Resource efficient network design and traffic grooming strategy with guaranteed survivability

In WDM networks, path protection has emerged as a widely accepted technique for providing guaranteed survivability of network traffic. However, it requires allocating resources for backup lightpaths, which remain idle under normal fault-free conditions. In this paper, we introduce a new design strategy for survivable network design, which guarantees survivability of all ongoing connections that requires significantly fewer network resources than protection based techniques. In survivable routing, the goal is to find a Route and Wavelength Assignment (RWA) such that the logical topology remains connected for all single link failures. However, even if the logical topology remains connected after any single link fault, it may not have sufficient capacity to support all the requests for data communication, for all single fault scenarios. To address this deficiency, we have proposed two independent but related problem formulations. To handle our first formulation, we have presented an Integer Linear Program (ILP) that augments the concept of survivable routing by allowing rerouting of sub-wavelength traffic carried on each lightpath and finding an RWA that maximizes the amount of traffic that can be supported by the network in the presence of any single link failure. To handle our second formulation, we have proposed a new design approach that integrates the topology design and the RWA in such a way that the resulting logical topology is able to handle the entire set of traffic requests after any single link failure. For the second problem, we have first presented an ILP formulation for optimally designing a survivable logical topology, and then proposed a heuristic for larger networks. Experimental results demonstrate that this new approach is able to provide guaranteed bandwidth, and is much more efficient in terms of resource utilization, compared to both dedicated and shared path protection schemes.     

Recognition of cigarette brand names and logos by primary schoolchildren in Ankara, Turkey

OBJECTIVE: To assess the smoking behaviour of primary schoolchildren and their ability to recognise brand names and logos of widely advertised cigarettes, compared with other commercial products intended for children. DESIGN: Cross-sectional survey in classroom settings using a questionnaire designed to measure attitudes towards smoking and the recognition of brand names and logos for 16 food, beverage, cigarette, and toothpaste products. SETTING: Ankara, Turkey. SUBJECTS: 1093 children (54.6% boys, 44.4% girls) aged 7-13 years (mean = 10, SD = 1), from grades 2-5. The student sample was taken from three primary schools--one school in each of three residential districts representing high, middle, and low income populations. MAIN OUTCOME MEASURES: Prevalence of ever-smoking, recognition of brand names and logos. RESULTS: Prevalence of ever-smoking was 11.7% overall (13.9% among boys and 9.1% among girls; p < 0.05). Children aged eight years or less had a higher prevalence of ever-smoking (19.6%) than older children (p < 0.002). Ever-smoking prevalence did not differ significantly across the three school districts. Ever-smoking prevalence was higher among children with at least one parent who smoked (15.3%) than among those whose parents did not (4.8%) (p < 0.001). Brand recognition rates ranged from 58.1% for Chee-tos (a food product) to 95.2% for Samsun (a Turkish cigarette brand). Recognition rates for cigarette brand names and logos were 95.2% and 80.8%, respectively, for Samsun; 84.0% and 90.5%, respectively, for Camel; and 92.1% and 69.5%, respectively, for Marlboro. The Camel logo and the Samsun and Marlboro brand names were the most highly recognised of all product logos and brand names tested. CONCLUSIONS: The high recognition of cigarette brand names and logos is most likely the result of tobacco advertising and promotion. Our results indicate the need to implement comprehensive tobacco control measures in Turkey.     

Effects of nanowollastonite on biological resistance of medium-density fiberboard against Antrodia vaillantii

The effect of wollastonite nanofibers (NW) on biological resistance of medium-density fiberboards (MDF) made from wood and chicken-feather fibers (CF) against Antrodia vaillantii was studied. NW content of 10 % and CF content of 5 and 10 %, based on the dry weight of wood fibers, were applied to the MDF matrix, giving a total of six different MDF mixing treatments. Mass loss values were measured roughly following the EN 113 specifications. The results showed that NW significantly decreased mass loss to a considerable extent in all mixing ratios, proving its potential to be used as a suitable preservative in wood-composite materials without environmental hazards. A CF content of 5 % showed improving effects on biological resistance, while CF of 10 % was too high and resulted in a weak MDF-matrix; eventually the biological resistance did not improve properly. NW ameliorated part of the undesirable effect of adding chicken feather fibers to the MDF-matrix. A significantly high correlation was found between mass loss versus water absorption (R ² of 81 %), implying that the penetration of water and fungal hyphae can have rather similar patterns. It can be concluded that NW not only can be used to improve the biological resistance in wood-composite materials against fungi attack, but it can also reduce some of the undesirable properties of chicken feathers, thus providing a reliable and renewable resource for natural fibers to be used in the MDF manufacturing industry.     

The lithium intercalation process in the low-voltage lithium battery anode Li(1+x)V(1-x)O2

Lithium can be reversibly intercalated into layered Li(1+x)V(1-x)O(2) (LiCoO(2) structure) at ~0.1 V, but only if x>0. The low voltage combined with a higher density than graphite results in a higher theoretical volumetric energy density; important for future applications in portable electronics and electric vehicles. Here we investigate the crucial question, why Li cannot intercalate into LiVO(2) but Li-rich compositions switch on intercalation at an unprecedented low voltage for an oxide? We show that Li(+) intercalated into tetrahedral sites are energetically more stable for Li-rich compositions, as they share a face with Li(+) on the V site in the transition metal layers. Li incorporation triggers shearing of the oxide layers from cubic to hexagonal packing because the Li(2)VO(2) structure can accommodate two Li per formula unit in tetrahedral sites without face sharing. Such understanding is important for the future design and optimization of low-voltage intercalation anodes for lithium batteries.     

A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems

For more than three decades, similarity coefficient measures one of the important tools for solving group technology problems have gained the attention of the research community in cellular manufacturing systems. A new similarity coefficient measure that uses a set of important characteristic properties for grouping is developed here for use as an intermediate tool to form cohesive cells. A mathematical model that uses this similarity coefficient for optimally solving the cell-formation problems in cellular manufacturing is developed. A heuristic procedure that improves the optimal methodology in term of solution capability of the large instances is devised for an efficient solution. Both the optimal methodology and the heuristic are applied to some well-known problems from literature to compare the grouping efficiencies. The similarity coefficient and the solution methodologies developed are able to solve the cell formation problems efficiently.     

Securing Wireless Sensor Networks Against Denial‐of‐Sleep Attacks Using RSA Cryptography Algorithm and Interlock Protocol

Wireless sensor networks (WSNs) have been vastly employed in the collection and transmission of data via wireless networks. This type of network is nowadays used in many applications for surveillance activities in various environments due to its low cost and easy communications. In these networks, the sensors use a limited power source which after its depletion, since it is non‐renewable, network lifetime ends. Due to the weaknesses in sensor nodes, they are vulnerable to many threats. One notable attack threating WSN is Denial of Sleep (DoS). DoS attacks denotes the loss of energy in these sensors by keeping the nodes from going into sleep and energy‐saving mode. In this paper, the Abnormal Sensor Detection Accuracy (ASDA‐RSA) method is utilized to counteract DoS attacks to reducing the amount of energy consumed. The ASDA‐RSA schema in this paper consists of two phases to enhancement security in the WSNs. In the first phase, a clustering approach based on energy and distance is used to select the proper cluster head and in the second phase, the RSA cryptography algorithm and interlock protocol are used here along with an authentication method, to prevent DoS attacks. Moreover, ASDA‐RSA method is evaluated here via extensive simulations carried out in NS‐2. The simulation results indicate that the WSN network performance metrics are improved in terms of average throughput, Packet Delivery Ratio (PDR), network lifetime, detection ratio, and average residual energy.     

No-but-semantic-match: computing semantically matched xml keyword search results

Users are rarely familiar with the content of a data source they are querying, and therefore cannot avoid using keywords that do not exist in the data source. Traditional systems may respond with an empty result, causing dissatisfaction, while the data source in effect holds semantically related content. In this paper we study this no-but-semantic-match problem on XML keyword search and propose a solution which enables us to present the top-k semantically related results to the user. Our solution involves two steps: (a) extracting semantically related candidate queries from the original query and (b) processing candidate queries and retrieving the top-k semantically related results. Candidate queries are generated by replacement of non-mapped keywords with candidate keywords obtained from an ontological knowledge base. Candidate results are scored using their cohesiveness and their similarity to the original query. Since the number of queries to process can be large, with each result having to be analyzed, we propose pruning techniques to retrieve the top-k results efficiently. We develop two query processing algorithms based on our pruning techniques. Further, we exploit a property of the candidate queries to propose a technique for processing multiple queries in batch, which improves the performance substantially. Extensive experiments on two real datasets verify the effectiveness and efficiency of the proposed approaches.     

DimSUM: Dimension and Scale Unifying Map for Visual Abstraction of DNA Origami Structures

We present a novel visualization concept for DNA origami structures that integrates a multitude of representations into a Dimension and Scale Unifying Map (DimSUM). This novel abstraction map provides means to analyze, smoothly transition between, and interact with many visual representations of the DNA origami structures in an effective way that was not possible before. DNA origami structures are nanoscale objects, which are challenging to model in silico. In our holistic approach we seamlessly combine three‐dimensional realistic shape models, two‐dimensional diagrammatic representations, and ordered alignments in one‐dimensional arrangements, with semantic transitions across many scales. To navigate through this large, two‐dimensional abstraction map we highlight locations that users frequently visit for certain tasks and datasets. Particularly interesting viewpoints can be explicitly saved to optimize the workflow. We have developed DimSUM together with domain scientists specialized in DNA nanotechnology. In the paper we discuss our design decisions for both the visualization and the interaction techniques. We demonstrate two practical use cases in which our approach increases the specialists’ understanding and improves their effectiveness in the analysis. Finally, we discuss the implications of our concept for the use of controlled abstraction in visualization in general.     

Development of a bio-physicochemical technique for arsenic removal from groundwater

Oxidation of ferrous ions by iron-oxidizing bacteria facilitates adsorption of arsenic on iron and subsequent co-precipitation. Based on this technique, a novel treatment process has been developed and tested under field conditions for simultaneous iron and arsenic removal from groundwater. In this study, a biological fixed bed reactor containing coconut husk and subsequent layers of iron matrix, charcoal and sand filter combined the biological and physicochemical treatment processes in a single system. Experimental results showed that arsenic could be efficiently treated from initial concentration of 500 μg L^− 1 to residual (effluent) concentrations lower than 15 μg L^− 1. Simultaneous significant iron removal efficiency (over 95%) was also achieved. Microbial water quality examination confirmed absence of any contamination in the treated water. Simple and inexpensive construction using locally available materials, considerable treatment performance as well as ease of operation and maintenance present the developed system as a promising one.