Miracle-dz/UniFAR-FTUs huggingface dataset:
All SiC Grid-Connected PV Supply with HF Link MPPT Converter: System Design Methodology and Development of a 20 kHz, 25 kVA Prototype

Design methodology and implementation of an all SiC power semiconductor-based, grid-connected multi-string photovoltaic (PV) supply with an isolated high frequency (HF) link maximum power point tracker (MPPT) have been described. This system configuration makes possible the use of a simple and reliable two-level voltage source inverter (VSI) topology for grid connection, owing to the galvanic isolation provided by the HF transformer. This topology provides a viable alternative to the commonly used non-isolated PV supplies equipped with Si-based boost MPPT converters cascaded with relatively more complex inverter topologies, at competitive efficiency figures and a higher power density. A 20 kHz, 25 kVA prototype system was designed based on the dynamic model of the multi-string PV panels obtained from field tests. Design parameters such as input DC link capacitance, switching frequencies of MPPT converter and voltage source inverter, size and performance of HF transformer with nanocrystalline core, DC link voltage, and LCL filter of the VSI were optimized in view of the site dependent parameters such as the variation ranges of solar insolation, module surface temperature, and grid voltage. A modified synchronous reference frame control was implemented in the VSI by applying the grid voltage feedforward to the reference voltages in abc axes directly, so that zero-sequence components of grid voltages are taken into account in the case of an unbalanced grid. The system was implemented and the proposed design methodology verified satisfactorily in the field on a roof-mounted 23.7 kW multi-string PV system.
Segmentation of Drilled Holes in Textured Wood Panels using Deep Learning Framework

Automated vision-based detection and inspection systems become a key process in industry 4.0. Automatic precise detection of the drilled holes in various textured wood panels is an essential component in the automatic assembly lines to ensure the success of the assembly process and for the detection of the drilling defects. The wood panels are produced with a wide variety of complex textures and colors. This brings a big challenge to the vision detection process of the drilled hole panels. In this paper, we apply the deep learning mask region-based convolution neural network (Mask R-CNN) framework for the detection and segmentation of the drilled holes in synthetic images of wood panels with various textures, colors, and drilled hole patterns. A synthetic image dataset is generated for the drilled wood panels. Mask R-CNN provides simultaneous instance segmentation and detection for the drilled holes in a flexible and fast manner. The results show that the trained model can accurately perform the detection and segmentation process on the drilled holes for most images in the test dataset. We evaluate the model performance in terms of the mean average precision, the inference time, and the ability to extract the instance segmentation masks of the drilled holes.
E-Learning Gamification Model using Video Game Elements that Influence Engagement or Addiction

The common problem found in education was the low motivation and engagement of students to learn. One of the solutions offered to deal with this problem is the use of gamification. However, not all gamification implementations have successfully increased students’ motivation and engagement. One of the factors that contribute to the effectiveness of gamification is the selection of gamification elements. Improper selection of gamification elements may harm the gamification goals. On the other side, video games have been proven to influence users’ engagement. Learning from the video games domain, we tried to replicate the game elements from video games to e-learning. Thus, this study aims to identify video game elements that influence engagement or addiction from previous empirical studies and to develop an e-learning gamification model to increase user motivation and engagement. The finding revealed some game features and game practices to be used in the model proposed. The proposed gamification model was adapted from Landers’ Gamified Learning Theory with the addition of user type as a moderating variable.
Global Positioning System measurements: comparison of IoT wearable devices

Global Positioning System (GPS) receivers can be commonly found onboard Internet of Things devices, including wearables such as smartwatches and smart wristbands, thanks to miniaturization and power consumption reduction currently achieved by industrial processes. In recent applications, GPS-enabled smartwatches have been used also to monitor outdoor mobility of impaired or ageing users in free-living conditions. This work compares the GPS measurements performed by three commercial smartwatches in several outdoor positions. The results show that the devices present different measurement precision, depending on the chosen propagation scenario.
Genetic resistance to human malaria

to review the state of knowledge on genetic resistance associated with malaria Genetic resistance to malaria can be describe as an inherited alteration or changes in the genetic material of humans specifically DNA molecule and other vital biomolecules which the chances of resistance to malaria and in an increased survival of individuals with those genetic alterations. In such changes the general wellbeing and survival of the parasite to the extent that the parasite cannot multiply or replicate itself while in such erythrocyte. such alteration in the DNA molecule with some of the vital chemical and biochemical processes of the parasite ( Plasmodim ). several genetic disorders and trait Sickle cell disease, Glocose-6-Phosphatedehyrogenase deficiency, Pyruvate Kinase deficiency, Duffy antigen, Ovalocytocytosis, Thalassemia and blood against malaria in who at one of
A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces

High-frequency aerosol observation from a new-generation geostationary meteorological satellite is capable to capture and monitor the spatiotemporal dynamic variation of aerosols, which is of vital significance to environmental research and climate studies. Due to the diversity and complexity of land cover, it is a challenge to retrieve aerosol properties with high accuracy over land, especially over heterogeneous land surfaces. In this study, a geometry-discrete minimum reflectance aerosol retrieval algorithm (GeoMRA) has been proposed to retrieve 10-min high temporal resolution aerosol optical depth (AOD) datasets for geostationary Himawari-8 Advanced Himawari Imager (AHI) sensor, aiming at providing universal bidirectional reflectance distribution function (BRDF) descriptions for different land surfaces with different heterogeneous extent. The AOD retrievals from GeoMRA demonstrate good consistency against the ground-based AERONET measurements in East Asia from 2015 to 2020, with a correlation coefficient ( ${R}$ ) of 0.883 and approximately 65.6% of matchups falling within the expected error envelope of ±(0.05% +15%). Intercomparison between the GeoMRA retrieved AOD and other operational AOD products shows that the GeoMRA AOD retrievals, which generally possess similar spatial distribution and accuracy as Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products, have better performances than the Japan Aerospace Exploration Agency (JAXA) AOD products by providing more accurate AOD retrievals with higher spatial coverage. Moreover, the AOD bias analyses further demonstrate the robustness of GeoMRA algorithm, and an extreme haze event shows that the continuous GeoMRA AOD images illustrate smoother temporal variations than JAXA AOD products, demonstrating its efficacy and reliability in capturing the process of haze transport and monitoring the continuous spatiotemporal variation of aerosol. The above results suggest the considerable accuracy of GeoMRA algorithm for scientific application requirement and demonstrate the robustness of the proposed BRDF scheme in describing heterogeneous surfaces with diverse reflectance distribution.
An Intelligent Identification Approach Using VMD-CMDE and PSO-DBN for Bearing Faults

In order to improve the fault diagnosis accuracy of bearings, an intelligent fault diagnosis method based on Variational Mode Decomposition (VMD), Composite Multi-scale Dispersion Entropy (CMDE), and Deep Belief Network (DBN) with Particle Swarm Optimization (PSO) algorithm—namely VMD-CMDE-PSO-DBN—is proposed in this paper. The number of modal components decomposed by VMD is determined by the observation center frequency, reconstructed according to the kurtosis, and the composite multi-scale dispersion entropy of the reconstructed signal is calculated to form the training samples and test samples of pattern recognition. Considering that the artificial setting of DBN node parameters cannot achieve the best recognition rate, PSO is used to optimize the parameters of DBN model, and the optimized DBN model is used to identify faults. Through experimental comparison and analysis, we propose that the VMD-CMDE-PSO-DBN method has certain application value in intelligent fault diagnosis.
High-Resolution Marine Seismic Imaging of the Seattle Fault Zone: Near-Surface Insights into Fault Zone Geometry, Quaternary Deformation, and Long-Term Evolution

The Seattle fault zone (SFZ) is a north-directed thrust fault system that underlies the greater Seattle metropolitan area. Evidence of past land level changes, landslides, liquefaction, and a local tsunami indicate that this 70-km-long fault system can host up to M 7–7.5 earthquakes. Both the geometry and earthquake recurrence of the SFZ are debated and surveys of the shallow subsurface have not yet been incorporated into deeper crustal-scale structural interpretations, especially where the SFZ cuts across marine portions of the Puget Lowland. Here we use a new high-resolution marine seismic reflection dataset to image fault-related deformation in Quaternary sediments and Tertiary bedrock throughout Puget Sound and Lake Washington. We use this perspective of shallow geology as a link between existing crustal-scale geophysical insights into fault geometry at depth and paleoseismological observations of faulting at the surface and propose a refined structural model for the SFZ. We interpret that our new seismic reflection data in the Rich Passage area of Puget Sound images evidence of an inactive, south-dipping strand of the SFZ, which is overprinted by Quaternary folding and slip along north-dipping backthrusts within the hanging wall of a blind, south-dipping fault located 6 km farther north. To explain these results, we propose that the SFZ is a normal sequence fault propagation fold that has stepped northward through time, and we show the plausibility of this model through trishear forward modeling. Growth strata and faulting imaged in Quaternary sediments in Lake Washington and Rich Passage are consistent with the spatial distribution of folding and backthrusting that occurred during an M 7–7.5 earthquake in A.D. 900–930, corroborating existing evidence that the SFZ has been active throughout the Quaternary.
Enabling Efficient Slab-based Allocator on Fast NVMe SSD

The storage community has been struggling to exploit modern fast NVMe SSD in the storage software stack. This paper presents a new storage software layer, called SNallo, to efficiently support the upper software stack, i.e., file systems or KV stores. The key idea of the software layer is to introduce traditional DRAM allocators into block-addressable NVMe SSD with the key observation that modern fast NVMe SSD performs nearly as a random access device. However, SSD and DRAM are naturally different in terms of I/O granularity and persistent requirement. SNallo proposes an optimized layout algorithm considering fragmentation and I/O granularity, a two-phase write to achieve fast persistence, a fast address map-ping strategy between memory and block address, and light-weight defragmentation to further reduce fragmentation. To deliver efficient I/Os, SNallo uses SPDK to enable asynchronous per-core I/O processing. We build a KV store on SNallo and the evaluation result of YCSB benchmark shows that the new KV(key-value) store significantly outperforms all baselines in terms of space utilization, throughput, and latency.
Managing the pandemic in German federal states: types of mobility restrictions and their impacts on co-presence in innovation ecosystems

ABSTRACT This paper analyses the effects that mobility restrictions during the COVID-19 pandemic have had on different types of co-presence, which the existing literature considers to be central for science and innovation. Drawing on a regional analysis of COVID-19 restrictions in Germany, it links specific mobility restrictions to concrete impacts on co-presence, differentiating between co-presence in organizations, dynamic temporary co-presence, and the local ‘buzz’. It highlights that co-presence at workplaces and conferences was resilient to restrictions but that the detrimental effects on the ‘local buzz’ may have been substantial and long-lasting. In conclusion, it cautions against the severe effects of placing restrictions on the education system. Subsequently, the discussion links the reported disruptions of co-presence to the potential effects of the pandemic on preconditions for innovative processes and economic recovery.
Pengaruh Teknologi, Kualitas Dan Pemanfaatan Sistem Informasi Akuntansi Terhadap Kinerja Perusahaan

This study aims to determine the effect of technology, quality and utilization of accounting information systems on company performance. In this study, researchers examined the company's performance at PT Karunia Alam Segar in Gresik City by using independent variables, namely accounting information system technology, accounting information system quality and accounting information system utilization. The population of this research is all employees of accounting information system users who work at PT Karunia Alam Segar. Sampling was carried out using purposive sampling method, and the number of samples was 70 respondents. The data analysis technique used in this research is SEMPLS. The results of hypothesis testing in this study indicate that accounting information system technology and the quality of accounting information systems have a significant and significant effect on company performance. While the use of accounting information systems does not affect the company's performance. This is due to environmental factors in the form of attitudes that affect individual performance so that employees have a negative attitude towards the use of accounting information system technology forcibly due to pressure in the work environment.
Research on Complexity Change of Stock Market Based on Approximate Entropy

Approximate entropy, a method of analyzing the complexity of time series. This study analyzes the time series data of Shanghai Composite Index, and researches the complexity changes of stock market. By simulating, we generate periodic sequence, chaotic sequence, white noise sequence and combinatorial sequence, calculate the approximate entropy of different typical sequences, and it is verified that the approximate entropy method can reflect the complexity of different sequences. By calculating the approximate entropy of Shanghai Composite Index, the results show that the complexity of stock market is generally between periodic system and chaotic superimposed periodic system. In addition, the complexity of the stock market can reflect the volatility of the stock to some extent. It is also found that the higher the approximate entropy, the stronger the complexity of the stock market, and the greater the volatility of the stock market.
A Wearable Electrocardiography Armband Resilient Against Artifacts

Electrocardiography (ECG) is an essential technique to assess cardiovascular conditions and monitor physical activities. While the concept is mature, issues surrounding sampling convenience and device adoption as well as maintaining signal quality under artifacts remain a problem. In this article, we present a high-performing wearable ECG armband on the upper left arm. It is equipped with miniaturized hardware, capable of data storage and wireless communication. We evaluate different electrode configurations by conducting ECG measurements both at the static state and under motion and using improved algorithms to quantify data quality and assess the agreement between the proposed new technique and the gold standard. The optimal electrode position is determined by balancing wearable suitability and signal quality. We propose an electronic textile (E-textile) armband with improved design. It offers favorable wearing comfort and a fashionable appearance without sacrificing data quality. Its contact pressure is measured to get a better picture of intimacy and clothing comfort. Our system provides real-time and noise-resilient ECG data without interrupting daily life and can be implemented in use cases that warrant continuous ECG monitoring.
SUPG-YZβ computation of chemically reactive convection-dominated nonlinear models

In this computational study, we deal with the stabilized finite element solutions of convection-dominated models having nonlinear reaction mechanisms. The existence of advection terms in these models causes the numerical solutions obtained by standard discretization methods to exhibit nonphysical oscillations. The Galerkin finite element method is stabilized using the Streamline-Upwind/Petrov–Galerkin formulation to avoid such spurious oscillations. The stabilized formulation is also complemented with the YZβ shock-capturing technique to resolve steep gradients and discontinuities accurately. The nonlinear equation systems arising from the spatial discretizations are solved with the Newton–Raphson method supplemented with the ILU-preconditioned GMRES search technique. The proposed methods are tested on a comprehensive set of nonlinear reactive models. Numerical experiments show that the presented methods and techniques eliminate spurious oscillations significantly and resolve strong gradients accurately. All computations are performed in the FEniCS environment.
Planar Inverted-F Antenna for Bluetooth Applications

In this work a simple, low cost and compact PIFA antenna for Bluetooth application is presented. The size of the proposed antenna is 16.3*6*4.9mm and it is designed and simulated under CST software using the low cost substrate FR4. The simulated S11 is <-10 dB over 2.42-2.49 GHz. The antenna shows acceptable gain around of 1.56 dB at the frequency 2.45 GHz with nearly omnidirectional radiation patterns over Bluetooth application.
Angiogenic and Osteogenic Properties of Fibrin in Bone Tissue Engineering

The bone scaffold has become a promising alternative in bone tissue engineering due to the limitation associated with current bone treatments. However, the selection of scaffold material that could accurately mimic the extracellular matrix of native tissue remains challenging. Owing to its biological origin properties, natural materials including fibrin are widely used as scaffold materials as compared to synthetic materials. Fibrin has been recognized as one of the appealing natural biopolymers, which possesses unique characteristic due to its natural formed nano-scaffold, which provide a temporary matrix that facilitates cellular activities of cells. Fibrin has shown remarkable effects over other biomaterials in inducing angiogenesis and osteogenesis in bone regeneration owing to its mechanical and biological properties. In this article, we highlight the significance of fibrin materials in facilitating bone regeneration. We focus on the manipulation of fibrin composition and on the recent developments of fibrin composites in enhancing osteogenesis and angiogenesis for bone healing.
StegFog: Distributed Steganography Applied to Cyber Resiliency in Multi Node Environments

This paper presents a new study about the communication system named StegFog. It is based on applying distributed steganography linked with the concept of cyberfog security. The idea of cyberfog is to secure data by splitting it into numerous fragments and spreading them to end-user devices. The design of StegFog combines steganographic methods previously investigated by the Authors – StegHash and SocialSteg Disc. The reference design of the system is proposed and analyzed in terms of security, reliability, performance and timing. To prove the feasibility of the proposed solution, the prototype of StegFog was implemented, consisting of steganographic nodes operating over BitTorrent P2P networks with a hidden communication channel established by the multimedia files shared within it. Experiments were conducted for the implemented prototype to understand the basic features of the system, such as operational aspects of the address generator constructed using the modified StegHash method, timing of the basic methods within the system – reading, writing and notifying, steganographic rate of the system and overall security provided by the system. The presented results show how system such as StegFog aligned with the cyberfog security concept could be considered as the protection measure for secure network communications. The practicality, challenges and research directions to extend the concept are also discussed.
Validity and Repeatability of Inertial Measurement Unit for
Measuring Walking Gait Parameter of Patients with Non-specific
Low Back Pain

Introduction: The Inertial Measurement Unit (IMU) is electronic device that enabled us to record joint angles, gait event and spatiotemporal parameter using accelerometers. IMU contain sensors known as inertial sensor which measures its movement by using the inertia principle. This study aimed to determine validity and reliability of spatiotemporal gait parameter using the IMU sensor. Methods: This study are prospective cross-sectional recruited thirteen convenience subjects (four men, nine women; 50.0 +/-15.0 years) diagnosed with chronic Non-Specific Lower Back Pain (LBP) from Physiotherapy Department, upon an Orthopedic Specialist’s referral, at Hospital Sultanah Aminah Johor Bahru. Spatiotemporal parameters interested: left and right velocity, cadence, stride/step time and stride/step length recorded by Vicon system and IMU sensors synchronously. Results: Higher validity was indicated at the Trial 2 detected by the IMU sensors comparing Vicon system, with significant correlation p ≤ 0.05 except stride time left shank (r = 0.539, p = 0.06) , left foot (r = 0.495, p = 0.11) and step length left shank (r = 0.532, p = 0.06). The result of study also indicated that the reliability of the IMU sensors based on ICCs ≥ 0.75 and 95% CI 0.180 – 0.993, p ≤ 0.01 in Non-specific LBP patients for spatiotemporal gait parameters comparing Trial 1 and Trial 2. Conclusion: The IMU system performs to be valid and reliable for determine spatiotemporal gait parameters in Non-specific LBP patients. IMU provides a possible solution to measure spatiotemporal gait in a clinical setting without requiring specific working area and professional technician.