Indicadores de sostenibilidad ambiental en el periurbano de la ciudad de Mar del Plata, Argentina

Los indicadores de sostenibilidad conforman herramientas útiles para la toma de decisiones. Las ciudades latinoamericanas, y especialmente las áreas de expansión sin planificación adecuada, enfrentan desafíos cada vez mayores para revertir problemáticas que amenazan su sostenibilidad. El presente trabajo evalúa de manera preliminar, la sostenibilidad ambiental del periurbano de Mar del Plata (Argentina) tomando como referencia algunos de los indicadores propuestos por el modelo del Banco Interamericano de Desarrollo en la Iniciativa Ciudades Emergentes y Sostenibles. Se construyó un índice sintético (Índice de Sostenibilidad Ambiental, ISA) que integra trece indicadores agrupados en ocho temas. Las situaciones más críticas (ISA: 0,45-0,558) se identifican fundamentalmente en zonas en las que se desarrollan actividades rurales y en las que se localizan asentamientos de carácter precario. El estudio realizado profundiza en el conocimiento de la dimensión ambiental de la sostenibilidad, enfatizando en el análisis de los contrastes internos del periurbano marplatense.

Analysis of the effect of finite d.c. blocking capacitance and finite d.c. feed inductance on the performance of inverse class-E amplifiers

The first analysis and synthesis equations for the newly introduced inverse Class-E amplifier when operated with a finite d.c. blocking capacitance and a finite d.c.-feed inductance are presented in the paper. Closed-form design equations are derived in order to establish the circuit component values required for optimum synthesis. Excellent agreement between numerical simulation results and theoretical prediction is obtained. It is shown that drain efficiency approaching 100 at a pre-specified output power level can be achieved as zero-current switching and zero-current derivative conditions are simultaneously satisfied. The proposed analysis offers the prospect for realistic MMIC implementation.

A Low Complexity Real-time MIMO-Preprocessing For Fixed Complexity Sphere Decoder

Modern Multiple-Input Multiple-Output (MIMO) communication systems place huge demands on embedded processing resources in terms of throughput, latency and resource utilization. State-of-the-art MIMO detector algorithms, such as Fixed-Complexity Sphere Decoding (FSD), rely on efficient channel preprocessing involving numerous calculations of the pseudo-inverse of the channel matrix by QR Decomposition (QRD) and ordering. These highly complicated operations can quickly become the critical prerequisite for real-time MIMO detection, exaggerated as the number of antennas in a MIMO detector increases. This paper describes a sorted QR decomposition (SQRD) algorithm extended for FSD, which significantly reduces the complexity and latency
of this preprocessing step and increases the throughput of MIMO detection. It merges the calculations of the QRD and ordering operations to avoid multiple iterations of QRD. Specifically, it shows that SQRD reduces the computational complexity by over 60-70% when compared to conventional
MIMO preprocessing algorithms. In 4x4 to 7x7 MIMO cases, the approach suffers merely 0.16-0.2 dB reduction in Bit Error Rate (BER) performance.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

An Improvement of Subject Reacquisition by Reasoning and Revision

CCTV systems are broadly deployed in the present world. Despite this, the impact on anti-social and criminal behaviour has been minimal. Subject reacquisition is a fundamental task to ensure in-time reaction for intelligent surveillance. However, traditional reacquisition based on face recognition is not scalable, hence in this paper we use reasoning techniques to reduce the computational effort which deploys the time-of-flight information between interested zones such as airport security corridors. Also, to improve accuracy of reacquisition, we introduce the idea of revision as a method of post-processing.We demonstrate the significance and usefulness of our framework with an experiment which shows much less computational effort and better accuracy.