Search results for: functional relatedness of inner-outer class
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1584

Search results for: functional relatedness of inner-outer class

444 A study of Cancer-related MicroRNAs through Expression Data and Literature Search

Authors: Chien-Hung Huang, Chia-Wei Weng, Chang-Chih Chiang, Shih-Hua Wu, Chih-Hsien Huang, Ka-Lok Ng

Abstract:

MicroRNAs (miRNAs) are a class of non-coding RNAs that hybridize to mRNAs and induce either translation repression or mRNA cleavage. Recently, it has been reported that miRNAs could possibly play an important role in human diseases. By integrating miRNA target genes, cancer genes, miRNA and mRNA expression profiles information, a database is developed to link miRNAs to cancer target genes. The database provides experimentally verified human miRNA target genes information, including oncogenes and tumor suppressor genes. In addition, fragile sites information for miRNAs, and the strength of the correlation of miRNA and its target mRNA expression level for nine tissue types are computed, which serve as an indicator for suggesting miRNAs could play a role in human cancer. The database is freely accessible at http://ppi.bioinfo.asia.edu.tw/mirna_target/index.html.

Keywords: MicroRNA, miRNA expression profile, mRNAexpression profile, cancer genes, oncogene, tumor suppressor gene

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443 Supply Chain Decarbonisation – A Cost-Based Decision Support Model in Slow Steaming Maritime Operations

Authors: Eugene Y. C. Wong, Henry Y. K. Lau, Mardjuki Raman

Abstract:

CO2 emissions from maritime transport operations represent a substantial part of the total greenhouse gas emission. Vessels are designed with better energy efficiency. Minimizing CO2 emission in maritime operations plays an important role in supply chain decarbonisation. This paper reviews the initiatives on slow steaming operations towards the reduction of carbon emission. It investigates the relationship and impact among slow steaming cost reduction, carbon emission reduction, and shipment delay. A scenario-based cost-driven decision support model is developed to facilitate the selection of the optimal slow steaming options, considering the cost on bunker fuel consumption, available speed, carbon emission, and shipment delay. The incorporation of the social cost of cargo is reviewed and suggested. Additional measures on the effect of vessels sizes, routing, and type of fuels towards decarbonisation are discussed.

Keywords: Slow steaming, carbon emission, maritime logistics, sustainability, green supply chain.

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442 Biosorption of Cu (II) and Zn (II) from Real Wastewater onto Cajanus cajan Husk

Authors: Mallappa A. Devani, John U. Kennedy Oubagaranadin, Basudeb Munshi

Abstract:

In this preliminary work, locally available husk of Cajanus cajan (commonly known in India as Tur or Arhar), a bio-waste, has been used in its physically treated and chemically activated form for the removal of binary Cu (II) and Zn(II) ions from the real waste water obtained from an electroplating industry in Bangalore, Karnataka, India and from laboratory prepared binary solutions having almost similar composition of the metal ions, for comparison. The real wastewater after filtration and dilution for five times was used for biosorption studies at the normal pH of the solutions at room temperature. Langmuir's binary model was used to calculate the metal uptake capacities of the biosorbents. It was observed that Cu(II) is more competitive than Zn(II) in biosorption. In individual metal biosorption, Cu(II) uptake was found to be more than that of the Zn(II) and a similar trend was observed in the binary metal biosorption from real wastewater and laboratory prepared solutions. FTIR analysis was carried out to identify the functional groups in the industrial wastewater and EDAX for the elemental analysis of the biosorbents after experiments.

Keywords: Biosorption, Cajanus cajan, multi metal remediation, wastewater.

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441 An Anatomically-Based Model of the Nerves in the Human Foot

Authors: Muhammad Zeeshan UlHaque, Peng Du, Leo K. Cheng, Marc D. Jacobs

Abstract:

Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.

Keywords: Diabetic neuropathy, Finite element modeling, Monte Carlo Algorithm, Somatosensory nerve networks

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440 A Fragile Watermarking Scheme for Color Image Authentication

Authors: M. Hamad Hassan, S.A.M. Gilani

Abstract:

In this paper, a fragile watermarking scheme is proposed for color image specified object-s authentication. The color image is first transformed from RGB to YST color space, suitable for watermarking the color media. The T channel corresponds to the chrominance component of a color image andYS ÔèÑ T , therefore selected for embedding the watermark. The T channel is first divided into 2×2 non-overlapping blocks and the two LSBs are set to zero. The object that is to be authenticated is also divided into 2×2 nonoverlapping blocks and each block-s intensity mean is computed followed by eight bit encoding. The generated watermark is then embedded into T channel randomly selected 2×2 block-s LSBs using 2D-Torus Automorphism. Selection of block size is paramount for exact localization and recovery of work. The proposed scheme is blind, efficient and secure with ability to detect and locate even minor tampering applied to the image with full recovery of original work. The quality of watermarked media is quite high both subjectively and objectively. The technique is suitable for class of images with format such as gif, tif or bitmap.

Keywords: Image Authentication, LSBs, PSNR, 2D-Torus Automorphism, YST Color Space.

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439 Photoimpedance Spectroscopy Analysis of Planar and Nano-Textured Thin-Film Silicon Solar Cells

Authors: P. Kumar, D. Eisenhauer, M. M. K. Yousef, Q. Shi, A. S. G. Khalil, M. R. Saber, C. Becker, T. Pullerits, K. J. Karki

Abstract:

In impedance spectroscopy (IS) the response of a photo-active device is analysed as a function of ac bias. It is widely applied in a broad class of material systems and devices. It gives access to fundamental mechanisms of operation of solar cells. We have implemented a method of IS where we modulate the light instead of the bias. This scheme allows us to analyze not only carrier dynamics but also impedance of device locally. Here, using this scheme, we have measured the frequency-dependent photocurrent response of the thin-film planar and nano-textured Si solar cells using this method. Photocurrent response is measured in range of 50 Hz to 50 kHz. Bode and Nyquist plots are used to determine characteristic lifetime of both the cells. Interestingly, the carrier lifetime of both planar and nano-textured solar cells depend on back and front contact positions. This is due to either heterogeneity of device or contacts are not optimized. The estimated average lifetime is found to be shorter for the nano-textured cell, which could be due to the influence of the textured interface on the carrier relaxation dynamics.

Keywords: Carrier lifetime, Impedance, nano-textured, and photocurrent.

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438 A Real-Time Specific Weed Recognition System Using Statistical Methods

Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan

Abstract:

The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.

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437 Information Gain Ratio Based Clustering for Investigation of Environmental Parameters Effects on Human Mental Performance

Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin

Abstract:

Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.

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436 Reliability Based Investigation on the Choice of Characteristic Soil Properties

Authors: Jann-Eike Saathoff, Kirill Alexander Schmoor, Martin Achmus, Mauricio Terceros

Abstract:

By using partial factors of safety, uncertainties due to the inherent variability of the soil properties and loads are taken into account in the geotechnical design process. According to the reliability index concept in Eurocode-0 in conjunction with Eurocode-7 a minimum safety level of β = 3.8 for reliability class RC2 shall be established. The reliability of the system depends heavily on the choice of the prespecified safety factor and the choice of the characteristic soil properties. The safety factors stated in the standards are mainly based on experience. However, no general accepted method for the calculation of a characteristic value within the current design practice exists. In this study, a laterally loaded monopile is investigated and the influence of the chosen quantile values of the deterministic system, calculated with p-y springs, will be presented. Monopiles are the most common foundation concepts for offshore wind energy converters. Based on the calculations for non-cohesive soils, a recommendation for an appropriate quantile value for the necessary safety level according to the standards for a deterministic design is given.

Keywords: Asymptotic sampling, characteristic value, monopile foundation, probabilistic design, quantile values.

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435 An Overview of Georgia’s Economic Growth Since 2012: Current Status, Challenges, and Opportunities for Future Development

Authors: V. Benidze

Abstract:

After the Rose Revolution of 2003, Georgia has achieved an unparalleled socioeconomic success. However, economic growth since 2012 has been sluggish and certainly not enough to rapidly improve the county’s standard of living that still remains substantially low compared to that in developed nations. Recent poor economic performance has shown that some key challenges need to be addressed if Georgia is to achieve high future economic growth that will decrease the poverty rate and create a middle class in the country. This paper offers in detail analysis of the economic performance of Georgia since 2012 and identifies key challenges facing the country’s economy. The main challenge going forward will be transforming Georgia from a consumption-driven to a production-oriented economy. It is identified that mobilizing domestic investment through savings, attracting foreign investment in tradable sectors and expanding the country’s export base will be crucial in the facilitation of the above-mentioned structural transformation. As the outcome of the research, the paper suggests a strategy for accelerating Georgia’ future economic growth and offers recommendations based on the relevant conclusions.

Keywords: Challenges, development, economic growth, economic policy, Georgia.

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434 Generalized Mathematical Description and Simulation of Grid-Tied Thyristor Converters

Authors: V. S. Klimash, Ye Min Thu

Abstract:

Thyristor rectifiers, inverters grid-tied, and AC voltage regulators are widely used in industry, and on electrified transport, they have a lot in common both in the power circuit and in the control system. They have a common mathematical structure and switching processes. At the same time, the rectifier, but the inverter units and thyristor regulators of alternating voltage are considered separately both theoretically and practically. They are written about in different books as completely different devices. The aim of this work is to combine them into one class based on the unity of the equations describing electromagnetic processes, and then, to show this unity on the mathematical model and experimental setup. Based on research from mathematics to the product, a conclusion is made about the methodology for the rapid conduct of research and experimental design work, preparation for production and serial production of converters with a unified bundle. In recent years, there has been a transition from thyristor circuits and transistor in modular design. Showing the example of thyristor rectifiers and AC voltage regulators, we can conclude that there is a unity of mathematical structures and grid-tied thyristor converters.

Keywords: Direct current, alternating current, rectifier, AC voltage regulator, generalized mathematical model.

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433 Empirical Process Monitoring Via Chemometric Analysis of Partially Unbalanced Data

Authors: Hyun-Woo Cho

Abstract:

Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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432 Combining Gene and Chemo Therapy using Multifunctional Polymeric Micelles

Authors: Hong Yi Huang, Wei Ti Kuo, Yi You Huang

Abstract:

Non-viral gene carriers composed of biodegradable polymers or lipids have been considered as a safer alternative for gene carriers over viral vectors. We have developed multi-functional nano-micelles for both drug and gene delivery application. Polyethyleneimine (PEI) was modified by grafting stearic acid (SA) and formulated to polymeric micelles (PEI-SA) with positive surface charge for gene and drug delivery. Our results showed that PEI-SA micelles provided high siRNA binding efficiency. In addition, siRNA delivered by PEI-SA carriers also demonstrated significantly high cellular uptake even in the presence of serum proteins. The post-transcriptional gene silencing efficiency was greatly improved by the polyplex formulated by 10k PEI-SA/siRNA. The amphiphilic structure of PEI-SA micelles provided advantages for multifunctional tasks; where the hydrophilic shell modified with cationic charges can electrostatically interact with DNA or siRNA, and the hydrophobic core can serve as payloads for hydrophobic drugs, making it a promising multifunctional vehicle for both genetic and chemotherapy application.

Keywords: polyethyleneimine, gene delivery, micelles, siRNA

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431 An Adaptive Virtual Desktop Service in Cloud Computing Platform

Authors: Shuen-Tai Wang, Hsi-Ya Chang

Abstract:

Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.

Keywords: Cloud Computing, Virtualization, Virtual Desktop, VDaaS.

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430 Numerical Modeling of Wave Run-Up in Shallow Water Flows Using Moving Wet/Dry Interfaces

Authors: Alia Alghosoun, Michael Herty, Mohammed Seaid

Abstract:

We present a new class of numerical techniques to solve shallow water flows over dry areas including run-up. Many recent investigations on wave run-up in coastal areas are based on the well-known shallow water equations. Numerical simulations have also performed to understand the effects of several factors on tsunami wave impact and run-up in the presence of coastal areas. In all these simulations the shallow water equations are solved in entire domain including dry areas and special treatments are used for numerical solution of singularities at these dry regions. In the present study we propose a new method to deal with these difficulties by reformulating the shallow water equations into a new system to be solved only in the wetted domain. The system is obtained by a change in the coordinates leading to a set of equations in a moving domain for which the wet/dry interface is the reconstructed using the wave speed. To solve the new system we present a finite volume method of Lax-Friedrich type along with a modified method of characteristics. The method is well-balanced and accurately resolves dam-break problems over dry areas.

Keywords: Run-up waves, Shallow water equations, finite volume method, wet/dry interface, dam-break problem.

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429 Dynamic-Stochastic Influence Diagrams: Integrating Time-Slices IDs and Discrete Event Systems Modeling

Authors: Xin Zhao, Yin-fan Zhu, Wei-ping Wang, Qun Li

Abstract:

The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.

Keywords: Time-sliced influence diagrams, discrete event systems, dynamic-stochastic influence diagrams, modeling formalism, simulation algorithm.

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428 Analysis of Genotype Size for an Evolvable Hardware System

Authors: Emanuele Stomeo, Tatiana Kalganova, Cyrille Lambert

Abstract:

The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.

Keywords: Evolvable hardware, genotype size, computational intelligence, design of logic circuits.

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427 A Composite Developed from a Methyl Methacrylate and Embedded Eppawala Hydroxyapatite for Orthopedics

Authors: H. K. G. K. D. K. Hapuhinna, R. D. Gunaratne, H. M. J. C. Pitawala

Abstract:

This study aimed to find out chemical and structural suitability of synthesized eppawala hydroxyapatite composite as bone cement, by comparing and contrasting it with human bone as well as commercially available bone cement, which is currently used in orthopedic surgeries. Therefore, a mixture of commercially available bone cement and its liquid monomer, commercially available methyl methacrylate (MMA) and a mixture of solid state synthesized eppawala hydroxyapatite powder with commercially available MMA were prepared as the direct substitution for bone cement. Then physical and chemical properties including composition, crystallinity, presence of functional groups, thermal stability, surface morphology, and microstructural features were examined compared to human bone. Results show that there is a close similarity between synthesized product and human bone and it has exhibited high thermal stability, good crystalline and porous properties than the commercial product. Finally, the study concluded that synthesized hydroxyapatite composite can be used directly as a substitution for commercial bone cement.

Keywords: Hydroxyapatite, bone cement, methyl methacrylate, orthopedics.

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426 Effect of Shear Wall Openings on the Fundamental Period of Shear Wall Structures

Authors: Anas M. Fares, A. Touqan

Abstract:

A common approach in resisting lateral forces is the use of reinforced concrete shear walls in buildings. These walls represent the main elements to resist the lateral forces due to their large strength and stiffness. However, such walls may contain many openings due to functional requirements, and this may largely affect the overall lateral stiffness of them. It is thus of prime importance to quantify the effect of openings on the dynamic performance of the shear walls. SAP2000 structural analysis program is used as a main source after verifying the results. This study is made by using linear elastic analysis. The results are compared to ASCE7-16 code empirical equations for estimating the fundamental period of shear wall structures. Finally, statistical regression is used to fit an equation for estimating the increase in the fundamental period of shear-walled regular structures due to windows openings in the walls.

Keywords: Concrete, earthquake-resistant design, finite element, fundamental period, lateral stiffness, linear analysis, modal analysis, rayleigh, SAP2000, shear wall, ASCE7-16.

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425 The Ability of Forecasting the Term Structure of Interest Rates Based On Nelson-Siegel and Svensson Model

Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

Abstract:

Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector autoregressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is Neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel model, Neural networks, Svensson model, Vector autoregressive model, Yield curve.

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424 Effect of adding Supercritical Carbon Dioxide Extracts of Cinnamomum tamala (Bay Leaf) on Nutraceutical Property of Tofu

Authors: Sudip Ghosh, Probir Kumar Ghosh, Paramita Bhattacharjee

Abstract:

Supercritical carbon dioxide extracts of Cinnamomum tamala (bay) leaves obtained at 55°C, 512 bar was found to have appreciable nutraceutical properties and was successfully employed as value-added ingredients in preparation of tofu. The bay leaf formulated tofu sample was evaluated for physicochemical properties (pH, texture analysis and lipid peroxidation), proximate analysis, phytochemical properties (total phenol content, antioxidant properties and total reducing sugar), microbial load and sensory profile analysis for a storage period of ten days, vis-à-vis an experimental control sample. These assays established the superiority of the tofu sample formulated with supercritical carbon dioxide extract of bay leaf over the control sample. Bay leaf extract formulated tofu is a new green functional food with promising nutraceutical benefits. 

Keywords: Cinnamomum tamala, Physicochemical properties Phytochemical properties, Supercritical carbon dioxide extraction, Tofu.

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423 Developing a Sustainable Educational Portal for the D-Grid Community

Authors: Viktor Achter, Sebastian Breuers, Marc Seifert, Ulrich Lang, Joachim Götze, Bernd Reuther, Paul Müller

Abstract:

Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.

Keywords: D-Grid, e-learning, e-science, Grid computing, SuGI.

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422 FleGSens – Secure Area Monitoring Using Wireless Sensor Networks

Authors: Peter Rothenpieler, Daniela Kruger, Dennis Pfisterer, Stefan Fischer, Denise Dudek, Christian Haas, Martina Zitterbart

Abstract:

In the project FleGSens, a wireless sensor network (WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information security. The intended prototype consists of 200 sensor nodes for monitoring a 500m long land strip. The system is focused on ensuring integrity and authenticity of generated alarms and availability in the presence of an attacker who may even compromise a limited number of sensor nodes. In this paper, two of the main protocols developed in the project are presented, a tracking protocol to provide secure detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols and particularly demonstrating the impact and cost of several attacks.

Keywords: Wireless Sensor Network, Security, Trespass Detection, Testbed.

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421 Kinematic Hardening Parameters Identification with Respect to Objective Function

Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

Abstract:

Constitutive modeling of material behavior is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behavior of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behavior modeling.

Keywords: Genetic algorithm, kinematic hardening, material model, objective function

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420 Using Statistical Significance and Prediction to Test Long/Short Term Public Services and Patients Cohorts: A Case Study in Scotland

Authors: Sotirios Raptis

Abstract:

Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found  that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.

Keywords: Class, cohorts, data frames, grouping, prediction, probabilities, services.

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419 An Improved k Nearest Neighbor Classifier Using Interestingness Measures for Medical Image Mining

Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

Abstract:

The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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418 Underlying Cognitive Complexity Measure Computation with Combinatorial Rules

Authors: Benjapol Auprasert, Yachai Limpiyakorn

Abstract:

Measuring the complexity of software has been an insoluble problem in software engineering. Complexity measures can be used to predict critical information about testability, reliability, and maintainability of software systems from automatic analysis of the source code. During the past few years, many complexity measures have been invented based on the emerging Cognitive Informatics discipline. These software complexity measures, including cognitive functional size, lend themselves to the approach of the total cognitive weights of basic control structures such as loops and branches. This paper shows that the current existing calculation method can generate different results that are algebraically equivalence. However, analysis of the combinatorial meanings of this calculation method shows significant flaw of the measure, which also explains why it does not satisfy Weyuker's properties. Based on the findings, improvement directions, such as measures fusion, and cumulative variable counting scheme are suggested to enhance the effectiveness of cognitive complexity measures.

Keywords: Cognitive Complexity Measure, Cognitive Weight of Basic Control Structure, Counting Rules, Cumulative Variable Counting Scheme.

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417 Investigation of Water Deficit Stress on Agronomical Traits of Soybean Cultivars in Temperate Climate

Authors: Jahanfar Daneshian, P. Jonoubi, D. Barari Tari

Abstract:

In order to investigate water deficit stress on 24 of soybean (Glycine Max. L) cultivars and lines in temperate climate, an experiment was conducted in Iran Seed and Plant Improvement Institute. Stress levels were irrigation after evaporation of 50, 100, 150 mm water from pan, class A. Randomized Completely Block Design was arranged for each stress levels. Some traits such as, node number, plant height, pod number per area, grain number per pod, grain number per area, 1000 grains weight, grain yield and harvest index were measured. Results showed that water deficit stress had significant effect on node number, plant height, pod number per area, grain number per pod, grain number per area, 1000 grains weight and harvest index. Also all of agronomic traits except harvest index influenced significantly by cultivars and lines. The least and most grain yield was belonged to Ronak X Williams and M41 x Clark respectively.

Keywords: Soybean, water deficit stress, Agronomic traits, Yield

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416 Indoor Localization by Pattern Matching Method Based On Extended Database

Authors: Gyumin Hwang, Jihong Lee

Abstract:

This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: Chirp Spread Spectrum (CSS), Indoor Localization, Pattern-Matching, Time of Arrival (ToA), Multi-Path, Mahalanobis Distance, Reception Rate, Simultaneous Localization and Mapping (SLAM), Laser Range Finder (LRF).

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415 Fluorescence Spectroscopy of Lysozyme-Silver Nanoparticles Complex

Authors: S. Ashrafpour, T. Tohidi Moghadam, B. Ranjbar

Abstract:

Identifying the nature of protein-nanoparticle interactions and favored binding sites is an important issue in functional characterization of biomolecules and their physiological responses. Herein, interaction of silver nanoparticles with lysozyme as a model protein has been monitored via fluorescence spectroscopy. Formation of complex between the biomolecule and silver nanoparticles (AgNPs) induced a steady state reduction in the fluorescence intensity of protein at different concentrations of nanoparticles. Tryptophan fluorescence quenching spectra suggested that silver nanoparticles act as a foreign quencher, approaching the protein via this residue. Analysis of the Stern-Volmer plot showed quenching constant of 3.73 μM−1. Moreover, a single binding site in lysozyme is suggested to play role during interaction with AgNPs, having low affinity of binding compared to gold nanoparticles. Unfolding studies of lysozyme showed that complex of lysozyme- AgNPs has not undergone structural perturbations compared to the bare protein. Results of this effort will pave the way for utilization of sensitive spectroscopic techniques for rational design of nanobiomaterials in biomedical applications.

Keywords: Nanocarrier, Nanoparticles, Surface Plasmon Resonance, Quenching Fluorescence.

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