MOGUĆNOSTI PRIMENE IOT TEHNOLOGIJE U STOČARSTVU I VETERINI

Internet stvari (eng. Internet of Things, IoT) je niz tehnologija za povezivanje nainternet uređaja kao što su senzori, laboratorijska i druga merna oprema koji prikupljajuinformacije od značaja i njihovo slanje prema serverima smeštenim u oblakuna kojima se vrši agregacija podataka i njihovo pretvaranje u informacije i izveštavanjenad njima prema potrebama različitih zainteresovanih strana. IoT tehnologijazasniva se na projektovanju i izradi vertikalnih rešenja za izveštavanje korisnika sistemao događajima i procesima od interesa. Poslednjih godina razvijeno je niz vertikalnihIoT rešenja u stočarstvu i veterini kojima se omogućavaju telemedicina,totalno praćenje lanaca snabdevanja prehrambenim proizvodima te informacije ozdravstvenom stanju stoke. Kao suštinski revolucionarna tehnologija, IoT bi mogaotransformisati način na koji posluje agrarni sektor, ali i način na koji se kontroliše ivrši upravljanje bezbednošću prehrambenih proizvoda

Information Leakage Games

We consider a game-theoretic setting to model the interplay between attacker and defender in the context of information flow, and to reason about their optimal strategies. In contrast with standard game theory, in our games the utility of a mixed strategy is a convex function of the distribution on the defender's pure actions, rather than the expected value of their utilities. Nevertheless, the important properties of game theory, notably the existence of a Nash equilibrium, still hold for our (zero-sum) leakage games, and we provide algorithms to compute the corresponding optimal strategies. As typical in (simultaneous) game theory, the optimal strategy is usually mixed, i.e., probabilistic, for both the attacker and the defender. From the point of view of information flow, this was to be expected in the case of the defender, since it is well known that randomization at the level of the system design may help to reduce information leaks. Regarding the attacker, however, this seems the first work (w.r.t. the literature in information flow) proving formally that in certain cases the optimal attack strategy is necessarily probabilistic

CORRELATION OF MORPHOLOGIC AND PRODUCTION TRAITS OF HONEY BEE COLONIES FROM SERBIA

Abstract: State of mutual or reciprocal relationship between traits is determined by the correlation coefficients. Correlation of morphological and production traits was determined in two generations of honey bee colonies. In the first generation, mother queen bees were studied, and in the second generation, their offspring. The study of one generation lasted two years. Morphological traits were determined in the beginning of the study and production traits were determined in the spring and autumn inspections of every year. In the first generation, the positive and mostly high correlation between morphological traits, and honey yield and hygienic behaviour was determined. Correlation of morphological traits, colony strength and food supplies per colony ranged from highly positive to slightly negative values. It was found that there was a high correlation between some production traits (colony strength in the spring and autumn inspections and honey yield per colony). In the analysis of offspring (second generation), most traits that were positively correlated in mother generation now, also, showed a similar relationship. The only difference, in contrast to mother generation, was that, for most traits, the intensity of interaction increased

Natural mycobiota and aflatoxin B1 presence in bee pollen collected in Serbia

Total fungal count, incidence of fungi and aflatoxin B1 (AFB1) concentration were studied in 33 samples of bee pollen randomly collected from beekeepers in Serbia. The total number of fungi was determined by dilution method whereas AFB1 was detected using the Enzyme-Linked Immuno-Sorbent Assay (ELISA). The mycological estimation showed the presence of nine genera of fungi as followed: Acremonium, Alternaría, Aspergillus, Cladosporium, Epiccocum, Fusarium, Mucor, Pénicillium and Rhizopus, with total number ranging from 1 x 103 to 1 x 105 CFU g-1. The results have shown the predominance of the fungi from the genera Aspergillus and Alternaria. Among Aspergillus species it was observed that the most frequent species was A. flavus with incidence of 27.27 %. Mycotoxin AFB1 was detected as 100% positive in all samples (100%) with an average concentration of 8.61 μg kg-1. The obtained results indicated that honey bee pollen must be strictly controlled during its manipulation in the harvesting and manufacturing. Therefore, the implementation of good manufacturing (beekeeping) practice to define procedures for honeybee products could be crucial to reduce the risk of possible contamination and provide natural and safety product without risk on the human health

NAJVAŽNIJE BOLESTI PASA I MA9AKA I NOVI TRENDOVI U IMUNOPROFILAKSI

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Approximate policy iteration: A survey and some new methods

We consider the classical policy iteration method of dynamic programming (DP), where approximations and simulation are used to deal with the curse of dimensionality. We survey a number of issues: convergence and rate of convergence of approximate policy evaluation methods, singularity and susceptibility to simulation noise of policy evaluation, exploration issues, constrained and enhanced policy iteration, policy oscillation and chattering, and optimistic and distributed policy iteration. Our discussion of policy evaluation is couched in general terms and aims to unify the available methods in the light of recent research developments and to compare the two main policy evaluation approaches: projected equations and temporal differences (TD), and aggregation. In the context of these approaches, we survey two different types of simulation-based algorithms: matrix inversion methods, such as least-squares temporal difference (LSTD), and iterative methods, such as least-squares policy evaluation (LSPE) and TD (λ), and their scaled variants. We discuss a recent method, based on regression and regularization, which rectifies the unreliability of LSTD for nearly singular projected Bellman equations. An iterative version of this method belongs to the LSPE class of methods and provides the connecting link between LSTD and LSPE. Our discussion of policy improvement focuses on the role of policy oscillation and its effect on performance guarantees. We illustrate that policy evaluation when done by the projected equation/TD approach may lead to policy oscillation, but when done by aggregation it does not. This implies better error bounds and more regular performance for aggregation, at the expense of some loss of generality in cost function representation capability. Hard aggregation provides the connecting link between projected equation/TD-based and aggregation-based policy evaluation, and is characterized by favorable error bounds.National Science Foundation (U.S.) (No.ECCS-0801549)Los Alamos National Laboratory. Information Science and Technology InstituteUnited States. Air Force (No.FA9550-10-1-0412

Advances in low-memory subgradient optimization

One of the main goals in the development of non-smooth optimization is to cope with high dimensional problems by decomposition, duality or Lagrangian relaxation which greatly reduces the number of variables at the cost of worsening differentiability of objective or constraints. Small or medium dimensionality of resulting non-smooth problems allows to use bundle-type algorithms to achieve higher rates of convergence and obtain higher accuracy, which of course came at the cost of additional memory requirements, typically of the order of n2, where n is the number of variables of non-smooth problem. However with the rapid development of more and more sophisticated models in industry, economy, finance, et all such memory requirements are becoming too hard to satisfy. It raised the interest in subgradient-based low-memory algorithms and later developments in this area significantly improved over their early variants still preserving O(n) memory requirements. To review these developments this chapter is devoted to the black-box subgradient algorithms with the minimal requirements for the storage of auxiliary results, which are necessary to execute these algorithms. To provide historical perspective this survey starts with the original result of N.Z. Shor which opened this field with the application to the classical transportation problem. The theoretical complexity bounds for smooth and non-smooth convex and quasi-convex optimization problems are briefly exposed in what follows to introduce to the relevant fundamentals of non-smooth optimization. Special attention in this section is given to the adaptive step-size policy which aims to attain lowest complexity bounds. Unfortunately the non-differentiability of objective function in convex optimization essentially slows down the theoretical low bounds for the rate of convergence in subgradient optimization compared to the smooth case but there are different modern techniques that allow to solve non-smooth convex optimization problems faster then dictate lower complexity bounds. In this work the particular attention is given to Nesterov smoothing technique, Nesterov Universal approach, and Legendre (saddle point) representation approach. The new results on Universal Mirror Prox algorithms represent the original parts of the survey. To demonstrate application of non-smooth convex optimization algorithms for solution of huge-scale extremal problems we consider convex optimization problems with non-smooth functional constraints and propose two adaptive Mirror Descent methods. The first method is of primal-dual variety and proved to be optimal in terms of lower oracle bounds for the class of Lipschitz-continuous convex objective and constraints. The advantages of application of this method to sparse Truss Topology Design problem are discussed in certain details. The second method can be applied for solution of convex and quasi-convex optimization problems and is optimal in a sense of complexity bounds. The conclusion part of the survey contains the important references that characterize recent developments of non-smooth convex optimization

Autonomous mobile robots in manufacturing : Highway Code development, simulation and testing

A dynamic and flexible manufacturing environment presents many challenges in the movement of Autonomous Mobile Robots (AMRs), leading to delays due to the complexity of operations while negotiating even a simple route. Therefore, an understanding of rules related to AMR movement is important both from a utility perspective as well as a safety perspective. Our survey from literature and industry has revealed a gap in methodology to test rules related to AMR movement in a factory environment. Testing purely through simulations would not able to capture the nuances of shop floor interactions whereas physical testing alone would be incredibly time-consuming and potentially hazardous. This work presents a new methodology that can make use of observations of AMR behaviour on selected cases on the shop floor and build up the fidelity of those simulations based on observations. This paper presents the development of a Highway Code for AMRs, development of simulation models for an ideal-AMR (based on the rules from the Highway Code) and physical testing of real-AMR in an industrial environment. Finally, a behavioural comparison of an ideal-AMR and a real-AMR in five scenarios (taken from the shop floor of an industrial partner) is presented. This work could enable informed decisions regarding the implementation of AMRs through identification of any adverse behaviours which could then be mitigated either through improvements on the AMR or through establishing shop floor protocols that reduce the potential impact of these behaviours