Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid

Recently there has been increasing interest in improving smart grids efficiency using computational intelligence. A key challenge in future smart grid is designing Optimal Power Flow tool to solve important planning problems including optimal DG capacities. Although, a number of OPF tools exists for balanced networks there is a lack of research for unbalanced multi-phase distribution networks. In this paper, a new OPF technique has been proposed for the DG capacity planning of a smart grid. During the formulation of the proposed algorithm, multi-phase power distribution system is considered which has unbalanced loadings, voltage control and reactive power compensation devices. The proposed algorithm is built upon a co-simulation framework that optimizes the objective by adapting a constriction factor Particle Swarm optimization. The proposed multi-phase OPF technique is validated using IEEE 8500-node benchmark distribution system.Comment: IEEE PES GM 2014, Washington DC, US

The use of animated agents in e‐learning environments: an exploratory, interpretive case study

There is increasing interest in the use of animated agents in e‐learning environments. However, empirical investigations of their use in online education are limited. Our aim is to provide an empirically based framework for the development and evaluation of animated agents in e‐learning environments. Findings suggest a number of challenges, including the multiple dialogue models that animated agents will need to accommodate, the diverse range of roles that pedagogical animated agents can usefully support, the dichotomous relationship that emerges between these roles and that of the lecturer, and student perception of the degree of autonomy that can be afforded to animated agents

MODLEACH: A Variant of LEACH for WSNs

Wireless sensor networks are appearing as an emerging need for mankind. Though, Such networks are still in research phase however, they have high potential to be applied in almost every field of life. Lots of research is done and a lot more is awaiting to be standardized. In this work, cluster based routing in wireless sensor networks is studied precisely. Further, we modify one of the most prominent wireless sensor network's routing protocol "LEACH" as modified LEACH (MODLEACH) by introducing \emph{efficient cluster head replacement scheme} and \emph{dual transmitting power levels}. Our modified LEACH, in comparison with LEACH out performs it using metrics of cluster head formation, through put and network life. Afterwards, hard and soft thresholds are implemented on modified LEACH (MODLEACH) that boast the performance even more. Finally a brief performance analysis of LEACH, Modified LEACH (MODLEACH), MODLEACH with hard threshold (MODLEACHHT) and MODLEACH with soft threshold (MODLEACHST) is undertaken considering metrics of throughput, network life and cluster head replacements.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

Uncertainty And Evolutionary Optimization: A Novel Approach

Evolutionary algorithms (EA) have been widely accepted as efficient solvers for complex real world optimization problems, including engineering optimization. However, real world optimization problems often involve uncertain environment including noisy and/or dynamic environments, which pose major challenges to EA-based optimization. The presence of noise interferes with the evaluation and the selection process of EA, and thus adversely affects its performance. In addition, as presence of noise poses challenges to the evaluation of the fitness function, it may need to be estimated instead of being evaluated. Several existing approaches attempt to address this problem, such as introduction of diversity (hyper mutation, random immigrants, special operators) or incorporation of memory of the past (diploidy, case based memory). However, these approaches fail to adequately address the problem. In this paper we propose a Distributed Population Switching Evolutionary Algorithm (DPSEA) method that addresses optimization of functions with noisy fitness using a distributed population switching architecture, to simulate a distributed self-adaptive memory of the solution space. Local regression is used in the pseudo-populations to estimate the fitness. Successful applications to benchmark test problems ascertain the proposed method's superior performance in terms of both robustness and accuracy.Comment: In Proceedings of the The 9th IEEE Conference on Industrial Electronics and Applications (ICIEA 2014), IEEE Press, pp. 988-983, 201

Should a clinical rotation in haematology be mandatory for undergraduate medical students?

Clinical rotations form the foundation of medical education. Medical students in the UK are offered conventional rotations such as cardiology, surgery and psychiatry as part of their curriculum, but a rotation of haematology is not currently compulsory. This article explores the benefits of a compulsory haematology rotation, and suggests recommendations for its implementation into UK medical school curricula

Improving Extractions of |Vcb| and the b Quark Mass from Semileptonic Inclusive B Decay

Recent advances in improving extractions of |Vcb| and m_b from spectra of semileptonic inclusive B decay are reported. Results of a general moment analysis of the lepton energy spectrum and the hadronic invariant mass spectrum are summarized. The calculation of the general O(\alpha_s) structure functions for semileptonic B decay is reported, which has allowed the calculation of the O(\alpha_s Lambda_{QCD} /m_b) terms for the hadronic invariant mass moments to be carried out. Recent theoretical advances and improvements in experimental data has allowed extractions of the CKM element |Vcb| to improve to the 2% level.Comment: 8 pages, 2 figures. Talk given at MRST2004, May 12-14, Concordia, Montrea

Sustainable water management in Iraq (Kurdistan) as a challenge for governmental responsibility

During the last few decades, a critical scarcity of water has occurred in the Middle East due to climate change and the mismanagement of water resources. The situation is complicated by the absence of an effective legislative framework at the local level as well as by the incapability and disrepute of the local water authorities. Most Iraqi citizens depend on the surface waters of the Tigris and Euphrates rivers, which have their sources in upstream neighbouring countries. Water crises concerning the shared waters urgently require a solution at the international level. Unfortunately, Iraq has faced several wars in a row (1980-2003), which has prevented the country from establishing its institutions. The rapid increase in the population of the transboundary countries on the Tigris and Euphrates rivers, and the high demands on agriculture, are accelerating water exploitation. In this paper, the present state of water management in Iraq from the viewpoint of the legislative framework, water balance, and transboundary issues will be discussed, with special attention to Kurdistan. Many legislative documents have been established or amended by the Iraqi and Kurdistan parliaments since 2003. In 2015, the Kurdistan Government Ministry of Agriculture and Water Resources, in cooperation with the EU, issued a guide for environmental legislation related to all environmental components such as air, water, and soil. The recommendations on actions needed in the water management in Kurdistan will be presented; they are inspired by the Water Framework Directive (WFD) (2000/60/EC) implemented in EU member states.Web of Science1011art. no. 165

Association Rules Mining Based Clinical Observations

Healthcare institutes enrich the repository of patients' disease related information in an increasing manner which could have been more useful by carrying out relational analysis. Data mining algorithms are proven to be quite useful in exploring useful correlations from larger data repositories. In this paper we have implemented Association Rules mining based a novel idea for finding co-occurrences of diseases carried by a patient using the healthcare repository. We have developed a system-prototype for Clinical State Correlation Prediction (CSCP) which extracts data from patients' healthcare database, transforms the OLTP data into a Data Warehouse by generating association rules. The CSCP system helps reveal relations among the diseases. The CSCP system predicts the correlation(s) among primary disease (the disease for which the patient visits the doctor) and secondary disease/s (which is/are other associated disease/s carried by the same patient having the primary disease).Comment: 5 pages, MEDINFO 2010, C. Safran et al. (Eds.), IOS Pres