RFID-based real-time smart waste management system

In an environmental context, the use of RFID (radio frequency identification) and load cell sensor technology can be employed for not only bringing down waste management costs, but also to facilitate automating and streamlining waste (e.g., garbage, recycling, and green) identification and weight measurement processes for designing smart waste management systems. In this paper, we outline a RFID and sensor model for designing a system in real-time waste management. An application of the architecture is described in the area of RFID and sensor based automatic waste identity, weight, and stolen bins identification system (WIWSBIS).<br /

Requirement analysis for building practical accident warning systems based on vehicular ad-hoc networks

An Accident Warning System (AWS) is a safety application that provides collision avoidance notifications for next generation vehicles whilst Vehicular Ad-hoc Networks (VANETs) provide the communication functionality to exchange these notifi- cations. Despite much previous research, there is little agreement on the requirements for accident warning systems. In order to build a practical warning system, it is important to ascertain the system requirements, information to be exchanged, and protocols needed for communication between vehicles. This paper presents a practical model of an accident warning system by stipulating the requirements in a realistic manner and thoroughly reviewing previous proposals with a view to identify gaps in this area

An intelligent forex monitoring system

The need for intelligent monitoring systems has become a necessity to keep track of the complex forex market. The vast currency market is a foreign concept to the average individual. However, once it is broken down into simple terms, the average individual can begin to understand the foreign exchange market and use it as a financial instrument for future investing. We attempt to compare the performance of a Takagi-Sugeno, type neuro-fuzzy system and a feedforward neural network trained using the scaled conjugate gradient algorithm to predict the average monthly forex rates. We considered the exchange values of Australian dollar with respect to US dollar, Singapore dollar, New Zealand dollar, Japanese yen and United Kingdom pounds. The connectionist models were trained using 70% of the data and remaining was used for testing and validation purposes. It is observed that the proposed connectionist models were able to predict the average forex rates one month ahead accurately. Experiment results also reveal that the neuro-fuzzy technique performed better than the neural network <br /

Image featuring for retrieval of multimedia documents

The utilization of massive multimedia documents collections, such as multimedia documents in the global Internet, needs search engines which can rank using both text and image evidence. Massive size and (dynamic) nature of collection can make manual indexing prohibitively expensive in such situations. Traditional search engines utilize only text components of multimedia documents. But there are information needs, which require the utilization of image evidence. In this paper, we investigate image-feature for large and heterogeneous collections. Both the nature and complexities of information needs are key elements for an effective retrieval. Retrieval needs that depend on perceptual similarities (as found in art galleries, building architecture) require the utilization of visual cues. In such situations, the retrieval of multimedia document based on image ranking can provide higher effectiveness. Experimental results show that effectiveness of ranking based on image feature can be higher where perceptual similarities are key elements for retrieval than the retrieval effectiveness of algorithms based on text ranking algorithms <br /

Explicit rate control for MANET

Streaming applications over Mobile Ad-hoc Networks (MANET) require a smooth transmission rate. The Internet is unable to provide this service during traffic congestion in the network. Designing congestion control for these applications is challenging, because the standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless multi hop channel well. In particular, the frequent changes to the network topology and the shared nature of the wireless channel pose major challenges. In this paper, we propose a novel approach, which allows a quick increase of throughput by using explicit feedback from routers

Modeling Security Risks at the System Design Stage Alignment of Mal Activity Diagrams and SecureUML to the ISSRM Domain Model

Turvatehnika disain on üks olulisi süsteemiarenduse komponente. Ta peaks läbima tervet süsteemiarendusprotsessi. Kahjuks pööratakse talle paljudel juhtudel tähelepanu ainult süsteemi arendamise ja haldamise ajal. Paljud turvalise modelleerimise keeled (näiteks Misuse Case, Secure Tropos) aitavad turvariskejuba nõuete analüüsi etapil hallata. Käesolevas magistritöös vaatleme modelleerimisvahendeid (pahateoskeemid ja SecureUML), mida kasutatakse süsteemi disainil. Täpsemalt, me uurime, kuivõrd need vahendid toetavad infosüsteemide turvariskide haldust (Information Systems Security Risks Management, ISSRM). Töö tulemuseks on tabel, mis seab pahateoskeemid ning SecureUML-keele konstruktsioonid ISSRM domeeni mõistetega omavahel vastavusse. Me põhjendame oma analüüsi ning valideerime saadud tulemusi mitmel illustratiivsel näitel. Me loodame, et saadud tulemused aitavad arendajatel paremini aru saada, kuidas turvariske süsteemi disainietapil arvesse võtta. Peale selle, nende keelte analüüs ühisel kontseptuaalsel taustal annab tulevikus võimaluse neid keeli korraga kasutada ning loodud mudeleid ühest keelest teise teisendada.Security engineering is one of the important concerns during system development. It should be addressed throughout the whole system development process; however in many cases it is often dealt only during system development and maintenance. There are several security modeling languages (e.g, Misuse case, Secure Tropos) that help dealing with security risk management at the requirements stage. In this thesis, we are focusing on the modeling languages (e.g. Mal activity diagrams and SecureUML) that are used to design the system. More specifically we investigate how these languages support information systems security risks management (ISSRM). The outcome of this work is an alignment table between the Mal activity diagrams and SecureUML language constructs to the ISSRM domain model concepts. We ground our analysis and validate the received results on the number of illustrative examples. We hope that our results will help developers to understand how they can consider security risks at the system design stage. In addition we open the way for the interoperability between different modeling languages that are analysed using the same conceptual background, thus, potentially leading to the transformation between these modeling approaches

Real-time early infectious outbreak detection systems using emerging technologies

The use of emerging technologies ( such as RFID - Radio Frequency Identification and remote sensing) can be employed to reduce health care costs and also to facilitate the automatic streamlining of infectious disease outbreak detection and monitoring processes in local health departments. It can assist medical practitioners with fast and accurate diagnosis and treatments. In this paper we outline the design and application of a real-time RFID and sensor-base Early Infectious (e.g., cholera) Outbreak Detection and Monitoring (IODM) system for health care.<br /