Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Entropy Multi-Decision Attribute Reduction Fuzzy Rough Set for Dust Particulate Imagery Characteristic Extraction

High-precision extraction of particulate characteristic modes is essential for dust explosion safety measurements, such as particulate concentration and size distribution. A new solution based on information entropy multi-decision attribute reduction fuzzy rough set is proposed to analyse the particulate morphology characteristics, which effectively avoids the shortcomings of traditional technology (low accuracy, stochasticity, etc.). The proposed approach consists of three stages: membership function modelling, attribute reduction, and maximum information entropy threshold segmentation. The membership coefficient was determined with a multi-segment function by developing the fuzzy degree of the membership model for dust image pixels. The fuzzy dependence of the conditional attribute was determined to extract the fuzzy attribute reduction. Finally, the model of coal dust particulates with information entropy was improved to extract the maximum segmentation threshold, which is significant for classification. The proposed methods were evaluated over a sequence of 30 image sets. The unclassified rate evaluation reached 0.978 for particle sizes <inline-formula> <tex-math notation="LaTeX">$\ge200~\mu \text{m}$ </tex-math></inline-formula>, 0.958 for [75 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>, 200 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>] and 0.950 for particle sizes <inline-formula> <tex-math notation="LaTeX">$< 75~\mu \text{m}$ </tex-math></inline-formula>. The proposed reduction approach offered a performance improvement in terms of more important attribute implementation. The paper demonstrated that the maximum information entropy reduction model can remove the redundant attributes without compromising the precision.
Wideband Asymmetric Coplanar Strip Fed Antennas With Pattern Diversity for mmWave 5G Base Stations

A compact asymmetric coplanar strip (ACS)-fed mmWave 5G antenna with 6.5-7.5 dBi end-fire gain is presented in this paper. The proposed antenna is wideband, operating from 26–32 GHz with fractional bandwidth of 20.7%. The proposed single element antenna has dimensions of $6 \times 10$ mm2 demonstrating small physical and electrical footprint. The antenna achieves 1-dB gain bandwidth of 20.7% which demonstrates pattern integrity over whole operating band. The reported antenna also achieves reasonable gain for the available aperture. In order to achieve pattern diversity, a shared ground compact two-port antenna topology is next presented for beam switching at ±30°. In addition to this, a quasi-stacked beam switching module integrated with low cost 3D-printed scaffolding with wide angular coverage is proposed with adequate technical justification.
Sentiment Analysis With Comparison Enhanced Deep Neural Network

Sentiment analysis is a significant task in Natural Language Processing. It refers to classification based on the emotional tendency in text by extracting text features. The existing results show that models based on RNN and CNN have good performance. In order to improve the performance of text sentiment analysis, we reformulate the classification task as a comparing problem, and propose Comparison Enhanced Bi-LSTM with Multi-Head Attention (CE-B-MHA). In fact, it is efficient to classify by comparison mechanism instead of doing complex calculation. In this model, bidirectional LSTM is used for initial feature extraction, and valuable information is extracted from different dimensions and representation subspaces by Multi-Head Attention. The comparison mechanism aims to score the feature vectors by comparing with the labeled vectors. The experimental results show that CE-B-MHA has better performance than many existing models on three sentiment analysis datasets.
Crosstalk-aware TSV-buffer Insertion in 3D IC

3D integration is one of the promising technologies to alleviate interconnection delay. Implementing 3D IC is to integrate 2D ICs with Through-Silicon Vias (TSVs). For yield consideration, TSVs are bundled together as a TSV block [1]. Regrettably, this placement will result in crosstalk coupling noises in TSV block, which may cause significant timing degradation. Traditionally, buffer sizing is one of the effective methods to solve the problem. However, we have observed that increasing the TSV-buffer size of aggressor TSV will cause serious timing degradation to the victim TSV in 3D than wires in 2D cases. In this paper, we develop a delay model of a victim TSV surrounded by aggressor TSVs with different driving TSVbuffer sizes. Based on the TSV delay model, we propose (1) an ILP (Integer Linear Programming) method, which is able to find the nearoptimal solution, and (2) an efficient crosstalk-aware heuristic method for practical use. Our experimental results show that the proposed heuristic method only uses 2.56% (3.05%) more TSV-buffers compared to the optimal ILP solution and achieves on average 32.88% (42.40%) and 18.21% (23.06%) area reduction of area-overheads compared to the conventional greedy [2] and separator sets [3] methods in our 2-tier (4-tier) benchmark circuits.
Enabling Neuromorphic Computing: BEOL Integration of CMOS RRAM Chip and Programmable Performance

Implementation of the neuromorphic computing requires a hardware network system to mimic the functionality of biological neural systems. The development of digital nonvolatile resistive memory in a large and dense array is maturing and it provides a tremendous commercial opportunity to enable the hardware accelerator development. In this work, we have designed the RRAM device structures and developed the backend-of-line (BEOL) CMOS integration processes to fabricate the memory chips of 64Kb array, and achieved a high fabrication yield $\gt99.79$% with programmable characteristics to meet the requirements of different application algorisms. The chips as the building block of artificial neuromorphic network have low writing energy, fast writing speed, high endurance and retention. Most importantly, we demonstrated the remarkable capabilities chips to facilitate neuromorphic computing.
A Bidirectional Buck-Boost Converter in Cascade with a Dual Active Bridge Converter to Increase the Maximum Input and Output Currents and Extend Zero Voltage Switching Range

Extension of zero voltage switching (ZVS) range of a Dual active bridge (DAB) converter is important especially at light loads. In this paper, the ZVS range of a DAB converter is increased by cascading a bidirectional buck-boost converter with a DAB converter. This proposed structure increases the maximum input and output currents, so output power can be controlled in a wider range. Simulation results confirm the performance of the proposed configuration.
Information Technology of Person’s Identification by Photo Portrait

The paper focuses on information technology of biometric identification based on Gabor and log-Gabor wavelets. During the research the experiments of log-Gabor filter bank coefficients determination were performed. Also, it was analyzed the methods of image feature vector extraction and classification with the use of Gabor and log-Gabor filter. Obtained experimental results were compared, then was found that log-Gabor filters performance combined with standard deviation calculation method and Euclidean distance indicated the highest result, which is 92,5%.
Co-Design of Highly Uniform ReRAM Arrays in 180nm CMOS Technology for Neuromorphic Systems

This paper presents the co-implementation of resistive random access memory inside a 180nm CMOS chip for low-cost, energy-efficient neuromorphic hardware accelerators. Systematic evaluation of different TaOx-based ReRAM stacks was performed to derive the optimal ReRAM stack that shows high spatial and temporal uniformities without compromising CMOS back-end-of-line compatibility. Detailed comparison among six different ReRAM stacks can reduce power consumption by $\sim89$% and increase uniformity by $\sim66$% via proper material selection. The optimized ReRAM cells are directly integrated on standard CMOS foundry chips, enabling low-cost, high-yield integration with high energy efficiency, fast speeds, high uniformity, suitable for neuromorphic computing applications.
Feature Extraction Methods in Quantitative Structure–Activity Relationship Modeling: A Comparative Study

Computational approaches for synthesizing new chemical compounds have resulted in a major explosion of chemical data in the field of drug discovery. The quantitative structure–activity relationship (QSAR) is a widely used classification and regression method used to represent the relationship between a chemical structure and its activities. This research focuses on the effect of dimensionality-reduction techniques on a high-dimensional QSAR dataset. Because of the multi-dimensional nature of QSAR, dimensionality-reduction techniques have become an integral part of its modeling process. Principal component analysis (PCA) is a feature extraction technique with several applications in exploratory data analysis, visualization and dimensionality reduction. However, linear PCA is inadequate to handle the complex structure of QSAR data. In light of the wide array of current feature-extraction techniques, we perform a comparative empirical study to investigate five feature-extraction techniques: PCA, kernel PCA, deep generalized autoencoder (dGAE), Gaussian random projection (GRP), and sparse random projection (SRP). The experiments are performed on a high-dimensional QSAR dataset, which comprises 6394 features. The transformed low-dimensional dataset is inputted into a deep learning classification model to predict a QSAR biological activity. Three approaches are adopted to validate and measure the proposed techniques: (i) comparing the performance of the classification models, (ii) visualizing the relationship (correlation) between features in the low-dimension Euclidean space, and (iii) validating the proposed techniques using an external dataset. To the best of our knowledge, this study is the first to investigate and compare the aforementioned feature-extraction techniques in QSAR modeling context. The results obtained provide invaluable insights regarding the behavior of different techniques with both negative and positive classes. With linear PCA as a baseline, we prove that the investigated techniques substantially outperform the baseline in multiple accuracy measures and demonstrate useful ways of extracting significant features.
Group Delay Compensation By Combining 3-tap FFE With CTLE for 80Gbps-PAM4 Optical Transmitter

Group delay peak-peak value and bandwidth bottleneck from VCSEL are challenges to achieve high speed optical interconnect at 50Gbps bits rates and above. This paper presents a PAM4 VCSEL-based Optical Transmitter that employs 3-tap feedforward equalizer (FFE) and continuous time linear equalizer (CTLE) to overcome these problems. By utilizing one pre-emphasis tap and CTLE, bandwidth of this system is extended to 26GHz. Moreover, peak-peak value of group delay for this system is reduced to 6.7pspp by using one pre-fall tap when frequency is below 26GHz. To adapt to various input signal amplitude, a variable gain amplifier (VGA) is placed in the frontend of transmitter. By using 0.18? m SiGe BiCMOS technology, the operating bits rates are up to 80Gbps with 2.8dBm optical modulation amplitude.
Preliminary Investigation of Across-Body Vibrotactile Pattern for the Design of Affective Furniture

This research is an exploratory work aimed at evaluating the ability of across-body vibration patterns to communicate emotions. We developed an affective haptic chair that allows seated users to feel tactile sensation around the upper and lower back, bottom, and leg area. We tested the system in two studies. The first study used 25 user-generated haptic patterns to represent five basic emotions, and suggested that across-body haptic patterns are effective in conveying emotions. In the second study, we tested four basic directional patterns identified in study 1 and validated the effect of up, down, left, and right movement on users’ emotional states. We observed an improvement in valence value from "up" movement, while the "down" movement was expressed to induce a sense of calmness in users. These findings could be useful in designing future affective furniture.
Genotype-by-Environment Interaction in Grain Sorghum. II. Effects of Temperature and Photoperiod on Ontogeny

(…) Development rate of all hybrids exhibited a curvilinear response to temperature in both phases. Old and new hybrids differed in their temperature responses in GS1 but were similar in GS2. New hybrids had slower rates of development at all temperatures, but the difference was greater at higher temperature (>25 o C). All hybrids had similar short-day photoperiodic response in GS1, with a critical photoperiod 13.2 h. The models were tested on a separate data set covering a similar broad range of environments and performed well
Proportional study of Perturb & Observe and Fuzzy Logic Control MPPT Algorithm for a PV system under different weather conditions

Photovoltaic (PV) system are highly affected by varying of insolation and temperature condition. Since a PV cell characteristic is a non-linear, P-V curve of a PV system shows multiple power peaks under partial shading conditions (PSC). Therefore, it is necessary to track the global maximum power to avoid the PV system operating in local peak power that result in a power loss. This paper presents the proportional study and evaluation of two maximum power point tracking (MPPT) algorithms, namely Perturb & Observe (P& O) and Fuzzy Logic Control (FLC). The MATLAB SIMULINK software is used to validate and prove the performance of the two MPPT techniques.
Design and Implementation of Junction Boxes for Preventing Animal Attacks in Farms

One of the most common obstacles faced in agricultural sector is the damage afflicted by wild animals. A trivial conflict, yet it has been a constant war since time immemorial between humans and the wild animal intruders. Several solutions have come up till date to tackle this problem. Since the world takes huge steps every day in technological innovations, it is crucial that a technological solution is implemented in a wide range so as to maintain for the future. It is also important to bear in mind the state of the natural resources available for human consumption. Hence, the implementation of solutions that are sustainable to the environment is essential. This paper proposes a sustainable technological system as a solution. This paper will explain in detail the proper working of an intelligent system that can be used to prevent crop damage due to wild animal attacks.
Winding Function Model of a 6/7 Variable Flux Reluctance Machine

Variable Flux Reluctance Machine (VFRM) is robust due to the fact that there isn't any windings or Permanent Magnets (PMs) on its rotor structure. Therefore, VFRMs are potential candidates for so many applications including electric vehicles and wind turbines. Consequently, developing a fast and accurate method for its electromagnetic performance analysis is essential. Although Finite Elements Method (FEM) is an accurate method, it is suffering from high simulation time. There are some other methods but they cannot easily apply to all topologies. Winding function is a fast modelling method for analyzing electric machines performance. Therefore, in this paper, Winding function modeling of a VFRM is proposed. In this regard, the concept of VFRMs and winding function modelling procedure is presented. Also, a 6 stator and 7 rotor poles VFRM is modelled by Winding Function Method (WFM) and the results are compared with the experimental results which proves that WFM is an efficient modelling and analysis tool.
Mathematical Simulation of Emission Devices on Arrays of Carbon Nanotubes

With the help of the described approaches to electric field (EF) modelling in the systems with carbon nanotubes (CNTs) arrays, analysis of such arrays parameters influence on the degree of the EF strength amplification on CNTs tips have been performed. Such approaches enable EF calculation at the applied computational grid step proportional to the CNTs height and for only one CNT from the array. Influence of correlation between the CNTs height, radius and distance between separate rods on the character of the EF distributions has been evaluated.
Modulated Predictive Current Control of PMSG-Based Wind Energy Systems

This paper presents an efficient modulated model predictive current control for direct driven wind energy system composed of surface-mounted permanent magnet synchronous generator and back-to-back connected voltage source converter. The proposed control method fulfils the generator-side control requirements such as maximum power point tracking, and grid-side control objectives such as DC-link voltage control and power factor correction. These objectives are achieved through the regulation of generator and grid currents with fast transient response, smooth steady-state and fixed switching frequency operation simultaneously. The proposed controller predicts the future behavior of generator and grid currents using quasi-exact discrete-time models and eight voltage vectors, and then evaluates them by two independent cost functions. Finally, the switching sequence is designed by the space vector modulation using three stationary voltage vectors corresponding to the optimal cost function. The performance of the proposed method is validated through the MATLAB simulations using a 750-kW wind energy system at different wind speeds and grid reactive powers.
Boosting the Performance of SSDs via Fully Exploiting the Plane Level Parallelism

Solid state drives (SSDs) are constructed with multiple level parallel organization, including channels, chips, dies, and planes. Among these parallel levels, plane level parallelism, which is the last level parallelism of SSDs, has the most strict restrictions. Only the same type of operations that access the same address in different planes can be processed in parallel. In order to maximize the access performance, several previous works have been proposed to exploit the plane level parallelism for host accesses and internal operations of SSDs. However, our preliminary studies show that the plane level parallelism is far from well utilized and should be further improved. The reason is that the strict restrictions of plane level parallelism are hard to be satisfied. In this article, a from plane to die parallel optimization framework is proposed to exploit the plane level parallelism through smartly satisfying the strict restrictions all the time. In order to achieve the objective, there are at least two challenges. First, due to that host access patterns are always complex, receiving multiple same-type requests to different planes at the same time is uncommon. Second, there are many internal activities, such as garbage collection (GC), which may destroy the restrictions. In order to solve above challenges, two schemes are proposed in the SSD controller: First, a die level write construction scheme is designed to make sure there are always $N$N pages of data written by each write operation. Second, in a further step, a die level GC scheme is proposed to activate GC in the unit of all planes in the same die. Combing the die level write and die level GC, write accesses from both host write operations and GC induced valid page movements can be processed in parallel at all time. To further improve the performance of SSDs, host write operations blocked by GCs are suggested to be processed in parallel with GC induced valid page movements, bringing lesser waiting time cost of host write operations. As a result, the GC cost and average write latency can be significantly reduced. Experiment results show that the proposed framework is able to significantly improve the write performance without read performance impact.
Species‐specific responses of a root‐ and shoot‐feeding insect to arbuscular mycorrhizal colonization of its host plant

Summary • The responses of root-feeding black vine weevil (Otiorhynchus sulcatus) larvae and leaf-feeding adults to colonization of strawberry (Fragaria x ananassa) plants by one or two species of arbuscular mycorrhizal fungi are reported here. • Glomus mosseae and Glomus fasciculatum were isolated from a commercial field and used to colonize strawberry plants, singly and in combination. Vine weevil larvae were reared on roots of colonized and uncolonized plants. When the larvae were mature, leaves from all plants, with and without larvae, were fed to adult weevils. • Colonization by either fungus reduced larval survival and biomass. However, colonization by both fungi had no effect on the larvae. These effects were manifested in changes in plant performance; weevil feeding decreased plant foliar and root biomass as well as runner production, but only when mycorrhizas were absent or inoculated together. Mycorrhizas also mitigated the effects of larval feeding on adult weevils. • The response of root-feeding insects to arbuscular mycorrhizal colonization depends on which fungi are present in the root system. Furthermore, arbuscular mycorrhizal fungi might play a critical role in mitigating interactions between phytophagous insects.
Human impacts on hydrological health and the provision of ecosystemservices: a case study of the eMthonjeni–Fairview Spring Wetland, Grahamstown, South Africa

Wetland hydrological health and the provision of indirect ecosystem services in the eMthonjeni–Fairview Spring Wetland, Grahamstown, South Africa, were assessed in 2008, using the newly developed wetland assessment tools WET-Health and WET-EcoServices. Variation in health and ecosystem services were assessed over time, based on aerial photograph interpretation and the use of the score sheets in these assessment tools. Hydrological health and indirect ecosystem services of the wetland have been altered since 1949, due to human activities both in the catchment and the wetland. The most significant human intervention on the wetland's hydrological health was the result of road construction and invasion by alien plants. Water use by local residents had an unmeasurable effect on hydrological health. Wetland health is related to the provision of wetland ecosystem services, and cumulative impacts in the catchment and wetland have reduced the provision of many indirect wetland ecosystem services.
Discontinuous Pulse Width Modulation Techniques for Modular Multilevel Converter

Modular Multilevel Converter (MMC) has already been strongly found its application in high voltage applications, and is lately been explored in medium voltage applications. The modulation techniques play an important role in the performance of the MMC in terms of the output fundamental component, distortions and the switching losses. So, this paper is focused on analyzing converter performance in terms of fundamental component and total harmonic distortion (T.H.D.). with the application of various discontinuous pulse width modulation (DPWM) techniques to the MMC. Comprehensive simulations have been carried out on 5-level MMC using MATLAB/Simulink software.