Spam Mail Detection by Counter Technique

Authors: Raheleh Kholghi, Soheil Behnam Roudsari, Alireza Nemaney Pour

Abstract:

Spam mails are unwanted mails sent to large number of users. Spam mails not only consume the network resources, but cause security threats as well. This paper proposes an efficient technique to detect, and to prevent spam mail in the sender side rather than the receiver side. This technique is based on a counter set on the sender server. When a mail is transmitted to the server, the mail server checks the number of the recipients based on its counter policy. The counter policy performed by the mail server is based on some pre-defined criteria. When the number of recipients exceeds the counter policy, the mail server discontinues the rest of the process, and sends a failure mail to sender of the mail; otherwise the mail is transmitted through the network. By using this technique, the usage of network resources such as bandwidth, and memory is preserved. The simulation results in real network show that when the counter is set on the sender side, the time required for spam mail detection is 100 times faster than the time the counter is set on the receiver side, and the network resources are preserved largely compared with other anti-spam mail techniques in the receiver side.

Keywords: Anti-spam, Mail server, Sender side, Spam mail

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1073 The Genesis of the Anomalous Sernio Fan, Valtellina, Northern Italy

Authors: E. De Finis, P. Gattinoni, L. Scesi

Abstract:

Massive rock avalanches formed some of the largest landslide deposits on Earth and they represent one of the major geohazards in high-relief mountains. This paper interprets a very large sedimentary fan (the Sernio fan, Valtellina, Northern Italy), located 20 Km SW from Val Pola Rock avalanche (1987), as the deposit of a partial collapse of a Deep Seated Gravitational Slope Deformation (DSGSD), afterwards eroded and buried by debris flows. The proposed emplacement sequence has been reconstructed based on geomorphological, structural and mechanical evidences. The Sernio fan is actually considered anomalous with reference to the very high ratio between the fan area (≈ 4.5km2) and the basin area (≈ 3km2). The morphology of the fan area is characterised by steep slopes (dip ≈ 20%) and the fan apex is extended for 1.8 km inside the small catchment basin. This sedimentary fan was originated by a landslide that interested a part of a large deep-seated gravitational slope deformation, involving a wide area of about 55 km². The main controlling factor is tectonic and it is related to the proximity to regional fault systems and the consequent occurrence of fault weak rocks (GSI locally lower than 10 with compressive stress lower than 20MPa). Moreover, the fan deposit shows sedimentary evidences of recent debris flow events. The best current explanation of the Sernio fan involves an initial failure of some hundreds of Mm3. The run-out was quite limited because of the morphology of Valtellina’s valley floor, and the deposit filled the main valley forming a landslide dam, as confirmed by the lacustrine deposits detected upstream the fan. Nowadays the debris flow events represent the main hazard in the study area.

Keywords: Anomalous sedimentary fans, debris flow, deep seated gravitational slope deformation, Italy, rock avalanche.

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1072 Landowers' Participation Behavior on the Payment for Environmental Service (PES): Evidences from Taiwan

Authors: Wan-Yu Liu

Abstract:

To respond to the Kyoto Protocol, the policy of Payment for Environmental Service (PES), which was entitled “Plain Landscape Afforestation Program (PLAP)", was certified by Executive Yuan in Taiwan on 31 August 2001 and has been implementing for six years since 1 January 2002. Although the PLAP has received a lot of positive comments, there are still many difficulties during the process of implementation, such as insufficient technology for afforestation, private landowners- low interests in participating in PLAP, insufficient subsidies, and so on, which are potential threats that hinder the PLAP from moving forward in future. In this paper, selecting Ping-Tung County in Taiwan as a sample region and targeting those private landowners with and without intention to participate in the PLAP, respectively, we conduct an empirical analysis based on the Logit model to investigate the factors that determine whether those private landowners join the PLAP, so as to realize the incentive effects of the PLAP upon the personal decision on afforestation. The possible factors that might determine private landowner-s participation in the PLAP include landowner-s characteristics, cropland characteristics, as well as policy factors. Among them, the policy factors include afforestation subsidy amount (+), duration of afforestation subsidy (+), the rules on adjoining and adjacent areas (+), and so on, which do not reach the remarkable level in statistics though, but the directions of variable signs are consistent with the intuition behind the policy. As for the landowners- characteristics, each of age (+), education level (–), and annual household income (+) variables reaches 10% of the remarkable level in statistics; as for the cropland characteristics, each of cropland area (+), cropland price (–), and the number of cropland parcels (–) reaches 1% of the remarkable level in statistics. In light of the above, the cropland characteristics are the dominate factor that determines the probability of landowner-s participation in the PLAP. In the Logit model established by this paper, the probability of correctly estimating nonparticipants is 98%, the probability of correctly estimating the participants is 71.8%, and the probability for the overall estimation is 95%. In addition, Hosmer-Lemeshow test and omnibus test also revealed that the Logit model in this paper may provide fine goodness of fit and good predictive power in forecasting private landowners- participation in this program. The empirical result of this paper expects to help the implementation of the afforestation programs in Taiwan.

Keywords: Forestry policy, logit, afforestation subsidy, afforestation policy.

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1071 A Comprehensive and Integrated Framework for Formal Specification of Concurrent Systems

Authors: Sara Sharifi Rad, Hassan Haghighi

Abstract:

Due to important issues, such as deadlock, starvation, communication, non-deterministic behavior and synchronization, concurrent systems are very complex, sensitive, and error-prone. Thus ensuring reliability and accuracy of these systems is very essential. Therefore, there has been a big interest in the formal specification of concurrent programs in recent years. Nevertheless, some features of concurrent systems, such as dynamic process creation, scheduling and starvation have not been specified formally yet. Also, some other features have been specified partially and/or have been described using a combination of several different formalisms and methods whose integration needs too much effort. In other words, a comprehensive and integrated specification that could cover all aspects of concurrent systems has not been provided yet. Thus, this paper makes two major contributions: firstly, it provides a comprehensive formal framework to specify all well-known features of concurrent systems. Secondly, it provides an integrated specification of these features by using just a single formal notation, i.e., the Z language.

Keywords: Concurrent systems, Formal methods, Formal specification, Z language

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1070 The Dilemma of Retention in the Context of Rapidly Growing Economies Based on the Effectiveness of HRM Policies: A Case Study of Qatar

Authors: A. Qayed Al-Emadi, C. Schwabenland, B. Czarnecka

Abstract:

In 2009, the new HRM policy was implemented in Qatar for public sector organisations. The purpose of this research is to examine how Qatar’s 2009 HRM policy was significant in influencing employee retention in public organisations. The conducted study utilised quantitative methodology to analyse the data on employees’ perceptions of such HRM practices as Performance Management, Rewards and Promotion, Training and Development associated with the HRM policy in public organisations in comparison to semi-private organisations. Employees of seven public and semi-private organisations filled in the questionnaire based on the 5-point Likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Performance Management had the relationship with Employee Retention, and Rewards and Promotion influenced Job Satisfaction in public organisations. Relationship between Job Satisfaction and Employee Retention was also observed. However, no significant differences were observed in the role of HRM practices in public and semi-private organisations.

Keywords: Performance management, rewards, promotion, training and development, job satisfaction, employee retention, SHRM, configurationally perspective.

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1069 Application of the Data Distribution Service for Flexible Manufacturing Automation

Authors: Marco Ryll, Svetan Ratchev

Abstract:

This paper discusses the applicability of the Data Distribution Service (DDS) for the development of automated and modular manufacturing systems which require a flexible and robust communication infrastructure. DDS is an emergent standard for datacentric publish/subscribe middleware systems that provides an infrastructure for platform-independent many-to-many communication. It particularly addresses the needs of real-time systems that require deterministic data transfer, have low memory footprints and high robustness requirements. After an overview of the standard, several aspects of DDS are related to current challenges for the development of modern manufacturing systems with distributed architectures. Finally, an example application is presented based on a modular active fixturing system to illustrate the described aspects.

Keywords: Flexible Manufacturing, Publish/Subscribe, Plug & Produce.

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1068 Poverty: Its Causes and Solutions

Authors: Alex Hou Hong Ng, Abdul Ghani Farinda, Fock Kui Kan, Ai Ling Lim, Teo Ming Ting

Abstract:

Poverty is a multi-facet phenomenon in today’s globalised world. It is rooted in various causes and there are also multiple ways to do away with it. This paper begins with a review on the definitions and measurement of poverty and followed by discussing the various causes of poverty. This paper specifically identifies corruption, education, political instability, geographical characteristics, ineffective local governance and government policies as the causes of poverty. It then suggests possible solutions or recommendations to eradicate poverty based on the causes discussed earlier. Some of the suggestions include strengthening democratic transparency and government budget transparency, public awareness, creation of a framework for economic growth and transformation, and ways to increase the ability of the poor to raise their income.

Keywords: Economic Policy, Government Policy, Poverty Eradication, Sustainable Development.

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1067 Optimized Weight Vector for QoS Aware Web Service Selection Algorithm Using Particle Swarm Optimization

Authors: N. Arulanand, P. M. Ananth

Abstract:

Quality of Service (QoS) attributes as part of the service description is an important factor for service attribute. It is not easy to exactly quantify the weight of each QoS conditions since human judgments based on their preference causes vagueness. As web services selection requires optimization, evolutionary computing based on heuristics to select an optimal solution is adopted. In this work, the evolutionary computing technique Particle Swarm Optimization (PSO) is used for selecting a suitable web services based on the user’s weightage of each QoS values by optimizing the QoS weight vector and thereby finding the best weight vectors for best services that is being selected. Finally the results are compared and analyzed using static inertia weight and deterministic inertia weight of PSO.

Keywords: QoS, Optimization, Particle Swarm Optimization (PSO), weight vector, web services, web service selection.

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1066 Construction of Strain Distribution Profiles of EDD Steel at Elevated Temperatures

Authors: Eshwara K. Prasad, Raman R. Goud, Swadesh Kumar Singh, N. Sateesh

Abstract:

In the present work, forming limit diagrams and strain distribution profile diagrams for extra deep drawing steel at room and elevated temperatures have been determined experimentally by conducting stretch forming experiments by using designed and fabricated warm stretchforming tooling setup. With the help of forming Limit Diagrams (FLDs) and strain, distribution profile diagrams the formability of Extra Deep Drawing steel has been analyzed and co-related with mechanical properties like strain hardening COEFFICIENT (n) and normal anisotropy (r−). Mechanical properties of EDD steel from room temperature to 4500C were determined and discussed the impact of temperature on the properties like work hardening exponent (n) anisotropy (r-) and strength coefficient of the material. In addition, the fractured surfaces after stretching have undergone the some metallurgical investigations and attempt has been made to co-relate with the formability of EDD steel sheets. They are co-related and good agreement with FLDs at various temperatures.

Keywords: FLD, microhardness, strain distribution profile, stretch forming.

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1065 Deep Learning Based Fall Detection Using Simplified Human Posture

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: Fall detection, machine learning, deep learning, pose estimation, tracking.

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1064 Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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