Abstract: Due to heavy energy constraints in WSNs clustering is
an efficient way to manage the energy in sensors. There are many
methods already proposed in the area of clustering and research is
still going on to make clustering more energy efficient. In our paper
we are proposing a minimum spanning tree based clustering using
divide and conquer approach. The MST based clustering was first
proposed in 1970’s for large databases. Here we are taking divide and
conquer approach and implementing it for wireless sensor networks
with the constraints attached to the sensor networks. This Divide and
conquer approach is implemented in a way that we don’t have to
construct the whole MST before clustering but we just find the edge
which will be the part of the MST to a corresponding graph and
divide the graph in clusters there itself if that edge from the graph can
be removed judging on certain constraints and hence saving lot of
computation.
Abstract: Markov games are a generalization of Markov
decision process to a multi-agent setting. Two-player zero-sum
Markov game framework offers an effective platform for designing
robust controllers. This paper presents two novel controller design
algorithms that use ideas from game-theory literature to produce
reliable controllers that are able to maintain performance in presence
of noise and parameter variations. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. Our approach
generates an optimal control policy for the agent (controller) via a
simple Linear Program enabling the controller to learn about the
unknown environment. The controller is facing an unknown
environment, and in our formulation this environment corresponds to
the behavior rules of the noise modeled as the opponent. Proposed
controller architectures attempt to improve controller reliability by a
gradual mixing of algorithmic approaches drawn from the game
theory literature and the Minimax-Q Markov game solution
approach, in a reinforcement-learning framework. We test the
proposed algorithms on a simulated Inverted Pendulum Swing-up
task and compare its performance against standard Q learning.
Abstract: Wireless Sensor Networks (WSNs) have attracted the attention of many researchers. This has resulted in their rapid integration in very different areas such as precision agriculture,environmental monitoring, object and event detection and military surveillance. Due to the current WSN characteristics this technology is specifically useful in industrial areas where security, reliability and autonomy are basic, such as nuclear power plants, chemical plants, and others. In this paper we present a system based on WSNs to monitor environmental conditions around and inside a nuclear power plant, specifically, radiation levels. Sensor nodes, equipped with radiation sensors, are deployed in fixed positions throughout the plant. In addition, plant staff are also equipped with mobile devices with higher capabilities than sensors such as for example PDAs able to monitor radiation levels and other conditions around them. The system enables communication between PDAs, which form a Mobile Ad-hoc Wireless Network (MANET), and allows workers to monitor remote conditions in the plant. It is particularly useful during stoppage periods for inspection or in the event of an accident to prevent risk situations.
Abstract: Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.
Abstract: Dill contains range of phytochemicals, such as vitamin C and polyphenols, which significantly contribute to their total antioxidant activity. The aim of the current research was to determine the best blanching method for processing of dill prior to microwave vacuum drying based on the content of phenolic compounds, vitamin C and free radical scavenging activity. Two blanching mediums were used – water and steam, and for part of the samples microwave pretreatment was additionally used. Evaluation of vitamin C, phenolic contents and scavenging of DPPH˙ radical in dried dill was performed. Blanching had an effect on all tested parameters and the blanching conditions are very important. After evaluation of the results, as the best method for dill pretreatment was established blanching at 90 °C for 30 seconds.
Abstract: This article presents the results of a study conducted to identify operational risks for information systems (IS) with service-oriented architecture (SOA). Analysis of current approaches to risk and system error classifications revealed that the system error classes were never used for SOA risk estimation. Additionally system error classes are not normallyexperimentally supported with realenterprise error data. Through the study several categories of various existing error classifications systems are applied and three new error categories with sub-categories are identified. As a part of operational risks a new error classification scheme is proposed for SOA applications. It is based on errors of real information systems which are service providers for application with service-oriented architecture. The proposed classification approach has been used to classify SOA system errors for two different enterprises (oil and gas industry, metal and mining industry). In addition we have conducted a research to identify possible losses from operational risks.
Abstract: The overlay approach has been widely used by many service providers for Traffic Engineering (TE) in large Internet backbones. In the overlay approach, logical connections are set up between edge nodes to form a full mesh virtual network on top of the physical topology. IP routing is then run over the virtual network. Traffic engineering objectives are achieved through carefully routing logical connections over the physical links. Although the overlay approach has been implemented in many operational networks, it has a number of well-known scaling issues. This paper proposes a new approach to achieve traffic engineering without full-mesh overlaying with the help of integrated approach and equal subset split method. Traffic engineering needs to determine the optimal routing of traffic over the existing network infrastructure by efficiently allocating resource in order to optimize traffic performance on an IP network. Even though constraint-based routing [1] of Multi-Protocol Label Switching (MPLS) is developed to address this need, since it is not widely tested or debugged, Internet Service Providers (ISPs) resort to TE methods under Open Shortest Path First (OSPF), which is the most commonly used intra-domain routing protocol. Determining OSPF link weights for optimal network performance is an NP-hard problem. As it is not possible to solve this problem, we present a subset split method to improve the efficiency and performance by minimizing the maximum link utilization in the network via a small number of link weight modifications. The results of this method are compared against results of MPLS architecture [9] and other heuristic methods.
Abstract: Enterprise applications are complex systems that are hard to develop and deploy in organizations. Although software application development tools, frameworks, methodologies and patterns are rapidly developing; many projects fail by causing big costs. There are challenging issues that programmers and designers face with while working on enterprise applications. In this paper, we present the three of the significant issues: Architectural, technological and performance. The important subjects in each issue are pointed out and recommendations are given. In architectural issues the lifecycle, meta-architecture, guidelines are pointed out. .NET and Java EE platforms are presented in technological issues. The importance of performance, measuring performance and profilers are explained in performance issues.
Abstract: this article proposed a methodology for computer
numerical control (CNC) machine scoring. The case study company
is a manufacturer of hard disk drive parts in Thailand. In this
company, sample of parts manufactured from CNC machine are
usually taken randomly for quality inspection. These inspection data
were used to make a decision to shut down the machine if it has
tendency to produce parts that are out of specification. Large amount
of data are produced in this process and data mining could be very
useful technique in analyzing them. In this research, data mining
techniques were used to construct a machine scoring model called
'machine priority assessment model (MPAM)'. This model helps to
ensure that the machine with higher risk of producing defective parts
be inspected before those with lower risk. If the defective prone
machine is identified sooner, defective part and rework could be
reduced hence improving the overall productivity. The results
showed that the proposed method can be successfully implemented
and approximately 351,000 baht of opportunity cost could have
saved in the case study company.
Abstract: Tanzania secondary schools in rural areas are geographically and socially isolated, hence face a number of problems in getting learning materials resulting in poor performance in National examinations. E-learning as defined to be the use of information and communication technology (ICT) for supporting the educational processes has motivated Tanzania to apply ICT in its education system. There has been effort to improve secondary school education using ICT through several projects. ICT for e-learning to Tanzania rural secondary school is one of the research projects conceived by the University of Dar-es-Salaam through its College of Engineering and Technology. The main objective of the project is to develop a tool to enable ICT support rural secondary school. The project is comprehensive with a number of components, one being development of e-learning management system (e-LMS) for Tanzania secondary schools. This paper presents strategies of developing e-LMS. It shows the importance of integrating action research methodology with the modeling methods as presented by model driven architecture (MDA) and the usefulness of Unified Modeling Language (UML) on the issue of modeling. The benefit of MDA will go along with the development based on software development life cycle (SDLC) process, from analysis and requirement phase through design and implementation stages as employed by object oriented system analysis and design approach. The paper also explains the employment of open source code reuse from open source learning platforms for the context sensitive development of the e-LMS for Tanzania secondary schools.
Abstract: Quantitative Structure-Activity Relationship (QSAR)
approach for discovering novel more active Calanone derivative as
anti-leukemia compound has been conducted. There are 6
experimental activities of Calanone compounds against leukemia cell
L1210 that are used as material of the research. Calculation of
theoretical predictors (independent variables) was performed by
AM1 semiempirical method. The QSAR equation is determined by
Principle Component Regression (PCR) analysis, with Log IC50 as
dependent variable and the independent variables are atomic net
charges, dipole moment (μ), and coefficient partition of noctanol/
water (Log P). Three novel Calanone derivatives that
obtained by this research have higher activity against leukemia cell
L1210 than pure Calanone.
Abstract: The use of computer hardware and software in
education and training dates to the early 1940s, when American
researchers developed flight simulators which used analog computers
to generate simulated onboard instrument data.Computer software is
widely used to help engineers and undergraduate student solve their
problems quickly and more accurately. This paper presents the list of
computer software in geotechnical engineering.
Abstract: The selection of appropriate requirements for product
releases can make a big difference in a product success. The selection
of requirements is done by different requirements prioritization
techniques. These techniques are based on pre-defined and
systematic steps to calculate the requirements relative weight.
Prioritization is complicated by new development settings, shifting
from traditional co-located development to geographically distributed
development. Stakeholders, connected to a project, are distributed all
over the world. These geographically distributions of stakeholders
make it hard to prioritize requirements as each stakeholder have their
own perception and expectations of the requirements in a software
project. This paper discusses limitations of the Analytical Hierarchy
Process with respect to geographically distributed stakeholders-
(GDS) prioritization of requirements. This paper also provides a
solution, in the form of a modified AHP, in order to prioritize
requirements for GDS. We will conduct two experiments in this
paper and will analyze the results in order to discuss AHP limitations
with respect to GDS. The modified AHP variant is also validated in
this paper.
Abstract: Transferring patient information between medical care
sites is necessary to deliver better patient care and to reduce medical
cost. So developing of electronic medical records is an important trend
for the world.The Continuity of Care Document (CCD) is product of
collaboration between CDA and CCR standards. In this study, we will
develop a system to generate medical records with entry level based on
CCD template module.
Abstract: Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.
Abstract: This research attempts to explore gaps in Information
Systems (IS) and innovation literatures by developing a model of
Information Technology (IT) capability in enabling innovation. The
research was conducted by using semi-structured interview with six
innovators in business consulting, financial, healthcare and academic
organizations. The interview results suggest four elements of ITenabled
innovation capability which are information (ability to
capture ideas and knowledge), connectivity (ability to bridge
geographical boundary and mobilize human resources),
communication (ability to attain and engage relationships between
human resources) and transformation (ability to change the functions
and process integrations) in defining IT-enabled innovation platform.
The results also suggests innovators- roles and IT capability.
Abstract: With the advancement of wireless sensor network technology,
its practical utilization is becoming an important challange.
This paper overviews my past environmental monitoring project,
and discusses the process of starting the monitoring by classifying
it into four steps. The steps to start environmental monitoring can
be complicated, but not well discussed by researchers of wireless
sensor network technology. This paper demonstrates our activity and
challenges in each of the four steps to ease the process, and argues
future challenges to enable quick start of environmental monitoring.
Abstract: The present study addresses problems and solutions
related to new functional food production. Wheat (Triticum aestivum
L) bran obtained from industrial mill company “Dobeles
dzirnavieks”, was used to investigate them as raw material like
nutrients for Bifidobacterium lactis Bb-12. Enzymatic hydrolysis of
wheat bran starch was carried out by α-amylase from Bacillus
amyloliquefaciens (Sigma Aldrich). The Viscozyme L purchased
from (Sigma Aldrich) were used for reducing released sugar.
Bifidibacterium lactis Bb-12 purchased from (Probio-Tec® CHR
Hansen) was cultivated in enzymatically hydrolysed wheat bran
mash. All procedures ensured the number of active Bifidobacterium
lactis Bb-12 in the final product reached 105 CFUg-1. After enzymatic
and bacterial fermentations sample were freeze dried for analysis of
chemical compounds. All experiments were performed at Faculty of
Food Technology of Latvia University of Agriculture in January-
March 2013. The obtained results show that both types of wheat bran
(enzymatically treated and non-treated) influenced the fermentative
activity and number of Bifidibacterium lactis Bb-12 viable in wheat
bran mash. Amount of acidity strongly increase during the wheat
bran mash fermentation. The main objective of this work was to
create low-energy functional enzymatically and bacterially treated
food from wheat bran using enzymatic hydrolysis of carbohydrates
and following cultivation of Bifidobacterium lactis Bb-12.
Abstract: In this paper, we propose a robust disease detection
method, called adaptive orientation code matching (Adaptive OCM),
which is developed from a robust image registration algorithm:
orientation code matching (OCM), to achieve continuous and
site-specific detection of changes in plant disease. We use two-stage
framework for realizing our research purpose; in the first stage,
adaptive OCM was employed which could not only realize the
continuous and site-specific observation of disease development, but
also shows its excellent robustness for non-rigid plant object searching
in scene illumination, translation, small rotation and occlusion changes
and then in the second stage, a machine learning method of support
vector machine (SVM) based on a feature of two dimensional (2D)
xy-color histogram is further utilized for pixel-wise disease
classification and quantification. The indoor experiment results
demonstrate the feasibility and potential of our proposed algorithm,
which could be implemented in real field situation for better
observation of plant disease development.
Abstract: Continuous innovation is becoming a necessity if
firms want to stay competitive. Different factors influence the rate of
innovation in a firm, among which corporate culture has often been
recognized among the most important factors. In this paper we argue
that the development of corporate culture that will support and foster
innovation must be accompanied with an appropriate reward system.
A research conducted among Croatian firms showed that a
statistically significant relationship exists among corporate culture
that supports innovations and reward system features.