Search

The ultimate goal of most European countries, especially of the Western Balkan countries, is to become full members of the European Union (EU). The mentioned countries are included in the Stabilisation and Association Process (with the Stabilisation and Association Agreement (SAA) as its main segment) and they are in a different stage of EU accession. Cooperation among the Western Balkan countries within the Central European Free Trade - CEFTA 2006, is the starting point for their future cooperation with the EU member states, allowing them to prepare for joining the common EU market more quickly and efficiently. By signing the Central European Free Trade Agreement (CEFTA 2006), Bosnia and Herzegovina (BiH) became a member of a free trade zone, together with other (non-EU) Western Balkan countries and Moldova. Removing trade barriers and improving trade cooperation was the primary goal of signing this agreement. Although the tariffs in the trade among inter-CEFTA countries were abolished, the existence of a large number of non-tariff barriers is evident, which significantly hampers most economic and trade relations in particular, within the mentioned regional group. Therefore, the starting point in this work is to study the impact of non-tariff barriers on the size of BiH import/export within CEFTA 2006. This paper presents the research results obtained on the basis of processing the secondary data sources using quantitative and qualitative methods. To check the main and supporting hypotheses we used the Spearman's correlation coefficient. Based on the analysis, it was found that there is a significant correlation between the non- tariff barriers and BiH import/export during this period.

This paper proposes the use of the discrete wavelet transform (DWT) to analyze and locate the low frequency oscillations of power systems, which can result in a loss of stability or in a black-out. The proposed DWT applied to active power signal is tested and compared with more conventional approaches of Prony and Eigenvalue analyses. The DWT also enables estimation of the total active power imbalance of a system. Estimation performances of different wavelet families are tested. Based on the proposed DWT of electromechanical transient oscillations, the DWT is also applied to identify the network nodes in the neighbourhood of the original disturbance. The performance of the proposed DWT is evaluated on the New England (NE) 39-bus test system.

The aim of this paper is to point to the very nature of the relationship between the organizational structure and organizational culture as very important mechanisms by means of which enterprises set their employees' behavior on the target course, or direct their efforts at accomplishing organizational goals, respectively. Besides the examination of the phenomenon of the organizational structure and organizational culture at the general level, the paper also includes the analysis of empirical study results entailing Bosnian enterprises. The research was made for two reasons. The first one was to identify the formalization and centralization level. The second one was to identify dominant organizational types of the structure and the culture (using the Charles Handy’s culture typology). The research analysis was made with respect to the interaction between organizational structure and organizational culture on one hand, and the point of view of the national culture and transitional processes characteristic of the area on the other hand.

Motivation: Affymetrix microarrays are widely used to measure global expression of mRNA transcripts. That technology is based on the concept of a probe set. Individual probes within a probe set were originally designated by Affymetrix to hybridize with the same unique mRNA transcript. Because of increasing accuracy in knowledge of genomic sequences, however, a substantial number of the manufacturer's original probe groupings and mappings are now known to be inaccurate and must be corrected. Otherwise, analysis and interpretation of an Affymetrix microarray experiment will be in error.Results: AffyProbeMiner is a computationally efficient platform-independent tool that uses all RefSeq mature RNA protein coding transcripts and validated complete coding sequences in GenBank to (1) regroup the individual probes into consistent probe sets and (2) remap the probe sets to the correct sets of mRNA transcripts. The individual probes are grouped into probe sets that are ‘transcript-consistent’ in that they hybridize to the same mRNA transcript (or transcripts) and, therefore, measure the same entity (or entities). About 65.6 % of the probe sets on the HG-U133A chip were affected by the remapping. Pre-computed regrouped and remapped probe sets for many Affymetrix microarrays are made freely available at the AffyProbeMiner web site. Alternatively, we provide a web service that enables the user to perform the remapping for any type of short-oligo commercial or custom array that has an Affymetrix-format Chip Definition File (CDF). Important features that differentiate AffyProbeMiner from other approaches are flexibility in the handling of splice variants, computational efficiency, extensibility, customizability and user-friendliness of the interface.Availability: The web interface and software (GPL open source license), are publicly-accessible at http://discover.nci.nih.gov/affyprobeminer.Contact: hl224@georgetown.edu or barry@discover.nci.nih.gov

Agricultural cooperatives emerge as tools through which individual farmers meet their economic and social needs and they do so in a manner that allows them both to economize on costs and to disperse the risks associated with pursuing these needs individually. They are particularly useful for enhancing economic development of transition countries in which basic market economy infrastructure is either underdeveloped or is altogether missing. However, agricultural cooperatives do not always deliver the desired level of rural development. Although the literature sometimes takes this to mean that the model itself is defective, I argue to the contrary. In this thesis, I propose that it is the evolutionary path of cooperative idea, its implementation in reality and the way in which it interacts with its institutional surroundings that condition the ability of the model to perform. In other words, cooperative idea is not immune to its political and economic context but rather it is molded by it, and sometimes to the point that it no longer resembles its original substance. In line with that, the main objective of this thesis is to look into factors that either stimulate or discourage development and functioning of agricultural cooperatives in a context of post-socialist and post-conflict Bosnia and Herzegovina (BiH). In doing so, the thesis adopts a new institutionalist frame of analysis combining it with the insights from the economics of the third sector and the cooperative theory to highlight both the evolutionary nature of cooperative idea as well as its embeddedness in the socio-economic context. The research relied on quantitative and qualitative approaches and gathered data from field work and secondary sources. The main findings can be summarized in the following several points: both formal and informal institutions have shaped the way in which cooperatives are understood and utilized by farmers in BiH; cooperatives in post-socialist and post-conflict settings require legal clarity that not only sets them apart from other types of firms in the market but also from degenerated forms of cooperatives that exist to serve interests of few individuals rather than cooperative members and their communities; when judged by the standards that apply to cooperatives in economically advanced societies, it is safe to state that there are very few true cooperatives in BiH; given the structure of agricultural market and number of farmers, there is a lot of potential in utilizing the cooperative model for purposes of rural development. However, using cooperatives for development purposes requires a basic alignment between the features of institutional environment and cooperative organizational characteristics. If stimulated properly through positive policy changes, cooperatives can exhibit transformative potential that is best reflected in how they empower their patrons as well as contribute to the development of their communities.

Arbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprüft Graz, Univ., Masterarb., 2015

This paper investigates the possibility of classifying power system dynamics events using discrete wavelet transform (DWT) and a neural network (NN) by analyzing one variable at a single network bus. Following a disturbance in the power system, it will propagate through the system in the form of low-frequency electromechanical oscillations (LFEOs) in a frequency range of up to 5 Hz. DWT allows the identification of components of the LFEO, their frequencies, and magnitudes. After determining the energy components' share of the analyzed signal using DWT and Parseval's theorem, the input data for the classification process using a NN are obtained. A total of 5 classes of disturbances, 3 different wavelet functions, and 2 different variables are tested. Simulation results show that the proposed approach can classify different power disturbance types efficiently, regardless of the choice of variable or wavelet function.

From April 1993 until July 1995, Hasan Nuhanovic worked as an interpreter and translator for the UN Military Observers (UNMO) and the Dutchbat team guarding the demilitarised enclave of Srebrenica. Here, for the first time, Hasan Nuhanovic tells what happened the day the Serbs arrived to destroy the town, massacre its menfolk and drive their widows into exile

Any banking activity involves a certain level of risk. Regardless of the fact that risk has always been present in banks, active risk management in conventional banking started only in the 1990s, specially after the collapse of Barings PLC, the bank with more than 200-year-old tradition, while such practice is still underdeveloped in Islamic (interest-free) banking whose practical implementation in the world started only in the 1970s. However, in the times of the recent sub-prime mortgage crisis and a large number of collapses and near collapses, multibillion losses and write-offs all banks, whether conventional or Islamic, saw the necessity for active risk management. Specific features of banks in Bosnia and Herzegovina and their way of managing risks are conditioned by a particular legal framework. This framework regulates primarily the conventional banks, but it indirectly affects the Islamic bank as well, since it does not allow the bank to offer all types of products and services which are generally present in Islamic banking. Since, to our knowledge, not a single specific comparative research into conventional and Islamic banks has been done in this part of the world, the aim of this paper is to provide an insight into risk management practiced by BiH banks, and to determine the dependence of their financial performance on the process of active risk management.

In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently., {"references":["S. Tong and N.V.Thacor, Engineering in Medicine & Biology-\nQuantitative EEG Analysis Methods and Clinical Applications,\nBoston/London: Artech House, 2009.","L. M. Patnaika and O. K. Manyamb, \"Epileptic EEG detection using\nneural networks and post-classification\" Computer methods and\nprograms in biomedicine- Elsevier, vol. 91, pp. 100-109. 2008.","A. Prochazka, J. Kukal and O.Vysata, \"Wavelet transform use for\nfeature extraction and EEG signal segments classification,\" in Proc.\n2008 IEEE Communications, Control and Signal Processing, 3rd\nInternational Symposium, pp. 719 - 722.","V. Bostanov and B. Kotchoubey, \"Recognition of affective prosody:\nContinuous wavelet measures of event-related brain potentials to\nemotional exclamations,\" Psychophysiology, vol. 41, pp. 259-268, 2004.","M. Murugappan, M. Rizon, R. Nagarajan, S. Yaacob, I. Zunaidi, and D.\nHazry, \"EEG Feature Extraction for Classifying Emotions using FCM\nand FKM,\" Int. Journal of Computers and Comunications, vol. 1, pp.\n21-25, 2007.","C. Wang, J. Zou, J. Zhang, M. Wang and R. Wang, \"Feature extraction\nand recognition of epileptiform activity in EEG by combining PCA with\nApEn\", Biomedical and Life Sciences- Springer, vol. 4, pp. 233-240,\n2010.","L. Guo, D. Rivero, J. A. Seoane and A. Pazos, \"Classification of EEG\nSignals Using Relative Wavelet Energy and Artificial Neural\nNetworks,\" GEC-09, Shanghai, China, 2009.","M. Akin, M. A. Arserim, M. K. Kiymik and I. Turkoglu, \"A New\nApproach For Diagnosing Epilepsy By Using Wavelet Transform And\nNeural Networks,\" in Proc. 2001 IEEE/EMBS 23rd Annual Conference,\npp. 1596 - 1599.","H. S. Liu, T. Zhang and F. S. Yang, \"A Multistage, Multimethod\nApproach for Automatic Detection and Classification of Epileptiform\nEEG,\" IEEE Transactions on Biomedical Engineering, vol. 49, pp. 1557\n- 1566, 2002.\n[10] P. Jahankhani, V. Kodogiannis, and K. Revett, \"EEG Signal\nClassification Using Wavelet Feature Extraction and Neural Networks,\"\nin Proc. 2003 International Symposium on Modern Computing, pp. 120\n- 124.\n[11] A. A. Mashakbeh, \"Analysis Of Electroencephalogram To Detect\nEpilepsy,\" Int. Journal Of Academic Research, vol. 2, pp. 63-69, 2010.\n[12] M. M. Shaker, \"EEG Waves Classifier using Wavelet Transform and\nFourier Transform,\" Int. Journal of Biological and Life Sciences, vol. 1,\npp. 85-90, 2005.\n[13] I. Omerhodzic, E. Causevic, K. Dizdarevic, S. Avdakovic, M. Music, M.\nKusljugic, E. Hajdarpasic, N. Kadic, \"First neurosurgical experience\nwith the wavelet based EEG in diagnostic of concussion,\" 11th Congress\nof Neurosurgeons of Serbia, Nis, Serbia, 2008. Abstract book p. 18.\n[14] L. M. Patnaik, O. K. Manyam, \"Epileptic EEG detection using neural\nnetworks and post-classification\". Comput Methods Programs Biomed.\n2008 Aug;91(2):100-9.\n[15] A. Subasi, E. Er├ºelebi, \"Classification of EEG signals using neural\nnetwork and logistic regression\". Comput Methods Programs Biomed.\n2005 May;78(2):87-99.\n[16] K. Asaduzzaman, M. B. Reaz, F. Mohd-Yasin, K. S. Sim, M. S.\nHussain, \"A study on discrete wavelet-based noise removal from EEG\nsignals\", Adv Exp Med Biol. 2010;680:593-9.\n[17] H. Adeli, Z. Zhou, N. Dadmehr. \"Analysis of EEG records in an\nepileptic patient using wavelet transform\", J Neurosci Methods. 2003\nFeb 15;123(1):69-87.\n[18] L. Guo, D. Rivero, J. Dorado, J. R. Rabunal, A. Pazos, \"Automatic\nepileptic seizure detection in EEGs based on line length feature and\nartificial neural networks\", J Neurosci Methods. 2010 Aug\n15;191(1):101-9.\n[19] A. S. Zandi, M. Javidan, G. A. Dumont, R. Tafreshi, \"Automated realtime\nepileptic seizure detection in scalp EEG recordings using an\nalgorithm based on wavelet packet transform\", IEEE Trans Biomed Eng.\n2010 Jul;57(7):1639-51.\n[20] P. Mirowski, D. Madhavan, Y. Lecun, R. Kuzniecky, Classification of\npatterns of EEG synchronization for seizure prediction. Clin\nNeurophysiol. 2009 Nov;120(11):1927-40.\n[21] A. S. Zandi, G. A. Dumont, M. Javidan, R. Tafreshi, B. A. MacLeod, C.\nR. Ries, E. A. Puil, \"A novel wavelet-based index to detect epileptic\nseizures using scalp EEG signals\", Conf Proc IEEE Eng Med Biol Soc.\n2008;2008:919-22.\n[22] A. Subasi, A. Alkan, E. Koklukaya, M. K. Kiymik, \"Wavelet neural\nnetwork classification of EEG signals by using AR model with MLE\npreprocessing\", Neural Netw. Sep 2005, vol. 18(7), 985-997.\n[23] S. J. Schiff, A. Aldroubi, M. Unser, S. Sato, \"Fast wavelet\ntransformation of EEG\", Electroencephalogr Clin Neurophysiol. Dec\n1994, vol. 91(6), 442-455.\n[24] L. Senhadji, J. L. Dillenseger, F. Wendling, C. Rocha, A. Kinie,\n\"Wavelet analysis of EEG for three-dimensional mapping of epileptic\nevents\", Ann Biomed Eng. Sep-Oct 1995, 23(5):543-52.\n[25] C. E. D'Attellis, S. I. Isaacson, R. O. Sirne, \"Detection of epileptic\nevents in electroencephalograms using wavelet analysis\", Ann Biomed\nEng. Mar-Apr 1997, 25(2):286-93.\n[26] H. Adeli, S. Ghosh-Dastidar, N. Dadmehr, \"A wavelet-chaos\nmethodology for analysis of EEGs and EEG subbands to detect seizure\nand epilepsy\", IEEE Trans Biomed Eng. Feb 2007, 54(2):205-11.\n[27] H. Leung, K. Schindler, A. Y. Chan, A. Y. Lau, K. L. Leung, E. H. Ng,\nK. S. Wong, \"Wavelet-denoising of electroencephalogram and the\nabsolute slope method: a new tool to improve electroencephalographic\nlocalization and lateralization\", Clin Neurophysiol. Jul 2009,\n120(7):1273-81.\n[28] I. Daubechies, Ten Lectures on Wavelets, Philadelphia: Society for\nIndustrial and Applied Mathematics, 1992.\n[29] H. He and J. A. Starzyk, \"A Self-Organizing Learning Array System for\nPower Quality Classification Based on Wavelet Transform,\" IEEE\nTransaction On Power Delivery, vol. 21(1), pp. 286-295, 2006.\n[30] S. Mallat, A Wavelet Tour of Signal Processing, San Diego, CA:\nAcademic, 1998.\n[31] S. Avdakovic and A. Nuhanovic, \"Identifications and Monitoring of\nPower System Dynamics Based on the PMUs and Wavelet Technique,\"\nInternational Journal of Energy and Power Engineering, vol. 3, pp. 202-\n209, 2010.\n[32] R. G. Andrzejak, K. Lehnertz, C. Rieke, F. Mormann, P. David, C. E.\nElger, \"Indications of nonlinear deterministic and finite dimensional\nstructures in time series of brain electrical activity: Dependence on\nrecording region and brain state, Phys. Rev. E, 64, 061907. [Online]\nAvailable: http://epileptologie-bonn.de/cms/\n[33] P. Settipalli, \"Automated Classification Of Power Quality Disturbances\nUsing Signal Processing Technique and Neural Network\", Ph.D.\ndissertation, University of Kentucky; USA, 2007.\n[34] S. Dreiseitl, L. Ohno-Machado, Logistic regression and artificial neural\nnetwork classification models: a methodology review, J. Biomed.\nInform. vol. 35, 352-359, 2002.\n[35] I.A. Basheer, M. Hajmeer, Artificial neural networks: fundamentals,\ncomputing, design, and application, J. Microbiol. Methods vol. 43, 3-31,\n2000.\n[36] B.B. Chaudhuri, U. Bhattacharya, Efficient training and improved\nperformance of multilayer perceptron in pattern classification,\nNeurocomputing vol. 34, 11-27, 2000."]}

Introduction: The prevalence of human brucellosis in Bosnia and Herzegovina and the Tuzla Canton reached its peak in 2008, with a reported total of 994 cases within country, and with 104 cases within the Tuzla Canton. Aim: to analyze the clinical and epidemiological features of human brucellosis in patients hospitalized at the University Clinical Center Tuzla during the period from 01/01/2000 till the 31/12/2010. Methods: We retrospectively analyzed the clinical symptoms, the laboratory and X-ray findings, the treatments, and the course and outcome of the disease. The diagnosis of brucellosis was based on anamnesis, clinical presentation, in correlation with a positive blood-culture, and/or serological tests. Results: The majority of patients (93.18%) were from rural regions. There were more males (79.54%) than females. Most of the patients were aged between 30 to 39 years (21% cases). Contact with infected animals was registered for 83.40% of the patients. The main symptoms and signs were fever, joint-pains, night sweating, anorexia, headaches, and hepatosplenomegaly. The important laboratory findings were increased erythrocyte sedimentation rates, increased values of C-reactive protein, and anemia. Adult patients were treated with a combination of gentamicin or streptomycin with doxycycline, and the children with a combination of gentamicin, and trimethoprim-sulfametaxasol, over at least 6 weeks. Complications were documented in 20.45% of the patients. Relapses were observed in 14.20%, and a chronic form of brucellosis in 5.11% of patients. There were no cases with lethal outcomes. Conclusion: Brucellosis is a growing public health problem, not only within the Tuzla Canton, but throughout Bosnia and Herzegovina.

Power system is a complex, dynamic system, composed of a large number of interrelated elements. Its primary mission is to provide a safe and reliable production, transmission and distribution of electrical energy to final consumers, extending over a large geographic area. It comprises of a large number of individual elements which jointly constitute a unique and highly complex dynamic system. Some elements are merely the system's components while others affect the whole system (Machowski, 1997). Securing necessary level of safety is of great importance for economic and reliable operation of modern electric power systems.

Ibrahim Omerhodzic1, Samir Avdakovic2, Amir Nuhanovic3, Kemal Dizdarevic1 and Kresimir Rotim4 1Clinical Center University of Sarajevo, Department of Neurosurgery, Sarajevo 2EPC Elektroprivreda of Bosnia and Herzegovina, Sarajevo 3Faculty of Electrical Engineering, University of Tuzla, Tuzla 4University Hospital “Sisters of Charity”, Department of Neurosurgery, Zagreb 1,2,3Bosnia and Herzegovina 4Croatia

Renewable energy systems are becoming a topic of great interest and investment in the world. In recent years wind power generation has experienced a very fast development in the whole world. For planning and successful implementations of good wind power plant projects, wind potential measurements are required. In these projects, of great importance is the effective choice of the micro location for wind potential measurements, installation of the measurement station with the appropriate measuring equipment, its maintenance and analysis of the gained data on wind potential characteristics. In this paper, a wavelet transform has been applied to analyze the wind speed data in the context of insight in the characteristics of the wind and the selection of suitable locations that could be the subject of a wind farm construction. This approach shows that it can be a useful tool in investigation of wind potential., {"references":["T.H. Le, D.A. Nguyen, \"Orthogonal-based wavelet analysis of wind\nturbulence and correlation between turbulence and forces\", Journal of\nMechanics, VAST, vol. 29(2), pp. 73-82, 2007.","S. Rehman, A.H. Siddiqi, \"Wavelet based correlation coefficient of time\nseries of Saudi Meteorological Data\", Chaos, Solitons and Fractals, Vol.\n39(4), pp. 1764-1789, 2009.","M. D. Popescu, D. Banerjee, E. O'Shea, J. G. Doyle,L. D. Xia, \"Very\nlong period activity at the base of solar wind streams\",\nAstronomy&Astrophysics, Vol. 442(3), pp. 1087 - 1090, 2005.","Gurley K, Kareem A, \"Applications of wavelet transforms in earthquake,\nwind and ocean engineering\", Engineering Structures, vol. 21, pp. 149-\n67, 1999.","A.H. Siddiqi, S. Khan, S. Rehman, \"Wind speed simulation using\nwavelets\", American Journal of Applied Sciences, Vol. 2(2), pp. 557-\n564, 2005.","M. Jose, A. Bolzan, \"Statistical and Wavelet Analysis of the Solar Wind\nData\", Brazilian Journal of Physics, Vol. 35(3A), pp. 592-596, 2005.","E. Terradellas, G. Morales, J. Cuxart , C. Yag├╝e, \"Wavelet methods:\napplication to the study of the stable atmospheric boundary layer under\nnon-stationary conditions\", Dynamics of Atmospheres and Oceans, Vol.\n34(2-4), pp. 225-244, 2001.","S. Rehman, A. H. Siddiqui, N. M. Al-Abbadi, \"Application of Discrete\nand Continuous Wavelets for Saudi Arabian Meteorological Data\nAnalysis\", Indian Journal of Industrial and Applied Mathematics, Vol.\nI(I), pp. 1-17, 2007.","F. Boberg, \"Solar Wind Variations Related to Fluctuations of the North\nAtlantic Oscillation\", Geophysical Research Letters, Vol. 29(15), pp. 13-\n(1-4), 2002\n[10] M. Jose, A. Bolzan, P.C. Vieira, \"Wavelet Analysis of theWind Velocity\nand Temperature Variability in the Amazon Forest \", Brazilian Journal\nof Physics, Vol. 36(4A), pp. 1217-1222, 2006.\n[11] I. Daubechies, Ten Lectures on Wavelets, Philadelphia: Society for\nIndustrial and Applied Mathematics, 1992.\n[12] S. Mallat, A Wavelet Tour of Signal Processing, San Diego, CA:\nAcademic, 1998.\n[13] S. Avdakovic, A. Nuhanovic, \"Identifications and Monitoring of Power\nSystem Dynamics Based on the PMUs and Wavelet Technique\"\nInternational Journal of Electrical and Electronics Engineering, vol.\n4(8), pp 512-519, 2010.\n[14] I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic, \"Energy\nDistribution of EEG Signals: EEG Signal Wavelet-Neural Network\nClassifier\", International Journal of Biological and Life Sciences, vol.\n6(4), pp 210-215, 2010.\n[15] Sander + Partner GmbH, Elektronic Wind Atlas for Bosnia and\nHerzegovina, Switzerland, 2008\n[16] C. Torrence, and G. P. Compo, \"A practical guide to wavelet analysis\"\nBulletin of the American Meteorological Society, vol. 79(1), pp. 61-78,\n1998."]}

Low frequency power oscillations may be triggered by many events in the system. Most oscillations are damped by the system, but undamped oscillations can lead to system collapse. Oscillations develop as a result of rotor acceleration/deceleration following a change in active power transfer from a generator. Like the operations limits, the monitoring of power system oscillating modes is a relevant aspect of power system operation and control. Unprevented low-frequency power swings can be cause of cascading outages that can rapidly extend effect on wide region. On this regard, a Wide Area Monitoring, Protection and Control Systems (WAMPCS) help in detecting such phenomena and assess power system dynamics security. The monitoring of power system electromechanical oscillations is very important in the frame of modern power system management and control. In first part, this paper compares the different technique for identification of power system oscillations. Second part analyzes possible identification some power system dynamics behaviors Using Wide Area Monitoring Systems (WAMS) based on Phasor Measurement Units (PMUs) and wavelet technique., {"references":["B. Pai, B. Chaudhuri, Robust Control in Power Systems, New York,\nSpringer, 2005.","P. Kundur, Power System Stability and Control, New York, McGraw-\nHill Inc., 1994.","D. Novosel, M. Begovic, V. Madani, \"Shedding Light on Blackouts\",\nIEEE Power and Energy Magazine, vol. 2, February 2004, pp. 32-43.","D. Novosel, V. Madani, B. Bhargava, K. Vu, J. Cole, \"Down of the\nSynchronization\", IEEE Power and Energy Magazine, vol. 6, December\n2008, pp. 91-97.","M. Kusljugic, D. Novosel, M. Glavic, J.A.D. Pinto, \"Wide Area\nMonitoring of Power System Dynamics\", presented at the International\nConference on Electrical Engineering, CEE05 Coimbra, Portugal, 2005.","A.G.Phadke, J.S.Thorp, Synchronized Phasor Measurements and Their\nApplications. New York: Springer, 2008.","IEEE/CIGRE Joint Task Force on Stability Terms and Definitions,\nDefinition and Classification of Power System Stability, IEEE Trans.\nPower Systems, vol. 19, 2004, 1387-1399.","I. Ngamroo, Y. Mitani, S. Dechanupapritta, PMU Based Monitoring of\nInter-Area Oscillation in Thailand Power System via Home Power\nOutlets, ECTI Transactions On Electrical Eng., Electronics, And\nCommunications, vol. 5, August 2007, 199-205.","T. Hashiguchi, Y. Mitani, O. Saeki, K. Tsuji, M. Hojo, H.Ukai,\n\"Monitoring power system dynamics based on phasor measurements\nfrom demand side outlets developed in Japan Western 60 Hz System\",\npresented at the Power Systems Conference and Exposition, IEEE PES,\nvol. 2, Oct. 2004, 1183- 1189.\n[10] M. Bronzini, S. Bruno, De Benedictis, La Scala, Taking the pulse of\nPower Systems: Monitoring Oscillations by Wavelet Analysis and Wide\nArea Measurement System, IEEE-PES Power Systems Conference and\nExposition, Atlanta, USA, vol. 1, 2006, 436-443.\n[11] L. Qi, L. Qian, S. Woodruff, D. Cartes, \"Prony Analysis for Power\nSystem Transient Harmonics\", EURASIP Journal on Advances in Signal\nProcessing, vol. 2007, no. 48406, December, 2006.\n[12] N. Zhang, M. Kezunovic, Transmission Line Boundary Protction Using\nWavelet Transform and Neural Network, IEEE Transaction On Power\nDelivery, vol. 22, 2007, 859-869.\n[13] S. Nath, A. Dey, A. Chakrabarti, Detection of Power Quality\nDisturbances Using Wavelet Transform, Proceedings of World Academy\nof Science, Engineering and Technology, vol. 37, 2009, 2070-3740.\n[14] S.Sutha, N.Kamaraj, Real Power Contingency Ranking Using Wavelet\nTransform Based Artificial Neural Network (WNN), International\nJournal of Electrical and Power Engineering- Medwell Journals, vol. 2,\n2008, 116-121.\n[15] K.Gayathri, N. Kumarappan, Comparative Study of Fault Identification\nand Classification on EHV Lines Using Discrete Wavelet Transform and\nFourier Transform Based ANN, International Journal of Electrical,\nComputer, and Systems Engineering, vol. 2, 2008, 127-137.\n[16] M. Uyara, S. Yildirima, M. T. Gencoglub, An Effective Wavelet-based\nFeature Extraction Method For Classification of Power Quality\nDisturbance Signals, Electric Power Systems Research, vol. 78, 2008,\n1747-1755.\n[17] B.Mohammadi-Ivatloo, Optimal placement of PMUs for Power System\nObservability Using Topology Based Formulated Algorithms, Journal of\nApplied Science, vol. 9, 2009, 2463-2468.\n[18] H. Breulmann, E. Grebe, M. Lösing, W. Winter, R. Witzmann, P.\nDupuis, M.P. Houry, T. Margotin, J. Zerenyi, . Dudzik, PSE S.A., J.\nMachowski, L. Mart├¡n, J. M. Rodr├¡guez, E. Urretavizcaya, \"Analysis\nand Damping of Inter-Area Oscillations in the UCTE/CENTREL Power\nSystem\", CIGRE 2000, pp 38-113. Paris, France, 2000.\n[19] M.Hojo, K. Ohnishi, T. Ohnishi, \"Analysis Of Load Frequency Control\nDynamics Based On Multiple Synchronized Phasor Measurements\",\nPower Engineering Society General Meeting, vol. 2, July 2003, 13-17."]}

Prevalence of hepatitis C virus (HCV) genotypes in Bosnia and Herzegovina (B&H) is an issue that is not sufficiently researched and there is a need for studies that would explore this in detail.The aim of this study was to determine the distribution of HCV genotypes in the group of patients with chronic hepatitis C and also in the group of first time blood donors that tested positive for anti HCV antibodies during the blood screening process. Our secondary goal was to compare the proportions of HCV genotypes between these two groups.We analyzed 75 blood samples of patients with confirmed chronic hepatitis C. We also analyzed 13/16082 blood samples of first time blood donors found to be HCV positive during the blood screening process. We also determined HCV genotype in HCV RNA positive samples.We have found that genotype 1b was more prevalent in chronic hepatitis C patients (52/75; 69,3%) than in first time blood donors (6/13; 46,1%), however this difference was not statistically significant (c2=1,721; df=1; p=0,19). Genotype 1a was more prevalent in the group of first time blood donors (3/13; 23,1%) than in the group of chronic hepatitis C patients (3/75; 4%), but this was also with limited statistical significance (c2=3,71; df=1; p=0,054). We have not found any significant difference in prevalence of genotypes 1a (p=0,2) and genotypes 3 (p=0,70) when compared between chronic patients (3/75 and 16/75; respectively) and first time blood donors (3/13 and 4/13; respectively). Our study confirmed domination of genotype 1b in the region of northeastern B&H which is in accordance with HCV genotype prevalence in other countries in our part of Europe.

In power system, stability problem and problems with electromechanical oscillations or generators swinging are consistent in power system. Electromechanical oscillations are noticeable in characteristic variables of synchronous generators. Consequences of synchronous generator connecting on grid are physical nature, apropos more generators connecting on one power system. The responses of power system on any system disturbance are electromechanical oscillations. Oscillations can be low damped or undamped with constant or increasing amplitude, so they can achieve value which can disrupt the system operation. The monitoring of power system electromechanical oscillations is very important in the frame of modern power system management and control. This paper presents techniques for identification and analysis of low-frequency oscillations. Simulations and analysis shall be performed on two-area test system.

Eine kulturgeschichtliche Studie, die einen möglichst breiten Überblick über die wichtigsten Ereignisse, welche die österreich-ungarische Ära mit sich brachte, verschaffen. Die Arbeit beschäftigt sich mit Okkupation und Annexion von Bosnien und Herzegowina und den Neuregelungen in den Religionsbereichen, dem Schulwesen und ihrer Auswirkung auf die politische, wirtschaftliche und kulturelle Entwicklung des damaligen Bosnien und Herzegowina

Möjligheterna att använda förnybara, sol- och vindenergi, att driva luftvärmepumpar har studerats. En typisk luftvärmepump drar 1,8kW effekt som högst under de kallaste perioderna. Studien visar att Sverige är ganska solfattig under tiden då värmepumpen behövs som mest. Investeringen i solel är mycket dyr. En kWh solel kostar cirka 4 - 5 kronor, räknat på 25års drift. Solel, som energikälla rekommenderas inte för att driva värmepumpar. Vindkraft å andra sidan kan vara ekonomisk hållbar under vissa förhållanden. I motsats till solstrålning har vinden olika hastigheter vid olika höjder och olika lägen. Småskalig vindkraft vid bra läge kan vara ekonomisk hållbar medan vid ett vindfattigt läge kan vindkraft inte bära sina kostnader. Rapporten visar vidare kostnadskalkyler för småskalig sol och vind elproduktion. Vidare jämförs prisnivån i Sverige med Tyskland, som är ledande inom solel. Lagstiftning och regelverk för installation av vindkraft berörs också.

Möjligheterna att använda förnybara, sol- och vindenergi, att driva luftvärmepumpar har studerats. En typisk luftvärmepump drar 1,8kW effekt som högst under de kallaste perioderna. Studien visar att Sverige är ganska solfattig under tiden då värmepumpen behövs som mest. Investeringen i solel är mycket dyr. En kWh solel kostar cirka 4 - 5 kronor, räknat på 25års drift. Solel, som energikälla rekommenderas inte för att driva värmepumpar. Vindkraft å andra sidan kan vara ekonomisk hållbar under vissa förhållanden. I motsats till solstrålning har vinden olika hastigheter vid olika höjder och olika lägen. Småskalig vindkraft vid bra läge kan vara ekonomisk hållbar medan vid ett vindfattigt läge kan vindkraft inte bära sina kostnader. Rapporten visar vidare kostnadskalkyler för småskalig sol och vind elproduktion. Vidare jämförs prisnivån i Sverige med Tyskland, som är ledande inom solel. Lagstiftning och regelverk för installation av vindkraft berörs också.

The common cases of a nonselective operation of the phase to ground fault protection in the insulated power grids, which utilize inductive sensors for a voltage unbalance indication, are explained by ferroresonant processes in voltage transformers of healthy drains. This paper deals with phase to ground faults simulations in a known grid, that provide information about possible nonselective phase to ground faults protection operation.

[1 ]H. He, J.A. Starzyk, A self-organizing learning array system for power quality classification based on wavelet transform, IEEE Transactions on Power Delivery 21 (1) (2006) 286–295. [2 ]P. O’Shea, E. Palmer, G. Frazer, Power system disturbance monitoring using spectral analysis techniques, IEEE Int. Conference on Acoustics, Speech and Signal Processing (1995) 2731–2734. [3 ]K. Mei, S.M. Rovnyak, C-M. Ong, Dynamic event detection using wavelet analysis, IEEE PES General Meeting (2006) 1–7.

The validation of a power system clustering algorithm proposed by Glavic et al. on a real-life power system, the Bosnian electric power system, is presented. Voltage collapse is associated with a stress condition of the power system. Theoretical investigations of this complex phenomenon have resulted in many different analyses and solutions. It has been confirmed that the voltage instability problems start locally at the weakest nodes in a reduced area of the network, and the problem spreads to neighbouring nodes, resulting in a cascading phenomenon. Identification of reduced areas in a power system, with coherent behaviour of node voltages, may reduce the computational burden for voltage collapse analysis. A network clustering is proposed to reduce the computational burden associated with the analysis of voltage instability in large power networks. The algorithm is based on a method which was initially developed for coherency based system decomposition into study and external areas based on the linearised dynamic model of power system (satisfactory results have been obtained using the 30-bus New England test system). The algorithm is disturbance-independent, computationally fast and avoids computational burden because it requires only a limited number of basic arithmetic operations on the reduced Jacobian matrix of the load flow model.

Many power systems around the world, specially in developing countries and island-countries, are characterized by weak longitudinal structure. In these power systems it is common to have load nodes electrically distant from generating sources, and voltage problems are closely to system configuration, distribution and balance of reactive power in system elements, and voltage stability is strongly affected by discrete changes in the topology of power network. This paper presents main characteristics of longitudinal power systems and common voltage stability problems are described and illustrated. Voltage stability analysis, in these systems, using static and "snapshot" approaches with application of modal analysis technique and with appropriate device modelling, are presented. The examples included in this paper are based on simulation using real-life longitudinal power system, i.e. a part of the Bosnian Power System which in past two years, and as expected in near future will, has typical longitudinal structure.