This paper focuses on the problem of 5G network cell planning. In addition, it presents an example of a rough estimation of the required number of cells or base stations in a certain area for arbitrary number of users who are provided with a certain bandwidth per user within these cells. The cell number estimation is the initial step and the essence of planning and implementation of 5G network in an area. It is helpful for the operators to create and take into the account business plans in order to fully implement the network as a function of number of users which have to be served. Considering that, knowing the rough number of 5G base stations per user is very important for pre-sale activities and eventually necessity for widening of the initial investments. Therefore, the paper presents four scenarios that include different network parameters. Depending on the network parameters, the required number of base stations in a certain area changes. Given scenarios are examples of one 5G network in virtual area per bandwidth per user.

Cancer is the leading disease in the world by the increasing number of new patients and deaths every year. Hence, it is the most feared disease of our time. It is believed that lung cancer and breast cancer are most common types of cancer and they both are subtypes of the same group of cancer – carcinoma. With this type of cancer early detection is of great importance for patient survival. As it is the disease that has unfortunately been around for many years, today we have datasets with all necessary information for diagnosing and predicting cancer. Predicting cancer means deciding if the cancer is malignant or benign. The key to this answer lays in different values of parameters that have been stored when the disease was discovered. Machine learning plays the crucial role in predicting cancer, given the fact that algorithms such as Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF) and etc. are designed to find the pattern that occurs in large sets of data and based on that make a decision. In this paper, author's goal is to see how machine learning and its practical implementation on public datasets can help with early breast cancer diagnosis and hopefully help save more lives.

This paper presents a model push on which to determine the flow rates vehicles per share on the basis of circular intersections recorded entries and exits of vehicles in the aisles. In addition it is possible to analyze the influence of individual flows at intersections capacity, and determine the number of vehicles at the intersection of routes in the knowledge of the number of vehicles leaving the intersection at the next exit. Count the number of vehicles it is easier to manually and by using new technologies. Model (MIKR) results in a longer or shorter period of time which gives both static and dynamic characteristics.

The trend of continuous increase for mobility requirements results in a progressive increase in the use of vehicles of all modes of transport, which contributes to a significant increase in noise levels, especially in urban areas. The most significant noise in urban areas is traffic noise, where road traffic contributes the most. This paper reviews the treatment of road traffic noise in the European Union with a focus on Directive 2002/49 / EC. The paper presents the basics of the mechanisms of the institutional and management framework in the field of road traffic noise monitoring in EU countries. Also, the results of road traffic noise monitoring in EU countries, indicators of population exposure to road traffic noise, as well as indicators of the impact of road traffic noise on the health of the population, were presented.

Information-Communication Technologies (ICTs) are currently used in various fields and there are many amazing inventions that are already present and make communication and life easier for us on a daily basis. The use of ICTs is less represented in the social work institutions. Therefore, this paper presents the implementation of ICTs through the chatbot application for the needs of social work created on the Tidio platform and within the webpage of the Public Institution “Center for Social Work Tešanj”. The application facilitates the work of social workers in collecting information from the users and eases the aid received by the users of social care in terms of faster responses to inquiries during emergencies, such as the COVID-19 pandemic, but also after. For the purpose of this research, an end-user survey was created and conducted with the aim of collecting user opinions on the acceptance and motivation for the use of chatbots in social work institutions. The results showed good acceptance and usage motivation of social work chatbot.

New technologies primarily affect the lives of all people, their habits, needs, desires, but also significantly affect the demands placed on various business sectors. Discussions on the increasingly rapid development of technical-technological solutions that can be applied in the postal sector and logistics have a long history. New technologies in all areas bring a constant change in the relationship between companies and their customers, which significantly affect the quality of work and activities. In the years to come, it will be an increasing challenge for postal operators around the world, as well as for other companies, to achieve substantive communication and understanding of their customers through the application of innovative technologies. Understanding and learning about customer issues is key to offering them services that, with their precise targeting of stakeholders, quality, visibility, efficiency, and, perhaps most importantly, flexibility, will be able to meet needs that change so quickly over time. This will be possible with new technologies and innovative solutions. The paper presents a market research on the potential use of autonomous vehicles and drones in the postal sector in Bosnia and Herzegovina. The research is based on a survey questionnaire on the use of drones and autonomous vehicles in the postal sector in the segment of shipment delivery.

Com a ascensão do comércio eletrônico em todo o mercado mundial, empresas e lojas físicas desenvolveram plataformas de vendas online para acompanhar a evolução digital e adentrar nesse novo âmbito concorrencial. Baseado nisso, o presente estudo implementou o programa 5S em operações de uma empresa de e-commerce com o objetivo de verificar a possibilidade de eliminação de desperdícios, redução de custos e otimização de seu desempenho operacional, visando garantir vantagem competitiva nesse meio. Para aplicação prática do programa, primeiramente foi feita uma visita especulativa sem aviso prévio à empresa, a fim de analisar a situação inicial do ambiente de trabalho e registrá-la por meio de fotografias e da classificação de um primeiro checklist por dois avaliadores. Além disso, foi medido o tempo de ciclo (separação no estoque, faturamento, embalagem e expedição) de um pedido para três funcionários, previamente à implementação do 5S. Posteriormente, foi então feita a aplicação da ferramenta no setor estudado através de técnicas requeridas para este fim, descritas na literatura e agrupadas em cinco sensos. De modo a garantir a constância destes sensos, o ciclo PDCA também foi utilizado. Para análise dos resultados, foi aplicado um segundo checklist pelos mesmos avaliadores e o tempo de ciclo pós modificações foi cronometrado para os mesmos funcionários e pedido. Houve um aumento de 38,4% na média de pontos dada pelos avaliadores no segundo checklist, com a categorização do ambiente de trabalho passando de “substancial” (préimplementação) para “ótima” (pós-implementação). O tempo de ciclo foi otimizado em 74,1% (pós-implementação). Portanto, a aplicação da ferramenta 5S nos processos de operação logística da empresa de ecommerce estudada, supervisionada pelo ciclo PDCA, otimizou a condição e o desempenho operacional do seu ambiente de trabalho.

Limited knowledge exists about the effects of commonly used diuretic medications on the human normal flora. Thus, we investigated potential stimulatory effects of diuretic drug furosemide on urogenital tract microbiota in women. Three strains of E. coli and C. albicans with different biofilm forming capacities were obtained from female patients diagnosed with urinary tract infections. All tested strains were treated with two different concentrations of furosemide drug, in comparison to non-treated strains as the negative control. At specific time intervals, samples were obtained from growing culture and analyzed for their proliferation rate, aspartyl proteinase excretion and biofilm formation ability. E. coli and C. albicans strains significantly increased their aspartyl proteinase excretion under furosemide treatment. This effect was frequently observed after 16 hours of incubation at 37oC. This drug has also increased the biofilm forming capacities of E. coli and C. albicans strains. Interestingly, both E. coli and C. albicans non-biofilm former strains, gained the capacity of biofilm formation when treated with furosemide at certain concentrations. E. coli control became a weak biofilm former after 48 hours of incubation, while non-biofilm former C. albicans strain became a weak biofilm former in dose-dependent fashion, after 48 hours incubation with furosemide in concentration of 0.1 mg/mL, and after 16 hours of incubation with furosemide in concentration of 0.5 mg/mL. Loop diuretic drug furosemide is able to increase the microbial virulence and turn commensal microbes into opportunistic pathogens. Additionally, the results suggest that enzyme aspartyl proteinase might act as a signal molecule for the biofilm formation, leading to the increased microbial pathogenicity.

Routing in multidomain and multilayer networks is the subject of constant theoretical research, with special emphasis on routing optimization algorithms based on several criteria. Such research results in new proposals. The basic task of the algorithm is to perform the given task in a finite and reasonable period of time and with reasonable resource requirements. When new solutions are compared with previous solutions, it is necessary to consider as much information as possible about the characteristics and differences between these algorithms, which ultimately determines the degree of success of the algorithm. Routing algorithms depend on the goals to be achieved and most often solve a certain group of problems with certain simplifications of the overall problem and to the detriment of performance that are not crucial for a given routing optimization problem. Therefore, it is necessary to have acceptable methods for efficiency-complexity evaluation methods of routing algorithms with certain, universally applicable, metrics. Several theoretical approaches, including graph theory, optimization theory, complexity theory, allow approaches to compare the algorithms and the results achieved with the help of these algorithms.

Data with censoring is common in many areas of science and the associated statistical models are generally estimated with the method of maximum likelihood combined with a model selection criterion such as Akaike’s information criterion. This manuscript demonstrates how the information theoretic minimum message length principle can be used to estimate statistical models in the presence of type I random and fixed censoring data. The exponential distribution with fixed and random censoring is used as an example to demonstrate the process where we observe that the minimum message length estimate of mean survival time has some advantages over the standard maximum likelihood estimate.

Microbiomes are typically characterised by high species diversity but it is poorly understood how such system-level complexity can be generated and propagated. Here, we used soils as a relevant model to study microbiome development. Despite inherent stochastic variation in manipulating species-rich communities, both laboratory-mixed medium complexity (21 soil bacterial isolates in equal proportions) and high-diversity natural top-soil communities followed highly reproducible succession paths, maintaining distinct soil microbiome signatures. Development trajectories and compositional states were different for communities propagated in soils than in liquid suspension. Microbiome states were maintained over multiple renewed growth cycles but could be diverged by short-term pollutant exposure. The different but robust trajectories demonstrated that deterministic taxa-inherent characteristics underlie reproducible development and self-organized complexity of soil microbiomes within their environmental boundary conditions. Our findings also have direct implications for potential strategies to achieve controlled restoration of desertified land. TEASER Species-rich soil microbiomes grow and propagate reproducibly despite inherent stochastic complexity, paving the way for soil restoration.

Even though water-related forest ecosystem services are important for forestry and water management sectors, they have different definitions and are regulated differently in each sector, which makes them poorly recognized. How stakeholders from two main sectors (forestry and water management) perceive the importance of water-related forest ecosystem services, the trade-offs between ecosystem services and the effectiveness and implementation of payments schemes related to forest water ecosystem services were our areas of interest. We have conduct surveys with different groups of stakeholders from both sectors in four selected countries (the Federation of Bosnia and Herzegovina, Croatia, Slovenia and Serbia) with a lot of similarities and the potential to learn from each other. The results show that in spite of the spotted differences among analyzed countries, there is a high level of agreement among respondents on all investigated aspects. In addition, even though different payment schemes exist in three of four countries, stakeholders are rarely aware of their existence, or it is better to say that they do not recognize them as payment schemes for ecosystem services because of their names and definitions, which do not clearly define ecosystem services. Mostly, they use bundled services and non-voluntary payments and are designed and implemented by the states. Due to the strong role of states and the low transparency in the existing schemes, we looked at possible conditions reflected through stakeholders’ opinions for overcoming that obstacle for the development of new payment schemes. We found that there is a high level of acceptance of payments schemes as more effective than “command and control” schemes and of the involvement of other stakeholders in decision-making processes as those conditions that can positively influence development of new payment schemes in all four countries. These results give us hope that in spite of the strong role of the state in selected countries, the role of stakeholders will be more acknowledged and, by that, the future schemes will be more harmonized among the sectors and their goals and needs, contributing to its effectiveness as well.

Background Sustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended—SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. Methods Research was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx— Microsoft Research’s Bayesian Network Authoring and Evaluation Tool . Results Due to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks. Conclusion Testing of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks.

Introduction: Electromagnetic imaging is an emerging technology which promises to provide a mobile, and rapid neuroimaging modality for pre-hospital and bedside evaluation of stroke patients based on the dielectric properties of the tissue. It is now possible due to technological advancements in materials, antennae design and manufacture, rapid portable computing power and network analyses and development of processing algorithms for image reconstruction. The purpose of this report is to introduce images from a novel, portable electromagnetic scanner being trialed for bedside and mobile imaging of ischaemic and haemorrhagic stroke. Methods: A prospective convenience study enrolled patients (January 2020 to August 2020) with known stroke to have brain electromagnetic imaging, in addition to usual imaging and medical care. The images are obtained by processing signals from encircling transceiver antennae which emit and detect low energy signals in the microwave frequency spectrum between 0.5 and 2.0 GHz. The purpose of the study was to refine the imaging algorithms. Results: Examples are presented of haemorrhagic and ischaemic stroke and comparison is made with CT, perfusion and MRI T2 FAIR sequence images. Conclusion: Due to speed of imaging, size and mobility of the device and negligible environmental risks, development of electromagnetic scanning scanner provides a promising additional modality for mobile and bedside neuroimaging.