Built to last versus meant to end : time bounds specification in strategic alliances

This article explores an important temporal aspect of the design of strategic alliances by focusing on the issue of time bounds specification. Time bounds specification refers to a choice on behalf of prospective alliance partners at the time of alliance formation to either pre-specify the duration of an alliance to a specific time window, or to keep the alliance open-ended (Reuer & Ariňo, 2007). For instance, Das (2006) mentions the example of the alliance between Telemundo Network and Mexican Argos Comunicacion (MAC). Announced in October 2000, this alliance entailed a joint production of 1200 hours of comedy, news, drama, reality and novella programs (Das, 2006). Conditioned on the projected date of completing the 1200 hours of programs, Telemundo Network and MAC pre-specified the time bounds of the alliance ex ante. Such time-bound alliances are said to be particularly prevalent in project-based industries, like movie production, construction, telecommunications and pharmaceuticals (Schwab & Miner, 2008). In many other instances, however, firms may choose to keep their alliances open-ended, not specifying a specific time bound at the time of alliance formation. The choice between designing open-ended alliances that are “built to last”, versus time bound alliances that are “meant to end” is important. Seminal works like Axelrod (1984), Heide & Miner (1992), and Parkhe (1993) demonstrated that the choice to place temporal bounds on a collaborative venture has important implications. More specifically, collaborations that have explicit, short term time bounds (i.e. what is termed a shorter “shadow of the future”) are more likely to experience opportunism (Axelrod, 1984), are more likely to focus on the immediate present (Bakker, Boros, Kenis & Oerlemans, 2012), and are less likely to develop trust (Parkhe, 1993) than alliances for which time bounds are kept indeterminate. These factors, in turn, have been shown to have important implications for the performance of alliances (e.g. Kale, Singh & Perlmutter, 2000). Thus, there seems to be a strong incentive for organizations to form open-ended strategic alliances. And yet, Reuer & Ariňo (2007), one of few empirical studies that details the prevalence of time-bound and open-ended strategic alliances, found that about half (47%) of the alliances in their sample were time bound, the other half were open-ended. What conditions, then, determine this choice?

A new analytic approach for power system fault diagnosis employing the temporal information of alarm messages

Traditional analytic models for power system fault diagnosis are usually formulated as an unconstrained 0–1 integer programming problem. The key issue of the models is to seek the fault hypothesis that minimizes the discrepancy between the actual and the expected states of the concerned protective relays and circuit breakers. The temporal information of alarm messages has not been well utilized in these methods, and as a result, the diagnosis results may be not unique and hence indefinite, especially when complicated and multiple faults occur. In order to solve this problem, this paper presents a novel analytic model employing the temporal information of alarm messages along with the concept of related path. The temporal relationship among the actions of protective relays and circuit breakers, and the different protection configurations in a modern power system can be reasonably represented by the developed model, and therefore, the diagnosed results will be more definite under different circumstances of faults. Finally, an actual power system fault was served to verify the proposed method.

Effective discrimination of acoustic emission source signals for structural health monitoring

Acoustic emission (AE) is the phenomenon where stress waves are generated due to rapid release of energy within a material caused by sources such as crack initiation or growth. AE technique involves recording the stress waves by means of sensors and subsequent analysis of the recorded signals to gather information about the nature of the source. Though AE technique is one of the popular non destructive evaluation (NDE) techniques for structural health monitoring of mechanical, aerospace and civil structures; several challenges still exist in successful application of this technique. Presence of spurious noise signals can mask genuine damage‐related AE signals; hence a major challenge identified is finding ways to discriminate signals from different sources. Analysis of parameters of recorded AE signals, comparison of amplitudes of AE wave modes and investigation of uniqueness of recorded AE signals have been mentioned as possible criteria for source differentiation. This paper reviews common approaches currently in use for source discrimination, particularly focusing on structural health monitoring of civil engineering structural components such as beams; and further investigates the applications of some of these methods by analyzing AE data from laboratory tests.

Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications

Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

Environmental and economic evaluation of N fertilizer rates in a maize crop in Italy : a spatial and temporal analysis using crop models

Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

The calculation of acoustic indices to characterise acoustic recordings of the environment

This technical report describes the methods used to obtain a list of acoustic indices that are used to characterise the structure and distribution of acoustic energy in recordings of the natural environment. In particular it describes methods for noise reduction from recordings of the environment and a fast clustering algorithm used to estimate the spectral richness of long recordings.

Emergency department in hospitals, a window of the world : a preliminary comparison between Australia and China

BACKGROUND: This study aimed to make a preliminary comparison of emergency department (ED) presentations between Australia and China. The comparison could provide insights into the health systems and burden of diseases and potentially stimulate discussion about the development of acute health system in China. METHODS: An observational study was performed to compare Australian ED presentations using data obtained from a single adult tertiary-referral teaching hospital in metropolitan Brisbane against Chinese ED presentations using public domain information published in existing Chinese and international medical journals. RESULTS: There are major differences in ED presentations between Australia and China. In 2008, 1) 35.4% of patients arrived at a tertiary teaching hospital ED in Brisbane, Australia by ambulance; 2) 1.7% were treated for poisoning; 3) 1.4% for cerebral vascular disease; 4) 1.7% for cardiac disease; and 5) 42.6% for trauma. The top events diagnosed were mental health problems including general psychiatric examination, psychiatric review, alcohol abuse, and counselling for alcohol abuse, which accounted for 5.5% of all ED presentations. Among ED patients in China, 6.7% arrived at a tertiary teaching hospital by ambulance in Shenyang in 1997; 3.7% were treated for poisoning in Shanxi Zhouzhi County People's Hospital ED in 2006; 14.9% for cerebral vascular diseases at Qinghai People's Hospital ED in 1993-1995; 1.7% for cardiac diseases at the Second People's Hospital ED, Shenzhen Longgang in 1993; and 44.3% for trauma at Shanxi Zhouzhi County People's Hospital ED in 2006. The top events were trauma and poisoning among the young and cerebral infarction in the older population. CONCLUSIONS: Compared with Australian, Chinese ED patients had 1) lower ambulance usage; 2) higher proportion of poisoning; 3) higher proportion of cerebral vascular diseases; 4) similar proportion of cardiac disease; 5) similar proportion of trauma; and 6) little reported mental health problems. Possible explanations for these differences in China include a pay for service pre-hospital care system, lack of public awareness about poisons, inadequate hypertension management, and lack of recognition of mental health problems.

Temporal boundary objects in megaprojects : mapping the system with the integrated master schedule

Recently, a stream of project management research has recognized the critical role of boundary objects in the organization of projects. In this paper, we investigate how one advanced scheduling tool, the Integrated Master Schedule (IMS), is used as a temporal boundary object at various stages of complex projects. The IMS is critical to megaprojects which typically span long periods of time and face a high degree of complexity and uncertainty. In this paper, we conceptualize projects of this type as complex adaptive systems (CAS). We report the findings of four case projects on how the IMS mapped interactions, interdependencies, constraints, and fractal patterns of these emerging projects, and how the process of IMS visualization enabled communication and negotiation of project realities. This paper highlights that this advanced timeline tool acts as a boundary object and elicits shared understanding of complex projects from their stakeholders.

The open window of susceptibility to infection after acute exercise in healthy young male elite athletes

The 'open window' theory is characterised by short term suppression of the immune system following an acute bout of endurance exercise. This window of opportunity may allow for an increase in susceptibility to upper respiratory illness (URI). Many studies have indicated a decrease in immune function in response to exercise. However, many studies do not indicate changes in immune function past 2 hours after the completion of exercise, consequently failing to determine whether these immune cells numbers, or importantly their function, return to resting levels before the start of another bout of exercise. Ten male 'A' grade cyclists (age 24.2 +/- 5.3 years; body mass 73.8 +/- 6.5 kg; VO(2peak) 65.9 +/- 7.1 mL.kg(-1).min(-1)) exercised for two hours at 90% of their second ventilatory threshold. Blood samples were collected pre-, immediately post-, 2 hours, 4 hours, 6 hours, 8 hours, and 24 hours post-exercise. Immune variables examined included total leukocyte counts, neutrophil function (oxidative burst and phagocytic function), lymphocyte subset counts (CD4(+), CD8(+), and CD16(+)/56(+)), natural killer cell activity (NKCA), and NK phenotypes (CD56(dim)CD16(+), and CD56(bright)CD16(-)). There was a significant increase in total lymphocyte numbers from pre-, to immediately post-exercise (p<0.01), followed by a significant decrease at 2 hours post-exercise (p<0.001). CD4(+) T-cell counts significantly increased from pre-exercise, to 4 hours post- (p<0.05), and 6 hours post-exercise (p<0.01). However, NK (CD16(+)/56(+)) cell numbers decreased significantly from pre-exercise to 4 h post-exercise (p<0.05), to 6 h post-exercise (p<0.05), and to 8 h post-exercise (p<0.01). In contrast, CD56(bright)CD16- NK cell counts significantly increased from pre-exercise to immediately post-exercise (p<0.01). Neutrophil oxidative burst activity did not significantly change in response to exercise, while neutrophil cell counts significantly increased from pre-exercise, to immediately post-exercise (p<0.05), and 2 hours post-exercise (p<0.01), and remained significantly above pre-exercise levels to 8 hours post-exercise (p<0.01). Neutrophil phagocytic function significantly decreased from 2 hours post-exercise, to 6 hours post- (p<0.05), and 24 hours post-exercise (p<0.05). Finally, eosinophil cell counts significantly increased from 2 hours post to 6 hours post- (p<0.05), and 8 hours post-exercise (p<0.05). This is the first study to show changes in immunological variables up to 8 hours post-exercise, including significant NK cell suppression, NK cell phenotype changes, a significant increase in total lymphocyte counts, and a significant increase in eosinophil cell counts all at 8 hours post-exercise. Suppression of total lymphocyte counts, NK cell counts and neutrophil phagocytic function following exercise may be important in the increased rate of URI in response to regular intense endurance training.

Reputation modelling in citizen science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, as the gathered information is from the crowd, the data quality is always hard to manage. There are many ways to manage data quality, and reputation management is one of the common approaches. In recent year, many research teams have deployed many audio or image sensors in natural environment in order to monitor the status of animals or plants. The collected data will be analysed by ecologists. However, as the amount of collected data is exceedingly huge and the number of ecologists is very limited, it is impossible for scientists to manually analyse all these data. The functions of existing automated tools to process the data are still very limited and the results are still not very accurate. Therefore, researchers have turned to recruiting general citizens who are interested in helping scientific research to do the pre-processing tasks such as species tagging. Although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Therefore, this research aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we aim to investigate how to use reputation management to enhance data reliability. Reputation systems have been used to solve the uncertainty and improve data quality in many marketing and E-Commerce domains. The commercial organizations which have chosen to embrace the reputation management and implement the technology have gained many benefits. Data quality issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. However, research on reputation management in this area is relatively new. We therefore start our investigation by examining existing reputation systems in different domains. Then we design novel reputation management approaches for Citizen Science projects to categorise participants and data. We have investigated some critical elements which may influence data reliability in Citizen Science projects. These elements include personal information such as location and education and performance information such as the ability to recognise certain bird calls. The designed reputation framework is evaluated by a series of experiments involving many participants for collecting and interpreting data, in particular, environmental acoustic data. Our research in exploring the advantages of reputation management in Citizen Science (or crowdsourcing in general) will help increase awareness among organizations that are unacquainted with its potential benefits.

Spatial and temporal distribution of falciparum malaria in China

Background: Falciparum malaria is the most deadly among the four main types of human malaria. Although great success has been achieved since the launch of the National Malaria Control Programme in 1955, malaria remains a serious public health problem in China. This paper aimed to analyse the geographic distribution, demographic patterns and time trends of falciparum malaria in China. Methods: The annual numbers of falciparum malaria cases during 1992–2003 and the individual case reports of each clinical falciparum malaria during 2004–2005 were extracted from communicable disease information systems in China Center for Diseases Control and Prevention. The annual number of cases and the annual incidence were mapped by matching them to corresponding province- and county-level administrative units in a geographic information system. The distribution of falciparum malaria by age, gender and origin of infection was analysed. Time-series analysis was conducted to investigate the relationship between the falciparum malaria in the endemic provinces and the imported falciparum malaria in non-endemic provinces. Results: Falciparum malaria was endemic in two provinces of China during 2004–05. Imported malaria was reported in 26 non-endemic provinces. Annual incidence of falciparum malaria was mapped at county level in the two endemic provinces of China: Yunnan and Hainan. The sex ratio (male vs. female) for the number of cases in Yunnan was 1.6 in the children of 0–15 years and it reached 5.7 in the adults over 15 years of age. The number of malaria cases in Yunnan was positively correlated with the imported malaria of concurrent months in the non-endemic provinces. Conclusion: The endemic area of falciparum malaria in China has remained restricted to two provinces, Yunnan and Hainan. Stable transmission occurs in the bordering region of Yunnan and the hilly-forested south of Hainan. The age and gender distribution in the endemic area is characterized by the predominance of adult men cases. Imported falciparum malaria in the non-endemic area of China, affected mainly by the malaria transmission in Yunnan, has increased both spatially and temporally. Specific intervention measures targeted at the mobile population groups are warranted.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Characterization of sky-region morphological-temporal airborne collision detection

Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.