Influence of single and multiple dry bands on critical flashover voltage of silicone rubber outdoor insulators: simulation and experimental study

Dry band formation on the surface of outdoor insulators is one of the main reasons leading to flashover and power outages. In this paper, a dynamic arc model is proposed for single and multiple dry bands configuration to predict the critical flashover voltage for silicone rubber outdoor insulators. An arc is modelled as a time dependent impedance consisting of a Resistor Inductor Capacitor (RLC) circuit. The effect of dry band location and existence of multiple dry bands on critical flashover voltage is investigated. To validate the proposed model, experiments were conducted in a climate chamber under controlled environmental conditions on rectangular silicone rubber sheets polluted using improved solid layer method based on IEC 60,507. Tests were conducted at different dry band configurations and pollution severity levels. A good correlation was found between experimental results and simulation results. This model can provide a good foundation for the development of mathematical models for station post insulators having multiple dry and clean bands and can be used in the design and selection of outdoor insulators for polluted conditions

Collaborative spectrum sensing optimisation algorithms for cognitive radio networks

The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance

Insights and approaches for low-complexity 5G small-cell base-station design for indoor dense networks

This paper investigates low-complexity approaches to small-cell base-station (SBS) design, suitable for future 5G millimeter-wave (mmWave) indoor deployments. Using large-scale antenna systems and high-bandwidth spectrum, such SBS can theoretically achieve the anticipated future data bandwidth demand of 10000 fold in the next 20 years. We look to exploit small cell distances to simplify SBS design, particularly considering dense indoor installations. We compare theoretical results, based on a link budget analysis, with the system simulation of a densely deployed indoor network using appropriate mmWave channel propagation conditions. The frequency diverse bands of 28 and 72 GHz of the mmWave spectrum are assumed in the analysis. We investigate the performance of low-complexity approaches using a minimal number of antennas at the base station and the user equipment. Using the appropriate power consumption models and the state-of-the-art sub-component power usage, we determine the total power consumption and the energy efficiency of such systems. With mmWave being typified nonline-of-sight communication, we further investigate and propose the use of direct sequence spread spectrum as a means to overcome this, and discuss the use of multipath detection and combining as a suitable mechanism to maximize link reliability

Relationship between female secondary education and economic growth of Pakistan

The main focusing of this study is to examine empirically the connection between female secondary school enrollment and economic growth of Pakistan taking the period of 1975-2014. The variables of the series passed the test of stationary by the first difference as evaluated by the ADF and PP test. Therefore, by employing the Johansen test of cointegration, the result shows that female secondary school enrollment and labor employment have insignificantly long run positive influence on economic growth, however, capital formation has significantly positive impact on economic growth of Pakistan. The Granger causality test based on VECM shows that female secondary school enrollment and GDP have long run two-way causality, however, the short run bidirectional causality does not exist but unidirectional causality, which is running from GDP to female secondary school enrollment.Â

Exploiting peer group concept for adaptive and highly available services

This paper presents a prototype for redundant, highly available and fault tolerant peer to peer framework for data management. Peer to peer computing is gaining importance due to its flexible organization, lack of central authority, distribution of functionality to participating nodes and ability to utilize unused computational resources. Emergence of GRID computing has provided much needed infrastructure and administrative domain for peer to peer computing. The components of this framework exploit peer group concept to scope service and information search, arrange services and information in a coherent manner, provide selective redundancy and ensure availability in face of failure and high load conditions. A prototype system has been implemented using JXTA peer to peer technology and XML is used for service description and interfaces, allowing peers to communicate with services implemented in various platforms including web services and JINI services. It utilizes code mobility to achieve role interchange among services and ensure dynamic group membership. Security is ensured by using Public Key Infrastructure (PKI) to implement group level security policies for membership and service access.Comment: The Paper Consists of 5 pages, 6 figures submitted in Computing in High Energy and Nuclear Physics, 24-28 March 2003 La Jolla California. CHEP0

Bulk Scheduling with the DIANA Scheduler

Results from the research and development of a Data Intensive and Network Aware (DIANA) scheduling engine, to be used primarily for data intensive sciences such as physics analysis, are described. In Grid analyses, tasks can involve thousands of computing, data handling, and network resources. The central problem in the scheduling of these resources is the coordinated management of computation and data at multiple locations and not just data replication or movement. However, this can prove to be a rather costly operation and efficient sing can be a challenge if compute and data resources are mapped without considering network costs. We have implemented an adaptive algorithm within the so-called DIANA Scheduler which takes into account data location and size, network performance and computation capability in order to enable efficient global scheduling. DIANA is a performance-aware and economy-guided Meta Scheduler. It iteratively allocates each job to the site that is most likely to produce the best performance as well as optimizing the global queue for any remaining jobs. Therefore it is equally suitable whether a single job is being submitted or bulk scheduling is being performed. Results indicate that considerable performance improvements can be gained by adopting the DIANA scheduling approach.Comment: 12 pages, 11 figures. To be published in the IEEE Transactions in Nuclear Science, IEEE Press. 200