A differential operator realisation approach for constructing Casimir operators of non-semisimple Lie algebras

We introduce a search algorithm that utilises differential operator realisations to find polynomial Casimir operators of Lie algebras. To demonstrate the algorithm, we look at two classes of examples: (1) the model filiform Lie algebras and (2) the Schr\"odinger Lie algebras. We find that an abstract form of dimensional analysis assists us in our algorithm, and greatly reduces the complexity of the problem.Comment: 22 page

On Casimir Operators of Conformal Galilei Algebras

In previous work, we introduced an algorithm that utilises differential operator realisations to find polynomial Casimir operators of Lie algebras. In this article we build on this work by applying the algorithm to several classes of finite dimensional conformal Galilei algebras with central extension. In these cases we highlight the utility of an algebra anti-automorphism, and give relevant details through key examples.Comment: 18 page

Improved movie recommendations based on a hybrid feature combination method

Recommender systems help users find relevant items efficiently based on their interests and historical interactions with other users. They are beneficial to businesses by promoting the sale of products and to user by reducing the search burden. Recommender systems can be developed by employing different approaches, including collaborative filtering (CF), demographic filtering (DF), content-based filtering (CBF) and knowledge-based filtering (KBF). However, large amounts of data can produce recommendations that are limited in accuracy because of diversity and sparsity issues. In this paper, we propose a novel hybrid method that combines user–user CF with the attributes of DF to indicate the nearest users, and compare four classifiers against each other. This method has been developed through an investigation of ways to reduce the errors in rating predictions based on users’ past interactions, which leads to improved prediction accuracy in all four classification algorithms. We applied a feature combination method that improves the prediction accuracy and to test our approach, we ran an offline evaluation using the 1M MovieLens dataset, well-known evaluation metrics and comparisons between methods with the results validating our proposed method

Investigation of the Influences of Human Error Factor in Maritime Transportation

Marine transport has a vital role in people and cargo transport across the world, where, more than 90% of the world’s cargo transports by merchant ships. Marine transport industry is considered one of the huge and high-risk industries. This clarify why safety is one of the imperatives of the maritime industry and which highly affect the success and efficient exist of this industry. Therefore, reducing the associate risks and improving maritime safety are of the essential requirements for main marine transport industry. There are many parameters contributing into improving maritime safety and reducing the associate risks of accidents. Efforts are presented and attention is given by shipping industry toward that. This is mainly by focusing in safety regulations, improving ship’s structural design and construction methodologies and techniques and by improving ship’s systems operation and reliability. Accordingly, improvements in ship’s hull design, building processes and methodologies; utilization of advanced technologies and equipment and improving ships legislation and regulations have been clearly noticed. Instead of that, the maritime casualty rate and accidents are still high. This is because ship structure and system reliability are a relatively small part of the safety equation. Where, ship safety is highly affected by human actions as the majority of maritime accidents are consequences of human error. Meanwhile, human factors have the largest share in marine accidents, where, more than 80% of marine accidents have been caused by human error. Therefore, human error is one of the most important issues concerning global maritime communities and it is one of the important factors in the assessment of maritime accidents. Several studies are conducted to assess the contribution of human factors in maritime accidents in order to reduce the overall number of marine accidents. The study of human behavior in the field of marine activities is challenging task due to the difficulties, expenses, and time-consuming factors. Moreover, there is lack of information on the role of human in marine accidents. This study aiming at presenting the effect of human errors in the overall maritime safety. This is through analyzing 98 of ships accidents happened during 2014-2017 to investigate the main parameters contributing in these accidents, identify human error related causes and estimate the overall contribution of the human error causes to the occurrence of these accidents. The results of the analysis indicated that 75% of the causes of the registered accidents were due to human error. In order to provide details about the contribution of the human error to the overall ship accidents causes, analysis to the reported accidents by European Marine Casualty Information Platform from 2011-2017 for cargo ships, fishing vessels, passenger ships and service ships. The results of survey indicated high contribution of human error to the causes of ships accidents, where it represents: • 62.2% of the total of 156 accidental events analyzed of service ships • 60.8% of the total of 781 accidental events analyzed of cargo ships • 54.4% of the total of 338 accidental events analyzed of fishing vessels • 51.4% of the total of 319 accidental events analyzed of passenger ships Moreover, a detailed analysis of a collision case study between Kuwaiti oil tanker “Kaifan” and cargo ship “Unison Star” collided at Chittagong - Bangladesh anchorage area (2017). The analysis of the collision case study conducted using step-by-step events evaluation technique and a systematic process for accident investigation based on comprehensive and multi linear description of events sequences using STEP methodology to investigate rout causes of the collision and identify the contribution of human error causes. The results of investigation clearly prove the contribution of human error as a main factor led to collision. In addition, this thesis investigates collision avoidance procedures, which use a dedicated negotiation and communication system to optimize locally found trajectories according to a global performance measure. This is by introducing, discussing and analyzing of three ship collisions avoidance algorithms based on multiple‐ship situations, which are the Distributed Local Search Algorithm (DLSA), the Distributed Tabu Search Algorithm (DTSA) and the Distributed Stochastic Search Algorithm (DSSA) Furthermore, in experimental results, compared to DLSA and DTSA, DSSA produced good results, such as decreasing the number of messages. Therefore, DSSA enables ships to exchange significantly fewer messages than DLSA and DTSA then I developed a mathematical algorithm for the risk assessment and collision avoidance and calculating collision risk index and present a criteria to be applied and present the MATLAB code which used to calculate collision risk index. Finally, the thesis ended by detailed conclusions, remarks and recommendations to improve maritime safety and improving human factor by eliminating the concerned associated errors.Chapter 1 Introduction 1 1.1 Research Motivation and Problem Identification 1 1.2 Ship Accident Types 2 1.3 Human Error Definition 4 1.4 Research Questions 5 1.5 Aim and Objectives 6 1.6 Contribution 7 1.7 Thesis Structure 8 Chapter 2 Literature Review 10 2.1 Introduction 10 2.2 Investigation the Causes of Marine Accident 10 2.2.1 Gained Points from Literature Review 14 2.2.2 Human Errors Contribution on Maritime Accidents 14 2.2.3 Gained Points from Literature Review of Human Error Contribution 17 2.3 Marine Accident Investigation Methods 18 2.3.1 Events and Causal Factors Charting (ECFC) 18 2.3.2 STEP (Sequential Timed Events Plotting) 21 2.3.3 Fault Tree Analysis (FTA) 22 2.3.4 Event Tree Analysis 23 2.3.5 Root Cause Analysis 25 2.3.6 SHELL Analysis Method 27 2.3.7 Step-By-Step Approach 29 Chapter 3 Analysis and Investigation of Human Error Influences on Maritime Transportation 30 3.1 Introduction 30 3.2 Analysis of KOTC’s Ships Accidents 31 3.2.1 Statistical Survey of KOTC’s Ships Accidents 31 3.2.2 Human Error Types on Ship Accidents 36 3.3 Analysis of Ship Accidents Types and Causes Reported By EMCIP 39 3.4 Human Error Contribution to the Overall Ships Accidents (2011 – 2017) 42 Chapter 4 Detailed Analysis Methodology of KOTC Ship Accident Case Study 55 4.1 Introduction 55 4.2 Description of Chittagong – Bangladesh Port 55 4.3 Description of Vessels 59 4.3.1 Kaifan Oil Tanker 59 4.3.2 Unison Star Bulk Carrier 62 4.4 Collision Case Study 64 4.4.1 Course of Events 64 4.4.2 Comprehensive and Multi-Linear Description of the Accident Process 68 4.4.3 Collision Consequences 71 4.4.4 Results and Discussion 73 4.5 Recommendation 75 Chapter 5 Ships Collision Avoidance Algorithm 77 5.1 Introduction 77 5.2 Framework and Terminology 78 5.2.1 Framework 78 5.2.2 Terminology 80 5.2.3 Cost and Improvement 84 5.3 Distributed Local Search Algorithm 87 5.3.1 Reason of Selection 87 5.3.2 DLSA Procedure 88 5.3.3 Results 91 5.4 Distributed Tabu Search Algorithm 92 5.4.1 Reason of Selection 92 5.4.2 DTSA Procedure 93 5.4.3 Simulation 96 5.4.4 Results 101 5.5 Distributed Stochastic Search Algorithm 101 5.5.1 Reason of Selection 101 5.5.2 DSSA Procedure 102 5.5.3 Simulation 103 5.5.4 Results 105 5.6 Comparative Analysis between Distributed Algorithms 106 5.6.1 Results 109 Chapter 6 Conclusions and Recommendations 110 6.1 Conclusions 110 6.2 Recommendation 115 Acknowledgement 118 References 119 Appendix (A) Mathematical Collision Avoidance Algorithm 125Docto

Development of an R script for simple lipidomic and metabolomic data analysis

Background: Metabolomic and lipidomic studies generate vast quantities of data that are often analysed in a closed software environment with little to no access to the underlying algorithms. As a result, data processed via different software pipelines yield different results thus leading to a widespread problem of low reproducibility within these fields. To address this problem, we are developing LipidAnalyst; an R based lipidomics software pipeline. As a part of this project, we are creating a simple statistical analysis and graphing module in R to generate accurate, reproducible, high-resolution figures. Methods: R scripts were developed under version 3.5.3 with the capability to undertake statistical analyses (e.g. ANOVA) and post-hoc tests (e.g. Tukey). Additional code plotted resultant information as high resolution violin and box plots that depicted statistical significance. Thereafter, lipidomic and metabolomic data were analysed by this code and compared against commercial software and Metaboanalyst, a primary software used in metabolomic and lipidomic research. Results: Code generated in house demonstrated the same results as those generated using commercial software (e.g. JMP 14.0 Pro) but were different from results obtained by using the MetaboAnalyst pipeline. Conclusions: This study demonstrated the prevalent danger of using closed-source software pipelines for the analysis of lipidomic and metabolomic data without validating the analysis outcomes via open-source software. Open source software such as LipidAnalyst, that has also been independently validated using multiple data sets, can then be published with the results to enable transparency of data analysis and improve the replicability of results across different labs.https://scholarscompass.vcu.edu/gradposters/1092/thumbnail.jp

The Impact of the Teacher’s Personality on the Motivation of Learning the English Language Among Governmental School Students in Saudi Arabia

The current study aimed to identify the impact of the teachers personality on the motivation of learning English among government school students in the city of Abha, Saudi Arabia. The descriptive correlative method was used, and two questionnaires were designed to collect the data. They were distributed electronically, and the study targeted a sample of English language teachers in public secondary schools in Abha, and a sample of high school students in Abha, who were chosen randomly in a simple way. The results of the study showed that English language teachers have personal characteristics that qualify them to teach in high government schools, with an average of (3.6918), which is considered as a highly - approved degree, and that students have a motivation to learn English with an average of (3.7828), which means they scored a high degree of approval. The results also showed the effect of the teachers personality on the motivation of students towards learning English. The results also showed that it is possible to predict the motivation of learning English through the teachers personality

On Using Magnetic and optical methods to determine the size and characteristics of nanoparticles embedded in oxide semiconductors

Films of oxides doped with transition metals are frequently believed to have magnetic inclusions. Magnetic methods to determine the amount of nanophases and their magnetic characteristics are described. The amount of the sample that is paramagnetic may also be measured. Optical methods are described and shown to be very powerful to determine which defects are also magnetic.Comment: Manuscript of poster to be presented at MMM-Intermag 2010. Accepted for publication in Magnetic Trans of IEE

Evidence-Based Use of Cold for Plantar Fasciitis

Objective The purpose of this study was to examine the effect of cold applied the night before or in the morning on pain and symptoms of plantar fasciitis. Design Experimental study. Methods Thirty subjects with plantar fasciitis were recruited for this study. Subjects with plantar fasciitis either had no intervention, cold applied (20 minutes) at night before bed, or 20 minutes in the morning upon wakening. Plantar fascia tenderness and pain were evaluated. There were ten subjects in each group. Measures included visual analog scale, plantar facial thickness via high resolution ultrasound, algometer measure, and range of motion of the ankle and foot. There were 3 groups of 10 subjects, control (no intervention), cold the night before bed, and cold in the morning before rising. Results The greatest relief of symptoms was cold used at bedtime the night before the measurements. Cold used in the morning was not as effective as cold used in the evening before bed. Cold use reduced the thickness of the plantar fascia and irritation. There was a 13% reduction in plantar fascia thickness with cold the night before (p\u3c0.05), a 44% reduction in pain and an 86 % increase in the force that could be applied to the bottom of the foot without pain (p\u3c0.05). Conclusions Cold applied for 20 minutes prior bedtime is effective for reduced symptomology caused by plantar fascia inflammation

Dynamics of electronic transitions and frequency dependence of negative capacitance in semiconductor diodes under high forward bias

We observed qualitatively dissimilar frequency dependence of negative capacitance under high charge injection in two sets of functionally different junction diodes: III-V based light emitting and Si-based non-light emitting diodes. Using an advanced approach based on bias activated differential capacitance, we developed a generalized understanding of negative capacitance phenomenon which can be extended to any diode based device structure. We explained the observations as the mutual competition of fast and slow electronic transition rates which are different in different devices. This study can be useful in understanding the interfacial effects in semiconductor heterostructures and may lead to superior device functionality