CAINE 2020:Papers with Abstracts

Abstract. We propose multiple factors of authentication, more specifically a two factor. We have developed an algorithm ESC which utilizes a combination of public key and symmetric key encryption that provides a solid secured communication framework. As a proof of concept, we report here Java based implementation of the approach.

Abstract. To think about the experience that the user will have when interacting with a piece of software, is to begin to understand that, in the process of interaction, different factors influence: individual, social, contextual, cultural and those of the product in question. So, there is a need to have some strategy, technique, model or method that allows to systematically organize the tasks to help software developers and professionals from different disciplines to work together for the development of software interfaces. The objective of this paper is to provide software development companies with a quality model that serves as an instrument, guide or good practice that allows them to position themselves at a highly competitive level in the current market through production of quality software based on user experience. A quality model is proposed for which the structure of the International Standard ISO 13407:1999, the ISO 25000 standard and information collected from the software service industry of the region were taken into consideration.

Abstract. COVID-19 has arguably impacted every dimension of social living — be that employ- ment, schooling, healthcare or recreational activities. In a matter of months, businesses have shut down and the workforce and schools have been redirected to online work in many regions of the world. One key element of the North American pandemic response has been the emphasis that the spread or prevention of the pandemic is largely dependent on the measures taken by residents of any region. As such, our research focuses on outlining the factors that determine if an individual is less likely to take this pandemic seriously (i.e. is taking fewer measures to prevent the spread of COVID-19). We have analyzed the results of a U.S. wide COVID-impact survey using random forest classification (RFC) to associate individual demographic factors to measures taken against the pandemic such as washing/sanitizing hands. Our results indicate that the top three influential factors are household size, the number of adults living in one household and the health of the respon- dent (poor to excellent). Using these insights, we used association rules to determine key combinations of features that may lead to an apathetic response to a global pandemic in U.S. citizens, such as lower income households.

Abstract. One of the major reasons of road related accidents is driver distraction. The aim of this study is to classify driver attention level which can be extended to improving driver warning systems by generating adaptive driver alert warning systems. In this paper logistic regression (LR) and support vector machine (SVM) classifiers are used to classify driver attention level. The performance of mentioned classifiers is illustrated and compared via the figures of predicted decision boundaries. Also, in comparison to LR, higher accuracy of SVM has been verified.

Abstract. Microservices have recently emerged as an architectural style that gained widespread popularity in industries. Not long time ago, software applications were designed monolith- ically, that is all components were woven together as one single executable artifact unit sharing the resources of the same machine. In this paper, we look at microservice architec- tures through evolutionary lenses as it does not capture the essence of a new software move- ment. Microservices offer a new trend in software architecture and deliver a set of benefits and best practices. However, this is by no means without their own share of challenges and problems that are self-inflicted or inherited from its predecessors (i.e., component-based software architecture (CBSA), service-oriented architecture, (SOA), and service-oriented computing (SOC). The evolution of these different paradigms and their gradual interweav- ing have fostered the development of microservices afterwards. We introduce two finite state-based formalisms called, monitoring microservice automata (MMA) and container microservice automata (CMA). The former is a powerful and parallel formalism to model microservices’ infrastructures, including monitoring microservices’ functionalities, resource usage, compositions, and interface operations. The later models each microservice func- tionality independently as an automaton that accounts for local behavior that contains a microservice and its code. Such as code is required to run within an isolated environment and a system which is fully supported by MMA. As another phase of the evolution of ag- ile software development, microservice architectures have made their footprints in several industries such as Amazon, Twiter, PayPal, LinkedIn, Netflix, and SoundCloud.

Abstract. This paper offers insights about the most important properties of vehicular platooning. A key feature is determining circumstances when platooning will reduce travel times and emission reductions. In a given roadmap, we highlight quantifiable measures corresponding to travel times corresponding to optimal platooning locations. We have performed simulated experiments that showed using platooning provides nontrivial financial benefits for organizations deploying platoons as well as overall travel time reductions.

Abstract. In this work, we have considered designing secured communication protocols for Chinese remainder theorem based structured p2p architecture. Such an architecture has been the choice because of the complexity in Inter or Intra group communications are just O(1) [16]. In this work, we have considered efficient way to make the already existing communication protocols [16] secured. We have extended these protocols further to include anonymity. We have considered security separately for multicasting inside a group and multicasting outside the group.

Abstract. High-throughput phenotyping of seeds is the assessment of seed morphometry to aid in the prediction of yield, tolerance, resistance, and development of seeds in various environmental conditions. The paper focuses on the application of 3D graphics to image processing as a means to conduct seed phenotyping better. The paper proposes two algorithms - similar in the outcome, but different in implementation. The algorithms perform image processing on a variety of seeds such as wheat, soy, sorghum, rough rice, white rice, and canola to arrive at their morphometric estimations. In the area of static image processing, addressed are at least three common yet significant problems of seed clusters on images, skewed images, and poor image quality. As a means to address the problems, we propose the use of low-cost physical components. The algorithms provide the estimated count, area, perimeter, length, and width of seeds within an image.

Abstract. In this paper, we have considered an existing non-DHT-based structured P2P network. It is known as pyramid tree. A node i in this tree represents a group (cluster) of peers that are interested in a particular resource of type i. It is not a conventional tree. In the present work, such a P2P architecture has been the choice because in a pyramid tree, search latency for its inter-group data lookup algorithm is bounded by the tree diameter and is independent of the total number of peers present in the system. In addition, any intra-group data look up communication needs only one overlay hop. In the present work, we have explored some important structural properties of the tree and incorporated them to design an efficient inter cluster broadcast protocol with complexity O(log n) for complete pyramid tree architecture, where n denotes the number of nodes in the tre

Abstract. High-throughput phenotyping of seeds is the assessment of seed morphometry to aid in the prediction of yield, tolerance, resistance, and development of seeds in various environmental conditions. The paper focuses on the application of 3D graphics to image processing as a means to conduct seed phenotyping better. The paper proposes two algorithms - similar in the outcome, but different in implementation. The algorithms perform image processing on a variety of seeds such as wheat, soy, sorghum, rough rice, white rice, and canola to arrive at their morphometric estimations. In the area of static image processing, addressed are at least three common yet significant problems of seed clusters on images, skewed images, and poor image quality. As a means to address the problems, we propose the use of low-cost physical components. The algorithms provide the estimated count, area, perimeter, length, and width of seeds within an image.

Abstract. The Assignment Problem is a basic combinatorial optimization problem. In a weighted bipartite graph, the Assignment Problem is to find the largest sum of weights matching. The Hungarian method is a well-known algorithm, which is combinatorial optimization. Adding a new row and a new column to a weighted bipartite graph is called the Incremental Assignment Problem (IAP). The algorithm of the Incremental Assignment Problem utilizes the given optimal solution (the maximum weighted matching) and the dual variables to solve the matrix after extending the bipartite graph. This paper proposes an improvement of the Incremental Assignment Algorithm (IAA), named the Improved Incremental Assignment Algorithm (IIAA). The improved algorithm will save the operation time and operation space to find the optimal solution (the maximum weighted matching) of the bipartite graph.