Miracle-dz/UniFAR-FTUs huggingface dataset:
Establishing Customer Behavior Through E-Commerce Websites in Newly Emerging Market

E-commerce is creating growth opportunities for e-retailers, especially during the Covid-19 outbreak. It increases the perceptions of both providers and customers toward their shopping convenience. In 2021, Vietnam became one of the fastest-growing countries among Southeast Asia’s Internet economies. However, both scholars and management practitioners have argued the inconsistent assessments of the factors affecting customer purchase behavior in online settings. Thus, this study aims to identify the critical factors influencing customer behavioral intention toward e-commerce websites that were adopted from well-established models and relevant literature. The online survey was the data collection method. All items were measured through a 5-point Likert scale. This study proposed and analyzed a conceptual framework using existing survey data from 312 samples in the context of online buying via e-commerce websites. Data were analyzed by using the statistical tool SPSS. The results indicated that factors including perceived usefulness, transaction security, perceived ease of use, trust, and subjective norm positively influence customer shopping intention. The results revealed the most prominent impact of the transaction security on customer purchase intention. Besides, perceived risk is a significant barrier in online shopping through e-commerce websites. The researchers have brought practical insights and made conceptual contributions by extending existing research on the technology acceptance model (TAM) and theory of planned behavior (TPB) regarding online shopping on the e-commerce website. The paper helps to validate and strengthen the importance of customer purchase intention in an e-shopping environment. The findings would help e-commerce providers be able to formulate specific strategies to increase customer usage significantly. Moreover, managers can focus their attention and resources on the greatest significant factors regarding their effects on behavioral intention.
A method for comparing properties of cirrus clouds in global climate models with those retrieved from IR sounder satellite observations

A methodology to compare cloud properties simulated by global climate models with those retrieved from observations by satellite-based infrared (IR) sounders has been developed. The relatively high spectral resolution in the CO2 absorption band of these instruments leads to especially reliable cirrus properties, day and night. Additionally, bulk microphysical properties can be retrieved for semi-transparent cirrus, based on the observed spectral emissivity differences between 8 and 11 µm. The particular intention of this study is to compare macro-and microphysical properties of high cloudiness as represented by the model simulations and the satellite data. For this purpose, a method has been developed to process the model output to be comparable to the satellite measurements, as in other observational simulator packages (for example the ISCCP-simulator). This simulator method takes into account i) the differences in horizontal resolution of the model and the observations, ii) the specific observation time windows, iii) the determination of the pressure of a cloud system, identified with the pressure at the middle of the uppermost cloud, and iv) the selection of high clouds with specific cloud optical thickness ranges for the microphysical property retrieval using IR sounder data. Applying this method to simulations by the global climate model ECHAM and TOVS satellite observations has important effects. The frequency of high clouds selected from the model output by using the method is significantly smaller than the total frequency of high cloudiness in the model. Largest differences occur around the equator where the zonal mean frequency of high cloudiness is reduced by about 30 % (relative change). The selection method is essential for the comparison of modelled and observed microphysical properties of high clouds. The selection of high clouds from the ECHAM simulation according to the optical thickness range of the TOVS data results in a reduction of the mean water path of high clouds by factors of more than 3 compared to the case where also high clouds of other optical thicknesses are considered. Furthermore, the selection by optical thickness causes a significant increase in the mean effective cloud particle diameter. These changes significantly reduce the differences between the simulation and the observations. The method can also be applied for comparisons with other IR sounder climatologies such as from AIRS and IASI. © Gebruder Borntraeger, Stuttgart 2010.
Charge Growth Equation for Belts of Insulating Materials Passing over Grounded Rollers

The magnitude of the electrostatic charge density on an insulating belt of photographic film increases as the belt passes repeatedly over a set of grounded metal rollers. The charge density q asymptotically approaches an equilibrium value qe according to the relation q = qe (1 − e−n/τ), where n is the number of roller passages and τ is an arbitrary constant. An equivalent circuit which describes this behavior is presented. The circuit elements are an electromotive force, a contact resistance, a leakage resistance, and a capacitance between the belt and the roller. The physical equivalents of these elements and the possibility of their measurement are discussed.
Thermal Diffusivity of Concrete Samples Assessment Using a Solar Simulator

The thermal properties of pavement layers made of concrete with varying bulk densities are a particularly interesting topic in the context of development road technologies. If a hybrid layer system is used as a starting point, with thin asphalt layers (from 1 cm to 4 cm) laid on top of a foam concrete layer, thermal properties begin to play a crucial role. The main research problem was to create a test method enabling the assessment of the influence of solar heating on the thermal parameters of the building material, especially cement concrete. For this reason, this paper is concerned specifically with the assessment of a new methodology for testing and calculating the value of the thermal diffusivity coefficient of samples made of concrete varying bulk densities. In this case, using the proprietary concept the authors built a solar simulator using a multi-source lighting system. The analysis of the results of laboratory tests and numerical analyses allowed the authors to observe that there is a strong correlation between the bulk density of samples heated and the thermal diffusivity parameter, which appears in the unidirectional heat transfer equation. The strength of this relationship has been expressed with the coefficient of determination and amounts to 99%. The calculated values of the coefficient of thermal diffusivity for samples made of foam concrete range from 0.16×10−6m2s to 0.52×10−6m2s and are lower (from 2.5 to 8 times) than the value determined for samples made of typical cement concrete.
Mode Analysis, Transformer Saturation, and Fault Diagnosis Technique for an Open-Circuit Fault in a Three-Phase DAB Converter

The three-phase dual active bridge (DAB3) is a popular dc–dc converter topology for high-power applications, capable of high-efficiency bidirectional power transfer with galvanic isolation. A single point of failure in power converters is the open-circuit fault (OCF) due to failure in a semiconductor device or its gate drive circuit. This study presents detailed waveform analyses for the normal- and the fault-mode operation. A novel logic-based fault diagnosis scheme is proposed based on the unique pattern in the dc bias of phase currents. Unlike previous schemes, the proposed scheme requires low-bandwidth current sensing only one side of the transformer to detect faults on either side, providing a cost and design benefit. Experimental results verify the analyses and the proposed identification scheme, detecting the fault within a few switching cycles. An in-depth study of the transformer under fault mode is presented for the first time, setting a guideline of time available for fault diagnosis and response. Experimental B–H curves and magnetizing currents of the three-phase transformer illustrate the cycle-by-cycle progression toward core saturation under fault mode. The study also reveals a new potential benefit of the three-phase DAB over the single-phase DAB; i.e., even in the presence of a secondary-side OCF, the DAB3 may continue to operate normally at full load.
An Efficient Configurable Hardware Accelerator Design for CNN on Low Memory 32-Bit Edge Device

Nowadays the ability of Convolutional Neural Networks (CNN) to mimic the behavioral characteristics of the biological visual neuron makes it a popular choice for image identification. It comprises a deep structure and a high network that performs convolutional calculations. Most of the operations are in CONV layers, hence they are compute-intensive. The need for more computing power for CNN is a key factor in the creation of robust parallel computing platforms like GPUs, or specialized hardware accelerators. Therefore an efficient implementation of CNNs to improve performance using limited resources without accuracy reduction is a challenge. A configurable template-based single convolution layer which includes convolution, relu, and pooling sub-layers is designed and it is used to match all CONV layers of CNN. It contains a processing element array with twenty-five processing elements inside for making parallel computations and data reuse. Pipelining, Loop unrolling, and array partitioning are the techniques for increasing the speed of computing the CONV layer. This design is verified with MNIST handwritten digit image classification on a low-cost, low-memory 32-bit PYNQ-Z2 system on chip edge device. The computation time of the proposed hardware design achieved 86.14% lesser than INTEL core3 CPU, 82.24 % lesser than Haswell core2 CPU, 76.48% lesser than NVIDIA Tesla K80 GPU and 29.26% reduction in compute time when compared to the conventional accelerator. The implementation results show that there was no accuracy drop with an increase in the speed of the computations in the proposed hardware design.
Electrochemical Biosensors as a Novel Platform in the Identification of Listeriosis Infection

Listeria monocytogenes (L.M.) is a gram-positive bacillus with wide distribution in the environment. This bacterium contaminates water sources and food products and can be transmitted to the human population. The infection caused by L.M. is called listeriosis and is common in pregnant women, immune-deficient patients, and older adults. Based on the released statistics, listeriosis has a high rate of hospitalization and mortality; thus, rapid and timely detection of food contamination and listeriosis cases is necessary. During the last few decades, biosensors have been used for the detection and monitoring of varied bacteria species. These devices are detection platforms with great sensitivity and low detection limits. Among different types of biosensors, electrochemical biosensors have a high capability to circumvent several drawbacks associated with the application of conventional laboratory techniques. In this review article, different electrochemical biosensor types used for the detection of listeriosis were discussed in terms of actuators, bioreceptors, specific working electrodes, and signal amplification. We hope that this review will facilitate researchers to access a complete and comprehensive template for pathogen detection based on the different formats of electrochemical biosensors.
Limit theorems for random maximum of independent and non-identically distributed random vectors

In this paper, we study the weak convergence of the random maximum of independent and non-identical random vectors. When the random sample size is assumed to be independent of the basic variables and its distribution function is assumed to converge weakly to a non-degenerate limit, the necessary and sufficient conditions for the weak convergence of the random maximum are derived. An illustrative example is given.
Effect of the magnetic field on the collision frequencies for fusion reactions at low energies

The results of a theoretical study of the effect of a magnetic field, B, on the collision frequencies, Ff, for fusion reactions at comparatively low energies are presented. In a usual magnetic field strength, both the cross-section for fusion reactions and the cross-section for the Coulomb scattering between the ion-ion collisions are unaffected by B. However, due to both the gyration of the particle and the Coulomb scatterings occurring during a free path for fusion reactions, the relative velocity between colliding particles making the fusion reaction is affected by B. If omega is a gyrofrequency and tc the deflection time for a 90 degrees deflection of multiple Coulomb scattering when omega tc>2 pi , it was determined that the velocity component contribution to the collision for fusion reactions is only the velocity component along the field axis and that Ff decreases with increasing B. However, when omega tc<or=2 pi , Ff is unaffected by B because a number of collisions for the 90 degrees deflection occur during the path of a Larmor orbit.
Distributed-feedback fiber Raman laser

Summary form only given. Fiber Raman lasers are of great interest for applications in optical communications. To date such lasers have been demonstrated in Fabry-Perot configurations where feedback is provided by mirrors located at the ends of the Raman-active fiber medium. We propose and analyze for the first time a distributed-feedback fiber Raman laser and show that such a laser is feasible with current fiber Bragg grating (FBG) technology. Because the threshold gain of a DFB Raman laser scales inversely as the length cubed, the recent availability of FBG's with lengths of order 1 m should enable the operation of such lasers with standard CW pump sources.
Training Load Within a Soccer Microcycle Week—A Systematic Review

Supplemental Digital Content is Available in the Text. ABSTRACT Quantifying training load is important to ensure that athletes correctly respond to training prescription and reduce injury risk. Training load can be divided into internal training load, the response of an individual to the training demand, and external training load, the physical “work” of the players. We aimed to analyze training load during a training week (microcycle) in soccer players. Systematic searches of 3 electronic databases (PubMed, SPORTDiscus, and Web of Science) were conducted, and Preferred Reporting Items for Systematic Review and Meta-analysis guidelines were followed. From 1,718 studies initially found, 16 were selected after screening. Descriptive and Z-score analyses were performed for each variable (acceleration and deceleration [DEC], average speed, high-speed running, sprint, total distance, player load, percentage of maximal heart rate, and rating of perceived exertion [RPE]). A sample of this review was 317 male soccer players aged 16.4–27.6 years, competing in elite, professional, and youth levels. Three days prior to match day was the most demanding session of the week, except for DEC, average speed, and player load demands. The day prior to match day was the least demanding session, except for sprint and RPE. In conclusion, midweek sessions can be chosen to apply higher training loads, whereas training sessions immediately before and after the match can be used to taper or recover.
Wireless Power Transfer Characterization Based on Inductive Coupling Method

Wireless power transfer (WPT) technology has been developed and encountered in a wide range of charging applications. This paper describes the WPT model with an experimental validation to obtain the relation between the inductive coupling parameter and electrical characteristic. The important aspect in the WPT design with inductive coupling method is the range between coupling device, transmission signal frequency and inductance. Selected wire diameter, coil diameter and the ratio of coil turn number are chosen according to the inductive coupling observation based on electromagnetic field. Measured voltage, current and power were also investigated. The mechanism of energy transfer is conducted by exploration of electrical characteristic between transmitter and receiver, respectively. The measured electrical parameter can be directly influenced by these indicators associated with the efficiency investigation. The highest efficiency was achieved by 40 J.1H inductance of 35.85%. The higher efficiency of the transferred energy was obtained by the inductor with a low inductance value.
DMD:DNA alignment in memory constrained device

Genome analysis plays a vital role in the treatment of patients, forensic science as well as historical gatherings. Advancements in the sequencing technologies such as Third Generation Sequencing (TGS) and High Throughput Sequencing (HTS) have resulted in accelerated genome sequencing. However, genome analysis remains slower in comparison to advanced sequencing technology. The aforementioned constraints are addressed in this paper by designing a secured, scalable, economical, compact and internet-independent system for secured DNA alignment. In this work, a novel architecture has been presented for miniature system utility characterized by limited processing capabilities exploiting its constrained memory against a partial reference genome. Optimising memory communication and applying distributed computing resulted in the implementation of such big data application on SWARAM, an ARM-based computation device. In this paper, we extended our previous publication by optimising in-memory communications and algorithms on SWARAM to align reads securely and efficiently. NA12878 Illumina platinum, a standard benchmark dataset has been used to test reads extensively. The test confirmed that the time consumption for data transfer and completion of reads securely processing on a single ODROID device was competitive to one unit of the original SWARAM system.
Combining the External Medical Knowledge Graph Embedding to Improve the Performance of Syndrome Differentiation Model

The electronic medical records (EMRs) of traditional Chinese medicine (TCM) include a wealth of TCM knowledge and syndrome diagnosis information, which is crucial for improving the quality of TCM auxiliary decision-making. In practical diagnosis, one disease corresponds to one syndrome, posing considerable hurdles for the informatization of TCM. The purpose of this work was to create an end-to-end TCM diagnostic model, and the knowledge graph (KG) created in this article is used to improve the model's information and realize auxiliary decision-making for TCM disorders. We approached auxiliary decision-making for syndrome differentiation in this article as a multilabel classification task and presented a knowledge-based decision support model for syndrome differentiation (KDSD). Specifically, we created a KG based on TCM features (TCMKG), supplementing the textual representation of medical data with embedded information. Finally, we proposed fusing medical text with KG entity representation (F-MT-KER) to get prediction results using a linear output layer. After obtaining the vector representation of the medical record text using the BERT model, the vector representation of various KG embedded models can provide additional hidden information to a certain extent. Experimental results show that our method improves by 1% (P@1) on the syndrome differentiation auxiliary decision task compared to the baseline model BERT. The usage of EMRs can aid TCM development more efficiently. With the help of entity level representation, character level representation, and model fusion, the multilabel classification method based on the pretraining model and KG can better simulate the TCM syndrome differentiation of the complex cases.
Vehicle-to-Infrastructure based Algorithms for Traffic Light Detection, Red Light Violation, and Wrong-Way Entry Applications

Major injuries and fatalities in the United States (US) frequently occur as a result of drivers attempting to run red lights at the intersections and driving in the wrong-way on access ramps or against the legal direction of the traffic leading to red light violations (RLVs) and wrong-way entry (WWE) events respectively. But, these incidents can be detected earlier using connected vehicle (CV) technology which may then be reported to the drivers through a human-machine interface. In this work, we propose algorithms to detect the approaching traffic light status, red light running (RLR), and wrong-way driving (WWD) events using Basic Safety Messages (BSMs) obtained through vehicle-to-infrastructure (V2I) communication. To detect the accurate and applicable light, we assume that road-side units (RSUs) are installed on each traffic light in such a way its heading direction is opposite to the legal flow of traffic. After the approaching light status is detected, we check if the vehicle is going to be in an RLR zone. Similarly for WWD, we assume the same except that the RSUs are installed on street poles. After the detection, we display the traffic light status, red light violation warning (RLVW), and wrong-way entry warning (WWEW) to the drivers in real time. To validate the proposed algorithms, the CARLA simulator is used to conduct experiments for various scenarios. Also, to support connectivity between vehicles and infrastructure, we added the V2I ability to CARLA.
84 Gigahertz Observations of Five Crab-like Supernova Remnants

Flux density measurements at 3.6 mm have been made to extend the frequency coverage for three Crablike remnants and two Crablike components within remnants whose large-scale morphologies show shell-type structure. All five objects show flat, polarized, nonthermal radio spectra and associated X-ray emission characteristic of this class. The flux density is found to be lower than expected on the basis of an extrapolation of the spectrum from lower frequencies. If this is due to steepening caused by evolutionary effects, severe constraints can be put on the characteristics of the objects showing spectral steepening: all must be less than 2000 yr old, and the supernovae in which they were born must all have had very unusual properties. 30 refs.