Miracle-dz/UniFAR-FTUs huggingface dataset:
Standardized evaluation of camera-based driver state monitoring systems

Driver state sensing technologies, such as vehicular systems, start to be widely considered by automotive manufacturers. To reduce the cost and minimize the intrusiveness towards driving, the majority of these systems rely on the in-cabin camera ( s ) and other optical sensors. With their great capabilities in detecting and intervening of driver distraction and inattention, these technologies may become key components in future vehicle safety and control systems. However, to the best of our knowledge, currently, there is no common standard available to objectively compare the performance of these technologies. Thus, it is imperative to develop one standardized process for evaluation purposes. In this paper, we propose one systematic and standardized evaluation process after successfully addressing three difficulties: 1) defining and selecting the important influential individual and environmental factors, 2) countering the effects of individual differences and randomness in driver behaviors, and 3) building a reliable in-vehicle driver head motion tracking tool to collect ground-truth motion data. We have collected data on a large scale on a commercial driver state-sensing platform. For each subject, 30 to 40 minutes of head motion data was collected and included variables, such as lighting conditions, head / face features, and camera locations. The collected data was analyzed based on a proposed performance measure. The results show that the developed process can efficiently evaluate an individual camera-based driver state sensing product, which builds a common base for comparing the performance of different systems.
Two‐Dimensional Spectra of Radar Returns from Sea: 1. Theoretical and Numerical Study of the Group Line

The work presented here aims at interpreting the pattern observed at low frequencies in wavenumber-frequency (k,) representations (dispersion diagrams) of radar returns from sea surface. This pattern is sometimes referred to as the "group line" in the literature and is supposed to result from the nonlinear behavior of the signal with respect to surface profile. To confirm this assumption, we have calculated the patterns generated by various nonlinear terms of second order in sea surface height. It is shown that the resolution in frequency of most data is not sufficient to allow for an accurate representation of the group line through an FFT. A methodology is proposed to define an average slope of the group line, which can be interpreted in terms of velocity.
Tropical cyclone—Induced heavy rainfall and flow in Colima, Western Mexico

Tropical cyclone (TC) landfall is often accompanied by storm surges, strong winds, and heavy rain that cause destructive flash floods, especially in mountainous regions. However, there is limited understanding of the contribution of TCs to major flood events, especially in Western Mexico. In this study, we assess the contribution of TCs to the annual rainfall, extreme rainfall and stream flow in the mountainous region of Colima, one of the most TC‐exposed areas in Western Mexico. The top 1% of daily rainfall and stream flow, annual maximum rainfall and the highest 20 stream flow events from 1970 to 2015 are examined for their association to TCs. Results indicate that the relative contribution of TCs to the average annual rainfall can exceed 25% in the coastal area of Colima. Over 25–35% of heavy daily rainfall (top 1% rainfall) recorded in the coastal rain gauges is found to be associated with TCs. In terms of high flow, approximately 20–24% of the top 1% flow events and 28–35% (~7 events) of the top 20 flow events are driven by TCs. The heaviest precipitation and high flow events occur typically in the late TC season (September and October). Our results provide insights on the role of TCs in inducing rainfall and stream flow relevant for water and flood risk management.
QRS Complex Detection Based on Smoothed Nonlinear Energy Operator

In this work, we present a novel algorithm for QRS complex detection in the Electrocardiogram (ECG) signal. The proposed algorithm is based on a combination of an Infinite Impulse Response (IIR) Filter, a Nonlinear transform termed Smoothed Nonlinear Energy Operator (SNEO) and an efficient simple thresholding process. In our scheme, ButterWorth filter is used to enhance the raw ECG signal and the SNEO is applied to accentuate the QRS complex features. The simulation tests and experimental results carried out on the MIT-BIH Arrhythmia Database show that our proposed approach gives a higher detection performances in comparison with some recently developed techniques with an average Sensitivity (Se) of 99.70%, average Positive Predictivity (P+) of 99.78% and a Detection Error Rate (DER) of 0.52%.
From the Ground Up: Herbaceous Community Diversity and Management in Coffee Agroforestry Systems

The herbaceous community (HC) is an understudied yet critical aspect of tropical agroecosystems. I measured the diversity and perceptions of the HC within organic coffee systems in the Central Valley of Costa Rica. The HC was taxonomically and functionally diverse; comprised of 39 species from 20 taxonomic groups. Farms below the regional mean size and those with canopy openness of 20-30% had higher HC functional diversity. Farmers perceived tall species with low SLA and LNC, but high height and LDMC to be undesirable, due to slow decomposition rates and management limitations. Farmers’ cognitive map complexity was positively related to HC functional richness, and negatively related to functional evenness and functional dissimilarity. All farmers placed higher emphasis on soil health and organic matter than coffee yield, which may be indicative of their role as land stewards. Workshops are needed to disseminate HC management information to optimize labour and ecosystem
Analyzing the recency effects on long series audit information and its mitigation methods with group discussions

This study aims to examine the recency effect that occurs due to the effect of sequences on long series audit information and test the effectiveness of group discussion to improve the decision quality. The recency effect is a tendency to give more weight to the latest information compared to other information received. Therefore, it is necessary to provide a method for mitigating the recency effect by using group discussion. This study used a 2x2x2 experimental design for a subject with 81 participants from accounting students. The results show that the individual decision quality that experienced the recency effect due to positive-negative and negative-positive sequential information after group discussion became better than before group discussion. The individual decision quality that experienced the recency effect due to positive-negative simultaneous information could not be mitigated by group discussion. Group discussion is an effective method for overcoming the recency effect on sequential information rather than on simultaneous information. Therefore, group discussion can be used as a strategy to reduce recency effects and improve the quality of audience decisions.
DOA Estimation Using Single or Dual Reception Channels Based on Cyclostationarity

This paper addresses the problem of direction-of-arrival (DOA) estimation for cyclostationary signals using less reception channel in comparison with the number of sensors. The system is considered to be realized by using the reception channel(s) to receive the signal reached each sensor in turn. Such simplification results in a cost reduction of the system and the effect of inconsistency among different channels are removed. However, non-synchronized sampling also makes the traditional DOA estimation algorithms ineffective. To cope with the problem, the signal models for DOA estimation using a single channel and dual channels are formulated based on signal cyclostationary, and the single channel cyclic MUSIC (SC-Cyclic-MUSIC) algorithm and the dual channels cyclic MUSIC (DC-Cyclic-MUSIC) algorithm are proposed correspondingly. This paper shows that both SC-Cyclic-MUSIC algorithm and DC-Cyclic-MUSIC algorithm work well when the switching interval is known, and a satisfied performance can also be obtained by DC-Cyclic-MUSIC algorithm when the uncertainty of the switching interval exists. Moreover, the proposed estimators are suitable for both narrow-band and wide-band signals. The computer simulations are provided to verify the effectiveness of the proposed algorithms.
Control Topology of Hybrid Energy Storage System for AC-DC Microgrid

The increasing demand for ac and dc loads has emphasized the need for effective control and energy management scheme of a hybrid AC-DC microgrid. The control of Hybrid Energy Storage System (HESS) maintains a constant DC bus voltage with required power sharing among different sources and loads. The ac/dc microgrid comprises of a PV array, Battery storage system, supercapacitors and VSC (Voltage Source Converter) feeding DC and AC loads. The supercapacitor having high power density responds to the transients due to a sudden change in load or source power. The aim of the paper is to purge the switching of control to incur minimal transients in the microgrid. The system is simulated in MATLAB/SIMULINK and its control hardware implementation is carried out on an FPGA based NI LabView PXI with SbRio interface to obtain the experimental results validating the proposed hybrid energy management control scheme.
RBF-SVM Based Resource Allocation Scheme for 5G CRAN Networks

Cloud Radio Access Network (CRAN) is one of the possible solutions to provide high data rates for next generation users (fifth generation). Additionally, CRAN also reduces the operational (OPEX) and capital (CAPX) cost. In the current cellular system (up to fourth generation), resource allocation is allocated by base station (BS) based on channel state information (CSI). This increases the overhead as well as operational and capital cost. Therefore, in this paper, a CRAN based resource allocation scheme for fifth generation (5G) network is presented. The proposed scheme consider the user position in spite of CSI. The proposed resource allocation scheme applies machine learning technique. Specifically, radio basil function-support vector machine (RBF-SVM) machine learning technique is applied for allocating the resource block. The Numerical result shows that proposed scheme gives the significant result over the random forest based resource allocation scheme and other machine learning based resource allocation scheme.
A Buck-Boost Common-Mode Transformerless Inverter for Photovoltaic Applications

This paper proposes a novel common mode transformerless grid feeding topology with buck and boost operation from dc-link. This enables wide maximum power point tracking capability and yields higher energy. The novelty lies in coupling two switch buck-boost converter with four switch inverter such that a constant voltage is seen by parasitic capacitances of photovoltaic array. Furthermore, this connection is achieved in such a way that the operations of dcdc converter and inverter are not disrupted. This connection leads to very low earth leakage current and compliance with international standards. Since the front end converter seen by grid side is a conventional four switch inverter, the structure offers high conversion efficiency and ability to perform various grid support functions such as voltage ride through and reactive power support etc. The use of proven converter topologies makes the idea viable and intuitive. A proportional resonant controller is used for average current control, leading to reduced dc-link capacitance requirement for front end inverter. The working of structure is validated with help of simulations in MATLAB/Simulink software environment and the results are provided. Efficiency of the proposed topology is also estimated to show that it offers high efficiency over wide variation in voltage of photovoltaic array.
School Students’ Intrinsic Motivation for Learning Science in RRI Activity: the Influence of Perceived Competence and Relatedness

The article deals with the influences of perceived competence and relatedness on school students‘ intrinsic motivation for learning science (IMLS) in responsible research and innovation (RRI) activity. RRI activity in the science classroom discloses the positive and negative impact of research and innovation discoveries for the society. The evaluation of the negative and positive sides of the research and innovation involves school students in discussion and gives a possibility to feel competent and related with others. 5E model is used in this research. It encompasses formal and informal science education. The purpose of the study is to explore the influence of perceived competence and relatedness on school students‘ intrinsic motivation for learning science in RRI activity. The data presented in the current study are a part of the 7BP ENGAGE project, implemented in Lithuania (2014-2017). The participants chosen for this study were 8th-10th grade school students from different schools of Lithuania. Multiple regression analysis was used to test if the two basic psychological needs (perceived competence and relatedness) significantly predicted students' intrinsic motivation for learning science. Our research revealed that school students‘ motivation for learning science was simultaneously influenced by perceived competence and relatedness in RRI activity. We established a statistically significant relation between the students‘ motivation for learning science and their perceived competence and relatedness. Perceived competence influenced the school students‘ motivation for learning science more than perceived relatedness in RRI.
Sacralization and Herniated Nucleus Pulposus -An Association Study

Introduction: Herniated nucleus pulposus (HNP) can be best diagnosed clinically by history followed by physical examinations suggested by Mckenzie and Cyriax as well as radiologically by MRI. Sacralization, which is mostly congenital in origin in later life, gives rise to altered biomechanics. It is thought to be a leading cause of low back pain and HNP. There is controversy in the literature whether sacralization is associated with HNP or not. So the present study intended to find out whether sacralization is associated with HNP. Methodology: A total no of 150 subjects with LBP with or without radiation to lower limb were taken in the study. MRI report from each subject was studied. Subjects were diagnosed as HNP when they fulfill the clinical criteria as well as the MRI suggesting HNP. Sacralization was diagnosed by using lumbo-sacral A-P radiograph and various types of sacralization were noted. Pain was measured by using VAS, A-P diameter of spinal canal is noted from MRI and disability status was measured using ODI and WHODAS-2 (12 items). Results: Result of the study showed that 71.42% sacralized subjects have HNP and sacralized subjects are 5.92 times risk for HNP, the relative risk factor for HNP in type 2 a and 1b is highest i.e., 9.44 each , next to it is type – 4 i.e., 7.08. The prevalence of LSTV was found to be 44% which includes sacralization (42%) and lumbarisation (2%). It has been found that incidence of sacralization in HNP group also found to be more i.e., 64.28 %. Besides this, it has also been found that sacralized subjects suffer from more disability and there is a weak correlation between SLR and disability. However, sacralization doesn’t give rise to significant reduction of A-P diameter of spinal canal and more pain. Conclusion: Sacralization is a risk factor for HNP and out of all sacralization type – 1B and 2A risk factor is highest. It has also been found that prevalence of sacralization in the low back pain population is more, sacralized individual suffered from more disability but not more pain or any changes in A-P diameter of spinal canal. SLR is weakly correlated with disability, A-P diameter of spinal canal and pain are not correlated.
Stimulations of Thermophysical Characteristics of Nano-Diamond and Silver Nanoparticles for Nonlinear Radiative Curved Surface Flow

Thermal radiations and effective characteristics of the nanoparticles play a vibrant role in the heat transfer enhancement. This work aims to investigate the influence of thermophysical characteristics of nano-diamond (ND) and silver (Ag) nanoparticles on the heat transfer intensifications in the nonlinear radiative and dissipative flow over an arched geometry. A self-similar coupled nature of the nanofluid model is acquired via similarity transformations. Furthermore, the mathematical treatment of the model is carried out by the RK scheme. Moreover, stimuli of various pertinent flow parameters on the velocity, heat transfer, streamlines, and isotherms are examined graphically.
Cluster Validation Measures for Label Noise Filtering

Cluster validation measures are designed to find the partitioning that best fits the underlying data. In this paper, we show that these well-known and scientifically proven validation measures can also be used in a different context, i.e., for filtering mislabeled instances or class outliers prior to training in super-vised learning problems. A technique, entitled CVI-based Outlier Filtering, is proposed in which mislabeled instances are identified and eliminated from the training set, and a classification hypothesis is then built from the set of remaining instances. The proposed approach assigns each instance several cluster validation scores representing its potential of being an outlier with respect to the clustering properties the used validation measures assess. We examine CVI-based Outlier Filtering and compare it against the LOF detection method on ten data sets from the UCI data repository using five well-known learning algorithms and three different cluster validation indices. In addition, we study two approaches for filtering mislabeled instances: local and global. Our results show that for most learning algorithms and data sets, the proposed CVI-based outlier filtering algorithm outperforms the baseline method (LOF). The greatest increase in classification accuracy has been achieved by combining at least two of the used cluster validation indices and global filtering of mislabeled instances.
Evaluation of wound‑healing effect of Ziziphus mauritiana L. leaf extract in rats

Background: Ziziphus mauritiana L. leaves are used traditionally for burns, wounds, inflamed parts, hypertension and as a diuretic. Objective: To evaluate the wound‑healing property of ethanol extract of Ziziphus mauritiana L. leaf (EEZM) on rats using excision, incision and dead space wound models. Materials and Methods: Wistar albino rats (150 − 200 gm) were divided into four groups (n = 6). Group I (control) animals received no treatment, group II animals were given EEZM 300 mg/kg orally, group III animals were applied EEZM gel, 100 mg/cm2 and group IV animals were applied Framycetin skin cream, 100 mg/cm2 topically. In incision and dead space wound models, the treatment was given for 10 days only from the day of wound, skin‑breaking strength and dry granulation tissue weight were estimated in incision wound model. Hydroxyproline content was estimated in dead space wound model. In excision wound model, treatment continued till the complete healing of the wound. Rate of wound contraction and period of epithelisation was evaluated thereafter. The data was analyzed by one‑way ANOVA, followed by Dunnett’s test. P <0.05 is considered significant. Results: EEZM increased the rate of wound contraction, decreased period of epithelisation, increased skin‑breaking strength and dry granulation tissue weight, elevated hydroxyproline content. Conclusion: Ziziphus mauritiana possesses wound healing activity. Key words: Period of epithelisation, skin breaking strength, wound healing, wound contraction, Ziziphus mauritiana
A Single-Phase 5-Level Inverter Topology with Reduced Semiconductor Switches

For any switching frequency, multilevel inverters produce better harmonic profile compared to basic 2-level inverters. Among the available multilevel inverters topologies in the literature, some of the topologies like neutral point clamped (NPC) or diode clamped, flying capacitor (FC) or capacitor clamped, and H-bridge are conventionally used. However, the NPC and FC type inverter topologies comprises the capacitor voltage balancing issue, and the H-bridge requires more number of isolated DC voltage sources and semiconductor switches. To overcome the issues encountered with the conventional topologies, a new single-phase 5-level inverter topology by excluding the capacitor components and with a reduced number of semiconductor switches is proposed in this paper. A reduced number of levels is also achieved with the proposed topology under certain fault conditions.
Health Conditions, Activity Limitations, and Participation Restrictions among Older People with Visual Impairments

Data from the Second Supplement on Aging (1994) were analyzed to evaluate the presence of selected medical conditions, performance of basic and instrumental activities of daily living, and participation in life situations in two groups of visually impaired elders (persons aged 70–74 and persons aged 85 years or older) and two other groups of elders in the same age groups who are not visually impaired. Results indicated that, for both age groups, visual impairment is a significant risk factor for additional medical conditions, activity limitations, and participation restrictions.
A Brief Overview of New York City's Calorie Labeling Regulation and Evaluation

In 2008, the New York City Department of Health and Mental Hygiene (NYC DOHMH) adopted a regulation that requires chain restaurants with 15 or more locations nationwide to post calorie information prominently on menu boards and menus. This regulation is intended to help customers make informed choices at the point of purchase. To assess the impact of this calorie labeling requirement, NYC DOHMH is conducting 3 studies to examine changes in (1) customer purchasing behavior, (2) awareness about calorie posting, and (3) menu options at fast-food chains, before and after implementation of the regulation. Preliminary results suggest that posting calorie information prominently at the point of purchase can increase the number of customers who see and use that information. The city's approach to calorie labeling helps provide customers with important information to make food choices. Calorie labeling policies have gained support in jurisdictions across the nation as implementing regulations such as this one can have broad implications at the population level
CADAP: A student’s emotion monitoring solution for e-learning performance analysis

Nowadays it is widely accepted that emotions greatly influence the process of teaching and learning, however, how to recognize the emotions of students, and how to relate the various types of emotions with learning, still remains an open question. This article presents a tool that uses students’ emotions as a means to improve the learning process. The students’ emotions are obtained through a facial expression recognition tool - Cara de Aprendizagem - CADAP. With the help of this tool it is possible to establish relationships between facial expressions, emotions, teaching methodologies and student performance.