Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling ITOETAM for Cloud Computing Challenges validation and developing in Tourism and Hospitality Higher Education Institutions

Cloud computing is considered as one of the strongest innovations that has gained the attention of technological experts everywhere. It offers lots of benefits. , but it also poses several security threats that no establishment can afford to ignore. The progressive education in creating nations is experiencing the issue of conveying dimension of the data and interchanges innovation. Based on these difficulties, the study attempts to develop and validate the Model for cloud computing challenges (CCC) in tourism and hospitality higher education institutions (THHEI) to find solutions to these challenges. In order to identify those challenges, the research aims to create and validate the model created by Juma and Tjahyanto (2019) for a unique model referred to as the proposed model for cloud computing adoption challenges (ITOETAM) to categories various difficulties and specific issues higher education institutions in tourism and hospitality face when using the educational cloud computing services. The model consists of five constructs named CCC, Internal, External factor (IEF), technological factors (TF), organizational factors (OF), and environmental factors (EF). The researchers relied on the following variables from the model as follows "CCC-THHEI, TF, EF and IEF. A total of 431 respondents are students, graduate students, staff, IT personnel and employees of Egyptian tourism and hotel education faculties and institutions. The research supports the "ITOETAM" concept. Which structural equation modelling (SEM) testing technique was used. The goodness of fit indices were good; they were as follows: x2 = 505.131 (df = 214), p 0.001, x2/df = 2.360, GFI = 0.912, Comparative Fit Index (CFI) = 0.953, Normed Fit Index (NFI) = 0.922, Root Mean Square Residual (RMR) = 0.071, Incremental Fit Index (IFI) = 0.954, Relative Fit Index We've talked about potential restrictions and lines of inquiry.
Driver Emotion and Fatigue State Detection Based on Time Series Fusion

Studies have shown that driver fatigue or unpleasant emotions significantly increase driving risks. Detecting driver emotions and fatigue states and providing timely warnings can effectively minimize the incidence of traffic accidents. However, existing models rarely combine driver emotion and fatigue detection, and there is space to improve the accuracy of recognition. In this paper, we propose a non-invasive and efficient detection method for driver fatigue and emotional state, which is the first time to combine them in the detection of driver state. Firstly, the captured video image sequences are preprocessed, and Dlib (image open source processing library) is used to locate face regions and mark key points; secondly, facial features are extracted, and fatigue indicators, such as driver eye closure time (PERCLOS) and yawn frequency are calculated using the dual-threshold method and fused by mathematical methods; thirdly, an improved lightweight RM-Xception convolutional neural network is introduced to identify the driver’s emotional state; finally, the two indicators are fused based on time series to obtain a comprehensive score for evaluating the driver’s state. The results show that the fatigue detection algorithm proposed in this paper has high accuracy, and the accuracy of the emotion recognition network reaches an accuracy rate of 73.32% on the Fer2013 dataset. The composite score calculated based on time series fusion can comprehensively and accurately reflect the driver state in different environments and make a contribution to future research in the field of assisted safe driving.
Optimum and equilibrium in a transport problem with queue penalization effect

Abstract Consider a distribution of citizens in an urban area in which some services (supermarkets, post offices. . . ) are present. Each citizen, in order to use a service, spends an amount of time which is due both to the travel time to the service and to the queue time waiting in the service. The choice of the service to be used is made by every citizen in order to be served more quickly. Two types of problems can be considered: a global optimization of the total time spent by the citizens of the whole city (we define a global optimum and we study it with techniques from optimal mass transportation) and an individual optimization, in which each citizen chooses the service trying to minimize just his own time expense (we define the concept of equilibrium and we study it with techniques from game theory). In this framework we are also able to exhibit two time-dependent strategies (based on the notions of prudence and memory respectively) which converge to the equilibrium.
Efficient Approximate Posit Multipliers for Deep Learning Computation

Posit numeric format is getting more and more attention in recent years. Its tapered precision makes it especially suitable in many applications including deep learning computation. However, due to its dynamic component bit-width, the cost of implementing posit arithmetic in hardware is more expensive than its floating-point counterpart. To solve this cost problem, in this paper, posit multipliers with approximate computing features are proposed. The core idea of the proposed design is to truncate the fraction multiplier according to the estimated fraction bit-width of the product. So that the resource consumption of the fraction multiplier and thus the fraction adder can be significantly reduced. The proposed method is applied in both linear domain and logarithm domain posit multipliers. The 8/16/32-bit version of the proposed approximate posit multipliers are implemented and analyzed. For the commonly used 16-bit posit format in deep learning computation, the proposed approximate posit multiplier can consume 16% less power compared to the conventional posit multiplier design. The proposed 16-bit approximate logarithm multiplier can achieve a 15% improvement in terms of power consumption compared to the state-of-the-art posit approximate logarithm multiplier. The proposed 16-bit approximate posit multipliers are applied in the computation of several deep neural network models and significant improvements on energy efficiency can be achieved with negligible accuracy degradation.
Enabling Safe ITS: EEG-Based Microsleep Detection in VANETs

Researchers nowadays are particularly focusing on the interpretation of EEG signals to understand and exploit the information they provide for brain activities. Deep learning architectures performing sleep staging have recently grown to their full potential with their ability to learn and interpret highly complex mathematical contexts. This has been catered to owing to the increasing availability of large EEG data sets. In this paper, we describe how sleep staging differs from microsleep prediction. We also provide a fresh methodology for the microsleep classification job that works with even less training data. Our proposed model exploits the attention-based mechanism that clubs the advantages available in Wavelet transform with Short Time Fourier Transform(STFT) Spectrogram. We also put forward a robust deep learning model that contains separate “time-dependent” and “time-independent” parts, which can record contexts from the sequence of features and simultaneously learn intra-epoch relations. A single-electrode EEG signal was employed for our analysis to accommodate such procedures’ social acceptance. For the task of microsleep detection on the MWT dataset, our model achieves fairly high accuracy rates (92% training and 89.9% testing accuracy), and an overall improvement in the kappa value by ≈ 42%, as compared to prior novel approaches.
OCULUS Sea Track Fusion Service

Oculus Sea is a complete solution regarding maritime surveillance and communications at Local as well as Central Command and Control level. It includes a robust and independent track fusion service whose main functions include: 1) Interaction with the User to suggest the fusion of two or more tracks, confirm Track ID and Vessel Metadata creation for the fused track, and suggest de-association of two tracks 2) Fusion of same vessel tracks arriving simultaneously from multiple radar sensors featuring track Association, track Fusion of associated tracks to produce a more accurate track, and Multiple tracking filters and fusion algorithms 3) Unique Track ID Generator for each fused track 4) Track Dissemination Service. Oculus Sea Track Fusion Service adopts a system architecture where each sensor is associated with a Kalman estimator/tracker that obtains an estimate of the state vector and its respective error covariance matrix. Finally, at the fusion center, association and track state estimation fusion are carried out. The expected benefits of this system include multi-sensor information fusion, enhanced spatial resolution, and improved target detection.
Classification of oscillators in the Heisenberg-matrix representation

For an arbitrary finite and not too singular (presumably, phenomenological) superposition of potentials rdelta with rational exponents we solve the old problem of conversion of the corresponding differential Schrodinger bound-state problem into its matrix equivalent with the minimalized number L of non-zero diagonals. The construction-with proofs-is performed via the standard power-series method in its non-Hermitean matrix (sometimes called Hill-determinant) version. All the simplest and (in this sense) 'algebraizable' interactions are then displayed up to L=5. An example of application in perturbation theory is included.
The Relationship Between the Radio and Gamma-Ray Emission of Blazars

Blazars are active galaxies with a jet closely oriented to our line of sight. They are powerful, variable emitters from radio to gamma-ray wavelengths. Although the general picture of synchrotron emission at low energies and inverse Compton at high energies is well established, important aspects of blazars are not well understood. In particular, the location of the gamma-ray emission region is not clearly established, with some theories favoring a location close to the central engine, while others place it at parsec scales in the radio jet. We developed a program to locate the gamma-ray emission site in blazars, through the study of correlated variations between their gamma-ray and radio-wave emission. Correlated variations are expected when there is a relation between emission processes at both bands, while delays tell us about the relative location of their energy generation zones. Monitoring at 15 GHz using the Owens Valley Radio Observatory 40 meter telescope started in mid-2007. The program monitors 1593 blazars twice per week, including all blazars detected by the Fermi Gamma-ray Space Telescope (Fermi) north of -20 degrees declination. This program complements the continuous monitoring of gamma-rays by Fermi. Three year long gamma-ray light curves for bright Fermi blazars are cross-correlated with four years of radio monitoring. The significance of cross-correlation peaks is investigated using simulations that account for the uneven sampling and noise properties of the light curves, which are modeled as red-noise processes with a simple power-law power spectral density. We found that out of 86 sources with high quality data, only three show significant correlations (AO 0235+164, B2 2308+34 and PKS 1502+106). Additionally, we find a significant correlation for Mrk 421 when including the strong gamma-ray/radio flare of late 2012. In all four cases radio variations lag gamma-ray variations, suggesting that the gamma-ray emission originates upstream of the radio emission. For PKS 1502+106 we locate the gamma-ray emission site parsecs away from the central engine, thus disfavoring the model of Blandford and Levinson (1995), while other cases are inconclusive. These findings show that continuous monitoring over long time periods is required to understand the cross-correlation between gamma-ray and radio-wave variability in most blazars.
CoQ Regulates Brown Adipose Tissue Respiration and Uncoupling Protein 1 Expression

Coenzyme Q (CoQ, aka ubiquinone) is a key component of the mitochondrial electron transport chain (ETC) and membrane-incorporated antioxidant. CoQ10 deficiencies encompass a heterogeneous spectrum of clinical phenotypes and can be caused by hereditary mutations in the biosynthesis pathway or result from pharmacological interventions such as HMG-CoA Reductase inhibitors, and statins, which are widely used to treat hypercholesterolemia and prevent cardiovascular disease. How CoQ deficiency affects individual tissues and cell types, particularly mitochondrial-rich ones such as brown adipose tissue (BAT), has remained poorly understood. Here we show that pharmacological and genetic models of BAT CoQ deficiency show altered respiration that can only in part be explained by classical roles of CoQ in the respiration chain. Instead, we found that CoQ strongly impacts brown and beige adipocyte respiration via the regulation of uncoupling protein 1 (UCP1) expression. CoQ deficiency in BAT robustly decreases UCP1 protein levels and uncoupled respiration unexpectedly, resulting in increased inner mitochondrial membrane potential and decreased ADP/ATP ratios. Suppressed UCP1 expression was also observed in a BAT-specific in vivo model of CoQ deficiency and resulted in enhanced cold sensitivity. These findings demonstrate an as yet unappreciated role of CoQ in the transcriptional regulation of key thermogenic genes and functions.
The Long-Term Dynamical Behavior of Short-Period Comets

We have developed and carefully tested a new computer code to follow the long-term dynamical evolution of a swarm of test particles in the solar system. This new integrator is approximately an order of magnitude faster than previously existing codes. The technique efficiently and accurately handles close approaches between test particles and planets while retaining the powerful features of recently developed mixed variable symplectic integrators. We use the new code to numerically integrate the orbits of the known short-period comets (those with periods P 20 yr) orbits many times in their dynamical lifetimes. However, it is found that the Tisserand parameter, T, does not vary substantially for most comets. Therefore, we adopt a classification originally suggested by Carusi et al. (1987) that defines Jupiter-family comets (JFCs) as comets with T > 2 and Halley-family comets (HFCs) as those with T < 2. In this scheme, less than 8% of comets change families during the integration and most of those that change tend to remain near the Tisserand dividing line throughout. Thus, the JFCs (as defined by the Tisserand parameter) are dynamically distinct from the HFCs. We find that in our forward integration, 92% of comets are ejected from the solar system, and that ≈6% are destroyed by becoming sun-grazers. The number of sun-grazers is far more than would be expected from the existing analytic theories. The median lifetime of all known short-period comets from the current time to ultimate destruction or ejection is approximately 4.5 × 105 years. The very flat inclination distribution of Jupiter-family comets is found to become more distended as it ages. Since JFCs are dynamically distinct from HFCs, they must have an inclination distribution, when they first become visible, that is even flatter than that currently observed. For reasonable values of the physical lifetime before fading, we calculate that there should be roughly 5-20 times as many extinct JFCs as currently known JFCs. Our prediction for the mean cos (i) of the extinct JFCs is consistent with the existing data on these objects.
Neoadjuvant Treatment Versus Upfront Surgery in Resectable Pancreatic Cancer: A Cost-Effectiveness Analysis

PURPOSE: Pancreatic cancer (PC) has an overall 5-year survival rate of 10%. The use of neoadjuvant chemoradiation is debated in resectable disease. The purpose of this study is to evaluate the cost-effectiveness of neoadjuvant chemoradiation followed by pancreaticoduodenectomy (NACRT) versus upfront pancreaticoduodenectomy and adjuvant chemotherapy (USR) in resectable PC. METHODS: A decision tree model was used to estimate the cost-effectiveness of NACRT versus USR. Values from the published literature populate the tree: costs from Medicare (FY2021) reimbursements, and morbidity and survival data for quality-adjusted life-years (QALYs). Patients with resectable pancreatic adenocarcinoma who qualified for resection were included. The ICER was the primary outcome. The model was validated using one-way and two‐way deterministic, as well as probabilistic sensitivity analyses. RESULTS: The base case was modeled using a 65-year-old male. NACRT yielded 1.61 QALYs at $45,483.52 USD. USR yielded 1.47 QALYs at a discount of $6,840.96 USD. The ICER was $48,130 USD, which favors NACRT. One-way sensitivity analyses upheld these results except when ≤ 21.0% of NACRT patients proceeded to surgery and when ≤ 85.4% of NACRT patients were resectable at surgery. Two-way sensitivity analyses also favored NACRT except in cases when the proportion of resected disease after NACRT decreased. NACRT was favored in 94.3% of 100,000 random-sampling simulations. CONCLUSION: It is more cost-effective to administer NACRT before surgery for patients with resectable PC. On the basis of sensitivity analyses, USR with adjuvant therapy is only favored if rates of resection and eligibility for resection after NACRT decrease. NACRT should be considered in all patients unless there is an absolute contraindication.
Spectral Simulations of Electromagnetic Wave Scattering

This paper present a multidomain pseudospectral method for accurately solving Maxwell's equations in the time domain. The scheme is developed for computing scattering by two-dimensional smooth perfectly conducting objects like circular or elliptic cylinders in free space and utilizes a Fourier collocation method in the azimuthal direction and a multidomain Chebyshev collocation method in the radial direction. Proper absorbing boundary conditions are discussed and a new perfectly matched layer (PML) method in polar coordinates is constructed and shown to be superior to other PML methods. For the elliptic cylinders we propose to use a matched layer in connection with the multidomain approach and a cubic grid mapping. Numerical results of monochromatic electromagnetic scattering by circular and elliptic perfectly electrically conducting cylinders are presented. Comparisons between results obtained using the multidomain pseudospectral method and the finite-difference time domain method clearly illustrate the superiority of spectral methods in obtaining accurate values for the scattered fields and the bistatic radar cross section.
Real-time visualization of retinal microcirculation by laser flowgraphy

A new real-time measuring system is developed to visualize the blood flow map of the human retina using dynamic laser speckle effects and a hardware logic circuit. The retina is illuminated with a diode laser spot through a retinal camera, and the speckle field at the image plane of the spot is scanned by an area sensor. The output signal is analog-to-digital (AID) converted and the blur rate of the intensity at each pixel point is evaluated through a hardware logic circuit specially devel- oped for this system. The results are displayed in 2-D color maps suc- cessively at a rate of 16 frames/s, which allows the real-time observation of retinal blood flow.
Bulletin of Electrical Engineering and Informatics

Received Jun 26, 2022 Revised Jul 14, 2022 Accepted Aug 19, 2022 In the last decade, healthcare systems have played an effective role in improving medical services by monitoring and diagnosing patients' health remotely. These systems, either in hospitals or in other health centers, have experienced significant growth with emerging technologies. They are becoming of great interest to many countries worldwide nowadays. Portable healthcare monitoring systems (HMS) depend on internet of things (IoT) technology due to its effectiveness and reliability in several sectors, as well as in the sector of telemedicine. This paper proposes a portable healthcare system in an IoT environment controllable via a smartphone application that aims to facilitate utilization. This proposed system can track physiological indicators of a patient's body as well as the environmental conditions where the patient lives in real-time and auto-manage databases. Moreover, this paper touched on a comparison between three servers, concerning data transfer speeds from the proposed system into the servers.
Leveraging Mobile Technology for Public Health Promotion: A Multidisciplinary Perspective.

Health behaviors are inextricably linked to health and well-being, yet issues such as physical inactivity and insufficient sleep remain significant global public health problems. Mobile technology-and the unprecedented scope and quantity of data it generates-has a promising but largely untapped potential to promote health behaviors at the individual and population levels. This perspective article provides multidisciplinary recommendations on the design and use of mobile technology, and the concomitant wealth of data, to promote behaviors that support overall health. Using physical activity as an exemplar health behavior, we review emerging strategies for health behavior change interventions. We describe progress on personalizing interventions to an individual and their social, cultural, and built environments, as well as on evaluating relationships between mobile technology data and health to establish evidence-based guidelines. In reviewing these strategies and highlighting directions for future research, we advance the use of theory-based, personalized, and human-centered approaches in promoting health behaviors. Expected final online publication date for the Annual Review of Public Health, Volume 44 is April 2023. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Effect of Loblolly Pine (Pinus taeda L.) Hemicellulose Structure on the Properties of Hemicellulose-Polyvinyl Alcohol Composite Film

Hemicellulose is the second most abundant natural polysaccharide and a promising feedstock for biomaterial synthesis. In the present study, the hemicellulose of loblolly pine was obtained by the alkali extraction-graded ethanol precipitation technique, and the hemicellulose-polyvinyl alcohol (hemicellulose-PVA) composite film was prepared by film casting from water. Results showed that hemicellulose with a low degree of substitution is prone to self-aggregation during film formation, while hemicellulose with high branching has better compatibility with PVA and is easier to form a homogeneous composite film. In addition, the higher molecular weight of hemicellulose facilitates the preparation of hemicellulose-PVA composite film with better mechanical properties. More residual lignin in hemicellulose results in the better UV shielding ability of the composite film. This study provides essential support for the efficient and rational utilization of hemicellulose.