The proven safe operation and the high availability of aerial ropeways is mainly thanks to their design. This is based on the manufacturer’s extensive experience as well as the strict application of the relevant rules and norms. In that regard, this paper describes an analysis of the haulage ropes on ropeways in case of accidental loads. In solving this problem, analyzed ropeway system with sufficient accuracy was modeled as a system with three degrees of freedom. For solving differential equations we have used the software “Wolfram Mathematica”. At the end of the paper, we discuss the results of the dynamic forces in the haulage ropes in a certain time interval, and the results of the safety factors which in this case are sufficient to ensure reliable operation of the system.

In this paper, we model an extended DC state estimation (SE) in an electric power system as a factor graph (FG) and solve it using belief propagation (BP) algorithm. The DC model comprises bus voltage angles as state variables, while the extended DC model includes bus voltage angles and bus voltage magnitudes as state variables. By applying BP to solve the SE problem in the extended DC model, we obtain a Gaussian BP scenario for which we derive closed-form expressions for BP messages exchanged along the FG. The performance of the BP algorithm is demonstrated for the IEEE 14 bus test case. Finally, the application of BP algorithm on the extended DC scenario provides significant insights into a fundamental structure of BP equations in more complex models such as the AC model - the topic we will investigate in our follow up work. As a side-goal of this paper, we aim at thorough and detailed presentation on applying BP on the SE problem in order to make the powerful BP algorithm more accessible and applicable within the power-engineering community.

In this paper, we propose a solution to an AC state estimation problem in electric power systems using a fully distributed Gauss-Newton method. The proposed method is placed within the context of factor graphs and belief propagation algorithms and closed-form expressions for belief propagation messages exchanged along the factor graph are derived. The obtained algorithm provides the same solution as the conventional weighted least-squares state estimation. Using a simple example, we provide a step-by-step presentation of the proposed algorithm. Finally, we discuss the convergence behaviour using the IEEE 14 bus test case.

Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.

Marketing of fuel wood is an important source of livelihood for most parts of Nigeria. The study examined the economics of marketing of wood fuel in south western Nigeria with a view to determine the socio-economic characteristics of the marketers, the profitability of marketing wood fuel, the market structure and constraints to profitability. Data for the study were obtained from a total sample of 100 randomly selected wood fuel marketers through interviews schedules and application of structured questionnaires. Descriptive statistics was used to analyze the socio-economic characteristics of the marketers. Cash analysis was used to determine the profitability of the enterprise while Gini-coefficient was used to examine the markets’ concentration. The result showed that majority of the marketers was in their active years as 51% were between 21-40 years of age. 71% were female while 56% of them were married. Most of the marketers (76%) had formal education and were well experienced in the business. Cash analysis revealed that marketing of wood fuel is profitable with an average Gross margin of 21,190.65 naira per month. The marketing efficiency was found to be 128% and the rate of return on investment was 28% which indicates that for every 100 naira investment in the business, the marketers will enjoy a return of 28 naira. The value of Gini-Coefficient (0.393) indicates high level of market concentration and inefficiency in the market structure. Transportation was the greatest constraint to the business profitability followed by season of the year and government policy.

OBJECTIVE The aim of this study was to assess caries prevalence and severity in preschool children in the Federation of Bosnia and Herzegovina. In addition, the relationship between the frequency and clinical types of early childhood caries and behavioral factors, oral hygiene and eating habits were assessed. SUBJECTS AND METHODS An oral health survey was performed in line with the World Health Organization methodology and criteria. The research consisted of clinical examinations of children to determine dentition status, oral hygiene and severity of caries distribution according to Wyne's classification. Information about behavioral factors was collected by means of a questionnaire administered to parents/guardians. RESULTS The sample consisted of a total of 165 preschool children aged 3-5 years. Mean dmft (decay, missing, filled teeth index for primary dentition) was 6.79. The percentage of caries-free children was 17.0%. The results showed a statistically significant correlation between oral hygiene and eating habits, and also the frequency and types of early childhood caries. CONCLUSION The present study demonstrates high caries prevalence in preschool children in the Federation of Bosnia and Herzegovina. Community based preventive programs should be developed and urgently implemented, in order to achieve the WHO goals, improve oral and general health, thus improving the quality of life of these populations.