2,469 research outputs found

    On green routing and scheduling problem

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    The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

    Control of free-ranging automated guided vehicles in container terminals

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    Container terminal automation has come to the fore during the last 20 years to improve their efficiency. Whereas a high level of automation has already been achieved in vertical handling operations (stacking cranes), horizontal container transport still has disincentives to the adoption of automated guided vehicles (AGVs) due to a high degree of operational complexity of vehicles. This feature has led to the employment of simple AGV control techniques while hindering the vehicles to utilise their maximum operational capability. In AGV dispatching, vehicles cannot amend ongoing delivery assignments although they have yet to receive the corresponding containers. Therefore, better AGV allocation plans would be discarded that can only be achieved by task reassignment. Also, because of the adoption of predetermined guide paths, AGVs are forced to deploy a highly limited range of their movement abilities while increasing required travel distances for handling container delivery jobs. To handle the two main issues, an AGV dispatching model and a fleet trajectory planning algorithm are proposed. The dispatcher achieves job assignment flexibility by allowing AGVs towards to container origins to abandon their current duty and receive new tasks. The trajectory planner advances Dubins curves to suggest diverse optional paths per origin-destination pair. It also amends vehicular acceleration rates for resolving conflicts between AGVs. In both of the models, the framework of simulated annealing was applied to resolve inherent time complexity. To test and evaluate the sophisticated AGV control models for vehicle dispatching and fleet trajectory planning, a bespoke simulation model is also proposed. A series of simulation tests were performed based on a real container terminal with several performance indicators, and it is identified that the presented dispatcher outperforms conventional vehicle dispatching heuristics in AGV arrival delay time and setup travel time, and the fleet trajectory planner can suggest shorter paths than the corresponding Manhattan distances, especially with fewer AGVs.Open Acces

    An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

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    Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

    Fabrication and properties of gallium phosphide variable colour displays

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    The unique properties of single-junction gallium phosphide devices incorporating both red and green radiative recombination centers were investigated in application to the fabrication of monolithic 5 x 7 displays capable of displaying symbolic and alphanumeric information in a multicolor format. A number of potentially suitable material preparation techniques were evaluated in terms of both material properties and device performance. Optimum results were obtained for double liquid-phase-epitaxial process in which an open-tube dipping technique was used for n-layer growth and a sealed tipping procedure for subsequent p-layer growth. It was demonstrated that to prepare devices exhibiting a satisfactory range of dominant wavelengths which can be perceived as distinct emission colors extending from the red through green region of the visible spectrum involves a compromise between the material properties necessary for efficient red emission and those considered optimum for efficient green emission

    On the relationship between travel time and travel distance of commuters. Reported versus network travel data in the Netherlands

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    This paper gives a detailed empirical analysis of the relationships between different indicators of costs of commuting trips by car: difference as the crow flies, shortest travel time according to route planner, corresponding travel distance, and reported travel time. Reported travel times are usually rounded in multiples of five minutes. This calls for special statistical techniques. Ignoring the phenomenon of rounding leads to biased estimation results for shorter distances. Rather surprisingly, the distance as the crow flies and the network distance appear to be slightly better proxies of the reported travel time compared with the shortest network travel time as indicated by the route planner. We conclude that where actual driving times are missing in commuting research the other three indicators mentioned may be used as proxies, but that the following problems may emerge: actual travel times may be considerably higher than network times generated by route planners, and the average speed of trips increases considerably with distance, implying an overestimate of travel time for long distance commuters. The only personal feature that contributes significantly to variations in reported travel times is gender: women appear to drive at lower average speeds according to our data. As indicated in the paper this may be explained by the differences in the car types of male and female drivers (females drive older and smaller cars) as well as higher numbers of stops/trip chaining among women. A concise analysis is carried out for carpoolers. Car-pooling leads to an increase in travel time of some 17% compared with solo drivers covering the same distance. In the case of car poolers, the above mentioned measures appear to be very poor proxies for the actual commuting times

    Classification of microarray gene expression cancer data by using artificial intelligence methods

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    Günümüzde bilgisayar teknolojilerinin gelişmesi ile birçok alanda yapılan çalışmaları etkilemiştir. Moleküler biyoloji ve bilgisayar teknolojilerinde meydana gelen gelişmeler biyoinformatik adlı bilimi ortaya çıkarmıştır. Biyoinformatik alanında meydana gelen hızlı gelişmeler, bu alanda çözülmeyi bekleyen birçok probleme çözüm olma yolunda büyük katkılar sağlamıştır. DNA mikroarray gen ekspresyonlarının sınıflandırılması da bu problemlerden birisidir. DNA mikroarray çalışmaları, biyoinformatik alanında kullanılan bir teknolojidir. DNA mikroarray veri analizi, kanser gibi genlerle alakalı hastalıkların teşhisinde çok etkin bir rol oynamaktadır. Hastalık türüne bağlı gen ifadeleri belirlenerek, herhangi bir bireyin hastalıklı gene sahip olup olmadığı büyük bir başarı oranı ile tespit edilebilir. Bireyin sağlıklı olup olmadığının tespiti için, mikroarray gen ekspresyonları üzerinde yüksek performanslı sınıflandırma tekniklerinin kullanılması büyük öneme sahiptir. DNA mikroarray’lerini sınıflandırmak için birçok yöntem bulunmaktadır. Destek Vektör Makinaları, Naive Bayes, k-En yakın Komşu, Karar Ağaçları gibi birçok istatistiksel yöntemler yaygın olarak kullanlmaktadır. Fakat bu yöntemler tek başına kullanıldığında, mikroarray verilerini sınıflandırmada her zaman yüksek başarı oranları vermemektedir. Bu yüzden mikroarray verilerini sınıflandırmada yüksek başarı oranları elde etmek için yapay zekâ tabanlı yöntemlerin de kullanılması yapılan çalışmalarda görülmektedir. Bu çalışmada, bu istatistiksel yöntemlere ek olarak yapay zekâ tabanlı ANFIS gibi bir yöntemi kullanarak daha yüksek başarı oranları elde etmek amaçlanmıştır. İstatistiksel sınıflandırma yöntemleri olarak K-En Yakın Komşuluk, Naive Bayes ve Destek Vektör Makineleri kullanılmıştır. Burada Göğüs ve Merkezi Sinir Sistemi kanseri olmak üzere iki farklı kanser veri seti üzerinde çalışmalar yapılmıştır. Sonuçlardan elde edilen bilgilere göre, genel olarak yapay zekâ tabanlı ANFIS tekniğinin, istatistiksel yöntemlere göre daha başarılı olduğu tespit edilmiştir

    Older people’s experiences of informal care in rural Flanders, Belgium

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    Flanders (Belgium) is ageing at high speed. The number of people aged over 80 will increase from more than 400.000 today to nearly 800.000 in 2060, which is 10 % of the population. Although the entire region is ageing, older people are overrepresented in non-urban areas. A large majority of the elderly have to ''age in place', being the consequence of a very clear-cut policy to foster staying put. However, one can question if their quality of life can be guaranteed, knowing that basic facilities are often unavailable in sparsely populated areas. This is especially relevant when personal mobility decreases and (health) care is needed. Based on qualitative research methods (in-depth interviews, focus groups and observations made while following care providers), this paper discusses the everyday experiences and perceptions of older people with regard to informal care. We focus on elderly people living in two different rural regions, rudimentary defined as a work-poor area (Westhoek) and a work-rich area (Kempen). The results indicate that the availability of informal care is -among others- dependent on the spatial context and can therefore not be guaranteed everywhere

    Engineering Algorithms for Dynamic and Time-Dependent Route Planning

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    Efficiently computing shortest paths is an essential building block of many mobility applications, most prominently route planning/navigation devices and applications. In this thesis, we apply the algorithm engineering methodology to design algorithms for route planning in dynamic (for example, considering real-time traffic) and time-dependent (for example, considering traffic predictions) problem settings. We build on and extend the popular Contraction Hierarchies (CH) speedup technique. With a few minutes of preprocessing, CH can optimally answer shortest path queries on continental-sized road networks with tens of millions of vertices and edges in less than a millisecond, i.e. around four orders of magnitude faster than Dijkstra’s algorithm. CH already has been extended to dynamic and time-dependent problem settings. However, these adaptations suffer from limitations. For example, the time-dependent variant of CH exhibits prohibitive memory consumption on large road networks with detailed traffic predictions. This thesis contains the following key contributions: First, we introduce CH-Potentials, an A*-based routing framework. CH-Potentials computes optimal distance estimates for A* using CH with a lower bound weight function derived at preprocessing time. The framework can be applied to any routing problem where appropriate lower bounds can be obtained. The achieved speedups range between one and three orders of magnitude over Dijkstra’s algorithm, depending on how tight the lower bounds are. Second, we propose several improvements to Customizable Contraction Hierarchies (CCH), the CH adaptation for dynamic route planning. Our improvements yield speedups of up to an order of magnitude. Further, we augment CCH to efficiently support essential extensions such as turn costs, alternative route computation and point-of-interest queries. Third, we present the first space-efficient, fast and exact speedup technique for time-dependent routing. Compared to the previous time-dependent variant of CH, our technique requires up to 40 times less memory, needs at most a third of the preprocessing time, and achieves only marginally slower query running times. Fourth, we generalize A* and introduce time-dependent A* potentials. This allows us to design the first approach for routing with combined live and predicted traffic, which achieves interactive running times for exact queries while allowing live traffic updates in a fraction of a minute. Fifth, we study extended problem models for routing with imperfect data and routing for truck drivers and present efficient algorithms for these variants. Sixth and finally, we present various complexity results for non-FIFO time-dependent routing and the extended problem models

    Travel Disruption: Three Case Studies

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    Six stages of travel disruption from travellers are identified from the survey data of peole affected by the volcanic ash flight ban (2010), the loss of road bridges in Workington, west Cumbria (2009-2010) and severe winter weather over most of the UK in December 2010. This report describes expectations of normal travel and how social practices reflect those expectations. It details the expectations travellers had about what should happen when travel is disrupted, how they 'touch the new travel context', revise their plans and the consequences for them and others. It reports on how travellers say it will change their expectations and practices for future trave

    Travel Disruption: Three Case Studies

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    This report draws together the findings of three studies of travel disruption and its impacts on travellers: the volcanic ash cloud which disrupted aviation in Europe in 2010, the loss of road bridges between November 2009 and April 2010 at Workington, Cumbria and the severe winter weather across the UK in the winter of 2010-2011. It proposes a six phase cycle: normality, when transport provision matches expectations drawn from experience, tickets, timetables, etc;, disruption, when the transport provision fails to meet expectations; touching the new context when travellers seek to assess how the changed conditions affect their travel plans; the revised plan, when travellers make new plans on the basis of what they know about the context, the consequences, which includes counting the cost of changed travel plans in terms of extra expenditure of time, money, effort, prolonged absences as well as any benefits emanating from the experience; reflection and incorporation whereby the experience of disruption is assimilated int the new normality; this can include trust of agents, information, travelling more prepared for disruption or being aware of new channels of information or help
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