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The objective is to detect Novel Social Distancing using Local Binary Pattern (LBP) in comparison with Principal Component Analysis (PCA). Social Distance deduction is performed using Local Binary Pattern(N=20) and Principal Component Analysis(N=20) algorithms. Google AI open Images dataset is used for image detection. Dataset contains more than 10,000 images. Accuracy of Principal Component Analysis is 89.8% and Local Binary Pattern is 93.9%. There exists a statistical significant difference between LBP and PCA with (p<0.05). Local Binary Pattern appears to perform significantly better than Principal Component Analysis for Social Distancing Detection. © 2023 Author(s).
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At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.
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Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the process of classifying reviews many researchers have adopted machine learning approaches. Keeping in view, the rising demand for educational applications, especially during COVID-19, this research aims to automate Android application education reviews' classification and sentiment analysis using natural language processing and machine learning techniques. A baseline corpus comprising 13,000 records has been built by collecting reviews of more than 20 educational applications. The reviews were then manually labelled with respect to sentiment and issue types mentioned in each review. User reviews are classified into eight categories and various machine learning algorithms are applied to classify users' sentiments and issues of applications. The results demonstrate that our proposed framework achieved an accuracy of 97% for sentiment identification and an accuracy of 94% in classifying the most significant issues. Moreover, the interpretability of the model is verified by using the explainable artificial intelligence technique of local interpretable model-agnostic explanations. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) to distribute post-disaster relief more reasonably. Unlike general route optimizations, patients' suffering is taken into account in the model, allowing patients in more urgent situations to receive relief operations first. A new metaheuristic algorithm, the hybrid brain storm optimization (HBSO) algorithm, is proposed to deal with the model. The hybrid algorithm adds the ideas of the simulated annealing (SA) algorithm and large neighborhood search (LNS) algorithm into the BSO algorithm, improving its ability to escape from the local optimum trap and speeding up the convergence. In simulation experiments, the BSO algorithm, BSO+LNS algorithm (combining the BSO with the LNS), and HBSO algorithm (combining the BSO with the LNS and SA) are compared. The results of simulation experiments show the following: (1) The HBSO algorithm outperforms its rivals, obtaining a smaller total cost and providing a more stable ability to discover the best solution for the ERRP;(2) the ERRP model can greatly reduce the level of patient suffering and can prioritize patients in more urgent situations.
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Following the elaboration of a Tunnel Safety Documentation for the T4 tunnel, several deviations from the European and national Standards were identified. Moreover, due the tunnels' special characteristics and its ageing equipment, the rehabilitation plan had not only to upgrade the level of safety to "Category A” as per the ADR agreement, but also to perform heavy maintenance works and provide sustainable solutions for the tunnel operations and the local community. The construction methodology poses significant challenges in the operation and the construction. Therefore, special provisions, technical and operational, were required in order for the transport of heavy and dangerous goods vehicles to be allowed in the tunnel during construction. The Covid pandemic and the geopolitical conditions (Ukraine war), seem to negatively affect the projects' duration and financing. With a budget of more than €20M, it is the first tunnel upgrade project of this magnitude and complexity in Greece, that sets the basis as refence for future tunnel upgrades. © 2023 The Author(s).
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PurposeFood festivals are prevalent for those passionate about food experience globally. More importantly, feedback from food reviewers on mass media platforms has been becoming a critical factor in facilitating the decision-making process of tourists in particular cities. Moreover, stimulating local tourism activities, thanks to food festivals, prove advantageous to the well-being of local habitants. The purpose of this paper is to provide readers with a general overview of food festival research trends in tourist cities, as tourism has the potential to contribute to targets in Goals 8, 12 and 14 on sustainable consumption and production and the sustainable use of resources, respectively, (UNWTO: World Tourism Organization).Design/methodology/approachThis study searched and filtered documents from the Scopus and Web of Science databases, as well as used bibliometric analysis and other mathematical and statistical methods, to better understand the food festival research context between 1970 and 2021. The carriers with mathematical and statistical methods. VOSviewer algorithm was used to identify critical input for visualizing bibliometric networks and to create a framework for this academic food festival research.FindingsThe findings are primarily related to pre and post-COVID-19 research on food festivals worldwide. Furthermore, using an inductive approach, this paper reveals the impact of food festivals in cities and tourist behaviors. According to the findings, the food festival research trends are about "food festivals,” "slow food festivals” and "local food festivals.” Factor analysis is one of the most common analyses in this type of research. Other studies could use the findings and limitations to select appropriate themes and analysis approaches for their research topics.Research limitations/implicationsResearch data sets are mainly from articles that may not account for all actual trends during this pandemic.Originality/valueThis review expects to provide insights into food festivals and help future researchers to recognize several research gaps such as the lack of research on food festival manufacturers and producers or the consistency in visitors' aspect research of quality service, visitors' loyal intentions, satisfaction and culinary experience. The tourism industry can find research trends of food festivals and issues following COVID-19 to find their management styles to fit the context of the post-COVID-19 pandemic, facilitating organizing a safe and effective food festival.
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While the rationale for localizing humanitarian health response is well established at the level of policy rhetoric, the operationalization of the concept and its mainstreaming into concrete practice still require clearer intentionality. With COVID-19 pushing more people further into vulnerability, placing local communities at the heart of humanitarian and development health efforts has never been more urgent. Focusing on Jordan, this essay brings attention to the significant toll of violence against women and girls in conflict-affected communities and the importance of empowering local actors with community knowledge and resources to prevent and respond to gender-based violence. The essay follows on from the research conducted for CARE Jordan's She Is a Humanitarian report (2022) and draws on interviews I conducted with the heads of women's organizations in the summer of 2022. The essay explores the role of local women humanitarian actors as frontline responders, the challenges that hinder their role, and the advantages such actors enjoy, which, if harnessed, can achieve gains in accountability, health service quality, and gender equality.
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The COVID-19 pandemic, together with other shocks, have exposed the vulnerability and risk of local, national and global food systems and are threatening the attainment of Sustainable Development Goals (SDGs) especially SDG 2 - to end hunger, achieve food security and improved nutrition and promote sustainable agriculture. However, the scientific evidence is relatively thin on how local food systems can cope with the COVID-19 pandemic and other shocks. The aim of this chapter is to draw lessons from Zimbabwe on how local food systems can be strengthened to cope with COVID-19 pandemic and other shocks. To this end, an online survey was conducted with 46 people with purposively sampled participants representing development partners, academia, research organisations, civil society organisations, think tanks and the private sector. Key informant interviews (KIIs) (15 in total) with a subset of them complemented the survey. The study used descriptive statistics to analyse quantitative data, while qualitative data was analysed thematically. The majority of respondents agreed that it is important to formulate policies and programmes that focus on building resilience of local food systems to withstand shocks and emergencies like the COVID-19 pandemic. Promoting local food production, building resilience of local communities, shortening food supply chains and designing effective social protection programmes are some of the important factors that were highlighted as being essential in strengthening local food systems to respond to shocks. The study concludes that adequate budgetary support and capacitating the local people to deal with and recover from shocks are also key ingredients in supporting the local food systems during COVID-19 pandemic and other shocks. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
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COVID-19 is caused by the novel coronavirus SARS-CoV-2. First started in Wuhan, COVID-19 has spread everywhere, including Indonesia. COVID-19 can cause severe pneumonia, severe acute respiratory distress syndrome (ARDS) symptoms, and multiple organ failure. According to the WHO, COVID-19 generally has an incubation period of 5-6 days, ranging from 1 to 14 days. However, in Jakarta, the cases have decreased significantly since the implementation of PPKM (Restrictions of Activity), running since early July 2021. The government claimed that the PPKM rule has significantly impacted COVID-19 cases, decreasing every day, especially in Jawa-Bali Region. In addition, the Vaccination rate in Indonesia also played a significant part in decreasing COVID-19 cases, with Jakarta currently standing with 9 million people fully vaccinated per December 2021. To monitor the development of COVID-19 in Jakarta and provide information to the public about health facilities, especially hospitals in Jakarta, in this study, the distribution area of COVID-19 cases will be mapped with CHIME using ArcGIS Online tools. The analysis results obtained based on the mapping results that most cases were in the Cengkareng area, and the area with the most hospitals werein East Jakarta. © 2022 IEEE.
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Objectives: We present a case report of medical intensivist driven ECMO program using ECMO as a pre-procedural tool to maintain oxygenation in a patient with critical tracheal stenosis during tracheostomy placement. Method(s): VV ECMO is primarily used to support patients when mechanical ventilation is unable to provide adequate gas exchange. Alternatively, it has been used pre-procedurally when intubation is required in anticipation of a difficult airway. Described here is the first intensivist preformed awake VV ECMO cannulation to facilitate tracheostomy in a patient with severe tracheal stenosis. Result(s): The patient is a 41-year-old female with the relevant background of COVID19 pneumonia status post tracheostomy and subsequently decannulated after prolonged intubation and ICU stay. As a result, the patient developed symptomatic tracheal stenosis and presented two years after her ICU stay for scheduled bronchoscopy and balloon dilation. However, the patient developed worsening stridor and shortness of breath requiring heliox and BPAP. After multidisciplinary discussion between the critical care team ENT teams, the decision was made to cannulate for VV ECMO as a pre-procedural maneuver to allow for oxygenation during open tracheostomy in the OR. Dexmedetomidine and local anesthesia were used for the procedure with the patient sitting at 30 degrees on non-invasive ventilation and heliox. The patient was cannulated with a 21F right internal jugular return cannula and 25F right common femoral drainage cannula by medical intensivists in the intensive care unit using ultrasound guidance. The patient went for operative tracheostomy the next day and was subsequently decannulated from ECMO the following day without complication. She was discharged home on trach collar. Conclusion(s): Intensivist performed ECMO cannulation has been shown to be safe and effective. We anticipate the indications and use will continue to expand. This case is an example that intensivist driven preprocedural ECMO is a viable extension of that practice.
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This paper investigates the dynamics and drivers of informational inefficiency in the Bitcoin futures market. To quantify the adaptive pattern of informational inefficiency, we leverage two groups of statistics which measure long memory and fractal dimension to construct a global-local market inefficiency index. Our findings validate the adaptive market hypothesis, and the global and local inefficiency exhibits different patterns and contributions. Regarding the driving factors of the time-varying inefficiency, our results suggest that trading activity of retailers (hedgers) increases (decreases) informational inefficiency. Compared to hedgers and retailers, the role played by speculators is more likely to be affected by the COVID-19 crisis. Extremely bullish and bearish investor sentiment has more significant impact on the local inefficiency. Arbitrage potential, funding liquidity, and the pandemic exert impacts on the global and local inefficiency differently. No significant evidence is found for market liquidity and policy uncertainty related to cryptocurrency.
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The spread of teleworking, both in private companies and in the public administration, is one of the consequences of the struggle against the COVID-19 pandemic. However, teleworking is not really a new mode of carrying out public services. It was already a decade ago when teleworking was initially regulated in Spain and, since then, it is linked to the development of digital technologies in public administrations. In 2020 new basic state legislation on teleworking was passed for civil servants. This legislation was developed by regional and local regulations and agreements. This article presents a summary of the current legal framework on the matter. © 2022, Fundacion Democracia y Gobierno Local. All rights reserved.
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Based on the content analysis of the websites of 102 Spanish municipalities related to actions aligned with the 2030 Agenda and the Sustainable Development Goals (SDGs), the X-STATIS technique was applied to analyze the status and dynamic evolution of commitment to the SDGs in regional and local governments over the period of 2016-2021. The results show a low but increasing level of SDG commitment, which also varies significantly across municipalities and regions, as well as by SDGs, which can be attributed to the influence of several sociodemographic factors, such as the number of inhabitants, dependent population and population density. SDG8 and SDG11 stand out as the main priorities of the municipalities, while initiatives related to SDG5, SDG6 and SDG 17 are the least prioritized. The COVID-19 pandemic has marked a turning point in this regard, with greater importance being given to the SDGs more related to people and prosperity. Our findings help citizens and public authorities to understand sustainable regions and municipalities, assess their performance in relation to different dimensions of sustainability and identify key challenges for future improvements. Specifically, the results suggest that public policies should promote actions related to gender equality, drinking water and sanitation and partnerships, as well as favor investment in the regions and municipalities that are lagging behind, in order to improve their level of commitment to the 2030 Agenda and reduce inequalities. From an academic point of view, our results open a door for the analysis of possible trajectories in the implementation of the SDGs at regional and local levels and the study of their determinants. © 2023 the Author(s), licensee AIMS Press.
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Basic local alignment search tool (BLAST) is one of the popular sequence similarity analysis tools. However, some students and researchers just blindly use the default parameters. Moreover, some students are confused about how to choose the right program. In a word, it is prone to be misused and researchers often draw conclusions incorrectly. In view of this, we traced back the internet hot topic in early 2020 - "MORDERATELY STRONG CONFIRMATION OF A LABORATORY ORIGIN OF COVID-19", and took it as teaching materials to guide the student to use BLAST currently through reanalyzing and reproducing the source of errors. Then we arranged an interesting experiment about fabricating dinosaur genes through modifying a chicken gene. In the experimental design to make the students grasp the BLAST tools better, one group fabricated the dinosaur gene and the other group decrypted the added bases. This instructional design could be conducive to cultivate students ' ability about distinguishing different viewpoints correctly, and we hope it can be enlightening and helpful to the teaching of BLAST tools.Copyright © 2022 by the authors.
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Until recent decades, labour-intensive subsistence farming was a way of life and livelihood in the hill communities of Uttarakhand, India. However, the nature of agriculture falls far short of the expectations of the main labour force, the rural youth, leading to their mass migration to non-agricultural occupations. The large-scale youth migration has left many hill farming landscapes depopulated and farmlands abandoned. As youth have special stakes in food systems, they must be included in the sustainable transformation of food systems. By doing so, the migration-prone hill region may be transformed into a place where rural youth have more options for work and income. Therefore, the agriculture sector needs to change and develop into a more engaging and youthful workplace. There are opportunities to explore and barriers to be removed. Besides identifying priority research areas on local food systems, in this exploratory research, we investigate opportunities to involve rural young people in the transformation of the food system. We document information by conducting focus group discussion (FGD) meetings in about 100 villages in the Uttarakhand hills, representing all major farming landscapes. This study mainly focuses on improving the production and consumption aspects of local food, which not only benefits the health and wellbeing of local communities but also has many positive economic, social, and environmental effects. In addition, we explore opportunities for reviving mountain agriculture through agri-ecotourism, which is a symbiotic relationship between tourism and agriculture. Making home- or farm stays in agri-ecotourism a subsistence strategy for local youth will contribute to a more prosperous rural economy. Recognising Uttarakhand's rich culture and heritage while exploring the culinary travel opportunities in homestays will provide opportunities to focus more on traditional food systems, exposing various tangible and intangible aspects of the host region's food culture to tourists. The findings of this study will aid in identifying specific policy issues for consideration by planners and policymakers at the local and state levels. Additionally, this exploratory study will assist young, motivated researchers in conducting follow-up, in-depth investigations and producing empirical data in their specialised fields.
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The Covid-19 pandemic and Brexit have focused attention on the resilience of key sectors and firms. This paper explores the financial resilience of the 50 largest automotive firms in the West Midlands region of the UK in their response to disruption and economic shocks. The findings demonstrate that 22 firms are at high risk due to poor current liquidity ratios, with Coventry and Birmingham emerging as locations most susceptible to firm closures. High-risk firms include key flagship original equipment manufacturers operating at the downstream end of supply chains. If these firms were to fail, there would be a significant destructive impact on both the industry and the local economy. We assert an effective subnational industrial policy is required in order to support economic resilience in regions such as the West Midlands where a few firms account for a disproportionate share of employment and value-added.
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Automated face recognition is a widely adopted machine learning technology for contactless identification of people in various processes such as automated border control, secure login to electronic devices, community surveillance, tracking school attendance, workplace clock in and clock out. Using face masks have become crucial in our daily life with the recent world-wide COVID-19 pandemic. The use of face masks causes the performance of conventional face recognition technologies to degrade considerably. The effect of mask-wearing in face recognition is yet an understudied issue. In this paper, we address this issue by evaluating the performance of a number of face recognition models which are tested by identifying masked and unmasked face images. We use six conventional machine learning algorithms, which are SVC, KNN, LDA, DT, LR and NB, to find out the ones which perform best, besides the ones which poorly perform, in the presence of masked face images. Local Binary Pattern (LBP) is utilized as the feature extraction operator. We generated and used synthesized masked face images. We prepared unmasked, masked, and half-masked training datasets and evaluated the face recognition performance against both masked and unmasked images to present a broad view of this crucial problem. We believe that our study is unique in elaborating the mask-aware facial recognition with almost all possible scenarios including half_masked-to-masked and half_masked-to-unmasked besides evaluating a larger number of conventional machine learning algorithms compared the other studies in the literature. © 2023 IEEE.
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Permissibility of repeal or amend participatory (civil) budget resolution can become a real problem during the COVID-19 pandemic (or during other crisis-like periods). On the one hand, that kind of action can undermine members of the local community trust in local authorities. On the other hand, the issue discloses a conflict between the essential values of local government. © 2022, Jagiellonian University. All rights reserved.
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This paper explores relationships between vaccination coverage and indicators at the level oflocal administrative units for the case of rural localities of Romania. Positive correlations have been identified in relation to fiscal capacity, coverage of the population with general practitioners, COVID‐19 incidence rate and absence of a marginalized community within the locality. Regional differences are again highlighted in the analysis. This means that there is at least partially an overlap of the disadvantaged rural areas with the ones registering low vaccination uptakes against COVID‐19. Further on, it means that these territorial areas accumulate a series of structural disadvantages that can prove to increase the discrepancies between them and other rural or large urban areas. The paper contributes to enlarging the perspective on vaccination coverage by adding both conceptual and practical insights. From the point ofview of practitioners, the results of the study can be used to tailor intervention in communities with similar characteristics, to underscore public health inequalities across territories. Points for practitioners are relevant for a wide range of stakeholders from public health, public management, and social protection fields, placed in both local and central level decision‐making positions. [ FROM AUTHOR] Copyright of NISPAcee Journal of Public Administration & Policy is the property of Sciendo 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.)
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The commercial strategies of the small businesses of Alajuela Street in the Portoviejo Canton of Manabí in Ecuador in times of COVID-19 have had different impacts. This article seeks to explore and disseminate the main business strategies of SMEs in Latin America and their impacts of these business strategies on small business sales. A case study is proposed from one of the cantons of Ecuador. To carry out the research, the consultation of specialized bibliography, the survey, direct observation and statistical processing are used. As main re-sults, it is obtained that in 99% of the cases, the merchants who applied online marketing strategies in periods of Covid-19 had a positive impact on their income, a behavior similar to that of studies in the Latin American field. 74% of those surveyed decided to keep offering the same kind of item or product during the pandemic and 18% decided to switch products to food. 94.1% of businesses were affected by COVID-19. © 2023, University of Cienfuegos, Carlos Rafael Rodriguez. All rights reserved.