REAL TIME DATA ACQUISITION AND MONITORING OF PATIENTS WITH CORONARY HEART DISEASE IN A HOME ENVIRONMENT

The high mortality rate associated with cardiovascular related diseases requires the implementation of a personalised, ubiquitous health monitoring system. With the recent advancements of wireless sensor network technologies, these study proposes a real time data acquisition and monitoring system for patients with a track history of coronary heart diseases based on the implementation of a microcontroller, GSM Module and temperature sensors. This pervasive healthcare system will provide a round the clock monitoring and has an in built alerting mechanism for detecting anomalies in cardiac activities. The aim of the study is to minimize the need for caretakers and help the gravely ill senior citizens to survive an independent life. Apart from that, this study will help reduce the mortality rate of victim by shortening the response time of medical team to the victims. In these study, the proposed design mechanism will consider the following key criteria namely safety, data security, energy efficiency, durability and cost incurred

Improving cross language information retrieval using corpus based query suggestion approach

Users seeking information may not find relevant information pertaining to their information need in a specific language. But information may be available in a language different from their own, but users may not know that language. Thus users may experience difficulty in accessing the information present in different languages. Since the retrieval process depends on the translation of the user query, there are many issues in getting the right translation of the user query. For a pair of languages chosen by a user, resources, like incomplete dictionary, inaccurate machine translation system may exist. These resources may be insufficient to map the query terms in one language to its equivalent terms in another language. Also for a given query, there might exist multiple correct translations. The underlying corpus evidence may suggest a clue to select a probable set of translations that could eventually perform a better information retrieval. In this paper, we present a cross language information retrieval approach to effectively retrieve information present in a language other than the language of the user query using the corpus driven query suggestion approach. The idea is to utilize the corpus based evidence of one language to improve the retrieval and re-ranking of news documents in the other language. We use FIRE corpora - Tamil and English news collections in our experiments and illustrate the effectiveness of the proposed cross language information retrieval approach

REAL TIME DATA ACQUISITION AND MONITORING OF PATIENTS WITH CORONARY HEART DISEASE IN A HOME ENVIRONMENT

The high mortality rate associated with cardiovascular related diseases requires the implementation of a personalised, ubiquitous health monitoring system. With the recent advancements of wireless sensor network technologies, these study proposes a real time data acquisition and monitoring system for patients with a track history of coronary heart diseases based on the implementation of a microcontroller, GSM Module and temperature sensors. This pervasive healthcare system will provide a round the clock monitoring and has an in built alerting mechanism for detecting anomalies in cardiac activities. The aim of the study is to minimize the need for caretakers and help the gravely ill senior citizens to survive an independent life. Apart from that, this study will help reduce the mortality rate of victim by shortening the response time of medical team to the victims. In these study, the proposed design mechanism will consider the following key criteria namely safety, data security, energy efficiency, durability and cost incurred

Virtual Sensing for Structural Health Monitoring of Off-shore Structures

Department of Urban and Environmental Engineering(Urban Infrastructure Engineering)Offshore structures are generally subjected to harsh environment with strong tidal current and wind loading, which demands robust and reliable Structural Health Monitoring (SHM) to avoid any catastrophic failure. The growing size, complexity, and harsh environment of offshore structures lead to difficulties in sensor deployment and maintenance. Response at critical locations in complex offshore rigs are inaccessible during sensor deployment. Moreover, their operational environment demands frequent sensor maintenance for uninterrupted monitoring. Virtual sensing addresses these issues by estimating unmeasured responses with the help of measured responses. This dissertation delineates a virtual sensing method based on Kalman state estimator to combine multi-sensor data under non-stationary random excitation. The estimation algorithm effectively uses the FE model of a structure to predict and fuse different type of structural response (acceleration, strain, and angular displacement). This study investigates various combinations of sensor fusion to improve the estimation accuracy. In addition, an erroneous model is purposefully used to support the robustness and practicality of estimator. The performance of virtual sensing is successfully verified with numerical and experimental test over simply-supported and bottom fixed off-shore structure. Test results conclude that the unmeasured responses are reasonably recovered form measured responses.ope

Analysis of combustion performance and emission of extended expansion cycle and iEGR for low heat rejection turbocharged direct injection diesel engines

Increasing thermal efficiency in diesel engines through low heat rejection concept is a feasible technique. In LHR engines the high heat evolution is achieved by insulating the combustion chamber surfaces and coolant side of the cylinder with partially stabilized zirconia of 0.5 mm thickness and the effective utilization of this heat depend on the engine design and operating conditions. To make the LHR engines more suitable for automobile and stationary applications, the extended expansion was introduced by modifying the inlet cam for late closing of intake valve through Miller’s cycle for extended expansion. Through the extended expansion concept the actual work done increases, exhaust blow-down loss reduced and the thermal efficiency of the LHR engine is improved. In LHR engines, the formation of nitric oxide is more, to reduce the nitric oxide emission, the internal EGR is incorporated using modified exhaust cam with secondary lobe. Modifications of gas exchange with internal EGR resulted in decrease in nitric oxide emissions. In this work, the parametric studies were carried out both theoretically and experimentally. The combustion, performance and emission parameters were studied and were found to be satisfactory

Modelling IBE-based Key Exchange Protocol using Tamarin Prover

Tamarin Prover is a formal security analysis tool that is used to analyse security properties of various authentication and key exchange protocols. It provides built-ins like Diffie-Hellman, Hashing, XOR, Symmetric and Asymmetric encryption as well as Bilinear pairings. The shortfall in Tamarin Prover is that it does not support elliptic curve point addition operation. In this paper, we present a simple IBE (Identity-Based Encryption) based key exchange protocol and tamarin model. For modelling, we define a function to replace the point addition operation by the concept of pre-computation. We demonstrate that the security model functions for theoretical expectation and is able to resist Man-In-The-Middle (MITM) Attack. This model can be used to analyse the formal security of authentication and key exchange protocols designed based-on the IBE technique

IIDS: Design of Intelligent Intrusion Detection System for Internet-of-Things Applications

With rapid technological growth, security attacks are drastically increasing. In many crucial Internet-of-Things (IoT) applications such as healthcare and defense, the early detection of security attacks plays a significant role in protecting huge resources. An intrusion detection system is used to address this problem. The signature-based approaches fail to detect zero-day attacks. So anomaly-based detection particularly AI tools, are becoming popular. In addition, the imbalanced dataset leads to biased results. In Machine Learning (ML) models, F1 score is an important metric to measure the accuracy of class-level correct predictions. The model may fail to detect the target samples if the F1 is considerably low. It will lead to unrecoverable consequences in sensitive applications such as healthcare and defense. So, any improvement in the F1 score has significant impact on the resource protection. In this paper, we present a framework for ML-based intrusion detection system for an imbalanced dataset. In this study, the most recent dataset, namely CICIoT2023 is considered. The random forest (RF) algorithm is used in the proposed framework. The proposed approach improves 3.72%, 3.75% and 4.69% in precision, recall and F1 score, respectively, with the existing method. Additionally, for unsaturated classes (i.e., classes with F1 score < 0.99), F1 score improved significantly by 7.9%. As a result, the proposed approach is more suitable for IoT security applications for efficient detection of intrusion and is useful in further studies

Performance Analysis of Fuel cell Powered Electric Vehicle Using MATLAB

In this research article, a proton exchange membrane fuel cell (PEMFC) is instrumented as an electrical generator that utilizes hydrogen gas as fuel and air as an oxidizing agent to perform photoelectricity through electrochemical reactions simulated in MATLAB-Simulink environment. Most of the model is based on specifications with direct real-world significance, with a focus of going beyond empirically reporting the features of the fuel cell. Further exploration manifested that the execution of the PEMFC depends on the air supply pressure and rate of fuel supply. The output voltage and current waveforms from the fuel cell stack and the lithium-ion battery’s efficiency and voltage waveforms are plotted as well. We also designed the powertrain systems required for a Fuel cell powered electric vehicle. The Fuel cell vehicle presented draws its power from the hydrogen powered fuel cell instead of relying on a separate battery. Electric Vehicle parameters such as speed and distance have also been plotted showing the efficiency and performance of the system. Obtained results under MATLAB/Simulink and some experimental ones are presented and discussed