Miracle-dz/UniFAR-FTUs huggingface dataset:
Implications of SBS Assisted Slow-Light in One-rod Core Chalcogenide MOF

We elucidate attributes of the slow-light facilitated by stimulated Brillouin scattering (SBS) in chalcogenide (As2Se3) glass based one-rod core microstructured optical fiber (MOF). Our theoretical results comprise the assessment of Brillouin gain spectrum, Brillouin gain coefficient and Brillouin frequency shift by taking into account of acoustic mode. The time-delay up to 137.1ns can be accomplished from 1m length of fiber with pump power of 100mW. Our theoretical results nominate that slowlight can be adapted by tailoring the structural parameters of an MOF, and thereby tunable slow-light features can be acquired.
Single Ended Schmitt Trigger based 13T Static Random Access Memory using FinFETs

Advancement in CMOS technology has made the Static Random Access Memory (SRAM) design to be very demanding. The designers face several challenges in increasing the performance by improving the read stability, write ability and leakage power. The inverter characteristic degrades the performance with low supply voltage. The proposed Memory cell uses Schmitt-trigger based inverters to develop SRAM that increases stability and decreases the leakage power. For any dual-bit scheme based SRAM, an amount of power is wasted in form of charging or discharging the bit-lines. The proposed design has 70.02% and 14.17% increased read stability and write ability and it also dissipates 44.45% less leakage power when compared to the first Schmitt trigger based SRAM at 1 V of supply voltage.
A Hybrid Model Integrating Three-Terminal Switch with PNGV Battery Models for LiFePO4 Battery Chargers

This study A LiFePO4 battery pack (LBP) rapid charger was developed and implemented in this study. Using the partnership for a new generation of vehicles (PNGV) battery and three-terminal switch models, this study can yield a small-signal system matrix from dynamic equations to derive transfer functions and further analyze frequency responses for the charge voltage and current loops. In order to stratify practical applications, the proposed equivalent model considered the wire resistance-inductance of the power cable. Moreover, the design features for implementing the constant-voltage and constant-current charges are presented, and the current overshoot during the start-up phase can be depressed using a novel proportional shifting proportional-integral control.
Performance Investigation for Tracking GMPP of Photovoltaic System Under Partial Shading Condition Using Coyote Algorithm

this paper presents a methodology utilizing Coyote Optimization Algorithm (COA) for Global Maximum Power Point Tracking (GMPPT) considering the impact of partial shading on a PV system. COA is utilized to clarify GMPP by comparing all the existing peaks on the PV curve. COA is also employed to control the boost converter. Different shading patterns are applied to a photovoltaic system. Simulations of this process are established utilizing MATLAB software. The suggested algorithm is compared with enhanced Grey Wolf Optimization (E-GWO), Dragonfly Algorithm (DA), Ant Lion Optimization (ALO), and Particle Swarm Optimization (PSO). According to the results, the suggested COA improves the tracking speed and accuracy of MPPT during partial shading conditions. Also, the suggested methodology is providing high efficiency for solar PV systems in any irradiation conditions.
Maximized Spectral Efficiency and QoS Based Power Allocation Schemes for Co-operative UWB-WBAN

In this paper, accurate health care with a long life time is noted to be one of the salient specification of wireless body area network(WBAN). In improving these factors power allocation plays a prominent role.Thus a co-operative WBAN system with AF relaying is considered and the power to these relays is optimally allocated. This formulates the first objective where the spectral efficiency is maximized in terms of effective signal to noise ratio(SNR) under the restriction of the total power being constant. Further, allocating equal power to the relay nodes at all the values of SNR is identified to be inappropriate and this formulates the second proposition where the total power is minimized by allocating the relay power in accordance with the effective SNR value of the system. The performance of the above two proposed objectives are compared with the equal power allocation to all the nodes and is measured in terms of the bit error rate(BER) in order to measure preciseness in the transmission.
Preliminary assessment for the development of CADe system for brain tumor in MRI images utilizing transfer learning in Xception model

Brain tumor is one of the most detrimental diseases. Magnetic resonance imaging (MRI) has been used for the diagnosis of the brain tumor; however, manual tumor diagnosis in MRIs is a time-consuming process, necessitating a development of automatic brain tumor diagnosis system. This study applied a novel architecture, named Xception, which enabled both high performance and reduced size and computational cost of convolutional neural networks (CNNs) using depthwise separable convolution to develop highperformance computer aided diagnosis (CADe) system for brain tumor detection from MRI. Preliminary assessment for the Xception model utilizing transfer learning demonstrated good performance with high accuracy and prediction probability. Interestingly prediction probabilities were different when different layers were relearned. The prediction probability values were highest in both normal and tumor cases when the 109th layer and after (ie, the exit flow) were relearned, indicating the importance of re-learning for the Exit flow. The study results suggest that a high-performance CADe system for brain tumor in MRIs could be developed with relatively cheap small-scale learning utilizing transfer learning in the Xception model.
Die neurologische Frührehabilitation Phase B als neuer Subsektor der akutstationären Behandlung

Zusammenfassung In Deutschland ist die neurologische Frührehabilitation in spezialisierten Einrichtungen für die intensivmedizinische Weiterbehandlung von Patienten mit neurologischen Grunderkrankungen und Komplikationen seit Jahren etabliert. Mit Einführung des Fallpauschalensystems ist sie zu einem integralen Bestandteil der akutstationären Behandlung geworden. Ihr Ausbau variiert noch zwischen den Bundesländern. Der Artikel beschreibt regulatorische Hintergründe, das Leistungsgeschehen und klinische Problemkonstellationen der neurologischen Frührehabilitation.
An advanced object classification strategy using YOLO through camera and LiDAR sensor fusion

In this paper, we propose weighted-mean YOLO to improve real-time performance of object detection by fusing information of RGB camera and LIDAR. RGB camera is vulnerable to external environments and therefore strongly affected by illumination. Conversely, LIDAR is robust to external environments, but has low resolution. Since each sensor can complement their disadvantages, we propose a method to improve the performance of object detection through sensor fusion. We design the system using weighted-mean to construct a robust system and compared with other algorithms, it shows performance improvement of missed-detection.
A 14-18GHz 6bit passive phase shifter in 0.13µm SiGe BiCMOS

A 6-bit digital switch-type passive phase shifter (PS) with low gain-variation is presented for satellite communication and Ku-band phased array radar. Switch-type high-pass/low-pass and bridged T-type topology are used to implement the 90°/180° and 5.625°/11.25°/22.5°/45° phase shifting cell, respectively. The PS is fabricated in 0. 13µm BiCMOS (IBM 8HP) process. Measured results show that the PS achieves 4.2°-6° RMS phase error, and 0.3-0.6dB RMS gain error at 14–18 GHz. The total chip size is 2.7 x 1.1 mm2 with 0 mW DC power consumption.
Low Complexity Expectation Propagation Detection for SCMA Using Approximate Computing

Sparse code multiple access (SCMA) is one of the promising non-orthogonal multiple access (NOMA) techniques for the future wireless communication systems, which can provide more connections and higher spectral efficiency than orthogonal multiple access (OMA). In this paper, we propose a novel expectation propagation algorithm based on approximate computing to achieve low complexity and high performance SCMA detection, which is referred as approximate expectation propagation algorithm (AEPA). Three approximate approaches are provided for variable node update, function node update and log likelihood ratio calculation to reduce the algorithm complexity. The parameter optimization methods are also provided to get the trade-off between the detection performance and the algorithm complexity. Simulation and evaluation results show that AEPA can obtain more than 32% complexity reduction with only 0.1dB performance loss when the codebook size is 4 compared with the traditional expectation propagation algorithm (EPA), and the complexity reduction gain will become more significant when the codebook size is larger.
High Resolution Analysis of Targets Based on Plasma Cylinder

Motivated by classic laws of refraction which has been realized in optical systems, a scattered microwave modulated by plasma cylinder is proposed to obtain focused high-resolution distances of targets. Such a radar coincidence signal processing method resolves targets based on nonlinear microwave refracted by plasma cylinders which is quite different from conventional radar resolving techniques where target distance depending on 3 dB bandwidth and Doppler analysis. By constructing the mathematic model, the amplitude and phase conditions of transmitting microwaves are analyzed for achieving high-resolution distance of targets. Furthermore, the resolution experiments are conducted in chamber and distance of 12.6 cm of two pyramidal horn antennas are resolved.
SERVPERF Analysis of Retail Banking Service Performance: A South African Study

This paper investigates retail banking service quality using a service performance measurement model. SERVPERF model measure service quality based on customers' perceptions using five dimensions. The findings based on 520 respondents show that the quality of service delivered by retail banks in South Africa needs to improve. Although the differences in SERVPERF mean scores were insignificant, however the mean scores based on banks were significant. This means banks offer different levels of service quality. Hence, bank need to improve on service quality across all demographic groups for customer satisfaction and retention.
ECG Analysis and Automatic Detection of R-peak in MATLAB

Cardiovascular disease (CVD) is one of the significant reasons of death around the world, so a proper tool is required to monitor the heart conditioning. ECG (Electrocardiogram) is a noninvasive tool to measure the heart condition. This paper presents automatic detection of R-peaks in ECG by using Notch filter, a median filter with the Pan-Tompkins algorithm. The ECG signal waveform constitutes P, QRS and T wave complexes, which contains relevant information about heart rate. Naturally, the ECG signal gets contaminated by different noises, especially power line interferences and motion artifacts which must be eradicated, otherwise, it will lead to misdiagnosis. The effectiveness of this proposed module is assessed by applying recorded ECG signal samples from the MIT- BIH Arrhythmia database to the designed algorithm.
A Dynamically High-Impedance Charge-Pump-Based LDO With Digital-LDO-Like Properties Achieving a Sub-4-fs FoM

This article presents an event-driven charge-pump-based low-dropout (LDO) regulator with an ac-coupled high-impedance (ACHZ) feedback loop. By using the ACHZ loop and continuous-time dead-zone detection, the proposed LDO responds in less than a clock cycle during load transients, achieving the response and settling times of 6.9 and 65 ns, respectively, all at a 4.9-<inline-formula> <tex-math notation="LaTeX">$\mu \text{A}$ </tex-math></inline-formula> quiescent current for a sub-4-fs FoM. The output ripple is measured to have a stable amplitude and is <15 mV over the LDO’s 105000<inline-formula> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> stable load range (1 <inline-formula> <tex-math notation="LaTeX">$\mu \text{A}$ </tex-math></inline-formula>–105 mA). In addition to all these features, the proposed LDO also retains the advantages of normal digital LDOs: process portability and the ability to operate at a low supply voltage.
QoS-Based Performance Analysis of mmWave UAV-Assisted 5G Hybrid Heterogeneous Network

Unmanned aerial vehicles (UAVs) provide us with the ability for rapid, on demand, and infrastructure-less deployment. This capability can be exploited to meet the rising demands of future fifth generation (5G) and Internet of things (IoT) networks. In this study, we consider a downlink scenario in a multi-tier heterogeneous network (HetNet), with sub-6GHz and millimeter wave (mmWave) UAVs coexisting as aerial base stations (ABSs), to meet the network quality-of- service (QoS) requirements. The considered QoS metrics are network coverage and data rates. The network area has no pre-existing communication infrastructure. We study the impact of various network configurations, by varying ratio of mmWave UAVs to total UAVs in the HetNet, number of users, and bias factor for mmWave tier. Our results validate that sub-6GHz and mmWave UAVs can be deployed together to complement each other in a multi-tier HetNet where the sub-6GHz tier will enhance the coverage and the mmWave tier will improve the data rates. Through extensive simulations, we propose and implement a methodology to configure the HetNet for an efficient coverage-rate trade off, while meeting the desired QoS metrics at the same time.
Success Prioritized Binary Exponential Backoff Algorithm for Non-Persistent CSMA

We present a success prioritized binary exponential backoff algorithm of non-persistent carrier-sense multiple access (NP-CSMA) for vast-area large-scale data gathering with power-limited wireless sensors in order to simultaneously gain the transmission and energy efficiencies of the wireless communication devices in this paper. The proposed medium access control (MAC) mechanism does not require any additional physical-layer functions such as multiple antennas, interference canceller, etc. It has high flexibility and scalability without any complex configuration in an autonomous and distributed manner. In this paper, we provide a performance analysis model to estimate the throughput and consumed energy for the proposed backoff algorithm. We show the validity of the performance analysis model by comparing the analysis results with the simulation results for the number of active nodes more than 500 of interest to us.
Music Genre Classification Based on Chroma Features and Deep Learning

Music genre classification is an important branch of content-based music signal analysis. It is a challenging task in the field of music information retrieval (MIR). At present, the method based on deep learning has achieved good results. This paper constructs a neural network framework for music genre classification based on chroma feature. The chroma feature can represent the time domain and the frequency domain of music character and consider the existence of harmony. Besides, it is independent of the timbre, volume, absolute pitch, which are completely irrelevant to the genre classification. It is relatively robust to the background noise and can represent the primary information such as monophonic and polyphonic music distribution. In this paper, we estimate the type of music audio based on chroma feature combined with deep learning network. We input this feature into VGG16 network for training, and improve the last three layers. In the experiment, the classifier is trained by GTZAN dataset. The experimental results show that the framework can obtain higher classification accuracy and better performance.
An Effective Routing with Delay Minimization for Multi-Hop Wireless Mesh Network

As wireless communication develops rapidly, next- generation networks have higher demand for short delay. Routing is an important part of network configuration, and can influence the network performance including delay significantly. Thus designing an effective routing is essential. To achieve the global best network performance, the problem of routing can be modeled as a mathematical optimization problem. An effective routing with the objective of delay minimization for multi-hop wireless mesh network (RODM) is proposed in this paper. Delay is derived according to interference, bandwidth and probability of transmission failure. As the link between two neighboring nodes is bidirectional, RODM considers the asymmetrical transmission failure probabilities of two-direction links between two neighbor nodes. The relationship between delay and the number of interfering nodes is then built. To solve this optimization problem, an improved genetic algorithm is proposed to balance load. The dynamic network performance produced by different chosen routes is also considered. Simulation results show that RODM can obtain better network performance.
AMMONIA EMISSIONS FROM ANIMAL FEEDING OPERATIONS

An accepted definition of antibiotic resistance as presented in 1998 by the Institute of Medicine is “a property of bacteria that confers the capacity to inactivate or exclude antibiotics, or a mechanism that blocks the inhibitory or killing effects of antibiotics, leading to survival despite exposure to antimicrobials (Jjemba and Robertson, 2002). The occurrence of microbial pathogens demonstrating “resistance” to adverse stressors threatening their very survival is not a new (Phillips et al., 2004; WHO, 2001). Bacteria have developed mechanisms for protection in a wide range of environments over time, some of which are currently better understood due to advances in scientific methods and analytical techniques. The development of antibiotics for human and animal use dates back many years; perhaps most notable was Alexander Flemming’s creation of penicillin in 1928 (GIH, 2000). Many infectious diseases that once caused increasing mortality and morbidity rates among humans and animal populations have been effectively managed as a result of having antibiotics and pharmaceuticals available in health care management. Despite these positive outcomes, both the widespread usage and lack of prudent use of antibiotics have caused global concerns about increasing incidences of antibiotic resistance properties and strains of resistant organisms. Concerns have also increased with the recognition of greater interconnectedness between humans, animals and the environment throughout the global community. Further complicating this issue are the economic interests associated with industrial progress; hazards considered low-level and long-term seldom gain the same attention as that of crisis scenarios; and incremental knowledge about public health concerns often raises troubling questions about risk and response (GIH, 2000).
IoT Based Smart Embedded System for Environmental Pollution Monitoring

Continuous monitoring of pollution is required especially in agricultural field for the better cultivation. Proposed pollution monitoring device senses the pollution levels in the surrounding environment by using suitable sensors. Quality of the sources like soil, water, air can be identify and thereby know the polluted level. By Internet of Things (IoT), data is uploaded to server. User can monitor real-time data of pollution level through this. As farmers are following smart farming, these data can be used for better cultivation.
Slice-Aware Capacity Expansion Strategies in Multi-Tenant Networks

5G introduces a broad range of new applications with diverse and demanding performance targets that require substantial investments on the radio access infrastructure. The network slicing model allows to share resources and to distribute responsibilities for network capacity expansion to infrastructure providers and for identifying resource needs to slice tenants specialized in different application domains. In this paper, we focus on the problem of taking capacity expansion decisions considering the traffic needs and performance requirements of network slices instantiated on the access infrastructure. We build on a techno-economic model that allows to describe the trade of resources between infrastructure provider and tenants. The model is based on a resource market that generates revenues for matching infrastructure recurrent costs, but also extra revenues for capacity expansion and technology upgrade. Being the pricing scheme based on resource scarcity in different geographical regions, we propose to guide capacity expansion decisions through an automatic algorithm based on utility functions and available budget generated by the market. Results show the effectiveness of the approach proposed.
Power Flow Control and Seamless transfer of Single-Phase Grid Interactive Inverter Between Off-grid and Utility-Connected Systems

A strategy for control of active and reactive power flow for a single-phase grid-interactive inverter is presented. For utility-connected configuration, the power flow is controlled by employing hysteresis current control whereas hysteresis voltage control is implemented for off-grid configuration. Seamless transition between off-grid and utility-connected operations is achieved by switching between voltage and current control algorithms accordingly. The control algorithms are simulated in SIMULINK/MATLAB environment and the results obtained are presented and discussed.
Experimental Evaluation of the Relationship between Filter Inductor Impedances and Dimensional Resonances of MnZn Ferrites

This paper explores the relationship between filter inductor impedance and dimensional resonance in magnetic cores. Experimental results were obtained showing multiple factors behind the resonances that appear in the frequency characteristics of inductor impedances: the inherent characteristics of a magnetic material, the self-inductance of an inductor and stray capacitance in its winding, and the winding acting as a distributed constant line. Next, based on the measurement results, the dimensional dependencies of the complex permeabilities (dimensional resonance) and the influence of dimensional resonance on inductor impedance are discussed in detail. Finally, this paper shows that the effect of dimensional resonance on complex permeability can be mitigated and filter inductor impedance can be increased in the high frequency range by a core lamination. These results are verified by the experiments described in this paper.
Image Segmentation using FCM-Darwinian Particle Swarm Optimization

Segmentation of biomedical images is an essential requirement in image processing for assessment of different medical images i.e. microscopic, MRI and US. It can be a crucial step for decision support or can get the second opinion for medical expert for atypical cases. There are numerous segmentation methods available for different kind of images. An image segmentation method based on hybrid approach using Darwinian particle swarm optimizer and fuzzy C-means is implemented in this work for various medical and multimedia images. In the present work Darwinian particle swarm optimizer tries to solve the problems regarding the segmentation. The proposed method firstly initializes each of the particles present in the swarm with membership value of each pixel belonging to particular centroids with respect to fuzzy C-means and then optimizes the centroids values using Darwinian particle swarm optimizer. An efficient method for segmenting different areas and edges of various images is implemented in this work. For validating the output of proposed algorithm, it is compared with other segmentation techniques i.e FCM and FCM_PSO. Segmentation is evaluated on ground truth using various indexes. Finally, it is observed that the proposed technique turns out to be more consistent on segmenting the different medical and multimedia images.