bluuebunny/crossref_metadata_2025 huggingface dataset:
Three-Parameter P-S-N Curve Fitting Based on Improved Maximum Likelihood Estimation Method
Authors: Tan Xiufeng , Li Qiang , Wang Guanqin , Xie Kai
Published: February 2023

The P-S-N curve is a vital tool for dealing with fatigue life analysis, and its fitting under the condition of small samples is always concerned. In the view that the three parameters of the P-S-N curve equation can better describe the relationship between stress and fatigue life in the middle- and long-life range, this paper proposes an improved maximum likelihood method (IMLM). The backward statistical inference method (BSIM) recently proposed has been proven to be a good solution to the two-parameter P-S-N curve fitting problem under the condition of small samples. Because of the addition of an unknown parameter, the problem exists in the search for the optimal solution to the three-parameter P-S-N curve fitting. Considering that the maximum likelihood estimation is a commonly used P-S-N curve fitting method, and the rationality of its search for the optimal solution is better than that of BSIM, a new method combining BSIM and the maximum likelihood estimation is proposed. In addition to the BSIM advantage of expanding the sample information, the IMLM also has the advantage of more reasonable optimal solution search criteria, which improves the disadvantage of BSIM in parameter search. Finally, through the simulation tests and the fatigue test, the P-S-N curve fitting was carried out by using the traditional group method (GM), BSIM, and IMLM, respectively. The results show that the IMLM has the highest fitting accuracy. A test arrangement method is proposed accordingly.
The Impact of Capital Structure on the Profitability Performance of ICT Firms
Authors: Kim Yeongjun , Jung Sungwook , Kim Changhee
Published: February 2023

Information and communication technology (ICT) companies strive for ceaseless innovation to remain competitive while facing the challenge of maximizing firm value (FV) with limited resources, and increasing the interests of shareholders. However, capital structures have a considerable effect on FV, and the literature still disagrees with the optimum structure in specific industries and countries. Therefore, this study evaluates the FV of ICT companies in terms of profitability efficiency using data envelopment analysis. In addition, this study applies a Tobit regression and Kruskal-Wallis one-way ANOVA to identify the impact of leverage, liquidity, and firm size, which are major capital structure factors influencing FV. The analysis yields three main results. First, in the ICT industry, small and medium companies tend to have better profitability efficiency than companies of other sizes. Second, only small and medium ICT manufacturing companies’ profitability efficiency is positively impacted by the current ratio. Third, only mid-sized service companies’ profitability efficiency is positively impacted by the debt-equity ratio. The results have policy and practical implications for improving the FV of ICT companies.
Efficiency of Electrochemical Methods of Purification and Control over the Oxide Concentration in Halide Melts: PbCl2
Authors: Nikolaev Andrey , Mullabaev Albert , Suzdaltsev Andrey , Zaikov Yuriy P.
Published: February 2023

The purification of molten salts from admixtures as well as the effective control of admixture concentration has attracted researchers’ interests. In the present paper, the possibility of the electrochemical purification of PbCl2 from PbO and the effective control over the oxide ions concentration in molten PbCl2 is studied at the temperature of 520 °C. The PbCl2 melt with the initial addition of 0.5 wt% of PbO was used as a molten salt sample. The method of potentiostatic electrolysis was used to remove the oxide additions from the melt; the linear and square-wave voltammetry dependencies were recorded, and the melt samples were taken for analysis. Based both on the results of the electrochemical measurements and the analysis of oxygen concentration in the electrolyte, we built linear empirical dependencies of the anode peak current of the oxidation of oxygen-containing electroactive anions on the PbO concentration in the studied melt. We demonstrated that the obtained dependencies may be used for direct electrochemical nondestructive in-situ control over the concentration of PbO dissolved in the PbCl2 melt containing up to 0.5 wt% of PbO. The deep electrochemical purification of the chloride PbCl2 melt from molten oxide (up to 0.044 wt% PbO or to 0.007 wt% of oxygen) was achieved by the potentiostatic electrolysis.
Investigation of the Fuel Shape Impact on the MTR Reactor Parameters Using the OpenMC Code
Authors: Alnahdi Alaa H. , Alghamdi Ahmed A. , Almarshad Abdullah I.
Published: February 2023

The goal of this study was to evaluate the impact of simulating different fuel shapes for the material testing reactor (MTR). Two OpenMC codes were built, and the first OpenMC model was simulated using a curved shape fuel element to mimic the real dimensions and shape of the MTR. The code core parameters were validated with the collected parameters from the experimental work and two well-known Monte Carlo simulation codes (MCNP and SCALE). The validation process included the axial flux profile and criticality. After the OpenMC curve fuel model was validated, the MTR fuel was simulated as flat fuel elements with the exact amount of fuel as in the curve fuel model. By comparing the two OpenMC models’ calculations, it was observed that the radial flux distribution has only a slight difference due to fuel mass similarity. In conclusion, simulating the MTR fuel as flat elements provided a good agreement calculation compared to the real shape, but it was also observed that this might carry some discrepancies for in-depth simulation studies.
Creep Characteristics and Creep Model of Coal Based on Pore Water Pressure
Authors: Zhang Fumin , Zhang Dongfeng , Huang Shunjie
Published: February 2023

Anthracite in a specific area of Shanxi Province is the subject of this essay’s research. In the creep studies, different porosity intervals and pore water pressures were employed to evaluate the mechanical properties of creep under various test paths. The conventional Burges model was coupled in series with the nonlinear viscous elements and plastic elements. The key parameters in the equation are fitted, and a creep model is created to describe the nonlinear viscosity-elastic-plastic characteristics of coal under the influence of pore water pressure with varying porosities. The creep tests used varied porosity intervals, pore water pressures, and test paths to study the mechanical properties of creep. The conventional Burges model was coupled in series with the nonlinear viscous element and plastic element. To represent the nonlinear viscosity-elastic-plastic properties of coal under the effect of pore water pressure with variable porosities, the main parameters in the equation are fitted, and a creep model is developed. The results show that the porosity and strength of the coal sample are negatively correlated. In comparison to coal samples with a porosity of 5–10%, the uniaxial compressive strength of coal samples with a porosity of 10–15% and 15–20% reduced by 9.6% and 22.3%. Throughout the creep process, instantaneous strain rises with porosity, and changes in pore water pressure and porosity have an effect on instantaneous creep under low-stress loading, resulting in different creep curve starting strain values. The duration from stress loading to the accelerated creep stage in the failure stage and the time from the deceleration creep stage to the accelerated creep stage are both gradually shortened with an increase in porosity and pore water pressure. For regression analysis and parameter identification, a creep constitutive model was developed to describe the creep characteristics of coal samples with varying porosity under varying pore water pressure. The creep parameters of the new constitutive model were obtained, and they could very well reflect the creep characteristics of specimens with varying porosity intervals under the influence of pore water pressure.
Application of Parametric Design in the Optimization of Traditional Landscape Architecture
Authors: Han Yue , Zhang Kejia , Xu Yanyan , Wang Hao , Chai Tianlong
Published: February 2023

Parametric design, with its unique scientific and logical nature, is gradually applied in the field of landscape design. Therefore, the GIS (geographic information systems) technology of parametric software was applied to the optimization of traditional landscape architecture, and its practical application quality was discussed. The actual analysis results showed that the evaluation result of parametric design had the highest score of 7.71 in behavioral perception. The overall score was 7.28, showing a high scientific nature. In the evaluation of landscape environmental benefits, after the optimization of landscape greening by parametric design, the air cleanliness and living comfort were generally improved, compared with those before optimization, and the highest values were 11.97 ± 6.01 and 5.86 ± 2.11 respectively. In the evaluation of the economic benefits of gardens, the economic income of gardens in the past 8 years generally increased, reaching the highest of 3.5795 billion yuan, with a growth rate of 78.92%. At the same time, the return on investment reached 26.17%, far exceeding the expected 20%. Among the social benefits, the weight of increasing employment opportunities was the largest at 0.36. In summary, parameterized optimization of traditional landscape design can effectively improve its social, environmental, and economic benefits and has good practical value.
Progress of Reactions between Furfural and Aliphatic Alcohols via Catalytic Oxidation Processes: Reaction Routes, Catalysts, and Perspectives
Authors: Tian Junying , Cheng Xiaowei , Fan Yingying , Fang Weiguo , Dong Peng , Li Guixian , Guo Yongle
Published: February 2023

Furfural is one of the most important biomass platform compounds and can be used to prepare various high-value-added chemicals. The reactions of furfural with aliphatic alcohols via an oxidative esterification reaction or oxidative condensation reaction can bond two carbon molecules together and produce longer hydrocarbon chains chemicals, including methylfuroate and some low-volatility liquid biomass fuels. Thus, these reactions are considered significant utilization routes of furfural, and many inspiring catalytic systems have been designed to promoted these reactions. In this work, the reported catalytic systems for the oxidative esterification and oxidative condensation reactions are reviewed separately. The catalysts for the oxidative esterification reaction are reviewed for the classification of noble metal catalysts and non-noble metal catalysts, according to the active metals in the catalysts. For the oxidative condensation reactions, the studies using oxygen as the oxidant are reviewed firstly, and then the studies conducted using the hydrogen transfer process are analyzed subsequently. Furthermore, suggestions for future research directions for the oxidative esterification and oxidative condensation reactions are put forward.
Evanescent-Field Excited Surface Plasmon-Enhanced U-Bent Fiber Probes Coated with Au and ZnO Nanoparticles for Humidity Detection
Authors: Afsharipour Elnaz , Malviya Kirtiman Deo , Montazeri Mohammadreza , Mortazy Ebrahim , Soltanzadeh Ramin , Hassani Alireza , Rosei Federico , Chaker Mohamed
Published: February 2023

We report the design, fabrication, and testing of a humidity sensor based on an optical fiber-based evanescent wave probe. The fiber was bent into a U-shape and de-cladded at the location of the bending. The de-cladded section was coated either with Au or with ZnO nanoparticles. Humidity is detected based on the interaction in the surface plasmon resonance of the Au/ZnO nanoparticles excited by an evanescent wave of light passing through the optical fiber. The response of the U-bent fibers to humidity was investigated using a specifically designed low-voltage portable interrogation box. We found that the fibers coated with ZnO nanoparticles were able to detect a minimum 0.1% change in humidity with an average sensitivity of 143 µV/%RH and 95% linearity over the 10% to 80% humidity range. In comparison, samples coated with Au and Au + ZnO nanoparticles demonstrated a minimum change detection of 0.3% RH and 2% RH respectively. The response and recovery time of the sensor were measured to be 3 s and 4 s, respectively, for a 60% change in humidity from 20% to 80%. The entire measurement system was operated by consuming an electrical power of 1.62 W at an input voltage of 12 Vdc.
A Review on the Impact of Cannabis in Society and the Analytical Methodologies for Cannabinoids
Authors: Vergne Matthew J. , Reynolds Lindsey , Brown Alexus , Pullias Grayson , Froemming Anna
Published: February 2023

The use of plant-based medicine dates back centuries, and cannabis (Cannabis sativa) is one such plant that has been used medicinally and illicitly. Although cannabis contains hundreds of cannabinoids and other natural products, its potential medicinal use was largely ignored by modern researchers due to the legal restrictions and heavy regulations introduced in the 1930s. As restrictions on cannabis access have eased since the 1990s there is renewed interest in the research of cannabinoids and the other components in the cannabis plant. The focus of this review article is an overview of cannabis and the analytical challenges in the quality control and biological analysis. The pharmacological effects of psychoactive cannabinoids, delta-9-tetrahydrocannabinol (Δ9-THC) and delta-8-trans- tetrahydrocannabinol (Δ8-THC) is discussed, along with an abundant non-intoxicating cannabinoid, cannabidiol (CBD). The analytical methods for the quality control assays of cannabis products include gas chromatography and liquid chromatography coupled to different detectors, including mass spectrometry. This review will highlight various analytical methods for the quality control of cannabis products and the quantitation of cannabinoids in biological matrices for forensics and toxicology.
Exploratory Bibliometrics: Using VOSviewer as a Preliminary Research Tool
Authors: Kirby Andrew
Published: February 2023

This paper explores ways in which open access bibliometric software can be used to undertake exploratory research and to generate new avenues of inquiry. It takes as its focus VOSviewer, a freely available software package used to construct and display bibliometric relationships between a variety of variables. Beginning with published examples, the paper proceeds to create an original case study using bibliometrics to explore the extent to which the field of remote sensing is contributing to the implementation of sustainable development goals. This example uses Scopus data and VOSviewer to examine and contrast co-occurrence data among publications in six journals, and it demonstrates how such software can be successfully used to undertake preliminary studies and to shape subsequent research which employs more formal approaches.
Sexual Morality of Young Poles as a Challenge for Religious Education
Authors: Przygoda Wiesław , Święs Kazimierz , Rozpędowski Piotr
Published: February 2023

As indicated by numerous sociological reports, the morality of young people is currently undergoing dynamic changes, and this applies especially to morality in the sphere of sexuality. The purpose of this article is to analyze the opinions on sexual morality expressed by young Poles. The results of this analysis can help to develop a better program for their religious education. The analyses are based on the results of social quantitative surveys conducted in 2020 on a random sample of 410 high school seniors (age 18–20) residing in cities of various sizes and in rural areas. The research verified the following leading hypothesis: “The morality of young Poles regarding sexual activity is becoming increasingly autonomous and is formed independently of the morality model that is offered by leading educational institutions, particularly family, Church, and school”. The detailed hypotheses were only partially confirmed. The empirical material presented in the article confirms that the moral education of youth in the sphere of human sexuality currently being implemented in Poland is inefficient and requires changes to several pastoral postulates. First of all, young people must not be treated as passive recipients of pastoral programs or strategies. They want to be the creators of the social, cultural, and religious changes taking place. Reaching the hearts of young people with the message of the Gospel requires immersing oneself in their life experience, perceptions, and understanding of reality, as well as their highly individualized axiology and complex decision-making processes. Young people should be set moral requirements also in the sphere of sexuality, as this is necessary for their personal development and the preparation of the foundations for a good life as an adult; however, this must be done with perceptible love and from the position of a witness of a positive and happy life.
Translative Trends in Three Modern Greek Renderings of the Daodejing
Authors: Amarantidou Dimitra
Published: February 2023

Many Chinese and Western scholars have looked into the relation between Daoist and Greek thought, implementing Greek philosophical vocabularies to explain or highlight the distinctness of Daoist terms. This paper offers a view of an alternative and unexplored area of such endeavors: the translation of Daoist philosophy in modern Greek. More specifically, I offer an account of the reception and interpretation of the text by looking at three renderings of the Daodejing 道德經 (or Laozi 老子) in modern Greek. I first summarize the translators’ methodologies, overall understanding of the Daodejing’s focus and current relevance, and views on authorship and translation, and identify a set of translative trends: reliance on familiar notions, frameworks, and cultural experiences; mystification; attention to poeticity; and emphasis on a perceived remedial function of the text for a modern Greek readership. I then look at the renderings and explications of the key notions dao 道 and de 德 in four passages as case studies. The final section sums up the findings and concludes that the dominant interpretive tendency and translative trend in the examined translations is the assumption of similarity between Daoist and more familiar beliefs and frameworks.
Assessing Snow Water Retrievals over Ocean from Coincident Spaceborne Radar Measurements
Authors: Yin Mengtao , Yuan Cheng
Published: February 2023

Spaceborne snow water retrievals over oceans are assessed using a multiyear coincident dataset of CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Mission (GPM) Dual-frequency Precipitation Radar (DPR). Various factors contributing to differences in snow water retrievals between CPR and DPR are carefully considered. A set of relationships between radar reflectivity (Ze) and snow water content (SWC) at Ku- and W-bands is developed using the same microphysical assumptions. It is found that surface snow water contents from CPR are much larger than those from DPR at latitudes above 60°, while surface snow water contents from DPR slightly exceed those from CPR at latitudes below 50°. Coincident snow water content profiles between CPR and DPR are further divided into two conditions. One is that only CPR detects the falling snow. Another is that both CPR and DPR detect the falling snow. The results indicate that about 88% of all snow water content profiles are under the first condition and usually associated with light snowfall events. The remaining snow water content profiles are generally associated with moderate and heavy snowfall events. Moreover, CPR surface snow water contents are larger than DPR ones at high latitudes because most light snowfall events are misdetected by DPR due to its low sensitivity. DPR surface snow water contents exceed CPR ones at low latitudes because CPR may experience a significant reduction in backscattering efficiency of large particles and attenuation in heavy snowfall events. The low sensitivity of DPR also causes a noticeable decrease in detected snow layer depth. The results presented here can help in developing global snowfall retrieval algorithms using multi-radars.
Mapping Cropland Abandonment in Mountainous Areas in China Using the Google Earth Engine Platform
Authors: Xu Suchen , Xiao Wu , Yu Chen , Chen Hang , Tan Yongzhong
Published: February 2023

Knowledge about the spatial-temporal pattern of cropland abandonment is the premise for the management of abandoned croplands. Traditional mapping approaches of abandoned croplands usually utilize a multi-date classification-based land cover change trajectory. It requires quality training samples for land cover classification at each epoch, which is challenging in regions of smallholder agriculture in the absence of high-resolution imagery. Facing these challenges, a theoretical model is proposed to recognize abandoned croplands based on post-abandonment secondary succession. It applies the continuous change detection and classification (CCDC) temporal segmentation algorithm to Landsat time series (1986~2021) to obtain disjoint segments, representing croplands’ status. The post-abandonment secondary succession showing a greening trend is recognized using NDVI-based harmonic analysis, so as to capture its preceding abandonment. This algorithm is applied to a mountainous area in southwest China, where cropland abandonments are widespread. Validation based on stratified random samples referenced by a vegetation index time series and satellite images shows that the detected abandoned croplands have user accuracy, producer accuracy and an F1 score ranging from 43% to 71%, with variation among abandonment year. The study area has a potential cropland extent of 22,294 km2, within which 9252 km2 of the cropland was abandoned. The three peak years of abandonment were 1994, 2000, and 2011. The algorithm is suitable to be applied to large-scale mapping due to its automatic manner.
SAM-HIT: A Simulated Annealing Multispectral to Hyperspectral Imagery Data Transformation
Authors: Mohamed Ali , Emam Ashraf , Zoheir Basem
Published: February 2023

Space-borne hyperspectral imagery data are known for their high spectral resolution in a number of narrow wavelength intervals, which makes these data useful for mineral mapping. However, the available free-of-charge hyperspectral scenes cover only narrow and scattered geographic areas. In contrast, multispectral imagery scenes have a nearly complete spatial coverage and wider wavelength intervals. The low spectral resolution of the multispectral data, however, limits their efficiency in the mineral mapping of small geological massifs or hydrothermal alteration halos. The present contribution presents a new transformation tool (SAM-HIT) to simulate the hyperspectral sensor responses in unscanned areas based on partially overlapping hyperspectral and multispectral scenes. Simulation or prediction of the pseudohyperspectral data is here accomplished by using the simulated annealing linear optimization algorithm, which allows the lowest possible mismatch between the original and predicted data. The high visual and numerical correlation of the resultant data confirms the reliability of the newly adopted transformation. Further, the application of the SAM-HIT to a well-exposed part of the Egyptian basement complex with available hyperspectral data showed high concordance and nearly identical band signatures, opening a new outlook for mineral exploration in vast areas by a nearly automated cost-free means.
Remote Interference Discrimination Testbed Employing AI Ensemble Algorithms for 6G TDD Networks
Authors: Zhang Hanzhong , Zhou Ting , Xu Tianheng , Hu Honglin
Published: February 2023

The Internet-of-Things (IoT) massive access is a significant scenario for sixth-generation (6G) communications. However, low-power IoT devices easily suffer from remote interference caused by the atmospheric duct under the 6G time-division duplex (TDD) mode. It causes distant downlink wireless signals to propagate beyond the designed protection distance and interfere with local uplink signals, leading to a large outage probability. In this paper, a remote interference discrimination testbed is originally proposed to detect interference, which supports the comparison of different types of algorithms on the testbed. Specifically, 5,520,000 TDD network-side data collected by real sensors are used to validate the interference discrimination capabilities of nine promising AI algorithms. Moreover, a consistent comparison of the testbed shows that the ensemble algorithm achieves an average accuracy of 12% higher than the single model algorithm.
Physiological Synchrony Predict Task Performance and Negative Emotional State during a Three-Member Collaborative Task
Authors: Algumaei Mohammed , Hettiarachchi Imali , Veerabhadrappa Rakesh , Bhatti Asim
Published: February 2023

Evaluation of team performance in naturalistic contexts has gained popularity during the last two decades. Among other human factors, physiological synchrony has been adopted to investigate team performance and emotional state when engaged in collaborative team tasks. A variety of methods have been reported to quantify physiological synchrony with a varying degree of correlation with the collaborative team task performance and emotional state, reflected in the inconclusive nature of findings. Little is known about the effect of the choice of synchrony calculation methods and the level of analysis on these findings. In this research work, we investigate the relationship between outcomes of different methods to quantify physiological synchrony, emotional state, and team performance of three-member teams performing a collaborative team task. The proposed research work employs dyadic-level linear (cross-correlation) and team-level non-linear (multidimensional recurrence quantification analysis) synchrony calculation measures to quantify task performance and the emotional state of the team. Our investigation indicates that the physiological synchrony estimated using multidimensional recurrence quantification analysis revealed a significant negative relationship between the subjectively reported frustration levels and overall task performance. However, no relationship was found between cross-correlation-based physiological synchrony and task performance. The proposed research highlights that the method of choice for physiological synchrony calculation has direct impact on the derived relationship of team task performance and emotional states.
A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson
Authors: Kota Venkata Deepa , Sharma Himanshu , Albert Mark V. , Mahbub Ifana , Mehta Gayatri , Namuduri Kamesh
Published: February 2023

The survival rate for sudden cardiac arrest (SCA) is low, and patients with long-term risks of SCA are not adequately alerted. Understanding SCA’s characteristics will be key to developing preventive strategies. Many lives could be saved if SCA’s early onset could be detected or predicted. Monitoring heart signals continuously is essential for diagnosing sporadic cardiac dysfunction. An electrocardiogram (ECG) can be used to continuously monitor heart function without having to go to the hospital. A zeolite-based dry electrode can provide safe on-skin ECG acquisition while the subject is out-of-hospital and facilitate long-term monitoring. To the ECG signal, a low-power 1 μW read-out circuit was designed and implemented in our prior work. However, having long-term ECG monitoring outside the hospital, i.e., high battery life, and low power consumption while transmission and reception of ECG signal are crucial. This paper proposes a prototype with a 10-bit resolution ADC and nRF24L01 transceivers placed 5 m apart. The system uses the 2.4 GHz worldwide ISM frequency band with GFSK modulation to wirelessly transmit digitized ECG bits at 250 kbps data rate to a physician’s computer (or similar) for continuous monitoring of ECG signals; the power consumption is only 11.2 mW and 4.62 mW during transmission and reception, respectively, with a low bit error rate of ≤0.1%. Additionally, a subject-wise cross-validated, three-fold, optimized convolutional neural network (CNN) model using the Physionet-SCA dataset was implemented on NVIDIA Jetson to identify the irregular heartbeats yielding an accuracy of 89% with a run time of 5.31 s. Normal beat classification has an F1 score of 0.94 and a ROC score of 0.886. Thus, this paper integrates the ECG acquisition and processing unit with low-power wireless transmission and CNN model to detect irregular heartbeats.
NITS-IQA Database: A New Image Quality Assessment Database
Authors: Ruikar Jayesh , Chaudhury Saurabh
Published: February 2023

This paper describes a newly-created image database termed as the NITS-IQA database for image quality assessment (IQA). In spite of recently developed IQA databases, which contain a collection of a huge number of images and type of distortions, there is still a lack of new distortion and use of real natural images taken by the camera. The NITS-IQA database contains total 414 images, including 405 distorted images (nine types of distortion with five levels in each of the distortion type) and nine original images. In this paper, a detailed step by step description of the database development along with the procedure of the subjective test experiment is explained. The subjective test experiment is carried out in order to obtain the individual opinion score of the quality of the images presented before them. The mean opinion score (MOS) is obtained from the individual opinion score. In this paper, the Pearson, Spearman and Kendall rank correlation between a state-of-the-art IQA technique and the MOS are analyzed and presented.
Integrating Sparse Learning-Based Feature Detectors into Simultaneous Localization and Mapping—A Benchmark Study
Authors: Mollica Giuseppe , Legittimo Marco , Dionigi Alberto , Costante Gabriele , Valigi Paolo
Published: February 2023

Simultaneous localization and mapping (SLAM) is one of the cornerstones of autonomous navigation systems in robotics and the automotive industry. Visual SLAM (V-SLAM), which relies on image features, such as keypoints and descriptors to estimate the pose transformation between consecutive frames, is a highly efficient and effective approach for gathering environmental information. With the rise of representation learning, feature detectors based on deep neural networks (DNNs) have emerged as an alternative to handcrafted solutions. This work examines the integration of sparse learned features into a state-of-the-art SLAM framework and benchmarks handcrafted and learning-based approaches by comparing the two methods through in-depth experiments. Specifically, we replace the ORB detector and BRIEF descriptor of the ORBSLAM3 pipeline with those provided by Superpoint, a DNN model that jointly computes keypoints and descriptors. Experiments on three publicly available datasets from different application domains were conducted to evaluate the pose estimation performance and resource usage of both solutions.
Sustainable Health-Related Quality of Life in Older Adults as Supported by the vINCI Technology
Authors: Dobre Ciprian , Băjenaru Lidia , Drăghici Rozeta , Prada Gabriel-Ioan , Balog Alexandru , Herghelegiu Anna Marie
Published: February 2023

The vINCI technology represents an innovative instrument developed specifically but not exclusively for older adults by technology researchers together with a medical team specialized in geriatrics and gerontology. It was designed to be independently and effortlessly used by older adults in the comfort and safety of their own environment. It is a modular and flexible platform that can integrate a large array of various sensors and can easily adapt to specific healthcare needs. The pilot study tested sensors and standardized instruments capable of evaluating several care-related parameters and of generating personalized feedback for the user dedicated to optimizing physical activity level, social interaction, and health-related quality of life. Moreover, the system was able to detect and signal events and health-related aspects that would require medical assistance. This paper presents how the innovative vINCI technology improves quality of life in older adults. This is evidenced by the results obtained following the clinical validation of the vINCI technology by older adults admitted to the Ana Aslan National Institute of Gerontology and Geriatrics (NIGG) in Bucharest.
Continuous Prediction of Web User Visual Attention on Short Span Windows Based on Gaze Data Analytics
Authors: Diaz-Guerra Francisco , Jimenez-Molina Angel
Published: February 2023

Understanding users’ visual attention on websites is paramount to enhance the browsing experience, such as providing emergent information or dynamically adapting Web interfaces. Existing approaches to accomplish these challenges are generally based on the computation of salience maps of static Web interfaces, while websites increasingly become more dynamic and interactive. This paper proposes a method and provides a proof-of-concept to predict user’s visual attention on specific regions of a website with dynamic components. This method predicts the regions of a user’s visual attention without requiring a constant recording of the current layout of the website, but rather by knowing the structure it presented in a past period. To address this challenge, the concept of visit intention is introduced in this paper, defined as the probability that a user, while browsing, will fixate their gaze on a specific region of the website in the next period. Our approach uses the gaze patterns of a population that browsed a specific website, captured via an eye-tracker device, to aid personalized prediction models built with individual visual kinetics features. We show experimentally that it is possible to conduct such a prediction through multilabel classification models using a small number of users, obtaining an average area under curve of 84.3%, and an average accuracy of 79%. Furthermore, the user’s visual kinetics features are consistently selected in every set of a cross-validation evaluation.
Finding the Best Lighting Mode for Daguerreotype, Ambrotype, and Tintype Photographs and Their Deterioration on the Cruse Scanner Based on Selected Methods
Authors: Berger Haladová Zuzana , Bohdal Róbert , Černeková Zuzana , Štancelová Paula , Ferko Andrej , Blaško Križanová Janka , Hojstričová Jana , Baráthová Kitti
Published: February 2023

In the digital heritage field, the accurate reproduction of hard-to-photograph items, such as daguerreotypes, ambrotypes, and tintypes, is an ongoing challenge. Industrial contactless sensors offer the potential to improve the quality of scanned images, but their capabilities and limitations have not been fully explored. In our research, a dataset of 48 scans was created using the hi-tech industrial contactless sensor CRUSE. Moreover, 3 rare original photographs were scanned in 16 different modes, the most suitable images were determined by specialists in the restoration, and validated through experiments involving eye-tracking, multiple computer vision, and image processing methods. Our study identified the Cruse scanning modes, which can be utilized to achieve the most accurate digital representation of scanned originals. Secondly, we proposed several methods for highlighting the degradation and minor scratches on photographs that otherwise might not be detected by the restorer’s naked eye. Our findings belong to four overlapping areas, i.e., image understanding, digital heritage, information visualization, and industrial sensors research. We publish the entire dataset under the CC BY-NC 4.0 license. The CRUSE sensor shows promise as a tool for improving the quality of scanned images of difficult-to-photograph items. Further research is necessary to fully understand its capabilities and limitations in this context.
Creation and Analysis of a Respiratory Sensor Using the Screen-Printing Method and the Arduino Platform
Authors: Wojciechowski Jarosław , Skrzetuska Ewa
Published: February 2023

The aim of this paper is to present novel highly sensitive and stretchable strain sensors using data analysis to report on human live parameters using the Arduino embedded system as a proof of concept in developing new and innovative solutions for health care. The article introduces the solution of textile sensor origination with electrical resistance measurement using the mobile Arduino microcontroller in the designed/elaborated textile printed sensor. The textile sensor was developed by the screen printing technique based on the water dispersion of carbon nanotubes during printing composition. By stretching and squeezing the T-shirt during breathing, the electrical resistances of the printed sensor were changed. The measured resistance corresponded to the number of breaths of the person wearing the T-shirt. The microcontroller calculated the number of breaths as a number of electrical resistance peaks, which then led to monitoring human live parameters.
Towards a Machine Learning Driven Trust Management Heuristic for the Internet of Vehicles
Authors: Siddiqui Sarah Ali , Mahmood Adnan , Sheng Quan Z. , Suzuki Hajime , Ni Wei
Published: February 2023

The rapid proliferation of the emerging yet promising notion of the Internet-of-Vehicles (IoV) has led to the development of a variety of conventional trust assessment schemes to tackle insider attackers. The primary reliance of these frameworks is on the accumulation of individual trust attributes. While aggregating these influential parameters, weights are often associated with each individual attribute to reflect its impact on the final trust score. It is of paramount importance that such weights be precise to lead to an accurate trust assessment. Moreover, the value of the minimum acceptable trust threshold employed for the identification of dishonest vehicles needs to be carefully defined to avoid delayed or erroneous detection. This paper employs an IoT data set from CRAWDAD by suitably transforming it into an IoV format. This data set encompasses information regarding 18,226 interactions among 76 nodes, both honest and dishonest. First, the influencing parameters (i.e., packet delivery ratio, familiarity, timeliness and interaction frequency) were computed, and two feature matrices were formed. The first matrix (FM1) takes into account all the pairwise individual parameters as individual features, whereas the second matrix (FM2) considers the average of all pairwise computations performed for each individual parameter as one feature. Subsequently, unsupervised learning is employed to achieve the ground truth prior to applying supervised machine learning algorithms for classification purposes. It is worth noting that Subspace KNN yielded a perfect precision, recall, and the F1-score equal to 1 for individual parametric scores, whereas Subspace Discriminant returned an ideal precision, recall, and the F1-score equal to 1 for mean parametric scores. It is also evident from extensive simulations that FM2 yielded more accurate classification results compared to FM1. Furthermore, decision boundaries among honest and dishonest vehicles have also been computed for respective feature matrices.
Diagnosis of the Pneumatic Wheel Condition Based on Vibration Analysis of the Sprung Mass in the Vehicle Self-Diagnostics System
Authors: Prażnowski Krzysztof , Mamala Jarosław , Deptuła Adam , Deptuła Anna M. , Bieniek Andrzej
Published: February 2023

This paper presents a method for the multi-criteria classification of data in terms of identifying pneumatic wheel imbalance on the basis of vehicle body vibrations in normal operation conditions. The paper uses an expert system based on search graphs that apply source features of objects and distances from points in the space of classified objects (the metric used). Rules generated for data obtained from tests performed under stationary and road conditions using a chassis dynamometer were used to develop the expert system. The recorded linear acceleration signals of the vehicle body were analyzed in the frequency domain for which the power spectral density was determined. The power field values for selected harmonics of the spectrum consistent with the angular velocity of the wheel were adopted for further analysis. In the developed expert system, the Kamada–Kawai model was used to arrange the nodes of the decision tree graph. Based on the developed database containing learning and testing data for each vehicle speed and wheel balance condition, the probability of the wheel imbalance condition was determined. As a result of the analysis, it was determined that the highest probability of identifying wheel imbalance equal to almost 100% was obtained in the vehicle speed range of 50 km/h to 70 km/h. This is known as the pre-resonance range in relation to the eigenfrequency of the wheel vibrations. As the vehicle speed increases, the accuracy of the data classification for identifying wheel imbalance in relation to the learning data decreases to 50% for the speed of 90 km/h.
Fabrication and Optimization of Nafion as a Protective Membrane for TiN-Based pH Sensors
Authors: Paul Shylendra Shimrith , Wajrak Magdalena , Alameh Kamal
Published: February 2023

In this study, a solid-state modified pH sensor with RF magnetron sputtering technology was developed. The sensor consists of an active electrode consisting of a titanium nitride (TiN) film with a protective membrane of Nafion and a reference glass electrode of Ag/AgCl. The sensitivity of the pH sensor was investigated. Results show a sensor with excellent characteristics: sensitivity of 58.6 mV/pH for pH values from 2 to 12, very short response time of approximately 12 s in neutral pH solutions, and stability of less than 0.9 mV in 10 min duration. Further improvement in the performance of the TiN sensor was studied by application of a Nafion protective membrane. Nafion improves the sensor sensitivity close to Nernstian by maintaining a linear response. This paves the way to implement TiN with Nafion protection to block any interference species during real time applications in biosensing and medical diagnostic pH sensors.
Flight Controller as a Low-Cost IMU Sensor for Human Motion Measurement
Authors: Iluk Artur
Published: February 2023

Human motion analysis requires information about the position and orientation of different parts of the human body over time. Widely used are optical methods such as the VICON system and sets of wired and wireless IMU sensors to estimate absolute orientation angles of extremities (Xsens). Both methods require expensive measurement devices and have disadvantages such as the limited rate of position and angle acquisition. In the paper, the adaptation of the drone flight controller was proposed as a low-cost and relatively high-performance device for the human body pose estimation and acceleration measurements. The test setup with the use of flight controllers was described and the efficiency of the flight controller sensor was compared with commercial sensors. The practical usability of sensors in human motion measurement was presented. The issues related to the dynamic response of IMU-based sensors during acceleration measurement were discussed.
Safety Climate Assessment in Fuel Stations in the West Java Region
Authors: Wibowo Aryo , Lestari Fatma , Modjo Robiana
Published: February 2023

Fuel station accidents still happen frequently all around the world. Accidents in fuel stations may cause harm to many. Fuel station environments must thus be managed well to maintain a high safety climate level. However, our literature review shows that research on the safety climate in fuel stations is scarce. This study attempts to assess the safety climate level in fuel stations in the West Java region, Indonesia. The aims of this research are to acquire the safety climate level of fuel stations, review safety climate dimensions which need serious improvement, and discover key aspects that impact the safety climate level. To achieve these goals, the Bahasa Indonesia version of the NOSACQ-50 questionnaire was used to assess the safety climate in 240 fuel stations; 678 responses were collected. The findings show that the safety climate level of fuel stations was, on average, 3.07, which is a fairly good score. Among all seven dimensions, workers’ safety priority and risk non-acceptance need the most improvement. Moreover, safety training is found to be the most influential aspect on safety climate because workers with training experience have higher safety climate perceptions. Ironically, more than 28% of respondents reported that they had not been properly trained. Therefore, fuel stations need to make sure that all employees have attended appropriate safety training. In this way, higher safety climate ratings can be achieved, hence moving forward to a safer working environment.
Multiple Sclerosis and Sodium Toxicity: Controversy and Future Directions for Low-Salt Interventions
Authors: Brown Ronald B.
Published: February 2023

Salt intake is associated with multiple sclerosis; however, controversial findings that challenge this association rely primarily on methods that do not measure total sodium storage within the body, such as food surveys and urinary sodium excretion. In contrast, tissue sodium concentrations measured with sodium MRI confirm high sodium levels in multiple sclerosis, suggesting a role for sodium toxicity as a risk factor for the disease. Research on demyelination in the central nervous system has identified myelin phase transitions associated with increased salinity, which cause structural instabilities of myelin sheaths and add further evidence implicating sodium toxicity as a causative factor in multiple sclerosis. Inflammatory and immune responses in multiple sclerosis are also related to high sodium intake. In addition, salt is a potential mediating factor associating multiple sclerosis with comorbidities, including systemic lupus erythematosus, rheumatic arthritis, inflammatory bowel disease, and cardiovascular disease. Current confusion exists over classifying dietary sodium intake levels as low, normal, and high, and questions remain over levels of sodium restriction necessary for disease prevention. To reduce multiple sclerosis symptoms and prevent disease progression in patients, future research should investigate low-salt interventions with levels of sodium intake associated with ancestral hunter-gatherer tribes.