Intellectual Property Protection : an External Factor that Influences a Foreign Company’s Market Entry Mode into a Prospective Market

Intellectual Property Protection is been understood in this paper as IP laws and enforcement of these laws in order to protect intellectual property rights. The goal of this research work is to understand how Swedish companies view issues regarding to Intellectual Property Protection (IPP) and how it influences a foreign company?s market entry mode. In order to achieve this objective, the Nigerian market situation and its? laws that govern IPP will be used to analyzed this issue. This paper argues that IPP is an important factor that influences a company?s entry mode and this argument finds IP laws and enforcement as two variables that influence the market while the market situation influences the foreign company. In carrying out this research literature was reviewed and interviews carried out. The research methodology section has presented a qualitative research and explains the nature of the interview stages that have been used to achieve the goals concerning the findings of the empirical data. A qualitative method was adopted by carrying out in-depth semi-structured interviews. The empirical data collected from the investigation were gathered and analyzed based on the research questions. The findings show that IPP of a host market influences a potential foreign company through the market situation that is also influenced by IP laws and enforcement. The outcome of these findings argues that the Swedish companies that were interviewed in this research will enter the Nigerian market through an intermediary mode. This has been based on the current IPP system of Nigerian.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.

Predicting entry of Swedish wholesale firms into local markets

Applying microeconomic theory, we develop a forecasting model for firm entry into local markets and test this model using data from the Swedish wholesale industry. The empirical analysis is based on directly estimating the profit function of wholesale firms. As in previous entry studies, profits are assumed to depend on firm- and location-specific factors,and the profit equation is estimated using panel data econometric techniques. Using the residuals from the profit equation estimations, we identify local markets in Sweden where firm profits are abnormally high given the level of all independent variables included in the profit function. From microeconomic theory, we then know that these local markets should have higher net entry than other markets, all else being equal, and we investigate this in a second step,also using a panel data econometric model. The results of estimating the net-entry equation indicate that four of five estimated models have more net entry in high-return municipalities, but the estimated parameter is only statistically significant at conventional levels in one of our estimated models.

Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease

A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Connecting Scientific Data to Scientific Experiments with Provenance

As scientific workflows and the data they operate on, grow in size and complexity, the task of defining how those workflows should execute (which resources to use, where the resources must be in readiness for processing etc.) becomes proportionally more difficult. While "workflow compilers", such as Pegasus, reduce this burden, a further problem arises: since specifying details of execution is now automatic, a workflow's results are harder to interpret, as they are partly due to specifics of execution. By automating steps between the experiment design and its results, we lose the connection between them, hindering interpretation of results. To reconnect the scientific data with the original experiment, we argue that scientists should have access to the full provenance of their data, including not only parameters, inputs and intermediary data, but also the abstract experiment, refined into a concrete execution by the "workflow compiler". In this paper, we describe preliminary work on adapting Pegasus to capture the process of workflow refinement in the PASOA provenance system.

Entry strategies on an emerging market: Brazil: case studies of French cosmetics companies in Brazil

Este trabalho envolve as estrategias de entrada sobre um mercado emergente, o mercado brasileiro. Os estudos de casos que apoiam o assunto são de empresas francesas do setor de cosméticos. Uma revisão da literatura sobre o assunto sera comparada com os resultados dos estudos de caso. Isso para conduzir numa observação do estado atual das caractéristicos de instalação no mercado brasileiro deste setor para empresas estrangeiras de tamanho médio. O estudo da literatura que já existe sobre o assunto se concentra sobre varias problemáticas conectadas com a problemática geral: as razões para internacionalizar, o modo de entrada, os obstáculos encontrados, as estrategias especificais e as adaptações do marketing mix. Depois este trabalho se concentra sobre tres empresas francesas representativas das problematicas atuais do setor : Norlessi, LaboBio e Plains Cosmetics. Os estudos de caso são sustentados por entrevistas e coleção de dados de varios origens, descrevedo mas precisamente na parte de methodologia. Depois será feito uma cross-analysis tentando comparar as conclusões do estudo empirico e do estudo literário. As conclusões finais tem como objetivo de ser uma observação objetiva do raciocinio das empresas consideradas sobre as problemáticas escolhidas.

Entry strategies into biosimilars: assessment of entry modes into the field of biosimilars from the perspective of pharmaceuticals, generics and biologics companies

Indústria farmacêutica de hoje está em transição. Como grandes blockbuster drogas estão perdendo ou estão prestes a perder a proteção de patente, e as grandes empresas farmacêuticas não estão substituindo os produtos com novas drogas químicas inovadoras, a indústria busca novas áreas de crescimento. Uma dessas áreas é o mercado de biossimilares, que está sendo inseridos por produtos farmacêuticos, genéricos e empresas de produtos biológicos. Mesmo que o grande potencial de mercado será acordado por volta de 2020, quando importantes blockbusters biológicos perder a proteção de patente, as empresas precisam decidir logo se querem participar ou não devido a elevadas barreiras à entrada técnicos, bem como de desenvolvimento de longo prazos. Como todas as empresas vêm de diferentes origens, compreendem capacidades diferentes e têm diferentes incentivos de entrada, a questão que surge é se esses fatos estão relacionados com as suas estratégias de entrada correspondentes. A tese utiliza estudos de caso de cada segmento da indústria farmacêutica - produtos farmacêuticos, biológicos e genéricos - e examina através de entrevistas semi-estruturadas, por isso que os participantes do estudo de caso entrevistados explicitamente escolhido sua estratégia de entrada. Os dados de entrevistas será então ligada a quadros estratégicos da revisão da literatura e irá ser utilizado para uma comparação global e análise. O estudo revelou que o fundo do participante do mercado que influenciam a sua estratégia de entrada. Os principais pontos de influência derivam tanto as barreiras à entrada, bem como os incentivos de entrada. A tese não é possível determinar o sucesso futuro do modo de entrada analisados no novo mercado.

Entry and externality : hydroelectric generators in Brazil

This work analyzes the entry problem in the hydroelectric generation industry. The operation of a generator upstream regularizes the river flow for generators located downstream on the same river, increasing the production capacity of the latter. This positive externality increases the attractiveness of the locations downstream whenever a generator decides to enter upstream. Therefore, the entry decision of a generator in a given location may affect all entry decisions in potential locations for plants downstream. I first model the problem of generators located in cascade on the same river to show the positive effect of the externality. Next, I develop a method to estimate an entry model specific to the hydro generation industry which takes into account the externality of the entry decisions. Finally, I use a data set on investment decisions of Brazilian hydro-generators to estimate the model. The results show a positive incentive to locate downstream from existing plants and from locations where entry is likely to occur. An interesting by-product of the analysis is that the year effects’ estimates show an increase one year before the energy crisis of 2001, providing evidence that the market anticipated the crisis. It contradicts the governmental version that the crisis was due to an unexpected drought.

Entry mode choice and market selection of born globals in developing countries: a multiple-case study of the ecuadorian software sector

O fenômeno "Born global" refere-se a empresas que consideram o mercado global como seu contexto natural e que iniciam seu processo de internacionalização muito cedo após sua criação. As teorias tradicionais como o modelo de Uppsala não conseguem explicar este processo. Portanto, outras teorias têm surgido, como a perspectiva de redes. Existem alguns estudos relacionados a esta área, principalmente realizados em países desenvolvidos com pequenos mercados e economias abertas. No entanto, poucos estudos têm sido feitos em economias em desenvolvimento. Além disso, o número de pesquisas quanto à escolha do modo de entrada e seleção de mercados das empresas “born global” é bastante limitado. Consequentemente, este estudo pretende descrever os principais fatores que influenciam a escolha do modo de entrada e seleção de mercados das empresas, de economias em desenvolvimento, nascidas globais. O foco da pesquisa é a indústria de software e um estudo de casos múltiplo foi realizado com três empresas no Equador. A metodologia incluiu entrevistas com fundadores, bem como a coleta de dados secundários. Com base na evidência empírica, verificou-se que os principais fatores que influenciam a escolha do modo de entrada são as restrições financeiras, as receitas esperadas, a velocidade de internacionalização, mercados nicho e a experiência empresarial anterior dos fundadores. Por outro lado, a seleção de mercado é influenciada por semelhanças de língua e cultura, mercados nicho e relações em rede.

The analysis of foreign market entry strategies on the basis of different cultural backgrounds and environments: a qualitative study characterising the differences and similarities of Brazilian and European firms

Moving into a new and foreign market can be challenging, especially when such market has a different culture and working environment in comparison to the home market. Thus, it is of utter importance to adjust a company’s strategy to the new market conditions. Currently, there are no concrete guidelines of what aspects are most important when moving from a developing market such as Brazil into a more sophisticated market like Europe, or vice versa. The present study will examine two companies from the same industry, but with different cultural backgrounds and its strategic similarities and differences for operating in multiple international markets. The data was collected via semi-structured interviews with the Chief Executive Officers (CEOs’) from both companies, using an interview guideline that is based on three different theoretical frameworks. The aim is to give recommendations to these two industries of how to efficiently use existing theoretical frameworks and which aspects are most significant when moving into a new market while keeping in mind a company’s size and background.

Organizational modeling with a semantic wiki: formalization of content and automatic diagram generation

A key to maintain Enterprises competitiveness is the ability to describe, standardize, and adapt the way it reacts to certain types of business events, and how it interacts with suppliers, partners, competitors, and customers. In this context the field of organization modeling has emerged with the aim to create models that help to create a state of self-awareness in the organization. This project's context is the use of Semantic Web in the Organizational modeling area. The Semantic Web technology advantages can be used to improve the way of modeling organizations. This was accomplished using a Semantic wiki to model organizations. Our research and implementation had two main purposes: formalization of textual content in semantic wiki pages; and automatic generation of diagrams from organization data stored in the semantic wiki pages.

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.