Using combined keying materials for key distribution in wireless sensor networks

In this paper, we propose a probabilistic key predistribution scheme for wireless sensor networks that increases connectivity of the basic scheme while keeping sizes of keyring and key pool fixed. We introduce the concept of XORed key, which is the bitwise XOR of two regular (a.k.a. single) keys. Sensor nodes are preloaded with a mixture of single and XORed keys. Nodes establish secure links by using shared XORed keys whenever possible. If node pairs do not have any shared XORed or single keys, they transfer keys from their secure neighbors in a couple of ways, and use them to match with their XORed keys. In this way, the probability of securing links, i.e. local connectivity, increases. The decision of which key is to be transferred from which node is given based on local information at the hand of the nodes. We aim to control the resilience of the network against node capture attacks by using XORed keys since an attacker has to know either both single key operands or the XORed key itself. Simulations show that our scheme is up to 50% more connected as compared to basic scheme. Also it has better resilience performance at the beginning of a node capture attack. When it starts to deteriorate, the difference between the resilience of our proposed scheme and basic scheme is not greater than 5%

A resilient key predistribution scheme for multiphase wireless sensor networks

In wireless sensor networks, sensor nodes eventually die due to battery depletion. Wireless sensor networks (WSNs) in which new nodes are periodically redeployed with certain intervals, called generations, to replace the dead nodes are called multi-phase wireless sensor networks. In the literature, there are several key predistribution schemes proposed for secure operation of WSNs. However, these schemes are designed for single phase networks which are not resilient against continuous node capture attacks; even under temporary attacks on the network, the harm caused by the attacker does not heal in time. However, the periodic deployments in multi-phase sensor networks could be utilized to improve the resiliency of the WSNs by deploying nodes with fresh keys. In the literature, there is limited work done in this area. In this paper, we propose a key predistribution scheme for multi-phase wireless sensor networks which is highly resilient under node capture attacks. In our scheme, called RGM (random generation material) key predistribution scheme, each generation of deployment has its own random keying material and pairwise keys are established between node pairs of particular generations. These keys are specific to these generations. Therefore, a captured node cannot be abused to obtain keys of other generations. We compare the performance of our RGM scheme with a well-known multi-phase key predistribution scheme and showed that RGM achieves up to three-fold more resiliency. Even under heavy attacks, our scheme's resiliency performance is 50% better in steady state

An integrated variable speed limit and ALINEA ramp metering model in the presence of High Bus Volume

Under many circumstances, when providing full bus priority methods, urban transport officials have to operate buses in mixed traffic based on their road network limitations. In the case of Istanbul’s Metrobus lane, for instance, when the route comes to the pre-designed Bosphorus Bridge, it has no choice but to merge with highway mixed traffic until it gets to the other side. Much has been written on the relative success of implementing Ramp Metering (RM), for example ALINEA (‘Asservissement line´ aire d’entre´ e autoroutie’) and Variable Speed Limits (VSL), two of the most widely-used “merging congestion” management strategies, in both a separate and combined manner. However, there has been no detailed study regarding the combination of these systems in the face of high bus volume. This being the case, the ultimate goal of this study is to bridge this gap by developing and proposing a combination of VSL and RM strategies in the presence of high bus volume (VSL+ALINEA/B). The proposed model has been coded using microscopic simulation software—VISSIM—and its vehicle actuated programming (VAP) feature; referred to as VisVAP. For current traffic conditions, the proposed model is able to improve total travel time by 9.0%, lower the number of average delays of mixed traffic and buses by 29.1% and 81.5% respectively, increase average speed by 12.7%, boost bottleneck throughout by 2.8%, and lower fuel consumption, Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Volatile Organic Compounds (VOC) emissions by 17.3% compared to the existing “VSL+ALINEA” model. The results of the scenario analysis confirmed that the proposed model is not only able to decrease delay times on the Metrobus system but is also able to improve the adverse effects of high bus volume when subject to adjacent mixed traffic flow along highway sections

Resilient and highly connected key predistribution schemes for wireless sensor networks

Wireless sensor networks are composed of small, battery-powered devices called sensor nodes with restricted data processing, storage capabilities. Sensor nodes collect environmental data, such as temperature, humidity, light conditions, and transmit them using their integrated radio communication interface. In real life scenarios, the exact position of a node is not determined prior to deployment because their deployment methods are arbitrary. Wireless sensor networks may be used for critical operations such as military tracking, scientific and medical experiments. Sensor nodes may carry sensitive information. In such cases, securing communication between sensor nodes becomes an essential problem. Sensor nodes may easily be impersonated and compromised by malicious parties. In order to prevent this, there is a need for some cryptographic infrastructure. Public key cryptography is infeasible for sensor nodes with limited computation power. Hence symmetric key cryptography mechanisms are applied in order to provide security foundations. Due to resource constraints in sensor nodes, best solution seems to be symmetric key distribution prior to deployment. For each node, a number of keys are drawn uniformly random without replacement from a pool of symmetric keys and loaded in the node’s memory. After deployment, neighboring sensor nodes may share a key with a certain probability since all the keys are drawn from the same key pool. This is the basic idea of key predistribution schemes in wireless sensor networks. Also there are more advanced deployment models that take the change of network in time into consideration. The nodes are powered by batteries and the batteries eventually deplete in time. However the network needs to operate longer than the lifetime of a single node. In order to provide continuity, nodes are deployed and integrated in the network at different times along the operation of the network. These networks are called multiphase wireless sensor networks. The main challenge of these networks is to provide connectivity between node pairs deployed at different times. In this thesis, we proposed three different key predistribution schemes. In the first scheme, we introduce the concept of XORed key, which is the bitwise XOR of two regular (a.k.a single) keys. Sensor nodes are preloaded with a mixture of single and XORed keys. Nodes establish secure links by shared XORed keys if they can. If no shared XORed key exists between two neighboring nodes, they try single keys loaded in their memory. If node pairs do not have any shared XORed or single keys, they transfer keys from their secure neighbors in a couple of ways, and use them to match with their XORed keys. In this scheme, we aim to have a more resilient network to malicious activities by using XORed keys since an attacker has to know either both single key operands or the XORed key itself. We performed several simulations of our scheme and compared it with basic scheme [4]. Our scheme is up to 50% more connected as compared to basic scheme. Also it has better resilience performance at the beginning of a node capture attack and when it starts to deteriorate the difference between the resilience of our proposed scheme and basic scheme is not greater than 5%. The second scheme that we proposed is actually an extension that can be applied to most of the schemes. We propose an additional phase that is performed right after shared keys between neighboring nodes are discovered. As mentioned above, neighboring node pairs share a common key with a certain probability. Obviously some neighboring node pairs fail to find any shared key. In our proposed new phase, keys preloaded in memories of secure neighbors of a node a are transferred to a, if necessary, in order for a to establish new links with its neighboring nodes that they do not share any key. In this way, we achieve the same connectivity with traditional schemes with significantly fewer keys. We compared the performance of our scheme with basic scheme [4] after shared-key discovery phase and our results showed that our scheme achieved the same local connectivity performance with basic scheme, moreover while doing that, nodes in our scheme are loaded with three fourth of keys fewer than the keys loaded in nodes in basic scheme. In addition to that, our scheme is up to 50% more resilient than basic scheme with shared-key discovery phase under node capture attacks. The last scheme that we proposed is designed to be used for multi-phase wireless sensor networks. In our model, nodes are deployed at the beginning of some time epochs, called generations, in order to replace the dead nodes. Each generation has completely different key pool. Nodes are predistributed keys drawn uniformly random from key pools of different generations in order to have secure communication with nodes deployed at those generations. In other words, in our scheme keys are specific to generation pairs. This makes the job of attacker more difficult and improves the resiliency of our scheme. We compared our scheme to another key predistribution scheme designed for multi-phase wireless sensor networks. Our results showed that our scheme is up to 35% resilient in steady state even under heavy attacks

Exploring equity in public transportation planning using smart card data

Existing public transport (PT) planning methods use a trip-based approach, rather than a user-based approach, leading to neglecting equity. In other words, the impacts of regular users—i.e., users with higher trip rates—are overrepresented during analysis and modelling because of higher trip rates. In contrast to the existing studies, this study aims to show the actual demand characteristic and users’ share are different in daily and monthly data. For this, 1-month of smart card data from the Kocaeli, Turkey, was evaluated by means of specific variables, such as boarding frequency, cardholder types, and the number of users, as well as a breakdown of the number of days traveled by each user set. Results show that the proportion of regular PT users to total users in 1 workday, is higher than the monthly proportion of regular PT users to total users. Accordingly, users who have 16–21 days boarding frequency are 16% of the total users, and yet they have been overrepresented by 39% in the 1-day analysis. Moreover, users who have 1–6 days boarding frequency, have a share of 66% in the 1-month dataset and are underrepresented with a share of 22% in the 1-day analysis. Results indicated that the daily travel data without information related to the day-to-day frequency of trips and PT use caused incorrect estimation of real PT demand. Moreover, user-based analyzing approach over a month prepares the more realistic basis for transportation planning, design, and prioritization of transport investments

Simulation supported analytic hierar-chy approach in public transport mode selection

Ulaştırma yatırımları ve özellikle de kentiçi koridorlarda gerçekleştirilecek olan toplu taşıma yatırımlarında hangi ulaştırma türünün tercih edileceği son derece önemli bir karardır. Bu tercihte bir bölümü nicel bir bölümü ise nitel olan pek çok faktör etkili olur. Ölçüt olarak kabul edilen bu faktörlerin hepsinin birlikte değerlendirmede etkili olmasını sağlayacak yöntemlerden bir tanesi, bir çok ölçütlü karar verme yöntemi olan analitik hiyerarşi yöntemidir. Bu çalışmada bir kentiçi koridorda, hangi toplu taşıma sisteminin uygulanması gerektiğine ilişkin verilecek olan karar süreci için analitik hiyerarşi yöntemi uygulanmıştır. Öte yandan, toplu taşıma türünün seçimi, seçenek türlerin performanslarının koşullara göre nasıl değişeceği öngörülerek yapılmalıdır. Toplu taşıma sistemlerinde performans göstergelerinden önemli bir tanesi taşıtların yolculuk süreleridir. Taşıtların yolculuk süreleri bir dizi etmene göre değişmektedir. Değişen yolcu talebi, durak aralıkları, ödeme türü ve buna bağlı olarak ödeme süresi, taşıt hızı, yolcuların taşıtlara biniş ve iniş süresi gibi koşullara göre toplu taşıma sistemlerinin performanslarının nasıl değiştiğini görebilmek için bu çalışmada bir simülasyon modeli geliştirilmiştir. Bu simülasyon modeli ile elde edilen sonuçlar, toplu taşıma türleri arasında seçim yapılması amacıyla kullanılan analitik hiyerarşi yöntemine uyarlanmıştır. Analitik hiyerarşi yönteminde, toplu taşıma türü seçimi için göz önüne alınacak diğer ölçütler belirlenmiştir. Ölçütlerin kendi aralarında ve iki toplu taşıma türü seçeneği için ağırlıkları anket ve sayısal değerlerin karşılaştırılması ile saptanmıştır. Bu simülasyon destekli analitik hiyerarşi yöntemi, İstanbul kenti içerisindeki iki koridorda “otobüs yolu” ve “tramvay” seçenekleri için uygulanmıştır.Anahtar Kelimeler: Toplu taşıma, simülasyon, çok ölçütlü karar verme, analitik hiyerarşi yöntemi.Critical decisions that are taken at the stage of planning new transportation investments or improving present transportation systems usually turn out to be selecting one alternative among others. The most important condition in transport mode selection is to make a comparison between different alternatives. This comparison stage is perhaps the most precision-requiring stage in the transport mode selection process. The comparison process has many difficulties. The foremost difficulty is to decide on the factors to be included in the comparison. Some of these factors are quantitative or are capable of being quantified; many others are qualitative. Evaluation of the qualitative factors requires experience and enforces the correct jurisdictions. Therefore, defining the comparison process with just a quantitative model is not meaningful. Accordingly, expressing the results of the comparison analysis with just a single quantitative value would not be accurate. One of the important problems in comparing investment alternatives come out in including the some criteria that cannot be expressed numerically in the analysis. These kinds of criteria are either incorrectly quantified and included in the analysis or they are being tried to be evaluated verbally. In this study, one of the methods that are developed for including both numerical and nonnumeric criteria in the evaluation, the analytical hierarchy method is used. This method is supported by a travel time simulation model; and an application that can be useful in public transport mode selection is made. When deciding on a new investment that is going to be made within an urban public transport system, several criteria, which expand over a broad scale, should be taken into consideration. Since they make non-numerical important factors considerable, using multiple criteria decision making processes will be more meaningful in selecting a public transport mode. Analytical hierarchy method, which is one of multiple criteria decision making methods, is used in this study. This method provides meaningful results because of its simplicity and its ability to be adopted for different conditions. For evaluating some of the varying physical conditions, a simulation model is developed and used. Thus, the proposed method can be called a simulation supported analytic hierarchy method. Forecasting the possible performance of a public transport mode in a corridor has numerous benefits. It is important to forecast the performance in order to make accurate decisions on factors like vehicle frequency, station places and station spacing and in deciding between more than one alternative. The varying performance of a public transport based on characteristics like varying passenger demand, speed, station spacing and boarding/alighting time (according to payment type and other physical factors) system can be forecasted with the help of a simulation model. Such a simulation model is developed in this study. The performance indicator in the model is travel time. The model is run separately for busway and tram systems. In this study, two different examples for an urban corridor on which a public transport system will be built were taken into consideration. The alternatives of “busway” and “tram” were evaluated in the two examples, which are the Beşiktaş-Levent and Taksim-Aksaray corridors. As stated above, the analytical hierarchy method was utilised in deciding on the public transport alternative. In the analytical hierarchy method, first, the weights (w) of each alternative and each criterion should be estimated. A survey was organised in order to receive the experts’ opinions. After assessing the expert opinions gathered through the survey, relative weights of each criterion was determined. In the following step, the weights of each criterion for each of the public transport alternatives were estimated. For quantitative criteria, information from different sources was used; while for non-quantitative criteria, the second part of the survey was utilised. The weights of the criteria at the lower level of the hierarchy, which was defined by the analytical hierarchy method, were estimated for busway and tram alternatives through the method explained above. In the following step, these weights were multiplied by the criteria’s own weights that are placed in the middle level of the hierarchy. The results for each alternative were then summed up in order to find a total weight for each alternative. The results show that the relative weight of the busway is slightly higher than that of the tram’s. With the analytical hierarchy method, the busway is found out to be a more preferable option than the tram. Keywords: Public transport, simulation, multiple-criteria decision making, analytic hierarchy process

Cervical Priming Before Diagnostic Operative Hysteroscopy in Infertile Women: A Randomized, Double-Blind, Controlled Comparison of 2 Vaginal Misoprostol Doses

The aim of this study was to evaluate the efficacy of vaginal misoprostol for cervical priming at doses of 200 mcg and 400 mcg, 12 to 15 hours before diagnostic office hysteroscopy (OH) without anesthesia in patients with infertility. Sixty infertile patients requiring a diagnostic office hysteroscopy for investigation of infertility were included in the study. The patients were randomly allocated into 3 vaginally administered misoprostol groups: (1) control group, (2) 200-mcg dose group, and (3) 400-mcg dose group. Misoprostol significantly facilitated the procedure of OH: cervical entry was easier; procedural time was shorter; baseline cervical width was larger; and pain scoring was lower in the misoprostol groups compared with the control group. Increasing the dose of misoprostol from 200 mcg to 400 mcg did not improve the effect on cervical dilation. Misoprostol is a promising analog to use for cervical priming before OH. Since doses of 200 mcg and 400 mcg vaginal misoprostol 12 hours before the OH both have proven to be effective regimens, 200 mcg may be preferred. However, before routine clinical usage, further research is needed through large, randomized, controlled trials powered to detect a difference in complications to determine whether misoprostol reduces complications in OH.Scientific Research Projects Coordination Unit of Istanbul UniversityIstanbul University [26324]An earlier version of this research was presented at the 42nd Annual Meeting of American Society of Reproductive Medicine in San Diego, 2012. This was made possible by funding from the Scientific Research Projects Coordination Unit of Istanbul University (grant 26324)

An Automatic Calibration Procedure of Driving Behaviour Parameters in the Presence of High Bus Volume

Most of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the O-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.</p

Identification of an mRNA isoform switch for HNRNPA1 in breast cancers.

Roles of HNRNPA1 are beginning to emerge in cancers; however, mechanisms causing deregulation of HNRNPA1 function remain elusive. Here, we describe an isoform switch between the 3′-UTR isoforms of HNRNPA1 in breast cancers. We show that the dominantly expressed isoform in mammary tissue has a short half-life. In breast cancers, this isoform is downregulated in favor of a stable isoform. The stable isoform is expressed more in breast cancers, and more HNRNPA1 protein is synthesized from this isoform. High HNRNPA1 protein levels correlate with poor survival in patients. In support of this, silencing of HNRNPA1 causes a reversal in neoplastic phenotypes, including proliferation, clonogenic potential, migration, and invasion. In addition, silencing of HNRNPA1 results in the downregulation of microRNAs that map to intragenic regions. Among these miRNAs, miR-21 is known for its transcriptional upregulation in breast and numerous other cancers. Altogether, the cancer-specifc isoform switch we describe here for HNRNPA1 emphasizes the need to study gene expression at the isoform level in cancers to identify novel cases of oncogene activation