Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the mechanical behavior of railway ballast using artificial neural networks

Ballast is one of the most commonly used construction materials in railway tracks. Under heavy train loads, ballast is subjected to a high stress level that is always associated with significant track deformation. Consequently, an accurate prediction of the mechanical behavior of ballast under static and dynamic loading conditions is important for the stability of railway tracks. In this paper, the feasibility of using artificial neural networks (ANNs) for modeling the mechanical behavior of railway ballast under static loading is investigated. The database used for the development of the ANN model is obtained from selected literature and comprises a series of 29 large-scale drained triaxial compression tests conducted on three types of commonly used ballast (i.e., basalt, dolomite, and granite). Predictions from the ANN model are compared with the results of experimental tests and with those obtained from the hardening-soil constitutive model in PLAXIS finite-element code. The results indicate that the A.
Ownership structure and loan quality of deposit money banks in Nigeria

Purpose - This study examined the effect of Ownership Structure (Management Shareholding and Ownership Concentration) on the loan quality (LDR) of banks in Nigeria for a period of 10 years (2008-2017). The study utilized data extracted from the annual reports of the fourteen (14) studied banks.Method - Robustness tests were carried out to determine: the existence or otherwise of multi-collinearity, fitness of the model and appropriate regression analysis for the study. Descriptive statistics, correlation and Fixed Effect GLS regression were used to describe and analyze the data.Result - The study found that, ownership structure (ownership concentration and management shareholding) has significant negative effect on loan quality of banks in Nigeria.Implication - The implications of this research is that increased ownership concentration as well as management shareholding can strengthen banks’ loan quality owing to reduced proportion of depositors funds used to finance loan. This could spur confidence in the bank by the general public with regards to the safety of their deposits.Originality - This study is different from other studies that concentrated on the use of ownership structure in relations to various financial performance measurements such as ROA, ROE, NPM among other. In this study, effort was made to consider the financial health of banks owing to the nature of their business (loan).
Electric Power Equipment Condition Intelligent Monitoring by Using Data Mining Method

Industrial equipment has large amount of historical operation data, and the real-time sampling data is massive and multi-dimensions. This paper proposes an equipment condition intelligent monitoring algorithm based on data mining. The algorithm firstly makes adaptive clustering analysis of historical data on the good running condition of equipment, builds the mathematical model of the equipment, and makes prediction of equipment operation state according to this model and the value of real-time state of equipment operation. This algorithm fully considers the actual demand of industrial application, automatically determines the number of clustering class, solves the problem of large cost and low efficiency of traditional clustering algorithm processing massive historical data, and ensures the efficiency of regression forecasting process.
Therapeutic Singing as a Swallowing Intervention in Head and Neck Cancer Patients With Dysphagia

Background: Head and neck cancer patients often suffer from dysphagia after surgery and radiotherapy. A singing-enhanced swallowing protocol was established to improve their swallowing function. This study aimed to evaluate the beneficial effects of therapeutic singing on dysphagia in head and neck cancer (HNC) patients. Methods: Patients who participated in this study were allocated to the intervention group (15 patients) and the control group (13 patients). Patients assigned to the intervention group received therapeutic singing 3 times per week for 4 weeks. Each group was divided into 2 subgroups, including the oral cavity cancer group and the pharyngeal cancer group. The patients’ vocal functions were evaluated in maximum phonation time, pitch, intensity, jitter, shimmer, harmonics to noise ratio, and laryngeal diadochokinesis (L-DDK). To evaluate swallowing function, videofluoroscopic swallowing study was done, and the results were analyzed by videofluoroscopic dysphagia scale (VDS) and dynamic imaging grade of swallowing toxicity (DIGEST). Results: Among the voice parameters, L-DDK of the intervention group significantly increased compared to that of the control group. Swallowing functions of the intervention group were significantly improved in VDS and DIGEST after the intervention. Detailed items of VDS and DIGEST showed improvements especially in the pharyngeal phase score of VDS, such as laryngeal elevation, pharyngeal transit time, and aspiration. In addition, the pharyngeal cancer group showed significant improvements in VDS and DIGEST scores after the intervention. Conclusions: Our outcomes highlight the beneficial effects of singing for HNC patients with dysphagia. The notable improvements in the pharyngeal phase suggest that therapeutic singing would be more appropriate for HNC patients who need to improve their intrinsic muscle movements of vocal fold and laryngeal elevation.
A Passivity-Based Approach to the Rotor Resistance Estimation and Sliding Mode Control for Induction Motors

Based on the passivity theorem, an approach of the rotor resistance estimation and sliding mode position control for induction motor drives is proposed in this paper. Owing to values of the moment of inertia and the viscous coefficient of induction motors are generally small, the load torque disturbance is a critical term to create the chattering phenomenon. The adaptive laws are taken into account for estimating the rotor resistance and the gain of a load torque. Therefore, the chattering associated with the conventional sliding mode controller can be alleviated. The stability analysis of the estimator and the position control system is carried out by employing the passivity theorem. Finally, experimental results are presented to show the performance and robustness of the estimator and the controller with the variations of the motor mechanical parameters, rotor resistance, and load torque disturbances.
Multirate Signal Processing: a Solution for Wide-band GNSS Signal Recovery

In this paper, a new approach based on multirate signal processing is proposed for the recovery of new wide-band GNSS signals. The use of two or more narrow-band front-ends is suggested and di erent portions of the spectrum of the wide-band signal are recovered separately. The wide-band signal is then reconstructed from its narrow-band components. Algorithms for compensating phase o sets and amplitude imbalances have been developed and used to equalize possible di erences among the narrow-band components. Specific focus is given to the case where two front-ends are employed and live GNSS data from the Galileo In-Orbit Validation Elements, GIOVE-A and GIOVE-B, are used for demonstrating the e ectiveness of the developed multirate algorithms.
Calibration and Time-independence of Buffer-less System for Thermistor Temperature Measurement

This paper presents a temperature measurement system without the input buffer. A voltage follower or a buffer is required to minimize the influence of the ADC input impedance in the thermistor temperature measurement system. In such system, a high performance operational amplifier is usually required to prevent the noise and distortion due to the additional circuit. Negative power is also necessary to prevent the distortion of the low voltage input signal. This paper introduces a buffer-less system with a calibration method to resolve such problems. The low temperature coefficient precision resistors were employed to calibrate the input resistance and the leakage current of ADC. The experimental results show that the calibrated error decreased from 190mK to 40mK. As a result, it was shown that the ADC input impedance is time-independent.
Imitation of a procedural greenhouse model with an artificial neural network

Kok, R. , Lacroix, R. , Clark, G. and Taillefer, E. 1994. Imitation of a procedural greenhouse model with an artificial neural net work. Can. Agric. Eng. 36:117-126. Our overall objective is to replace procedural models with neural networks for some reasoning activities in cognitive systems. We have initially attempted to imitate a procedural thermal exchange model of a greenhouse with a number of neural networks, each of which was subjected to various amounts of learning. An evaluation method was developed with which the performance of each network was compared to that of the procedural model. The efficacy of the evaluation method was assessed in com parison to human visual judgment. Each network was also tested for its ability to respond meaningfully to data sets which were different from its learning set. The evaluation method was found to agree with the general trend of human visual judgment and can be used to monitor a network's progress in learning. The networks were given input values for date, time, solar radiation, exterior temperature, relative humidity, and wind speed, as well as one-hour lag values of the radiation and exterior temperature. After 100,000 learning cy cles, the networks adequately mimicked the greenhouse procedural model with regard to the three output variables of interest: interior temperature, heating load, and ventilation. This network configura tion (8 inputs, 3 outputs, 100,000 learning cycles) also performed acceptably when the input data used during recall were different
A wafer-bonded floating-element shear stress microsensor with optical position sensing by photodiodes

This paper discusses a noninvasive sensing technique for the direct measurement of low-magnitude shear stresses in laminar and turbulent air flows. The sensing scheme detects the flow-induced in-plane displacement of a microfabricated floating-element structure (500 /spl mu/m/spl times/500 /spl mu/m/spl times/7 /spl mu/m), using integrated photodiodes. The wall-mounted floating-element sensors were fabricated using a wafer-bonding technology. The sensors were calibrated in a custom-designed laminar flow cell and subsequently shown to be able to transduce shear stresses of 0.01 Pa during tests in a low-speed wind tunnel.
Reflection imaging of complex geology in crystalline environment using virtual-source seismology: case study from the Kylylahti polymetallic mine, Finland

Abstract. For the first time, we apply a full-scale 3D seismic virtual-source survey (VSS) for the purpose of near-mine mineral exploration. The data was acquired directly above the Kylylahti underground mine in Finland. Recorded ambient noise (AN) data is characterized using power-spectral density (PSD) and beamforming. Data has most energy at frequencies 25–90 Hz and arrivals with velocities higher than 4 km/s have wide range of azimuths. Based on the PSD and beamforming results, we created 10-days subset of AN recordings that were dominated by multi-azimuth high-velocity arrivals. We use illumination-diagnosis technique and location procedure to show that the AN recordings associated with high apparent velocities are related to body-wave events. Next, we produce 994 virtual-source gathers by applying seismic-interferometry processing by cross-correlating AN at all receivers resulting in full 3D VSS. We apply standard 3D time-domain reflection seismic data processing and imaging using both a selectively stacked subset and full passive data, and validate the results against a pre-existing detailed geological information and 3D active-source survey data processed in the same way as the passive data. The resulting post-stack migrated sections show agreement of reflections between the passive and active data and indicate that VSS provide images where the active-source data are not available due to terrain restrictions. We conclude that while the all-noise approach provides some higher quality reflections related to the inner geological contacts within the target formation and the general dipping trend of the formation, the selected subset is most efficient in resolving the base of formation.
Unconventional Bogie Designs - Their Practical Basis and Historical Background

SUMMARY This paper deals with the design concepts for steerable bogies. A brief historical background is given and the modern design basis generated by the creep theory is summarised with regard to curving performance and dynamic stability of two- and three-axle bogies. The basic structural elements used for trailing and motorised steerable bogies are illustrated. Experience gained with some recent designs of self-steering and forced-steering bogies is discussed and achievable stability and curving performances are quoted.
Investigation of candidate VRM topologies for future microprocessors

By reducing the power supply voltage, faster, lower power consumption, and high integration density data processing systems can be achieved. The current generation high-speed complementary metal-oxide-semiconductor (CMOS) processors (e.g., Alpha, Pentium, Power PC) are operating at above 300 MHz with 2.5 to 3.3 V output range. Future processors will be designed in the 1.1-1.8 V range, to further enhance their speed-power performance. These new generation microprocessors will present very dynamic loads with high current slew rates during transient. As a result, they will require a special power supply, voltage regulator module (VRM), to provide well-regulated voltage. The VRMs should have high power densities, high efficiencies, and good transient performance. In this paper, the critical technical issues to achieve this target for future generation microprocessors are addressed. A VRM candidate topology, interleaved quasisquare-wave (QSW), is proposed. The design, simulation and experimental results are presented.
Phyto-Synthesized Silver Nanoparticle Toxicity Effect on Aquatic Plant Lemna minor L.

Silver nanoparticles (AgNPs) are made up about 55% of all nanomaterials produced and are widely used in consumer products. Its is inevitable that these particles are released to the aquatic environment during production, use and disposal. In this study, subacute toxicity of AgNPs obtained by phyto-synthesis was investigated on Lemna minor L. (duckweed) plants. The formation of AgNPs obtained from laurel (Laurus nobilis L.) extract was determined by UV-VIS spectrophotometric measurements. The AgNPs synthesized by the phytosynthesis method were characterized by Fourier transform infrared spectroscopy (FT-IR), Zeta size and potential, Inductively Coupled Plasma Mass Spectrometry and Scanning electron microscopy (SEM-EDS) analysis. The analysis results show that AgNPs are homogeneously distributed, spherical in shape with an average size of 34 nm and coated with phyto-content. For toxicity tests, plant stock cultures were grown in the climate room according to OECD 221 guidelines. After 8 weeks of acclimation, the plants were treated with AgNP concentrations ranging from 0.005 to 50 mg L for 7and 14-days. The increase in AgNP concentration caused a decrease in frond numbers. Growth inhibition data showed that the EC50 value of phyto-synthesized AgNP was 4.78 mg L and the lowest observed effect concentration (LOEC) was 0.5 mg L for 7-days. AgNP concentrations below LOEC level (0.05, to 0.5 mg L) caused a significant decrease in growth rate by 20.07% after 7 days of exposure while it was found 4.03% for 14-days treatment at the highest AgNP concentration (0.5 mg L). Similar trend was observed in fresh-and dry weight of plants indicating prolonged exposure time triggering tolerance mechanism which was corroborated by chlorophyll a/b and carotenoids content results. Based on higher NOEC, LOEC and EC50 values, phyto-synthesized AgNP usage may lead less environmental toxicity.
Enlarging switching frequency in direct torque-controlled inverter by means of dithering

This paper presents a novel, simple method to enlarge switching frequency in the direct torque-controlled inverter for an induction motor drive, which makes an acoustically silent motor operation possible. It is actually impossible to raise the inverter switching frequency in the conventional system, although the hysteresis bandwidths for the stator flux and torque control are sufficiently diminished, because of the delay in estimating the flux and the torque. In order to overcome the problem, the proposed method introduces a dithering technique into the conventional system by superposing triangular waves with high frequency and minute amplitude on the flux error and the torque error, respectively. According to the simulation and experimental results, the stator flux ripple and the torque ripple were suppressed to approximately 30% compared with those of the conventional system. Also, the acoustic noise level of the motor was reduced to less than 56 dB over the whole speed range from 100 to 1500 r/min.
The Terpene Mini-Path, a New Promising Alternative for Terpenoids Bio-Production

Terpenoids constitute the largest class of natural compounds and are extremely valuable from an economic point of view due to their extended physicochemical properties and biological activities. Due to recent environmental concerns, terpene extraction from natural sources is no longer considered as a viable option, and neither is the chemical synthesis to access such chemicals due to their sophisticated structural characteristics. An alternative to produce terpenoids is the use of biotechnological tools involving, for example, the construction of enzymatic cascades (cell-free synthesis) or a microbial bio-production thanks to metabolic engineering techniques. Despite outstanding successes, these approaches have been hampered by the length of the two natural biosynthetic routes (the mevalonate and the methyl erythritol phosphate pathways), leading to dimethylallyl diphosphate (DMAPP) and isopentenyl diphosphate (IPP), the two common universal precursors of all terpenoids. Recently, we, and others, developed what we called the terpene mini-path, a robust two enzyme access to DMAPP and IPP starting from their corresponding two alcohols, dimethylallyl alcohol and isopentenol. The aim here is to present the potential of this artificial bio-access to terpenoids, either in vitro or in vivo, through a review of the publications appearing since 2016 on this very new and fascinating field of investigation.
What Is the Customer Value of the Circular Economy? Cross-Industry Exploration of Diverse Values Perceived by Consumers and Business Customers

A growing number of companies provide CE products, technologies, services, and solutions, and similarly, an increasing number of researchers have analyzed sustainable and CE business models providing knowledge about CE technology businesses. However, this research has focused almost solely on the providers’ perspective on CE business and offerings, remaining silent on the customer perspective. Therefore, this study contributes by focusing on the customer value of CE innovations and solutions, conducting an explorative qualitative multiple-case investigation among customers of diverse CE businesses, and mapping diverse customer value dimensions, including economic, functional, emotional, and symbolic, and comparing them as perceived by consumer and business customers. The findings show that the functional value of CE offerings dominates. We develop conceptual maps for CE customer value for a theoretical understanding of the CE from the customer perspective and provide insights for managers to assert the value of their CE solutions.
SPEECH ACTS IN PUBLIC FIGURES’ TWEETS ON ENVIRONMENTAL ISSUES

This paper presents the detailed analysis and interpretation of the main speech acts used in the tweets of public figures. Our novel findings discover the major types of the speech acts found in the utterances of public figures related to the environment. Based on the studies of numerous scholars and rich theoretical background on speech acts theory, the study touches the aspect of global problems depicted in media discourse with regard to the pragmatic reference to the audience reaction. The methodology of this article begins with the task to collects the data in the English Twitter Corpus from the utterances of renown environmental activists. The highlight of the publication is the classification of these utterances supported by the numerical data. In addition to the illocutionary aspect, perlocutionary effect was identified proceeding from the reaction count. Along with a single and complex speech act, the authors identified the meaning of a complex speech act within the Twitter social networking service. Another major feature of the publication is identifying reversed speech acts used by the public figures for highlighting the importance of the topic raised on their microblogs. The present research explores the perlocutionary effect of the tweets by counting replies on tweets, quote tweets and likes. Having applied quantitative methods, the leading environmental topics were identified judging by the response of the audience. Calculated data is extensively used in the research to show the considerable impact of specific topics on the audience. This research will contribute to a deeper understanding of pragmatic study of social media for more profound arrangement of public figures’ speeches which can be translated to a schema for creating targeted social media discourse.
Pattern Recognition for Classification and Matching of Car Tires

Abstract Commercial databases containing images of tire tread patterns are currently used by product designers, forensic specialists and product application personnel to identify whether a given tread pattern matches an existing tire. Currently, this pattern matching process is almost entirely manual, requiring visual searches of extensive libraries of tire tread patterns. Our work explores a first step toward automating this pattern matching process by building on feature analysis techniques from computer vision and image processing to develop a new method for extracting and classifying features from tire tread patterns and automatically locating candidate matches from a database of existing tread pattern images. Our method begins with a selection of tire tread images obtained from multiple sources (including manufacturers' literature, Web site images, and Tire Guides, Inc.), which are preprocessed and normalized using Two‐Dimensional Fast Fourier Transforms (2D‐FFT). The results of this preprocessing ar.