Data-driven design of intelligent wireless networks: an overview and tutorial

Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves

Analysis of the optimum gain of a high-pass l-matching network for rectennas

Rectennas, which mainly consist of an antenna, matching network, and rectifier, are used to harvest radiofrequency energy in order to power tiny sensor nodes, e.g., the nodes of the Internet of Things. This paper demonstrates for the first time, the existence of an optimum voltage gain for high-pass L-matching networks used in rectennas by deriving an analytical expression. The optimum gain is that which leads to maximum power efficiency of the rectenna. Here, apart from the L-matching network, a Schottky single-diode rectifier was used for the rectenna, which was optimized at 868 MHz for a power range from -30 dBm to -10 dBm. As the theoretical expression depends on parameters not very well-known a priori, an accurate search of the optimum gain for each power level was performed via simulations. Experimental results show remarkable power efficiencies ranging from 16% at -30 dBm to 55% at -10 dBm, which are for almost all the tested power levels the highest published in the literature for similar designs.Postprint (author's final draft

Evaluation of multiple slices and tiles in HEVC video encoding

Σημείωση: διατίθεται συμπληρωματικό υλικό σε ξεχωριστό αρχείο

Prediction of necrotic core and hypoxic zone of multicellular spheroids in a microbioreactor with a U-shaped barrier

© 2018 by the authors. Microfluidic devices have been widely used for biological and cellular studies. Microbioreactors for three-dimensional (3D) multicellular spheroid culture are now considered as the next generation in in vitro diagnostic tools. The feasibility of using 3D cell aggregates to form multicellular spheroids in a microbioreactor with U-shaped barriers has been demonstrated experimentally. A barrier array is an alternative to commonly used microwell traps. The present study investigates oxygen and glucose concentration distributions as key parameters in a U-shaped array microbioreactor using finite element simulation. The effect of spheroid diameter, inlet concentration and flow rate of the medium are systematically studied. In all cases, the channel walls are considered to be permeable to oxygen. Necrotic and hypoxic or quiescent regions corresponding to both oxygen and glucose concentration distributions are identified for various conditions. The results show that the entire quiescent and necrotic regions become larger with increasing spheroid diameter and decreasing inlet and wall concentration. The shear stress (0.5-9 mPa) imposed on the spheroid surface by the fluid flow was compared with the critical values to predict possible damage to the cells. Finally, optimum range of medium inlet concentration (0.13-0.2 mM for oxygen and 3-11 mM for glucose) and flow rate (5-20 μL/min) are found to form the largest possible multicellular spheroid (500 μm), without any quiescent and necrotic regions with an acceptable shear stress. The effect of cell-trap types on the oxygen and glucose concentration inside the spheroid was also investigated. The levels of oxygen and glucose concentration for the microwell are much lower than those for the other two traps. The U-shaped barrier created with microposts allows for a continuous flow of culture medium, and so improves the glucose concentration compared to that in the integrated U-shaped barrier. Oxygen concentration for both types of U-shaped barriers is nearly the same. Due to the advantage of using U-shaped barriers to culture multicellular spheroids, the results of this paper can help to choose the experimental and design parameters of the microbioreactor

Advanced CMOS Integrated Circuit Design and Application

The recent development of various application systems and platforms, such as 5G, B5G, 6G, and IoT, is based on the advancement of CMOS integrated circuit (IC) technology that enables them to implement high-performance chipsets. In addition to development in the traditional fields of analog and digital integrated circuits, the development of CMOS IC design and application in high-power and high-frequency operations, which was previously thought to be possible only with compound semiconductor technology, is a core technology that drives rapid industrial development. This book aims to highlight advances in all aspects of CMOS integrated circuit design and applications without discriminating between different operating frequencies, output powers, and the analog/digital domains. Specific topics in the book include: Next-generation CMOS circuit design and application; CMOS RF/microwave/millimeter-wave/terahertz-wave integrated circuits and systems; CMOS integrated circuits specially used for wireless or wired systems and applications such as converters, sensors, interfaces, frequency synthesizers/generators/rectifiers, and so on; Algorithm and signal-processing methods to improve the performance of CMOS circuits and systems

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Energy and Area Efficient Machine Learning Architectures using Spin-Based Neurons

Recently, spintronic devices with low energy barrier nanomagnets such as spin orbit torque-Magnetic Tunnel Junctions (SOT-MTJs) and embedded magnetoresistive random access memory (MRAM) devices are being leveraged as a natural building block to provide probabilistic sigmoidal activation functions for RBMs. In this dissertation research, we use the Probabilistic Inference Network Simulator (PIN-Sim) to realize a circuit-level implementation of deep belief networks (DBNs) using memristive crossbars as weighted connections and embedded MRAM-based neurons as activation functions. Herein, a probabilistic interpolation recoder (PIR) circuit is developed for DBNs with probabilistic spin logic (p-bit)-based neurons to interpolate the probabilistic output of the neurons in the last hidden layer which are representing different output classes. Moreover, the impact of reducing the Magnetic Tunnel Junction\u27s (MTJ\u27s) energy barrier is assessed and optimized for the resulting stochasticity present in the learning system. In p-bit based DBNs, different defects such as variation of the nanomagnet thickness can undermine functionality by decreasing the fluctuation speed of the p-bit realized using a nanomagnet. A method is developed and refined to control the fluctuation frequency of the output of a p-bit device by employing a feedback mechanism. The feedback can alleviate this process variation sensitivity of p-bit based DBNs. This compact and low complexity method which is presented by introducing the self-compensating circuit can alleviate the influences of process variation in fabrication and practical implementation. Furthermore, this research presents an innovative image recognition technique for MNIST dataset on the basis of p-bit-based DBNs and TSK rule-based fuzzy systems. The proposed DBN-fuzzy system is introduced to benefit from low energy and area consumption of p-bit-based DBNs and high accuracy of TSK rule-based fuzzy systems. This system initially recognizes the top results through the p-bit-based DBN and then, the fuzzy system is employed to attain the top-1 recognition results from the obtained top outputs. Simulation results exhibit that a DBN-Fuzzy neural network not only has lower energy and area consumption than bigger DBN topologies while also achieving higher accuracy

Miniature high dynamic range time-resolved CMOS SPAD image sensors

Since their integration in complementary metal oxide (CMOS) semiconductor technology in 2003, single photon avalanche diodes (SPADs) have inspired a new era of low cost high integration quantum-level image sensors. Their unique feature of discerning single photon detections, their ability to retain temporal information on every collected photon and their amenability to high speed image sensor architectures makes them prime candidates for low light and time-resolved applications. From the biomedical field of fluorescence lifetime imaging microscopy (FLIM) to extreme physical phenomena such as quantum entanglement, all the way to time of flight (ToF) consumer applications such as gesture recognition and more recently automotive light detection and ranging (LIDAR), huge steps in detector and sensor architectures have been made to address the design challenges of pixel sensitivity and functionality trade-off, scalability and handling of large data rates. The goal of this research is to explore the hypothesis that given the state of the art CMOS nodes and fabrication technologies, it is possible to design miniature SPAD image sensors for time-resolved applications with a small pixel pitch while maintaining both sensitivity and built -in functionality. Three key approaches are pursued to that purpose: leveraging the innate area reduction of logic gates and finer design rules of advanced CMOS nodes to balance the pixel’s fill factor and processing capability, smarter pixel designs with configurable functionality and novel system architectures that lift the processing burden off the pixel array and mediate data flow. Two pathfinder SPAD image sensors were designed and fabricated: a 96 × 40 planar front side illuminated (FSI) sensor with 66% fill factor at 8.25μm pixel pitch in an industrialised 40nm process and a 128 × 120 3D-stacked backside illuminated (BSI) sensor with 45% fill factor at 7.83μm pixel pitch. Both designs rely on a digital, configurable, 12-bit ripple counter pixel allowing for time-gated shot noise limited photon counting. The FSI sensor was operated as a quanta image sensor (QIS) achieving an extended dynamic range in excess of 100dB, utilising triple exposure windows and in-pixel data compression which reduces data rates by a factor of 3.75×. The stacked sensor is the first demonstration of a wafer scale SPAD imaging array with a 1-to-1 hybrid bond connection. Characterisation results of the detector and sensor performance are presented. Two other time-resolved 3D-stacked BSI SPAD image sensor architectures are proposed. The first is a fully integrated 5-wire interface system on chip (SoC), with built-in power management and off-focal plane data processing and storage for high dynamic range as well as autonomous video rate operation. Preliminary images and bring-up results of the fabricated 2mm² sensor are shown. The second is a highly configurable design capable of simultaneous multi-bit oversampled imaging and programmable region of interest (ROI) time correlated single photon counting (TCSPC) with on-chip histogram generation. The 6.48μm pitch array has been submitted for fabrication. In-depth design details of both architectures are discussed

Cities' Identity Through Architecture and Art

Intended to be a guide for academics, scholars, and interested leaders, this book was designed to critically assess issues related to architectural identity, the city as a scene, the city as an organism, the city as a subject, and the planning or rather approaching of one. A pressing issue for many researchers in the field, the book discusses the negative repercussions resulting from globalization. Studies have indicated that globalization, despite all the positive effects, has resulted in a loss of identity within a city. As a city develops over time, its identity is evolving as well and may even be lost due to rapid and constant changes it is subjected to. Discussed as well are examples and tendencies in dealing with urban identities as well as the transformation of cities and urban cultures mentioned in terms of form, identity, and art. This book is a combination of innovative research submitted to a conference on Cities’ Identity Through Architecture and Arts (CITAA) whereas scholars from all over the world gather in one venue to discuss cultural, historical, and economic issues of the city. Thus, the book offers a collective and global solution that is applicable on a universal level. The research presented in this book was conducted by authors, or rather participants of the conference from, three different continents of the world and organized by IEREK. It was a distinct opportunity for them to share their thoughts with leading scholars and professionals in the field of Architecture, Arts, and Planning. The research and materials in this book are directed at those who are actively engaged in the decision-making processes and to a heterogeneous audience who has an interest to critically examine all the new literature available in the field. A special word of thanks should be made to the editors of this book and to all the authors and co-authors of the chapters who collectively provided the academic community with unique and increasingly valuable literature