Effect of high resistive barrier on earthing system

Substation earthing provides a low impedance path and carries current into ground under normal and fault conditions without adversely affecting continuity of service. Under a fault condition, the ground voltage may rise to a level that may endanger the public outside the vicinity of the substation. In such a case a high resistive barrier can be inserted around the vicinity of the substation to reduce the surface potentials immediately beyond the barrier. In this paper the effect of barrier on the overall performance of the earthing system has been investigated experimentally and computationally based on an earthing system consisted of combined grid and rods in a water tank. The effect of the position and depth of the barrier to the resistance of the earthing system and surface potentials in and around the substation have been examined

Investigating the use of semantic technologies in spatial mapping applications

Semantic Web Technologies are ideally suited to build context-aware information retrieval applications. However, the geospatial aspect of context awareness presents unique challenges such as the semantic modelling of geographical references for efficient handling of spatial queries, the reconciliation of the heterogeneity at the semantic and geo-representation levels, maintaining the quality of service and scalability of communicating, and the efficient rendering of the spatial queries' results. In this paper, we describe the modelling decisions taken to solve these challenges by analysing our implementation of an intelligent planning and recommendation tool that provides location-aware advice for a specific application domain. This paper contributes to the methodology of integrating heterogeneous geo-referenced data into semantic knowledgebases, and also proposes mechanisms for efficient spatial interrogation of the semantic knowledgebase and optimising the rendering of the dynamically retrieved context-relevant information on a web frontend

Ectopic Thyroid Presenting as a Sublingual Mass in a Sudanese Girl

Although extremely rare, the presence of ectopic thyroid tissue in the sublingual region should be considered in the differential diagnosis of masses in the cervical region. Diagnosis is confirmed by Fine-needle Aspiration\Biopsy Cytology and exclusion of malignancy by histopathologic analysis of the lesion. In general, surgery should not be attemptrd before radioisotope scan is obtained as this might be the only functioning thyroid tissue.  This is a rare case of ectopic thyroid in the sublingual region reported in a Sudanese girl; it was diagnosed after radioisotope thyroid scan and proved to be the only functioning thyroid tissue. &nbsp

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

The Performance of Candidates in the Examinations of the Otorhinolaryngology Specialty, Sudanese National Board of Medical Specializations

Introduction: The Otorhinolaryngology, Head and Neck Surgery Council is one of the first established councils of the Sudanese National Board of Medical Specializations (SNBMS).This report covers the fourth rotation period from 2009-2013. It is meant to be in the form of an analytical study for more objectivity and transparency and to be a model for promotion of the general performance of other councils in administrative, examination and training issues. Objectives: The main objective of this study is to analyze the trainees’ results in part 1 and part 2 (final) examinations with regard to gender and pass rates and to draw relevant indices that help in planning for training and expansion of specialist services. Materials and Methods: This is an analytical retrospective study conducted at the (SNMSB) headquarters Khartoum, Sudan during the period from January 2009- December 2012 .This study covers the fourth rotation of the scientific council for the specialty. The study included all candidates sitting for both part 1 and part 2 examinations (265). Candidates were classified according to gender and pass rates. Candidates who withdrew form the program after passing the part 1 examination were excluded. Results:  The total number of doctors sitting for part 1 examinant was 207. Females were 118 and males were 89. Female to male ratio was 1.3:1.0. Sixty nine (69) doctors passed the examination with over all pass percentage of 33.3%. The percentage of passed candidates among females was 31% and among males was 36%. The total number for trainees sitting for the final examination was 58. Females were 23 and males were 35. Female to male ratio was 1.0: 1.5. Thirty three (33) trainees passed the examination with over all pass percentage of 56.9%. The percentage of passed trainees among females was 52.2% and among males was 60%. The annual number of doctors sitting for part 1 examination showed marked reduction from 69 in the first year to 48 in the fourth year although there was a steady increase in-between. The average annual pass rate for part 1 examination showed noticeable increase from 23% to 42% by the end of the fourth year. The annual number of trainees sitting for the final examination was fluctuating and the biggest number was in the first year. There was a minimal increase in the number of graduates.  Conclusions: Applicants for part one examination are mostly females. Applicants numbers are generally decreasing. The pass percentages are increasing in both parts of the examination. Males performance in both part one and part two examinations is better than females. The number of graduates does not satisfy the national needs for specialist services provision and expansion

Mathematical modeling of ultra wideband in vivo radio channel

This paper proposes a novel mathematical model for an in vivo radio channel at ultra-wideband frequencies (3.1–10.6 GHz), which can be used as a reference model for in vivo channel response without performing intensive experiments or simulations. The statistics of error prediction between experimental and proposed model is RMSE = 5.29, which show the high accuracy of the proposed model. Also, the proposed model was applied to the blind data, and the statistics of error prediction is RMSE = 7.76, which also shows a reasonable accuracy of the model. This model will save the time and cost on simulations and experiments, and will help in designing an accurate link budget calculation for a future enhanced system for ultra-wideband body-centric wireless systems

Predicting house damage class using artificial intelligence method

The unsatisfactory performance of light structures founded on expansive soils subject to seasonal movements is frequently reported since the early 1950\u27s in Australia. Excessive movements have caused damage to numerous structures that have not been adequately designed to accommodate soil volume changes. However, the sole presence of expansive soil is not necessarily the main cause of damage. Other factors such as vegetation, climate factors, types of construction materials and geology type may also contribute. This paper presents a model which predicts the damage class by analyzing combinations of the contributing factors using artificial intelligence methods. This model can help to identify if any serious and urgent repairs are necessary and immediate actions could be initiated without delay

Einstein Geometrization Philosophy and Differential Identities in PAP-Geometry

The importance of Einstein's geometrization philosophy, as an alternative to the least action principle, in constructing general relativity (GR), is illuminated. The role of differential identities in this philosophy is clarified. The use of Bianchi identity to write the field equations of GR is shown. Another similar identity in the absolute parallelism geometry is given. A more general differential identity in the parameterized absolute parallelism geometry is derived. Comparison and interrelationships between the above mentioned identities and their role in constructing field theories are discussed.Comment: LaTeX file, 17 pages, comments and criticism are welcom