Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Design of Aperiodic Arrays for Ultrawideband Beam Scanning and Full
 Polarization Reconfiguration

─ In this letter, a multifunction aperture array is proposed for ultrawideband (UWB) scanning and polarization reconfiguration. The UWB array consisted of linearly polarized elements is capable of operating in four polarization modes (+45° linear polarization (LP), -45° linear polarization, left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP)). This work involves two essential techniques: (a) A new beam-scanning UWB array synthesis approach. An iterative convex optimization strategy is utilized to determine the element locations and obtain the minimum sidelobe level (SLL) for multiple patterns. (b) The polarization reconfigurable technique for beam-scannable arrays. In this part, a sequential rotation and excitation compensation (SR-EC) technique provides polarization reconfiguration for a beam-scannable array consisting of linearly polarized elements. A beam-scanning UWB array is designed by using the proposed UWB array synthesis approach and the SR-EC polarization reconfigurable technique. The Feko numerical result shows 0°-60° beam peak steering, a 4:1 bandwidth (1-4 GHz), and fourpolarization reconfigurability. Index Terms ─ Array synthesis, beam scanning, polarization reconfiguration, ultrawideband.
Monolithic GaAs PHEMT MMICs integrated with high performance MEMS microrelays

We report the successful integration of MEMS microrelays with PHEMT MMIC in a single monolithic structure. The process we describe here allows us to build MEMS microrelays along GaAs PHEMT devices without any sacrifice in performance or yield to either device. The test structure used the switches to activate one of two X-band LNAs. The switches have an insertion loss of less than 0.3 dB up to 50 GHz while the LNAs have a gain of 20 dB and 1.1 dB NF at 9 GHz.
CCGT unit with a carbonation system for CO2 capture

The paper considers the issues of creating energy-efficient and environmentally friendly resource-saving energy generation technologies based on fossil fuels, solid waste and materials. A natural gas CCGT with a MSW ash carbonation unit was chosen as the research object. The prototype of the CCGT unit is the CCGT “Akademicheskaya” with an installed capacity of 230 MW. For the carbonation of MSW ash, a direct semi-dry route is used. In the calculation of the CCGT, the power and efficiency of the cycle are determined, as well as the parameters of the flue gas, which are transferred to the calculation of carbonation. As a result of calculations, it was found that this specific CO2 emissions from the power plant using carbonation can be reduced by almost 20% from 403 to 329 g kWh-1, however, a large amount of required MSW (2.6-6.7 kg per kg of flue gases) causes certain difficulties for the implementation of the project.
Applicability of single sample method to test strength parameters of sandstone

The single sample method allows the mechanical parameters of rocks to be obtained with very few rock samples; however, the method has not been widely used. This is mainly because the yield point of the single sample method is more difficult to control than the conventional triaxial compressive test and the effect of the different control methods on the measured data is not well understood. The single sample method obtains the strength parameters of the rock by loading a single rock sample with multiple stages of confining pressure. Multistage loading tests are divided into peak strength control and long-term strength control according to yield point control. In this study, multistage loading tests of sandstone were carried out to obtain strength parameters using long-term strength control. The results show that sandstones undergo seriously brittle damage in conventional triaxial compressive tests. Although the sandstones have been rigorously selected, they still vary considerably, and long-term strength points are more difficult to control. The error of strength parameters of sandstone obtained using the single sample method may exceed 20% compared to those obtained by conventional triaxial compressive tests. So this method must be used with caution for sandstones.
Rare earth doping effect on the thermal stability of Ce0.35Zr0.60M0.05O2: insights from experiment and simulation

CexZr1-xO2 (CZ) plays an important role in many environment catalytic fields such as automobile three-way catalysts (TWCs), but improving their thermal stability is still a great challenge. In this work, a strategy was proposed to enhance the thermal stability of CZ by combining experiment with ab-initio molecular dynamics (AIMD) method. It is found that the thermal stability of Ce0.35Zr0. 60M0.05O2 (M represent La, Y, and Nd elements) could be adjusted by doping the suitable rare earth (RE) elements in the surface of CZ. With this strategy, the thermal stability of Ce0.35Zr0. 60M0.05O2 (CZ-Y) with surface doping of Y is highest among these Ce0.35Zr0. 60M0.05O2 samples. In comparison with the CZ sample without doping (specific surface area SSA=20.16 m2⋅g-1), CZ-Y exhibit superior thermal stability (SSA=26.83 m2⋅g-1) after thermal treatment (1100 °C/10 h). To give a deep insight into the RE doping effects, the thermal displacement rate (TDR) of Ce0.35Zr0. 60M0.05O2 are further calculated by AIMD. It is found that CZ-Y has the lowest TDR values, which is beneficial for suppressing the thermal displacement of atoms and improving the thermal stability of CZ. This study provides a deep insight into the origin of rare earth (RE) doping effect on CexZr1-xO2 (CZ), which is of fundamental interest for the development of high performance CZ in practical applications.
The Quantum Calculation for Valence Band Structure of Strained Zinc-blende GaN Using Six-Band Based k·p Method

The variations of valence band energy with stress effects in zinc-blende GaN are proposed in this paper. The calculations are based on a six-band strain dependent k·p Hamiltonian, and can be self-consistently solved by Schrödinger-Poisson equation. Accurate physical pictures are given for the quantized valence subband structure under biaxial and uniaxial stress in (001) surface along the [110] direction accounting the quantum confinement effect. The warping of the energy profile results in carrier distribution change. This research will be beneficial for improving the hole mobility and the selective of optimum stress for group-III nitride semiconductor based devices.
A Study on Taekwondo Training System using Hybrid Sensing Technique

We present a Taekwondo training system using a hybrid sensing technique of a body sensor and a visual sensor. Using a body sensor (accelerometer), rotational and inertial motion data are captured which are important for Taekwondo motion detection and evaluation. A visual sensor (camera) captures and records the sequential images of the performance. Motion chunk is proposed to structuralize Taekwondo motions and design HMM (Hidden Markov Model) for motion recognition. Trainees can evaluates their trial motions numerically by computing the distance to the standard motion performed by a trainer. For motion training video, the real-time video images captured by a camera is overlayed with a visualized body sensor data so that users can see how the rotational and inertial motion data flow.
A Novel approach: Design Issues and Challenges in Hierarchical Routing Protocols for Wireless Sensor Networks.

: A Wireless sensor network (WSN) consists of many devices like sensor nodes, a power unit, processing and storage element etc. A normal routing protocols cannot be used in WSNs because of the internal characteristics of WSNs that distinguishes it from other wireless networks. Recent years it has been observed a lot of advancement in wireless communication technology. Implementation of efficient system in a multidisciplinary research such as WSNs is becoming very difficult task.Cluster-based routing provides certain advantages like scalability, increased network lifetime and efficient data aggregation. Routing protocols are classified into four groups: Data centric and flat architecture, Hierarchical, Location based and finally Quality of Service (QoS) based protocols. In this paper we discuss the design issues in hierarchical routing protocols for WSNs by considering its various dimensions and metrics such as Energy consumption, Scalability, Addressing, Robustness, Topology, Mobility, Power Usage, Traffic and QoS. This paper presents a comparative study for different hierarchical routing protocols for WSNs, which are analyzed and compared based on performance parameters, and finally summarizes the problems of routing protocols along with their limitations.
Assessment of Sepsis in the ICU by Linear and Complex Characterization of Cardiovascular Dynamics

Sepsis is one of the pathological conditions with the highest incidence in intensive care units. Sepsis-induced cardiac and autonomic dysfunction are well-known effects, among others, caused by a dysregulated host response to infection. In this context, we investigate the role of complex cardiovascular dynamics quantified through sample entropy indices from the inter-beat interval, systolic and diastolic blood pressure time series as well as the cross-entropy between heartbeat and systolic blood pressure in patients with sepsis in the first hour of intensive care when compared with non-septic subjects. Results show a significant (p<0.05) reduction in the probability of being septic for a unitary increase in entropy for systolic and diastolic time series (odds equal to 0.038 and 0.264, respectively) when adjusting for confounding factors. A significant (p<0.001) odds ratio (0.248) is observed also in cross-entropy, showing a reduced probability of being septic for an increase in heartbeat and systolic pressure asynchrony. The inclusion of our measures of complexity also determines an increase in the predictive ability (+0.03) of a logistic regression model reaching an area under the receiving operating and precision recall curves both equal to 0.95. Clinical relevance The study demonstrates the ability of information theory in catching a reduction of complex cardiovascular dynamics from vital signs commonly recorded in ICU. The considered complexity measures contribute to characterize sepsis development by showing a general loss of the interaction between heartbeat and pressure regulation. The extracted measures also improve the ability to identify sepsis in the first hour of intensive care.
Tragedy T.V.: Rights Fragmentation and the Junk Band Problem

Tragedy of the anti-commons occurs when property rules fail to enable efficient social coordination. In radio spectrum, rights issued to airwave users have traditionally been severely truncated, leaving gains from trade unexploited. The social losses that Ronald Coase (1959) asserted, appealing to basic theories of resource allocation, are now revealed via intense under-utilization of the TV Band.Despite the end of analog TV transmissions in June 2009, vast spectrum continues to be allocated to terrestrial broadcasting. Broadcast video content could, however, inexpensively shift to cable and satellite. Making the TV Band (49 channels spanning 294 MHz) available for new services is worth $120 billion to service providers (at 2008 auction prices) and at least ten times more in consumer welfare.Instead, U.S. regulators treat TV airwaves as a “junk band. ” Analogizing to wi-fi radios accessing frequencies without exclusive licenses, the FCC seeks to permit government-approved devices to transmit in unoccupied TV Band “white spaces. ” No radios have been approved in seven years of rule makings, reflecting regulatory difficulty in weighing economic trade-offs.Yet common interest tragedy, already visible in the long under-utilized TV Band, predictably locks in once white space devices are approved. By pre-empting exclusive spectrum ownership, the opportunity for market reallocation of frequencies is lost. Specifically, fragmented and overlapping use rights cannot support investments to efficiently mitigate broadcast TV pollution, cleaning up the “junk band. ” Were, alternatively, white spaces assigned via exclusive overlay rights, spectrum owners would contract with cable and satellite operators to guarantee broadcast video distribution, releasing valuable airwaves for new services. Gains from reducing airwave pollution would induce cooperation, replacing political gridlock.
Motion Artifact Resilient SCG-based Biometric Authentication Using Machine Learning

On account of privacy preserving issue and health-care monitoring, physiological signal biometric authentication system has gained popularity in recent years. Seismocardiogram (SCG) is now easily accessible owing to the advance of wearable sensor technology. However, SCG biometric has not been widely explored due to the challenging motion artifact removal. In this paper, we design placing the sensors at different body parts under different activities to determine the best sensor location. In addition, we develop SCG noise removal algorithm and utilize machine learning approach to perform biometric authentication tasks. We validate the proposed methods on 20 healthy young adults. The dataset contains acceleration data of sitting, standing, walking, and sitting post-exercise activities with the sensor placed at the wrists, neck, heart and sternum. We demonstrate that vertical and dorsal-ventral SCG near the heart and the sternum produce reliable SCG biometric evidenced by achieving the state-of-the-art performance. Moreover, we present the efficacy of the devised noise removal procedure in the authentication during walking motion.Clinical relevance— A seismocardiography-based biometric authentication system can help serve privacy preserving and reveal cardiovascular functioning information in clinics.
Morphological Taxonomy of Galaxies Using Convolutional Neural Networks

:- There are millions of huge collections of stars, gas, dust and stellar remnants all held together by gravity in our vast universe. These collections, or galaxies, help in deciphering the structure and history of the universe in general. The classification of these galaxies based on morphological parameters is a relevant requirement in understanding their formation and evolution. Manual identification of the categories to which each belongs to can be tire-some, time consuming and error prone. The objective of our work was to automate the process of finding the features that characterize a galaxy using convolutional neural networks, a cardinal concept in the image data space, whilst comparing the accuracy of the classification with and without prior processing of the image dataset. The Galaxy Zoo dataset was used for the same and it was pre-processed by applying median filtering and contrast limited adaptive histogram equalization. The final classification model was a CNN based on the VGG-16 architecture with some modifications. We considered all 37 features as per the decision tree by Willet et. al. and with a multi-regression approach, obtained a model with a validation loss of 0.0102 (mean square error) on processed images as the best performing model. The model was then deployed onto a client-side interface using Flask to predict the features of the galaxies in real-time.
Hydrological responses to large-scale changes in land cover of river watershed: Review

: Despite many studies on the hydrological responses to forest cover changes in micro and mesoscale watersheds, the hydrological responses to forest cover alterations and associated mechanisms through the large spatial scale of the river watershed have not been comprehensively perceived. This paper thus reviews a wide range of available scientific evidence concerning the impacts exerted by the forest removal on precipitation, water yield, stream flow, and flow regimes. It is concluded that there is no statistical correlation between forest cover and precipitation and water yield at the micro and mesoscale. In contrast, there is a relative correlation coefficient ( r = 0.77, p < 0.05) between forest cover and water yield at large scales (>1000 km 2 ). These findings help our understanding of the hydrological response to forest disturbance at large and regional scale and provide a scientific perception to future watershed management in the context of human activities and natural hazards.
Comparison of ACM and CLAMP for Entity Extraction in Clinical Notes

Rapid increase in adoption of electronic health records in health care institutions has motivated the use of entity extraction tools to extract meaningful information from clinical notes with unstructured and narrative style. This paper investigates the performance of two such tools in automatic entity extraction. In specific, this work focuses on automatic medication extraction performance of Amazon Comprehend Medical (ACM) and Clinical Language Annotation, Modeling and Processing (CLAMP) toolkit using 2014 i2b2 NLP challenge dataset and its annotated medical entities. Recall, precision and F-score are used to evaluate the performance of the tools.Clinical Relevance— Majority of data in electronic health records (EHRs) are in the form of free text that features a gold mine of patient’s information. While computerized applications in healthcare institutions as well as clinical research leverage structured data. As a result, information hidden in clinical free texts needs to be extracted and formatted as a structured data. This paper evaluates the performance of ACM and CLAMP in automatic entity extraction. The evaluation results show that CLAMP achieves an F-score of 91%, in comparison to an 87% F-score by ACM.
Robust and efficient EBG-backed wearable antenna for ISM applications

A structurally compact, semiflexible wearable antenna composed of a distinctively miniaturized electromagnetic band gap (EBG) structure is presented in this work. Designed for body-centric applications in the 5.8 GHz band, the design draws heavily from a novel planar geometry realized on Rogers RT/duroid 5880 laminate with a compact physical footprint spanning lateral dimensions of 0.6 λ 0 × 0.06 λ 0 . Incorporating a 2×2 EBG structure at the rear of the proposed design ensures sufficient isolation between the body and the antenna, doing away with the performance degradation associated with high permittivity of the tissue layer. The peculiar antenna geometry allows for reduced backward radiation and low specific absorption rate (SAR). With the inclusion of EBG, the gain of the antenna undergoes a considerable increase to 7.2 dBi with more than 95% reduction in SAR value. In addition, the front-to-back ratio also amplified to 13 dB. A rigorous analysis detailing the structural robustness is reported for varied bend angle configurations of the proposed antenna. To assess the suitability of the proposed design as a body-worn antenna, an experimental investigation is carried out on different parts of the body. Experimental findings are congruent with computationally obtained results, validating the applicability of the novel antenna structure for body-worn applications.
A Laplacian-Gaussian Mixture Model for Surface EMG Signals from Upper Limbs

Existing literature suggests that the probability density function (pdf) of surface Electromyography (sEMG) signals follows either a Gaussian or Laplacian model. In this paper, a Laplacian-Gaussian mixture model is proposed for the EMG signals extracted from the upper limbs. The model is validated using both quantitative and qualitative perspectives. Specifically, for a benchmark dataset, the Kullback–Leibler (KL) divergence is computed between the proposed model and the histogram based empirical probability density function (mpdf). For a sample signal, a goodness of fit plot with R squared value and a visual comparison between the histogram based mpdf and the estimated pdf from the proposed model are presented. Moreover, the Expectation-Maximization (EM) algorithm is derived for the estimation of the parameters of the proposed mixture model. The weight of the Laplacian component is computed for each of the signals from a benchmark dataset. It has been empirically determined that the Laplacian component has a major contribution to the mixture.
A Take on Obfuscation with Ethical Adversaries

Although specific patterns of ‘unfair’ behaviours differ widely between fields (stereotypical embeddings in natural language processing, unequal performances in computer vision, etc.), a simple and general approach consists in ignoring protected attributes during training. However, this is not always straightforward and because of dependencies between features this approach provides few guarantees and may even lead to internal representations that could reconstruct protected attributes’ value. This can significantly affect social groups (Angwin and Larson 2016, Corbett-Davies and Goel 2018, Pierson et al. 2018). In other cases, unfair behaviours stem from insufficient coverage of social groups in the training data, e.g. facial recognition algorithms with ethnicity-dependent performance.
SYSTEM IN ELECTRONIC HEALTH RECORDS USING MACHINE LEARNING

__________________________________________________________________________________________ Abstract These days dependent on accessible clinical examination specialist is utilizing experimentation approach for anticipating infections. To foresee the infection is one of the real difficulties in past years and today too. Among the different maladies, heart disease is normal nowadays due to pushing the issue and remaining burden. On the basis of available symptoms and patients health, there is a great need of some system that predicts the diseases at an early stage. This research paper provides a survey of different data mining techniques which have already used for heart disease prediction and understand how efficiently Electronic Health Record (EHRs) offer clinicians functions that could never be achieved with written records. We are proposing the Disease status identification system by the Machine Learning algorithm. By using this algorithm we are going to predict Heart Disease based on their symptoms.