Miracle-dz/UniFAR-FTUs huggingface dataset:
MSP-MFCC: Energy-Efficient MFCC Feature Extraction Method With Mixed-Signal Processing Architecture for Wearable Speech Recognition Applications

Feature extraction is an essential part of automatic speech recognition (ASR) to compress raw speech data and enhance features, where conventional implementation methods based on the digital domain have encountered energy consumption and processing speed bottlenecks. Thus, we propose a Mixed-Signal Processing (MSP) architecture to efficiently extract Mel-Frequency Cepstrum Coefficients (MFCC) features. We design MSP-MFCC to pre-process speech signals in the analog domain, which significantly reduces the cost of the analog-to-digital converter (ADC), as well as the computational complexity of the digital back-end. Moreover, MSP-MFCC eliminates the time-consuming Fourier transform in the conventional digital realization by improving processing flow. We fabricated the analog part based on 180nm CMOS mixed-signal technology, then measured the chip. The measured results show the energy consumption of MSP-MFCC is <inline-formula> <tex-math notation="LaTeX">$0.72~\mu \text{J}$ </tex-math></inline-formula>/frame, and the processing speed is up to <inline-formula> <tex-math notation="LaTeX">$45.79~\mu \text{s}$ </tex-math></inline-formula>/frame. MSP-MFCC achieves 95% energy saving and about <inline-formula> <tex-math notation="LaTeX">$6.4\times $ </tex-math></inline-formula> speedup than state of the art. Further, by using the features extracted by MSP-MFCC, speech recognition simulation reaches the accuracy of 98.2%, which also keeps the leading performance to its current counterparts. The proposed MFCC extractor is competitive for integration in the ultra-low-power always-on wearable speech recognition applications.
Unsupervised Anomaly Detection and Localization Based on Deep Spatiotemporal Translation Network

Anomaly detection is of great significance for intelligent surveillance videos. Current works typically struggle with object detection and localization problems due to crowded and complex scenes. Hence, we propose a Deep Spatiotemporal Translation Network (DSTN), novel unsupervised anomaly detection and localization method based on Generative Adversarial Network (GAN) and Edge Wrapping ( $EW$ ). In training, we use only the frames of normal events in order to generate their corresponding dense optical flow as temporal features. During testing, since all the video sequences are input into the system, unknown events are considered as anomalous events due to the fact that the model knows only the normal patterns. To benefit from the information provided by both appearance and motion features, we introduce (i) a novel fusion of background removal and real optical flow frames with (ii) a concatenation of the original and background removal frames. We improve the performance of anomaly localization in the pixel-level evaluation by proposing (iii) the Edge Wrapping to reduce the noise and suppress non-related edges of abnormal objects. Our DSTN has been tested on publicly available anomaly datasets, including UCSD pedestrian, UMN, and CUHK Avenue. The results show that it outperforms other state-of-the-art algorithms with respect to the frame-level evaluation, the pixel-level evaluation, and the time complexity for abnormal object detection and localization tasks.
Design and Analysis of a VCO for Implementing an Analog to Digital Converter Based on PLL in 0.25-um CMOS Technology

This paper presents a research of voltage-controlled generators (VCO) for the implementation of an analog to digital converter based on a PLL with a proportional-integrating filter.This research was carried out based on the obtained parameters of the three circuit implementations of VCO in 0.25 um CMOS technology. These implementations include John Maneatis’ generator, a generator using differential delay cells and a relaxation generator based on the 555-timer circuit. The input voltage control range, output frequency range and linearity of the control range were the key parameters to determine the schematic implementation of the VCO to create an analog to digital converter based on the PLL. These parameters affect the transition time of the PLL in the balanced state and the bandwidth of the converter.
Recent progress of Wireless Power Transfer via Sub-THz wave

Research on wireless power transmission (WPT) by a rectenna using Sub-THz (herein 100GHz~700GHz) waves is gaining attention. Increasing the frequency, make it possible to improve the beam directivity and to miniaturize rectenna. Therefore, it becomes suitable for long distance and high power WPT. Also, it is expected that energy harvesters at high frequencies will be developed for use with 5 G (28 GHz) and beyond 5G (110 GHz). We succeeded in the world's first sub-terahertz WPT using a gyrotron as a high-power oscillation source. At 303 GHz, a microstrip patch antenna was used for rectenna and record RF-DC conversion efficiency of 2.17 % and rectenna power density (DC output power per unit area) of 3.43 kW/m2. At 265 GHz, a coplanar slot antenna was used for rectenna and record a RF-DC conversion efficiency of 0.07 % and a rectenna power density of 0.09 kW/m2. We aim to develope GaN Schottky Barrier Diode (GaN SBD) for high-efficiency WPT in the sub-terahertz band.
Statistical Analysis of Rain at Millimeter Waves in Tropical Area

The high frequencies of millimeter wave (mm-wave) bands have been recognized for the fifth generation (5G) and beyond wireless communication networks. However, the radio propagation channel at high frequencies can be largely influenced by rain attenuation, especially in tropical regions with high rainfall intensity. In this paper, we present the results of rainfall intensity and rain attenuation in tropical regions based on one-year measurement campaign. The measurements were conducted from September 2018 until September 2019 at 21.8 GHz (K-band) and 73.5 GHz (E-band) in Malaysia. The rainfall intensity was collected using three rain gauges installed along a 1.8 km link. The rain attenuation is computed from the difference between the measured minimum received signal level (RSL) during clear sky and rain conditions. The measured rain rate and rain attenuation distributions are then analysed and benchmarked with several previous measurements and well-known prediction models such as the ITU-R P. 530-17. The rainfall rate results showed that the best agreement between the measured rainfall rate in Malaysia and the ITU-R PN.837-1 prediction value for Zone P is up to 0.01% of time (99.99% of time agrees well and only disagrees for 0.01% of time). For the E-band, the maximum measured rain attenuation exceeding 0.03% of the year is around 40.1 and 20 dB for 1.8 and 0.3 km links, respectively, at the maximum rain rate of 108 mm/h. For the K-band, the maximum rain attenuation exceeding 0.01% of the year is around 31 dB for the 1.8 km link. Finally, the rain rates exceeding 108 and 180 mm/h at 73.5 and 21.8 GHz, respectively, along the 1.8 km path caused an outage on our measurement setup. The rain rate of 193 mm/h and above caused an outage for the 0.3 km E-band link. The experimental data as well as the presented data analysis can be utilized for efficient planning and deployments of mm-wave wireless communication systems in tropical regions.
On-Chip All-Optical Tunable Filter With High Tuning Efficiency

We propose and realize a bandwidth and wavelength-tunable all-optical filter with high tuning efficiency based on double opto-mechanical microring resonators (MRRs) assisted Mach-Zehnder interferometer (MZI) structure, which is beneficial to achieve high extinction ratio and shape factor. As the optical field gradient is largely enhanced in the free-hanging MRRs, the opto-mechanical effect could be excited by low power consumption. By injecting the corresponding low resonance powers, the drop transmission of each MRR could be flexibly tuned based on the opto-mechanical effect. Consequently, the synthetic transmission of the microring-assisted MZI could be efficiently manipulated. The results show that by injecting pump powers of 0.40 mW and 1.84 mW, the bandwidth and wavelength of the all-optical filter could be tuned from 0.17 nm to 0.30 nm, and from 1550.09 nm to 1550.60 nm respectively with maintaining a high extinction ratio of 38 dB and a small passband ripple of 1 dB. Especially, the tuning efficiencies of bandwidth and wavelength could realize up to 0.325 nm/mW and 0.277 nm/mW, respectively. The proposed optical filter has dominant advantages of high tuning efficiencies and extinction ratios, small passband ripple and compact footprint, which has significant applications in on-chip all-optical systems.
Classification of Weeds and Crops at the Pixel-Level Using Convolutional Neural Networks and Data Augmentation

The Pixel-Level Classification of crops and weeds is an open problem in computer vision. The use of agrochemicals is necessary for effective weed control, but one of the great challenges of precision agriculture is to reduce their use while maintaining high crop yields. Recently, automated weed control techniques based on computer vision were developed despite experiencing difficulties in creating agricultural datasets. One possible solution to the small volume of data available is Data Augmentation. This paper investigates the impact of individual data augmentation transformations on the pixel-level classification of crops and weeds when using a Deep Learning model. It also investigates the influence of input image resolution on the classification performance and proposes a patch augmentation strategy. Results have shown that applying individual transformations can be valuable to the model, but gets outperformed by the combination of all transformations. This work also finds that higher resolution inputs can increase the classification performance when combined with augmentation techniques, and that patch augmentation can be a valuable asset when dealing with a small number of high-resolution images. The method reaches the mark of 83.44% in Average Dice Similarity Coefficient, an increase of 19.96% percentage points compared to the non-augmented model.
HLA-A Alleles Differentially Associate with Severity to Plasmodium falciparum Malaria Infection in Ibadan, Nigeria

Human Leukocyte Antigen (HLA), particularly HLA-B and class II alleles have been differentially associated with disease outcomes in different populations following infection with the malaria Plasmodium falciparum. However, the effect of HLA-A on malaria infection and/or disease is not fully understood. Recently, HLA-A alleles have been suggested to play a role in the outcome of P. falciparum malaria infection in a Malian study. Herein, we investigated the association between HLA-A alleles and the outcome of malaria infection in children in Ibadan southwest Nigeria. HLA-A genotyping was performed on 393 children samples (DNA) using the sequence-based method. We compared genotype and allele frequencies data obtained from these Nigerian children; 176 with asymptomatic malaria infection (controls), 124 with uncomplicated malaria and 93 children with severe malaria (51 severe malarial anaemia and 42 cerebral malaria). We found a high frequency of HLA-A*36:01 (13.5%) in the entire studied population and also confirmed the high frequency of a previously reported allele of African origin (HLA-A*30:01). After adjusting for age and parasite density, we found a significant association between HLA-A*20:01:01 (OR = 3.19, p < 0.001) and susceptibility to severe malarial anaemia. We also found significant associations between HLA-A* 29:02:01 (OR = 7.26, p = 0.008) and A* 66:02 (Or = 4.19, p = 0.03) and susceptibility to cerebral malaria. Our findings suggest that HLA-A alleles play a role in the outcome of malaria in children in Ibadan. These findings may help elucidate the molecular background of malaria resistance in the study population.
Low-Profile Implementation of U-Shaped Power Quasi-Isotropic Antennas for Intra-Vehicle Wireless Communications

Intra-vehicle wireless communication applications, e.g. the wireless sensor network, are in need of antennas with uniformly radiated power for signal transmitting and receiving with their randomly distributed neighboring targets. This demand can be met with power quasi-isotropic antennas with low angular gain variation (<italic>GV</italic>). In this paper, two types of practical implementation for conventional U-shaped <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>/4 resonators, which are supposed to have theoretically ideal (approaching zero) <italic>GV</italic> but have intrinsically low radiation resistance, have been proposed. One is a dual-layer U-shaped radiator. The extra added layer introduces a resonance that can be utilized for a good impedance matching with a commonly used <inline-formula> <tex-math notation="LaTeX">$50~\Omega $ </tex-math></inline-formula> feeding line. A two-element array model and the two-port network are used to show the working mechanism and design considerations. The other is a U-shaped RFID tag antenna, which can be considered as the miniaturized form of a U-shaped <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>/4 resonator. With a structure evolution starting from a simple triple element model, the tag can have a good conjugate impedance matching with the terminated chip. Compared to their respective counterparts, both proposed antennas have the lowest measured <italic>GV</italic>. Meanwhile, their attracting features such as extremely low profile, small lateral size, light weight, simple configuration and fabrication process, and the possibility of a conformal implementation make them excellent candidates for future intra-vehicle wireless communications.
True Random Number Generator Integration in a Resistive RAM Memory Array Using Input Current Limitation

A novel True Random Number Generator circuit fabricated in a 130 nm HfO2-based resistive RAM process is presented. The generation of the random bit stream is based on a specific programming sequence applied to a dedicated memory array. In the proposed programming scheme, all the cells of the memory array are addressed at the same time while the current provided to the circuit is limited to program only a subset of the memory array, resulting in a stochastic distribution of cell resistance values. Some cells are switched in a low resistive state, other cells are slightly programmed to reach an intermediate resistance state, while the remaining cells maintain their initial high resistance state. Resistance values are next converted into a bit stream and confronted to National Institute of Standards and Technology (NIST) test benchmarks. The generated random bit stream has successfully passed twelve NIST tests out of fifteen. Compared to state-of-the-art resistive RAM-based true random number generators, our proposed methodology is the first one to leverage on programming current limitation at a memory array level.
A Software Defined Approach for Improving Resilience in Smart Distribution Grids

Smart grid is an essential part of the world's changing energy landscape. The uptake of smart grid by utilities is however hampered by the perceived complexity and large capital investment required to implement resilient Information Communication Technology (ICT) and networks that can support self-healing smart grids. Furthermore, failure to meet stringent smart grid communication reliability requirements can have disastrous consequences for grid owners and users. Many of the challenges utilities face with their smart grid ICT network development plans can be attributed to a reliance on conventional designs centred on expanding network hardware infrastructure in vast grid networks. What is needed to overcome these challenges is alternative ways of designing smart grid communication networks, using software defined approaches. This paper proposes a framework that supports software defined designs by combining the principles of the Internet of Things (IoT) paradigm and Machine-to-Machine (M2M) communication. Using the frameworks of software defined systems and virtualisation, our proposed architecture aims to provide a more flexible and affordable approach to developing and maintaining grid communication networks while offering a high level of network reliability, required for various smart grid applications. An evaluation of the implementation of this architecture in a design, based on a real city distribution grid, shows that a software defined communication network is easy to implement when using virtual machines running on existing computer infrastructure and that it is capable of supporting the network functions required for improving communication reliability. We conclude that this approach can potentially promote the adoption of smart grid by utilities while offering new innovative ways for smart grid developers to improve their grid designs.
An Effect on Form Particle Contamination in Biodegradable Transformer Oil

Nowadays, power transformer is most crucial electrical equipment in a power system. Researcher has been emphasized a lot of researches on natural ester oils to replace mineral oil that act as insulating liquid in power transformer. In this paper, an effort has been made to investigate corn oil (CO) as alternate liquid insulation to mineral oil (MO). Copper are used as particles contamination in this project. There are 12 oil samples has been prepared. Two samples which are pure MO and pure CO for before aging and 10 oil samples which are five samples of pure MO and five samples of pure CO for after aging. The particles contamination that used in this experiment which is copper with different size of length was added in each sample for after aging. The length sizes of copper were 5cm, 10cm, 15 cm, 20cm, 25cm and 30cm. In this report, the investigation of AC breakdown voltage involved two stages which are before aging and after aging. For before aging, two oil samples are only conducting AC breakdown voltage. Moreover, for after aging another 10 sample has been heated in the oven with temperature 115°C at 96 hours in order to investigate the effect of particle contamination in the transformer oil. From the experiment result that conducted, pure CO higher value of AC breakdown voltage than pure MO for before aging. But, after aging process, the value of pure MO with difference size of copper is higher than pure CO. It show that CO is good oil insulator to replaced MO for the future, but for use in long term, MO still the best insulator because has higher AC breakdown voltage than CO after aging process.
Concurrent and Optimal Structure, Control and Implementation Design

Mechatronic system design includes a combination of different engineering disciplines. A common approach in design of mechatronic systems is based on a sequential method, where different disciplines are treated and designed separately. This paper extends earlier work on integrated physical and control design optimization with integrating an additional aspect of the corresponding embedded control system implementation. Our previous publications describe integrated design optimization through a few specific use cases but the impact of embedded control implementation on the structural design of the systems is neglected. In this paper, the approach is extended to cover discussions on control implementation and its effect on the physical dimensioning and vice versa. A multi-objective optimization approach is implemented and tested on a mechatronic system case study consisting of a DC-motor, a planetary gear, a flexible shaft, an embedded controller and a load. The couplings between the properties of different engineering domains are studied and highlighted. The presented approach which is aimed for early phases of design, considers the integration of three engineering disciplines in one design framework which so far has been missing.
Efficacy of increased-dose erlotinib for central nervous system metastases in non-small cell lung cancer patients with epidermal growth factor receptor mutation

Purpose Recent reports indicate that refractory central nervous system (CNS) metastases of non-small cell lung cancer (NSCLC) are improved by high-dose gefitinib or erlotinib administration. We describe a Japanese woman with NSCLC and CNS metastases who was resistant to 75 mg daily erlotinib, but the metastases were improved by 150 mg daily erlotinib. We investigated the plasma and CSF concentrations of erlotinib at each dose as well as the correlation between the plasma and CSF concentrations of erlotinib. Methods Including this patient, we administered 150 mg erlotinib daily to nine NSCLC patients with CNS metastases and measured the plasma and CSF concentrations just before administration on day 8. The concentrations were determined using high-performance liquid chromatography with ultraviolet detection. Results The plasma and CSF concentrations of erlotinib at a dose of 75 mg were 433 and 14 nM, respectively. The plasma and CSF concentrations of erlotinib at a dose of 150 mg were increased to 1,117 and 44 nM, respectively. The mean ± standard deviation of CSF concentrations and penetration rates were 106 ± 59 nM and 4.5 ± 1.5%, respectively. There was a good correlation (R 2 = 0.84) between plasma and CSF concentrations (P = 0.0005). Conclusions This study indicates that CSF concentrations of erlotinib depend on its plasma concentration. As seen in this patient, high CSF concentrations of erlotinib can be achieved by high-dose administration, and this finding suggests the efficacy of high-dose administration, especially to refractory CNS metastases of NSCLC patients.
Working Hours, Burnout and Musculoskeletal Discomfort in Middle and Senior Management of Mexican Industrial Sector

Work-related stress is one of the ten most frequent occupational health problems worldwide and precedes a variety of serious mental disorders. It occurs when employees’ capabilities fail to meet job demands or when their knowledge and skills are insufficient to comply with company expectations. The aim of this research was to evaluate the impact of working hours and burnout syndrome (BS) on the appearance of musculoskeletal discomfort (MSD) through three dimensions. A cross-sectional study was conducted on 472 middle and senior management staff in the industrial sector in Mexico. Structural Equation Modeling was used to evaluate the relationship between variables. The results showed that 54% of participants reported to be working a maximum of 48 hours a week, the four most frequent MSD occurring in the low back, upper back, neck and eyes. Regarding BS, 59.6% of the participants experienced it at levels ranging from medium to extreme. These findings showed that working hours have a direct impact on emotional exhaustion and indirectly affect MSD and the dimensions of professional efficacy and cynicism. In addition, discomfort in the upper back is directly associated to ailments in the low back and neck and indirectly, to discomfort in the eyes. This points to the need for a greater focus on developing specific measures to reduce or prevent musculoskeletal discomfort symptoms which result from employees’ long working hours and emotional exhaustion.