Miracle-dz/UniFAR-FTUs huggingface dataset:
Heat Transfer Enhancement for Internal Flows with a Centrally Located Circular Obstruction and the Impact of Buoyancy

Abstract Numerical simulations have been carried out for gas flow through a horizontal pipe. Accounting is made of buoyancy effects, changes to the thermophysical properties, and the presence of a blockage. It was found that for low-to-moderate Reynolds numbers, the combined effects on heat transfer and pressure loss lead to an improved performance with the obstruction. On the other hand, the influence of heating on properties is shown to have a significant effect on the Nusselt number in both the laminar and the turbulent regions. Property variations increase the laminar Nusselt number and decrease the turbulent values. The results also show that a blockage has a much bigger impact on laminar flows than on turbulent flows and can inhibit downstream buoyant motion and convective heat transfer.
Pattern-growth methods for frequent pattern mining

Mining frequent patterns from large databases plays an essential role in many data mining tasks and has broad applications. Most of the previously proposed methods adopt apriori-like candidate-generation-and-test approaches. However, those methods may encounter serious challenges when mining datasets with prolific patterns and/or long patterns. In this work, we develop a class of novel and efficient pattern-growth methods for mining various frequent patterns from large databases. Pattern-growth methods adopt a divide-and-conquer approach to decompose both the mining tasks and the databases. Then, they use a pattern fragment growth method to avoid the costly candidate-generation-and-test processing completely. Moreover, effective data structures are proposed to compress crucial information about frequent patterns and avoid expensive, repeated database scans. A comprehensive performance study shows that pattern-growth methods, FP-growth and H-mine, are efficient and scalable. They are faster than some recently reported new frequent pattern mining methods. Interestingly, pattern growth methods are not only efficient, but also effective. With pattern growth methods, many interesting patterns can also be mined efficiently, such as patterns with some tough non-anti-monotonic constraints and sequential patterns. These techniques have strong implications to many other data mining tasks.
Personnel selection based on intuitionistic fuzzy sets

One of the most important activities carried out by human resource management is personnel selection, concerned with identifying an individual from a pool of candidates suitable for a vacant position. Traditionally, personnel selection is a group decision‐making problem under multiple criteria containing subjectivity, imprecision, and vagueness, which are best represented with fuzzy data. In this article, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method extended to intuitionistic fuzzy environments is proposed to select appropriate personnel among candidates. An intuitionistic fuzzy set (IFS), which is characterized by membership function, nonmembership function, and hesitation margin, is a more suitable way to deal with vagueness when compared to a fuzzy set. To demonstrate the applicability and effectiveness of the intuitionistic fuzzy TOPSIS method, a numerical example of personnel selection in a manufacturing company for a sales manager position is given. © 2011 Wiley Periodicals, Inc.
Necessity of the bridge health monitoring system to mitigate natural and man-made disasters

In Korea, there has been a wide consensus about the necessity of bridge monitoring systems. This is primarily due to a chain of accidental bridge collapses over the past decade. The first generation bridge monitoring system originated from an instrumentation system introduced upon the reconstruction of the New-Haengju Bridge after its sudden collapse in 1995. After that, on-line instrumentation systems were installed in existing cable-supported bridges including Namhae, Jindo and Dolsan Bridges. These systems can be considered the second generation bridge health monitoring systems (BHMSs). These were then followed by the development of the third generation bridge monitoring systems installed and currently in service on the Seohae and Yeongjong Bridges. This study tracks the background and advent of Korean bridge monitoring systems and their developmental history up to the present time. It also investigates current associated studies in progress and the limitations of contemporary BHMS technologies, and suggests possible remedial solutions for a follow-up bridge monitoring system.
Relationship Classi�cation based on Dependency Parsing and Pre-training Model

As an important part of information extraction, relationship extraction aims to extract the relationships between given entities from natural language text. On the basis of the pre-training model R-BERT, this paper proposes an entity relationship extraction method that integrates entity dependency path and pre-training model, which generates a dependency parse tree by dependency parsing, obtains the dependency path of entity pair via a given entity, and uses entity dependency path to exclude such information as modi�er chunks and useless entities in sentences. This model has achieved good F1 value performance on the SemEval2010 Task 8 dataset. Experiments on dataset show that dependency parsing can provide context information for models and improve performance.
Application of LCA to support solid waste management policy in Phuket

Life Cycle Assessment (LCA) is employed to evaluate the environmental performance of the existing Municipal Solid Waste (MSW) management system in Phuket and compared with different possible alternative Integrated Waste Management Systems (IWMSs). The results show that the scenario comprising source separation of waste for anaerobic digestion and recycling plus incineration (with energy recovery) and landfilling has the least environmental burdens for all the impact categories considered. The study suggests a policy promoting source separation for the waste to be recycled and anaerobically digested including the application of landfill gas recovery for electricity.
Intra-examiner and inter-examiner reliability of rehabilitative ultrasound imaging for lumbar multifidus and anterolateral abdominal muscles in females with recurrent low back pain: an observational, cross-sectional study

Abstract Aim: To examine the reliability of rehabilitative ultrasound imaging performed to measure the thickness of the transverse abdominis, internal oblique, external oblique, and lumbar multifidus muscles in females with recurrent low back pain. Material and methods: A sample of 15 women was recruited. Two independent examiners recorded the thickness of their deep abdominal and spinal muscles by rehabilitative ultrasound imaging. Imaging scans of the transverse abdominis, internal oblique, and external oblique muscles were performed in the supine position and in the midaxillary line, between the lower edge of the ribcage and the iliac crest. Imaging of the lumbar multifidus was done in the prone position and at the level of the L5/S1 zygapophyseal joints. Imaging scans were performed bilaterally in rest and contraction, three times by the first examiner (at baseline, after two hours, and one week later) and once by the second examiner. Results: Good to excellent within-session intra-rater (ICC = 0.76, 0.97), good to excellent between-session intra-rater reliability (ICC = 0.73, 0.93), and good to excellent inter-rater reliability (ICC = 0.73, 0.98) were obtained. Conclusions: The results showed that rehabilitative ultrasound imaging can be used as an excellent reliable instrument by one or two examiners to measure the thickness of the transverse abdominis, internal oblique, external oblique and lumbar multifidus muscles in females with recurrent low back pain.
Preventive measures of the tracking fire generated between a home electric outlet and plugs

A fire by tracking is generated occasionally. The cause of tracking is a dust of space between an electrical outlet and a plug. Spark discharges at the space covered with dust are generated when the dust absorbs moisture. A fire caused by tracking is generated by changing the isolated surface between plugs into a carbonized surface. This type of fire of 35 cases occurred at the first half of 2011 in Japan. Such fire occurs in the hidden electrical outlet. Therefore, the determination of the fire, whether the fire occurs, is not so easy in the early stages. The experimental objective is to study the preventive measures of fire caused by the tracking. In this paper, we study the difference between an enhanced tracking plug and a normal plug. The experiments are carried out when water is dripped between the electrical outlet and the plugs with dust.
Monitoring the rotation status of wind turbine blades using high-speed camera system

The measurement of the rotating object is of great significance in engineering applications. In this study, a high-speed dual camera system based on 3D digital image correlation has been developed in order to monitor the rotation status of the wind turbine blades. The system allows sequential images acquired at a rate of 500 frames per second (fps). An improved Newton-Raphson algorithm has been proposed which enables detection movement including large rotation and translation in subpixel precision. The simulation experiments showed that this algorithm is robust to identify the movement if the rotation angle is less than 16 degrees between the adjacent images. The subpixel precision is equivalent to the normal NR algorithm, i.e.0.01 pixels in displacement. As a laboratory research, the high speed camera system was used to measure the movement of the wind turbine model which was driven by an electric fan. In the experiment, the image acquisition rate was set at 387 fps and the cameras were calibrated according to Zhang’s method. The blade was coated with randomly distributed speckles and 7 locations in the blade along the radial direction were selected. The displacement components of these 7 locations were measured with the proposed method. Conclusion is drawn that the proposed DIC algorithm is suitable for large rotation detection, and the high-speed dual camera system is a promising, economic method in health diagnose of wind turbine blades.
Design of Handwriting-based Text Interface for Support of Mobile
 Platform Education Contents

This study proposes a text interface for support of language-based educational contents in a mobile platform environment. The proposed interface utilizes deep learning as an input structure to write words through handwriting. Based on GUI (Graphical User Interface) using buttons and menus of mobile platform contents and input methods such as screen touch, click, and drag, we design a text interface that can directly input and process handwriting from the user. It uses the EMNIST (Extended Modified National Institute of Standards and Technology database) dataset and a trained CNN (Convolutional Neural Network) to classify and combine alphabetic texts to complete words. Finally, we conduct experiments to analyze the learning support effect of the interface proposed by directly producing English word education contents and to compare satisfaction. We compared the ability to learn English words presented by users who have experienced the existing keypad-type interface and the proposed handwriting-based text interface in the same educational environment, and we analyzed the overall satisfaction in the process of writing words by manipulating the interface.
ADVERTISING STRATEGY ACCORDING TO THE CONCEPT OF THE FCB MODEL IN THE CONDITIONS OF THE VARIOUS GENERATIONS

The aims of the paper are: 1) to verify the validity of the traditional theoretical definition of the Foote, Cone & Belding (FCB) model based on the use of representative products concerning the age (generation) and gender of the selected target group in the conditions of the Czech Republic, and 2) to verify the validity of defined advertising strategies in the traditional theoretical conception of the Foote, Cone & Belding (FCB) model with the current level of acceptance and perception of advertising within the defined selected target group according to age (generation) and gender in the conditions of the Czech Republic. To meet both aims, both secondary and primary marketing research was implemented. The theoretical background of the paper is based on knowledge of marketing communication principles in general with emphasis on advertising theories. The greatest attention is focused on the traditional version of the FCB model which is based on a matrix of consumer thinking–feeling and high–low involvement behaviours and proposes four advertising strategies. Primary research data were obtained using a questionnaire, on the online panel of research agency Ipsos, on 1,100 Czech respondents. The methods used are positional maps for the FCB grid and chi-squared with a suitable post-hoc test. The outputs reveal the differences of the theoretical FCB model in comparison with its practical implementation. It is necessary to adapt (extend) the model according to specific conditions and identification features of different Czech generations and genders, then adjust recommendations for advertising strategies. In Czech conditions, the sextant grind should be used. There is a prevalence of representative product placement in quadrants 1 and 3, i.e., rational appeals even for products where this is not expected. The outcomes can be used for the choice of correct advertising strategy, advertising media, and types.
Youth resilience and training programmes in Australia and the US: Beyond neoliberal social therapeutics

ABSTRACT In a world where opportunities are increasingly limited, young people are encouraged to become resilient and entrepreneurial in their pursuit of the traditional markers of adulthood. Social enterprise and community organisations dedicated to supporting young people seek to recast these expectations by providing supportive work and training environments and cultures and encouraging young people to find passion and hope in economic conditions that have failed to deliver the security and wellbeing that was promised. These organisations identify and respond to complex issues like unemployment and disengagement, homelessness and housing precarity, and provide personal development, support, education, training and employment options. In this paper, we explore how youth-focused social enterprise and community organisation programmes shape dispositions of resilience and entrepreneurialism. Drawing on the work of Butler and Anthanasiou and Dey and Mason, we argue that social organisations re-imagine the ‘social therapeutics’ that young people may require in relation to their participation in neoliberal forms of governmentality. We hope to challenge conceptualisations of such interventions as purely bounded by neoliberal and pro-capitalist therapeutic logics, by identifying the complex and sometimes contradictory goals that community organisations and social enterprises work towards in supporting young people to navigate a precarious economic landscape.
Wireless sensors with dual-controller architecture for active diagnosis in structural health monitoring

Wireless sensor technology, which integrates transducers with microcontrollers and wireless communication, has become increasingly vital in structural health monitoring (SHM) applications. However, the low I/O (input/output) throughput of conventional wireless sensors impedes their usage in applications using high-frequency signals, such as active diagnosis and passive acoustic emission (AE). In this paper, the limitations of extending conventional wireless sensors to handle high-speed acquisition are first identified and discussed. Based on the efforts made in improving wireless sensors with centralized system architecture, a novel dual-controller based architecture is proposed to facilitate high-speed data acquisition and improve power efficiency. Then, a wireless sensor platform, specifically designed for active diagnosis employing stress waves to localize damages, is presented. The newly developed wireless sensor with dimensions of 30 mm × 30 mm × 35 mm utilizes a field programmable gate array (FPGA) as a secondary controller and can support a sampling rate up to 20 million samples per second (Msps). Laboratory experiments for verification show that the wireless sensor can explore new applications at the opposite end of the spectrum from conventional applications: those involving high fidelity and high-speed data acquisition.
Recognition of arrows in the environment of road markings

In the domain of image understanding in road environment, we have developed a method to recognize and locate arrows. The ambiguities in natural environment and the execution time for online processing motivated our approach. The model of the scene (including road, vehicle, camera and markings) is analysed and applied as early as possible in the appropriate levels of processing. We also tried to simplify the algorithms which work on huge data in the early stage of processing. In this article we present the model of the scene and its intervention in the processing as well as the algorithms.
A Study on Chinese Motorists' Operational Behavior in Angry Driving

With the increase of vehicles in China and the participation of young novice drivers, more and more emotional conflicts are caused by drivers. Some even attack people and other vehicles to vent their anger which is known as road rage. In order to study the characteristics of road rage and the process of identification of anger level, twenty male drivers were recruited in Wuhan, and asked to complete Driving Anger Scale (DAS). Ten drivers who scored higher were invited to do driving experiment on road rage in real traffic environment. The throttling, clutching, steering angle, engine speed, gear and velocity are analyzed particularly. The results show that in angry driving (1) the operation of the vehicle is more frequent, (2) the operation range is large and uneven, and (3) steering wheel angle change is more obvious.
RoPod, a customizable toolkit for non-invasive root imaging, reveals cell type-specific dynamics of plant autophagy

Arabidopsis root is a classic model system in plant cell and molecular biology. The sensitivity of plant roots to local environmental perturbation challenges data reproducibility and incentivizes further optimization of imaging and phenotyping tools. Here we present RoPod, an easy-to-use toolkit for low-stress live time-lapse imaging of Arabidopsis roots. RoPod comprises a dedicated protocol for plant cultivation and a customizable 3D-printed vessel with integrated microscopy-grade glass that serves simultaneously as a growth and imaging chamber. RoPod reduces impact of sample handling, preserves live samples for prolonged imaging sessions, and facilitates application of treatments during image acquisition. We describe a protocol for RoPods fabrication and provide illustrative application pipelines for monitoring root hair growth and autophagic activity. Furthermore, we showcase how the use of RoPods advanced our understanding of plant autophagy, a major catabolic pathway and a key player in plant fitness. Specifically, we obtained fine time resolution for autophagy response to commonly used chemical modulators of the pathway and revealed previously overlooked cell type-specific changes in the autophagy response. These results will aid a deeper understanding of the physiological role of autophagy and provide valuable guidelines for choosing sampling time during end-point assays currently employed in plant autophagy research.
Comparative study of the highly sensitive plasmonic sensor based on a D-Shaped photonic crystal fiber with silver or gold layers

A highly sensitive D-shaped photonic crystal fiber sensor with circular lattice is proposed for external plasmonic sensing. The proposed design of plasmonic material in a D-shaped form effectively facilitates the excitation of surface plasmons and enhances the sensor performance. As a comparative study, two different plasmonic materials, gold and silver, are applied D-shapely on the fiber and the proposed sensor performance is numerically investigated and evaluated. Moreover, the optimized structural parameters such as air-hole diameters and the thickness of silver and gold layers are selected via simulation results which cause the highest sensitivity of 40000 nm/RIU for the gold coated fiber using the wavelength interrogation method. Furthermore, the maximum figure of merit can reach 621.50 RIU−1. Analytes with the refractive indices ranging from 1.34 to 1.39 can be detected by double-loss peak that is a more reliable method of simultaneous detection and verification of sensing characteristics. Due to its promising results, the proposed sensor can be widely useful in the area of chemical and biological sensing.
Design of a spread-spectrum modulation signal bearing directional information

In this article, we propose a multiple beams spread-spectrum modulation signal transmitted by a Cassegrain antenna for communication and direction-finding applications. The main idea is that a sum beam and two difference beams are transmitted by the Cassegrain antenna similar to the Monopulse technique. According to the beams’ radiation pattern, a multiple beams spread-spectrum modulation scheme is designed to modulate the beams’ spatial parameters into the transmit signal constellation. In this way, a receiver with a single antenna demodulates the data information and the directional information from the receive signal constellation, simultaneously. Simulation results show that the proposed signal can be applied to the integrated system of communication and direction-finding in a low signal-to-noise ratio environment.
Compatibility analysis of macroscopic and microscopic traffic simulation modeling

To implement model predictive traffic control to reduce congestion, traffic state variables such as flow, speed, and density need to be accurately predicted with real-time measurements. To evaluate the accuracy of online prediction of a macroscopic traffic model, this paper compares the predicted flow, density, and speed from a macroscopic simulation model with those from a microscopic simulation model, using METANET and VISSIM respectively, on a section of urban freeway. Three levels of traffic demands and seven different time step lengths in macroscopic simulation were applied to evaluate the compatibility of the two models. It was concluded that in the macroscopic simulation model there exists an optimum time step length, under moderate to heavy traffic demands the predicted traffic states from the macroscopic simulation are consistent with the outputs from the microscopic simulation, and under stop-and-go traffic states significant difference exists between the two models.