Miracle-dz/UniFAR-FTUs huggingface dataset:
An Injection-Locked Power Up-Converter in 65-nm CMOS for Cellular Applications

This paper presents an injection-locked 65-nm CMOS circuit that upconverts and power amplifies baseband signals to RF. The circuit delivers an RF output power of 28.7 dBm, with a power gain and maximum power added efficiency (PAE) of 20.6 dB and 68.1%, respectively. Both AM–AM-conversion and AM–PM-conversion are low, less than 1 dB and 1°, respectively, resulting in an EVM of 4.7% for Long Term Evolution (LTE) and 4.1% for WCDMA signals. The circuit provides an average output power of 20.3 dBm for LTE, with a PAE of 44.1%, and for WCDMA, the average output power is 23.8 dBm with a PAE of 55.6%. Supply modulation improves power back-off efficiency and the voltage range is from 540 mV to 3 V. The spectral mask for LTE signals has a worst case ACLR of 33.2 dBc using predistortion. For WCDMA signals, ACLR<sub>1</sub> is 39.9 dBc and ACLR<sub>2</sub> is 47.2 dBc, both values worst case and using baseband predistortion. This performance is achieved by introducing a cross-coupled cascode topology, and supporting theory and simulations are presented. The startup loop-gain and small-signal equivalents are derived, a power dissipation analysis is performed, and the injection circuit is analyzed to investigate the AM–PM behavior. Analysis and simulations show that, compared to conventional cascode amplifiers, PAE is improved by 24% (15% points). The circuit is implemented in an STM 65-nm CMOS process and occupies an area of <inline-formula> <tex-math notation="LaTeX">$1.0 \times 0.53$ </tex-math></inline-formula> mm<sup>2</sup>.
Design of the Software Architecture for Starcraft Video Game on the Basis of Finite State Machines

Video game StarCraft is a tool for development of control algorithms. Authors describe different approaches to win the game: coordination of independent rational agents and central control of squad of agents as a whole. Authors select classical approach of finite state machines. The article shows specific in software design for both approaches. Authors describe differences in software architecture and in finite state machines in these approaches and format of storing the information in separate files.Authors propose mathematical model of the solution, realization of generic algorithms for game control, discuss differences in variations of finite state machines. Authors discuss possibility of using state machines in combination with decision trees. Authors conducted the experiment; the results showed advantages and limitations of the discussed architecture.
Acidianus, Sulfolobus and Metallosphaera surface layers: structure, composition and gene expression

The cell walls of Sulfolobales species consist of proteinaceous S‐layers assembled from two polypeptides, SlaA and SlaB. We isolated the large S‐layer protein of Acidianus ambivalens and both S‐layer subunits of Sulfolobus solfataricus and Metallosphaera sedula, respectively. The slaAB genes, lying adjacently in the chromosomes, are constitutively transcribed as bicistronic operons in A. ambivalens and S. solfataricus. A smaller slaA transcript appeared in Northern hybridizations of A. ambivalens RNA. PCRs experiments showed that 80–85% of the transcripts stop at an oligo‐T terminator downstream of slaA while 15–20% are read through to a second terminator downstream of slaB. The bicistronic operons including promoter and terminator regions are conserved in the Sulfolobales. While no SlaA homologue is found outside the Sulfolobales, SlaB is distantly similar to S‐layer proteins of other Crenarchaeota, e.g. the Staphylothermus marinus tetrabrachion. Molecular modelling suggests SlaBs to be composed of 2–3 consecutive beta sandwich domains, a coiled‐coil domain of 15–17 nm in length and a C‐terminal transmembrane helix. Electron microscopy shows crystalline protein arrays with triangular and hexagonal pores. We propose that the mushroom‐shaped ‘unit cells’ of the Sulfolobales' S‐layers consist of three SlaBs anchoring the complex in the membrane and six SlaAs forming the detergent‐resistant outer sacculus.
BIM, GIS, IoT, and AR/VR Integration for Smart Maintenance and Management of Road Networks: a Review

The management and maintenance of road infrastructures demand the use of a tremendous amount of data about their maintenance history and current status. One very characteristic of this information is its geographic nature, which suggests that Geographic Information Systems (GIS) are appropriate to facilitate the way we handle it. However, the access to such information nowadays is challenging because of numerous reasons: some data is still mainly stored on paper; databases are out of date; managing scarcely existing records and creating new ones is quite a laborious and time-consuming task; field inspections require human resources and are expensive; and so forth. Thus, we need to make smarter the way management and maintenance of road infrastructures are performed. Some promising technologies appeared in the last few years to overcome a number of the identified issues. This paper presents and discusses on the most prominent work efforts aiming at more intelligent management of the city infrastructures, specially focusing on transport networks. Several of such efforts use Geographic Information Systems, Building Information Modelling (BIM), Internet of Things (IoT), and Virtual/Augmented Reality (VR/AR) technologies. Thus, this study emphasizes on the GIS-BIM-IoT and GIS-BIM-VR/AR integrations showing the possibilities and potentials when these technologies work together.
Wideband Microwave Frequency Division Based on an Optoelectronic Oscillator

A novel wideband microwave frequency divider based on a single-loop optoelectronic oscillator (OEO) is proposed and demonstrated. The Mach-Zehnder modulator in the OEO is biased at the carrier suppression point to generate the ±1st order optical sidebands by the input frequency and the oscillating frequency, which produces an intermediate-frequency (IF) signal at a photodetector. If the IF frequency is half of the input frequency, optoelectronic oscillation is established, which outputs an RF signal with a frequency that is 1/2 of the input frequency. Because there are no filters incorporated in the OEO loop, the operation frequency range is broad. In a proof-of-concept experiment, the input signal with a frequency ranging from 12 to 20 GHz (or from 20 to 36 GHz) is successfully divided into 6 to 10 GHz (or 10 to 18 GHz). The maximum power ripple is 2.92 dB, and the phase noise improvement is 5.71 dB, which agrees well with the theoretical value.
Experimental Study of Inductive Energy Transfer in Strong Coupling Mode

Specific geometry of inductively coupled coils can be distinguished for transcutaneous energy powering of implantable medical devices. Characteristic dimensions of the transmitter and receiver are of order 0.1. 1 cm, distance between the coils is less than their characteristic dimension. "Strong coupling" phenomenon and appearance of the "frequency splitting" effect occur, if quality factors are high and coupling between the coils is good. An experimental scheme was developed for studying of a strongly coupled system. The analysis of RLC-circuits was carried out and ratios between coupling and frequency splitting coefficients were determined. Frequency response in the "strong coupling" mode in the range of axial distances from 5 to 70 mm and frequencies from 780 to 2460 kHz was obtained. The designed scheme can be used for the researches of wireless energy transfer and for verification frequency tuning methods.
Unexpected chemoreceptors mediate energy taxis towards electron acceptors in Shewanella oneidensis

Shewanella oneidensis uses a wide range of terminal electron acceptors for respiration. In this study, we show that the chemotactic response of S. oneidensis to anaerobic electron acceptors requires functional electron transport systems. Deletion of the genes encoding dimethyl sulphoxide and trimethylamine N‐oxide reductases, or inactivation of these molybdoenzymes as well as nitrate reductase by addition of tungstate, abolished electron acceptor taxis. Moreover, addition of nigericin prevented taxis towards trimethylamine N‐oxide, dimethyl sulphoxide, nitrite, nitrate and fumarate, showing that this process depends on the ΔpH component of the proton motive force. These data, together with those concerning response to metals ( Bencharit and Ward, 2005 ), support the idea that, in S. oneidensis, taxis towards electron acceptors is governed by an energy taxis mechanism. Surprisingly, energy taxis in S. oneidensis is not mediated by the PAS‐containing chemoreceptors but rather by a chemoreceptor (SO2240) containing a Cache domain. Four other chemoreceptors also play a minor role in this process. These results indicate that energy taxis can be mediated by new types of chemoreceptors.
Co-Designed mm-Wave and LTE Handset Antennas

Fifth generation (5G) mobile networks will introduce several new frequencies for short-range high-capacity communications. Future handsets must also support current frequency bands for backward compatibility and long-range communications. This paper presents a proof-of-concept solution for co-designed millimeter-wave (mm-wave) and Long Term Evolution (LTE) antennas in a metal-rimmed handset. The design shows that both antenna types can be accommodated in a shared volume and be integrated into the same structure. Presented antennas operate at 700–960 MHz, 1710–2690 MHz, and 25–30 GHz. Simulations and measurements suggest that the system can be designed in such a way that the mm-wave antenna does not hinder the low-band performance. LTE antennas generally reach over 60% total efficiency while the mm-wave module has a peak gain of 7 dBi with measurement-verified beam-steering capability. The proposed design proves that 5G mm-wave antennas can be embedded to 4G systems without greatly sacrificing display size or sub-6 GHz antenna performance.
An Interaction-Aware Lane Change Behavior Planner for Automated Vehicles on Highways Based on Polygon Clipping

This letter presents automated driving using polygon clipping (A-D-PolyC), a novel framework for lane change behavior planning of automated vehicles on highways. It assumes that a mission planning layer generates lane change requests. In crowded traffic scenes, various variants for the lane change execution arise. The developed algorithm identifies the maneuver variants deterministically and in bounded runtime using polygon clipping in spatiotemporal domain. The variants are represented using a graph that captures the scene topology. Afterward, it efficiently samples optimal lateral and longitudinal trajectories with regard to vehicle dynamics. The satisfaction of hard constraints is checked. Finally, a scene prediction is conducted for a subset of the sampled trajectories. In comparison with most state of the art approaches, the framework accounts for traffic interaction and collects meaningful features. A novel measure based on generalized kinetic energies for the impact of a maneuver execution on the whole traffic scene is introduced. A-D-PolyC is a hierarchical, holistic, modular, and parallelizable concept that can be coupled with different scene prediction engines and lower-level local trajectory planners. The performance of A-D-PolyC is statistically evaluated using randomized simulation runs and compared to a state of the art approach.
Three-Way Multiple-Mode Cavity Filtering Crossover for Narrowband and Broadband Applications

In this paper, the design of a cavity crossover with three intersecting channels is presented. The three fundamental modes of a cavity resonator, namely, TE011, TE101, and TM110 modes, are adopted to resonate at each of three channels, respectively. Due to the modal orthogonality of these fundamental modes, high isolation among three channels can be achieved. Two kinds of crossovers, for narrowband and broadband applications, are presented. For the narrowband case, the proposed crossover resonates at 2.91 GHz with the fractional bandwidth of 1.4%. For the broadband case, the proposed crossover resonates at 3 GHz with the fractional bandwidth of 24%. The isolations of both designs reach more than 50 dB. For a proof of concept, the broadband example of the cavity crossover structures is fabricated and measured. A good agreement between the simulated and the measured results verifies the accuracy of the proposed design methodology.
Enhancing the Efficiency and Technology of Community Kitchen for 5500 Persons Through Scheffler Solar Concentrator

This paper presents three different studies for enhancing efficiency and technology for the cooking system through CST (Concentrated Solar Thermal) based cooking system which has capacity to cook for 5,500 people, installed at Baru Sahib, in Sirmaur district of Himachal Pradesh, India at latitude 30.76°N and longitude 77.30°E. Firstly, this paper presents a cumulative analysis of thermal efficiency and other parameters, which are studied to evaluate the performance of Scheffler based cooking system under various seasons. Efficiency for winter season was found as 40.08% which is higher when compared to efficiencies for other seasons. Secondly, calculation of thermal efficiency and analysis of heat loss are done for CST based cooking system resulting in 32.32% thermal efficiency and 25% heat loss respectively. Lastly, this study focuses on comparative analysis conducted for running the community kitchen through Scheffler solar concentrator (with diesel operated boiler as back-up) with conventional LPG based system and diesel operated boiler system. This analysis resulted as more cost-effective for Scheffler based cooking system with respect to diesel operated boiler and LPG based system as high as 53.99% and 86.34% respectively.
Digging Deeper Into Egocentric Gaze Prediction

This paper digs deeper into factors that influence egocentric gaze. Instead of training deep models for this purpose in a blind manner, we propose to inspect factors that contribute to gaze guidance during daily tasks. Bottom-up saliency and optical flow are assessed versus strong spatial prior baselines. Task-specific cues such as vanishing point, manipulation point, and hand regions are analyzed as representatives of top-down information. We also look into the contribution of these factors by investigating a simple recurrent neural model for ego-centric gaze prediction. First, deep features are extracted for all input video frames. Then, a gated recurrent unit is employed to integrate information over time and to predict the next fixation. We propose an integrated model that combines the recurrent model with several top-down and bottom-up cues. Extensive experiments over multiple datasets reveal that (1) spatial biases are strong in egocentric videos, (2) bottom-up attention models perform poorly in predicting gaze and underperform spatial biases, (3) deep features perform better compared to traditional features, (4) as opposed to hand regions, the manipulation point is a strong influential cue for gaze prediction, (5) combining the proposed recurrent model with bottom-up cues, vanishing points and, in particular, manipulation point results in the best gaze prediction accuracy over egocentric videos, (6) the knowledge transfer works best for cases where the tasks or sequences are similar, and (7) task and activity recognition can benefit from gaze prediction. Our findings suggest that (1) there should be more emphasis on hand-object interaction and (2) the egocentric vision community should consider larger datasets including diverse stimuli and more subjects.
Exploiting Dynamic Sparsity for Downlink FDD-Massive MIMO Channel Tracking

Accurate channel tracking with a small pilot overhead is vital for real-time massive multiple-input and multiple-output (MIMO) communication over a dynamic channel. Recently, compressive sensing has been applied to reduce the pilot overheads by exploiting the spatial and/or temporal correlation of massive MIMO channels. However, most existing channel estimation and tracking algorithms are based on oversimplified channel models with restrictive assumptions, and thus perform poorly under realistic channels. In this paper, we consider downlink frequency-division duplexing-massive MIMO system operating with limited scattering around the base station and flat fading channel is considered. We propose a two-dimensional Markov Model (2D-MM) to capture the 2-D dynamic sparsity (i.e., structured sparsity in the spatial domain and probabilistic temporal dependency of channel in the temporal domain) of massive MIMO channels. The 2D-MM has the flexibility to model different propagation environments in practice. We derive an effective message passing algorithm called dynamic turbo orthogonal approximate message passing (D-TOAMP) to recursively track a dynamic massive MIMO channel with a 2D-MM prior. The proposed D-TOAMP algorithm does not require knowledge of the 2D-MM channel parameters, which could be automatically learned through the expectation maximization framework. Extensive simulations show that the proposed D-TOAMP can achieve significant gains over the existing algorithms under realistic channels.
Online Machine Learning Experiments in HTML5

This work in progress paper describes software that enables online machine learning experiments in an undergraduate DSP course. This software operates in HTML5 and embeds several digital signal processing functions. The software can process natural signals such as speech and can extract various features, for machine learning applications. For example in the case of speech processing, LPC coefficients and formant frequencies can be computed. In this paper, we present speech processing, feature extraction and clustering of features using the K-means machine learning algorithm. The primary objective is to provide a machine learning experience to undergraduate students. The functions and simulations described provide a user-friendly visualization of phoneme recognition tasks. These tasks make use of the Levinson-Durbin linear prediction and the K-means machine learning algorithms. The exercise was assigned as a class project in our undergraduate DSP class. The description of the exercise along with assessment results is described.
Objective Quality Evaluation of an Angularly-Continuous Light-Field Format

With the rapid advances in light-field display and camera technology, research in light-field content creation, visualization, coding and quality assessment has gained momentum. While light-field cameras are already available to the consumer, light-field displays need to overcome several obstacles in order to become a commonplace. One of these challenges is the unavailability of a light-field visualization format which can be used across various light-field displays. Existing light-field representations are optimized for specific displays and converting them for visualization on a different display is a computationally expensive operation, often resulting in the degradation of perceptual quality. To this end, an intermediate, display-independent and angularly-continuous light-field representation format has been proposed recently, targeted towards large-field-of-view light-field displays. In this paper, we evaluate the said data format in terms of degradation in objective quality under three compression methods. We found that, while offering display-independence, the intermediate light-field format maintains the same objective quality in general and achieves higher objective quality in some cases compared to the conventional linear camera representation.
Compact 60 GHz Phased-Array Antennas With Enhanced Radiation Properties in Flip-Chip BGA Packages

Compact phased-array antennas embedded in flip-chip ball grid array (BGA) packages are proposed to operate over the unlicensed 60 GHz frequency band. Radiation properties are enhanced by designing novel corrugated soft-surface structures and implementing them using the low-temperature co-fired ceramic process with no extra cost and fabrication complexity. This is achieved by adjusting via land diameters of periodic grounded vias in top four layers of the package, which in fact create perfect magnetic boundaries between the phased-array antenna elements to modify the electric near-field distributions and consequently improve far-field characteristics including gain, cross polarization, sidelobe level, and beam steering. Low-loss transitions from flip-chip IC to antenna elements are designed with less than 0.1 dB amplitude and 2° phase imbalance over 50–70 GHz. Prototypes with/without soft-surface structures are fabricated to work with flip-chip ICs with/without switches. A USB-interface adapter and a waveguide-interface module with a compact vertical power combiner are proposed for the first time to experimentally evaluate the phased-array antenna while connected to the flip-chip RF IC. Significant miniaturizations and improvements are achieved over the wide frequency range of 56–67 GHz, demonstrating up to 7 dB reduction in sidelobe level, up to 4 dB reduction in cross polarization, and up to 3 dB enhancement in gain at different directions.
Ventral-Dorsal Neural Networks: Object Detection Via Selective Attention

Deep Convolutional Neural Networks (CNNs) have been repeatedly proven to perform well on image classification tasks. Object detection methods, however, are still in need of significant improvements. In this paper, we propose a new framework called Ventral-Dorsal Networks (VDNets) which is inspired by the structure of the human visual system. Roughly, the visual input signal is analyzed along two separate neural streams, one in the temporal lobe and the other in the parietal lobe. The coarse functional distinction between these streams is between object recognition — the "what" of the signal - and extracting location related information — the "where" of the signal. The ventral pathway from primary visual cortex, entering the temporal lobe, is dominated by "what" information, while the dorsal pathway, into the parietal lobe, is dominated by "where" information. Inspired by this structure, we propose the integration of a "Ventral Network" and a "Dorsal Network", which are complementary. Information about object identity can guide localization, and location information can guide attention to relevant image regions, improving object recognition. This new dual network framework sharpens the focus of object detection. Our experimental results reveal that the proposed method outperforms state-of-the-art object detection approaches on PASCAL VOC 2007 by 8% (mAP) and PASCAL VOC 2012 by 3% (mAP). Moreover, a comparison of techniques on Yearbook images displays substantial qualitative and quantitative benefits of VDNet.
Co‐ordinated regulation of two divergent promoters through higher‐order complex formation by the LysR‐type regulator ThnR

The genes required for tetralin biodegradation by Sphingomonas macrogolitabida strain TFA are clustered in two divergent and closely linked operons. ThnR, a LysR‐type regulator, activates transcription from each operon in response to tetralin. The regulatory thnR gene is co‐transcribed with the catabolic genes thnC, thnA3 and thnA4, resulting in positive autoregulation. ThnR binds with different affinity to two primary binding sites, designated B and C, in the intervening region between the two operons and makes additional contact with secondary sites that extend towards the promoters. In addition, ThnR may interact with itself when bound to each site via the formation of a DNA loop, as evidenced by the distortion of the DNA between the primary binding sites and the elimination of the higher‐order complexes following the introduction of a half‐turn of the DNA helix between the primary binding sites. Transcription from each promoter is not fully independent since mutations in each binding site affected transcription from both promoters. Based on these results, we propose a model of transcription activation that involves the formation of a complex structure by interactions between ThnR molecules bound to distant binding sites and favours transcription from one promoter to the detriment of the other.