Search results for: agent oriented architecture
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1785

Search results for: agent oriented architecture

375 Design of Non-Blocking and Rearrangeable Modified Banyan Network with Electro-Optic MZI Switching Elements

Authors: Ghanshyam Singh, Tirtha Pratim Bhattacharjee, R. P. Yadav, V. Janyani

Abstract:

Banyan networks are really attractive for serving as the optical switching architectures due to their unique properties of small depth and absolute signal loss uniformity. The fact has been established that the limitations of blocking nature and the nonavailability of proper connections due to non-rearrangeable property can be easily ruled out using electro-optic MZI switches as basic switching elements. Combination of the horizontal expansion and vertical stacking of optical banyan networks is an appropriate scheme for constructing non-blocking banyan-based optical switching networks. The interconnected banyan switching fabrics (IBSF) have been considered and analyzed to best serve the purpose of optical switching with electro-optic MZI basic elements. The cross/bar state interchange for the switches has been facilitated by appropriate voltage switching or the by the switching of operating wavelength. The paper is dedicated to the modification of the basic switching element being used as well as the architecture of the switching network.

Keywords: MZI switch, Banyan network, Reconfigurable switches.

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374 Biosensor Design through Molecular Dynamics Simulation

Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

Abstract:

The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structureprocess- property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: Biosensor, design, DNA, molecular dynamics simulation.

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373 Using Automated Database Reverse Engineering for Database Integration

Authors: M. R. Abbasifard, M. Rahgozar, A. Bayati, P. Pournemati

Abstract:

One important problem in today organizations is the existence of non-integrated information systems, inconsistency and lack of suitable correlations between legacy and modern systems. One main solution is to transfer the local databases into a global one. In this regards we need to extract the data structures from the legacy systems and integrate them with the new technology systems. In legacy systems, huge amounts of a data are stored in legacy databases. They require particular attention since they need more efforts to be normalized, reformatted and moved to the modern database environments. Designing the new integrated (global) database architecture and applying the reverse engineering requires data normalization. This paper proposes the use of database reverse engineering in order to integrate legacy and modern databases in organizations. The suggested approach consists of methods and techniques for generating data transformation rules needed for the data structure normalization.

Keywords: Reverse Engineering, Database Integration, System Integration, Data Structure Normalization

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372 Apoptosis Activity of Persea declinata (Bl.) Kosterm Bark Methanolic Crude Extract

Authors: P. Narrima, C. Y. Looi, M. A. Mohd, H. M. Ali

Abstract:

Persea declinata (Bl.) Kosterm is a member of the Lauraceae family, widely distributed in Southeast Asia. It is from the same genus with avocado (Persea americana Mill), which is widely consumed as food and for medicinal purposes. In the present study, we examined the anticancer properties of Persea declinata (Bl.) Kosterm bark methanolic crude extract (PDM). PDM exhibited a potent antiproliferative effect in MCF-7 human breast cancer cells, with an IC50 value of 16.68 .g/mL after 48h of treatment. We observed that PDM caused cell cycle arrest and subsequent apoptosis in MCF-7 cells, as exhibited by increased population at G0/G1 phase, higher lactate dehydrogenase (LDH) release, and DNA fragmentation. Mechanistic studies showed that PDM caused significant elevation in ROS production, leading to perturbation of mitochondrial membrane potential, cell permeability, and activation of caspases-3/7. On the other hand, real-time PCR and Western blot analysis showed that PDM treatment increased the expression of the proapoptotic molecule, Bax, but decreased the expression of prosurvival proteins, Bcl-2 and Bcl-xL, in a dose-dependent manner. These findings imply that PDM could inhibit proliferation in MCF-7 cells via cell cycle arrest and apoptosis induction, indicating its potential as a therapeutic agent worthy of further development.

Keywords: Antiproliferative, apoptosis, MCF-7 human breast cancer, Persea declinata.

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371 Holistic Simulation-Based Impact Analysis Framework for Sustainable Manufacturing

Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

Abstract:

The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: Life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development.

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370 Enhancing Thermal Efficiency of Double Skin Façade Buildings in Semi-Arid Climate

Authors: Farid Vahedi

Abstract:

There is a great deal of interest in constructing Double Skin Facade (DSF) structures which are considered as modern movement in field of Energy Conservation, renewable energies, and Architecture design. This trend provides many conclusive alternatives which are frequently associated with sustainable building. In this paper a building with Double Skin Facade is considered in the semiarid climate of Tehran, Iran, in order to consider the DSF-s performance during hot seasons. Mathematical formulations calculate solar heat gain by the external skin. Moreover, Computational Fluid Dynamics (CFD) simulations were performed on the case study building to enhance effectiveness of the facade. The conclusion divulged difference of gained energy by the cavity and room with and without blind and louvers. Some solutions were introduced to surge the performance of natural ventilation by plunging the cooling loads in summer.

Keywords: Double Skin Façade Buildings, Energy Conservation, Renewable Energy, Natural Ventilation, Semi-arid Climate.

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369 The Influence of Islamic Arts on Omani Weaving Motifs

Authors: Zahra Ahmed Al-Zadjali

Abstract:

The influence of Islam on arts can be found primarily in calligraphy, arabesque designs and architecture. Also, geometric designs were used quite extensively. Muslim craftsmen produced stunning designs based on simple geometric principles and traditional motifs which were used to decorate many surfaces. The idea of interlacing simple rectilinear lines to form the patterns impressed Arabs. Nomads of Persia, Turks and Mongols were equally impressed with the designs so they begin to use them in their homes in carpet weaving. Islamic designs, motifs and colours which were used became common place and served to influence people’s tastes. Modern life style and contemporary products have changed the style of people’s daily lives, however, people still long for the nomadic way of life. This is clearly reflected in people’s homes. In a great many Muslim homes, Islamic decorative motifs can be seen along with traditional ‘Bedouin’ style furnishing, especially in homes of the Arabian Peninsula.

Keywords: Cultural heritage, textile design, Islamic art, motifs.

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368 Evolutionary Techniques Based Combined Artificial Neural Networks for Peak Load Forecasting

Authors: P. Subbaraj, V. Rajasekaran

Abstract:

This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.

Keywords: Combined ANN, Evolutionary Programming, Particle Swarm Optimization, Genetic Algorithm and Peak load forecasting.

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367 Pattern Recognition as an Internalized Motor Programme

Authors: M. Jändel

Abstract:

A new conceptual architecture for low-level neural pattern recognition is presented. The key ideas are that the brain implements support vector machines and that support vectors are represented as memory patterns in competitive queuing memories. A binary classifier is built from two competitive queuing memories holding positive and negative valence training examples respectively. The support vector machine classification function is calculated in synchronized evaluation cycles. The kernel is computed by bisymmetric feed-forward networks feed by sensory input and by competitive queuing memories traversing the complete sequence of support vectors. Temporary summation generates the output classification. It is speculated that perception apparatus in the brain reuses structures that have evolved for enabling fluent execution of prepared action sequences so that pattern recognition is built on internalized motor programmes.

Keywords: Competitive queuing model, Olfactory system, Pattern recognition, Support vector machine, Thalamus

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366 A Real-Time Simulation Environment for Avionics Software Development and Qualification

Authors: U. Tancredi, D. Accardo, M. Grassi, G. Fasano, A. E. Tirri, A. Vitale, N. Genito, F. Montemari, L. Garbarino

Abstract:

The development of guidance, navigation and control algorithms and avionic procedures requires the disposability of suitable analysis and verification tools, such as simulation environments, which support the design process and allow detecting potential problems prior to the flight test, in order to make new technologies available at reduced cost, time and risk. This paper presents a simulation environment for avionic software development and qualification, especially aimed at equipment for general aviation aircrafts and unmanned aerial systems. The simulation environment includes models for short and medium-range radio-navigation aids, flight assistance systems, and ground control stations. All the software modules are able to simulate the modeled systems both in fast-time and real-time tests, and were implemented following component oriented modeling techniques and requirement based approach. The paper describes the specific models features, the architectures of the implemented software systems and its validation process. Performed validation tests highlighted the capability of the simulation environment to guarantee in real-time the required functionalities and performance of the simulated avionics systems, as well as to reproduce the interaction between these systems, thus permitting a realistic and reliable simulation of a complete mission scenario.

Keywords: ADS-B, avionics, NAVAIDs, real time simulation, TCAS, UAS ground control station.

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365 The Quality of Public Space in Mexico City: Current State and Trends

Authors: Mildred Moreno Villanueva

Abstract:

Public space is essential to strengthen the social and urban fabric and the social cohesion; there lies the importance of its study. Hence, the aim of this paper is to analyze the quality of public space in the XXI century in both quantitative and qualitative terms. In this article, the concept of public space includes open spaces such as parks, public squares and walking areas. To make this analysis, we take Mexico City as the case study. It has a population of nearly 9 million inhabitants and is composed of sixteen boroughs. For this analysis, we consider both existing public spaces and the government intervention for building and improving new and existent public spaces. Results show that on the one hand, quantitatively there is not an equitable distribution of public spaces due to both the growth of the city itself as well as due to the absence of political will to create public spaces. Another factor is the evolution of this city, which has been growing merely in a “patched pattern”, where public space has played no role at all with a total absence of urban design. On the other hand, qualitatively, even the boroughs with the most public spaces have not shown interest in making these spaces qualitatively inclusive and open to the general population aiming for integration. Therefore, urban projects that privatize public space seem to be the rule, rather than a rehabilitation effort of the existent public spaces. Hence, state intervention should reinforce its role as an agent of social change acting in benefit of the majority of the inhabitants with the promotion of more inclusive public spaces.

Keywords: Exclusion, inclusion, Mexico City, public space.

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364 The Influence of Gender on Job-Competencies Requirements of Chemical-Based Industries and Undergraduate-Competencies Acquisition of Chemists in South West, Nigeria

Authors: Rachael Olatoun Okunuga

Abstract:

Developing young people’s employability is a key policy issue for ensuring their successful transition to the labour market and their access to career oriented employment. The youths of today irrespective of their gender need to acquire the knowledge, skills and attitudes that will enable them to create or find jobs as well as cope with unpredictable labour market changes throughout their working lives. In a study carried out to determine the influence of gender on job-competencies requirements of chemical-based industries and undergraduate-competencies acquisition by chemists working in the industries, all chemistry graduates working in twenty (20) chemical-based industries that were randomly selected from six sectors of chemical-based industries in Lagos and Ogun States of Nigeria were administered with Job-competencies required and undergraduate-competencies acquired assessment questionnaire. The data were analysed using means and independent sample t-test. The findings revealed that the population of female chemists working in chemical-based industries is low compared with the number of male chemists; furthermore, job-competencies requirements are found not to be gender biased while there is no significant difference in undergraduate-competencies acquisition of male and female chemists. This suggests that females should be given the same opportunity of employment in chemical-based industries as their male counterparts. The study also revealed the level of acquisition of undergraduate competencies as related to the needs of chemicalbased industries.

Keywords: Acquired, attitude, employability, knowledge, required, skill.

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363 Co-Composting of Poultry Manure with Different Organic Amendments

Authors: M. E. Silva, I. Brás

Abstract:

To study the influence of different organic amendments on the quality of poultry manure compost, three pilot composting trials were carried out with different mixes: poultry manure/carcasse meal/ashes/grape pomace (Pile 1), poultry manure/ cellulosic sludge (Pile 2) and poultry manure (Pile 3). For all piles, wood chips were applied as bulking agent. The process was monitored, over time, by evaluating standard physical and chemical parameters, such as, pH, electric conductivity, moisture, organic matter and ash content, total carbon and total nitrogen content, carbon/nitrogen ratio (C/N) and content in mineral elements. Piles 1 and 2 reached a thermophilic phase, however having different trends. Pile 1 reached this phase earlier than Pile 2. For both, the pH showed a slight alkaline character and the electric conductivity was lower than 2 mS/cm. Also, the initial C/N value was 22 and reached values lower than 15 at the end of composting process. The total N content of the Pile 1 increased slightly during composting, in contrast with the others piles. At the end of composting process, the phosphorus content ranged between 54 and 236 mg/kg dry matter, for Pile 2 and 3, respectively. Generally, the Piles 1 and 3 exhibited similar heavy metals content. This study showed that organic amendments can be used as carbon source, given that the final composts presented parameters within the range of those recommended in the 2nd Draft of EU regulation proposal (DG Env.A.2 2001) for compost quality.

Keywords: Co-composting, compost quality, organic amendments, poultry manure.

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362 The Antidiabetic Properties of Indonesian Swietenia mahagoni in Alloxan-Induced Diabetic Rats

Authors: T. Wresdiyati, S. Sa’diah, A. Winarto

Abstract:

Diabetes mellitus (DM) is a metabolic disease that can be indicated by the high level of blood glucose. The objective of this study was to observe the antidiabetic properties of ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed on the profile of pancreatic superoxide dismutase and β-cells in the alloxan- experimental diabetic rats. The Swietenia mahagoni seed was obtained from Leuwiliang-Bogor, Indonesia. Extraction of Swietenia mahagoni was done by using ethanol with maceration methods. A total of 25 male Sprague dawley rats were divided into five groups; (a) negative control group, (b) positive control group (DM), (c) DM group that was treated with Swietenia mahagoni seed extract, (d) DM group that was treated with acarbose, and (e) non-DM group that was treated with Swietenia mahagoni seed extract. The DM groups were induced by alloxan (110 mg/kgBW). The extract was orally administrated to diabetic rats 500 mg/kg/BW/day for 28 days. The extract showed hypoglycemic effect, increased body weight, increased the content of superoxide dismutase in the pancreatic tissue, and delayed the rate of β-cells damage of experimental diabetic rats. These results suggested that the ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed could be proposed as a potential anti-diabetic agent.

Keywords: β-cell, diabetes mellitus, superoxide dismutase, Swietenia mahagoni.

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361 Third Order Current-mode Quadrature Sinusoidal Oscillator with High Output Impedances

Authors: Kritphon Phanruttanachai, Winai Jaikla

Abstract:

This article presents a current-mode quadrature oscillator using differential different current conveyor (DDCC) and voltage differencing transconductance amplifier (VDTA) as active elements. The proposed circuit is realized fro m a non-inverting lossless integrator and an inverting second order low-pass filter. The oscillation condition and oscillation frequency can be electronically/orthogonally controlled via input bias currents. The circuit description is very simple, consisting of merely 1 DDCC, 1 VDTA, 1 grounded resistor and 3 grounded capacitors. Using only grounded elements, the proposed circuit is then suitable for IC architecture. The proposed oscillator has high output impedance which is easy to cascade or dive the external load without the buffer devices. The PSPICE simulation results are depicted, and the given results agree well with the theoretical anticipation. The power consumption is approximately 1.76mW at ±1.25V supply voltages.

Keywords: Current-mode, oscillator, integrated circuit, DDCC, VDTA

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360 Outsourcing the Front End of Innovation

Authors: B. Likar, K. Širok

Abstract:

The paper presents a new method for efficient innovation process management. Even though the innovation management methods, tools and knowledge are well established and documented in literature, most of the companies still do not manage it efficiently. Especially in SMEs the front end of innovation - problem identification, idea creation and selection - is often not optimally performed. Our eMIPS methodology represents a sort of "umbrella methodology" - a well-defined set of procedures, which can be dynamically adapted to the concrete case in a company. In daily practice, various methods (e.g. for problem identification and idea creation) can be applied, depending on the company's needs. It is based on the proactive involvement of the company's employees supported by the appropriate methodology and external experts. The presented phases are performed via a mixture of face-to-face activities (workshops) and online (eLearning) activities taking place in eLearning Moodle environment and using other e-communication channels. One part of the outcomes is an identified set of opportunities and concrete solutions ready for implementation. The other also very important result is connected to innovation competences for the participating employees related with concrete tools and methods for idea management. In addition, the employees get a strong experience for dynamic, efficient and solution oriented managing of the invention process. The eMIPS also represents a way of establishing or improving the innovation culture in the organization. The first results in a pilot company showed excellent results regarding the motivation of participants and also as to the results achieved.

Keywords: Creativity, distance learning, front end, innovation, problem.

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359 Evaluation of the MCFLIRT Correction Algorithm in Head Motion from Resting State fMRI Data

Authors: V. Sacca, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: Head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI.

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358 Synthesizing an Artificial Loess for Geotechnical Investigations of Collapsible Soil Behavior

Authors: Hamed Sadeghi, Pouya A. Panahi, Hamed Nasiri, Mohammad Sadeghi

Abstract:

Collapsible soils like loess comprise an important category of problematic soils for construction purposes and sustainable development. As a result, research on both geological and geotechnical aspects of this type of soil have been in progress for decades. However, considerable natural variability in physical properties of in-situ loess strata even in a single block sample challenges the fundamental laboratory investigations. The reason behind this is that it is somehow impossible to remove the effect of a specific factor like void ratio from fair comparisons to come with a reliable conclusion. In order to cope with this limitation, two types of artificially made dispersive and calcareous loess are introduced which can be easily reproduced in any soil mechanics laboratory provided that all its compositions are known and controlled. The collapse potential is explored for a variety of soil water salinity and lime content and comparisons are made against the natural soil behavior. Trends are reported for the influence of pore water salinity on collapse potential under different osmotic flow conditions. The most important advantage of artificial loess is the ease of controlling cementing agent content like calcite or dispersive potential for studying their influence on mechanical soil behavior.

Keywords: Artificial loess, unsaturated soils, collapse potential, dispersive clays, laboratory tests.

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357 Towards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

Abstract:

Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: Feature recognition, automation, sheet metal manufacturing, CAM, CAD.

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356 Natural Language Database Interface for Selection of Data Using Grammar and Parsing

Authors: N. D. Karande, G. A. Patil

Abstract:

Databases have become ubiquitous. Almost all IT applications are storing into and retrieving information from databases. Retrieving information from the database requires knowledge of technical languages such as Structured Query Language (SQL). However majority of the users who interact with the databases do not have a technical background and are intimidated by the idea of using languages such as SQL. This has led to the development of a few Natural Language Database Interfaces (NLDBIs). A NLDBI allows the user to query the database in a natural language. This paper highlights on architecture of new NLDBI system, its implementation and discusses on results obtained. In most of the typical NLDBI systems the natural language statement is converted into an internal representation based on the syntactic and semantic knowledge of the natural language. This representation is then converted into queries using a representation converter. A natural language query is translated to an equivalent SQL query after processing through various stages. The work has been experimented on primitive database queries with certain constraints.

Keywords: Natural language database interface, representation converter, syntactic and semantic knowledge

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355 Deep Reinforcement Learning Approach for Trading Automation in the Stock Market

Authors: Taylan Kabbani, Ekrem Duman

Abstract:

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining  the financial assets price ”prediction” step and the ”allocation” step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. This work represents a DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem as a Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. We then solved the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and achieved a 2.68 Sharpe ratio on the test dataset. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of DRL in financial markets over other types of machine learning and proves its credibility and advantages of strategic decision-making.

Keywords: Autonomous agent, deep reinforcement learning, MDP, sentiment analysis, stock market, technical indicators, twin delayed deep deterministic policy gradient.

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354 Recovering Artifacts from Legacy Systems Using Pattern Matching

Authors: Ghulam Rasool, Ilka Philippow

Abstract:

Modernizing legacy applications is the key issue facing IT managers today because there's enormous pressure on organizations to change the way they run their business to meet the new requirements. The importance of software maintenance and reengineering is forever increasing. Understanding the architecture of existing legacy applications is the most critical issue for maintenance and reengineering. The artifacts recovery can be facilitated with different recovery approaches, methods and tools. The existing methods provide static and dynamic set of techniques for extracting architectural information, but are not suitable for all users in different domains. This paper presents a simple and lightweight pattern extraction technique to extract different artifacts from legacy systems using regular expression pattern specifications with multiple language support. We used our custom-built tool DRT to recover artifacts from existing system at different levels of abstractions. In order to evaluate our approach a case study is conducted.

Keywords: Artifacts recovery, Pattern matching, Reverseengineering, Program understanding, Regular expressions, Sourcecode analysis.

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353 Real-Time Image Encryption Using a 3D Discrete Dual Chaotic Cipher

Authors: M. F. Haroun, T. A. Gulliver

Abstract:

In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.

Keywords: Chaotic systems, image encryption, 3D Lorenz attractor, non-autonomous modulation, FPGA.

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352 Margin-Based Feed-Forward Neural Network Classifiers

Authors: Han Xiao, Xiaoyan Zhu

Abstract:

Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labelled samples and flexible network. We have conducted experiments on four UCI open datasets and achieved good results as expected. In conclusion, our model could handle more sparse labelled and more high-dimension dataset in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, Classifier.

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351 Analysis of Feature Space for a 2d/3d Vision based Emotion Recognition Method

Authors: Robert Niese, Ayoub Al-Hamadi, Bernd Michaelis

Abstract:

In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier.

Keywords: Facial expression analysis, Feature extraction, Image processing, Pattern Recognition, Application.

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350 The Status Info Processing and Keeping System for Production Equipment

Authors: So Jeong Nam, Seung Woo Lee, Jai-Kyung Lee

Abstract:

With the globalized production and logistics environment, the need for reducing the product development interval and lead time, having a faster response to orders, conforming to quality standards, fair tracking, and boosting information exchanging activities with customers and partners, and coping with changes in the management environment, manufacturers are in dire need of an information management system in their manufacturing environments. There are lots of information systems that have been designed to manage the condition or operation of equipment in the field but existing systems have a decentralized architecture, which is not unified. Also, these systems cannot effectively handle the status data extraction process upon encountering a problem related to protocols or changes in the equipment or the setting. In this regard, this paper will introduce a system for processing and saving the status info of production equipment, which uses standard representation formats, to enable flexible responses to and support for variables in the field equipment. This system can be used for a variety of manufacturing and equipment settings and is capable of interacting with higher-tier systems such as MES.

Keywords: DAS, Equipment Status, Regular Expression

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349 High Order Cascade Multibit ΣΔ Modulator for Wide Bandwidth Applications

Authors: S. Zouari, H. Daoud, M. Loulou, P. Loumeau, N. Masmoudi

Abstract:

A wideband 2-1-1 cascaded ΣΔ modulator with a single-bit quantizer in the two first stages and a 4-bit quantizer in the final stage is developed. To reduce sensitivity of digital-to-analog converter (DAC) nonlinearities in the feedback of the last stage, dynamic element matching (DEM) is introduced. This paper presents two modelling approaches: The first is MATLAB description and the second is VHDL-AMS modelling of the proposed architecture and exposes some high-level-simulation results allowing a behavioural study. The detail of both ideal and non-ideal behaviour modelling are presented. Then, the study of the effect of building blocks nonidealities is presented; especially the influences of nonlinearity, finite operational amplifier gain, amplifier slew rate limitation and capacitor mismatch. A VHDL-AMS description presents a good solution to predict system-s performances and can provide sensitivity curves giving the impact of nonidealities on the system performance.

Keywords: behavioural study, DAC nonlinearity, DEM, ΣΔ modulator, VHDL-AMS modelling.

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348 Agreement Options on Multi Criteria Group Decision and Negotiation

Authors: Christiono Utomo, Arazi Idrus, Madzlan Napiah, Mohd. Faris Khamidi

Abstract:

This paper presents a conceptual model of agreement options on negotiation support for civil engineering decision. The negotiation support facilitates the solving of group choice decision making problems in civil engineering decision to reduce the impact of mud volcano disaster in Sidoarjo, Indonesia. The approach based on application of analytical hierarchy process (AHP) method for multi criteria decision on three level of decision hierarchy. Decisions for reducing impact is very complicated since many parties involved in a critical time. Where a number of stakeholders are involved in choosing a single alternative from a set of solution alternatives, there are different concern caused by differing stakeholder preferences, experiences, and background. Therefore, a group choice decision support is required to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. Such civil engineering solutions as alternatives are referred to as agreement options that are determined by identifying the possible stakeholder choice, followed by determining the optimal solution for each group of stakeholder. Determination of the optimal solution is based on a game theory model of n-person general sum game with complete information that involves forming coalitions among stakeholders.

Keywords: Agreement options, AHP, agent, negotiation, multicriteria, game theory, and coalition.

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347 Adaptive Naïve Bayesian Anti-Spam Engine

Authors: Wojciech P. Gajewski

Abstract:

The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.

Keywords: Text classification, naïve Bayesian classification, spam, email.

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346 Architecture for Smart Cities’ Sustainable Modular Houses

Authors: Khaled Elbehiery, Hussam Elbehiery

Abstract:

Smart cities are a framework of technologies along with sustainable infrastructure to provide their citizens an improved quality of life, safer environment, affordability, and more, which in turn helps with the society's economic growth. The proposed research will focus on the primary building block of the smart city; the infrastructure of the house itself. The traditional method of building houses has been, for a long time, nothing but a costly manufacturing process, and consequently, buying a house becomes not an option for everyone anymore. The smart cities' Modular Houses are not using traditional building construction materials; the design reduces the common lengthy construction times and associated high costs. The Modular Houses are technological homes, low-cost and customizable based on a family's requirements. In addition, the Modular Houses are environmentally friendly and healthy enough to assist with the pandemic situation.

Keywords: Smart cities, modular houses, single-unit property, multi-unit property, mobility features, chain-supply, livable environment, carbon footprint.

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