Sensor Network Based Emergency Response and Navigation Support Architecture

In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment. 

A Framework for Urdu Language Translation using LESSA

Internet is one of the major sources of information for the person belonging to almost all the fields of life. Major language that is used to publish information on internet is language. This thing becomes a problem in a country like Pakistan, where Urdu is the national language. Only 10% of Pakistan mass can understand English. The reason is millions of people are deprived of precious information available on internet. This paper presents a system for translation from English to Urdu. A module LESSA is used that uses a rule based algorithm to read the input text in English language, understand it and translate it into Urdu language. The designed approach was further incorporated to translate the complete website from English language o Urdu language. An option appears in the browser to translate the webpage in a new window. The designed system will help the millions of users of internet to get benefit of the internet and approach the latest information and knowledge posted daily on internet.

The Impacts of Off-Campus Students on Local Neighbourhood in Malaysia

The impacts of near-campus student housing, or offcampus students accommodation cannot be ignored by the universities and as well as the community officials. Numerous scholarly studies, have highlighted the substantial economic impacts either; direct, indirect or induced, and cumulatively the roles of the universities have significantly contributed to the local economies. The issue of the impacts of off-campus student rental housing on neighbourhoods is one that has been of long-standing but increasing concern in Malaysia. Statistically, in Malaysia, there was approximately a total of 1.2 - 1.5 million students in 2009. By the year 2015, it is expected that 50 per cent of 18 to 30 year olds active population should gain access to university education, amounting to 120,000 yearly. The objectives of the research are to assess the impacts off-campus students on the local neighbourhood and specifically to obtain information on the living and learning conditions of off-campus students of Universiti Teknologi MARA Shah Alam, Malaysia. It is also to isolate those factors that may impede the successful learning so that priority can be given to them in subsequent policy implementations and actions by government and the higher education institutions.

Exploring More Productive Ways of Working

New ways of working- refers to non-traditional work practices, settings and locations with information and communication technologies (ICT) to supplement or replace traditional ways of working. It questions the contemporary work practices and settings still very much used in knowledge-intensive organizations today. In this study new ways of working is seen to consist of two elements: work environment (incl. physical, virtual and social) and work practices. This study aims to gather the scattered information together and deepen the understanding on new ways of working. Moreover, the objective is to provide some evidence of the unclear productivity impacts of new ways of working using case study approach.

Faster FPGA Routing Solution using DNA Computing

There are many classical algorithms for finding routing in FPGA. But Using DNA computing we can solve the routes efficiently and fast. The run time complexity of DNA algorithms is much less than other classical algorithms which are used for solving routing in FPGA. The research in DNA computing is in a primary level. High information density of DNA molecules and massive parallelism involved in the DNA reactions make DNA computing a powerful tool. It has been proved by many research accomplishments that any procedure that can be programmed in a silicon computer can be realized as a DNA computing procedure. In this paper we have proposed two tier approaches for the FPGA routing solution. First, geometric FPGA detailed routing task is solved by transforming it into a Boolean satisfiability equation with the property that any assignment of input variables that satisfies the equation specifies a valid routing. Satisfying assignment for particular route will result in a valid routing and absence of a satisfying assignment implies that the layout is un-routable. In second step, DNA search algorithm is applied on this Boolean equation for solving routing alternatives utilizing the properties of DNA computation. The simulated results are satisfactory and give the indication of applicability of DNA computing for solving the FPGA Routing problem.

Entanglement-based Quantum Computing by Diagrams of States

We explore entanglement in composite quantum systems and how its peculiar properties are exploited in quantum information and communication protocols by means of Diagrams of States, a novel method to graphically represent and analyze how quantum information is elaborated during computations performed by quantum circuits. We present quantum diagrams of states for Bell states generation, measurements and projections, for dense coding and quantum teleportation, for probabilistic quantum machines designed to perform approximate quantum cloning and universal NOT and, finally, for quantum privacy amplification based on entanglement purification. Diagrams of states prove to be a useful approach to analyze quantum computations, by offering an intuitive graphic representation of the processing of quantum information. They also help in conceiving novel quantum computations, from describing the desired information processing to deriving the final implementation by quantum gate arrays.

On the Parameter Optimization of Fuzzy Inference Systems

Nowadays, more engineering systems are using some kind of Artificial Intelligence (AI) for the development of their processes. Some well-known AI techniques include artificial neural nets, fuzzy inference systems, and neuro-fuzzy inference systems among others. Furthermore, many decision-making applications base their intelligent processes on Fuzzy Logic; due to the Fuzzy Inference Systems (FIS) capability to deal with problems that are based on user knowledge and experience. Also, knowing that users have a wide variety of distinctiveness, and generally, provide uncertain data, this information can be used and properly processed by a FIS. To properly consider uncertainty and inexact system input values, FIS normally use Membership Functions (MF) that represent a degree of user satisfaction on certain conditions and/or constraints. In order to define the parameters of the MFs, the knowledge from experts in the field is very important. This knowledge defines the MF shape to process the user inputs and through fuzzy reasoning and inference mechanisms, the FIS can provide an “appropriate" output. However an important issue immediately arises: How can it be assured that the obtained output is the optimum solution? How can it be guaranteed that each MF has an optimum shape? A viable solution to these questions is through the MFs parameter optimization. In this Paper a novel parameter optimization process is presented. The process for FIS parameter optimization consists of the five simple steps that can be easily realized off-line. Here the proposed process of FIS parameter optimization it is demonstrated by its implementation on an Intelligent Interface section dealing with the on-line customization / personalization of internet portals applied to E-commerce.

State-Space PD Feedback Control

A challenged control problem is when the performance is pushed to the limit. The state-derivative feedback control strategy directly uses acceleration information for feedback and state estimation. The derivative part is concerned with the rateof- change of the error with time. If the measured variable approaches the set point rapidly, then the actuator is backed off early to allow it to coast to the required level. Derivative action makes a control system behave much more intelligently. A sensor measures the variable to be controlled and the measured in formation is fed back to the controller to influence the controlled variable. A high gain problem can be also formulated for proportional plus derivative feedback transformation. Using MATLAB Simulink dynamic simulation tool this paper examines a system with a proportional plus derivative feedback and presents an automatic implementation of finding an acceptable controlled system. Using feedback transformations the system is transformed into another system.

Measuring the Structural Similarity of Web-based Documents: A Novel Approach

Most known methods for measuring the structural similarity of document structures are based on, e.g., tag measures, path metrics and tree measures in terms of their DOM-Trees. Other methods measures the similarity in the framework of the well known vector space model. In contrast to these we present a new approach to measuring the structural similarity of web-based documents represented by so called generalized trees which are more general than DOM-Trees which represent only directed rooted trees.We will design a new similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as strings of linear integers, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments to solve a novel and challenging problem: Measuring the structural similarity of generalized trees. More precisely, we first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based documents.

Children and Advertising: Issues in Consumer Socialization Process

Today advertising is actively penetrating into many spheres of our lives. We cannot imagine the existence of a lot of economic activities without advertising. That mostly concerns trade and services. Everyone of us should look better into the everyday communication and carefully consider the amount and the quality of the information we receive as well as its influence on our behaviour. Special attention should be paid to the young generation. Theoretical and practical research has proved the ever growing influence of information (especially the one contained in advertising) on a society; on its economics, culture, religion, politics and even people-s private lives and behaviour. Children have plenty of free time and, therefore, see a lot of different advertising. Though education of children is in the hands of parents and schools, advertising makers and customers should think with responsibility about the selection of time and transmission channels of child targeted advertising. The purpose of the present paper is to investigate the influence of advertising upon consumer views and behaviour of children in different age groups. The present investigation has clarified the influence of advertising as a means of information on a certain group of society, which in the modern information society is the most vulnerable – children. In this paper we assess children-s perception and their understanding of advertising.

Academic Mobbing in Turkey

People at workplace always face with stress and feel it in their lives. There are many factors that create stress and mobbing is one of them. Mobbing is a psychological terror, conducted systematically toward an individual by others at the same workplace. Mobbing started to become a famous subject last years in U.S and Europe. In Turkey, it is a new concept not because it does not occur, because of human nature that does not allow confessing it. Mobbing is being ignored by people, organizations and also government in our country. The focus of this study will be mobbing in Turkey by examining the workplace mobbing among Turkish academicians. There are other studies about mobbing in Turkey but none of them studied academy. Because mobbing methods change according to sectors and occupations, it is important to analyze each sector to understand the methods used in mobbing and the reactions of victims to these actions. The concept is analyzed in detail before focusing on mobbing at universities. This paper will be unique because there is no information about this specific subject in Turkish literature. In this paper, both qualitative and quantitative methods will be used to describe the mobbing at Turkish academic environment.

Efficiency in Urban Governance towards Sustainability and Competitiveness of City : A Case Study of Kuala Lumpur

Malaysia has successfully applied economic planning to guide the development of the country from an economy of agriculture and mining to a largely industrialised one. Now, with its sights set on attaining the economic level of a fully developed nation by 2020, the planning system must be made even more efficient and focused. It must ensure that every investment made in the country, contribute towards creating the desirable objective of a strong, modern, internationally competitive, technologically advanced, post-industrial economy. Cities in Malaysia must also be fully aware of the enormous competition it faces in a region with rapidly expanding and modernising economies, all contending for the same pool of potential international investments. Efficiency of urban governance is also fundamental issue in development characterized by sustainability, subsidiarity, equity, transparency and accountability, civic engagement and citizenship, and security. As described above, city competitiveness is harnessed through 'city marketing and city management'. High technology and high skilled industries, together with finance, transportation, tourism, business, information and professional services shopping and other commercial activities, are the principal components of the nation-s economy, which must be developed to a level well beyond where it is now. In this respect, Kuala Lumpur being the premier city must play the leading role.

Evolutionary Feature Selection for Text Documents using the SVM

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Development of Knowledge Portal using Open Source Tools: A Case Study of FIIT, UNISEL

Knowledge sharing culture contributes to a positive working environment. Currently, there is no platform for the Faculty of Industrial Information Technology (FIIT), Unisel academic staff to share knowledge among them. As it is done manually, the sharing process is through common meeting or by any offline discussions. There is no repository for future retrieval. However, with open source solution the development of knowledge based application may reduce the cost tremendously. In this paper we discuss about the domain on which this knowledge portal is being developed and also the deployment of open source tools such as JOOMLA, PHP programming language and MySQL. This knowledge portal is evidence that open source tools also reliable in developing knowledge based portal. These recommendations will be useful to the open source community to produce more open source products in future.

Torque Based Selection of ANN for Fault Diagnosis of Wound Rotor Asynchronous Motor-Converter Association

In this paper, an automatic system of diagnosis was developed to detect and locate in real time the defects of the wound rotor asynchronous machine associated to electronic converter. For this purpose, we have treated the signals of the measured parameters (current and speed) to use them firstly, as indicating variables of the machine defects under study and, secondly, as inputs to the Artificial Neuron Network (ANN) for their classification in order to detect the defect type in progress. Once a defect is detected, the interpretation system of information will give the type of the defect and its place of appearance.

Effective Defect Prevention Approach in Software Process for Achieving Better Quality Levels

Defect prevention is the most vital but habitually neglected facet of software quality assurance in any project. If functional at all stages of software development, it can condense the time, overheads and wherewithal entailed to engineer a high quality product. The key challenge of an IT industry is to engineer a software product with minimum post deployment defects. This effort is an analysis based on data obtained for five selected projects from leading software companies of varying software production competence. The main aim of this paper is to provide information on various methods and practices supporting defect detection and prevention leading to thriving software generation. The defect prevention technique unearths 99% of defects. Inspection is found to be an essential technique in generating ideal software generation in factories through enhanced methodologies of abetted and unaided inspection schedules. On an average 13 % to 15% of inspection and 25% - 30% of testing out of whole project effort time is required for 99% - 99.75% of defect elimination. A comparison of the end results for the five selected projects between the companies is also brought about throwing light on the possibility of a particular company to position itself with an appropriate complementary ratio of inspection testing.

Audio Watermarking Using Spectral Modifications

In this paper, we present a non-blind technique of adding the watermark to the Fourier spectral components of audio signal in a way such that the modified amplitude does not exceed the maximum amplitude spread (MAS). This MAS is due to individual Discrete fourier transform (DFT) coefficients in that particular frame, which is derived from the Energy Spreading function given by Schroeder. Using this technique one can store double the information within a given frame length i.e. overriding the watermark on the host of equal length with least perceptual distortion. The watermark is uniformly floating on the DFT components of original signal. This helps in detecting any intentional manipulations done on the watermarked audio. Also, the scheme is found robust to various signal processing attacks like presence of multiple watermarks, Additive white gaussian noise (AWGN) and mp3 compression.

Sonic Localization Cues for Classrooms: A Structural Model Proposal

We investigate sonic cues for binaural sound localization within classrooms and present a structural model for the same. Two of the primary cues for localization, interaural time difference (ITD) and interaural level difference (ILD) created between the two ears by sounds from a particular point in space, are used. Although these cues do not lend any information about the elevation of a sound source, the torso, head, and outer ear carry out elevation dependent spectral filtering of sounds before they reach the inner ear. This effect is commonly captured in head related transfer function (HRTF) which aids in resolving the ambiguity from the ITDs and ILDs alone and helps localize sounds in free space. The proposed structural model of HRTF produces well controlled horizontal as well as vertical effects. The implemented HRTF is a signal processing model which tries to mimic the physical effects of the sounds interacting with different parts of the body. The effectiveness of the method is tested by synthesizing spatial audio, in MATLAB, for use in listening tests with human subjects and is found to yield satisfactory results in comparison with existing models.

Encrypter Information Software Using Chaotic Generators

This document shows a software that shows different chaotic generator, as continuous as discrete time. The software gives the option for obtain the different signals, using different parameters and initial condition value. The program shows then critical parameter for each model. All theses models are capable of encrypter information, this software show it too.

A Preliminary Study on the Suitability of Data Driven Approach for Continuous Water Level Modeling

Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.