Element concentration and fatty acid composition of Serbian bee bread

The element concentration (Cu, Fe, Zn, Mn, Cr, Co, Ni, Se, K, Na, Ca and Mg), heavy metal concentration (Cd, Hg, Pb and As) and fatty acid composition of 12 Serbian bee bread samples from different geographical origins were examined. The element concentration was examined using ICP-MS, and total lipids for fatty acid determination were extracted from homogenized bee bread samples with hexane/isopropanol mixture by accelerated solvent extraction. Potassium was the major element, ranging between 5515 +/- 361.20 mg/kg and 7487 +/- 381.50 mg/kg. The highest As and Pb concentrations were found in bee breads from Lazarevac. This bee bread also contained the highest level of PUFA and SFA. Also, the n-6/n-3 ratio ranged between 0.86 +/- 0.28 and 1.40 +/- 0.05, indicating bee bread can be a good source of unsaturated fatty acids. Bee bread could be useful in monitoring environmental contamination by heavy metals (Cd, Hg, Pb and As), although complex studies of all bee products give sufficient information on this topic

Contribution of Osmotically Dehydrated Wild Garlic on Biscuits' Quality Parameters

Wild garlic generally improves strengths and regenerates the body and also helps in the treatment of various diseases. In this study the contribution of wild garlic osmotic dehydration process in sugar beet molasses on biscuits' quality parameters is investigated. Presented results showed that addition of osmotically dehydrated wild garlic in molasses impoved textural characteristics of biscuits by lowering hardness and increasing fracturability and also changed colour characteristics of biscuits. Chemical composition of biscuits with added osmotically dehydrated wild garlic was improved in comparison to the biscuits with added fresh wild garlic, where proteins, total sugars, celulose and ash compositions were increased in amounts of 1.86, 3.2, 15.8 and 5.76 % respectively. Addition of osmodehydrated wild garlic had provided higher Zn, Cu and Fe biscuits' content in comparison to the addition of fresh wild garlic, in amounts of 2.75, 15.33 and 15.84 % respectively. Developed mathematical models of biscuits quality parameters were statistically significant, while predicted and observed responses corresponded very well. In effort of obtaining new types of products, new application of known ingredients was proposed, allowing incorporation of sugar beet molasses' rich nutrient content in wheat products formulation

Application of Multi-Agent Systems and Particle Swarm Optimization Algorithm for Flexible Process Planning

Sistemi zasnovani na agentima primenju se za razvoj društvenih, bioloških i tehničkih sistema. U domenu tehničkih sistema, svoju primenu nalaze i u rešavanju problema optimizacije savremenih tehnoloških sistema. U radu je predstavljena razvijena multiagentna metodologija za optimalno projektovanje tehnoloških procesa obrade dela. Predložena multiagentna arhitehtura se sastoji od četiri agenta: agent za delove, agent za mašine, agent za transport i agent za optimizaciju. Nakon generisanja optimalnih tehnoloških procesa primenom biološki inspirisanog algoritma na bazi inteligencije roja čestica, u AnyLogic softverskom paketu je izvršena simulacija primenom razvijenih agenata. Eksperimentalni rezultati pokazuju opravdanost primene predložene metodologije u simuliranom modelu tehnološkog okruženja.Agent based systems have been used for the development of social, biological, and technical systems. In the domain of technical systems, they are widely applied in optimization problems of modern manufacturing systems. This paper presents multi-agent methodology for optimal process planning. The proposed multi-agent architecture consists of four intelligent agents: job/part agent, machine agent, transport agent, and optimization agent. After generation of optimal process plans, agent based simulation was performed using AnyLogic software. Use of applied method has been justified by experimental results in simulated model of manufacturing environment

Application of Multi-Agent Systems and Particle Swarm Optimization Algorithm for Flexible Process Planning

Sistemi zasnovani na agentima primenju se za razvoj društvenih, bioloških i tehničkih sistema. U domenu tehničkih sistema, svoju primenu nalaze i u rešavanju problema optimizacije savremenih tehnoloških sistema. U radu je predstavljena razvijena multiagentna metodologija za optimalno projektovanje tehnoloških procesa obrade dela. Predložena multiagentna arhitehtura se sastoji od četiri agenta: agent za delove, agent za mašine, agent za transport i agent za optimizaciju. Nakon generisanja optimalnih tehnoloških procesa primenom biološki inspirisanog algoritma na bazi inteligencije roja čestica, u AnyLogic softverskom paketu je izvršena simulacija primenom razvijenih agenata. Eksperimentalni rezultati pokazuju opravdanost primene predložene metodologije u simuliranom modelu tehnološkog okruženja.Agent based systems have been used for the development of social, biological, and technical systems. In the domain of technical systems, they are widely applied in optimization problems of modern manufacturing systems. This paper presents multi-agent methodology for optimal process planning. The proposed multi-agent architecture consists of four intelligent agents: job/part agent, machine agent, transport agent, and optimization agent. After generation of optimal process plans, agent based simulation was performed using AnyLogic software. Use of applied method has been justified by experimental results in simulated model of manufacturing environment

Changes in total viable count and TVB-N content in marinated chicken breast fillets during storage

Marination is a popular technique for enhancing meat properties. Depending on the marinade type and ingredients added, marination can improve sensory, chemical and microbiological quality of meat products. In this study, the total viable count and total volatile basic nitrogen (TVB-N) content in marinated chicken breast fillets were investigated. The possible correlation between bacterial growth and formation of TVB-N was also tested. Chicken breast fillets were immersed in a solution of table salt (as a control) orthree different marinades, which consisted of table salt, sodium tripolyphosphate and/or sodium citrate, and stored in air for nine days at 4 +/- 1 degrees C. Analyses of the total viable count and TVB-N were performed on days0, 3, 6 and 9 day of storage. The total viable count gradually increased in all examined groups, and statistically significant differences (p<0.01; p<0.05) between treatments on days0, 3 and 6 day of storage were established. TVB-N values in marinated chicken were significantly higher (p<0.01; p<0.05) compared to the control. Using the multiple linear regression, a positive correlation between total viable count and formation of TVB-N in chicken marinated with sodium citrate was established (p<0.05), while the intensity of TVB-N formation was lowest in chicken marinated with sodium tripolyphosphate

Comparison of two analytical methods (ELISA and LC-MS/MS) for determination of aflatoxin B-1 in corn and aflatoxin M-1 in milk

The aim of this paper is to assess the closeness of agreement between results of ELISA and LC-MS/MS methods for determination of aflatoxin B-1 in corn and aflatoxin M-1 in milk. Samples of corn (n=100) and milk (n=250) were simultaneously analyzed using ELISA and LC-MS/MS methods, after the severe drought that affected Serbia in summer 2012 resulting in occurrence of aflatoxin B1 in corn and aflatoxin M-1 in milk. Regression analysis showed higher level of agreement between aflatoxin B-1 samples (R2=0.994), compared to aflatoxin M-1 samples (r(2)=0.920). However, both techniques were satisfactory in meeting the requirements for official control purposes

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Integration of Process Planning and Scheduling Using Modified Particle Swarm Optimization Algorithm

Process planning and scheduling are two of the most important manufacturing functions which are usually performed sequentially in traditional approaches. Considering the fact that these functions are usually complementary, it is necessary to integrate them so as to improve performance of a manufacturing system. This paper conceptualizes a multi-agent methodology by considering four intelligent agents (job, machine, tool, and optimization agent) and presents developed modified particle swarm optimization (mPSO) algorithm to solve this combinatorial optimization problem effectively. In order to improve the search efficiency and increase ability to find global optimum, proposed mPSO algorithm has been enhanced with new crossover and mutation operators. Experimental results show applicability of the proposed approach in solving integrated process planning and scheduling problem

Multi-agent and Holonic Manufacturing Systems for Process Plannong and Scheduling

Projektovanje tehnoloških procesa predstavlja određivanje postupka proizvodnje uz zadovoljenje prethodno definisanih ciljeva i ograničenja. Terminiranjem proizvodnje se na osnovu proizvodnog plana i prethodno određenih tehnoloških postupaka dodeljuju optimalni proizvodni resursi za odgovarajući vremenski period. Uvođenjem koncepta masovne kastomizacije, već ranije ključne funkcije, projektovanje i terminiranje proizvodnje, sada imaju krucijalnu ulogu u tehnološkom sistemu zbog sve većih zahteva koje se pred ove funkcije postavljaju. Rad se bavi uvođenjem koncepta multiagentnih i holon tehnoloških sistema uz pregled stanja u oblasti projektovanja tehnoloških procesa i terminiranja proizvodnje. Radom je obuhvaćen tradicionalni, sledstveni, pristup projektovanju i terminiranju, ali i integrisan prilaz problematici.Process planning can be defined as determination of manufacturing processes by achieving its goals and constraints. Scheduling process assigns optimal manufacturing resources over time based on production plan and previously determined process plans. With the mass customization concept, previously key functions in the production, process planning and scheduling, now become crucial for satisfaction of more demanding requirements. The paper introduces the concepts of multi-agent and holonic manufacturing systems and presents state of the process planning and scheduling area of research. It gives an overview on both, sequential and integrated, process planning and scheduling

Particle Swarm Optimization Algorithm and Chaos Theory for Integration of Process Planning and Scheduling

U radu je prikazan pristup za integrisano projektovanje i terminiranje fleksibilnih teholoških procesa obrade delova primenom algoritma baziranog na inteligenciji roja čestica i teoriji haosa (cPSO algoritam). Pored metoda kodiranja/dekodiranja parametara planova terminiranja u jedinke cPSO algoritma, u radu je predložen matematički model za minimizaciju ukupnog vremena za obradu svih delova čije se terminiranje vrši, maksimizaciju uravnoteženog iskorišćenja mašina alatki i minimizaciju transportnih tokova materijala. Takođe, u cilju prevazilaženja nedostataka vezanih za brzu konvergenciju algoritma u ranim fazama optimizacije, predložena je implementacija haotičnih mapa u PSO algoritam. Predloženi pristup je eksperimentalno verifikovan na primeru dobijanja optimalnih planova terminiranja realnih delova.This paper presents an approach for integration of process planning and scheduling based on the particle swarm optimization algorithm and chaos theory (cPSO). Besides scheduling plans representation and particle encoding/decoding scheme, mathematical model for the minimization of makespan, maximization of balanced level of machine utilization and minimization of mean flow time was presented. Also, we proposed implementation of chaotic maps in PSO algorithm in order to prevent algorithm from converging prematurely. Experimental verification of the proposed algorithm was done through the optimal scheduling of real parts