Using Case Work as a Pretest to Measure Crisis Leadership Preparedness

Today’s leaders must thrive in a world of turbulence and constant change. Unstable conditions frequently generate crises, emphasizing the need for crisis leadership preparedness, which is missing from many business curricula. Thus, the purpose of this work was to develop a learning module in crisis leadership preparedness. As a baseline measure or pretest, 217 graduate students were asked to analyze two crisis leadership cases during the first week of an entry leadership class. Content analysis provided the method to identify where student analyses fell short. These gaps in learning then informed the creation of student learning objectives. Applying inquiry-based learning, I then suggest instructional methods that I incorporated into an active learning module to better prepare today’s leaders for crisis leadership

The influences of basic physical properties of clayey silt and silty sand on its laboratory electrical resistivity value in loose and dense conditions

Non-destructive test which refers to electrical resistivity method is recently popular in engineering, environmental, archaeological and mining studies. Based on the previous studies, the results on electrical resistivity interpretation were often debated due to lack of clarification and evidences in quantitative perspective. Traditionally, most of the previous result interpretations were depending on qualitative point of view which is risky to produce unreliable outcomes. In order to minimise those problems, this study has performed a laboratory experiment on soil box electrical resistivity test which was supported by an additional basic physical properties of soil test like particle size distribution test (d), moisture content test (w), density test (ρbulk) and Atterberg limit test (LL, PL and PI). The test was performed to establish a series of electrical resistivity value (ERV) with different quantity of water content for clayey silt and silty sand in loose and dense condition. Apparently, the soil resistivity value was different under loose (L) and dense (C) conditions with moisture content and density variations (silty SAND = ERVLoose: 600 - 7300 Ωm & ERVDense: 490 - 7900 Ωm while Clayey SILT = ERVLoose: 13 - 7700 Ωm & ERVDense: 14 - 8400 Ωm) due to several factors. Moreover, correlation of moisture content (w) and density (ρbulk) due to the ERV was established as follows; Silty SAND: w(L) = 638.8ρ-0.418, w(D) = 1397.1ρ-0.574, ρBulk(L) = 2.6188e-6E-05ρ, ρBulk(D) = 4.099ρ-0.07 while Clayey SILT: w(L) = 109.98ρ-0.268, w(D) = 121.88ρ-0.363, ρBulk(L) = -0.111ln(ρ) + 1.7605, ρBulk(D) = 2.5991ρ-0.037 with determination coefficients, R2 that varied from 0.5643 – 0.8927. This study was successfully demonstrated that the consistency of ERV was greatly influenced by the variation of soil basic physical properties (d, w, ρBulk, LL, PL and PI). Finally, the reliability of the ERV result interpretation can be enhanced due to its ability to produce a meaningful outcome based on supported data from basic geotechnical properties

Optimising routing and trustworthiness of ad hoc networks using swarm intelligence

This thesis was submitted for the degree of Doctor of Philsophy and awarded by Brunel UniversityThis thesis proposes different approaches to address routing and security of MANETs using swarm technology. The mobility and infrastructure-less of MANET as well as nodes misbehavior compose great challenges to routing and security protocols of such a network. The first approach addresses the problem of channel assignment in multichannel ad hoc networks with limited number of interfaces, where stable route are more preferred to be selected. The channel selection is based on link quality between the nodes. Geographical information is used with mapping algorithm in order to estimate and predict the links’ quality and routes life time, which is combined with Ant Colony Optimization (ACO) algorithm to find most stable route with high data rate. As a result, a better utilization of the channels is performed where the throughput increased up to 74% over ASAR protocol. A new smart data packet routing protocol is developed based on the River Formation Dynamics (RFD) algorithm. The RFD algorithm is a subset of swarm intelligence which mimics how rivers are created in nature. The protocol is a distributed swarm learning approach where data packets are smart enough to guide themselves through best available route in the network. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive data packets in order to maintain and find better routes. Data packets act like swarm agents (drops) where they carry their path information and update routing information without the need for backward agents. These data packets modify the routing information based on different network metrics. As a result, data packet can guide themselves through better routes. In the second approach, a hybrid ACO and RFD smart data packet routing protocol is developed where the protocol tries to find shortest path that is less congested to the destination. Simulation results show throughput improvement by 30% over AODV protocol and 13% over AntHocNet. Both delay and jitter have been improved more than 96% over AODV protocol. In order to overcome the problem of source routing introduced due to the use of the ACO algorithm, a solely RFD based distance vector protocol has been developed as a third approach. Moreover, the protocol separates reactive learned information from proactive learned information to add more reliability to data routing. To minimize the power consumption introduced due to the hybrid nature of the RFD routing protocol, a forth approach has been developed. This protocol tackles the problem of power consumption and adds packets delivery power minimization to the protocol based on RFD algorithm. Finally, a security model based on reputation and trust is added to the smart data packet protocol in order to detect misbehaving nodes. A trust system has been built based on the privilege offered by the RFD algorithm, where drops are always moving from higher altitude to lower one. Moreover, the distributed and undefined nature of the ad hoc network forces the nodes to obligate to cooperative behaviour in order not to be exposed. This system can easily and quickly detect misbehaving nodes according to altitude difference between active intermediate nodes

Enhancing Workflow with a Semantic Description of Scientific Intent

Peer reviewedPreprin

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

An ensemble of intelligent water drop algorithm for feature selection optimization problem

Master River Multiple Creeks Intelligent Water Drops (MRMC-IWD) is an ensemble model of the intelligent water drop, whereby a divide-and-conquer strategy is utilized to improve the search process. In this paper, the potential of the MRMC-IWD using real-world optimization problems related to feature selection and classification tasks is assessed. An experimental study on a number of publicly available benchmark data sets and two real-world problems, namely human motion detection and motor fault detection, are conducted. Comparative studies pertaining to the features reduction and classification accuracies using different evaluation techniques (consistency-based, CFS, and FRFS) and classifiers (i.e., C4.5, VQNN, and SVM) are conducted. The results ascertain the effectiveness of the MRMC-IWD in improving the performance of the original IWD algorithm as well as undertaking real-world optimization problems

Digital Twins

Progression of the field depends on convergence of information technology, operational technology and protocol-agnostic telecommunications. Making sense of the data, ability to curate data and perform data analytics at the edge (or mist rather than in the fog or cloud) is key to value. Delivering engines to the edge are crucial for analytics at the edge when latency is critical. The confluence of these and other factors may chart the future path for Digital Twins. The number of unknown unknowns and the known unknowns in this process makes it imperative to create global infrastructures and organize groups to pursue the development of fundamental building blocks and new ideas through research.Multiple forms of digital transformation are imminent. Digital Twins represent one concept. It is gaining momentum because it may offer real-time transparency. Rapid diffusion of digital duplicates faces hurdles due to lack of semantic interoperability between architectures, standards and ontologies. The technologies necessary for automated discovery are in short supply

Local search: A guide for the information retrieval practitioner

There are a number of combinatorial optimisation problems in information retrieval in which the use of local search methods are worthwhile. The purpose of this paper is to show how local search can be used to solve some well known tasks in information retrieval (IR), how previous research in the field is piecemeal, bereft of a structure and methodologically flawed, and to suggest more rigorous ways of applying local search methods to solve IR problems. We provide a query based taxonomy for analysing the use of local search in IR tasks and an overview of issues such as fitness functions, statistical significance and test collections when conducting experiments on combinatorial optimisation problems. The paper gives a guide on the pitfalls and problems for IR practitioners who wish to use local search to solve their research issues, and gives practical advice on the use of such methods. The query based taxonomy is a novel structure which can be used by the IR practitioner in order to examine the use of local search in IR