Post-WTO China : competition and technology transfer laws in the 'new' socialist market economy

China has been the focus of much academic and business scrutiny of late. Its economic climate is changing and its huge new market opportunities seem quite tantalizing to the would-be 'technology entrepreneur'. But China's market is a relatively immature one; it is still in the process of being opened up to real competition. The corollary of this is that, at this stage of the transitional process, there is still significant State control of market function. This article discusses Chinese competition law, the technology transfer system, how the laws are being reformed and how the technology entrepreneur fares under them. The bottom line is that while opportunities beckon, the wise entrepreneur will nevertheless continue to exercise caution.

More legislative traffic on the 'Doi Moi' superhighway : technology transfer, IP and competition law in Vietnam

Since 1986 Vietnam has been engaged in the transition from a centrally-controlled economy to a socialist-oriented market economy (the 'doi moi' renovation). The process for global economic integration has been slow given the magnitude of necessary reforms. Consequently technology entrepreneurs often discount Vietnam as a possible commercialization base which means that it is not realising its economic potential as a hub of technology transfer in the Asia-Pacific region. Three significant factors in the current uncertainty are Vietnam's laws on competition, intellectual property and technology transfer. Another problem is the lack of literature on these laws. This article first discusses the conceptual relationship between competition, intellectual property and technology transfer. Hopefully the article will provide some guidance for the technology entrepreneur considering foreign direct investment (FDI) in Vietnam. The bottom line is that these laws still need further reform to bolster entrepreneurial confidence.

Licensing technology : negotiating and drafting technology transfer agreements [3rd ed.]

Part I of this book covers the commercial and contractual background to technology licensing agreements. Part II discusses the European Community's new regime on the application and enforcement of Article 81 to technology licensing agreements. EC Council Regulation 1/2003 replaced the Council Regulation 17/1962 and repealed the system under which restrictive agreements and practices could be notified to the EC Commission. A new Commission regulation on technology transfer agreements, Regulation 772/2004. These two enactments required consequential amendments to the chapters in Part III where the usual terms of technology licensing agreements are analysed and exemplified by reference to decided cases.

Fixing the volatile : studio vocal performance techniques

The process of compiling a studio vocal performance from many takes can often result in the performer producing a new complete performance once this new "best of" assemblage is heard back. This paper investigates the ways that the physical process of recording can alter vocal performance techniques, and in particular, the establishing of a definitive melodic and rhythmic structure. Drawing on his many years of experience as a commercially successful producer, including the attainment of a Grammy award, the author will analyse the process of producing a “credible” vocal performance in depth, with specific case studies and examples. The question of authenticity in rock and pop will also be discussed and, in this context, the uniqueness of the producer’s role as critical arbiter – what gives the producer the authority to make such performance evaluations? Techniques for creating conditions in the studio that are conducive to vocal performances, in many ways a very unnatural performance environment, will be discussed, touching on areas such as the psycho-acoustic properties of headphone mixes, the avoidance of intimidatory practices, and a methodology for inducing the perception of a “familiar” acoustic environment.

Resembling Florida : transpacific transfer of ideas from one Gold Coast to another

Despite different political structures and planning systems, striking physical similarities exist between the tourist destinations of the Gold Coasts of Queensland and Florida. Both have been fast developing sub-tropical coastal areas, subject to massive land booms, speculation, and entrepreneurs’ grand visions throughout their history. As a result, both have become tourist destinations of international renown. Drawing on historical sources, the present research seeks to investigate the extent to which these similarities result from taking American cities as a model for newer development in Australia; in this case from transferring planning and marketing ideas from one Gold Coast to another, with the development of the Florida Gold Coast setting precedent for the development of the Queensland Gold Coast.

Deposition of hydroxyapatite and calcium oxalate dihydrate on a heat exchanger tube

Most studies on the characterisation of deposits on heat exchangers have been based on bulk analysis, neglecting the fine structural features and the compositional profiles of layered deposits. Attempts have been made to fully characterise a fouled stainless steel tube obtained from a quintuple Roberts evaporator of a sugar factory using X-ray diffraction and scanning electron microscopy techniques. The deposit contains three layers at the bottom of the tube and two layers on the other sections and is composed of hydroxyapatite, calcium oxalate dihydrate and an amorphous material. The proportions of these phases varied along the tube height. Energy-dispersive spectroscopy and XRD analysis on the surfaces of the outermost and innermost layers showed that hydroxyapatite was the major phase attached to the tube wall, while calcium oxalate dihydrate (with pits and voids) was the major phase on the juice side. Elemental mapping of the cross-sections of the deposit revealed the presence of a mineral, Si-Mg-Al-Fe-O, which is probably a silicate mineral. Reasons for the defects in the oxalate crystal surfaces, the differences in the crystal size distribution from bottom to the top of the tube and the composite fouling process have been postulated.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Novel car carrier design : prevention of falls from heights

This article reports the details of a research on novel design in the field of semitrailer sector and discuss design by hazard prevention techniques. The novel design made addresses occupational health and safety (OHS)concerns of fall from heights. The research includes a detailed survey of national data sources to examine the fatalities caused due to fall from heights in car carriers. The study investigates OHS recommendations in Australia for semitrailer sector. Often injuries are caused due to drivers working above the 1.5 meter height for loading, unloading of the cars, moving the decks up, down, strapping the cars, and slipperly. The new design is developed using latest computer aided design and engineeing (CAD, CAE), product data management (PDM), virtual design process (VDP). The new car carrier design excels in reducing the risks of injuries to drivers and new bench mark for OHS standards. The new design has all the decks operated with hydraulics and uses unique ratchet lock mechanism (fool proof design) and loading happens at a safe working height (below 1.5 meter). All the cars are strapped on the safe working height, and then car desks operated hydraulically to transfer them to the required position. This also includes the car on the prime mover, which shuttles across from one deck to other using hydraulic and rack-pinion mechanisms. The novel design car carrier solves the problem of falls from height: next step would be to transfer this technology across other similar effected sectors.

Reliability analysis of transform-based stereo matching techniques, and a new matching constraint

Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Practical applications for stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics and industrial automation. The initial motivation behind this work was to produce a stereo vision sensor for mining automation applications. For such applications, the input stereo images would consist of close range scenes of rocks. A fundamental problem faced by matching algorithms is the matching or correspondence problem. This problem involves locating corresponding points or features in two images. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This work implemented a number of areabased matching algorithms to assess their suitability for this application. Area-based techniques were investigated because of their potential to yield dense depth maps, their amenability to fast hardware implementation, and their suitability to textured scenes such as rocks. In addition, two non-parametric transforms, the rank and census, were also compared. Both the rank and the census transforms were found to result in improved reliability of matching in the presence of radiometric distortion - significant since radiometric distortion is a problem which commonly arises in practice. In addition, they have low computational complexity, making them amenable to fast hardware implementation. Therefore, it was decided that matching algorithms using these transforms would be the subject of the remainder of the thesis. An analytic expression for the process of matching using the rank transform was derived from first principles. This work resulted in a number of important contributions. Firstly, the derivation process resulted in one constraint which must be satisfied for a correct match. This was termed the rank constraint. The theoretical derivation of this constraint is in contrast to the existing matching constraints which have little theoretical basis. Experimental work with actual and contrived stereo pairs has shown that the new constraint is capable of resolving ambiguous matches, thereby improving match reliability. Secondly, a novel matching algorithm incorporating the rank constraint has been proposed. This algorithm was tested using a number of stereo pairs. In all cases, the modified algorithm consistently resulted in an increased proportion of correct matches. Finally, the rank constraint was used to devise a new method for identifying regions of an image where the rank transform, and hence matching, are more susceptible to noise. The rank constraint was also incorporated into a new hybrid matching algorithm, where it was combined a number of other ideas. These included the use of an image pyramid for match prediction, and a method of edge localisation to improve match accuracy in the vicinity of edges. Experimental results obtained from the new algorithm showed that the algorithm is able to remove a large proportion of invalid matches, and improve match accuracy.

Adaptive instantaneous frequency estimation: Techniques and algorithms

This thesis deals with the problem of the instantaneous frequency (IF) estimation of sinusoidal signals. This topic plays significant role in signal processing and communications. Depending on the type of the signal, two major approaches are considered. For IF estimation of single-tone or digitally-modulated sinusoidal signals (like frequency shift keying signals) the approach of digital phase-locked loops (DPLLs) is considered, and this is Part-I of this thesis. For FM signals the approach of time-frequency analysis is considered, and this is Part-II of the thesis. In part-I we have utilized sinusoidal DPLLs with non-uniform sampling scheme as this type is widely used in communication systems. The digital tanlock loop (DTL) has introduced significant advantages over other existing DPLLs. In the last 10 years many efforts have been made to improve DTL performance. However, this loop and all of its modifications utilizes Hilbert transformer (HT) to produce a signal-independent 90-degree phase-shifted version of the input signal. Hilbert transformer can be realized approximately using a finite impulse response (FIR) digital filter. This realization introduces further complexity in the loop in addition to approximations and frequency limitations on the input signal. We have tried to avoid practical difficulties associated with the conventional tanlock scheme while keeping its advantages. A time-delay is utilized in the tanlock scheme of DTL to produce a signal-dependent phase shift. This gave rise to the time-delay digital tanlock loop (TDTL). Fixed point theorems are used to analyze the behavior of the new loop. As such TDTL combines the two major approaches in DPLLs: the non-linear approach of sinusoidal DPLL based on fixed point analysis, and the linear tanlock approach based on the arctan phase detection. TDTL preserves the main advantages of the DTL despite its reduced structure. An application of TDTL in FSK demodulation is also considered. This idea of replacing HT by a time-delay may be of interest in other signal processing systems. Hence we have analyzed and compared the behaviors of the HT and the time-delay in the presence of additive Gaussian noise. Based on the above analysis, the behavior of the first and second-order TDTLs has been analyzed in additive Gaussian noise. Since DPLLs need time for locking, they are normally not efficient in tracking the continuously changing frequencies of non-stationary signals, i.e. signals with time-varying spectra. Nonstationary signals are of importance in synthetic and real life applications. An example is the frequency-modulated (FM) signals widely used in communication systems. Part-II of this thesis is dedicated for the IF estimation of non-stationary signals. For such signals the classical spectral techniques break down, due to the time-varying nature of their spectra, and more advanced techniques should be utilized. For the purpose of instantaneous frequency estimation of non-stationary signals there are two major approaches: parametric and non-parametric. We chose the non-parametric approach which is based on time-frequency analysis. This approach is computationally less expensive and more effective in dealing with multicomponent signals, which are the main aim of this part of the thesis. A time-frequency distribution (TFD) of a signal is a two-dimensional transformation of the signal to the time-frequency domain. Multicomponent signals can be identified by multiple energy peaks in the time-frequency domain. Many real life and synthetic signals are of multicomponent nature and there is little in the literature concerning IF estimation of such signals. This is why we have concentrated on multicomponent signals in Part-H. An adaptive algorithm for IF estimation using the quadratic time-frequency distributions has been analyzed. A class of time-frequency distributions that are more suitable for this purpose has been proposed. The kernels of this class are time-only or one-dimensional, rather than the time-lag (two-dimensional) kernels. Hence this class has been named as the T -class. If the parameters of these TFDs are properly chosen, they are more efficient than the existing fixed-kernel TFDs in terms of resolution (energy concentration around the IF) and artifacts reduction. The T-distributions has been used in the IF adaptive algorithm and proved to be efficient in tracking rapidly changing frequencies. They also enables direct amplitude estimation for the components of a multicomponent