Web Support System for Business Intelligence in Small and Medium Enterprises

Last decade belongs to business intelligence (BI) because it is one of the few concepts that have actually lived to the expectations. Not only the businesses have adopted it but also have reaped the fruits out of it. But the cost of BI solutions is very high and has restricted small and medium enterprises to use BI solutions. The human resource is also limited and resultantly expensive in this field. This research proposes a web support system for business intelligence which provides automated data mapping and loading from user application to BI framework and also validates it. The system also assists users in getting the outputs in terms of reports and dashboards. The implementation of the proposed framework demonstrates convenience of use and effective cost saving as it does not require any technical expertise. The beauty of this web support system is that all the steps are menu driven and any non-technical user can get hold of it easily.     

Evidence for Glass–glass Interfaces in a Columnar Cu–Zr Nanoglass

Comprehensive analyses of the atomic structure using advanced analytical transmission electron microscopy-based methods combined with atom probe tomography confirm the presence of distinct glass–glass interfaces in a columnar Cu-Zr nanoglass synthesized by magnetron sputtering. These analyses provide first-time in-depth characterization of sputtered film nanoglasses and indicate that glass–glass interfaces indeed present an amorphous phase with reduced mass density as compared to the neighboring amorphous regions. Moreover, dedicated analyses of the diffusion kinetics by time-of-flight secondary ion mass spectroscopy (ToF SIMS) prove significantly enhanced diffusivity, suggesting fast transport along the low density glass–glass interfaces. The present results further indicate that sputter deposition is a feasible technique for reliable production of nanoglasses and that some of the concepts proposed for this new class of glassy materials are applicable.     

A behavioral-based multi-agent optimization algorithm for system level radio design

This paper introduces a multi-agent behavioral-based optimization algorithm for system level radio design. Making multi-standard wireless communication receivers that meet their specs while keeping the requirements of the individual blocks as relaxed as possible is the goal of this algorithm. In order to achieve this goal a “divide and conquer” approach is proposed. Different agents focus on different objectives that are pursued in parallel. Agents adopt different behaviors depending on the status of the environment and their interaction with other agents. Agents are cooperative by default as they try to meet their spec without making changes that affect other agents. However, more aggressive behaviors that lead to global changes can be adopted when needed. The interaction between these simple entities yields an emergent behavior able to deal smoothly with the complexity of the problem at hand.     

Near- and Far-Field Characterization of Planar mm-Wave Antenna Arrays with Waveguide-to-Microstrip Transition

We present the design and characterization of planar mm-wave patch antenna arrays with waveguide-to-microstrip transition using both near- and far-field methods. The arrays were designed for metrological assessment of error sources in antenna measurement. One antenna was designed for the automotive radar frequency range at 77 GHz, while another was designed for the frequency of 94 GHz, which is used, e.g., for imaging radar applications. In addition to the antennas, a simple transition from rectangular waveguide WR-10 to planar microstrip line on Rogers 3003? substrate has been designed based on probe coupling. For determination of the far-field radiation pattern of the antennas, we compare results from two different measurement methods to simulations. Both a far-field antenna measurement system and a planar near-field scanner with near-to-far-field transformation were used to determine the antenna diagrams. The fabricated antennas achieve a good matching and a good agreement between measured and simulated antenna diagrams. The results also show that the far-field scanner achieves more accurate measurement results with regard to simulations than the near-field scanner. The far-field antenna scanning system is built for metrological assessment and antenna calibration. The antennas are the first which were designed to be tested with the measurement system.     

Statistical analysis of achievable resolution limit in the near field source localization context

In this fast communication, we derive the statistical resolution limit (SRL), characterizing the minimal parameter separation, to resolve two closely spaced known near-field sources impinging on a linear array. Toward this goal, we conduct on the first-order Taylor expansion of the observation model a Generalized Likelihood Ratio Test (GLRT) based on a Constrained Maximum Likelihood Estimator (CMLE) of the SRL. More precisely, the minimum separation between two near-field sources, that is detectable for a given probability of false alarm and a given probability of detection, is derived herein. Finally, numerical simulations are done to quantify the impact of the array geometry of the signal sources power distribution and of the array aperture on the statistical resolution limit.     

Computationally efficient methods for blind decision feedback equalization of QAM signals

This paper investigates computationally efficient methods for blind decision feedback equalization (DFE) that reduce the complexity and power requirements of blind equalization algorithms while maintaining their steady-state characteristics for quadrature amplitude modulation (QAM) signals. These include the power-of-two error (POT), selective coefficient update (SCU), and frequency-domain block (FDB) methods. A novel radius-directed stop-and-go (RSG) method is introduced, which selectively adjusts the equalizer tap coefficients based on the equalizer output radius. In addition, a new activation/de-activation method based on the equalizer output radius is utilized to control the feedback equalizer (FBE) of the DFEs. Simulation studies and analysis are provided for empirically derived cable and microwave channels and Ricean fading channels.     

Automatic analysis of human posture equilibrium using empirical mode decomposition

The present study proposes a new approach for the assessment of the human balance control. This approach is based on the decomposition of the center of pressure displacement using empirical mode decomposition (EMD) that provides an effective time-frequency analysis of non-stationary signals. Twenty-eight healthy subjects performed quiet standing in four conditions—feet apart/together with respect to eyes open/closed—while recording the stabilometric signals in the anteroposterior (AP) and mediolateral (ML) directions. The EMD method decomposes each stabilometric signal into several subsignals called intrinsic mode functions (IMFs). Stabilogram-diffusion analysis technique is applied to generate the diffusion curve of each IMF signal. Each diffusion curve is modeled as a second-order system and provides representative features, such as the gain parameter. Analysis of the gain parameter shows the major effect of visual input and feet conditions on the strategy to control/stabilize the balance. Significant differences were found between young and elderly, and between women and men. In addition, the impact of feet position seems to be higher in ML direction than in AP direction.     

Relevance feedback for CBIR: a new approach based on probabilistic feature weighting with positive and negative examples.

In content-based image retrieval, understanding the user's needs is a challenging task that requires integrating him in the process of retrieval. Relevance feedback (RF) has proven to be an effective tool for taking the user's judgement into account. In this paper, we present a new RF framework based on a feature selection algorithm that nicely combines the advantages of a probabilistic formulation with those of using both the positive example (PE) and the negative example (NE). Through interaction with the user, our algorithm learns the importance he assigns to image features, and then applies the results obtained to define similarity measures that correspond better to his judgement. The use of the NE allows images undesired by the user to be discarded, thereby improving retrieval accuracy. As for the probabilistic formulation of the problem, it presents a multitude of advantages and opens the door to more modeling possibilities that achieve a good feature selection. It makes it possible to cluster the query data into classes, choose the probability law that best models each class, model missing data, and support queries with multiple PE and/or NE classes. The basic principle of our algorithm is to assign more importance to features with a high likelihood and those which distinguish well between PE classes and NE classes. The proposed algorithm was validated separately and in image retrieval context, and the experiments show that it performs a good feature selection and contributes to improving retrieval effectiveness.     

Interoperability in Internet of Things: Taxonomies and Open Challenges

Mobile Networks and Applications - In the last few years, many smart objects found in the physical world are interconnected and communicate through the existing internet infrastructure which...