The next generation of wireless sensor networks will integrate communication systems beyond the third generation paradigm. As a result of this integration, the new communication systems will be fed by the sensor netwo...
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The next generation of wireless sensor networks will integrate communication systems beyond the third generation paradigm. As a result of this integration, the new communication systems will be fed by the sensor networks with information gathered from the environment, achieving context awareness. To reach the necessary end-to-end connectivity between all-IP networks and sensor networks, the IETF 6LoWPAN working group has designed an IPv6 adaptation layer for low power devices. This protocol stack provides IPv6 interoperability to the sensor networks, thus avoiding as much overhead as possible. This paper analyses and evaluates the associated IP communication overhead in each possible 6LoWPAN scenario, from intra to inter network communication. We conclude that, even the 6LoWPAN offering a light weight IP solution for link local sensor network communication, it has a relatively high overhead when data flows between different networks. In order to avoid the communication overhead when global IPv6 addressing is necessary we propose a new solution based on a 6LoWPAN global-to-link-layer address translation.
During the last years a large number of research works has focused on problems related to multi-core processors. Due to the possibilities of many cores, the number of opportunities in High Performance Computing (HPC) ...
During the last years a large number of research works has focused on problems related to multi-core processors. Due to the possibilities of many cores, the number of opportunities in High Performance Computing (HPC) has grown a lot. In fact, new fields related to HPC and processor architecture increase the future possibilities of a Grid-on-Chip (GoC). The goal of this paper is to show a high-throughput MCNoC (Multi-Cluster Network-on-Chip) as an alternative architecture to support clusters of cores and Grid features. In this new scenario data throughput, flexibility, and scalability are very important. The results verify that MCNoC has a similar area occupation and a better data throughput than a traditional Network-on-Chip.
Learner attention affects learning efficiency. However, in many classes, teachers cannot assess the degree of attention of every student. When a teacher is capable of addressing inattentive students immediately, he ca...
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Learner attention affects learning efficiency. However, in many classes, teachers cannot assess the degree of attention of every student. When a teacher is capable of addressing inattentive students immediately, he can avoid situations in which students are inattentive. Many studies have analyzed student attentiveness by the applying of image detection technologies. If this mechanism can be applied to in-class learning, it will help teachers keep students attentive, and reduce teacher load during class. This study mainly applies fuzzy logic analysis of student facial images when participating in class. Applying fuzzy logic can prevent erroneous judgments associated with a single term, and help teachers deal with student attentiveness.
In emergency response organizations with very limited resources, information technologies are not adequately explored. In such organizations, the simple adoption of new information technologies is not productive, as t...
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ISBN:
(纸本)9781424416509
In emergency response organizations with very limited resources, information technologies are not adequately explored. In such organizations, the simple adoption of new information technologies is not productive, as their efficient use depends on many other interrelated technologies. This work describes a model to help understanding these interrelationships. The model allows the cooperative evaluation of an organization through different perspectives. Using the model, an organization can measure its maturity level and guide the investment in emergency response capabilities. The information technology dimension of the model has been applied to the firefight organization in Brazil.
For the next processor generation, many cores and parallel programming will provide high-throughput and high-performance processing. As a consequence, research works have studied on-chip interconnection architectures ...
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For the next processor generation, many cores and parallel programming will provide high-throughput and high-performance processing. As a consequence, research works have studied on-chip interconnection architectures to identify alternatives capable of decreasing the communication latencies. The objective of this paper is to present the evaluation of three well-known architectures (bus, crossbar switch and a conventional network-on-chip) in order to propose a multi-cluster network-on-chip architecture for parallel processing. The results show that a NoC composed of programmable routers and crossbar switches to interconnect clusters of cores has a better performance than conventional NoCs.
Recommendation accuracy is especially important in mobile e-commerce environments due to the limited screen size of mobile devices and relatively expensive connection costs. Mobile content tends to be fashionable and ...
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ISBN:
(纸本)1601320639
Recommendation accuracy is especially important in mobile e-commerce environments due to the limited screen size of mobile devices and relatively expensive connection costs. Mobile content tends to be fashionable and are geared for young users. This paper presents a novel method of building a more accurate recommender system for mobile content in a mobile ecommerce environment. The method is based on collaborative filtering, and models content diffusion and user preference transition and incorporates them in constructing pseudo ratings from implicit feedback data. In a variety of experiments, recommender systems based on the method showed significantly better recommendation accuracy than a pure collaborative filtering-based recommender system.
The success rate of computer science and engineering students in private universities are not high. It is helpful to find the model to assist students in registration planning. The objective of this research is to pro...
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The success rate of computer science and engineering students in private universities are not high. It is helpful to find the model to assist students in registration planning. The objective of this research is to propose the classifier algorithm for building course registration planning model (CRPM) from historical dataset. The algorithm is selected by comparing performances of four classifiers include Bayesian network, C4.5, Decision Forest and NBTree. The dataset were obtained from student enrollments including grade point average (GPA) and grades of undergraduate students whose majors were computer science or computer engineering. These dataset included grades in each subject of first and second year students from a private university in Thailand. Results showed that NBTree seemed to be the best of four classifiers which had highest prediction power. NBTree was used to generate CRP model which can be used to predict student class of GPA and consider student course sequences for registration planning.
In this work we address two important issues of off-line signature verification. The first one regards feature extraction. We introduce a new graphometric feature set that considers the curvature of the main strokes o...
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In this work we address two important issues of off-line signature verification. The first one regards feature extraction. We introduce a new graphometric feature set that considers the curvature of the main strokes of the signature. The idea is to simulate the shape of the signature by using Bezier curves and then extract features from these curves. The second important aspect is the use of an ensemble of classifiers based on graphometric features to improve the reliability of the classification, hence reducing the false acceptance. The ensemble was built using a standard genetic algorithm and different fitness functions were assessed to drive the search. Thorough experiments were conduct on a database composed of 100 writers and the results compare favorably.
This article shows that the effect of holiday on Thursday affects significantly the load behavior on the next Friday due to the Brazilian culture of joining the holiday with the weekend. A statistic test shows that th...
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ISBN:
(纸本)9780769532578
This article shows that the effect of holiday on Thursday affects significantly the load behavior on the next Friday due to the Brazilian culture of joining the holiday with the weekend. A statistic test shows that there are differences between the Friday following the holidays and other Fridays. Also, using a legacy forecast system with usual MAPE (mean absolute percentage error) rates at 2.5%, forecasting tests for these special Fridays that follows the holiday reach about 10% MAPE. This error rate shows that this fact should be considered while performing load forecasting. Preliminary forecasting tests using an artificial neural network to adjust the legacy forecast result output for these special Fridays reduce the 10% MAPE to the same 2.5% MAPE level obtained by the legacy system on common days. It demonstrates that this is a possible solution that can be also applied to this specific forecast problem or to similarones.
The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registere...
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ISBN:
(纸本)9781424414895
The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registered by undergraduate students whose majors are computer science or engineering. The data set was obtained from student enrollments and include GPA and grades in each subject for first and second year students from a private university in Thailand. Evaluations show that the predictive power of this model is acceptable. The implications from this studypsilas findings suggest that the model can be applied for advising students in planning courses to be registered in each semester. Further, the model appears to be useful for improving curriculum development in order to fit both studentspsila and university requirements.
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