Dynamic hierarchical bandwidth allocation using Russian Doll Model in EPON

This paper demonstrates a new hierarchical Dynamic Bandwidth Allocation algorithm using the Russian Doll Model (RDM) to allocate bandwidth for intra-Optical Network Unit (ONU) in an Ethernet Passive Optical Network (EPON). The allocation of bandwidth is based on the classification and prioritization of service. The algorithm addresses the requests of ONUs and provides differentiated services by balancing priority and fairness. The simulation results show that the proposed algorithm performs well in supporting the triple-play services, i.e. video, voice, and data, as well as making effective adjustment in balancing bandwidth sharing between the ONUs compared with two other existing Dynamic Bandwidth Allocation (DBA) algorithm. The proposed algorithms shows significant performance improvements in terms of bandwidth utilization, packet delay and the fairness.     

The effect of heat treatment on high temperature mechanical properties of microalloyed medium carbon steel

In the present work, high temperature tensile properties and abrasive wear performance of a microalloyed medium carbon steel has been examined. Tensile and abrasive wear testing were carried out on as-received and heat treated specimens. The research has shown that microalloyed medium carbon steel was susceptible to dynamic strain ageing due to interaction of mobile dislocations and solid atoms, such as carbon and/or nitrogen. The interaction between dislocations and solid atoms at 200–300 °C changes the work hardening rate and contributes to dynamic strain ageing. These interactions also increased abrasive wear resistance of the microalloyed medium carbon steel at 300 °C. Therefore, the inference can be drawn that dynamic strain ageing caused an improvement on abrasion resistance.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).     

Hypergraph Models and Algorithms for Data-Pattern-Based Clustering

In traditional approaches for clustering market basket type data, relations among transactions are modeled according to the items occurring in these transactions. However, an individual item might induce different relations in different contexts. Since such contexts might be captured by interesting patterns in the overall data, we represent each transaction as a set of patterns through modifying the conventional pattern semantics. By clustering the patterns in the dataset, we infer a clustering of the transactions represented this way. For this, we propose a novel hypergraph model to represent the relations among the patterns. Instead of a local measure that depends only on common items among patterns, we propose a global measure that is based on the cooccurences of these patterns in the overall data. The success of existing hypergraph partitioning based algorithms in other domains depends on sparsity of the hypergraph and explicit objective metrics. For this, we propose a two-phase clustering approach for the above hypergraph, which is expected to be dense. In the first phase, the vertices of the hypergraph are merged in a multilevel algorithm to obtain large number of high quality clusters. Here, we propose new quality metrics for merging decisions in hypergraph clustering specifically for this domain. In order to enable the use of existing metrics in the second phase, we introduce a vertex-to-cluster affinity concept to devise a method for constructing a sparse hypergraph based on the obtained clustering. The experiments we have performed show the effectiveness of the proposed framework.     

Power Flattening in ARIES-RS Fusion Breeder Reactor Using Mixed Fuels

This study presents the possibility of the power flattening in the ARIES-RS breeder reactor using mixed (Th,U)C or (Th,U)N fuels. Two different types of mixing, namely, homogeneous mixing (HM) and linear mixing (LM) were used to investigate the uniformity of fission power distribution through the fuel zone. In HM, fraction of uranium content were kept constant in all rows of the fuel zone whereas, in LM the fraction of the uranium were linearly increased from the first to last fuel row in the fuel zone. Neutron transport calculations were performed with the aid of the SCALE4.3 system by solving the Boltzmann transport equation with the XSDRNPM code in 238 neutron groups and a S₈–P₃ approximation. Flat fission power distribution was maintained successfully for the blanket using linearly mixed fuels. However, the fission density profile was not uniform in the blanket with homogeneously mixed fuels. It decreased exponentially form the 1st to 10th fuel row.     

Radioactivity concentrations in soil and dose assessment for Samsun City Centre, Turkey

In this study, natural gamma radioactivity levels were determined in the soil samples of the Samsun city centre by using the gamma ray spectrometry method. The analysis carried out with the high-purity germanium gamma spectrometry system has shown that average activity concentrations of (238)U, (232)Th, (40)K and (137)Cs were 19±2, 22±4, 521±23 and 15±1 Bq kg(-1), respectively. From the gamma analysis of soil samples, the average value of the absorbed gamma dose rates in air and the average value of the external annual effective dose rates were calculated as 45±4 nGy h(-1) and 55±5 μSv y(-1), respectively. The external hazard index has also been calculated and it has been found that the radiation hazard in Samsun is insignificant.     

Perinatal Obesity Induces Hepatic Growth Restriction with Increased DNA Damage Response,Senescence, and Dysregulated Igf-1-Akt-Foxo1 Signaling in Male Offspring of Obese Mice

Maternal obesity predisposes for hepato-metabolic disorders early in life. However, the underlying mechanisms causing early onset dysfunction of the liver and metabolism remain elusive. Since obesity is associated with subacute chronic inflammation and accelerated aging, we test the hypothesis whether maternal obesity induces aging processes in the developing liver and determines thereby hepatic growth. To this end, maternal obesity was induced with high-fat diet (HFD) in C57BL/6N mice and male offspring were studied at the end of the lactation [postnatal day 21 (P21)]. Maternal obesity induced an obese body composition with metabolic inflammation and a marked hepatic growth restriction in the male offspring at P21. Proteomic and molecular analyses revealed three interrelated mechanisms that might account for the impaired hepatic growth pattern, indicating prematurely induced aging processes: (1) Increased DNA damage response (γH2AX), (2) significant upregulation of hepatocellular senescence markers (Cdnk1a, Cdkn2a); and (3) inhibition of hepatic insulin/insulin-like growth factor (IGF)-1-AKT-p38-FoxO1 signaling with an insufficient proliferative growth response. In conclusion, our murine data demonstrate that perinatal obesity induces an obese body composition in male offspring with hepatic growth restriction through a possible premature hepatic aging that is indicated by a pathologic sequence of inflammation, DNA damage, senescence, and signs of a possibly insufficient regenerative capacity.     

A minisum location problem with regional demand considering farthest Euclidean distances

We consider a continuous multi-facility location-allocation problem that aims to minimize the sum of weighted farthest Euclidean distances between (closed convex) polygonal and/or circular demand regions, and facilities they are assigned to. We show that the single facility version of the problem has a straightforward second-order cone programming formulation and can therefore be efficiently solved to optimality. To solve large size instances, we adapt a multi-dimensional direct search descent algorithm to our problem which is not guaranteed to find the optimal solution. In a special case with circular and rectangular demand regions, this algorithm, if converges, finds the optimal solution. We also apply a simple subgradient method to the problem. Furthermore, we review the algorithms proposed for the problem in the literature and compare all these algorithms in terms of both solution quality and time. Finally, we consider the multi-facility version of the problem and model it as a mixed integer second-order cone programming problem. As this formulation is weak, we use the alternate location-allocation heuristic to solve large size instances.     

Renewable and Storage Energy Integration for Smart Grid Housing

This paper presents the design,implementation and testing of an embedded system that integrates solar and storage energy resources to smart homes within the smart microgrid.The proposed system provides the required home energy by installing renewable energy and storage devices.It also manages and schedules the power flow during peak and off-peak periods.In addition,a two-way communication protocol is developed to enable the home owners and the utility service provider to improve the energy flow and the consumption efficiency.The system can be an integral part for homes in a smart grid or smart microgrid power networks.A prototype for the proposed system was designed,implemented and tested by using a controlled load bank to simulate a scaled random real house consumption behavior.Three different scenarios were tested and the results and findings are reported.Moreover,data flow security among the home,home owners and utility server is developed to minimize cyber-attacks.