Content analyses of the international federation of red cross and red crescent societies (ifrc) based on machine learning techniques through twitter

Intensity of natural disasters has substantially increased; disaster management has gained importance along with this reason. In addition, social media has become an integral part of disaster management. Before, during and after disasters; people use social media and large number of output is obtained through social media activities. In this regard, Twitter is the most popular social media tool as micro blogging. Twitter has also become significant in complex disaster environment for coordinating events. It provides a swift way to collect crowd-sourced information. So, how do humanitarian organizations use Twitter platform? Humanitarian organizations utilize resources and related information while managing disasters. The effective use of social media by humanitarian agencies causes increased peoples’ awareness. The international federation of red cross and Red Crescent Societies (IFRC) is the most significant humanitarian organization that aims providing assistance to people. Thus, the aim of this paper is to analyze IFRC’s activities on Twitter and propose a perspective in the light of theoretical framework. Approximately, 5201 tweets are passed the pre-processing level, some important topics are extracted utilizing word labeling, latent dirichlet allocation (LDA model) and bag of Ngram model and sentiment analysis is applied based on machine learning classification algorithms including Naïve Bayes, support vector machine SVM), decision tree, random forest, neural network and k-nearest neighbor (kNN) classifications. According to the classification accuracies, results demonstrate the superiority of support vector machine among other classification algorithms. This study shows us how IFRC uses Twitter and which topics IFRC emphasizes more. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature

Social network analysis of tourism data: A case study of quarantine decisions in COVID-19 pandemic

Tourism is one of the most affected sector during the COVID-19 pandemic all over the world. Quarantine decisions are the leading measures taken in practice to reduce possible negative consequences of the COVID-19 pandemic. There is limited work in the literature on how to make the right quarantine decisions in a pandemic. Therefore, the aim of this study is to propose the use of social network analysis (SNA) based on tourism data to make the right quarantine decisions in the COVID-19 pandemic. A case study on quarantine decision is conducted based on data obtained from Turkish Statistical Institute to show how to perform SNA. Household domestic tourism survey is used as input data for SNA. The most critical region among 12 regions in Türkiye is Istanbul to decrease possible negative affect of COVID-19 pandemic on the tourism sector. © 2022 The Author

Development of a decision support system for solving container loading problems

The globalization of supply chains and rising fuel costs are forcing container carriers both to minimize the number of trips and to maximize available container space. This makes container loading (CL) a critical process especially in real‐life applications. Container loading (CL), which is a difficult problem to be solved, has many applications in container transportation and distribution industries. This article presents a container loading support system (CLSS). The proposed CLSS composes of three main components, including a hybrid Bees Algorithm as the main computational algorithm, the graphical user interface (GUI) and a simulation program. The aim of the designed system is to make the packing pattern more visible to the user in order to simplify the loading process. An illustrative example ‐a CL problem from literature ‐ is also provided to introduce the operation of the system and to prove its efficiency. First published online: 24 Jun 201

Improvement of manufacturing productivity and responsiveness through integrated process planning and authorizing

Autoriziranje se može opisati kao signal u okviru sustava koji određuje može li neki posao započeti ili ne. Dok se u push sustavima započimanje poslova programira, u pull sustavima oni se autoriziraju budući da se proizvodni sustavi pull tipa upravljaju downstream informacijama. Tradicionalno se procesi planiranja i autoriziranja smatraju odvojenim zadacima koji se izvršavaju u slijedu te se autoriziranje izvršava nakon što su napravljeni planovi za odvijanje procesa. Imajući u vidu činjenicu da su njihove funkcije obično komplementarne, veća se proizvodnost i reaktivnost mogu postići kad se one integriraju. Iako radovi koji se bave planiranjem i programiranjem integriranih procesa (IPPS) postaju sve popularniji, koliko mi znamo, nema rada koji razmatra integraciju planiranja i autoriziranja procesa. Cilj je ovoga rada upozoriti na integraciju planiranja i autoriziranja procesa predstavljanjem novog modela nazvanog planiranje i autoriziranje integriranih procesa (IPPA). Prvi rezultati primjene IPPA pokazuju da je primjereno vršiti takvo integriranje te onda i stjecati prednosti kroz tu integraciju. Mala poduzeća (SMEs) naročito mogu imati koristi od IPPA zbog toga što on slabo ovisi od (profesionalne) softverske podrške.Authorizing can be described as an endogenous system signal that determines whether a job release is allowed or not. Whereas job releases are scheduled in push systems, they are authorized in pull systems since pull-type manufacturing systems are controlled by downstream information. Traditionally, process planning and authorizing are regarded as separate tasks performed sequentially, where authorizing is implemented after process plans have been generated. In view of the fact that their functions are usually complementary, higher productivity and responsiveness can be achieved when they are integrated. Although the studies related with integrated process planning & scheduling (IPPS) are increasingly popular, according to our best knowledge, there is no study researching the integration of process planning and authorizing. This study aims to call attention to the integration of process planning and authorizing through presenting a novel model that is called integrated process planning & authorizing (IPPA). Primary implementation results of IPPA demonstrate that making the integration and hence gaining advantage through integration are pertinent. SMEs can especially get in favour of IPPA because of its slight dependence on (professional) software support

An appeal to the global health community for a tripartite innovation: an ‘‘Essential Diagnostics List,’’ ‘‘Health in All Policies,’’ and ‘‘See-Through 21st Century Science and Ethics"

Diagnostics spanning a wide range of new biotechnologies, including proteomics, metabolomics, and nanotechnology, are emerging as companion tests to innovative medicines. In this Opinion, we present the rationale for promulgating an ‘‘Essential Diagnostics List.’’ Additionally, we explain the ways in which adopting a vision for ‘‘Health in All Policies’’ could link essential diagnostics with robust and timely societal outcomes such as sustainable development, human rights, gender parity, and alleviation of poverty. We do so in three ways. First, we propose the need for a new, ‘‘see through’’ taxonomy for knowledge-based innovation as we transition from the material industries (e.g., textiles, plastic, cement, glass) dominant in the 20th century to the anticipated knowledge industry of the 21st century. If knowledge is the currency of the present century, then it is sensible to adopt an approach that thoroughly examines scientific knowledge, starting with the production aims, methods, quality, distribution, access, and the ends it purports to serve. Second, we explain that this knowledge trajectory focus on innovation is crucial and applicable across all sectors, including public, private, or public–private partnerships, as it underscores the fact that scientific knowledge is a co-product of technology, human values, and social systems. By making the value systems embedded in scientific design and knowledge co-production transparent, we all stand to benefit from sustainable and transparent science. Third, we appeal to the global health community to consider the necessary qualities of good governance for 21st century organizations that will embark on developing essential diagnostics. These have importance not only for science and knowledge based innovation, but also for the ways in which we can build open, healthy, and peaceful civil societies today and for future generations

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Proseslerin bilgisayar ortamlarında modellenmesi, analizi ve seçimi

Bu makalede, günümüz üretim ve servis endüstrilerinin performanslarını artırmada modern bir yöntem olarak kabul edilen ve modern üretim yönetiminin vazgeçilmez bir aracı olma yolunda olan proses modelleme tekniği açıklanmakta ve tartışılmaktadır. Proses modelleme ile çözümlenmesi oldukça güç olan birçok endüstriyel probleme pratik çözümler üretmek mümkün olabilmektedir. Örneğin, bir üretim sistemine yeni teknoloji ürünü bir makina eklemek istendiğinde; bu yatırımın beklenen faydayı sağlayıp sağlayamayacağını, üretim hızının artıp artmayacağını ya da birim maliyetlerin düşüp düşmeyeceğini proses modelleme aracılığıyla kestirebilmek olasıdır. Yine, bir servis sisteminde yeni bir iş pratiği uygulanmak istendiğinde; yeni iş pratiği ile birlikte sistemin veriminin eskisinden daha iyi olup olmayacağının tespiti ve sağlanan faydanın düzeyi, sistemdeki darboğazlar, maliyeti en çok artıran ve/veya değer katmayan faaliyetlerin tespit edilmesi gibi kritik sorulara proses modelleme aracılığıyla cevap aranabilmekte ve hatta, alternatif proses zincirleri oluşturularak, sistem performansını en iyileyen çözüme yaklaşabilmektedir. Bunlara ek olarak, proses modelleme, ISO 9000 dokümanlarının hazırlanmasında, Toplam Kalite Yönetimi ve Yönetim Mühendisliği uygulamalarında ve maliyetlendirme çalışmalarında da kullanılabilen çok faydalı bir teknik olarak da karşımıza çıkmaktadır. Makalede, yukarıda bahsedilen ve benzeri konu ve sorulara proses modellemenin nasıl çözümler üretebileceği, bir örnek olay çalışması ile açıklanmaktadır. Ayrıca mevcut bazı proses modelleme yazılımlarının değerlendirilmesi yapılmakta ve bunlardan birinin kullanımı bir örnek ile tanıtılmaktadır.In this paper, the process modelling technique, which is accepted as a modern method for improving performance of production and service systems is explained and discussed. Process modelling is becoming an important tool in modern production management practice. The main reason behind this is that, it is possible to generate practical solutions to many complex problems using process modelling. For example; assume that it is required to add a new technology machine tool to the production system. Will this investment generate the expected utility? In other words, will production increase and unit costs decrease? Assume that it is required to apply a new working practice in the service system. Will the firm become more productive or what will be the benefit ratio? What are the bottlenecks in the system? What are the critical activities in terms of cost? What are the non-value adding activities? What will be the performance of a planned alternative process chain? It is possible to find answers to the questions like these in a short period of time by using the process modelling technique. In addition to these, process modelling is a valuable technique in preparing ISO 9000 documents, in applying Total Quality Management and Re-engineering practices, and in doing costing studies. In the paper, by the help of a case study it is presented how process modelling generates answers to the themes mentioned. Moreover, some of the available process-modelling tools are evaluated and SIMPROCESS is introduced in the paper