Abstract: Collaborative research has become more prevalent and important across disciplines because it stimulates innovation and interaction between scholars. Seeing as existing studies relatively disregarded the institutional conditions triggering collaborative research, this work aims to analyze the changing trend in collaborative work patterns among Korean social scientists. The focus of this research is the performance of social scientists who received research grants through the government’s Social Science Korea (SSK) program. Using quantitative statistical methods, collaborative research patterns in a total of 2,354 papers published under the umbrella of the SSK program in peer-reviewed scholarly journals from 2013 to 2016 were examined to identify changing trends and triggering factors in collaborative research. A notable finding is that the share of collaborative research is overwhelmingly higher than that of individual research. In particular, levels of collaborative research surpassed 70%, increasing much quicker compared to other research done in the social sciences. Additionally, the most common composition of collaborative research was for two or three researchers to conduct joint research as coauthors, and this proportion has also increased steadily. Finally, a strong association between international journals and co-authorship patterns was found for the papers published by SSK program researchers from 2013 to 2016. The SSK program can be seen as the driving force behind collaboration between social scientists. Its emphasis on competition through a merit-based financial support system along with a rigorous evaluation process seems to have influenced researchers to cooperate with those who have similar research interests.
Abstract: Titanium and its alloys have become more significant implant materials due to their mechanical properties, excellent biocompatibility and high corrosion resistance. Biomaterials can be produce by using the powder metallurgy (PM) methods and required properties can tailored by varying the processing parameters, such as ball milling time, space holder particles, and sintering temperature. The desired properties such as, structural and mechanical properties can be obtained by powder metallurgy method. In the present study, deals with fabrication of solid and porous Ti-20Nb-5Ag alloy using high energy ball milling for different times (5 and 20 h). The resultant powder particles were used to fabricate solid and porous Ti-20Nb-5Ag alloy by adding space holder particles (NH4HCO3). The resultant powder particles, fabricated solid and porous samples were characterized by scanning electron microscopy (SEM). The compressive strength, elastic modulus and microhardness properties were investigated. Solid and porous Ti-20Nb-5Ag alloy samples showed good mechanical properties for 20 h ball milling time as compare to 5 h ball milling.
Abstract: Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.
Abstract: This study outlines iterations of designing mobile augmented reality (MAR) applications for tourism specific contexts. Using a design based research model, several cycles of development to implementation were analyzed and refined upon with the goal of building a MAR platform that would facilitate the creation of augmented tours and environments by non-technical users. The project took on several stages, and through the process, a simple framework was begun to be established that can inform the design and use of MAR applications for tourism contexts. As a result of these iterations of development, a platform was developed that can allow novice computer users to create augmented tourism environments. This system was able to connect existing tools in widespread use such as Google Forms and connect them to computer vision algorithms needed for more advanced augmented tourism environments. The study concludes with a discussion of this MAR platform and reveals design elements that have implications for tourism contexts. The study also points to future case uses and design approaches for augmented tourism.
Abstract: Wheat is an important cereal crop for food security. Boosting the wheat production and productivity is the major challenge across the nation. Good quality of seed is required for maintaining optimum plant stand which ultimately increases grain yield. Ensuring a good germination is one of the key steps to ensure proper plant stand and moisture assurance during seed germination may help to speed up the germination. The tiny size of nanoparticles may help in entry of water into seed without disturbing their internal structure. Considering above, a laboratory experiment was conducted during 2012-13 at G.B. Pant University of Agriculture and Technology, Pantnagar, India. The completely randomized design was used for statistical analysis. The experiment was conducted in two phases. In the first phase, the appropriate concentration of nanoparticles for seed treatment was screened. In second phase seed soaking hours of nanoparticles for better seed germination were standardized. Wheat variety UP2526 was taken as test crop. Four nanoparticles (TiO2, ZnO, nickel and chitosan) were taken for study. The crop germination studies were done in petri dishes and standard package and practices were used to raise the seedlings. The germination studies were done by following standard procedure. In first phase of the experiment, seeds were treated with 50 and 300 ppm of nanoparticles and control was also maintained for comparison. In the second phase of experiment, seeds were soaked for 4 hours, 6 hours and 8 hours with 50 ppm nanoparticles of TiO2, ZnO, nickel and chitosan along with control treatment to identify the soaking time for better seed germination. Experiment revealed that the application of nanoparticles help to enhance seed germination. The study revealed that seed treatment with nanoparticles at 50 ppm concentration increases root length, shoot length, seedling length, shoot dry weight, seedling dry weight, seedling vigour index I and seedling vigour index II as compared to seed soaking at 300 ppm concentration. This experiment showed that seed soaking up to 4 hr was better as compared to 6 and 8 hrs. Seed soaking with nanoparticles specially TiO2, ZnO, and chitosan proved to enhance germination and seedling growth indices of wheat crop.
Abstract: The demand for energy is cumulatively increasing with time. Since the availability of conventional energy resources is dying out gradually, significant interest is being laid on searching for alternate energy resources and minimizing the wastage of energy in various fields. In such perspective, low-grade waste heat from several industrial sources can be reused to generate electricity. The present work is to further the adoption of the Organic Rankine Cycle (ORC) technology in Indian industrial sector. The present paper focuses on extending the previously reported idea to the next level through a comparative review with three different working fluids using practical data from an Indian industrial plant. For comprehensive study in the simulation platform of Aspen Hysys®, v8.6, the waste heat data has been collected from a current coke oven gas plant in India. A parametric analysis of non-regenerative ORC and regenerative ORC is executed using the working fluids R-123, R-11 and R-21 for subcritical ORC system. The primary goal is to determine the optimal working fluid considering various system parameters like turbine work output, obtained system efficiency, irreversibility rate and second law efficiency under applied multiple heat source temperature (160 °C- 180 °C). Selection of the turbo-expanders is one of the most crucial tasks for low-temperature applications in ORC system. The present work is an attempt to make suitable recommendation for the appropriate configuration of the turbine. In a nutshell, this study justifies the proficiency of integrating the ORC technology in Indian perspective and also finds the appropriate parameter of all components integrated in ORC system for building up an ORC prototype.
Abstract: This study examines dialect and gender variations in the place and manner of articulation between the two Korean fricatives, /s/ and /s’/, as produced by speakers of the Daegu and Jeju dialects. The acoustic parameters of center of gravity and skewness for the place of articulation, and the rise time and the amplitude rise slope for the manner of articulation were measured. The study results revealed a gender effect, but no dialect effect, for the center of gravity and the skewness. No main effect for either the gender or dialect was found for the rise time and the amplitude rise slope. These findings indicated that, with regard to the place of articulation, Korean fricative sound differences are a gender distinction, not a dialectal one.
Abstract: To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.
Abstract: Grape stem borer, Celosterna scrabrator is an important production constraint in grapes in India. Hitherto this pest was a severe menace only on the aged and unmanaged fields but during the recent past it has also started damaging the newly established fields. In India, since Karnataka, Andra Pradesh, Tamil Nadu and Maharashtra are the major grape production states, the incidence of stem borer is also restricted and severe in these states. The grubs of the beetle bore in to the main stem and even the branches, which affect the translocation of nutrients to the areal parts of the plant. Since, the grubs bore inside the stem, the chewed material along with its excreta is discharged outside the holes and the frass is found on the ground just below the bored holes. The portion of vines above the damaged part has a sticky appearance. The leaves become pale yellow which looks like a deficiency of micronutrients. The leaves ultimately dry and drop down. The status of the incidence of the grape stem borer in different grape growing districts of Northern Karnataka was carried out during three years. In each taluka five locations were surveyed for the incidence of grape stem borer. Further, the experiment on management of stem borer was carried out in the grape gardens of Vijayapur districts under farmers field during three years. Stem borer infested plants that show live holes were selected per treatments and it was replicated three times. Live and dead holes observed during pre-treatment were closely monitored and only plants with live holes were selected and tagged. Different doses of chlorantraniliprole 0.4% GR were incorporated into the soil around the vine basins near root zone surrounded to trunk region by removing soils up to 5-10 cm with a peripheral distance of 1 to 1.5 feet from the main trunk where feeder roots are present. Irrigation was followed after application of insecticide for proper incorporation of the test chemical. The results indicated that there was sever to moderate incidence of the stem borer in all the grape growing districts of northern Karnataka. Maximum incidence was recorded in Belagavi (11 holes per vine) and minimum was in Gadag district (8.5 holes per vine). The investigations carried out to study the efficacy of chlorantraniliprole on grape stem borer for successive three years under farmers field indicated that chlorantraniliprole @ 15g/vine applied just near the active root zone of the plant followed by irrigation has successfully managed the pest. The insecticide has translocated to all the parts of the plants and thereby stopped the activity of the pest which has resulted in to better growth of the plant and higher berry yield compared to other treatments under investigation. Thus, chlorantraniliprole 0.4 GR @ 15g/vine can be effective means in managing the stem borer.
Abstract: In today's popularity and progress of information technology, the big data set and its analysis are no longer a major conundrum. Now, we could not only use the relevant big data to analysis and emulate the possible status of urban development in the near future, but also provide more comprehensive and reasonable policy implementation basis for government units or decision-makers via the analysis and emulation results as mentioned above. In this research, we set Taipei City as the research scope, and use the relevant big data variables (e.g., population, facility utilization and related social policy ratings) and Analytic Network Process (ANP) approach to implement in-depth research and discussion for the possible reduction of land use in primary and secondary schools of Taipei City. In addition to enhance the prosperous urban activities for the urban public facility utilization, the final results of this research could help improve the efficiency of urban land use in the future. Furthermore, the assessment model and research framework established in this research also provide a good reference for schools or other public facilities land use and adaptive reuse strategies in the future.
Abstract: The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system. The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.
Abstract: In the search for new physics beyond the Standard
Model, Flavour Changing Neutral Current (FCNC) is a good research
field in terms of the observability at future colliders. Increased
Higgs production with higher energy and luminosity in colliders
is essential for verification or falsification of our knowledge of
physics and predictions, and the search for new physics. Prospective
electron-proton collider constituent of the Future Circular Collider
project is FCC-eh. It offers great sensitivity due to its high luminosity
and low interference. In this work, thq FCNC interaction vertex
with off-shell top quark decay at electron-proton colliders is studied.
By using MadGraph5_aMC@NLO multi-purpose event generator,
observability of tuh and tch couplings are obtained with equal
coupling scenario. Upper limit on branching ratio of tree level top
quark FCNC decay is determined as 0.012% at FCC-eh with 1 ab ^−1
luminosity.
Abstract: Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.
Abstract: Oil spills at sea can cause severe marine environmental damage, including bringing huge hazards to living resources and human beings. In situ burning or chemical dispersant methods can be used to handle the oil spills sometimes, but these approaches will bring secondary pollution and fail in some situations. Oil recovery techniques have also been developed to recover oil using oil skimmer equipment installed on ships, while the hydrodynamic process of the oil flowing through the oil skimmer is very complicated and important for evaluating the recovery efficiency. Based on this, a two-dimensional numerical simulation platform for simulating the hydrodynamic process of the oil flowing through the oil skimmer is established based on the Navier-Stokes equations for viscous, incompressible fluid. Finally, the influence of the design of the flow channel in the curved plane oil skimmer on the hydrodynamic process of the oil flowing through the oil skimmer is investigated based on the established simulation platform.
Abstract: The development of guidance, navigation and control algorithms and avionic procedures requires the disposability of suitable analysis and verification tools, such as simulation environments, which support the design process and allow detecting potential problems prior to the flight test, in order to make new technologies available at reduced cost, time and risk. This paper presents a simulation environment for avionic software development and qualification, especially aimed at equipment for general aviation aircrafts and unmanned aerial systems. The simulation environment includes models for short and medium-range radio-navigation aids, flight assistance systems, and ground control stations. All the software modules are able to simulate the modeled systems both in fast-time and real-time tests, and were implemented following component oriented modeling techniques and requirement based approach. The paper describes the specific models features, the architectures of the implemented software systems and its validation process. Performed validation tests highlighted the capability of the simulation environment to guarantee in real-time the required functionalities and performance of the simulated avionics systems, as well as to reproduce the interaction between these systems, thus permitting a realistic and reliable simulation of a complete mission scenario.
Abstract: Single phase transmission lines are used to transfer data or energy between two users. Transient conditions such as switching operations and short circuit faults cause the generation of the fluctuation on the waveform to be transmitted. Spatial voltage distribution on the single phase transmission line may change owing to the position and duration of the short circuit fault in the system. In this paper, the state space representation of the single phase transmission line for short circuit fault and for various types of terminations is given. Since the transmission line is modeled in time domain using distributed parametric elements, the mathematical representation of the event is given in state space (time domain) differential equation form. It also makes easy to solve the problem because of the time and space dependent characteristics of the voltage variations on the distributed parametrically modeled transmission line.
Abstract: OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.
Abstract: This study mainly concerns a safety device designed for child care. When children are out of sight or the caregivers cannot always pay attention to the situation, through the functions of this device, caregivers can immediately be informed to make sure that the children do not get lost or hurt, and thus, ensure their safety. Starting from this concept, a device is produced based on the relatively low-cost Bluetooth piconet system and a three-axis gyroscope sensor. This device can transmit data to a mobile phone app through Bluetooth, in order that the user can learn the situation at any time. By simply clipping the device in a pocket or on the waist, after switching on/starting the device, it will send data to the phone to detect the child’s fall and distance. Once the child is beyond the angle or distance set by the app, it will issue a warning to inform the phone owner.
Abstract: In seismic data processing, attenuation of random noise
is the basic step to improve quality of data for further application
of seismic data in exploration and development in different gas
and oil industries. The signal-to-noise ratio of the data also highly
determines quality of seismic data. This factor affects the reliability
as well as the accuracy of seismic signal during interpretation
for different purposes in different companies. To use seismic data
for further application and interpretation, we need to improve the
signal-to-noise ration while attenuating random noise effectively.
To improve the signal-to-noise ration and attenuating seismic
random noise by preserving important features and information
about seismic signals, we introduce the concept of anisotropic
total fractional order denoising algorithm. The anisotropic total
fractional order variation model defined in fractional order bounded
variation is proposed as a regularization in seismic denoising. The
split Bregman algorithm is employed to solve the minimization
problem of the anisotropic total fractional order variation model
and the corresponding denoising algorithm for the proposed method
is derived. We test the effectiveness of theproposed method for
synthetic and real seismic data sets and the denoised result is
compared with F-X deconvolution and non-local means denoising
algorithm.
Abstract: Relation between tolerance class and indispensable attribute and knowledge dependency in rough set model with tolerance relation is explored. After giving definitions and concepts of knowledge dependency and knowledge dependency degree for incomplete information system in tolerance rough set model by distinguishing decision attribute containing missing attribute value or not, the result of maintaining reflectivity, transitivity, augmentation, decomposition law and merge law for complete knowledge dependency is proved. Knowledge dependency degrees (not complete knowledge dependency degrees) only satisfy some laws after transitivity, augmentation and decomposition operations. An algorithm to solve attribute reduction in an incomplete decision table is designed. The correctness is checked by an example.