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Weather occurs in everyday discussion, in every language around the globe. Many people believe that weather does impact our mood and behavior. However, to what degree does this hold? We investigate a collection of weather data and link them to social media feeds. Our work focuses on the comparison of three popular sentiment metrics (previous work focused on one metric) connected to commonly used weather...
To create confusion in ciphertexts, encryption processes depends upon nonlinear mappings. This nonlinear mapping can be achieved by a process known as substitution. In a secure encryption algorithm, substitution plays a key role during confusion stage of encryption algorithms. In this work, we present a novel chaos-based substitution box that can be utilized in the encryption processes for securing...
This paper presents a novel register file with self-indexed features, targeting the DSP/media algorithm with massive data locality. The self-indexed register file (SIRF) contains 128 high-speed registers, 4 input ports and 4 output ports. It can be accessed with the double circular window mode, or simply with the immediate index mode. SIRF can eliminate write after write (WAW) dependence without register...
The study on machine learning has been flourishing for several years, and machine learning algorithms are being applied to various fields with great achievements. In this paper, combining the on-line machine learning method into optimization algorithms is to be studied. In many heuristic optimization algorithms, one common way to reduce execution time and improve solution optimality is, first estimating...
In this paper we propose a new approach for energy saving in Elastic Optical Networks (EONs) under physical impairments based on MILP solving instances. First we search for maximize the attended traffic on network whereas the blocking probability is maintained below a defined limit. Hence, the next step is to minimize the power consumption on network. The proposed MILP-based algorithm models the RMLSA...
Highly sophisticated artificial neural networks have achieved unprecedented performance across a variety of complex real-world problems over the past years, driven by the ability to detect significant patterns autonomously. Modern electronic stock markets produce large volumes of data, which are very suitable for use with these algorithms. This research explores new scientific ground by designing...
A novel evolutionary algorithm, which can be viewed as an extension to the simple, yet effective, approach of the Random-Mutation Hill Climber (RMHC), is presented. The algorithm addresses the shortcomings of RMHC and its multi-individual parallel version through the introduction of a penalty term into the fitness function, which penalizes individuals in the population for being too similar, hence...
Many organizations rely on Disaster Recovery services to ensure availability and continuity of their operations during undesired circumstances and outages. Business Impact Analysis concept enables adequate planning for business continuation as it delivers essential information on services' criticality levels and their impact on business. The advancement in communication and technology has reshaped...
This paper introduces an approach to harness the advantages of 3D virtual environments in a more effective way in order to benefit the student's learning in understanding abstract concepts. It is a proposal for a generalized framework that generates a mixed-simulation role-play activity. In this activity, the student functions as a part of a working system in a virtual environment in order to complete...
Here the Newton's Method direct action selection approach to continuous action-space reinforcement learning is extended to use an eligibility trace. This is then compared to the momentum term approach from the literature in terms of the update equations and also the success rate and number of trials required to train on two variants of the simulated Cart-Pole benchmark problem. The eligibility trace...
This paper proposes a fast and real-time background update mechanism for vehicle detection in urban city. The roads of urban city are relatively clean from the perspective of digital image which is helpful for developing a specialized fast algorithm of background update. However, frequent congestion in urban roads poses a great challenge on constructing a reliable real-time background model. In this...
Digital Image Processing (DIP) is one of the fastest evolving fields in Computer Science with growing numbers of applications. As the demand for multimedia increases, more advanced sensors are being developed, producing a more demanding volume of data. As a result, the theory of data compression has become extremely significant in reducing data redundancy to save hardware storage space and transmission...
Modern telecommunication networks are based on diverse applications that highlighted the status of efficient use of network resources and performance optimization. Various methodologies are developed to address multi-objectives optimization within the traffic engineering of MPLS/ GMPLS networks. However, Pareto based approach can be used to achieve the optimization of multiple conflicting objective...
In this paper we introduce a new histogram computation method to be used within the histogram of oriented gradients (HOG) algorithm. The new method replaces the arctangent with the slope computation and the classical magnitude allocation based on interpolation with a simpler algorithm. The new method allows a more efficient implementation of HOG in field programmable gate arrays (FPGAs), by considerably...
One of the challenges of Fifth Generation (5G) networks is how to support massive number of wireless devices in the Internet of Things (IoT). IoT will interconnect billions of devices under machine-to-machine communication links (M2M). However, this massive connectivity will create burden on the cellular network. Fixed sensors and wearable devices are expected to make the majority of future IoT traffic...
Twitter is a social network that lets users post their opinions about current affairs, share their social events, and interact with others. Twitter has now become one of the largest sources of news, with over 200 million active users monthly. This paper proposes a method to predict election results based on Twitter data analysis. The method extracts and analyses sentimental information from microblogs...
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