The foundation of capability modelling: A study of the impact and utilisation of human resources

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common ground for assessing individuals’ applied capability in a given job based on literature review of various disciplines in engineering, human sciences and economics. A set of criteria is found to be common and appropriate to be used as the basis of this assessment. Applied Capability is then described in this research as the impact of the person in fulfilling job requirements and also their level of usage from their resources with regards to the identified criteria. In other words how their available resources (abilities, skills, value sets, personal attributes and previous performance records) can be used in completing a job. Translation of the person’s resources and task requirements using the proposed criteria is done through a novel algorithm and two prevalent statistical inference techniques (OLS regression and Fuzzy) are used to estimate quantitative levels of impact and utilisation. A survey on post graduate students is conducted to estimate their applied capabilities in a given job. Moreover, expert academics are surveyed on their views on key applied capability assessment criteria, and how different levels of match between job requirement and person’s resources in those criteria might affect the impact levels. The results from both surveys were mathematically modelled and the predictive ability of the conceptual and mathematical developments were compared and further contrasted with the observed data. The models were tested for robustness using experimental data and the results for both estimation methods in both surveys are close to one another with the regression models being closer to observations. It is believed that this research has provided sound conceptual and mathematical platforms which can satisfactorily predict individuals’ applied capability in a given job. This research has contributed to the current knowledge and practice by a) providing a comparison of capability definitions and uses in different disciplines, b) defining criteria for applied capability assessment, c) developing an algorithm to capture applied capabilities, d) quantification of an existing parallel model and finally e) estimating impact and utilisation indices using mathematical methods

The number of distinguishing colorings of a Cartesian product graph

A vertex coloring is called distinguishing if the identity is the only automorphism that can preserve it. The distinguishing threshold $\theta(G)$ of a graph $G$ is the minimum number of colors $k$ required that any arbitrary $k$-coloring of $G$ is distinguishing. In this paper, we calculate the distinguishing threshold of a Cartesian product graph. Moreover, we calculate the number of non-equivalent distinguishing colorings of grids.Comment: 11 pages, 4 figure

A Characterization For 2-Self-Centered Graphs

A Graph is called 2-self-centered if its diameter and radius both equal to 2. In this paper, we begin characterizing these graphs by characterizing edge-maximal 2-self-centered graphs via their complements. Then we split characterizing edge-minimal 2-self-centered graphs into two cases. First, we characterize edge-minimal 2-self-centered graphs without triangles by introducing \emph{specialized bi-independent covering (SBIC)} and a structure named \emph{generalized complete bipartite graph (GCBG)}. Then, we complete characterization by characterizing edge-minimal 2-self-centered graphs with some triangles. Hence, the main characterization is done since a graph is 2-self-centered if and only if it is a spanning subgraph of some edge-maximal 2-self-centered graphs and, at the same time, it is a spanning supergraph of some edge-minimal 2-self-centered graphs

A new approach for simultaneous DNA-based monitoring of the polluted environments.

Taxon composition and biodiversity analyses are known powerful parameters for environmental site status and environment diagnosis. Many ecological studies assess taxon composition through traditional species identification and use bioindicator species to evaluate environmental conditions. The recent breakthrough in bulk sample sequencing combined with DNA barcoding has created a new era for environmental monitoring. Metabarcoding approaches are more robust in studying alpha, and beta diversity compare to the DNA barcoding and the conventional method of species identification, particularly for rare and cryptic species. Here we built upon ecological studies of bioindicator species and transferred the traditionally named taxa to DNA-based approaches. We developed a small customized DNA database for biodiversity assessment and taxonomic identification of environmental DNA samples using high-throughput amplicon sequences. It contains macroinvertebrate species that are known as indicators of specific environmental conditions. By implementing this small database into the KRAKEN algorithm for the first time, we were able to assess environmental biodiversity compared to other popular methods of taxonomic classification, especially in polluted environments where the taxonomic composition globally change by the presence of anthropogenic drivers. Our method is incredibly faster, and it requires significantly less computational power in contrast to common homology-based techniques. To evaluate our approach, we have also studied the importance of database’s size and the depth of sequencing in taxonomic classification of high-throughput DNA sequences.ThesisMaster of Science (MSc)We developed a small customized DNA database for biodiversity assessment and taxonomic identification of environmental DNA samples using high-throughput amplicon sequences. It contains macroinvertebrate species that are known as indicators of specific environmental conditions. By implementing this small database into the KRAKEN algorithm for the first time, we were able to assess environmental biodiversity compared to other popular methods of taxonomic classification, especially in polluted environments where the taxonomic composition globally change by the presence of anthropogenic drivers. Our method is incredibly faster, and it requires significantly less computational power in contrast to common homology-based techniques

An Investigation of Antioxidant Properties of Zinc and Molybdenum Dithiocarbamates in Hydrocarbons

The oxidation and degradation of hydrocarbons at high temperature and pressure in the presence of oxygen is one of the common oil product problems. There are many antioxidants to prevent or inhibit oxidation processes; molybdenum and zinc dithiocarbamates are known as powerful antioxidants. In this paper, the oxidation inhibition time of cumene has been investigated using zinc and molybdenum dithiocarbamate substituted with different alkyl groups as antioxidants and azobisisobutyronitrile (AIBN) as the initiator. The best result obtained for molybdenum dibutyldithiocarbamate was about 210 min, while zinc dialkyldithiophosphate (ZDDP), a well known commercial antioxidant, showed an oxidation inhibition time of about 14 min under the same conditions. It was shown that antioxidancy properties decreased with increasing the chain length of the substituted alkyl groups. This can be explained by the fact that alkyl groups participate in the oxidation process and thus increasing the alkyl chain length reduces antioxidancy effect. The synergism effect of molybdenum dibenzyl dithiocarbamate on ZDDP was also investigated and the oxidation inhibition time of about 110 min was obtained, which was greater than that of any individual antioxidant.</span

Developing national framework of monitoring and evaluation of non-communicable diseases control and prevention: an experience from Iran

Background: Islamic Republic of Iran, as a country has undergone dramatic and rapid demographical and economic transition leading to increase mortality and morbidity of Non-Communicable Diseases (NCDs). Furthermore, the prevalence of risk factors of NCDs is at alarming range for the population. In response to this challenge, a number of different high level policies have been developed dealing with NCDs, directly or indirectly. However, the fragmentation of policies makes monitoring of NCDs control difficult. Therefore, the aim of the present study was to develop a comprehensive framework for monitoring and evaluating of NCDs control and prevention.  Methods: A qualitative approach with content analysis method was conducted. Components of NCDs monitoring and evaluation framework were extracted and adaptation of components based on requirements of Iran’s health system was made.    Results: Based on the proposed framework, the three main components of NCDs surveillance are as follows; 1) monitoring outcomes (morbidity and mortality); 2) monitoring risk factors; and 3) assessing health care system response, which includes national capacity to prevent NCDs.  Conclusion: The developed framework is a political tool to strengthen activities to control and prevention of NCD and making more effective inter-sectorial collaboration