Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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Subject: search.filters.subject.algorithm

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Now showing 1 - 6 of 6
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    Cloud-based Salesman-Bot for Ontology-based Negotiation
    (IEEE, 2023-04-06) Fernando, A; Rahubedda, T; Jayasinghe, B; Mallikahewa, S; Hettiarachchi, O; Rajapaksha, S
    We have proposed a cloud-based ChatBot (Salesman-Bot) approach to handling multiple negotiation scenarios in a supermarket environment. The web application is a simple interface that can be implemented on a single standalone device or interacted with through a mobile phone. The Salesman-Bot responds both via text and speech. By introducing a Salesman-Bot, efficient negotiation, with quick preferences and suggestions can be provided. A new architecture proposed to operate the Salesman-Bot together with Google APIs and libraries such as Natural Language AI, Vision AI, Speech to Text API, Text to Speech API and Machine Learning using TensorFlow. The application also uses the Google Cloud Platform with related services such as Google App Engine. The goal is to make ChatBots more efficient in negotiating in different business scenarios. This paper presents the work carried out with ontology and machine learning in a cloud-based environment to handle multiple negotiation scenarios based on a negotiation hierarchy. It also proposes the opportunities and drawbacks of such a system.
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    An algorithm for labeling topological maps to represent point of interest for vision impaired navigation
    (IEEE, 2015-10-13) Jayakody, A; Murray, I; Herrmann, J
    Navigation in indoor environments is highly challenging for both vision impaired and sighted people, particularly in unknown environments visited for the first time. Several solutions have been implemented and proposed to deal with this challenge. Although some of them have shown to be useful in real scenarios, each solution involves a significant deployment effort or describes objects in a manner that is unfamiliar or incomprehensible to an individual with severe blindness. This paper presents a model of adding informational point of interest to the typical indoor topological map; with particular attention to the semantic labels of the different type of indoor places and proposes a simple way to include the tags to build the topological map. Using this POI and the semantic information, the system determines the user's path, locates possible obstacles on that route, and offers navigation information to assist vision impaired navigation.
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    A gyroscopic data based pedometer algorithm
    (IEEE, 2013-04-26) Jayalath, S; Abhayasinghe, N
    Accuracy of step counting is one of the main problems that exist in current Pedometers, especially when walking slowly on flat lands and performing different activities, such as climbing up and down stairs and walking on inclined planes. Although accelerometer based pedometers provide a reasonable accuracy when walking at higher speeds, the accuracy of them are not sufficient at slow walking speeds and performing different activities. This paper proposes a novel algorithm to detect steps using single-point gyroscopic sensors embedded in mobile devices. Preliminary analysis of data collected in different environments with the involvement of male and female volunteers indicated that gyroscope alone provides sufficient information necessary for accurate step detection. Algorithm was developed based on the gyroscopic data in conjunction with zero crossing and threshold detection techniques. The results proved that gyroscope based step detection algorithm provide a high accuracy when performing different activities and at slow paced walking.
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    An adaptive routing algorithm for Cognitive Packet Network infrastructure based on neural networks
    (IEEE, 2011-08-16) Madubashitha, D. K. D; Wijesinghe, W. M. S. S; Kamaladiwela, K. A. S. R; Ranaweera, M. G. P; Wijekoon, J; Abeygunawardhana, P. K. W
    This paper examines the possibility of introducing an intelligent routing protocol to the Internet, based on the Cognitive Packet Network (CPN) architecture with respect to the Quality of Service (QoS) delivered to the end users. In the present with increasing populations of countries it is clear that present infrastructure does not hold the sufficient capacity to deliver the expected level of service to the end users. Since there is an eminent need for a solution for improving the QoS in the Internet, this research focuses to provide a new network architecture which would improve the QoS, provide reliable and efficient service which can fulfill the ever growing Internet usage demand. This is achieved through a new network architecture known as CPN which is based on the basis of providing the best and user desired QoS. The main underlying technology behind the CPN will be a neural network. The neural network will be learning the changes in the network and adapt to the situation through the knowledge gathered. The packets will collectively learn about the network thus the load on the routers will be minimized. This mechanism completely replaces the need of a routing table thus making routing far more efficient when comparing to current routing protocols like Open Shortest Path First (OSPF). Final outcome of the research is coming to the conclusion that the future of the Internet is with the neural network based intelligent, dynamically adapting and learning CPN infrastructure instead of current packet switched network.
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    An adaptive routing algorithm for Cognitive Packet Network infrastructure based on neural networks
    (IEEE, 2011-08-16) Madubashitha, D. K. D; Wijesinghe, W. M. S. S; Kamaladiwela, K. A. S. R; Ranaweera, M. G. P; Wijekoon, J; Abeygunawardhana, P. K. W
    This paper examines the possibility of introducing an intelligent routing protocol to the Internet, based on the Cognitive Packet Network (CPN) architecture with respect to the Quality of Service (QoS) delivered to the end users. In the present with increasing populations of countries it is clear that present infrastructure does not hold the sufficient capacity to deliver the expected level of service to the end users. Since there is an eminent need for a solution for improving the QoS in the Internet, this research focuses to provide a new network architecture which would improve the QoS, provide reliable and efficient service which can fulfill the ever growing Internet usage demand. This is achieved through a new network architecture known as CPN which is based on the basis of providing the best and user desired QoS. The main underlying technology behind the CPN will be a neural network. The neural network will be learning the changes in the network and adapt to the situation through the knowledge gathered. The packets will collectively learn about the network thus the load on the routers will be minimized. This mechanism completely replaces the need of a routing table thus making routing far more efficient when comparing to current routing protocols like Open Shortest Path First (OSPF). Final outcome of the research is coming to the conclusion that the future of the Internet is with the neural network based intelligent, dynamically adapting and learning CPN infrastructure instead of current packet switched network.
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    An exhaustive search algorithm for checking limit cycle behavior of digital filters
    (IEEE, 1996-10) Premaratne, K; Kulasekere, E. C; Bauer, P. H; Leclerc, L. J
    The presence of limit cycles that may arise in fixed-point arithmetic implementation of a digital filter can significantly impair its performance. This paper presents an algorithm to determine the presence/absence of such limit cycles. For generality, the filter is taken to be in its state-space formulation. The algorithm is applicable independent of filter order, type of quantization nonlinearity, and whether the accumulator is single or double length. It may be utilized to construct limit cycle free regions in filter coefficient space. Once a filter is determined to be limit cycle free, a technique that provides a robustness region in coefficient space where all filters remain limit cycle free is also presented.