This paper describes a model driven methodology in order to implement an interoperable communication architecture supporting TSO-DSO information exchange. The model driven methodology goes through Smart Grid Architecture Model interoperability layers and leverage international standards. The Use Case approach is utilized for identification of information exchange requirements, which are materialized through Business Objects gap analysis against existing standardized IEC CIM (Common Information Model) profiles. Determined set of standardized Business Objects can be implemented using several communication technologies. Some of these up-to-date technologies are provided by off the shelf solutions such as ECCo SP, a secure and scalable platform provided by ENTSO-E.

Lighting systems based on light-emitting diodes (LEDs) possess many benefits over their incandescent counterparts including longer lifespans, lower energy costs, better quality of light and no toxic elements, all without sacrificing consumer satisfaction. Their lifespan is not affected by switching frequency allowing for better illumination control and system efficiency. In this paper, we present a fully distributed energy-saving illumination dimming control strategy for the system of a lighting network which consists of a group of LEDs and user-associated devices. In order to solve the optimization problem, we are using a distributed approach that utilizes factor graphs and the belief propagation algorithm. Using probabilistic graphical models to represent and solve the system model provides for a natural description of the problem structure, where user devices and LED controllers exchange data via line-of-sight communication.

Introduction: Compulsory electromyoneurography (EMNG) analysis of all neurophysiological parameters, including the most sensitive parameter for early detection of diabetic polyneuropathy (cutaneous silent periods), in patients without subjective symptoms, and EMNG analysis demonstrates the existence of incipient signs for polynomial neuropathy due to which timely therapeutic approach is needed to prevent complications of diabetic disease and prevent irreversible changes in peripheral nerves. Aim: Examine the influence of type diabetes mellitus, therapeutic modality, and gender of patients on neurophysiological parameters obtained by EMNG analysis. Methods: The study included 90 patients with diabetes who were divided into three groups of 30, depending on the duration of the disease. Group 1 consisted of 30 respondents with type 2 diabetes mellitus and up to 5 years of disease duration. Group 2 consisted of 30 respondents with type 2 diabetes mellitus type and 5 to 10 years of disease duration. Group 3 consisted of 30 respondents with Type 1 diabetes mellitus. An electron-neurography analysis of peripheral nerve in the extremities was performed. Results: Group 1 (50%) and group 2 (56.17%) respondents had statistically higher incidence of tingling than those in Group 3 (13.3%), p=0.004. Tingling was not statistically significantly different in relation to the examined groups (p=0.314). Reflexes were statistically the most preserved in Group 3 (86.7%), p = 0.001. Measurement of motor conductivity values at median nerve had a significant difference in all parameters (distal latency, amplitude, mean conduction velocity (MCV) and latency in the group with DM type 1, compared to respondents with DM type 2. The same significant difference between all parameters was found when testing peroneus nerve. When measuring motor velocity conductivity in ulnar nerve, there was no significant difference in amplitude, while DM1 type 1 patients had significant differences in values: distal latency and MCV p<0.0001, latency p<0.002. Measurement of sensory velocity was not statistically significant between patients with DM types 1 and 2. In relation to therapy, oral insulin therapy was not shown to be of statistical significance, except for tibialis amplitude measurements, where insulin-treated DM patients had a value amplitude of 12.96±1.48, and in oral therapy group less than 0.04 (p<0.05) 9.14±0.93. In the DM type 2 group no, neurophysiological parameters showed significant gender differences, while in respondents with DM type 2, where the disease lasted shorter, a significant gender difference was present in terms of motor velocity and sensory conductivity in all the nerves examines, except MCV in ulnar nerve. In the DM type 1 respondents, a significant gender difference was present in measuring MCV at tibial nerve and peroneus nerve (p <0.01 and p <0.02), as well as latency of MCV in H reflexes (p<0.01), in males was 56.25±1.03 and in females 32.89±0.47. Conclusion: Diabetic polyneuropathy is significantly more present in patients older than 60 years who have type 2 diabetes mellitus (2/3 of those with a duration of 5 years or less and in ½ respondents with DM duration of less than 5 years), without any hesitation on the type of therapy. Measurement values of motor conductivity at median nerve had a significant difference in all parameters (distal latency, amplitude, MCV, and latency F) in the group with DM type 1. The same significant difference between all parameters was also found in n. peroneus. Distal latency values at sural nerve and tibial nerve, latency values and MCV in H reflexes, do not depend on DM type.

The aim of this paper was to compare two business models, namely business to business and business to customer. The first model is oriented towards the delivery of intermediate goods ordered by an immense foreign market leader that is outsourcing a part of its business. The second model is consumers oriented and is more about innovation and the creation of goods ready to be immediately sold on the market. Bosnia is a developing country, and often a place for establishing B2B businesses. However, we are lacking in innovation, our own know-how, and the creation of challenging business opportunities. It also faces the problem of brain drain; therefore, it is in a need of a plan for retaining the youth within the country. The analysis aimed to show how the boosting jobs and living standards in Bosnia, are affected by the investments, exports, and salaries within the B2B and B2C companies. The results showed that Bosnia has a significant potential for raising living standards, employment and salary, if investments are directed towards innovations, knowledge-intensive and B2C businesses instead of labor-intensive investments.

The mountain rescue services in Croatia and BiH have been using UAVs on search and rescue missions for years. They prove to be very effective on the hard-to-reach Mediterranean karsts landscape, characterized by low but not too dense vegetation. After mapping some terrain segment and collecting a large number of precise and detailed footage from above, images are visually scanned and examined by search rescue member/s. In this paper we will examine the effectiveness of visual search of human observers for the purpose of finding missing/lost persons on aerial imagery.

Data mining is the process of knowledge discovery in a certain amount of data. Knowledge discovery in data reflects in the application of sophisticated machine learning methods such as regression, classification, clustering, etc. The focus of this study is the analysis of data from the real production system called Edu720, which is intended for internal education of employees in companies and which is used by numerous companies in Bosnia and Herzegovina and its region. A complex process of data preprocessing, including data cleaning and data transformation, was applied to the considered data set so it can be used in numerous classification tasks. The main goal of this study is to predict the success of the education that the company wants to set up for its employees. Information such as the number of questions in education, the average number of words per question in certain education, the number of employees and the duration of the educational video resource represented in seconds were used as attributes for applied classification methods. Class output represents the level of success for certain educations. K-nearest neighbors and decision tree algorithms were used for classification tasks and the accuracy of the classification was determined by the holdout method. The influence of applying the more sophisticated method for data set partitioning, which uses the K-means clustering method, is also presented.

Noninvasive load monitoring have been investigated by researchers for decades due to its cost-effective benefits. Upon introduction of smart meters, obtaining data about power consumption of households became easier. Numerous different techniques have been applied on the power consumption data to gain useful information out of it. This study applies machine learning techniques (Bayes network, random forest and rotational forest) to determine the operation state of households, where households are assumed to be either in ON or OFF state. Tracebase power consumption signature repository was used to train and test proposed machine learning models. Tracebase dataset was preprocessed to generate 4 different datasets. Test results have shown that these machine learning algorithms are able to estimate operation state with high accuracy and Bayes network shows outstanding performance among them with overall accuracy of 95%. Proposed method is extremely cost-effective for load monitoring and could replace some of the physical sensors in the smart houses.

Congestion control algorithms are crucial in achieving high utilization while preventing overloading the network. Over the years, many different congestion control algorithms have been developed, each trying to improve over others in specific situations. However, their interactions and co-existence has, to date, not been thoroughly evaluated, which is the focus of this paper. Through head-to-head comparisons of loss-based, delay-based and hybrid types of congestion control algorithms, we reveal that fairness in resources claimed is often not achieved, especially when flows sharing a link have different round-trip times or belong to different groups.

An indoor terrarium population of Amblyomma geoemydae was established subsequent to the import of a single yellow‐marginated box turtle Cuora flavomarginata. This indoor tick population revealed an unexpected resistance against de‐ticking trials, with persistence between 2010 and 2015, when the ticks were successfully eliminated. Ticks were collected from the bodies and shells of turtles, as well as from terraria soil. Species diagnosis of ticks was carried out according to distinguishable morphological characters and supported by molecular analysis using DNA‐barcoding. Introduced exotic ticks are potential vectors of pathogens and can have an impact on wildlife, domestic animals and the human population. This case emphasizes the need for sharp surveillance and control measures on imported reptiles.