Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Deep Networks with Residual Blocks and Different Activation Functions: Classification of Skin Diseases

Deep convolutional neural networks have been implemented for image classification tasks and achieved promising results in recent years. Particularly, ResNETs have been used since they can eliminate vanishing gradient problem in very deep networks. However, ResNET architectures with different activation functions, batch sizes, number of images in the testing and training stages can cause different results. Therefore, the effect of residual connections and activation functions image classification is still unclear. Also, in the literature, ResNET based models have been trained and tested with data sets having different characteristics. However, to make meaningful evaluations of the results obtained from different ResNET models, the same data sets should be used. Therefore, in this work, four network models have been implemented to analyze the effect of two activation functions (ReLU and SELU) and residual learning for image classification using the same data sets. To evaluate performances of these models, a real world issue, which is automated skin disease classification from colored digital images, has been handled. Experimental results and comparative analyses indicated that the ResNET with SELU and without residual block yields in the highest validation accuracy (97.01%) for image classification.
Reducing Interanalyst Variability in Photovoltaic Degradation Rate Assessments

The economic return on investment of a commercial photovoltaic system depends greatly on its performance over the long term and, hence, its degradation rate. Many methods have been proposed for assessing system degradation rates from outdoor performance data. However, comparing reported values from one analyst and research group to another requires a common baseline of performance; consistency between methods and analysts can be a challenge. An interlaboratory study was conducted involving different volunteer analysts reporting on the same photovoltaic performance data using different methodologies. Initial variability of the reported degradation rates was so high that analysts could not come to a consensus whether a system degraded or not. More consistent values are received when written guidance is provided to each analyst. Further improvements in analyst variance was accomplished by using the free open-source software RdTools, allowing a reduction in variance between analysts by more than two orders of magnitude over the first round, where multiple analysis methods are allowed. This article highlights many pitfalls in conducting “routine” degradation analysis, and it addresses some of the factors that must be considered when comparing degradation results reported by different analysts or methods.
Fast and Adaptive Boosting Techniques for Variational Based Image Restoration

Variational based problems are an important class of problems and have a space of improvement in image processing. Boosting techniques have been shown capable of improving many image restoration algorithms. This paper considers four fast and adaptive boosting techniques for variational based image restoration. The adaptive boosting frameworks can compute the existing image restoration algorithm iteratively. The primary idea is to get an enhanced result by using the output of the current step as a part of the input for the next step. Our techniques can boost variational based regularization models like total variation (TV) and total generalized variation (TGV). For image restoration, we used an adaptive regularization parameter selection, which produces signals with more details and preserves tiny objects. For efficient numerical optimization, we implement the alternating direction method of multipliers (ADMM) and demonstrate the effectiveness of the proposed techniques with a variety of experimental results. The simulation results show that the proposed boosting techniques achieve a better restoration performance on comparisons with TV and TGV in terms of quality metrics such as signal to noise ratio (SNR) and structure similarity (SSIM).
Combined Use of FCN and Harris Corner Detection for Counting Wheat Ears in Field Conditions

Accurate counting of wheat ears in field conditions is vital to predict yield and for crop breeding. To quickly and accurately obtain the number of wheat ears in a field, we propose herein a method to count wheat ears based on fully convolutional network (FCN) and Harris corner detection. The technical procedure consists essentially of 1) constructing a dataset of wheat-ear images from acquired red-green-blue (RGB) images; 2) training a FCN as the wheat-ear segmentation model by using the constructed image dataset; 3) preparing testing images and inputting them into the segmentation model to get the initial segmentation results; 4) binarizing the initial segmentation by using the Otsu algorithm (to facilitate subsequent processing); and 5) applying Harris corner detection after extracting the wheat-ear skeleton to obtain the number of wheat ears in the images. The segmentation results show that the proposed FCN-based segmentation model segments wheat ears with an average accuracy of 0.984 and at low computational cost. An average of only 0.033 s is required to segment a $256\times 256$ -pixel wheat-ear image. Moreover, the segmentation result is improved by nearly 10% compared with the previous segmentation methods under conditions of wheat-ear occlusion, leaf occlusion, uneven illumination, and soil disturbance. Subsequently, the proposed counting method achieves good results, with an average accuracy of 0.974, a coefficient of determination (R2) of 0.983, and a root mean square error (RMSE) of 14.043. These metrics are all improved by 10% compared with the previous methods. These results show that the proposed method accurately counts wheat ears even under conditions of wheat-ear adhesion. Furthermore, the results provide an important technique for studying wheat phenotyping.
Rate-Energy Outage Analysis of MISO SWIPT With Multiple Energy Harvesting Sensors

We study a multi-input-single-output (MISO) transmission system consisting of a multi-antenna basestation (BS) and a single-antenna user in the presence of multiple single-antenna radio frequency (RF) energy harvesting (EH) sensor nodes, where the user decodes information and multiple EH sensor nodes accumulate energy through the received signal from the BS. The sensor nodes coordinate their transmissions to perform virtual MISO beamforming, which requires sufficient individual and sum transmission power across multiple sensor nodes. For this reason, we consider simultaneously both the individual and sum EH constraints for SWIPT networks. Specifically, under both the individual and sum EH constraints, we propose beam selection of random unitary beamforming to maximize the transmission rate of the MISO system. Then we derive the exact rate-energy outage probability in closed-form for the system with identical average value of harvested energy across all sensor nodes and the exact probability in recursive form for the system with distinct average value of harvested energy at each sensor node. Numerical results confirm that the analyses are exact and the outage performance improves as the number of antennas at the BS increases and/or as the average received power at the user and sensor nodes increases.
Energy Efficient Data Management in Wireless Sensor Networks

In a Wireless Sensor Network (WSN), sensor nodes are small inexpensive sensing and computing devices collaborating to form a network. However, they work with limited power and memory in hard-to-reach locations and extreme weather conditions. In general, a large number of tiny sensor nodes are usually deployed randomly to monitor one or more physical phenomena like- temperature, humidity etc. Due to limited power resources sensing, storage and retrieval of data become critical issues in wireless sensor data management. In this paper we propose a novel data management scheme that facilitates- (i) power efficient sensing, (ii) optimal utilization of storage space and (iii) energy and time efficient query processing in a WSN. Our proposed data sensing and storage schemes are based on sleep-scheduling and collaborative sensing techniques respectively. Next, our query processing scheme involves a Lookup technique that exploits the collaborative sensing which is a result of sleep-scheduling of nodes in a WSN. Our simulation results have proved the validity of our proposal.
Silicon Nitride Deposition: Impact on Lifetime and Light-Induced Degradation at Elevated Temperature in Multicrystalline Silicon

Light and elevated temperature induced degradation (LeTID) in multicrystalline (mc) silicon (Si) is known to be sensitive to the silicon nitride (SiN<inline-formula><tex-math notation="LaTeX">$_{x}$</tex-math></inline-formula>:H) deposition and the firing, but the reason remains unknown. Three plasma-enhanced chemical vapor deposition (PECVD) tools are used to deposit five different layers, causing significant differences in the initial lifetimes before and after firing. The impact of the different depositions can be effectively compared by replacing the SiN<inline-formula><tex-math notation="LaTeX">$_{x}$</tex-math></inline-formula>:H with well-passivating room-temperature iodine ethanol passivation (IE). The IE passivation reveals that the firing of SiN<inline-formula><tex-math notation="LaTeX">$_{x}$</tex-math></inline-formula>:H and subsequent bulk hydrogenation leads to a lifetime increase only in the gettered samples. Although the PECVD temperature load affects the bulk lifetime, it does not cause LeTID without SiN<inline-formula><tex-math notation="LaTeX">$_{x}$</tex-math></inline-formula>:H deposition. LeTID is only detected in samples fired with SiN<inline-formula><tex-math notation="LaTeX">$_{x}$</tex-math></inline-formula>:H, but once the LeTID precursors have been activated, the PECVD layer can be etched and the wafer thinned down without affecting LeTID formation. No link is found between the LeTID defect density and the bulk-hydrogenated lifetime. Instead the LeTID defect density appears to decrease with decreasing PECVD deposition time and temperature.
Extending UTAUT2 to Explore Digital Wallet Adoption in Indonesia

In recent years, digital wallets (e-wallet) has taken public attention as an alternative payment system in Indonesia. However, based on data from the World Bank, only 3% of the Indonesian population aged over 15 years old used digital wallet service in 2017. Therefore, to create a cashless society, efforts are needed to expand the use of digital wallet in the community. This research aims to identify the factors that influence the adoption of the digital wallet in Indonesia. We collected the data from 345 respondents that already use an e-wallet via an online survey. Then, we analyzed the data using partial least square – structural equation modeling (PLS-SEM) based on UTAUT2 model with the addition of perceived risk and trust factor. This research supports that habit has the most substantial factor that influences the behavioral intention to adopt the digital wallet in Indonesia, followed by performance expectancy, trust, and facilitating conditions. However, effort expectancy, social influence, hedonic motivation, and perceived risk in the digital wallet adoption does not significantly affect the behavioral intention to adopt the digital wallet. The digital wallet stakeholder can use the result of this research as a suggestion to make a strategic decision related to digital wallet ecosystem.
Long-Period Gratings and Multimode Interference in Helical Single-Mode Fiber

Many interesting phenomena in twisted fiber have been reported. In this letter, the twisted single-mode fiber (TSMF) was proposed and studied. It was fabricated by CO2 splicer. Experiments and robust cladding modes resonant theoretical model demonstrated it has transmission dips of long-period gratings. Besides, the light in core will scatter into cladding due to disturbance in core. It will cause multimode interference. A tangential direction theoretical model was put forward to test the experiment characteristic, and was in good agreement with experiment results. In addition, some performance of physical parameters, such as temperature and bending loss response of TSMF are also analyzed. The results indicate that TSMF is a good candidate in sensing and the telecommunication fields.
Characterizing AFM Tip Lateral Positioning Variability Through Non-Vector Space Control-Based Nanometrology

Atomic force microscopy (AFM) based nanotechnology has been widely implemented in various fields for decades in light of its overwhelming advantages, such as nanometer spatial resolution, adaptability to liquid ambient, and various nanomechanical/electrical metrological approaches. It is noted that though AFM possesses imaging capability up to nanometer resolution, it is hard to achieve nanometer level positioning precision due to the existing system variability, especially the thermal drift, which distorts AFM images through relatively long capturing time. Since an AFM image is typically utilized as a global reference map to navigate its tip to the desired locations for precise measurement and manipulation, the system variability distorted image will definitely diversify the experimental results. Therefore, it is necessary to characterize the positioning variability for better experimental results evaluation and decision-making. Although various approaches were proposed to evaluate AFM positioning error, to our best knowledge, there is little research about characterizing its positioning variability precisely and systematically. In this study, we present a universal metrological approach to quantitatively measure AFM tip locating variability by developing a featureless spiral local scan strategy together with the non-vector space (NVS) navigation approach. As a demonstration, the proposed nanometrology was conducted on a specific AFM platform to unravel its positioning property.
Study on Failure Process of Silicon-Doped Amorphous Carbon by ReaxFF Molecular Dynamics Simulation for HAMR

The failure process of silicon-doped amorphous carbon (a-C:Si) films for heat-assisted magnetic recording (HAMR) disk is studied by reactive force field molecular dynamics (ReaxFF MD) simulations. Insights on the failure process of a-C:Si film are provided by analyzing system potential energy, amount of consumed oxygen molecules, film structure, number of carbon–oxygen bonds and silicon–oxygen bonds, atomic shear strain, radial distribution function, and density. The a-C:Si film graphitizes initially, and then it begins to combust accompanying by delamination of surface oxide layers with the increase in temperature. The mechanism of atomic oxygen diffuses in the film is proposed. The a-C:Si film shows a good thermal stability below 1500 K. It can act as carbon overcoat of HAMR disk.
Performance Analysis of Underlap Double Gate Oxide Stacked Junctionless MOSFET for Analog and RF Applications

This work illustrates the methodical analysis of underlapping double Gate (U-DG) junctionless (JL) MOSFET architecture with oxide stacked under persuade of high-k spacer layer. Underlap concept is generally utilized towards source/drain region to diminish the short channel effect, which in turn decreases ON-current (ION) because of enhanced channel resistance. To surmount this drawback, high-k spacer layer is assigned. Here, device factors for analog and RF presentations, namely drain current ($\mathrm {I}_{\mathrm {d}\mathrm {s}}$), transconductance (gm), transconductance generation factor ($\mathrm {g}_{\mathrm {m}}/\mathrm {I}_{\mathrm {d}\mathrm {s}}$), intrinsic gain ($\mathrm {g}_{\mathrm {m}}\mathrm {R}_{0}$), intrinsic capacitances ($\mathrm {C}_{\mathrm {g}\mathrm {d}}, \mathrm {C}_{\mathrm {g}\mathrm {s}}$), unity gain cut-off frequency ($\mathrm {f}_{\tau }$), transconductance-frequency product ($\mathrm {g}_{\mathrm {m}}\mathrm {f}_{\tau }$/$\mathrm {I}_{\mathrm {d}\mathrm {s}}$) and gain-bandwidth product (GBWP) are analyzed with ATLAS device simulation software.
Compact Dual-Band Dual-Mode Antenna With Omni-/Unidirectional Radiation Characteristics

A novel dual-band dual-mode antenna that operates at 2.45/5.8 GHz is proposed in this letter. The antenna exhibits linearly polarized omnidirectional radiation in the low band, and circularly polarized broadside radiation in the high band. To improve the 3 dB axial-ratio (AR) bandwidth, both truncated patches and a sequential rotation technique are combined together in the antenna design. The omnidirectional radiation in the low band is achieved by exciting four open-ended slots etched in the ground plane for the first time. The four slots form a magnetic-dipole-like current distribution along the edge of the ground plane, resulting in omnidirectional radiation. The low- and high-band operations are seamlessly integrated into a common design, sharing the same structure. This work provides a novel approach for improving the versatility of a radio frequency front-end subsystem without increasing footprint. The proposed antenna is prototyped and measured, showing good results in terms of impedance/AR bandwidths, isolation, radiation, and polarization.
Sixty Years of Coherent Versus Non-Coherent Tradeoffs and the Road From 5G to Wireless Futures

Sixty years of coherent versus non-coherent tradeoff as well as the twenty years of coherent versus non-coherent tradeoff in Multiple-Input Multiple-Output (MIMO) systems are surveyed. Furthermore, the advantages of adaptivity are discussed. More explicitly, in order to support the diverse communication requirements of different applications in a unified platform, the 5G New Radio (NR) offers unprecendented adaptivity, abeit at the cost of a substantial amount of signalling overhead that consumes both power and the valuable spectral resources. Striking a beneficial coherent versus non-coherent tradeoff is capable of reducing the pilot overheads of channel estimation, whilst relying on low-complexity detectors, especially in high-mobility scenarios. Furthermore, since energy-efficiency is of salient importance both in the operational and future networks, following the powerful Index Modulation (IM) pholosophy, we conceive a holistic adaptive pholosophy striking the most appropriate coherent/non-coherent, single-/multiple-antenna and diversity/multiplexing tradeoffs, where the number of RF chains, the Peak-to-Average Power Ratio (PAPR) of signal transmission and the maximum amount of interference tolerated by signal detection are all taken into account. We demonstrate that this intelligent tripple-fold adaptivity offers significant benefits in next-generation applications of mmWave and Terahertz solutions, in space-air-ground integrated networks, in full-duplex techniques and in other sophisticated channel coding assisted system designs, where powerful machine learning algorithms are expected to make autonomous decisions concerning the best mode of operation with minimal human intervention.
Tunnel Field Effect Transistor for Ultra Low Power Applications: A Review

Tunnel Field Effect Transistor (TFET) has emerged as a promising candidate for applications in low power VLSI/ULSI circuit design. TFETs have shown better performance in terms of short-channel effects and random dopant fluctuation etc as compared to the MOSFET. TFETs are based upon the concept of gated p-i-n diode and band to band tunneling phenomenon. This paper presents a comprehensive overview of TFETs and its performance variation with different parameters. The work also demonstrates the different advancements in TFETs to make it more reliable and cost effective in terms of lower subthreshold swing, higher on-current, lower leakage current, lower DIBL effect and ambipolar current etc. Finally, a comparison between different kinds of advanced TFETs as- doped/ undoped, symmetrical/ asymmetrical and single/double gate TFETs is presented in this work.
The influence of housing on the internal flow of a cross flow fan impeller

A 2D numerical model is used in order to assess the role of vortex wall/stabilizer over eccentric vortex inside of a cross flow fan impeller. The simulation was performed by using FLUENT code with RNG k-ε turbulence model. Three values for the inlet setting angles of the impeller were selected β1 = 150, 250, 350 and three positions for the vortex wall/stabilizer. Therefore, 3 impellers (RI, RII, RIII) were simulated for each three positions of a shaped vortex wall (A, B, C). Best results are reported for the impeller RI (β1 = 150). For this case the eccentric vortex is acting mostly outside the impeller for open positions of the wall/stabilizer A and B. As a result the region of low pressure is extended outside the impeller favoring flow recirculation. The C position of the vortex wall (lowest distance between housing and the impeller) provides the highest value for the average outlet velocity vm even the eccentric vortex axis is more close to internal impeller region. The results obtained for impeller RI shows that it is not necessary that eccentric vortex axis should be positioned outside the impeller for best performances of the fan. Also, increasing the inlet setting angle of the cross fan impeller (β1) creates high asymmetric velocity profile at outlet section of the fan casing and decreases the outlet average velocity.
Investigating Mental Models of Mechanical Engineering Students

Today's innovation processes are interdisciplinary and require communication between stakeholders from different domains. The compatibility of mental models, which determine how individuals think about technical problems, decides the success of this communication. Previous research indicates that mechanical engineering students prefer procedural over structural approaches. However, structured research into the source of this preference is rare. This paper presents a study (n = 67) that investigates the mental models of mechanical engineering students of technical systems. Results indicate that mental models may depend on the presentation of a problem. A questionnaire yielded a preference for a procedural approach, while questions prompting verbal information instead yield a structural preference.
Free-Space-Impedance-Matched Composite Dielectric Metamaterial With High Refractive Index

In this letter, we present an all-dieletric metamaterial (ADM) design to achieve both free-space impedance matching and high refractive index in the X-band. This design is formed by two different-size of dieletric resonator cubes, which are made of strontium titanate, SrTiO3, with high permittivity and low loss. The Mie theory is used as theoretical framework to design high permittivity and high permeability, simultaneously. By scaling the size and lattice constant of the individual units, the first magnetic resonance of one cube (generating high permeability) and the first electric resonance of the other cube (generating high permittivity) can be colocated in order to achieve the free-space impedance matching. The S-parameters and the constitutive parameters are used to demonstrate that the composite cube/cube design has a transmission window with a high refractive index. Experimental measurements are carried out to verify the design concept. All-dieletric metamaterial can be presented as an alternative way to achieve the reflection-less surface, referred to as a Huygens’ surface, and create a high index of refraction at the same time.