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Ad hoc networks capacity scaling problem
oai:ojs2.setjournal.com:article/1A 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
Development of mobile communication systems for high-speed railway
Development of high-speed railways set up challenges for new communication technologies. With the increase in speed, new requirements for communication systems have emerged that HSR requires greater reliability, capacity and shorter response time for efficient and safe operations. Mobile communication systems are crucial for the competitiveness of the railway industry and therefore have become one of the priorities addressed by the participants in the railway system to take advantage of technological opportunities to improve operational processes and the quality of provided transport services. The European Rail Traffic Management System (ERTMS) uses the Global System for Mobile Communications for Railways (GSM-R) for voice and data communication to communicate between trains and control centers. The International Railway Union is exploring new ways of communicating for high-speed railways because as speed increases this system becomes unreliable in information transmission. This paperwork presents an analysis of the evolution of communications on European railways since the usage of GSM-R. In addition, an overview of the various alternative solutions proposed during the time (LTE-R, Future Railway Mobile Communication System) as possible successors to GSM-R technology is given
A practical implementation of machine learning in predicting breast cancer
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\u27s 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
Quality management as the basis of business company operations for the purpose of customer satisfaction
Nowadays, companies face numerous challenges to operate successfully and remain competitive in the market. Globalization is increasing competition in the market, allowing many companies to operate in foreign markets. Increasing competition has made companies constantly trying to increase their productivity while reducing costs. To meet all the requirements, and at the same time function in the best possible way, companies must be organized adequately, taking into account the whole set of processes from the company\u27s internal organization to the company\u27s appearance on the market. It means, if the end-user is to be satisfied, the company must implement quality in all phases of business, ie business ethics and company culture, through the quality of technology, personnel, etc. In other words, it must be satisfied the system quality of the company, known in the literature as QMS (Quality Management System). The main purpose of this paper is to review the multiple understanding of the concept of QMS and its different underpinning theories in a business to customer context. The design of this research is based on mere documentary analysis and some observations
Recognition of traffic generated by WebRTC communication
Network traffic recognition serves as a basic condition for network operators to differentiate and prioritize traffic for a number of purposes, from guaranteeing the Quality of Service (QoS), to monitoring safety, as well as monitoring and detecting anomalies. Web Real-Time Communication (WebRTC) is an open-source project that enables real-time audio, video, and text communication among browsers. Since WebRTC does not include any characteristic pattern for semantically based traffic recognition, this paper proposes models for recognizing traffic generated during WebRTC audio and video communication based on statistical characteristics and usage of machine learning in Weka tool. Five classification algorithms have been used for model development, such as Naive Bayes, J48, Random Forest, REP tree, and Bayes Net. The results show that J48 and BayesNet have the best performances in this experimental case of WebRTC traffic recognition. Future work will be focused on comparison of a wide range of machine learning algorithms using a large enough dataset to improve the significance of the results
Use of information and communication technologies in social work institutions in extraordinary circumstances
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
Wireless communication technologies for the Internet of Things
Internet of Things (IoT) is the inter-networking paradigm based on many processes such as identifying, sensing, networking and computation. An IoT technology stack provides seamless connectivity between various physical and virtual objects. The increasing number of IoT applications leads to the issue of transmitting, storing, and processing a large amount of data. Therefore, it is necessary to enable a system capable to handle the growing traffic requirements with the required level of QoS (Quality of Service). IoT devices become more complex due to the various components such as sensors and network interfaces. The IoT environment is often demanding for mobile power source, QoS, mobility, reliability, security, and other requirements. Therefore, new IoT technologies are required to overcome some of these issues. In recent years new wireless communication technologies are being developed to support the development of new IoT applications. This paper provides an overview of some of the most widely used wireless communication technologies used for IoT applications
Rough estimation of cell numbers in 5G networks using simple mathematical calculations
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
Treatment of road traffic noise in EU countries with a focus on Directive 2002/49/EC
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
A pratical implementation of deep neural network for facial emotion recognition
People\u27s emotions are rarely put into words, far more often they are expressed through other cues. The key to intuiting another\u27s feelings is in the ability to read nonverbal channels, tone of voice, gesture, facial expression and the like. Facial expressions are used by humans to convey various types of meaning in a variety of contexts. The range of meanings extends from basic, probably innate, social-emotional concepts such as "surprise" to complex, culture-specific concepts such as "neglect". The range of contexts in which humans use facial expressions extends from responses to events in the environment to specific linguistic constructs in sign languages. In this paper, we will use an artificial neural network to classify each image into seven facial emotion classes. The model is trained on a database of FER+ images that we assume is large and diverse enough to indicate which model parameters are generally preferable. The overall results show that, the CNN model is efficient to be able to classify the images according to the state of emotions even in real time