Multi‐mode standardization under extreme time‐pressure – the case of COVID‐19 contact‐tracing apps - Windows 10 1703 download iso italy covid test - windows 10 1703 download iso italy covid test

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They can either develop these standards themselves or mandate the use of an existing standard Wiegmann et al. France, for example, pushed for a domestic, centralized solution.

Specifically, certain Bluetooth functions are limited when the app is not active or the device is in standby mode. Hence, for full operability, on iPhones the app has to be running in the foreground, limiting the use of the device for other tasks. This issue constrained the functionality of the apps, and because of negative user experiences, threatened the widespread adoption of such apps. This request was denied, leading to perpetual inoperability of the standard released by the French government Reuters, b.

A similar case unfolded in the United Kingdom UK , where the government had decided to develop a national centralized solution. This was followed by the release of more detailed interoperability guidelines eHealth Network, a , b. Beyond the national level, governments usually do not possess the hierarchical means to directly influence the standardization process.

Nevertheless, their backing and support can send strong signals to the market Wiegmann et al. European governments engaged in various standardization efforts with market players. What these examples have in common is that governments picked a single solution from the many under development in their respective country, thus aiming to avoid the usual period of competition for dominance among market actors.

While governments used their hierarchical means to influence the standardization process on the national level by involving themselves in the competition between market actors, two important shortcomings remained. First, national governments and market actors were unable to compel Apple to allow the required Bluetooth functionality on iOS devices, thus rendering any coordinated standard epidemiologically useless. Second, the coordinated standards were proprietary and not interoperable.

As the Novid20 CTO remarked during the interview, market actors saw the committee as means to coordination and exchange, and to gain information on approaches being deliberated and developed. Nevertheless, at the same time they continued pursuing the diffusion and adoption of their own standards. In some cases, a standard is the product of interplay between government and a committee. Initially, governments supported whichever of these two committees included actors from their respective country.

Thus, in the present case, governments were involved as powerful actors in both committees either through national research organizations, or as ardent promoters of a standard developed by committees in their respective countries.

In April , the centralized approach became the focus of serious criticism due to privacy and data protection concerns.

France hasn't yet conceded that, but that is the reality. You could not build a contact tracing app on iOS without Apple's involvement, because of the security and privacy features of the system.

We approached Apple and Google through our contacts, and send them a message — which was really a redundant message — that the two of them would have to work together so that there would be a solution that worked for all phones. We pushed our solution, which was at that point developed and published. And it turns out that because of Apple's fairly strong position in favor of privacy, this was the more favored solution to them than the centralized protocol.

And we worked with them and pushed them to implement a few other things. This led to the creation of a multitude of similar, yet mutually incompatible solutions. While the setting of standards through this mode benefits from legitimacy and network effects through the involvement of multiple stakeholders Koppell, , efforts can take years to result in a standard.

Eventually, and analogous to the market mode, committees did not have the opportunity to coordinate a standard. The sudden entrance of Apple and Google to the standardization process simply outpaced committee efforts to coordinate a standard.

This is noteworthy, as these two committees were seen by many to possess more legitimacy due to their wide representation and were expected to raise fewer concerns regarding data protection and privacy than commercial actors.

Governments can impose newly developed or existing standards by virtue of their hierarchical position Wiegmann et al. In the present case, countries such as the UK and France developed their own proprietary solutions, while other governments, sometimes in addition to their own developments, backed the emerging committees.

Ultimately, the involvement of governments was not substantial in the setting of a common standard, as they were constrained by technical limitations and outpaced by Apple and Google entering the process.

Specifically, the EU and national authorities then focused on linking individual apps to national health infrastructure and across member states. Prior literature on standard setting shows that often standards are not set through a single mode, but through the interaction of multiple actors and mechanisms e.

The present case also highlights such avenues of collaboration and interplay between different modes. In the initial phase, it was especially the interaction between governments and the market, as individual governments either pushed for their own solutions or backed, mostly local, market players. This is clearly in line with how governments are setting standards hierarchically. What grants Apple and Google this power is their absolute control over the platform.

This highlights that platform owners should be seen as a distinct standardization actor. This setting adds to the literature on standardization, which typically has focused on cases with longer timeframes e. Platform owners fall outside of the previously discussed actors and modes of standardization, and represent a completely new category, that given their increasing prevalence, will rise in importance.

This technology should include mobile and wearable devices of citizens to leveraging ubiquitous and pervasive computing resources. This policy should clarify the following questions: Who sets the standards? Which parties are invited to provide technological solutions? Whom does the government endorse and by which process? This is relevant for single market entities, such as the EU, and other regional blocs, such as the Association of Southeast Asian Nations or the African Union.

Regarding the increasing importance of mobile operating platforms in disaster and crisis response Manso and Manso, ; Tan et al. Our research is focused on time pressure during a crisis acting on the involved entities and the coordination of a standard. Within the stream of standardization literature, our case is atypical as it unfolded in the course of only months, rather than years.

We expect future research to investigate other cases in which the timeframe differs from established literature to provide additional insights into standard setting in crises and other situations characterized by a high level of time pressure. Beyond that, time and temporal aspects provide a number of perspectives for future research. For instance, the startups and committees in our case study could be investigated from the perspective of temporary organizing see Bakker et al.

Given the nature of the crisis and response, some of the insights may not be generalized. To generalize the results, we expect future research to investigate the role of platform owners in the standardization process in various settings and from various perspectives, such as the avenues of influence for the platform users and how this role could affect innovation Eaton, No conflicting interests were reported by the authors.

The authors thank the editors and two anonymous reviewers for their insightful and valuable suggestions. He obtained his Ph. His research focuses on open innovation and entrepreneurship. Jan Fell is a concurrently a Ph. Klaus Marhold, Email: ta. Jan Fell, Email: wt. Published online Oct C Find articles by Jan Fell. Author information Article notes Copyright and License information Disclaimer.

Corresponding author. Introduction There is a strong interest in the literature about technological standards and the process through which they are created and implemented Narayanan and Chen, Theoretical background 2. Standards and standard setting Standards are rules facilitating compatibility between technological products Katz and Shapiro, ; Gandal, , 1 and thereby complement dominant designs Gallagher, , which alone do not imply mutual compatibility Afuah, Standards are developed in committees and only diffused if members agree on a common solution Solutions intended as a standard can be developed by anyone.

Open in a separate window. Method 3. Data collection and analysis Our case study on the standardization of contact tracing apps in Europe is based on a variety of primary and secondary research data and has been conducted in three broad phases Table 2. Table 2 Phases of research and employed research data. Phase Focus Data and examples Phase 1: Initial observations Overall picture and timeline of the initial development process of contact tracing solutions from the perspective of one of the many startup actors involved in this effort.

Analysis of the resultant standard and how it arose with the involvement of a new type of actor i. Table 3 Overview of formal interviews. Table 4 Data analysis approach. Findings 4. However, realizing the harmful effects of competing to become the national standard, Novid20 decided not to release its app: Under normal circumstances, we should have released our app and let the market decide.

Novid20 CTO. Conclusion 6. Limitations and directions for further research Our research is focused on time pressure during a crisis acting on the involved entities and the coordination of a standard. Acknowledgements The authors thank the editors and two anonymous reviewers for their insightful and valuable suggestions. Appendix A. In the beginning, were there any established standards or other solutions that you could build up on?

How is Novid20 affected by standards and consortia? Can you describe positive or negative influences? Please let me know. Watering weed plants. In this regard, sending seeds to Australia is illegal; however, residents often carry it out.

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Federal Trade Commission should investigate how data brokers including Equifax Inc and Experian Plc have amassed payroll records about most Americans, a small rival urged in a letter to the agency on Monday that was seen by Reuters.

For decades, companies such as Equifax have acquired employee work histories and compensation data from employers to help lenders, landlords, hiring managers and other customers perform background checks of individuals.

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In the letter to the FTC, San Mateo, California-based startup Certree said that Equifax and Experian are providing financial incentives like a slice of their revenue to employers to gain exclusive access to payroll data. Equifax also has deals with payroll software vendors that help employers process paychecks. The letter describes the agreements as anticompetitive and potentially unlawful. The FTC declined to comment. Under new Chair Lina Khan, the agency has sought to increase enforcement on competition and privacy grounds.

The company said workers can view or block access to records and that it has improved data security. Experian's employment verification service launched last year.

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Bogdanlnx November 22, Reply. Cleveland November 22, Reply. Wally November 22, Reply. Reggie November 21, Reply. Frank November 21, Reply. Fredrick November 21, Reply. The remaining article is prepared in the following way: Sections 2 , 3 describes the artificial cell swarm optimization method and the type 2 fuzzy clustering framework respectively.

Section 6 discusses some of the relevant points and a brief conclusion is presented in Section 7. This is a recently developed metaheuristic procedure that is inspired by the artificial cell division procedure. The artificial cell swarm optimization procedure mimics the artificial cells as the search agents.

The actual artificial cell division approach [46] is slightly modified to design the optimization procedure. The incorporated modifications are listed below [47] :.

The hierarchical tree structure is formed throughout the generations due to the artificial cell division process.

Swarms of artificial cells are considered in the optimization process to take part in the artificial cell division process. No communication is allowed between any pair of artificial cells. Lifespan of the k th artificial cell at a certain timestamp t s is an important parameter and it is directly dependent on the fitness value f i t n e s s k as given in Eq.

A huge number of swarms can significantly increase the fitness evaluations and a small number of swarms can increase time to converge and therefore, is essential to decide the swarm count moderately.

In this work, the swarm count is considered is a fixed parameter. One artificial cell can produce some new cells and the production of new cells occur at a certain distance which is inversely dependent on the fitness of the producer cell as expressed in Eq. The distance between the k th cell and any of the l th cell, which are produced from the same parent cell, must be same.

Therefore, if a cell is near to global optima, then it can generate some other cells at a smaller distance and vice-versa. Smaller steps help to search the nearest portions of the global optima cautiously so that the global optima may not be missed accidentally. A cell does not have any effect on the population once its lifespan is over. This property helps to maintain the size of the population and prevents getting overpopulated.

The successor cells of a cell can produce some other cells by the cell division process to maintain the population. The life span of a cell can belong it belongs to the near-optimal area. The quality of a population is evaluated using the lambda function which is given in Eq.

Algorithm 1 illustrates the artificial cell swarm optimization approach in brief [47]. The proposed approach adopts the type 2 fuzzy logic-based clustering approach to effectively model and handle the random uncertainties. In most real-life applications, the uncertainty cannot be predicted in advance.

A wide range of input types can produce random uncertainties. Hence, it is essential to cope up with the random uncertainties in real-life scenarios. The fuzzy C-means clustering approach is one of the widely used clustering approaches which is suitable to various problems of different domains [48] , [49] , [50] , [51]. The main reason behind the increasing popularity of fuzzy systems is the suitability of this approach in different scenarios where the crisp clustering approaches do not perform well.

A single point can be a member of more than one cluster at the same time with some membership values. The total sum of all membership values for a certain point must be one. So, the value of the membership can be anything between 0 and 1. The dissimilarity function which is optimized by the fuzzy C-means clustering approach is given in Eq. The cluster centers can be updated using Eq. The type 2 fuzzy logic systems use separate sets of membership values that are also fuzzy in nature.

This approach allows efficient modeling of dynamic input uncertainties by providing additional degrees of freedom. In this work, the type 2 fuzzy logic-based clustering approach is adopted to overcome some of the common problems of type 1 fuzzy systems like noise sensitivity, relative membership values, etc. It is essential to improve the outcome of the segmentation process. The uncertainty of a point must be decided depending on the membership value i. So, a lower membership value indicates higher uncertainty and vice-versa.

Some of the basic reason behind the adoption of type 2 fuzzy system in this work is listed below [53] :. The membership value in type 2 fuzzy systems can be calculated using Eq. The proposed approach does not require Eq. The artificial cell swarm optimization process will guide the proposed approach to determine the optimal cluster centers. The type 2 fuzzy clustering system can be easily understood from algorithm 2 and the schematic diagram of the type 2 fuzzy system can be visualized from Fig.

The ever-growing technology allows us to increase the quality of the image acquisition hardware. High-quality biomedical images can be acquired from various biomedical image acquisition devices and it is helpful in a precise analysis of the biomedical images. Automated biomedical image analysis devices are facing some challenges due to the increasing quality of biomedical images. A high amount of spatial information creates severe problems for automated and computer-aided diagnostic systems because medical diagnostic systems demand quick and accurate results.

Image segmentation plays a vital role in many automated computer-aided image analysis systems. It is essential to generate precise reports within the stipulated amount of time to provide accurate treatment to the patients. To handle this situation effectively and to accelerate the screening process of the COVID infection, a superpixel-based novel approach is proposed in this work to segment the CT scan images. Superpixels are useful to represent a set of pixels in a computation-friendly manner.

Different approaches can be found in the literature to find the superpixel image from an input image [54] , [55] , [56]. Some superpixel computation methods like mean shift [54] and watershed [56] produce irregular superpixels and some methods like SLIC [55] generate regular superpixels.

Meanshift and watershed approaches are more useful due to the capability to generate irregular superpixels. The watershed approach is simpler to implement compared to the mean-shift approach but it is sensitive to the noise which is not at all desirable for the image segmentation approaches. In this work, the noise sensitivity of the watershed approach is removed with the help of the gradient image, which is generated using the approach, proposed in [57].

The obtained gradient image is processed using the morphological erosion and dilation-based reconstruction operations, which are given in Eqs. Here, s e is the structuring element and it is an important parameter that controls the segmented outcome.

The size of the structuring element is subjective and depends on the image under consideration. Practically, it is not possible to determine different structuring elements which are of various sizes, depending on the image.

Therefore, the pointwise maximum value is computed using Eq. The number of superpixels is inversely dependent on the size of the structuring elements. It can be easily understood in Fig. The image considered in these two figures is the T e s t 01 image [58] please refer to Table 3. Dependency of the number of superpixels on the size of the disk structuring element a — h superpixel images obtained using the disk structuring element of size 3 to 10 respectively, i Size of the structuring element vs.

Dependency of the number of superpixels on the size of the square structuring element a — h superpixel images obtained using the square structuring element of size 3 to 10 respectively, i Size of the structuring element vs.

A very small lower bound is not desirable because it will produce very small regions and some essential edge information can be lost. So, the threshold value can be adjusted as per the requirement and depending on the available resources. The conventional fuzzy C-means clustering approach often overlooks some important spatial information that can be costly in terms of the segmentation performance.

Some approaches try to solve this problem by considering and blending some local spatial information in the objective function but it increases the computational cost and therefore not suitable on many occasions. Superpixels can help in this context by over-segmenting an image in many small, perceptually uniform, and homogeneous regions. In this work, the CT images are first processed to determine the superpixels using the proposed approach and then the fuzzy artificial cell swarm optimization approach is used to determine the segmented image by finding the optimal clusters.

As discussed earlier, the type 2 fuzzy system is used to perform the segmentation. The fuzzy objective function which is given in Eq. To incorporate the advantages of the superpixel, it is necessary to modify the fuzzy objective function. The representative value is used in the objective function, and the modified objective function is given in Eq. The cluster centers can be updated and guided by the artificial cell swarm optimization and therefore, no equation is required to compute the updated positions of the cluster center.

This approach is not dependent on the selection of the initial cluster centers. The proposed procedure is given in algorithm 3 and the schematic flow diagram is given in Fig.

As discussed earlier, the properly annotated ground truth segmented images may not be available always, and therefore, some standard intrinsic cluster evaluation methods are used here to evaluate the proposed approach quantitatively. The proposed methods are applied to the images and the test results are demonstrated with the 10 CT scan images that are randomly selected which are obtained from different countries of the world.

Table 3 gives a brief overview of the test images and the test images along with their histograms are given in Fig. The experiments are performed in the MatLab Ra on a computer that is equipped with an Intel i3 processor and 4 GB main memory.

The proposed method is compared with some metaheuristic optimization-based image segmentation approaches like modified genetic algorithm [67] , modified PSO [68] , improved bat algorithm [69] and modified cuckoo search method [70] in both qualitative and quantitative manner. The visual comparison is presented in Fig. The acceptable values are highlighted in boldface. The comparisons and evaluations are performed for different numbers of clusters.

A comparative study of different approaches using T e s t 01 for different number of clusters. Performance evaluation of different approaches using Davies—Bouldin index The highlighted values indicates acceptable values. Performance evaluation of different approaches using Xie—Beni index The highlighted values indicates acceptable values.

Performance evaluation of different approaches using Dunn index The highlighted values indicates acceptable values. From the qualitative and quantitative results, it can be observed that the proposed SUFACSO approach outperforms some state-of-the-art works and can produce realistic outputs that are certainly helpful for the interpretation of the real-life CT scan images and therefore, this approach can be helpful for the early screening purposes.

At the end of each table, the average performance of the five approaches is reported which is beneficial to understand the overall performance of these methods for the different number of clusters and different cluster validity indices. In the case of average, the column-wise optimal values are highlighted instead of highlighting the row-wise optimal values.

The row-wise highlighted values talk about the performance of the individual algorithm for the different number of clusters whereas the column-wise highlighted values help to understand the performance of the individual algorithms. It can be observed that the proposed approach outperforms other approaches for most of the number of clusters as well as for most of the validity indices.

For example, on a total of 16 occasions i. These comparative results are graphically presented in Fig. In X -axis the number of clusters and in the Y -axis, the values of the corresponding validity index are plotted. The experiments are carried out for the different numbers of clusters. A particular approach may perform well for a particular cluster count.

That is why the average values of all experiments are reported at the end of each table for better interpretation. It can be observed that the proposed approach can optimize different objective functions effectively. Actually, the experiments are carried out on CT images in the first phase and CT images in the second phase.

It is already mentioned in Section 5. Results that are obtained from all images are not possible to report in this stipulated amount of space.

Therefore, only some results that are obtained from some selected images are reported. Apart from these tests, the proposed approach is also compared with some of the active contour models based on some standard parameters like accuracy, precision, and recall. This comparison is performed by using the database that is available at [71]. This dataset is created by collecting sample images from 49 patients with age range 32—86 years. The obtained average results are reported in Table 8.

The rate of convergence is an important parameter to be studied. The performance evaluation remains incomplete without studying and comparing the convergence of different algorithms. The convergence analysis gives a clear view of the comparative performance of different algorithms for the different numbers of clusters.

The graphical analysis of the convergence is presented in this subsection using the image T e s t 01 for the Dunn index. In Fig. In a single plot, four separate curves are indicating four different clusters. These curves show that the proposed approach can efficiently segment the images for a higher number of clusters. Moreover, the proposed approach also outperforms some other methods in terms of convergence besides quantitative and qualitative performance.

The time complexity is an important aspect that is to be analyzed. From the detailed discussion of the proposed approach, it can be noticed that the proposed approach can be viewed as a two-phase procedure where the watershed-based computation approach is used to determine the superpixel image from the underlying image in the first phase and the optimal segmented outcome is computed in the second phase. The task of optimization is performed using the proposed fuzzy ACSO approach. The gradient information of an image is used to avoid the noise sensitivity of the water-shed based superpixel computation process.

The watershed-based technique is a simple method to compute the superpixel and the implementation follows linear complexity [56]. It is quite inspiring and lucrative to adopt this approach on different occasions. In the optimization part, the fuzzy objective function is optimized by using the proposed fuzzy ACSO method. The ACSO approach is an effective and efficient approach that can be executed in linear time [47]. So, the proposed approach is efficient enough and can be effectively used in various real-life problem-solving scenarios.

This approach can effectively process high-quality images with the help of the proposed superpixel-based approach that is an essential quality for the real-life application of an image segmentation approach.

This approach removes the dependency of choice of the initial cluster centers as well as the ACSO approach determines the optimal cluster centers by optimizing some validity indices. These advantages motivate us to apply the proposed approach to automatically segment the radiological images that will be certainly helpful in diagnosing some symptoms of COVID The experimental outcomes show the efficiency of the proposed approach.

Under this pandemic environment, this work is designed hoping that it can help physicians and other domain experts to some extent in the early diagnosis of the disease. Early diagnosis can prevent the drastic spread of this highly infectious virus. Quantitative results do not have any direct implications in real-life diagnosis. The segmented outcomes are useful in the diagnosis process.

Physicians can investigate the segmented outcomes to find some prominent and common features as mentioned in Table 2. The segmented images will be helpful in the easy interpretation of the radiological images. The proposed SUFACSO approach is an efficient image segmentation approach that can effectively segment the radiological images that highly useful in the easy interpretation of these images.

There is a high possibility that a suspected patient can spread the disease in the community completely unwillingly. The proposed approach can reduce this chance because an initial screening can be performed by the physicians comfortable with the help of the proposed SUFACSO approach.

It is worth mentioning here that the proposed approach is neither a replacement of the RT-PCR test nor it can confirm the presence of the virus accurately. However, this approach can be helpful in an initial screening at an early stage that will restrict the spread of this highly infectious virus by separating suspected patients from the rest of the community. The obtained results indicate that the proposed approach is suitable for real-life scenarios and also performs efficiently.

This approach can be easily adapted for the automated screening purposes of the COVID infected patients. It is assumed the quality of the CT scan images is considerably high and the performance of the proposed approach is not verified against the presence of noise.

It will be interesting to study the proposed approach in the presence of noise. The scalability of the proposed approach to different types of biomedical images can be explored in future studies.

Missing manual annotations can jeopardize the generalizability of the proposed work. On the other hand, the obtained results are quite promising and encouraging. From the best of the knowledge of the authors, there is no publicly available manually annotated dataset for the chest CT scan images of the COVID positive cases.

Although the proposed approach is efficient enough to segment the CT scan images automatically and produces realistic segmented outcomes still, some important drawbacks can be observed in this proposed approach that can be addressed in the subsequent works. One important drawback of the proposed approach is that it cannot automatically determine the number of clusters and it can be overcome in future works.

Automated estimation of the clusters can make this approach more realistic, robust, and application friendly. The proposed method can handle only a single objective at a time.

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