Geometrical and functional criteria as a methodological approach to implement a new cycle path in an existing Urban Road Network: A Case study in Rome

Most road accidents occur in urban areas and notably at urban intersections, where cyclists and motorcyclists are the most vulnerable. In the last few years, cycling mobility has been growing; therefore, bike infrastructures should be designed to encourage this type of mobility and reduce motorized and/or private transport. The paper presents a study to implement a new cycle path in the existing cycle and road network in Rome, Italy. The geometric design of the new path complies with Italian standards regarding the technical characteristics of bicycle paths, while the Highway Capacity Manual has been considered for the traffic analysis. In particular, a before-after approach has been adopted to examine and compare the traffic flow at more complex and congested intersections where the cycle path will pass. Trams, buses, cars, bikes and pedestrians were the traffic components considered in each analysis. The software package PTV VISSIM 8 allowed the simulations of traffic flows at traffic-light intersections; an original linear process has been proposed to model dynamic intelligent traffic controls, which are not admitted by the software used. The traffic analysis allowed the identification of the best option for each of the five examined intersections. Particularly, the maximum queue length value and the total number of passed vehicles have been considered in order to optimize the transport planning process. The results of this study highlight the importance of providing engineered solutions when a cycle path is implemented in a complex road network, in order to avoid negative impacts on the citizens and maximize the expected advantages

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time

Investigating Data Similarity and Estimation Through Spatio-Temporal Correlation to Enhance Energy Efficiency in WSNs

International audienceWireless sensor networks are of energy-constrained nature, which calls for energy efficient protocols as a primary design goal. Thus, minimizing energy consumption is a main challenge.We are concerned in howcollected data by sensors, can be processed to increase the relevance of certain mass of data and reduce the overall data traffic. Since sensor nodes are often densely deployed, the data collected by nearby nodes are either redundant or correlated. One of the great challenges for the aforementioned problem is to exploit temporal and spatial correlation among the source nodes. Our work is composed of two main tasks: 1- A predictive modeling task that aims to capture the temporal correlation among collected data. 2- A data similarity detection task that measures the data similarity based on the spatial correlation

Features extraction scheme for behavioral biometric authentication in touchscreen mobile devices

Common authentication mechanisms in mobile devices such as passwords and Personal Identification Number have failed to keep up with the rapid pace of challenges associated with the use of ubiquitous devices over the Internet, since they can easily be lost or stolen. Thus, it is important to develop authentication mechanisms that can be adapted to such an environment. Biometric-based person recognition is a good alternative to overcome the difficulties of password and token approaches, since biometrics cannot be easily stolen or forgotten. An important characteristic of biometric authentication is that there is an explicit connection with the user's identity, since biometrics rely entirely on behavioral and physiological characteristics of human being. There are a variety of biometric authentication options that have emerged so far, all of which can be used on a mobile phone. These options include but are not limited to, face recognition via camera, fingerprint, voice recognition, keystroke and gesture recognition via touch screen. Touch gesture behavioural biometrics are commonly used as an alternative solution to existing traditional biometric mechanism. However, current touch gesture authentication schemes are fraught with authentication accuracy problems. In fact, the extracted features used in some researches on touch gesture schemes are limited to speed, time, position, finger size and finger pressure. However, extracting a few touch features from individual touches is not enough to accurately distinguish various users. In this research, behavioural features are extracted from recorded touch screen data and a discriminative classifier is trained on these extracted features for authentication. While the user performs the gesture, the touch screen sensor is leveraged on and twelve of the user‘s finger touch features are extracted. Eighty four different users participated in this research work, each user drew six gesture with a total of 504 instances. The extracted touch gesture features are normalised by scaling the values so that they fall within a small specified range. Thereafter, five different Feature Selection Algorithm were used to choose the most significant features subset. Six different machine learning classifiers were used to classify each instance in the data set into one of the predefined set of classes. Results from experiments conducted in the proposed touch gesture behavioral biometrics scheme achieved an average False Reject Rate (FRR) of 7.84%, average False Accept Rate (FAR) of 1%, average Equal Error Rate (EER) of 4.02% and authentication accuracy of 91.67%,. The comparative results showed that the proposed scheme outperforms other existing touch gesture authentication schemes in terms of FAR, EER and authentication accuracy by 1.67%, 6.74% and 4.65% respectively. The results of this research affirm that user authentication through gestures is promising, highly viable and can be used for mobile devices

Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks

Crime generates significant losses, both human and economic. Every year, billions of dollars are lost due to attacks, crimes, and scams. Surveillance video camera networks generate vast amounts of data, and the surveillance staff cannot process all the information in real-time. Human sight has critical limitations. Among those limitations, visual focus is one of the most critical when dealing with surveillance. For example, in a surveillance room, a crime can occur in a different screen segment or on a distinct monitor, and the surveillance staff may overlook it. Our proposal focuses on shoplifting crimes by analyzing situations that an average person will consider as typical conditions, but may eventually lead to a crime. While other approaches identify the crime itself, we instead model suspicious behavior—the one that may occur before the build-up phase of a crime—by detecting precise segments of a video with a high probability of containing a shoplifting crime. By doing so, we provide the staff with more opportunities to act and prevent crime. We implemented a 3DCNN model as a video feature extractor and tested its performance on a dataset composed of daily action and shoplifting samples. The results are encouraging as the model correctly classifies suspicious behavior in most of the scenarios where it was tested. For example, when classifying suspicious behavior, the best model generated in this work obtains precision and recall values of 0.8571 and 1 in one of the test scenarios, respectively.2020-2

Evaluation of Metaverse Traffic Safety Implementations using fuzzy Einstein based logarithmic methodology of additive weights and TOPSIS method

As the Metaverse’s popularity grows, its effect on everyday problems is beginning to be discussed. The upcoming Metaverse world will influence the transportation system as cross-border lines blur due to rapid globalization. The purpose of this paper is to investigate the capabilities of the Metaverse and its alternatives to traffic safety, as well as to prioritize its advantages. The case study is based on a densely populated metropolis with an extensive education system. The city’s decision-makers will have to weigh the pros and cons of the Metaverse’s effect on traffic safety. To illustrate the complex forces that drive the decision-making process in traffic safety, we create a case study with four alternatives to Metaverse’s integration into the traffic system. Alternatives are evaluated using twelve criteria that reflect the decision problem’s rules and regulations, technology, socioeconomic, and traffic aspects. In this study, fuzzy Einstein based logarithmic methodology of additive weights (LMAW) is applied to calculate the weights of the criteria. We present a new framework that combines Einstein norms and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the alternatives. The findings of this study show that public transportation is the most appropriate area for implementing the Metaverse into traffic safety because of its practical opportunities and broad usage area

Steps to an Ecology of Networked Knowledge and Innovation: Enabling new forms of collaboration among sciences, engineering, arts, and design

SEAD network White Papers ReportThe final White Papers (posted at http://seadnetwork.wordpress.com/white-paper- abstracts/final-white-papers/) represent a spectrum of interests in advocating for transdisciplinarity among arts, sciences, and technologies. All authors submitted plans of action and identified stakeholders they perceived as instrumental in carrying out such plans. The individual efforts led to an international scope. One of the important characteristics of this collection is that the papers do not represent a collective aim toward an explicit initiative. Rather, they offer a broad array of views on barriers faced and prospective solutions. In summary, the collected White Papers and associated Meta- analyses began as an effort to take the pulse of the SEAD community as broadly as possible. The ideas they generated provide a fruitful basis for gauging trends and challenges in facilitating the growth of the network and implementing future SEAD initiatives.National Science Foundation Grant No.1142510. Additional funding was provided by the ATEC program at the University of Texas at Dallas and the Institute for Applied Creativity at Texas A&M University

A Cross-Layer Modification to the DSR Routing Protocol in Wireless Mesh Networks

A cross-layer modification to the DSR routing protocol that finds high throughput paths in WMNs has been introduced in this work. The Access Efficiency Factor (AEF) has been introduced in this modification as a local congestion avoidance metric for the DSR routing mechanism as an alternative to the hop count (Hc) metric. In this modification, the selected path is identified by finding a path with the highest minimum AEF (max_min_AEF) value. The basis of this study is to compare the performance of the Hc and max_min_AEF as routing metrics for the DSR protocol in WMNs using the OPNET modeler. Performance comparisons between max_min_AEF, Metric Path (MP), and the well known ETT metrics are also carried out in this work. The results of this modification suggest that employing the max_min_AEF as a routing metric outperforms the Hc, ETT, and MP within the DSR protocol in WMNs in terms of throughput. This is because the max_min_AEF is based upon avoiding directing traffic through congested nodes where significant packet loss is likely to occur. This throughput improvement is associated with an increment in the delay time due to the long paths taken to avoid congested regions. To overcome this drawback, a further modification to the routing discovery mechanism has been made by imposing a hop count limit (HCL) on the discovered paths. Tuning the HCL allows the network manager to tradeoff throughput against delay. The choice of congestion avoidance metric exhibits another shortcoming owing to its dependency on the packet size. It penalises the smaller packets over large ones in terms of path lengths. This has been corrected for by introducing a ModAEF metric that explicitly considers the size of the packet. The ModAEF metric includes a tuning factor that allows the operator determine the level of the weighting that should be applied to the packet size to correct for this dependence

Método para la evaluación de usabilidad de sitios web transaccionales basado en el proceso de inspección heurística

La usabilidad es considerada uno de los factores más importantes en el desarrollo de productos de software. Este atributo de calidad está referido al grado en que, usuarios específicos de un determinado aplicativo, pueden fácilmente hacer uso del software para lograr su propósito. Dada la importancia de este aspecto en el éxito de las aplicaciones informáticas, múltiples métodos de evaluación han surgido como instrumentos de medición que permiten determinar si la propuesta de diseño de la interfaz de un sistema de software es entendible, fácil de usar, atractiva y agradable al usuario. El método de evaluación heurística es uno de los métodos más utilizados en el área de Interacción Humano-Computador (HCI) para este propósito debido al bajo costo de su ejecución en comparación otras técnicas existentes. Sin embargo, a pesar de su amplio uso extensivo durante los últimos años, no existe un procedimiento formal para llevar a cabo este proceso de evaluación. Jakob Nielsen, el autor de esta técnica de inspección, ofrece únicamente lineamientos generales que, según la investigación realizada, tienden a ser interpretados de diferentes maneras por los especialistas. Por tal motivo, se ha desarrollado el presente proyecto de investigación que tiene como objetivo establecer un proceso sistemático, estructurado, organizado y formal para llevar a cabo evaluaciones heurísticas a productos de software. En base a un análisis exhaustivo realizado a aquellos estudios que reportan en la literatura el uso del método de evaluación heurística como parte del proceso de desarrollo de software, se ha formulado un nuevo método de evaluación basado en cinco fases: (1) planificación, (2) entrenamiento, (3) evaluación, (4) discusión y (5) reporte. Cada una de las fases propuestas que componen el protocolo de inspección contiene un conjunto de actividades bien definidas a ser realizadas por el equipo de evaluación como parte del proceso de inspección. Asimismo, se han establecido ciertos roles que deberán desempeñar los integrantes del equipo de inspectores para asegurar la calidad de los resultados y un apropiado desarrollo de la evaluación heurística. La nueva propuesta ha sido validada en dos escenarios académicos distintos (en Colombia, en una universidad pública, y en Perú, en dos universidades tanto en una pública como en una privada) demostrando en todos casos que es posible identificar más problemas de usabilidad altamente severos y críticos cuando un proceso estructurado de inspección es adoptado por los evaluadores. Otro aspecto favorable que muestran los resultados es que los evaluadores tienden a cometer menos errores de asociación (entre heurística que es incumplida y problemas de usabilidad identificados) y que la propuesta es percibida como fácil de usar y útil. Al validarse la nueva propuesta desarrollada por el autor de este estudio se consolida un nuevo conocimiento que aporta al bagaje cultural de la ciencia.Tesi