Sistema y Gestión de Telecomunicaciones

This work is devoted to the issues of colorimetric measurements in hardware and software environments using technologies of digital image processing. Such measurements can be implemented by ensuring metrological traceability of results to standards or reference materials. The main idea of the research is to model and build a reference scale in a functional vector color space in space by creating a set of measures (reference samples) sources. To select the color space XYZ on sectors and build in each sector the calibration characteristics is proposed in this paper. This procedure allows to reduce the methodical component of uncertainty and to do measurements in hardware and software environments.

The impact of information technology on better management in small and medium industries was studied in the present paper. This research was a causal study which aimed to find answer to the question that whether the use of information technology can affect the management of small and medium industries or not or, in other words, whether the use of information technology leads to a better management in small and medium industries or not. Statistical population included small and medium manufacturing industries and the sample members were selected by random sampling. The required data and information were collected by handing out a questionnaire among the participants and statistical analyses were done in SPSS17. The results showed that information technology affects the accessibility of new tools of marketing for small and medium industries.

Ever since the industrial revolution, humans have been urbanizing at an exponential rate. There are 100s of thousands of new dwellings are being built every day. As of 2015, there is about 52% of the world population living in cities. Every week, there are at least a million new people moving into cities, worldwide. By 2050, the United Nations (UN) is expecting that 6 billion people will be living in cities; furthermore, cities consume about 70% of the global energy use; as a result, the strain on resources and the magnitude of challenges that cities face is phenomenal. It is imperative to develop solutions that improve the liveability of cities while vividly reducing resource consumption. There is a need for a city-wide smart, secure, and resilient transformation. Technological transformation is one option that governments can rely on to mitigate many of the risks and challenges they are facing. Local governments in general and the Chief Information Officers (CIO) in particular, have many objectives to achieve successful electronic government, such as studying the community, engaging the residents, allowing access to high-speed Internet, and adopting an open government philosophy. In short, government officials must develop a road map for building smart cities, in order to leverage and integrate technologies to create real economic opportunities and save lives.

In this paper a super pixel segmentation algorithm called Linear Spectral Clustering (LSC), which produces compact and uniform super pixels with low computational costs. Basically, a normalized cuts formulation of the super pixel segmentation is adopted based on a similarity metric that measures the colour similarity and space proximity between image pixels. However, instead of using the traditional Eigen-based algorithm, we approximate the similarity metric using a kernel function leading to an explicitly mapping of pixel values and coordinates into a high dimensional feature space. We revisit the conclusion that by appropriately weighting each point in this feature space, the objective functions of weighted K-means and normalized cuts share the same optimum point. As such, it is possible to optimize the cost function of normalized cuts by iteratively applying simple K-means clustering in the proposed feature space. LSC is of linear computational complexity and high memory efficiency and is able to preserve global properties of images. Experimental results show that LSC performs equally well or better than state of the art super pixel segmentation algorithms in terms of several commonly used evaluation metrics in image segmentation.

Today data communication is a modern technology that contains a powerful computer processor to exchange information. But brute force attacks are made to break the encryption techniques and these attacks are the main drawbacks of older algorithms. This paper is concerned with the development of a secure messaging system based on cryptographic algorithms that is which is more faster, better immune to attacks, more complex, easy to encrypt and many more advanced security feature included. This project work is designed and developed for a secure messaging both in web and android platforms. The application is well featured and provides encryption/decryption that can protect message from unauthorized access and disclosure over networks. To send message, a recipient or registered user types and encrypts a text message using keyword mono-alphabetic substitution algorithm with a key, selected from key list. The encrypted message is stored in the database and receiver’s inbox with serial number of key (not the value). The receiver, after log into his/her own account, selects the key value and then decrypts the encrypted message with the key to see the original message. With compared to other messaging systems, the proposed secure messaging system can be used for chat, messaging, video conferencing and real time file sharing in both web and android platforms.

In many communication systems, OFDM is extensively useful to reduce the bandwidth and for its enhancement ability of the data rate. In this paper, shows a comparison of the overall performance of OFDM system using different modulation schemes under the effect of AWGN channel. For OFDM signals, simulations are carried out with Rician fading as well as Rayleigh faded signal to recognize the effect of channel fading and to acquire optimum value of Bit Error rate (BER). In this paper, we proposed modified SL₀ (mSL₀) algorithm for sparse channel estimation in modern wireless communication system. We deal with simple OFDM system model for wireless communications. We address basic OFDM and related modulations, as well as techniques to improve the performance of existing SL₀ algorithm for wireless communications. In this paper, the BER performance of OFDM-BPSK, QPSK and M-QAM system over generalized AWGN channel has been stated. This model is versatile enough to represent fading such Rician and Rayleigh. The flexibility of this model helps to analyse the severity of fading more deeply. We executed various simulations for OFDM signals to find out the best BER overall performance which are carried with generalized faded signal to understand the effect of channel fading.

The main objective of this paper is to provide novel methods facilitating an efficient access and reuse of healthcarerelated data sources within a large scalable and reliable infrastructure, so called ecosystem of ontology-based services which reflect big data and specific patient care. This task focuses on developing ontology-based services for gathering outputs from the various data sources (portable wearable devices, the EHR data, clinical notes, claims, medical imaging data, etc.), that are used in various applied fields of mHealth, and on creating management technology for provision of interconnected healthcare-related data sources and processing procedures. The developed services are the main ‘building blocks’ for more complex applications that use some medical data processing scenarios. To hide the low-level details of the service orchestration mechanism, an automated ontology-based workflow management engine is introduced, that will allow expressing various data processing workflows in the abstract terms of the ‘glue’ high-level ontology rather than in low-level details of interaction different services.

Wireless channel assignment is one of the major challenging issues in multi hop wireless mesh networks (WMN) when there is the need to design them in a distributed fashion, specifically for multi-radio multi-channel (MRMC) systems. In this work, a new learning automata based channel and power assignment scheme which adaptively improve network overall throughput by expecting network dynamics was proposed. First, a utility function which reflected the user’s preference for the signal to interference and noise ratio (SINR) was applied, and then the transmitter power. The distributed channel assignment and power control problem is formulated as a multiple payoff stochastic game of automata. In this game, each user evaluates a channel and power selection strategy by computing a utility value. This evaluation is performed using a stochastic iterative procedure. The utility function that potentially reflected a measure of satisfaction of every node was used by every node as an environmental response for the current selected strategy chosen by the nodes. According to dynamics of system, the proposed algorithm assigned channels and powers to radio interface such that it minimized interference in the neighborhood of a node. The stability of the system was analyzed via appropriate Lyapunov-like trajectory; it was shown that the stability and optimum point of the system converged.