Utilising semantic technologies for decision support in dementia care

The main objective of this work is to discuss our experience in utilising semantic technologies for building decision support in Dementia care systems that are based on the non-intrusive on the non-intrusive monitoring of the patient’s behaviour. Our approach adopts context-aware modelling of the patient’s condition to facilitate the analysis of the patient’s behaviour within the inhabited environment (movement and room occupancy patterns, use of equipment, etc.) with reference to the semantic knowledge about the patient’s condition (history of present of illness, dependable behaviour patterns, etc.). The reported work especially focuses on the critical role of the semantic reasoning engine in inferring medical advice, and by means of practical experimentation and critical analysis suggests important findings related to the methodology of deploying the appropriate semantic rules systems, and the dynamics of the efficient utilisation of complex event processing technology in order to the meet the requirements of decision support for remote healthcare systems

Some Plane Symmetric Inhomogeneous Cosmological Models in the Scalar-Tensor Theory of Gravitation

The present study deals with the inhomogeneous plane symmetric models in scalar - tensor theory of gravitation. We used symmetry group analysis method to solve the field equations analytically. A new class of similarity solutions have been obtained by considering the inhomogeneous nature of metric potential. The physical behavior and geometrical aspects of the derived models are also discussed.Comment: 12 pages, 1 figure

Efficiency enhancement of black dye-sensitized solar cell by newly synthesized D-π\pi-A coadsorbents: A theoretical study

In this work, using the DFT and TDDFT, we have theoretically studied the electronic and optical properties of the two recently synthesized coadsorbents Y1 and Y2, which were aimed to enhance the efficiency of the black dye-sensitized solar cells. To determine the solvatochromic shifts, both the implicit and mixed implicit-explicit models have been used. The connection between the solvatochromic shifts and the changes of dipole moments in the excitation process is discussed. The difference in excitation charge transfer is utilized to explain the experimentally observed difference in $J_{sc}$ for Y1 and Y2. Investigating the interactions of I$_2$ molecules in the electrolyte solution with the coadsorbents showed that with Y1 the recombination loss was weakened through decreasing the I$_2$ concentration near the TiO$_2$ surface, whereas with Y2 it was increased. As a result, the higher values of both $J_{sc}$ and $V_{oc}$ with Y1 coadsorbent explains its experimentally observed higher efficiency. The present study sheds light on how to design and engineer newer coadsorbents or organic dyes for higher efficiencies.Comment: 10 pages, Double-column, 11 png figures, LaTeX forma

The edge environment in Cairo: An approach to reading the social pattern language of the Middle Eastern built environment

AbstractThis paper introduces a new concept that might help in reading both social life and urban process, showing how they are interlocked in a way that clarifies ideologies and their implications for the physical form of the city. This reading is capable of envisioning and analysing the relationship between the cohesive social pattern language of traditional built environment and its physical expression, relying on a new reflective and exploratory concept, the edge environment. This illuminates the relationship between the values hidden beneath the physical edges of spatial morphology in Middle Eastern urban contexts like Cairo, and allows those values to be understood in terms of modern ideologies relating to the human community. The concept of edge environment might help in the design education particularly in conservation and up-grading processes, as an analytical tool and as a design method by careful interventions at edges by fine tuning of the edge environment

Echo state network for occupancy prediction and pattern mining in intelligent environment

Pattern analysis and prediction of sensory data is becoming an increasing scientific challenge and a massive economical interest supports the need for better pattern mining techniques. The aim of this paper is to investigate efficient mining of useful information from a sensor network representing an ambient intelligence environment. The goal is to extract and predict behavioral patterns of a person in his/her daily activities by analyzing the time series data representing the behaviour of the occupant, generated using occupancy sensors. There are various techniques available for analysis and prediction of a continuous time series signal. However, the occupancy signal is represented by a binary time series where only discrete values of a signal are available. To build the prediction model, recurrent neural networks are investigated. They are proven to be useful tools to solve the difficulties of the temporal relationships of inputs between observations at different time steps, by maintaining internal states that have memory. In this paper, a special form of recurrent neural network, the so-called Echo State Network (ESN) is used in which discrete values of time series can be well processed. Then, a model developed based on ESN is compared with the most popular recurrent neural net-works; namely Back Propagation Through Time (BPTT) and Real Time Recurrent Learning (RTRL). The results showed that ESN provides better prediction results compared with BPTT and RTRL. Using ESN, large datasets are learnt in only few minutes or even seconds. It can be concluded that ESN are efficient and valuable tools in binary time series prediction. The results presented in this paper are based on simulated data generated from a simulator representing a person in a 1 bedroom flat

Secure and privacy-aware proxy mobile IPv6 protocol for vehicle-to-grid networks

Vehicle-to-Grid (V2G) networks have emerged as a new communication paradigm between Electric Vehicles (EVs) and the Smart Grid (SG). In order to ensure seamless communications between mobile EVs and the electric vehicle supply equipment, the support of ubiquitous and transparent mobile IP communications is essential in V2G networks. However, enabling mobile IP communications raises real concerns about the possibility of tracking the locations of connected EVs through their mobile IP addresses. In this paper, we employ certificate-less public key cryptography in synergy with the restrictive partially blind signature technique to construct a secure and privacy-aware proxy mobile IPv6 (SP-PMIPv6) protocol for V2G networks. SP-PMIPv6 achieves low authentication latency while protecting the identity and location privacy of the mobile EV. We evaluate the SP-PMIPv6 protocol in terms of its authentication overhead and the information-theoretic uncertainty derived by the mutual information metric to show the high level of achieved anonymity