Search results for: twin delayed deep deterministic policy gradient.

Authors: Sagaren Pillay

Abstract:

In this paper bi-annual time series data on unemployment rates (from the Labour Force Survey) are expanded to quarterly rates and linked to quarterly unemployment rates (from the Quarterly Labour Force Survey). The resultant linked series and the consumer price index (CPI) series are examined using Johansen’s cointegration approach and vector error correction modeling. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant co-integrating relationship is found to exist between the time series of unemployment rates and the CPI. Given this significant relationship, the study models this relationship using Vector Error Correction Models (VECM), one with a restriction on the deterministic term and the other with no restriction.

A formal statistical confirmation of the existence of a unique linear and lagged relationship between inflation and unemployment for the period between September 2000 and June 2011 is presented. For the given period, the CPI was found to be an unbiased predictor of the unemployment rate. This relationship can be explored further for the development of appropriate forecasting models incorporating other study variables.

Keywords: Forecasting, lagged, linear, relationship.

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Authors: Jiri F. Urbanek, Jiri Barta, Oldrich Svoboda, Jiri J. Urbanek

Abstract:

The organizations of European and Czech critical infrastructure have specific position, mission, characteristics and behaviour in European Union and Czech state/business environments, regarding specific requirements for regional and global security environments. They must respect policy of national security and global rules, requirements and standards in all their inherent and outer processes of supply - customer chains and networks. A controlling is generalized capability to have control over situational policy. This paper aims and purposes are to introduce the controlling as quite new necessary process attribute providing for critical infrastructure is environment the capability and profit to achieve its commitment regarding to the effectiveness of the quality management system in meeting customer/ user requirements and also the continual improvement of critical infrastructure organization’s processes overall performance and efficiency, as well as its societal security via continual planning improvement via DYVELOP modelling.

Keywords: Added Value, DYVELOP, Controlling, Environments, Process Approach.

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Authors: Dongliang Wang, Jun Han, Dianfu Ma, Xianqi Zhao

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Avionics software is safe-critical embedded software and its architecture is evolving from traditional federated architectures to Integrated Modular Avionics (IMA) to improve resource usability. ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Arinc653 uses two-level scheduling strategies, but current modeling tools only apply to simple problems of Arinc653 two-level scheduling, which only contain time property. In avionics industry, we are always manually allocating tasks and calculating the timing table of a real-time system to ensure it-s running as we design. In this paper we represent an automatically generating strategy which applies to the two scheduling problems with dependent constraints in Arinc653 partition run-time environment. It provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or not

Keywords: Arinc653, scheduling, task allocation, simulation.

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Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

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this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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Authors: Francis Bukola Dada, Samuel Ojo Ajayi, Babatunde Sunday Ewulo, Kehinde Oseni Saani

Abstract:

A key element in the sustainability of the soil-plant relationship in crop yield and performance is the soil's capacity to support tree crops prior to establishment. With the intention of determining the suitability and limitations of the soils of the locations, the northern and southern portions of Akure, a rainforest in Nigeria, were chosen for the suitability evaluation of land for tree crops. In the study area, 16 pedons were established with the help of the Global Positioning System (GPS), the locations were georeferenced and samples were taken from the pedons. The samples were subjected to standard physical and chemical testing. The findings revealed that soils in the research locations were deep to extremely deep, with pH ranging from highly acidic to slightly acidic (4.94 to 6.71). and that sand predominated. The soils had low levels of organic carbon, effective cation exchange capacity (ECEC), total nitrogen, and available phosphorus, whereas exchangeable cations were evaluated as low to moderate. The suitability result indicated that only Pedon 2 and Pedon 14 are currently highly suitable (S1) for the production of oil palms, while others ranged from moderately suitable to marginally suitable. Pedons 4, 12, and 16 were not suitable (N1), respectively, but other Pedons were moderately suitable (S2) and marginally suitable (S3) for the cultivation of cocoa. None of the study areas are currently highly suitable for the production of oil palms. The poor soil texture and low fertility status were the two main drawbacks found. Finally, sound management practices and soil conservation are essential for fertility sustainability.

Keywords: Cashew, cocoa, land evaluation, oil palm, soil fertility suitability.

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Authors: Gulnara N. Nabiyeva, Stephen M. Wheeler

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Geographic Information Systems (GIS) is a multipurpose computer-based tool that provides a sophisticated ability to map and analyze data on different spatial layers. However, GIS is far more easily applied in some policy areas than others. This paper seeks to determine the areas of sustainable development, including environmental, economic, and social dimensions, where GIS has been used to date to support efforts to implement the United Nations Sustainable Development Goals (SDGs), and to discuss potential areas where it might be used more. Based on an extensive analysis of published literature, we ranked the SDGs according to how frequently GIS has been used to study related policy. We found that SDG#15 “Life on Land” is most often addressed with GIS, following by SDG#11 “Sustainable Cities and Communities”, and SDG#13 “Climate Action”. On the other hand, we determined that SDG#2 “Zero Hunger”, SDG#8 “Decent Work and Economic Growth”, and SDG#16 “Peace, Justice, and Strong Institutions” are least addressed with GIS. The paper outlines some specific ways that GIS might be applied to the SDGs least linked to this tool currently.

Keywords: GIS, GIS application, sustainable community development, sustainable development goals.

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Authors: P. Mbecke

Abstract:

Developmental social welfare implemented through developmental social work is being applauded internationally as an approach that facilitates social development theory and practice. However, twenty-two years into democracy, there are no tangible evidences that the much-desired developmental social welfare approach has assisted the post-apartheid macroeconomic policy frameworks in addressing poverty and inequality, thus, the derailment of the post-apartheid development approach in South Africa. Based on the implementation research theory, and the literature review technique, this paper recognizes social work as a principal role-player in social development. It recommends the redesign and implementation of an effective developmental social welfare approach with specific strategies, programs, activities and sufficient resources aligned to and appropriate in delivering on the promises of the government’s macroeconomic policy frameworks. Such approach should be implemented by skilled and dedicated developmental social workers in order to achieve transformation in South Africa.

Keywords: Apartheid, developmental social welfare, developmental social work, inequality, poverty alleviation, social development, South Africa.

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Authors: N. Hachemi, A. Nouani, A. Benchabane

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The influence of cultivation factors such as content of ammonium sulfate, glucose and water in the culture medium and particle size of dry orange waste, on their bioconversion for pectinase production was studied using complete factorial design. A polygalacturonase (PG) was isolated using ion exchange chromatography under gradient elution 0-0,5 m/l NaCl (column equilibrate with acetate buffer pH 4,5), subsequently by sephadex G75 column chromatography was applied and the molecular weight was obtained about 51,28 KDa. Purified PG enzyme exhibits a pH and temperature optima of activity at 5 and 35°C respectively. Treatment of apple juice by purified enzyme extract yielded a clear juice, which was competitive with juice yielded by pure Sigma Aldrich Aspergillus niger enzyme.

Keywords: Bioconversion, orange wastes, optimization, pectinase.

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Authors: H. M. Haytham, E. A. Azza, E.S. Mohamed, E. G. Nesreen

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Thoracotomy is a great surgery that has serious pulmonary complications, so purpose of this study was to determine the response of diaphragmatic excursion to inspiratory muscle trainer post thoracotomy. Thirty patients of both sexes (16 men and 14 women) with age ranged from 20 to 40 years old had done thoracotomy participated in this study. The practical work was done in cardiothoracic department, Kasr-El-Aini hospital at faculty of medicine for individuals 3 days Post operatively. Patients were assigned into two groups: group A (study group) included 15 patients (8 men and 7 women) who received inspiratory muscle training by using inspiratory muscle trainer for 20 minutes and routine chest physiotherapy (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Group B (control group) included 15 patients (8 men and 7 women) who received the routine chest physiotherapy only (deep breathing, cough and early ambulation) twice daily, 3 days per week for one month. Ultrasonography was used to evaluate the changes in diaphragmatic excursion before and after training program. Statistical analysis revealed a significant increase in diaphragmatic excursion in the study group (59.52%) more than control group (18.66%) after using inspiratory muscle trainer post operatively in patients post thoracotomy. It was concluded that the inspiratory muscle training device increases diaphragmatic excursion in patients post thoracotomy through improving inspiratory muscle strength and improving mechanics of breathing and using of inspiratory muscle trainer as a method of physical therapy rehabilitation to reduce post-operative pulmonary complications post thoracotomy.

Keywords: Diaphragmatic excursion, inspiratory muscle trainer, ultrasonography, thoracotomy.

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.

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Authors: Timothy Akinwande, Eddie C. M. Hui

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Housing the urban poor has remained a challenge for many years across the world, especially in developing economies, despite the apparent research attention and policy interventions. It is apt to investigate the prevalent affordable housing (AH) provision challenges using unconventional approaches. It is pragmatic to thoroughly examine housing experts to provide supply-side solutions to AH challenges and investigate informal settlers to deduce solutions from AH demand viewpoints. This study, being the supply-side investigation of an ongoing research, interrogated housing experts to determine significant expert solutions. Focus group discussions and in-depth interviews were conducted with housing experts in Nigeria. Through descriptive, content, and systematic thematic analyses of data, major findings are that deliberate finance models designed for the urban poor are the most significant housing finance solution in developing economies. Other findings are that adequately implemented rent control policies, deliberate Public-Private Partnership (PPP) approaches like inclusionary housing and land-value capture, and urban renewal programs to enlighten and tutor the urban poor on how to earn more, spend wisely, and invest in their own better housing will effectively solve AH finance challenges. Study findings are informative for the best approaches to achieve effective, AH finance for the urban poor in Nigeria, which is indispensable for the achievement of sustainable development goals. This research’s originality lies in the exploration of experts’ opinions in relation to AH finance to produce an equation model of critical solutions to AH finance challenges. Study data are useful resources for future pro-poor housing studies. This study makes housing policy-oriented recommendations toward effective, AH for the urban poor in developing countries.

Keywords: Affordable housing, effective affordable housing, housing policy, housing research, sustainable development, urban poor.

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

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Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.

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Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

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Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: Marine sedimentology, seabed map, sediment classification, World Ocean.

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Authors: W. Munyoka, F. M. Manzira

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The purpose of this study is to analyze how varying alignment of e-Government policies in four countries in Sub-Saharan Africa Region, namely South Africa, Seychelles, Mauritius and Cape Verde lead to the success or failure of e-Government; and what should be done to ensure positive alignment that lead to e-Government project growth. In addition, the study aims to understand how various governments’ efforts in e-Government awareness campaign strategies, international cooperation, functional literacy and anticipated organizational change can influence implementation.

This study extensively explores contemporary research undertaken in the field of e-Government and explores the actual respective national ICT policies, strategies and implemented e-Government projects for in-depth comprehension of the status core. Data is analyzed qualitatively and quantitatively to reach a conclusion.

The study found that resounding successes in strategic e-Government alignment was achieved in Seychelles, Mauritius, South Africa and Cape Verde - (Ranked number 1 to 4 respectively).

The implications of the study is that policy makers in developing countries should put mechanisms in place for constant monitoring and evaluation of project implementation in line with ICT policies to ensure that e-Government projects reach maturity levels and do not die mid-way implementation as often noticed in many countries. The study recommends that countries within the region should make consented collaborative efforts and synergies with the private sector players and international donor agencies to achieve the implementation part of the set ICT policies.

Keywords: E-Government, ICT-Policy Alignment, Implementation, Sub-Saharan Africa.

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Authors: H. Anıl, G. Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations, since the geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning and time series methods, the total generation of the power plants belonging to Zorlu Doğal Electricity Generation, which has a high installed capacity in terms of geothermal, was predicted for the first one-week and first two-weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: Machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting.

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Authors: Ebere U. Okolo, Eunice C. Okpalaojiego, Chimaobi V. Okolo

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Some investors prefer to keep their money in the bank rather than invest in Small and Medium Enterprise (SME) due to the high cost of running small and medium scale enterprise in Enugu State. This cost primarily concerns multiple-taxation, enormous tax burdens, levies and charges. This study examines the effect of multiple-taxation on the investments in SMEs. The study used survey design with SME population of 80. Questionnaire was used to collect data. Simple percentages/frequencies were used to analyze the data and the research hypotheses were tested with ANOVA. It was found that multiple taxation has negative effect on SMEs investment. Furthermore, the relationship between SMEs investment and its ability to pay tax is significant. The researcher recommends that government should develop a tax policy that considers the enhancement of SMEs’ capital allowance when imposing taxes. Government should also consider a tax policy that encourages investment in SMEs by consolidating all taxes in one slot and latter disseminate to various government purses rather than having many closely related but different taxes at the same time.

Keywords: Investments, multiple taxation, small and medium enterprises.

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Authors: Toshinori Nawata

Abstract:

In this paper a nonlinear feedback control called augmented automatic choosing control (AACC) for a class of nonlinear systems with constrained input is presented. When designed the control, a constant term which arises from linearization of a given nonlinear system is treated as a coefficient of a stable zero dynamics. Parameters of the control are suboptimally selected by maximizing the stable region in the sense of Lyapunov with the aid of a genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

Keywords: Augmented automatic choosing control, nonlinear control, genetic algorithm, zero dynamics.

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Authors: Amirhossein Asadabadi, Amir Anvar

Abstract:

Small satellites have become increasingly popular recently as a means of providing educational institutes with the chance to design, construct, and test their spacecraft from beginning to the possible launch due to the low launching cost. This approach is remarkably cost saving because of the weight and size reduction of such satellites. Weight reduction could be realised by utilising electromagnetic coils solely, instead of different types of actuators. This paper describes the restrictions of using only “Electromagnetic" actuation for 3D stabilisation and how to make the magnetorquer based attitude control feasible using Fuzzy Logic Control (FLC). The design is developed to stabilize the spacecraft against gravity gradient disturbances with a three-axis stabilizing capability.

Keywords: Fuzzy, Attitude Control, Small Satellite, Fuzzy Logic Control, Electromagnetic, Magnetic Control.

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Authors: P. Vit, J. Uddin, V. Zuccato, F. Maza, E. Schievano

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Honeys are produced by Apis mellifera and stingless bees (Meliponini) in Ecuador. We studied honey produced in beeswax combs by Apis mellifera, and honey produced in pots by Geotrigona and Scaptotrigona bees. Chloroform extracts of honey were obtained for fast NMR spectra. The 1D spectra were acquired at 298 K, with a 600 MHz NMR Bruker instrument, using a modified double pulsed field gradient spin echoes (DPFGSE) sequence. Signals of 1H NMR spectra were integrated and used as inputs for PCA, PLS-DA analysis, and labelled sets of classes were successfully identified, enhancing the separation between the three groups of honey according to the entomological origin: A. mellifera, Geotrigona and Scaptotrigona. This procedure is therefore recommended for authenticity test of honey in Ecuador.

Keywords: Apis mellifera, honey, 1H NMR, entomological origin, Meliponini.

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: Deep learning, data mining, gender predication, MOOCs.

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Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

Abstract:

In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.

Keywords: Virtual routing function, NFV, resource allocation, minimum power consumption.

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Authors: R. G. Ramírez-Chavarría, C. Sánchez-Pérez, V. Argueta-Díaz

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In this paper we present the design of an optical device based on a Herriott multi-pass cell fabricated on a small sized acrylic slab for heat flux measurements using the deflection of a laser beam propagating inside the cell. The beam deflection is produced by the heat flux conducted to the acrylic slab due to a gradient in the refractive index. The use of a long path cell as the sensitive element in this measurement device, gives the possibility of high sensitivity within a small size device. We present the optical design as well as some experimental results in order to validate the device’s operation principle.

Keywords: Heat flux, herriott cell, optical beam deflection, thermal conductivity.

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Authors: Sriaroonnirun Sittha, Rotchanakitumnuai Siriluck

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This paper addresses a current problem that occurs among Thai internet service providers with regard to bandwidth network quality management. The IPSTAR department of Telecom Organization of Thailand public company (TOT); the largest internet service provider in Thailand, is the case study to analyze the problem that exists. The Internet bandwidth network quality management (iBWQM) framework is mainly applied to the problem that has been found. Bandwidth management policy (BMP) and quality of service (QoS) are two antecedents of iBWQM. This paper investigates internet user behavior, marketing demand and network operation views in order to determine bandwidth management policy (e.g. quota management, scheduling and malicious management). The congestion of bandwidth is also analyzed to enhance quality of service (QoS). Moreover, the iBWQM framework is able to improve the quality of service and increase bandwidth utilization, minimize complaint rate concerns to slow speed, and provide network planning guidelines through Thai Internet services providers.

Keywords: Internet bandwidth management, Internet serviceprovider, Internet usage behavior, Quality of Service.

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Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

Abstract:

This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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Authors: M. Azadi, M. Kalhor

Abstract:

Excavation of shallow tunnels such as subways in urban areas plays a significant role as a life line and investigation of the soil behavior against tunnel construction is one of the vital subjects studied in the geotechnical scope. Nowadays, urban tunnels are mostly drilled by T.B.Ms and changing the applied forces to tunnel lining is one of the most risky matters while drilling tunnels by these machines. Variation of soil cementation can change the behavior of these forces in the tunnel lining. Therefore, this article is designed to assess the impact of tunnel excavation in different soils and several amounts of cementation on applied loads to tunnel lining under static and dynamic loads. According to the obtained results, changing the cementation of soil will affect the applied loadings to the tunnel envelope significantly. It can be determined that axial force in tunnel lining decreases considerably when soil cementation increases. Also, bending moment and shear force in tunnel lining decreases as the soil cementation increases and causes bending and shear behavior of the segments to improve. Based on the dynamic analyses, as cohesion factor in soil increases, bending moment, axial and shear forces of segments decrease but lining behavior of the tunnel is the same as static state. The results show that decreasing the overburden applied to lining caused by cementation is different in two static and dynamic states.

Keywords: Tunnel, Soil cementation, Static, Dynamic.

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Authors: Khaled Ramadan Elbeydi

Abstract:

This study is carried out to provide an insight into the analysis of the impact of selected macro-economic variables on gross fixed capital formation in Libya using annual data over the period (1970-2010). The importance of this study comes from the ability to show the relative important factors that impact the Libyan gross fixed capital formation. This understanding would give indications to decision makers on which policy they must focus to stimulate the economy. An Autoregressive Distributed Lag (ARDL) modeling process is employed to investigate the impact of the Gross Domestic Product, Monetary Base and Trade Openness on Gross Fixed Capital Formation in Libya. The results of this study reveal that there is an equilibrium relationship between capital formation and its determinants. The results also indicate that GDP and trade openness largely explain the pattern of capital formation in Libya. The findings and recommendations provide vital information relevant for policy formulation and implementation aimed to improve capital formation in Libya.

Keywords: ARDL, Bounds test, capital formation, Cointegration, Libya.

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Authors: Muhammad T. Alam, Zheng Da Wu

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In this paper, we provide complete end-to-end delay analyses including the relay nodes for instant messages. Message Session Relay Protocol (MSRP) is used to provide congestion control for large messages in the Instant Messaging (IM) service. Large messages are broken into several chunks. These chunks may traverse through a maximum number of two relay nodes before reaching destination according to the IETF specification of the MSRP relay extensions. We discuss the current solutions of sending large instant messages and introduce a proposal to reduce message flows in the IM service. We consider virtual traffic parameter i.e., the relay nodes are stateless non-blocking for scalability purpose. This type of relay node is also assumed to have input rate at constant bit rate. We provide a new scheduling policy that schedules chunks according to their previous node?s delivery time stamp tags. Validation and analysis is shown for such scheduling policy. The performance analysis with the model introduced in this paper is simple and straight forward, which lead to reduced message flows in the IM service.

Keywords: Instant messaging, stateless, chunking, MSRP.

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Authors: Sayed Reza Hashemi, Amir Heidarinasab

Abstract:

Spent Sulfidic Caustic was biologically treated and regenerated for reusing by Thiobacillus denitrificans bacteria, sulfide content oxidized and RSNa reduced dramatically.PH in this test was 11.8 and no neutralization has been done on spent caustic, so spent caustic as the most difficult of industrial wastes to dispose could be regenerate and reuse instead of disposing to sea or deep wells

Keywords: Spent Caustic, Thiobacillus denitrificans, Bioregeneration

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Authors: Toshihiko Matsuka, James E. Corter

Abstract:

Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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Authors: Xingyu Pan, Laure Tougne

Abstract:

For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.

Keywords: Coin, detection, character recognition, topology.

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