A comparison of cancer classification methods based on microarray data.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.Cancer is among the leading causes of death in both developed and developing countries. Through gene expression profiling of tumors, the accuracy of cancer classification has been enhanced, leading to correct diagnoses and the application of effective therapies. Here, we discuss a comparative review of the binary class predictive ability of seven classification methods (support vector machines, with the radial basis kernel (SVM(RK)), linear kernel (SVM(LK)) and the polynomial kernel (SVM(PK)), artificial neural networks (ANN), random forests (RF), k-nearest neighbor (KNN), and naive Bayes (NB)), using publicly-available gene expression data from cancer research. Results indicate that NB outperformed the other methods in terms of the accuracy, sensitivity, specificity, kappa coefficient, area under the curve (AUC), and balanced error rate (BER) of the binary classifier. Thus, overall the Naive Bayes (NB) approach turned out to be the best classifier with our datasets

A Preliminary Study on Internet Impacts Toward Human Resources Operation: A Case of Selected HR Agencies in Kuala Lumpur

The impact of Information and Communication Technologies has been one of the most exciting major events in the 20th century. The reason why the internet seems all-powerful is because it has two characteristics no other mechanism possesses: First, the internet contains the biggest resource of information in the entire world; second, it enables people to obtain an interactive platform to instantly communicate with each other. The internet has attracted a great deal of interest in the field of human resources. Employers are increasingly turning to the web as a recruitment tool because online techniques are relatively cheap, are more dynamic and can often produce faster results than traditional methods of recruitment. This has impacted negatively on the operations of human resources agencies. A second school of thought believes that the advent of the internet has been positive through the introduction of more efficient tools for effective human resources management. This study provides insights into the impact of the internet on the management and operations of human resources agencies. The internet is shown as providing a whole set of challenges and opportunities for the human resources agency sector. The study shows that human resources agencies continue to play a key role in terms of defining and controlling the overall recruitment strategy and ensuring that systems are flexible to meet changing recruitment needs. All agencies face a threat from "side intermediation" because of the ways in which new technologies enable companies to recruit quickly at a relatively low cost. However, the overriding lesson is that the internet enables human resources agencies to continually innovate with new technologies themselves, finding ways of using technology to add real value to the services that they provide

Estimating electron probe diameter in the scanning electron microscope

The research aims to produce the theoretical study on the objective magnetic lens to estimate the electron probe diameter through the study of the parameters that effect on the efficiency of the scanning electron microscope, the optical performance of the objective lens depends  used in the scanning electron microscope by ability to form  precise electron probe and it focus on the specimen surface to be examined. The affective final electron probe diameter represented dp of the most important parameters that determine the resolving power in the scanning electron microscope, which in it role depends on several parameters related by focal properties of the objective lens as focal length f, Spherical Cs, chromatic Cc and diffraction dd aberration coefficients ,As it has been calculating the affective total diameter dp to the incident electron beam on the specimen surface , and the accompanying from broadening due contributions the Spherical , chromatic and diffraction aberrations which suffers from it the objective lens as a function of the angle of aperture αp to get on the smaller size of the electron probe at optimal aperture angle Keywords: electron probe diameter, magnetic objective lens, magnetic lens focal properties

Statistical and deep learning methods for cancer genomic data.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Statistical and machine learning methods have been applied in broad domains including the medical field. These methods have a massive impact on healthcare by providing the support for decision making to the specialist in diagnosis and prognosis of patient disease status and disease progression. Non-communicable diseases (NCDs) remain a major challenge the world over in the 21st century, especially in developing countries where resources are limited. Recent global public health research shows an epidemiological paradigm shift from infection to non-communicable diseases, which include cancer. Cancer is considered the most devastating among all NCDs and is ranked second to malaria as the leading causes of death in the developing countries. Cancer occurs in many different types affecting all community members, where the general mechanism of cancer disease etiology is uncontrolled cells proliferation that leads to a malignant or cancerous tumor, and abnormalities at the molecular level. However, earlier detection and accurate diagnosis of cancer symptoms increase the probability of curing the condition, which has become the best strategy for fighting the disease. In the past few years, a vast amount of cancer data have been generated through new high throughput technologies. Traditional clinical and experimental approaches lack the capacity to handle such a massive scale of data. Therefore, computational methods have been introduced to biomedical investigations, including genes/biomarkers selection of cancer types and stages of the disease. Many computational tools have been developed based on different statistical and machine learning strategies and data science approaches. We used statistical, machine and deep learning methods for cancer types, subtypes, and survival prediction in this work. First, we developed a hybrid (DNA mutation and RNA expression) signature and assessed its predictive properties for colorectal cancer (CRC) patients’ mutation status and survival. In addition, we proposed a stacking ensemble deep learning approach to evaluate and compare its predictive performance for cancer types (as a multi-class classification problem) with the different standard machine and deep learning methods. Finally, we assessed the predictive performance of the Cox proportional hazard and random survival forests methods based on a signature obtained using three gene mutations (KRAS, BRAF, and TP53). However, the most significant limitation lies in the sample size being small, and there is a lack of using independent data for validation. Also, we did not consider different features such as methylation and mutation data. Moreover, it is unfortunate that the study did not include detailed simulation studies to compare the traditional statistical and machine learning methods. Overall, the most prominent finding to emerge from this investigation is that combining different data sources leads to more robust statistical significance. Also, the stacking approach is more reliable and promising compared to a single machine or deep learning. Furthermore, the RSF is a proper and striking method for survival analysis since it does not depend on any model assumptions

Identity Crises and Religionism Attitudes

Das Scheitern der Gesellschaft, Lösungen für ihre Krisen zu finden, führt zu Krisen im Leben der Adoleszentenin einer Phase wo es für sie besonders wichtig ist, an etwas glauben zu können. Wenn einePerson erlebt, dass sie unter Ambiguität und Widersprüchen leidet und unfähig ist, ein klares Selbstbildzu bilden, kompensiert sie dies durch die Einbeziehung anderer kollektiver Identitäten, gekennzeichnetdurch gewaltsame Ideologien, die ihr Sicherheit bieten können. Innerhalb solcher ethnischer, konfessionellerund religiöser Extremgruppen finden die Jugendlichen nicht ihre Identität, sondern Interpretationenihrer Krise und ein Versprechen für eine bessere Zukunft.Es wurden Fragebögen zur intoleranten Einstellungen und Identitätskrise einer ausgewählten Gruppevon männlichen und weiblichen irakischen Jugendlichen vorgegeben. Statistische Indikatoren für eineIdentitätskrise zeigen, dass die Jugendlichen ihre Identitätskrisen als Ergebnis von zwei wichtigen Faktorensehen, nämlich den widersprüchliche Rollen und der Annahme einer negativen Identität (Anpassungan eine negative Identität).Society's failure to find solutions to crises leads to struggles in adolescents’ lives, as they need somethingto have faith in. When an individual finds he/she suffers from ambiguity, contradiction and inabilityto form a clear self-concept, he/she rushes to compensate by involving in other collective identitiescharacterized by violent ideologies that offer certainty to them. Within such ethnic, sectarian andreligious extreme groups the teenagers do not find their identities, but find interpretations to theircrises and promises for a better future. Therefore, identity is not only a personal and individual gift,but also a collective concept rooted in individual's homely, ethnic, sectarian and religious belonging.Both the intolerant attitudes questionnaire and scale identity crisis have been applied to a sample ofmale and female teenagers. Statistical indicators of adolescents' identity crisis show that the adolescents'identity crisis is the product of two important factors which are clear and evident in socializingsystem, namely the Contradictory of roles, and Adopting a negative identity (Adaptation to a negativeidentity).The research results show that there is a positive and significant relationship between identity crisisand intolerant attitudes among adolescents. This can be explained in the psychological debilitationcaused by the failure to set clear parameters for the relevant scattering self-images and the confusionof psychological and social role in adolescents

Immunohistochemical Expression of Epidermal Growth Factor Receptor in Astrocytic Tumors in Iraqi Patients

BACKGROUND: Diffuse astrocytomas constitute the largest group of primary malignant human intracranial tumours. They are classified by the World Health Organization (WHO) into three histological malignancy grades: diffuse astrocytomas (grade II), anaplastic astrocytomas (grade III) and glioblastoma (grade IV) based on histopathological features such as cellular atypia, mitotic activity, necrosis and microvascular proliferation. Epidermal growth factor receptor (EGFR) is a 170-kDa transmembrane tyrosine kinase receptor expressed in a variety of normal and malignant cells regulating critical cellular processes. When activated, epidermal growth factor receptor (EGFR) triggers several signalling cascades leading to increased proliferation and angiogenesis and decreased apoptosis and hence associated with aggressive progression of the tumour. Epidermal growth factor receptor (EGFR) level is known to be a strong indicator associated with the aggressive behaviour of the tumour and acts as a prognostic factor for evaluating the survival rate. AIM: To evaluate the expression of epidermal growth factor receptor (EGFR) in different grades of astrocytoma. MATERIAL AND METHODS: formalin-fixed paraffin-embedded astrocytic tumours of 44 patients were collected from the archival material of pathology department of Ghazi Al Hariri Teaching Hospital during the period from June to December 2018. Hematoxylin and eosin-stained sections were used to characterise the tumours histologically based on cellularity, nuclear hyperchromasia, polymorphism, mitotic activity, vascular proliferation and necrosis with or without pseudopallisading of tumour cells. Diagnosis and grading of astrocytic tumours in this study were made according to WHO criteria (2016). Using a monoclonal antibody to the epidermal growth factor receptor (EGFR) and immunohistochemical analysis, the expression and distribution of epidermal growth factor receptor in astrocytic tumours were examined. RESULTS: The study included 1 case pilocytic astrocytoma (grade I), 20 cases diffuse astrocytoma (grade II), 5 cases anaplastic astrocytoma (grade III) and 18 cases of glioblastoma (grade IV). Expression of EGFR was found in 38.88% of the glioblastoma samples (grade IV). However, none of the astrocytomas of WHO grades I, II and III showed immunoreactivity for EGFR protein. Different patterns of immunoreactive cells and significant intratumor heterogeneity of EGFR expression were observed in glioblastomas. CONCLUSION: The immunohistochemical expression of Epidermal growth factor receptor (EGFR) was restricted only to high-grade astrocytic tumours, namely glioblastoma, thus may use to predict glioblastoma

Palmprint Recognition by using Bandlet, Ridgelet, Wavelet and Neural Network

Palmprint recognition has emerged as a substantial biometric based personal identification. Tow types of biometrics palmprint feature. high resolution feature that includes: minutia points, ridges and singular points that could be extracted for forensic applications. Moreover, low resolution feature such as wrinkles and principal lines which could be extracted for commercial applications. This paper uses 700nm spectral band PolyU hyperspectral palmprint database. Multiscale image transform: bandlet, ridgelet and 2D discrete wavelet have been applied to extract feature. The size of features are reduced by using principle component analysis and linear discriminate analysis. Feed-forward Back-propagation neural network is used as a classifier. The recognition rate accuracy shows that bandlet transform outperforms others

Strain analysis at flat surfaces of loaded members using digital image correlation technique

This research examines the applicability of the planned Digital Image Correlation (DIC) system to measure the strains in tensile experiments. DIC is a low-cost optical technique, and is an appropriate measurement used to measure surface displacement, strain and stress map distribution without any contact with the tested surfaces. In the present research, the tensile test is conducted on two different flat samples, which are painted in a speckle pattern on the tested surface to use DIC features in stain measurements. To guarantee the efficiency of the planned DIC system, the DIC code has been built using MATLAB programming language. The obtained results from DIC technique is compared with the results from open-source software (Ncorr), the finite element analysis (ANSYS) as well as the exact and analytical solutions. The comparison results showed that there was A quite acceptable and agreement achieved between them. According to the exact solution, The percentage of accuracy of the obtained results for the Aluminum without hole plate was around (89-93) % whereas the accuracy with the NCORR was about 96 %. For the second copper plate with a central hole, the accuracy has been obtained to be (80.7-99) % with the analytical solution wherein its value has reached (81-97) % with Ncorr software

Investigation of the Supply Chain Management and Cash Balances Impact on Planning

Cash reserves of bank, including bill, coins and check, which are used for daily operation of customers, shall be managed so that in spite of covering the risk of liquidity, arising from cash deficit, the cost of cash excess stagnation is minimized. Therefore, the aim of this study is to optimize the remained cash of banks branches fund. To determine the optimum limit of money in the funds, we used two approaches of time series and propagation model 4 and prediction was conducted monthly and seasonally. The function of possible distribution of deposits and withdrawals of branch customers' cash and required net liquidity as well as the function of time distribution of cash deposit and withdrawal were used in the propagation model. The used data were daily gathered in the time intervals of 2016-2017 from the selected branches. Using the conducted stimulation, in addition to determine the optimal limit of money maintenance in fund, money limit was 25% reduced in comparison with current situation