A Straightforward Framework for Road Network Screening to Lombardy Region (Italy)

It is not possible to deal with sustainable mobility without considering road safety as a key element: Target 3.6 of the Sustainable Development Goals aims at halving the number of road deaths by 2030. To do so, further effort and effective tools are required for road authorities, to implement improvement measures and enhance road safety for all. Road network screening (RNS) is the first step of the whole Road Infrastructure Safety Management (RISM) System process. It is applied to a wide scale to assess the safety performance of the whole road network and identify the worst performing roads (or sites). The literature is quite rich with RNS models and methods, which have greatly improved, recently. Moreover, although many national frameworks on road safety have been issued over time, some barriers remain, specifically related to data quality, such as accurate crash location, which is mainly used to integrate crash data with other databases. In addition, most of these frameworks adopted partial indexes to identify black spots and presented results using fixed maps for visualization. This paper fills these gaps by the proposal of a straightforward operational framework to perform RNS, based on a simple and flexible rationale to integrate raw crash, traffic, and road data. Specifically, the framework: (i) manages crash location data, without relying on plane or geographical coordinates, which are missing or inaccurate and still are a crucial issue in many European countries such as Italy; (ii) adopts an adjusted accident cost rate index that integrates frequency and severity of crashes as well as a measurement of exposure; (iii) introduces variable maps that show the results at different jurisdiction levels. A relevant case study demonstrates the usefulness of this framework using 30,000+ crash data of the whole non-urban road network of the Lombardy Region (Northern Italy). Road authorities could adopt this framework to perform an accurate safety screening on the overall regional road network. Moreover, this framework could be implemented in a road traffic safety managerial system to better prioritise safety interventions within a tight budget and help achieve sustainable development targets

Message forwarding techniques in Bluetooth enabled opportunistic communication environment

These days, most of the mobile phones are smart enough with computer like intelligence and equipped with multiple communication technologies such as Bluetooth, wireless LAN, GPRS and GSM. Different communication medium on single device have unlocked the new horizon of communication means. Modern mobile phones are not only capable of using traditional way of communication via GSM or GPRS; but, also use wireless LANs using access points where available. Among these communication means, Bluetooth technology is very intriguing and unique in nature. Any two devices equipped with Bluetooth technology can communicate directly due to their unique IDs in the world. This is opposite to GSM or Wireless LAN technology; where devices are dependent on infrastructure of service providers and have to pay for their services. Due to continual advancement in the field of mobile technology, mobile ad-hoc network seems to be more realised than ever using Bluetooth. In traditional mobile ad-hoc networks (MANETs), before information sharing, devices have partial or full knowledge of routes to the destinations using ad-hoc routing protocols. This kind of communication can only be realised if nodes follow the certain pattern. However, in reality mobile ad-hoc networks are highly unpredictable, any node can join or leave network at any time, thus making them risky for effective communication. This issue is addressed by introducing new breed of ad-hoc networking, known as opportunistic networks. Opportunistic networking is a concept that is evolved from mobile ad-hoc networking. In opportunistic networks nodes have no prior knowledge of routes to intended destinations. Any node in the network can be used as potential forwarder with the exception of taking information one step closer to intended destination. The forwarding decision is based on the information gathered from the source node or encountering node. The opportunistic forwarding can only be achieved if message forwarding is carried out in store and forward fashion. Although, opportunistic networks are more flexible than traditional MANETs, however, due to little insight of network, it poses distinct challenges such as intermittent connectivity, variable delays, short connection duration and dynamic topology. Addressing these challenges in opportunistic network is the basis for developing new and efficient protocols for information sharing. The aim of this research is to design different routing/forwarding techniques for opportunistic networks to improve the overall message delivery at destinations while keeping the communication cost very low. Some assumptions are considered to improved directivity of message flow towards intended destinations. These assumptions exploit human social relationships analogies, approximate awareness of the location of nodes in the network and use of hybrid communication by combining several routing concept to gain maximum message directivity. Enhancement in message forwarding in opportunistic networks can be achieved by targeting key nodes that show high degree of influence, popularity or knowledge inside the network. Based on this observation, this thesis presents an improved version of Lobby Influence (LI) algorithm called as Enhanced Lobby Influence (ELI). In LI, the forwarding decision is based on two important factors, popularity of node and popularity of node’s neighbour. The forwarding decision of Enhanced Lobby Influence not only depends on the intermediate node selection criteria as defined in Lobby Influence but also based on the knowledge of previously direct message delivery of intended destination. An improvement can be observed if nodes are aware of approximate position of intended destinations by some communication means such as GPS, GSM or WLAN access points. With the knowledge of nodes position in the network, high message directivity can be achieved by using simple concepts of direction vectors. Based on this observation, this research presents another new algorithm named as Location-aware opportunistic content forwarding (LOC). Last but not least, this research presents an orthodox yet unexplored approach for efficient message forwarding in Bluetooth communication environment, named as Hybrid Content Forwarding (HCF). The new approach combines the characteristics of social centrality based forwarding techniques used in opportunistic networks with traditional MANETs protocols used in Bluetooth scatternets. Simulation results show that a significant increase in delivery radio and cost reduction during content forwarding is observed by deploying these proposed algorithms. Also, comparison with existing technique shows the efficiency of using the new schemes

Enhanced Community-Based Routing for Low-Capacity Pocket Switched Networks

Sensor devices and the emergent networks that they enable are capable of transmitting information between data sources and a permanent data sink. Since these devices have low-power and intermittent connectivity, latency of the data may be tolerated in an effort to save energy for certain classes of data. The BUBBLE routing algorithm developed by Hui et al. in 2008 provides consistent routing by employing a model which computes individual nodes popularity from sets of nodes and then uses these popularity values for forwarding decisions. This thesis considers enhancements to BUBBLE based on the hypothesis that nodes do form groups and certain centrality values of nodes within these groups can be used to improve routing decisions further. Built on this insight, there are two algorithms proposed in this thesis. First is the Community-Based- Forwarding (CBF), which uses pairwise group interactions and pairwise node-to-group interactions as a measure of popularity for routing messages. By having a different measure of popularity than BUBBLE, as an additional factor in determining message forwarding, CBF is a more conservative routing scheme than BUBBLE. Thus, it provides consistently superior message transmission and delivery performance at an acceptable delay cost in resource constrained environments. To overcome this drawback, the concept of unique interaction pattern within groups of nodes is introduced in CBF and it is further renewed into an enhanced algorithm known as Hybrid-Community-Based- Forwarding (HCBF). Utilizing this factor will channel messages along the entire path with consideration for higher probability of contact with the destination group and the destination node. Overall, the major contribution of this thesis is to design and evaluate an enhanced social based routing algorithm for resource-constrained Pocket Switched Networks (PSNs), which will optimize energy consumption related to data transfer. It will do so by explicitly considering features of communities in order to reduce packet loss while maintaining high delivery ratio and reduced delay

Domain Classification-based Source-specific Term Penalization for Domain Adaptation in Hate-speech Detection

State-of-the-art approaches for hate-speech detection usually exhibit poor performance in out-of-domain settings. This occurs, typically, due to classifiers overemphasizing source-specific information that negatively impacts its domain invariance. Prior work has attempted to penalize terms related to hate-speech from manually curated lists using feature attribution methods, which quantify the importance assigned to input terms by the classifier when making a prediction. We, instead, propose a domain adaptation approach that automatically extracts and penalizes source-specific terms using a domain classifier, which learns to differentiate between domains, and feature-attribution scores for hate-speech classes, yielding consistent improvements in cross-domain evaluation.Comment: COLING 2022 pre-prin

Social-context based routing and security in delay tolerant networks

Delay Tolerant Networks (DTNs) were originally intended for interplanetary communications and have been applied to a series of difficult environments: wireless sensor networks, unmanned aerial vehicles, and short-range personal communications. There is a class of such environments in which nodes follow semi-predictable social patterns, such as wildlife tracking or personal devices. This work introduces a series of algorithms designed to identify the social patterns present in these environments and apply this data to difficult problems, such as efficient message routing and content distribution. Security is also difficult in a mobile environment. This is especially the case in the event that a large portion of the network is unreliable, or simply unknown. As the network size increases nodes have difficulty in securely distributing keys, especially using low powered nodes with limited keyspace. A series of multi-party security algorithms were designed to securely transmit a message in the event that the sender does not have access to the destinations public key. Messages are routed through a series of nodes, each of which partially decrypts the message. By encrypting for several proxies, the message can only be intercepted if all those nodes have been compromised. Even a highly compromised network has increased security using this algorithm, with a trade-off of reduced delivery ratio and increased delivery time -- Abstract, page iv

The power of quasi-shortest paths and the impact of node mobility on dynamic networks

The objective of this thesis is to investigate three important aspects of dynamic networks: the impact of node mobility on multihop data transmission, the effect of the use of longer paths on the relative importance of nodes and the performance of the network in the presence of failure on central nodes. To analyze the first aspect, this work proposes the (κ, λ)-vicinity, which extends the traditional vicinity to consider as neighbors nodes at multihop distance and restricts the link establishment according to the relative speed between nodes. This proposal is used later on the development of three forwarding strategies. The relative speed restriction imposed on these strategies results in significant reduction of resources consumption, without incurring significant impact on the average packet delivery ratio. To analyze the second aspect, we propose the ρ-geodesic betweenness centrality, which uses shortest and quasi-shortest paths to quantify the relative importance of a node. The quasishortest paths are limited by a spreadness factor, ρ. The use of non-optimal paths causes the reranking of several nodes and its main effect is a reduced occupation of the most central positions by articulation points. Lastly, the network performenace in presence of failures is investigated through simulations, in which failures happen on nodes defined as the most central according to distinct centrality metrics. The result is a severe reduction of the average network throughput, and it is independent of the metric used to determine which nodes are the most central. The major strength of the proposed metric, then, is that, despite the severe reduction of the throughput, there is a high probability of maintaining the network connected after a failure, because it is unlikely that a failing node in the most central position is also an articulation point.O objetivo desta tese é investigar três aspectos importantes das redes dinâmicas: o impacto da mobilidade dos nós na transmissão de dados em múltiplos saltos, o efeito do uso de caminhos mais longos na importância relativa dos nós, e o desempenho da rede na presença de falha em nós centrais. Para analisar o primeiro aspecto, este trabalho propõe a (κ, λ)-vizinhança, que estende a vizinhança tradicional para considerar como vizinhos nós a múltiplos saltos de distância e restringe o estabelecimento de enlaces de acordo com a velocidade relativa entre os nós. Essa proposta é usada posteriormente no desenvolvimento de três estratégias de encaminhamento. A restrição de velocidade relativa imposta nessas estratégias resulta em uma redução significativa do consumo de recursos, sem que ocorra impacto significativo na taxa média de entrega de pacotes. Para analisar o segundo aspecto, propõe a centralidade de intermediação ρ-geodésica, que usa caminhos mais curtos e quase mais curtos para quantificar a importância relativa dos nos. Os caminhos quase mais curtos são limitados por um fator de espalhamento ρ. O uso de caminhos não ótimos provoca o reranqueamento de diversos nós e tem como principal efeito uma menor ocupação de posições mais centrais por pontos de articulação. Por fim, o desempenho da rede em presença de falha é investigado através de simulações nas quais as falhas atingem nós definidos como os mais centrais de acordo com métricas de centralidade distintas. O resultado é uma redução brusca da vazão média da rede, independentemente da métrica usada para determinar quais são os nós mais centrais. O grande trunfo da métrica proposta é que, apesar da severa redução na vazão, é grande a probabilidade de manter a rede conectada após a falha, uma vez que é pouco provável que um nó em falha nas posições mais centrais seja também um ponto de articulação

Resolving pronominal anaphora using commonsense knowledge

Coreference resolution is the task of resolving all expressions in a text that refer to the same entity. Such expressions are often used in writing and speech as shortcuts to avoid repetition. The most frequent form of coreference is the anaphor. To resolve anaphora not only grammatical and syntactical strategies are required, but also semantic approaches should be taken into consideration. This dissertation presents a framework for automatically resolving pronominal anaphora by integrating recent findings from the field of linguistics with new semantic features. Commonsense knowledge is the routine knowledge people have of the everyday world. Because such knowledge is widely used it is frequently omitted from social communications such as texts. It is understandable that without this knowledge computers will have difficulty making sense of textual information. In this dissertation a new set of computational and linguistic features are used in a supervised learning approach to resolve the pronominal anaphora in document. Commonsense knowledge sources such as ConceptNet and WordNet are used and similarity measures are extracted to uncover the elaborative information embedded in the words that can help in the process of anaphora resolution. The anaphoric system is tested on 350 Wall Street Journal articles from the BBN corpus. When compared with other systems available such as BART (Versley et al. 2008) and Charniak and Elsner 2009, our system performed better and also resolved a much wider range of anaphora. We were able to achieve a 92% F-measure on the BBN corpus and an average of 85% F-measure when tested on other genres of documents such as children stories and short stories selected from the web

Domain Classification-based Source-specific Term Penalization for Domain Adaptation in Hate-speech Detection

International audienceState-of-the-art approaches for hate-speech detection usually exhibit poor performance in out-of-domain settings. This occurs, typically, due to classifiers overemphasizing source-specific information that negatively impacts its domain invariance. Prior work has attempted to penalize terms related to hate-speech from manually curated lists using feature attribution methods, which quantify the importance assigned to input terms by the classifier when making a prediction. We, instead, propose a domain adaptation approach that automatically extracts and penalizes source-specific terms using a domain classifier, which learns to differentiate between domains, and feature-attribution scores for hate-speech classes, yielding consistent improvements in cross-domain evaluation