Improving Short DNA Sequence Alignment with Parallel Computing

Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.

A Needs Assessment: Language Instruction Stakeholders Engaging in Project Based Learning Outside the Classroom for Effective Strategic Problem Solving

Abstract A noted benefit of Project Based Learning (PBL) as a teaching strategy is how it engages the student and enhances learning outcomes as a result of working through challenges intended to depict dilemmas outside the classroom. PBL has seldom been applied outside the parameters of the classroom curriculum. The current needs assessment carried out in this research project examined current practices of language instruction and International Administrative Professionals of both the private and public Language Industry. Participants responded to survey questions on their current administrative practices, strategies, and program characteristics. The study investigated the usefulness of a handbook on the procedure of assisting administrative service teams in language instruction settings to an engaged approach to PBL for student service issues. The diverse opinions, beliefs, and ideas, along with institutional policy, can provide beneficial framework ideas for future tools.

How health organizations can apply scenario based planning and analytic technologies to make strategic consequential decisions in a time of uncertainty

The magnitude of the cervical cancer problem, coupled with the potential for prevention with recent technological advances, made it imperative to step back and reassess strategic options for dealing with cervical cancer screening in Kenya. The purpose of this qualitative study was: 1) to explore the extent to which the Participatory Action Research (PAR) methodology and the Scenario Based Planning (SBP) method, with the application of analytics, could enable strategic, consequential, informed decision making, and 2) to determine how influential Kenyan decision makers could apply SBP with analytic tools and techniques to make strategic, consequential decisions regarding the implementation of a Cervical Self Sampling Program (CSSP) in both urban and rural settings. The theoretical paradigm for this study was action research; it was experiential, practical, and action oriented, and resulted in co-created knowledge that influenced study participants’ decision making. Action Africa Help International (AAHI) and Brock University collaborated with Local Decision Influencing Participants (LDIP’s) to develop innovative strategies on how to implement the CSSP. SBP tools, along with traditional approaches to data collection and analysis, were applied to collect, visualize and analyze predominately qualitative data. Outputs from the study included: a) a generic implementation scenario for a CSSP (along with scenarios unique to urban and rural settings), and b) 10 strategic directions and 22 supporting implementation strategies that address the variables of: 1) technical viability, 2) political support, 3) affordability, 4) logistical feasibility, 5) social acceptability, and 6) transformation/sustainability. In addition, study participants’ capacity to effectively engage in predictive/prescriptive strategic decision making was strengthened.

Transfert de connaissances dans les entreprises multinationales : efficacité et influence des facteurs contextuels

Dans la présente recherche, nous nous sommes penchés sur le processus du transfert intra-organisationnel de connaissances au sein d’entreprises multinationales (EM). Partant du triple constat suivant : les connaissances organisationnelles constituent un avantage stratégique (Barney, 1991 ; Bartlett et Ghoshal, 1998), les transferts intra-organisationnels constituent la raison d’être des EM (Gupta et Govindarajan, 2000), lesquelles ont accès à un vaste bassin de connaissances disséminées à travers le monde par le biais de leurs filiales et les mécanismes organisationnels internes sont plus efficaces que ceux du marché (Williamson, 1987 ; Casson, 1976) pour transférer des connaissances entre unités organisationnelles; nous nous sommes intéressés aux facteurs pouvant affecter l’efficacité de ce processus de transfert. Ayant identifié, lors de notre revue des écrits théoriques, une multitude d’approches permettant d’appréhender ce phénomène, nous proposons, dans notre recherche, un modèle théorique intégrant les trois étapes propres au processus de transfert, soit : la détermination des connaissances à transférer, la sélection des mécanismes de transfert appropriés et, finalement, l’évaluation, d’une part, de l’efficacité des transferts et, d’autre part, de l’ensemble des facteurs contextuels ayant un impact sur l’efficacité de ce processus. Sur le plan théorique, cette recherche oppose deux courants dominant ce champ disciplinaire. L’approche stratégique, exprimée par la théorie des ressources, met l’accent sur l’importance prépondérante des facteurs organisationnels internes sur l’efficacité de toute action organisationnelle (Bartlett et Ghoshal, 1998 ; Barney, 1991). Cette approche s’oppose au courant institutionnel, lequel considère plutôt que les choix et les actions organisationnels sont surtout conditionnés par les contraintes de l’environnement externe (Ferner, 1997; Kostova, 1999; Scott, 1991). Les résultats de notre recherche démontrent que, malgré l’existence de contraintes de nature institutionnelle et culturelle, l’efficacité du processus de transfert des connaissances associées à la gestion des ressources humaines relève davantage des conditions organisationnelles internes et, plus particulièrement, de l’implication de la haute direction, du rôle accordé à la fonction RH et de l’alignement entre la stratégie corporative, la stratégie RH et la culture organisationnelle. Sur le plan méthodologique, il s’agit d’une recherche exploratoire qualitative menée auprès de trois EM (2 canadiennes et 1 française) oeuvrant dans les secteurs de la métallurgie et des télécommunications. Les données empiriques proviennent de 17 entrevues approfondies que nous ont accordées, au Canada, en France, en Allemagne et en Suisse des cadres responsables de la gestion des ressources humaines, affectés au siège social des EM en question ou œuvrant au sein de leurs filiales, et de sources documentaires secondaires.

Alignment Model and Training Technique in SMT from English to Malayalam

This paper investigates certain methods of training adopted in the Statistical Machine Translator (SMT) from English to Malayalam. In English Malayalam SMT, the word to word translation is determined by training the parallel corpus. Our primary goal is to improve the alignment model by reducing the number of possible alignments of all sentence pairs present in the bilingual corpus. Incorporating morphological information into the parallel corpus with the help of the parts of speech tagger has brought around better training results with improved accuracy

Extension schemes for the Alignment Model of English-Malayalam Statistical Machine Translator

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam sentence using statistical models. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set among the sentence pairs of the source and target language before subjecting them for training. This paper deals with certain techniques which can be adopted for improving the alignment model of SMT. Methods to incorporate the parts of speech information into the bilingual corpus has resulted in eliminating many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Presence of Malayalam words with predictable translations has also contributed in reducing the insignificant alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics.

Alignment by Maximization of Mutual Information

A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach registering magnetic resonance (MR) images with computed tomography (CT) images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image called EMMA. As applied here the technique is intensity-based, rather than feature-based. It works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. Finally, we will describe a number of additional real-world applications that can be solved efficiently and reliably using EMMA. EMMA can be used in machine learning to find maximally informative projections of high-dimensional data. EMMA can also be used to detect and correct corruption in magnetic resonance images (MRI).

Segmentation and Alignment of Speech and Sketching in a Design Environment

Sketches are commonly used in the early stages of design. Our previous system allows users to sketch mechanical systems that the computer interprets. However, some parts of the mechanical system might be too hard or too complicated to express in the sketch. Adding speech recognition to create a multimodal system would move us toward our goal of creating a more natural user interface. This thesis examines the relationship between the verbal and sketch input, particularly how to segment and align the two inputs. Toward this end, subjects were recorded while they sketched and talked. These recordings were transcribed, and a set of rules to perform segmentation and alignment was created. These rules represent the knowledge that the computer needs to perform segmentation and alignment. The rules successfully interpreted the 24 data sets that they were given.