With the development and implementation of the 5G systems worldwide, the shortages and imperfections that limit the functions and services of 5G networks were made apparent. This generation should enable its users to access unseen services and applications and a better quality of service in comparison to its predecessors. However, aside from the apparent importance of 6G networks, the possibilities, use cases, applications, and services that this technology would provide are yet to be explored. Our intention with this paper is to research the papers and compare the differences in requirements, capabilities, services, and use cases between 5G and 6G.

With modern technological progress and scientific achievements, companies are actively adjusting their business strategies in order to take advantage of new business opportunities and achieve maximum profit for their companies. One of the current changes in the field of marketing is the increasing emphasis on digital marketing. Digital channels, such as social networks, mobile applications and online advertising, are becoming essential tools for communication and engagement with target audiences. Mobile applications, m-commerce and other innovations allow consumers to easily buy products and access information about brands anytime, anywhere. This trend requires companies to be active on digital platforms and adapt to the mobile experience in order to achieve success in the market. In the decision-making process, it is important to have the best possible analysis so that the strategy is as good as possible. SWOT analysis of digital and traditional marketing through strengths, weaknesses, opportunities and threats gives clear facts about how marketing is developing in the modern market, especially in Bosnia and Herzegovina. This paper provides an analysis and comparison of digital and traditional marketing with the aim of understanding their strengths and weaknesses in the market of Bosnia and Herzegovina.

Software processes consist of a complex set of activities required to deliver software products within predicted quality, costs, and deadlines. To accomplish such goals, a software organization needs a quality and mature software process as a prerequisite for success. Adopting Software Capability Maturity Model Integration (CMMI) represents a well-known path in the pursuit of mature software processes. However, its implementation is a subject of a permanent effort that implies different approaches and methods, and often leads to unsuccessful or limited success, though. This is especially emphasized in small software companies given the dynamic environment influenced by different factors, including insufficient resources, changes in technology, and staff turnover. In this paper, a case study of a small software company implementing software process improvement is presented. In a tailored approach to process improvement, a specific method using the balanced scorecard as input into the IDEAL model has been designed, enabling a narrow link between business goals and specific improvement goals. The results show that the software process and selected performance indicators were improved, and suggest the potential of the proposed approach in small organizations.

Support channels represent a unique opportunity to improve customer satisfaction by offering a consistent experience in resolving customer issues. Several surveys show that customers have raised their standards of customer support services. While only a few years ago customers willingly waited a long time to speak with one of the service agents and were patient for their problem to be resolved, today’s customers have very limited patience and want a solution to the problem immediately. Customers don’t want to settle for a mediocre support channel experience. Support channels must provide superior service capacities so that customers see that the company values their choice and time. Efficient management of support centers implies accurate modeling of customer behavior on hold. The subject of our research is the application of data research techniques for predicting customer behavior in support channels. In this paper, we apply machine learning methods to predict customer behavior. Based on historical data in the service system, we use classification algorithms to predict customer patience in service channels.

The Internet of Things (IoT) is considered a new paradigm that aims to connect a large number of devices. IoT is increasingly present in domains such as healthcare, transport, agriculture, and other industrial branches. An increasing number of IoT devices, as well as the amount of data, leads to increased energy consumption and a negative impact on the environment. Therefore, researchers are focusing on the concept of Green IoT that aims to increase energy efficiency and create a safe environment. The focus of this paper is on energy-efficient techniques within green data centers. Also, the performance evaluation of data centers was performed in the GreenCloud simulator for the optimal load of data centers in terms of energy efficiency and sustainability.

Interaction channels are special opportunities to improve customer satisfaction by offering a consistent problem-solving experience. Contact center employees are the link between the company and the customer. They are responsible for maintaining an appropriate relationship between the company and the customer. So, they are personally responsible for the customer experience. In this paper, we present an objective evaluation method for evaluating customer-agent interaction, i.e., evaluating the effectiveness of the realization of customer requests from calls. The evaluation method is automatic and does not depend on the relationship between the call center manager and the employees. The motivation for evaluating calls stems from the key performance characteristics of a contact center, of which we particularly emphasize service time, first call resolution, handling time, and others.

Interaction channels are unique opportunities to improve customer satisfaction by offering a consistent problem-solving experience. The role of employees in the contact center is to maintain an appropriate relationship between the company and the customer, thus they are personally responsible for the customer experience. In this paper, an objective evaluation method for evaluating customer-agent interaction, i.e. evaluating calls is proposed. The motivation for evaluating calls stems from the key performance characteristics of a contact center.

The development of information society and broadband Internet is key indicators of social and economic change. They transform the way companies, political systems, and citizens communicate with each other. Today, we talk about various regional and national initiatives to first stabilize and then improve the economies of countries through the development of the Internet and information society. The European Union has recognized information technology as a major factor influencing economic growth and innovation. Among the seven flagship initiatives of the Europe 2020 economic strategy is the Digital Agenda for Europe. This shows the importance that information technologies have in the development of the modern economy. In this paper, we analyze the current state of development of the information society and broadband Internet access in Bosnia and Herzegovina. We highlight the necessity of considering mechanisms for the development of broadband access. We analyzed the current situation and progress in the implementation of the Digital Agenda guidelines in EU countries. The aim of this research is to highlight the advantages of using EU strategic guidelines to improve and develop the current situation in the field of broadband Internet in Bosnia and Herzegovina

The Internet of Things (IoT) connects everyone in the smart world, so the energy consumption of IoT technology is a challenging and attractive research area. The development of technology in the field of IoT has changed the way of life and enriched society with its benefits, but we must not ignore the fact that IoT consumes energy, contributes to toxic pollution, and generates electrical waste. To increase the benefits and reduce the harmfulness of IoT, there are increasing tendencies to move towards green IoT (G-IoT). The G-IoT is considered the future environmentally friendly IoT. Greening ICT technology plays a key role in G-IoT and promises many benefits to society such as efficient production, and reducing the energy used to design and distribute ICT devices and equipment. This paper will present a comprehensive overview of G-IoT technologies and strategies that demonstrate work and efforts to build a green and smart world, contributing to a safe and healthy environment, smart and high quality of life based on enabling technologies, reducing pollution, and reducing energy consumption. ICT technologies that enable G-IoT include Green RFID, Green Wireless Sensor Network (GWSN), Green Cloud Computing (GCC), Green M2M (G-M2M), and Green Data Center (GDC). The paper will also present an analysis of the importance of environmental technology processes in sustainable development, exploring the principles and roles of G-IoT in the progress of society through examining its potential for improving quality of life, environment, economic growth, and green global modernization.

Software process improvement implies a set of complex and systematic activities of software engineering. It requires theory and models established in management, technical and social sciences. The improvement is based on the assumption that the organization if it owns mature and capable processes, would be able to deliver quality software on time and in line with predicted costs. The maturity models are initially aimed for implementation in enterprise software organizations, government organizations and within the military industry. Their complexity and the size make them difficult to use in small software organizations and companies. In such organizations the interest for use and the efforts to make an efficient and effective organization is always presented, though. In this paper, the basic and derived capability maturity models are described and cases from their implementation are analyzed, along with assessment of results of such projects in business practices. The problem of the software process improvement in small organizations is described, extracting the risks and recommendations for its enhancement. These recommendations are provided in order to set up a foundation for implementation of these models in a specific managerial and organizational environment characterized by small organizations.

Introduction: Machine learning (ML) plays a significant role in the fight against the COVID-19 (officially known as SARS-CoV-2) pandemic. ML techniques enable the rapid detection of patterns and trends in large datasets. Therefore, ML provides efficient methods to generate knowledge from structured and unstructured data. This potential is particularly significant when the pandemic affects all aspects of human life. It is necessary to collect a large amount of data to identify methods to prevent the spread of infection, early detection, reduction of consequences, and finding appropriate medicine. Modern information and communication technologies (ICT) such as the Internet of Things (IoT) allow the collection of large amounts of data from various sources. Thus, we can create predictive ML-based models for assessments, predictions, and decisions. Methods: This is a review article based on previous studies and scientifically proven knowledge. In this paper, bibliometric data from authoritative databases of research publications (Web of Science, Scopus, PubMed) are combined for bibliometric analyses in the context of ML applications for COVID-19. Aim: This paper reviews some ML-based applications used for mitigating COVID-19. We aimed to identify and review ML potentials and solutions for mitigating the COVID-19 pandemic as well as to present some of the most commonly used ML techniques, algorithms, and datasets applied in the context of COVID-19. Also, we provided some insights into specific emerging ideas and open issues to facilitate future research. Conclusion: ML is an effective tool for diagnosing and early detection of symptoms, predicting the spread of a pandemic, developing medicines and vaccines, etc.

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.

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.

A large number of researchers found their interest in addressing the issue of capacity scaling for wireless ad hoc networks. This paper aims to provide a comprehensive overview of the development of capacity scaling laws in wireless networks, highlighting the problem of scaling as one of the basic challenges in their research. The review began with the definition of the notion of bandwidth of random networks, which were taken as a reference model of consideration when determining more advanced strategies for improving throughput capacity. Based on these strategies, other factors that have an impact on capacity scaling laws have been identified and elaborated. Finally, the capacity of hybrid wireless networks, ie networks in which at least two types of nodes functionally exist (ad hoc nodes/infrastructure nodes / auxiliary nodes), was partially investigated.

Contact centers are an operationally complex element of a company and play a major role in the experience of its customers. By offering relevant and quick responses to questions and prompt problem solving, a company can achieve a better customer experience. Contact centers generate huge amounts of very useful data, which are often underused, misused, or even not used at all. Our research aims to apply data research techniques to the problem of creating customer profiles in the contact center. Customer profiling mechanisms should provide an explicit set of information about the observed customer's preferences, interests, and behavior patterns. Based on the attributes contained in the customer profile, the system makes decisions in terms of choosing the right contact center agent by anticipating the needs of the observed customer. In our paper, the customer profile is based on the extraction of his properties from log information about used services, behavior patterns, and other general characteristics of each customer. The purpose of our research is to determine which attributes are the most relevant for creating a customer profile and how to evaluate them.