Competence foresight: linking the identification of HR competences and competence management alignment with business strategy

The objective of this study was to increase understanding of the link between the identification of required HR competences and competence management alignment with business strategy in a Finnish, global company employing over 8,000 people and about 100 HR professionals. This aim was approached by analyzing the data collected in focus group interviews using a grounded theory method and in parallel reviewing the literature of strategic human resource management, competence-based strategic management, strategy and foresight. The literature on competence management in different contexts dismisses in-depth discussions on the foresight process and individuals are often forgotten in strategic frameworks. However, corporate foresight helps in the detection of emerging opportunities for innovations and in the implementation of strategy. The empirical findings indicate a lack of strategic leadership and an alignment with HR and business. Accordingly, the most important HR competence areas identified were the need for increasing business understanding and enabling change. As a result, the study provided a holistic model for competence foresight, which introduces HR professionals as strategic change agents in the role of organizational futurists at the heart of the company: facilitating competence foresight and competence development on individual as well as organizational levels, resulting in an agile organization with increased business understanding, sensitive sensors and adaptive actions to enable change.

A forced running wheel system with a microcontroller that provides high-intensity exercise training in an animal ischemic stroke model

We developed a forced non-electric-shock running wheel (FNESRW) system that provides rats with high-intensity exercise training using automatic exercise training patterns that are controlled by a microcontroller. The proposed system successfully makes a breakthrough in the traditional motorized running wheel to allow rats to perform high-intensity training and to enable comparisons with the treadmill at the same exercise intensity without any electric shock. A polyvinyl chloride runway with a rough rubber surface was coated on the periphery of the wheel so as to permit automatic acceleration training, and which allowed the rats to run consistently at high speeds (30 m/min for 1 h). An animal ischemic stroke model was used to validate the proposed system. FNESRW, treadmill, control, and sham groups were studied. The FNESRW and treadmill groups underwent 3 weeks of endurance running training. After 3 weeks, the experiments of middle cerebral artery occlusion, the modified neurological severity score (mNSS), an inclined plane test, and triphenyltetrazolium chloride were performed to evaluate the effectiveness of the proposed platform. The proposed platform showed that enhancement of motor function, mNSS, and infarct volumes was significantly stronger in the FNESRW group than the control group (P<0.05) and similar to the treadmill group. The experimental data demonstrated that the proposed platform can be applied to test the benefit of exercise-preconditioning-induced neuroprotection using the animal stroke model. Additional advantages of the FNESRW system include stand-alone capability, independence of subjective human adjustment, and ease of use.

Investigating the Existence of Business-IT Alignment Trap in Finnish IT Organizations

The overall purpose of this master's thesis is to investigate the existence of business-IT alignment trap in Finnish IT organizations. The alignment trap refers to the inability of IT investments to deliver the expected business benefits. The basis for this investigation is due to the previous knowledge that high level of IT alignment practice with very low efficacy in an organization can lead to alignment trap. The theory which was established on the dimensions of IT-alignment and efficacy of IT as a whole with considerations for cost reduction and revenue growth benefits. This study explored the same dimensions with the previous study but identified additional benefit (profitability). The study was conducted using the Finnish IT barometer data from different IT organizations. A quantitative research method was used in conducting this study which was built on positivist philosophical stance. The empirical data is based on survey data, an excerpt from the Finnish IT barometer data that captured the annual survey results of IT significance to Finnish organizations as evaluated by business and IT professionals. The survey data comprised of 249 respondents and their responses were categorized into high and low IT intensive which form the basis of the statistical analysis conducted. Overall, five analyses were conducted using the variables of cost reductions, revenue growth and profitability in the 2x2 matrix dimensions of IT alignment and efficacy of IT, grouped into alignment trap, maintenance zone, well-oiled IT and IT-enabled growth. The empirical results, revealed a partial existence of alignment trap in Finnish IT organizations. This is due to a very minute number of organizations that were ensnared in the alignment trap zone on the analyses conducted. Although they recorded considerable high performances in terms of revenue growth rate with IT spending below the average companies, their profitability was considered very low. Generally it was observed that Finnish IT organizations with high efficacy of IT practices had good performances, while those with low efficacy of IT experienced low performances, especially in the aspect of profitability, regardless of the degree of IT alignment. The study proposes that organizations should improve on practices that enhance effectiveness of IT more in order for them to realize the full benefits of IT and to avoid alignment trap.

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

"Attitude is a little thing that makes a big difference" : further exploration of attitude alignment in the context of close relationship dyads /

One hundred and five primarily Caucasian undergraduate couples were tested to study the phenomenon of attitude alignment, or the way in which individuals change their opinions to achieve greater attitudinal congruence with their romantic partners, and the hypotheses that relationship closeness, affect, attachment, social desirability, and centrality are each related to attitude alignment for individuals in close couples. The couples filled out an attitude questionnaire consisting of 50 issues in which they were asked to give their attitude on a scale from 1 to 9 as well as to rate the centrality, or importance, of that issue on a scale from 1 to 9. Before discussing four of these issues with each other - 2 were more central to the man and less central, or peripheral, to the woman, whereas the other 2 were central to the woman and peripheral to the man - the individuals completed established measures of relationship closeness, affect, attachment, and social desirability. The couples then filled out the identical attitudes questionnaire again, and their answers on the four discussion issues were compared to their prediscussion answers to determine whether attitude alignment had occurred. There were two experimental groups: a social desirability group, where the couples were told it was natural and normal to disagree with their partners, and a control group. Results indicated that attitude alignment did significantly occur across all couples, but most other variables - including centrality, relationship closeness, and affect - did not predict attitude alignment behaviour. As well, the social desirability experimental groups did not significantly differ on attitude alignment behaviours, but higher scores on the social desirability scale, specifically self-deception, significantly predicted higher attitude alignment scores across all couples. Large differences between individuals' frequency.

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.

The regulation of adult hippocampal neurogenesis by wheel running and environmental enrichment

Introduction: Chez les mammifères, la naissance de nouveaux neurones se poursuit à l’âge adulte dans deux régions du cerveau: 1) l’hippocampe et 2) la zone sous-ventriculaire du prosencéphale. La neurogenèse adulte n’est pas un processus stable et peut être affectée par divers facteurs tels que l’âge et la maladie. De plus, les modifications de la neurogenèse peuvent être à l’origine des maladies de sorte que la régulation ainsi que le rétablissement de la neurogenèse adulte doivent être considérés comme d’importants objectifs thérapeutiques. Chez la souris saine ou malade, la neurogenèse hippocampale peut être fortement régulée par l’enrichissement environnemental ainsi que par l’activité physique. Cependant, lors même que l’activité physique et l’enrichissement environnemental pourraient contribuer au traitement de certaines maladies, très peu d’études porte sur les mécanismes moléculaires et physiologiques responsables des changements qui sont en lien avec ces stimuli. Objectifs et hypothèses: Les principaux objectifs de cette étude sont de caractériser les effets de stimuli externes sur la neurogenèse et, par le fait même, d’élucider les mécanismes sous-jacents aux changements observés. En utilisant le modèle d’activité physique volontaire sur roue, cette étude teste les deux hypothèses suivantes: tout d’abord 1) qu’une période prolongée d’activité physique peut influencer la neurogenèse adulte dans le prosencéphale et l’hippocampe, et 2) que l’activité volontaire sur roue peut favoriser la neurogenèse à travers des stimuli dépendants ou indépendants de la course. Méthodes: Afin de valider la première hypothèse, nous avons utilisé un paradigme incluant une activité physique volontaire prolongée sur une durée de six semaines, ainsi que des analyses immunohistochimiques permettant de caractériser l’activité de précurseurs neuronaux dans la zone sous-ventriculaire et l’hippocampe. Ensuite, pour valider la seconde hypothèse, nous avons utlisé une version modifiée du paradigme ci-dessous, en plaçant les animaux (souris) soit dans des cages traditionnelles, soit dans des cages munies d’une roue bloquée soit dans des cages munies d’une roue fonctionnelle. Résultats: En accord avec la première hypothèse, l’activité physique prolongée volontaire a augmenté la prolifération des précurseurs neuronaux ainsi que la neurogenèse dans le gyrus dentelé de l’hippocampe comparativement aux animaux témoins, confirmant les résultats d’études antérieures. Par ailleurs, dans ce paradigme, nous avons aussi observé de la prolifération acrue au sein de la zone sous-ventriculaire du prosencéphale. De plus, en accord avec la seconde hypothèse, les souris placées dans une cage à roue bloquée ont montré une augmentation de la prolifération des précurseurs neuronaux dans l’hippocampe comparable à celle observée chez les souris ayant accès à une roue fonctionnelle (coureurs). Cependant, seuls les animaux coureurs ont présenté une augmentation de la neurogenèse hippocampale. Conclusions: Ces résultats nous ont permis de tirer deux conclusions nouvelles concernant les effets de l’activité physique (course) sur la neurogenèse. Premièrement, en plus de la prolifération et de la neurogenèse dans le gyrus dentelé de l’hippocampe, la prolifération dans la zone sous-ventriculaire du prosencéphale peut être augmentée par l’activité physique sur roue. Deuxièmement, l’environnement dans lequel l’activité physique a lieu contient différents stimuli qui peuvent influencer certains aspects de la neurogenèse hippocampale en l’absence d’activité physique sur roue (course).

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.

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported