The Detection of Abnormal Behavior in Healthcare IoT Using IDS, CNN, and SVM

Health care is always a top priority, and that has not changed no matter how far we have come in terms of technology. Since the coronavirus epidemic broke out, almost every country has made health care a top priority. Therefore, the best way to deal with the coronavirus pandemic and other urgent health problems is through the use of IoHT. The tremendous growth of IoT devices and networks especially in the healthcare domain generates massive amounts of data, necessitating careful authentication and security. Other domains include agriculture, smart homes, industry, etc. These massive data streams can be evaluated to determine undesirable patterns. It has the potential to reduce functional risks, avoid problems that are not visible, and eliminate system downtime. Past systematic and comprehensive reviews have significantly aided the field of cybersecurity. However, this research focuses on IoT issues relating to the medical or healthcare domain, using the systematic literature review method. The current literature in health care is not enough to analyze the anomaly of IoHT. This research has revealed that fact. In our subsequent work, we will discuss the architecture of IoHT and use AI techniques such as CNN and SVM to detect intrusions in IoHT. In the interest of advancing scientific knowledge, this study identifies and suggests potential new lines of inquiry that may be pursued in this area of study. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Relational coupling of multiple streams: The case of COVID‐19 infections in German abattoirs

After a series of COVID‐19 outbreaks among employees in the German meat‐processing industry, the Work Safety Control Act protecting these workers made it on the government's agenda in July 2020. From a Multiple Streams perspective, local corona hotspots may be understood as policy windows for introducing respective measures. However, this alone is not sufficient to explain agenda setting. This study investigates the coupling of streams within policy windows. Introducing the notion of relational coupling to the MSF research agenda, discourse network analysis provides a new methodology to reveal entrepreneurial activities. Studying the German mass media discourse on the issue identifies two stages: (1) An initial problem brokerage without coupling of core policies, followed by (2) a coupling across all streams based on a focusing event. We argue that relational coupling allows for an enhanced understanding of agenda setting. (English) [ FROM AUTHOR] Resumen Después de una serie de brotes de COVID‐19 entre los empleados de la industria alemana de procesamiento de carne, la Ley de control de seguridad laboral que protege a estos trabajadores se incluyó en la agenda del gobierno en julio de 2020. Desde una perspectiva de múltiples corrientes, los puntos críticos locales de corona pueden entenderse como una política Ventanas para introducir las respectivas medidas. Sin embargo, esto por sí solo no es suficiente para explicar el establecimiento de la agenda. Este estudio investiga el acoplamiento de corrientes dentro de las ventanas de políticas. Al introducir la noción de acoplamiento relacional en la agenda de investigación de MSF, el análisis de redes de discurso proporciona una nueva metodología para revelar las actividades empresariales. El estudio del discurso de los medios de comunicación alemanes sobre el tema identifica dos etapas: (1) Una solución inicial del problema sin el acoplamiento de políticas centrales, seguida de (2) un acoplamiento en todas las corrientes basado en un evento focalizado. Sostenemos que el acoplamiento relacional permite una mejor comprensión del establecimiento de la agenda. (Spanish) [ FROM AUTHOR] 摘要: 德国肉制品加工业出现一系列2019冠状病毒病(COVID‐19)员工感染事件后,用于保护这类员工的《工作安全防控法》(Work Safety Control Act)于2020年7月被纳入政府议程。从多源流视角来看,地方COVID‐19事件可被理解为用于引入相应措施的政策之窗。不过,仅这一方面并不足以解释议程设置。本研究分析了政策之窗中各源流的耦合。通过将关系耦合(relational coupling)的概念引入多源流框架(MSF)的研究议程,话语网络分析为揭示企业活动一事提供新方法。通过研究有关该议题的德国大众媒体话语,识别了两个阶段:(1)核心政策未发生耦合的情况下出现的最初问题；(2)基于焦点事件出现的各源流耦合。我们论证认为,关系耦合促进了对议程设置的理解。 (Chinese) [ FROM AUTHOR] Copyright of Policy Studies Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Policy entrepreneurs and individuals: Influence and behavior in pandemic response

Policy entrepreneurs have traditionally been recognized for their ability to influence policymakers by framing policy problems and pairing them with preferred solutions. Does their influence extend to the public? We examine this question in the context of the COVID-19 pandemic in the United States. We analyze whether an individual's perception of a visible, national-level policy entrepreneur, director of the National Institute of Allergy and Infectious Diseases (NIAID) Dr. Anthony Fauci, influences their perceived risk of contracting the virus and their uptake of recommended COVID-19 risk mitigation behaviors. Findings indicate that approval of Dr. Fauci predicts individual risk perceptions and uptake of mask wearing practices, with his influence particularly strong among conservatives. However, Dr. Fauci's influence as a policy entrepreneur waned over time and was moderated by a host of factors such as an individual's worldview, perceptions of policy environment, and media consumption.

Towards a Paradigm Shift in Social Protection in Developing Countries? Analyzing the Emergence of the Ghana National Unemployment Insurance Scheme from a Multiple Streams Perspective

The COVID 19 pandemic continues to cause a lot of uncertainty around the world. At the onset of the pandemic, governments responded with policies and programs to curb its devastating effects on citizens, and Ghana was no exception. Although the Ghanaian government introduced various stop-gap measures to mitigate the effects of the pandemic, the inadequacies of the extant social welfare system was badly exposed. Consequently, as the pandemic seethed on, there were calls for reform of the existing social protection system and the introduction of new programs, especially for those in the informal sector. In response, the government introduced a new National Unemployment Insurance Scheme (NUIS). How did this happen? What led the government to accept tentatively the need to reform and transform the social welfare system after years of policy padding and the dragging of feet? Drawing on Kingdon's Multiple Streams Framework, we argue that the pandemic created a policy window, which enabled policy enntrepreneurs to push the unemployment insurance idea to reform the existing social welfare system. The introduction of a NUIS, is seen as a paradigm shift in social protection and more broadly in social policy. The objective of this paper is to examine how the NUIS got on government's agenda, and whether the NUIS is a game changer in social protection in Ghana. We sourced information mainly from secondary sources.

Anchor Institutions and Food Resilience: A Multiple Streams Approach

Anchor institutions (AIs) play an essential role in food system resilience. We utilize Kingdon's multiple streams approach (MSA) to analyze AIs' food system resilience activities in Vermont. Drawing on a series of focus groups to understand activities to foster food system resilience. Local food supply chains can be a source of resilience;barriers such as labor and infrastructure shortages can be overcome through greater use of local food processing and distribution. The MSA lens suggests that Covid-19 can serve as a focusing event, incentivizing investment and leveraging the national mood for greater consumption and support for local food. © 2023, International Journal on Food System Dynamics. All Rights Reserved.

COVID-19 and the second exams fiasco across the UK: four nations trying to avoid immediate policy failure.

In 2021, the UK and devolved governments tried to avoid the school exams fiasco of 2020. Their immediate marker of success was to prevent a similar U-turn on their COVID-19 school exams replacement policies. They still cancelled the traditional exam format, and sought teacher assessments to determine their grades, but this time without using an algorithm to standardise the results. The outcomes produced some concerns about inequity, since the unequal exam results are similar to those experienced in 2020. However, we did not witness the same sense of acute political crisis. We explain these developments by explaining this year's 'windows of opportunity' overseen by four separate governments, in which the definition of the problem, feasibility of each solution, and motive of policymakers to select one, connects strongly to the previous U-turn. A policy solution that had been rejected during the first window became a lifeline during the second and a likely choice during the third. This action solved an immediate crisis despite exacerbating the problem that ministers had previously sought to avoid ('grade inflation'). It produced another year of stark education inequity, but also ensured that inequity went from part of an acute political crisis to its usual status as a chronic low-attention policy problem.

Tracking the Evolution of Clusters in Social Media Streams

Tracking the evolution of clusters in social media streams is becoming increasingly important for many applications, such as early detection and monitoring of natural disasters or pandemics. In contrast to clustering on a static set of data, streaming data clustering does not have a global view of the complete data. The local (or partial) view in a high-speed stream makes clustering a challenging task. In this paper, we propose a novel density peak based algorithm, TStream, for tracking the evolution of clusters and outliers in social media streams, via the evolutionary actions of cluster adjustment, emergence, disappearance, split, and merge. TStream is based on a temporal decay model and text stream summarisation. The decay model captures the decreasing importance of textual documents over time. The stream summarisation compactly represents them with the help of cells (aka micro-clusters) in the memory. We also propose a novel efficient index called shared dependency tree (aka SD-Tree) based on the ideas of density peak and shared dependency. It maintains the dynamic dependency relationships in TStream and thereby improves the overall efficiency. We conduct extensive experiments on five real datasets. TStream outperforms the existing state-of-the-art solutions based on MStream, MStreamF, EDMStream, OSGM, and EStream, in terms of cluster mapping measure (CMM) by up to 17.8%, 18.6%, 6.9%, 16.4%, and 20.1%, respectively. It is also significantly more efficient than MStream, MStreamF, OSGM, and EStream, in terms of response time and throughput.

The impact of big data on decision-making on business support measures during the COVID-19 pandemic: The case of St. Petersburg

This article examines the use of big data in the decision-making process on measures to support small and medium-sized businesses in St. Petersburg during the COVID-19 pandemic. The theoretical novelty of this study lies in the demonstration of the use of big data to combat the pandemic and its consequences at the regional level. The research issue is considered in the context of introducing QR codes for entrepreneurs in St. Petersburg in order to control the requirements of safe activities during the pandemic. St. Petersburg was chosen as the region under study, since Moscow is closely connected with the federal government and does not fully reflect the regional peculiarities of the fight against the pandemic, at least because of the redundancy of resources in the capital. In turn, other regions of Russia are not as technologically advanced as St. Petersburg to demonstrate the use of big data during the COVID-19 pandemic. To determine the role of COVID-19 in accelerating the introduction of big data into the political process, I use the multiple streams framework in conjunction with the model of the political cycle. To study the very process of using big data, I focus on the actors in this process, their interests and values, namely, "data analysts" and "decision makers". Thus, my model combines a case study from the point of view of a dynamic process with causal relationships and from the point of view of the actors involved in this process. To analyse the case, I used the method of included observation, which implies participation in several meetings on the development of measures to support enterprises, as well as the study of documents - resolutions of the Government of St. Petersburg, internal accounting documents and official websites. As a result, the case under review appears to be a clear illustration of a regional initiative in the fight against the COVID-19 pandemic and how big data has been used to overcome the economic impact of the pandemic at the regional level. The pandemic has not only become a "window of opportunity" for regional authorities to pursue their own policies in the fight against COVID-19, but also made it possible for middle-level actors to take the initiative and promote their own decision on the regional agenda. The case of St. Petersburg demonstrates that the process of digitalization using big data occurs not only from the top down through the implementation of the national strategy and not only from the bottom up through the integration of private digital services. Mid-level structures also influence the digitalization process through the promotion of their products and services, using "windows of opportunity", such as the COVID-19 pandemic.

Regional Business Support Programs in the Context of Covid-19 as an Example of Introducing Big Data in Public Administration

The article puts forward a hypothesis about the difference between digitalization and management based on big data (hereinafter referred to as BD);it is assumed that these are stages of the same process. The transition from digitalization to BD-driven decisions is perceived as a kind of << leap >> in public administration. Authors set the research task of identifying the key differences between these stages, as well as determining the reasons for the transition from one to the other. To do this, we carry out an analysis of the implementation of BD-driven solutions in public administration during the COVID-19 period, with a focus on the regional level. The analysis is based on the multiple streams theory. The case-study method was used to compare the selected regions. At this stage of the study, a gap in the development of the digital infrastructure in the Russian regions was revealed - a situation where only rich regions can carry out their original solutions, having the opportunity to invest in advance in the development of digital infrastructure, training and original management solutions. As a result of the conducted research, the absence of original digital solutions in the regions was noted. An alternative to using a BD-driven policy is simple digitalization, by which we mean either imitation solutions or blind copying of technological solutions offered by the federal center. In order to switch to BD-driven management, regional administrations need to accumulate expertise, experience in implementing successful digital projects, and make investments in the development of technological infrastructure and training.

Monitoring of the Surfactants in Surface Waters in Slovakia and the Possible Impact of COVID-19 Pandemic on Their Presence

In order to keep the home and occupational environment clean and non-infectious, the consumption of cleaners and disinfectants, including cosmetics, is increasing. Excessive use of these products results in their accumulation in the aquatic environment. Conventional wastewater treatment plants are unable to effectively remove the emergent pollutants, including personal care products. This article is focused on the monitoring of the presence of personal care products in surface waters in two river basins in the Slovak Republic, in terms of the surfactant content. Ecotoxicological evaluation of the selected samples from the monitored river basins was performed by an acute toxicity test using the test organism Daphnia magna. The monitoring results indicate the presence of personal care products in the aquatic environment which poses an ecological and environmental risk. Monitoring in the Hron and Nitra river basins confirmed contamination with the surfactants, to which the measures related to the COVID-19 pandemic contributed. The content of the surfactants in personal care products is significant, and their impact on the aquatic environment is not sufficiently monitored.

Caught between a rock and a hard place: Impact of COVID-19 on feminist media in Uganda, Rwanda and Tanzania

This chapter explores how feminist and women-owned media/organisations in Uganda, Rwanda and Tanzania navigated the impact of COVID-19. Three debilitating realities contextualise this study. The first is the fact that feminist media find themselves trapped in a global existential struggle following the steady collapse of traditional media's economic models. Second, women's owned media by their nature are marginal and undermined by hegemonic patriarchal power structures and third, COVID-19 spared no media. The pandemic devastated the media industry globally especially print, and community-owned media such as women's owned media. The chapter is informed by political economy of feminist media theories with a main focus on principles of media viability. It draws from interviews with managers and senior reporters at leading feminist and women-owned media/organisations in the three countries. The findings shed light on how operations, human resources, content and financial sustainability were navigated and reshaped in a flawed health, political and socio-cultural systemic context that threatened to annihilate the case media. We highlighted the innovative solutions and resolve indicative of the resilience, determination and agency that these women-owned media/organisations exercised in the face of the crisis at the time, something others can learn from. © 2022 by Carol Azungi Dralega, Margaret Jjuuko and Eva Solomon.

Towards a socially fair green transition in the EU? An analysis of the Just Transition Fund using the Multiple Streams Framework

The Just Transition Fund was introduced in 2021 as part of the European Union's Green New Deal and aims to assuage some of the painful social consequences of the green transition. Relying on the Multiple Streams Framework, this article reconstructs the JTF's institution. It identifies 2018–2019 as a key conjuncture in the European Union when various social, ideational and political preconditions enabling policy innovation converged. Subsequently, the need to publicly finance a just transition emerged in relation to some Eastern European states' reluctance to work towards the 2050 climate neutrality target. After a Polish-led configuration of actors propelled the JTF onto the agenda, the von der Leyen Commission assumed the task of designing a less transparently self-serving policy instrument necessary to garner wider political support. The final JTF emerged from the interplay between two policy entrepreneurs in the context of the negotiations on the 2021–2027 European Union budget and the dislocations provoked by the COVID-19 crisis.

From multiple streams to a torrent: A case study of food policymaking and innovations in New York during the COVID-19 emergency.

The COVID-19 pandemic has had significant effects on urban and regional food systems. Local administrations worldwide have been challenged to design and implement policies to mitigate immediate food system disruptions while planning for longer-term equity and resilience. The fast pace and high degree of uncertainty of the pandemic have made systematic tracking and assessment of food system change and related policy responses arduous. To address this gap, this paper applies the multilevel perspective on sociotechnical transitions and the multiple streams framework on policy change to 16 months of food policy (March 2020 through June 2021) during the New York State-issued COVID-19 state of emergency, comprising more than 300 food policies advanced by New York City and State legislators and administrators. Content analysis of these policies revealed the most salient policy areas during this period, the status of legislation, and key programs and budget allocations, as well as local food governance and the organizational spaces within which food policy operates. The paper shows that food policy domains that gained prominence focused on support for food businesses and food workers and on ensuring and expanding food access through food security and nutrition policies. Most COVID-19 food policies were incremental and were limited to the duration of the emergency, yet the crisis allowed for enactment of novel policies that deviated from the common policy issues or the typical scale of changes proposed pre-pandemic. Taken together, and viewed through a multilevel and policy streams framework, the findings provide insight into the trajectory of food policymaking in New York during the pandemic and the areas that food justice activists, researchers, and policy makers should focus on as the COVID-19 pandemic is abated.

How Did the COVID-19 Pandemic Increase Salience of Intimate Partner Violence on the Policy Agenda?

Belgian authorities, like most authorities in European countries, resorted to unprecedented measures in response to the spread of the COVID-19 pandemic between March 2020 and May 2022. This exceptional context highlighted the issue of intimate partner violence (IPV) in an unprecedented way. At a time when many other issues are being put on hold, IPV is being brought to the fore. This article investigated the processes that have led to increasing political attention to domestic violence in Belgium. To this end, a media analysis and a series of semi-structured interviews were conducted. The materials, collected and analyzed by mobilizing the framework of Kingdon's streams theory, allowed us to present the agenda-setting process in its complexity and the COVID-19 as a policy window. The main policy entrepreneurs were NGOs and French-speaking feminist women politicians. Together, they rapidly mobilized sufficient resources to implement public intervention that had already been proposed in the preceding years, but which had been waiting for funding. By doing so, they responded during the peak of the pandemic to requests and needs that had already been expressed in a "non-crisis" context.

Feedstock planning and optimization of a sustainable distributed configuration biorefinery for biojet fuel production via ATJ process

In recent years, the production and consumption of fossil jet fuel have increased as a consequence of a rise in the number of passengers and goods transported by air. Despite the low demand caused by the coronavirus 2019 pandemic, an increase in the services offered by the sector is expected again. In an economic context still dependent on scarce oil, this represents a problem. There is also a problem arising from the fuel's environmental impact throughout its life cycle. Given this, a promising solution is the use of biojet fuel as renewable aviation fuel. In a circular economy framework, the use of lignocellulosic biomass in the form of sugar-rich crop residues allows the production of alcohols necessary to obtain biojet fuel. The tools provided by process intensification also make it possible to design a sustainable process with low environmental impact and capable of achieving energy savings. The goal of this work was to design an intensified process to produce biojet fuel from Mexican lignocellulosic biomass, with alcohols as intermediates. The process was modeled following a sequence of pretreatment/hydrolysis/fermentation/purification for the biomass-ethanol process, and dehydration/oligomerization/hydrogenation/distillation for ethanol-biojet process under the concept of distributed configuration. To obtain a cleaner, greener, and cheaper process, the purification zone of ethanol was intensified by employing a vapor side stream distillation column and a dividing wall column. Once designed, the entire process was optimized by employing the stochastic method of differential evolution with a tabu list to minimize the total annual cost and with the Eco-indicator-99 to evaluate the sustainability of the process. The results show that savings of 5.56% and a reduction of 1.72% in Eco-indicator-99 were achieved with a vapor side stream column in comparison with conventional distillation. On the other hand, with a dividing wall column, savings of 5.02% and reductions of 2.92% in Eco-indicator-99 were achieved. This process is capable of meeting a demand greater than 266 million liters of biojet fuel per year. However, the calculated sale price indicates that this biojet fuel still does not compete with conventional jet fuel produced in Mexico. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.

A creeping crisis when an urgent crisis arises: The reprioritization of plastic pollution issues during COVID‐19

Single‐use plastics (SUPs) are increasingly polluting terrestrial, coastal, and marine habits, contributing to the creeping “plastic crisis.” The COVID‐19 pandemic provided a window of opportunity for decision makers to change the degree of urgency and responsiveness to this crisis and for policy entrepreneurs and industry who are against reducing plastic consumption to influence decision makers to change their position on various plastic‐related issues. Hygiene/health concerns have been used as a justification by governments and industry to increase the use of SUPs resulting in a reversal in, or a reprioritization of, policy decisions. Through the Multiple Streams Framework (MSF), I examine how creeping crises become secondary to urgent crises through agenda setting that is influenced and leveraged by policy entrepreneurs. I explore examples of such plastic policy decisions finding that they have been politically driven and influenced by entrepreneurs and industry rather than being primarily based on health concerns.Related ArticlesDiaz‐Kope, Luisa, and John C. Morris. 2022. “Why Collaborate? Exploring the Role of Organizational Motivations in Cross‐sector Watershed Collaboration.” Politics & Policy 50(3): 516â€"39. https://doi.org/10.1111/polp.12470.Gerlach, John David, Laron K. Williams, and Colleen E. Forcina. 2013. “The Science‐Natural Resource Policy Relationship: How Aspects of Diffusion Theory Explain Data Selection for Making Biodiversity Management Decisions.” Politics & Policy 41(3): 326â€"54. https://doi.org/10.1111/polp.12017.Neill, Katharine A., and John C. Morris. 2012. “A Tangled Web of Principals and Agents: Examining the Deepwater Horizon Oil Spill through a Principalâ€"Agent Lens.” Politics & Policy 40(4): 629â€"56. https://doi.org/10.1111/j.1747‐1346.2012.00371.x.Alternate :Una crisis progresiva cuando surge una crisis urgente: La repriorización de los problemas de contaminación plástica durante el COVID‐19Los plásticos de un solo uso (SUP) están contaminando cada vez más los hábitos terrestres, costeros y marinos, lo que contribuye a la progresiva "crisis del plástico". La pandemia de COVID‐19 brindó una ventana de oportunidad para que los tomadores de decisiones cambien el grado de urgencia y capacidad de respuesta a esta crisis y para los empresarios de políticas y la industria que están en contra de reducir el consumo de plástico para influir en los tomadores de decisiones para cambiar su posición sobre varios temas relacionados con el plástico. Los gobiernos y la industria han utilizado las preocupaciones de higiene/salud como justificación para aumentar el uso de SUP, lo que ha dado lugar a una reversión o una nueva priorización de las decisiones políticas. A través del Marco de Corrientes Múltiples (MSF, por sus siglas en inglés), examinamos cómo las crisis progresivas se vuelven secundarias frente a las crisis urgentes a través del establecimiento de una agenda que es influenciada y aprovechada por los empresarios de políticas. Exploramos ejemplos de tales decisiones sobre políticas de plástico y descubrimos que han sido impulsadas políticamente e influenciadas por empresarios y la industria en lugar de basarse principalmente en preocupaciones de salud.Alternate :紧急危机发生时的慢性危机:2019å† çŠ¶ç—…æ¯'病期间塑料污æŸ"问题的优先次序调整一次性塑料(SUP)越来越多地污æŸ"陆地、沿海å'Œæµ·æ´‹çŽ¯å¢ƒï¼Œä¸ºæ…¢æ€§â€œå¡‘料危机”作贡献。2019å† çŠ¶ç—…æ¯'ç—…(COVID‐19)大流行为决策者提供了一个机会之窗，以改变对这场危机的紧迫程度å'Œå"åº”程度，并为反对减少塑料消费的政策企业家å'Œè¡Œä¸šæä¾›æœºä¼šï¼Œä»¥å½±å"å†³ç­–者改变其在不同塑料相关问题上的立场。卫生/健康问题已被政府å'Œè¡Œä¸šç”¨ä½œå¢žåŠ SUP使用的理由，从而导致政策决策发生逆转或优先次序调整。通过使用多源流框架(MSF)，我们分析了慢性危机如何在一个受政策企业家影å"å'Œåˆ©ç”¨çš„议程设置下次于 ´§æ€¥å±æœºã€‚我们探究了这类塑料政策决策的例子，发现决策的制定并非主要基于健康问题，而是受到企业家å'Œè¡Œä¸šçš„政治驱动å'Œå½±å"ã€‚

What Business Researchers are producing during Covid-19 A bibliometric approach

The way COVID-19 impacted every aspect of human life around the world, is now considered more disastrous than the World War II. Both the policy and academic researchers have been contributing to assess its severity and impact on businesses and economies while examining the foci of business researchers in this era of contagion. In this assessment, we have applied the approaches of bibliometric and content analysis on 403 qualified studies, drawn from the Scopus database. The period of data ranges from 2003 to June 2020. We identified 11 different research streams including tourism, supply chain besides economic and finance-related research. We highlighted the sub-streams and main concerns raised in the published literature. The findings of this research indicate that COVID will force the policy makers to come up with strategy and changes in various business fields. The implications of the study may be important for business managers to chalk out a proactive approach for business handling during and post-COVID eras. © 2022, University of the Punjab. All rights reserved.

Multiple Streams, Open Windows, and yet No Solution

Article VII of the Biological Weapons Convention (BWC) requires states to provide emergency assistance in the case of a deliberate bioweapons attack on any state party to the convention. Since no operational mechanism defining how to request or provide such assistance has yet been established, the painful lessons of the 2014-2016 West African Ebola crisis returned this topic to the agenda of the BWC. This study uses multiple streams analysis to investigate the impact of the Ebola crisis on the considerations of Article VII. While it revived the three streams of the debate - problem, policy, and politics - and opened a policy window, nevertheless, no political entrepreneur was able to couple the streams to produce policy output. As this window of opportunity begins to close, the Covid-19 pandemic seems to be the next focusing event shaping the BWC discourse on emergency assistance. © 2022 Copyright 2022 by Helge Schumacher.

Tracking the Evolution of Clusters in Social Media Streams

Tracking the evolution of clusters in social media streams is becoming increasingly important for many applications, such as early detection and monitoring of natural disasters or pandemics. In contrast to clustering on a static set of data, streaming data clustering does not have a global view of the complete data. The local (or partial) view in a high-speed stream makes clustering a challenging task. In this paper, we propose a novel density peak based algorithm, <monospace>TStream</monospace>, for tracking the evolution of clusters and outliers in social media streams, via the evolutionary actions of cluster adjustment, emergence, disappearance, split, and merge. <monospace>TStream</monospace> is based on a temporal decay model and text stream summarisation. The decay model captures the decreasing importance of textual documents over time. The stream summarisation compactly represents them with the help of cells (aka micro-clusters) in the memory. We also propose a novel efficient index called shared dependency tree (aka SD-Tree) based on the ideas of density peak and shared dependency. It maintains the dynamic dependency relationships in <monospace>TStream</monospace> and thereby improves the overall efficiency. We conduct extensive experiments on five real datasets. <monospace>TStream</monospace> outperforms the existing state-of-the-art solutions based on <monospace>MStream</monospace>, <monospace>MStreamF</monospace>, <monospace>EDMStream</monospace>, <monospace>OSGM</monospace>, and <monospace>EStream</monospace>, in terms of cluster mapping measure (CMM) by up to 17.8%, 18.6%, 6.9%, 16.4%, and 20.1%, respectively. It is also significantly more efficient than <monospace>MStream</monospace>, <monospace>MStreamF</monospace>, <monospace>OSGM</monospace>, and <monospace>EStream</monospace>, in terms of response time and throughput. IEEE

Fast Mining and Forecasting of Co-evolving Epidemiological Data Streams

Given a large, semi-infinite collection of co-evolving epidemiological data containing the daily counts of cases/deaths/recovered in multiple locations, how can we incrementally monitor current dynamical patterns and forecast future behavior? The world faces the rapid spread of infectious diseases such as SARS-CoV-2 (COVID-19), where a crucial goal is to predict potential future outbreaks and pandemics, as quickly as possible, using available data collected throughout the world. In this paper, we propose a new streaming algorithm, EPICAST, which is able to model, understand and forecast dynamical patterns in large co-evolving epidemiological data streams. Our proposed method is designed as a dynamic and flexible system, and is based on a unified non-linear differential equation. Our method has the following properties: (a) Effective: it operates on large co-evolving epidemiological data streams, and captures important world-wide trends, as well as location-specific patterns. It also performs real-time and long-term forecasting;(b) Adaptive: it incrementally monitors current dynamical patterns, and also identifies any abrupt changes in streams;(c) Scalable: our algorithm does not depend on data size, and thus is applicable to very large data streams. In extensive experiments on real datasets, we demonstrate that EPICAST outperforms the best existing state-of-the-art methods as regards accuracy and execution speed. © 2022 ACM.