Nearness to Local Subspace Algorithm for Subspace and Motion Segmentation

There is a growing interest in computer science, engineering, and mathematics for modeling signals in terms of union of subspaces and manifolds. Subspace segmentation and clustering of high dimensional data drawn from a union of subspaces are especially important with many practical applications in computer vision, image and signal processing, communications, and information theory. This paper presents a clustering algorithm for high dimensional data that comes from a union of lower dimensional subspaces of equal and known dimensions. Such cases occur in many data clustering problems, such as motion segmentation and face recognition. The algorithm is reliable in the presence of noise, and applied to the Hopkins 155 Dataset, it generates the best results to date for motion segmentation. The two motion, three motion, and overall segmentation rates for the video sequences are 99.43%, 98.69%, and 99.24%, respectively

STRESS ANALYSIS OF FLEXIBLE THERMOSETTING PIPE

Carbon steel pipeline is widely used in the offshore industry to transport oil and gas from offshore platforms to onshore. However, the main concern lies in the corrosion and flexibility of the pipe, which led to the development of a flexible thermosetting pipeline. Although the new pipeline is flexible and resistant to corrosion, its performance in terms of strength is yet to be tested for deep water applications. Therefore, the stress analysis was conducted using ANSYS Finite Element Modelling software to determine the strength of the flexible thermosetting pipeline in terms of stress, strain and deflection. The results were compared using different materials, which are graphite epoxy and glass fiber epoxy, polyethylene and carbon steel. The results showed that, although the carbon steel performs better, the thermosetting pipeline, using glass fiber, has almost achieved the same strength with a difference of 10% in equivalent stress, 7% in equivalent strain and 4% in total deformation. Further modifications is suggested such as by adding more layers to the thermosetting pipeline to improve its strength and adding fatigue tool or stress tool in the analysis

CUR Decompositions, Similarity Matrices, and Subspace Clustering

A general framework for solving the subspace clustering problem using the CUR decomposition is presented. The CUR decomposition provides a natural way to construct similarity matrices for data that come from a union of unknown subspaces $\mathscr{U}=\underset{i=1}{\overset{M}\bigcup}S_i$. The similarity matrices thus constructed give the exact clustering in the noise-free case. Additionally, this decomposition gives rise to many distinct similarity matrices from a given set of data, which allow enough flexibility to perform accurate clustering of noisy data. We also show that two known methods for subspace clustering can be derived from the CUR decomposition. An algorithm based on the theoretical construction of similarity matrices is presented, and experiments on synthetic and real data are presented to test the method. Additionally, an adaptation of our CUR based similarity matrices is utilized to provide a heuristic algorithm for subspace clustering; this algorithm yields the best overall performance to date for clustering the Hopkins155 motion segmentation dataset.Comment: Approximately 30 pages. Current version contains improved algorithm and numerical experiments from the previous versio

Suicide Rate Predictions In Pakistan By using Neural Networks

Suicide is the understudied subject in Pakistan that is a cause of death all over the world. Seventy-fivepercent of suicide occurs in LMIC.In Pakistan information about suicide is limited. The study is about tofind the number of suicide from major cities of Pakistan and then predict the number of suicides by usingNeural Networks Algorithm. About 24639 cases were found in our research from 2001-18 in majorcities of Pakistan. Hanging and poisoning were the most common methods of suicide. The peak age ofsuicide committers was 20-35 included males and females. The lowest number of suicide was inBahawalpur (130 from 2001 to 2018) and the Highest was in Lahore (5925 from 2001 to 2018)

Biotechnology, important applications and ethics

Background and aims: Recent advances in Genetic Engineering and Biotechnology provided more facilities for human to manipulate and alter any form of life. This technology has many useful applications in medicine, pharmacology, agriculture and industry. The most Important applications of biotechnology are: improving of inherited traits (plants and animals), production of new drugs in live bioreactors, creating models and patterns for the study of human diseases and organ transplantation. Like other technologies, it has own ethical considerations and Subsequently, it has come up with different ideas. So, it can be studied from different aspects of ethics. Methods: This study is a review project. All data that presented in this study were collected from different sources and electronic databases. Results: Although some scientists opposite with some of biotechnology applications using scientific reasons, some are basically opposite with biotechnology in any form and application. Important protestations come from two groups: some religious and some secular. Religious group resist to alteration of life with this concept that any alteration in life using genetic engineering, insult to God decision, humanity and life. Secular also like religious have this belief or faith and assume genetic engineering and biotechnology as insult to humanity and life merit. Conclusion: The analysis of the arguments of these two opponents based on the West ethical principles and the principles of Islamic ethics shows that using biotechnology with its ethical and scientific considerations toward life, not only insult to God decision, humanity and merit but also unusing of it in their concepts can reverse or violate humanity and merit

THE PROCESSES OF MANAGEMENT ACCOUNTING CHANGE IN LIBYAN PRIVATISED COMPANIES: AN INSTITUTIONAL PERSPECTIVE

Abstract: This study explains the management accounting process in two privatised Libyan manufacturing companies. In addition, it investigates the perception of managers regarding the emergence of new management accounting systems and/or practices. Moreover, it explores the effect of institutional factors on management accounting systems. The research is based on a case study of two privatised Libyan companies. It uses triangulation of data collection methods and multiple sources of evidence, including interviews, observation and documentation. Using an institutional framework from new institutional sociology (NIS), old institutional economics (OIE) and power mobilisation are used to help clarify the processes of change in Libyan companies. The hybrid-institutional framework utilised in this study has aided in explaining, interpreting and understanding effects which have occurred within the organisations, which involve rules and routines and/or external-organisation, including terms of coercive, mimetic and normative isomorphism. The position as mentioned above cannot be described in terms of quantitative approaches. So the main reason behind the selection of a qualitative approach for this was that the important aim of the qualitative approach is to provide an in-depth understanding of particular phenomena, such as management accounting change. Also, the case study strategy has been chosen from among qualitative strategies; this was appropriate as the researcher wished to provide a fuller understanding of the topics of the research. Triangulation data collection methods have been drawn on. The case studies were carried out during two stages of data collection in 2008-2009. The researcher relied on multiple sources of evidence, including interviews, observations and documents and archival records. Semi-structured interviews were adopted. In this context, the researcher had a list of themes and questions, as well as responses of interviewees which were recorded. Participant observation was converged as it is related to qualitative approach and case study strategy as well. The results of the case studies showed that the objectives of the companies have changed completely from social to economic. The study found that there were institutional factors which affected management accounting systems and practice before, during and after the privatisation process. Also, the case studies affirmed that the changes were incremental or evolutionary. Furthermore, the findings showed that there is no current revolutionary change within the management accounting systems and practices in the companies under the study. It was also found that there was resistance to change when the company attempted to introduce an Information Technology (IT) system

Reduced row echelon form and non-linear approximation for subspace segmentation and high-dimensional data clustering

Given a set of data W={w1,…,wN}∈RD drawn from a union of subspaces, we focus on determining a nonlinear model of the form U=⋃i∈ISi, where {Si⊂RD}i∈I is a set of subspaces, that is nearest to W. The model is then used to classify W into clusters. Our approach is based on the binary reduced row echelon form of data matrix, combined with an iterative scheme based on a non-linear approximation method. We prove that, in absence of noise, our approach can find the number of subspaces, their dimensions, and an orthonormal basis for each subspace Si. We provide a comprehensive analysis of our theory and determine its limitations and strengths in presence of outliers and noise

Large-scale classification based on support vector machine

Esta tese propón o fast support vector classifier, unha versión eficiente da máquina de vectores de soporte (SVM) con cerne gausiano para problemas de clasificación grandes. Este clasificador acada un acerto cercano aos mellores métodos dispoñíbeis, sendo moito máis rápido que aqueles en conxuntos de ata 31 millóns de datos, 30.000 entradas e 131 clases. Tamén axusta os requerimentos de memoria, permitindo a súa execución en datos de tamano case arbitrariamente grande. Esta tese tamén propón o algoritmo ideal kernel tuning, un método de sintonización eficiente da anchura do cerne gausiano para a SVM, método que é o máis rápido comparado con outras 5 alternativas da literatura, cun acerto moi perto do mellor dispoñíbel actualmente e cun reducido consumo de memoria