Search results for: twin delayed deep deterministic policy gradient.
Commenced in January 2007
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Edition: International
Paper Count: 1666

Search results for: twin delayed deep deterministic policy gradient.

1156 Variational Iteration Method for Solving Systems of Linear Delay Differential Equations

Authors: Sara Barati, Karim Ivaz

Abstract:

In this paper, using a model transformation approach a system of linear delay differential equations (DDEs) with multiple delays is converted to a non-delayed initial value problem. The variational iteration method (VIM) is then applied to obtain the approximate analytical solutions. Numerical results are given for several examples involving scalar and second order systems. Comparisons with the classical fourth-order Runge-Kutta method (RK4) verify that this method is very effective and convenient.

Keywords: Variational iteration method, delay differential equations, multiple delays, Runge-Kutta method.

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1155 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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1154 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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1153 Numerical Analyze of Corona Discharge on HVDC Transmission Lines

Authors: H. Nouri, A. Tabbel, N. Douib, H. Aitsaid, Y. Zebboudj

Abstract:

This study and the field test comparisons were carried out on the Algerian Derguna – Setif transmission systems. The transmission line of normal voltage 225 kV is 65 km long, transported and uses twin bundle conductors protected with two shield wires of transposed galvanized steel. An iterative finite-element method is used to solve Poisons equation. Two algorithms are proposed for satisfying the current continuity condition and updating the space-charge density. A new approach to the problem of corona discharge in transmission system has been described in this paper. The effect of varying the configurations and wires number is also investigated. The analysis of this steady is important in the design of HVDC transmission lines. The potential and electric field have been calculating in locations singular points of the system.

Keywords: Corona discharge, Electric field, Finite element method, HVDC.

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1152 Response Surface Based Optimization of Toughness of Hybrid Polyamide 6 Nanocomposites

Authors: E. Hajizadeh, H. Garmabi

Abstract:

Toughening of polyamide 6 (PA6)/ Nanoclay (NC) nanocomposites with styrene-ethylene/butadiene-styrene copolymer (SEBS) using maleated styrene-ethylene/butadiene-styrene copolymer (mSEBS)/ as a compatibilizer were investigated by blending them in a co-rotating twin-screw extruder. Response surface method of experimental design was used for optimizing the material and processing parameters. Effect of four factors, including SEBS, mSEBS and NC contents as material variables and order of mixing as a processing factor, on toughness of hybrid nanocomposites were studied. All the prepared samples showed ductile behavior and low temperature Izod impact toughness of some of the hybrid nanocomposites demonstrated 900% improvement compared to the PA6 matrix while the modulus showed maximum enhancement of 20% compared to the pristine PA6 resin.

Keywords: Hybrid nanocomposites, PA6, SEBS rubber, toughness.

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1151 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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1150 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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1149 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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1148 Improved Robust Stability and Stabilization Conditions of Discrete-time Delayed System

Authors: Zixin Liu

Abstract:

The problem of robust stability and robust stabilization for a class of discrete-time uncertain systems with time delay is investigated. Based on Tchebychev inequality, by constructing a new augmented Lyapunov function, some improved sufficient conditions ensuring exponential stability and stabilization are established. These conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. Compared with some previous results derived in the literature, the new obtained criteria have less conservatism. Two numerical examples are provided to demonstrate the improvement and effectiveness of the proposed method.

Keywords: Robust stabilization, robust stability, discrete-time system, time delay.

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1147 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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1146 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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1145 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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1144 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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1143 A Hybrid Data Mining Method for the Medical Classification of Chest Pain

Authors: Sung Ho Ha, Seong Hyeon Joo

Abstract:

Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of chest pain diseases.

Keywords: Data mining, medical decisions, medical domainknowledge, chest pain.

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1142 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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1141 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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1140 New Approaches on Stability Analysis for Neural Networks with Time-Varying Delay

Authors: Qingqing Wang, Shouming Zhong

Abstract:

Utilizing the Lyapunov functional method and combining linear matrix inequality (LMI) techniques and integral inequality approach (IIA) to analyze the global asymptotic stability for delayed neural networks (DNNs),a new sufficient criterion ensuring the global stability of DNNs is obtained.The criteria are formulated in terms of a set of linear matrix inequalities,which can be checked efficiently by use of some standard numercial packages.In order to show the stability condition in this paper gives much less conservative results than those in the literature,numerical examples are considered.

Keywords: Neural networks, Globally asymptotic stability , LMI approach , IIA approach , Time-varying delay.

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1139 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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1138 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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1137 Perspectives on Sustainable Bioeconomy in the Baltic Sea Region

Authors: Susanna Vanhamäki, Gabor Schneider, Kati Manskinen

Abstract:

‘Bioeconomy’ is a complex concept that cuts across many sectors and covers several policy areas. To achieve an overall understanding and support a successful bioeconomy, a cross-sectorial approach is necessary. In practice, due to the concept’s wide scope and varying international approaches, fully understanding bioeconomy is challenging on policy level. This paper provides a background of the topic through an analysis of bioeconomy strategies in the Baltic Sea region. Expert interviews and a small survey were conducted to discover the current and intended focuses of these countries’ bioeconomy sectors. The research shows that supporting sustainability is one of the keys in developing the future bioeconomy. The results highlighted that the bioeconomy has to be sustainable and based on circular economy principles. Currently, traditional bioeconomy sectors like food, wood, fish & waters as well as fuel & energy, which are in the core of national bioeconomy strategies, are best known and are considered more relevant than other bioeconomy industries. However, there is increasing potential for novel sectors, such as textiles and pharmaceuticals. The present research indicates that the opportunities presented by these bioeconomy sectors should be recognised and promoted. Education, research and innovation can play key roles in developing transformative and sustainable improvements in primary production and renewable resources. Furthermore, cooperation between businesses and educators is important.

Keywords: Bioeconomy, circular economy, policy, strategy.

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1136 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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1135 A Recognition Method of Ancient Yi Script Based on Deep Learning

Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

Abstract:

Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: Recognition, CNN, convolutional neural network, Yi character, divergence.

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1134 Electric Vehicle Market Penetration Impact on Greenhouse Gas Emissions for Policy-Making: A Case Study of United Arab Emirates

Authors: Ahmed Kiani

Abstract:

The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: Electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations.

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1133 Effective Implementation of Burst SegmentationTechniques in OBS Networks

Authors: A. Abid, F. M. Abbou, H. T. Ewe

Abstract:

Optical Bursts Switching (OBS) is a relatively new optical switching paradigm. Contention and burst loss in OBS networks are major concerns. To resolve contentions, an interesting alternative to discarding the entire data burst is to partially drop the burst. Partial burst dropping is based on burst segmentation concept that its implementation is constrained by some technical challenges, besides the complexity added to the algorithms and protocols on both edge and core nodes. In this paper, the burst segmentation concept is investigated, and an implementation scheme is proposed and evaluated. An appropriate dropping policy that effectively manages the size of the segmented data bursts is presented. The dropping policy is further supported by a new control packet format that provides constant transmission overhead.

Keywords: Burst length, Burst Segmentation, Optical BurstSwitching.

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1132 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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1131 Israeli Households Caring for Children and Adults with Intellectual and Developmental Disabilities: An Explorative Study

Authors: Ayelet Gur

Abstract:

Background: In recent years we are witnessing a welcome trend in which more children/persons with disabilities are living at home with their families and within their communities. This trend is related to various policy innovations as the UN Convention on the Rights of People with Disabilities that reflect a shift from the medical-institutional model to a human rights approach. We also witness the emergence of family centered approaches that perceive the family and not just the individual with the disability as a worthy target of policy planning, implementation and evaluation efforts. The current investigation aims to explore economic, psychological and social factors among households of families of children or adults with intellectual disabilities in Israel and to present policy recommendation. Methods: A national sample of 301 households was recruited through the education and employment settings of persons with intellectual disability. The main caregiver of the person with the disability (a parent) was interviewed. Measurements included the income and expense surveys; assets and debts questionnaire; the questionnaire on resources and stress; the social involvement questionnaire and Personal Wellbeing Index. Results: Findings indicate significant gaps in financial circumstances between households of families of children with intellectual disabilities and households of the general Israeli society. Households of families of children with intellectual disabilities report lower income and higher expenditures and loans than the general society. They experience difficulties in saving and coping with unexpected expenses. Caregivers (the parents) experience high stress, low social participation, low financial support from family, friend and non-governmental organizations and decreased well-being. They are highly dependent on social security allowances which constituted 40% of the household's income. Conclusions: Households' dependency on social security allowances may seem contradictory to the encouragement of persons with intellectual disabilities to favor independent living in light of the human rights approach to disability. New policy should aim at reducing caregivers' stress and enhance their social participation and support, with special emphasis on families of lower socio-economic status. Finally, there is a need to continue monitoring the economic and psycho-social needs of households of families of children with intellectual disabilities and other developmental disabilities.

Keywords: Disability policy, family policy, intellectual and developmental disabilities, Israel, households study, parents of children with disabilities.

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1130 End-to-End Pyramid Based Method for MRI Reconstruction

Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: Accelerate MRI scans, image reconstruction, pyramid network, deep learning.

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1129 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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1128 Analysis of Liquid Nitrogen Spray Atomization Characteristics by Internal-Mixing Atomizers

Authors: Zhang Lei, Liu Gaotong

Abstract:

The atomization effect is an important factor of the heat transfer of liquid nitrogen spray. In this paper, two kinds of internal-mixing twin-fluid atomizers were design. According to the fracture theory and fluid mechanics, the model is established to simulate atomization effect. The results showed that: Internal-mixing atomizers, with the liquid nitrogen atomization size from 20um to 40um, have superior performance. Y-jet atomizer spray speed is greater than Multi-jet atomizer, and it can improve the efficiency of heat transfer between the liquid nitrogen and its spray object. Multi-jet atomizer atomization cone angle is about 30°, Y-jet atomizer atomization cone angle is about 20°. During atomizer selection, the size of the heat transfer area should be considered.

Keywords: Atomization, two-phase flow, atomizer, heat transfer.

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1127 Nonlinear Controller for Fuzzy Model of Double Inverted Pendulums

Authors: I. Zamani, M. H. Zarif

Abstract:

In this paper a method for designing of nonlinear controller for a fuzzy model of Double Inverted Pendulum is proposed. This system can be considered as a fuzzy large-scale system that includes offset terms and disturbance in each subsystem. Offset terms are deterministic and disturbances are satisfied a matching condition that is mentioned in the paper. Based on Lyapunov theorem, a nonlinear controller is designed for this fuzzy system (as a model reference base) which is simple in computation and guarantees stability. This idea can be used for other fuzzy large- scale systems that include more subsystems Finally, the results are shown.

Keywords: Controller, Fuzzy Double Inverted Pendulums, Fuzzy Large-Scale Systems, Lyapunov Stability.

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