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.

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.

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.

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.

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.

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.

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.

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.

Thanks to the development of more powerful computers and efficient numerical techniques, numerical modelling has become a compulsory tool in solving various problems in the field of energetic materials. In cases where measuring techniques are still unable to measure a given parameter, numerical modelling may be the only option of obtaining a value. In addition, numerical modelling helps us to better understand some phenomena, particularly in understanding the influence of input parameters on output results, as well as saving time and money. The thermochemical equilibrium code EXPLO5 is such a tool which enables theoretical prediction of performance of high explosives, propellants and pyrotechnic compositions. The code is used by more than 80 research laboratories worldwide.

Tomato (Solanum lycopersicum L.), family Solanaceae, has become in the past fifty years one of the most important and extensively grown horticultural crops in the Mediterranean region and throughout the world. In 2019, more than 180 million tonnes of tomato have been produced worldwide, out of which around 42 million tonnes in Mediterranean countries. Due to its genetic properties, tomato is afflicted by numerous plant diseases induced by fungal, bacterial, phytoplasma, virus, and viroid pathogens. Not only is its genetic inheritance of great importance to the management of the numerous tomato pathogens, but equally as important are also the present climate changes, the recently revised phytopathological control measures, and the globalization of the seed industry. Thus, the recognition of symptoms and the knowledge of the distribution and spread of the disease and of the methods for early detection of the pathogens are the major prerequisites for a successful management of the disease. In this review, we will describe the main tomato pathogens in the Mediterranean area that impact mostly the tomato yield and provide the current and perspective measures necessary for their successful management.

Background Increasing urbanization as well as global warming requires an investigation of the influence of different construction methods and ground surfaces on the urban heat island effect (UHI effect). The extent of the influence of the urban structure, the building materials used and their surfaces on the UHI effect can be significantly reduced already in the planning phase using a designated OpenFOAM-based solver “uhiSolver”. Results In the first part of this research work, it is shown that inner building details and components can be neglected while still obtaining sufficiently accurate results. For this purpose, the building model was divided into two layers: a surface layer without mass, where the interaction with radiation takes place, and a component layer, which contains all relevant components and cavities of the building represented with mass-averaged material properties. It has become apparent that the three parameters—albedo, heat capacity and thermal resistance—which have a decisive influence on the interaction, have different effects on the component temperatures and the surface temperatures. In the second part of this research work, dynamic 3D computational fluid dynamics (CFD) simulations are performed with uhiSolver for a residential block in Vienna. Comparing the simulation results with measurement data collected on site, it is shown that the simplified assumption of homogeneous material data for building bodies provides very good results for the validation case investigated. However, the influence of the greening measures in the courtyard of the residential block on the air temperature is found to be negligible. Furthermore, it was observed that due to locally higher radiation density, lower air velocities and higher air humidity, the apparent temperature in the courtyard is sometimes perceived to be higher than in the adjacent streets, despite the lower air temperature. Conclusions Simplifying the modeling process of the uhiSolver software by reducing the model complexity helps to reduce manual work for setting up appropriate boundary conditions of buildings. Compared to market competitors, good results are obtained for the validation case Kandlgasse presented in this research work, despite the simplifications proposed. Thus, uhiSolver can be used as a robust analytical tool for urban planning.