Miracle-dz/UniFAR-FTUs huggingface dataset:
Asthma control questionnaires in the management of asthma in children: A review

Several self‐administered questionnaires have been developed to assess childhood asthma control in a simple and standardized way. This review discusses the most commonly used questionnaires and explores their usefulness in asthma management in children. We conclude that the use of asthma control questionnaires in daily practice and in research contributes to the standardized evaluation of children with asthma and helps to track asthma symptoms, but validation studies in a wider range of settings are needed. Pediatr Pulmonol. 2015; 50:202–208. © 2014 Wiley Periodicals, Inc.
Co-developing agile stage-gate in Danish SMEs

Existing research on participatory innovation mainly investigates collaborative processes of new product development between innovative organisation and users. In this paper, we contribute to research on participatory innovation by focusing on the co-development of new process development, rather than new product development. Overall, our study outlines the potential of a participatory innovation framework for new process development in which a codeveloping network participate in planned interactions that (1) fit the purpose of the project and (2) includes opportunities for by-product interactions and meanings that emerge in and across participants in between the planned
The Ability of Moral Intensity to Predict Purchasing Rates of Online Music Consumers

A study involving 454 respondents gathered from a random sample of American adults using SurveyMonkey found that a single variable, which described moral intensity, was able to account for 26.4% of the variance in the purchasing rates for consumers who acquire music online. The predictive ability of moral intensity was found to be significantly higher than the corresponding rates for age, gender, education, income, disposable income, and fear of legal sanction. Keywords-moral intensity, music piracy, piracy prediction Many music piracy studies attempt to predict piracy rates by using behavior intention models as conceptual frameworks (3)(8). These models typically use easily-determined consumer demographics such as age, income, gender, or education and may also include some other measures such as computer usage rates, computing expertise, and possession of a broadband connection as independent variables which are used to infer behavioral intention that results in a predicted purchase/pirate behavioral choice. A critique of this type of study was given by (9), who stated that quantitative piracy research tended to focus on measuring piracy rates rather than examining the decision-making process itself. Other researchers, such as (3) and (10), included socio- psychological measures or ethical decision-making models along with demographics into their behavioral intention models to study piracy. A limited number of studies (10) have investigated the relationship between music piracy and ethical position, as defined by Forsyth's Ethical Ideologies. One problem associated with the use of Ethical Ideologies in software piracy studies is that for many consumers, the moral intensity of piracy was insufficient for the file sharing/piracy to be viewed as a moral issue (11). In these instances, the researcher ends up attempting to predict a piracy rate based on the resolution of a moral dilemma that is not part of the respondent's decision-making process. The purpose of this study was to determine whether moral intensity is an effective predictor of purchasing rates for online digital music. In addition, the predictive strength of moral intensity was compared against several other commonly-used variables found in music piracy studies. Finally, descriptive statistics for the lowest and highest moral intensity groups were compared to determine if moral intensity is better at predicting purchasing or piracy. While this study uses quantitative methodologies to determine the extent to which a measurement of moral intensity may be used to predict piracy, it also tested a variable commonly associated with the decision-making process, rather than using demographic data to predict purchasing rates. Thus, it shifts the focus of the discussion away from the piracy rates and towards factors that influence the decision to engage in piracy.
Title Camera calibration from surfaces of revolution

This paper addresses the problem of calibrating a pinhole camera from images of a surface of revolution. Camera calibration is the process of determining the intrinsic or internal parameters (i.e., aspect ratio, focal length, and principal point) of a camera, and it is important for both motion estimation and metric reconstruction of 3D models. In this paper, a novel and simple calibration technique is introduced, which is based on exploiting the symmetry of images of surfaces of revolution. Traditional techniques for camera calibration involve taking images of some precisely machined calibration pattern (such as a calibration grid). The use of surfaces of revolution, which are commonly found in daily life (e.g., bowls and vases), makes the process easier as a result of the reduced cost and increased accessibility of the calibration objects. In this paper, it is shown that two images of a surface of revolution will provide enough information for determining the aspect ratio, focal length, and principal point of a camera with fixed intrinsic parameters. The algorithms presented in this paper have been implemented and tested with both synthetic and real data. Experimental results show that the camera calibration method presented here is both practical and accurate.
On path planning: Adaptation to the environment using Fast Marching

This paper presents a novel methodology for fast path planning based on an offline predefined skeleton of the environment by means of the Fast Marching Square method. The FM2 skeleton concept is introduced whose intuition is a set which contains the shortest paths (in terms of time) of a given environment This way, the path planning algorithm is adapted to the environment where a robot will navigate. An algorithm to obtain this skeleton is detailed in order to be able to use it for path planning purposes. When planning paths over the skeleton, the results show that the time reduction is about 50% while the characteristics of the FM2 method remain: completeness, safeness, smoothness and absence of local minima. This paper also shows that the proposed method performs well in more than 2 dimensions.
Transport Infrastructure Role in Climate Resilience: A Case Study in Hungary

Climate change is very important and plays a significant role. First solution against it could be the mitigation in order to reduce the global environmental impact of climate change, which can only work effectively over long-time. Second option is adaptation. These solution can be distinguished in transport as well. In the future in Hungary the probability, the frequency and the caused damage of extreme weather condition will increase in-line with that the adverse economic, environmental and ecological impacts will worsen. The environmental damage will cause social and economic problems such as damaged infrastructure - not only road and railway, but author focusing on them in this paper - pause in social services (hospital, public transport). The disasters seriously affect the transport and with that a significant proportion of the domestic population. The aim of this article is to analyse the connection between the spatial distribution of transport infrastructure and vulnerable areas. The targeted research question if transport infrastructure would enlarge or help avoiding the effects of climate change.
Sentence boundary detection in chinese broadcast news using conditional random fields and prosodic features

This paper studies the use of condition random fields (CRF) and prosodic features for sentence boundary detection in Chinese broadcast news. Previous approaches mostly use first-order CRF and ignore the important context and sequential information. In this paper, we explore high-order CRF models to fully make use of the contextual and sequential information. Moreover, we show the effectiveness of CRF in sentence boundary detection by comparing it with various competitive models. The prosodic feature set is usually designed to be as exhaustive as possible in previous approaches. As a result, features may be highly correlated and some of them may be not effective. In this paper, we use a correlation-based feature selection method to select a subset with the most useful features. Finally, the use of the prosodic features, e.g., pitch, in Chinese sentence segmentation deserves further investigation because the tonal aspect of Chinese may complicate the expressions of pitch features. In this paper, we study the effectiveness of the prosodic features and rank their importance by an analysis of feature usage.
Longitudinal Evaluation of Behavior Support Intervention in a Public Middle School

Student discipline problems are common in public schools; they interfere with instruction, create an unsafe learning environment, and demand increased attention from staff. Effective schoolwide discipline practices have been designed, but in most cases, intervention efficacy has been evaluated in the short term. This report describes a longitudinal (4-year) evaluation of a behavior support program implemented with the entire student population in a public middle school. The number of student detentions issued for disruptive—antisocial behaviors, vandalism, and substance use decreased progressively during each academic year. In addition, student attendance increased each year, as well as the proportion of students earning positive reinforcement. Although it represents a nonexperimental analysis, this evaluation documents protracted effects from a schoolwide behavioral intervention and suggests that long-term maintenance from such intervention can be achieved.
Signal, noise and interference power analysis in MRT-based Massive MIMO systems

Massive MIMO is a promising technology for 5G. While its advantages of increasing capacity and reducing output power are clear, understanding its SNR requirements in practical cases lacks sufficient theoretical support. This paper computes the relative power levels of the different signal, interference and noise terms in a Massive MIMO system using Maximum-Ratio Transmission (MRT). This brings light on the operational region of the system. The MRT operation is shown to support a maximum number of users, which is function of the selected modulation and coding scheme. The related expression also leads to a bound for other linear precoders. The impact of channel estimation is shown to be related to the number of orthogonal pilot sequences and users. When both are equal it leads to a 3 dB degradation. At system level, this model directly impacts output power requirements and hence system trade-offs when determining the number of antennas to use.
Dauan 4 and the Emergence of Ethnographically-Known Social Arrangements across Torres Strait during the Last 600-800 Years

Abstract Excavations at Dauan 4 on the island of Dauan in the Top Western Islands of Torres Strait revealed a 700 year sequence created by marine specialists who ate turtle, dugong, fish and shellfish and employed mostly a flaked quartz technology. The presence of bipolar micro-cores less than 10mm in length reveals extreme reduction of quartz, possibly for manufacture of small skin cutting tools. While recent research indicates an antiquity of at least 4000 years for marine specialists in Torres Strait, Dauan 4 follows a suite of sites across the Strait demonstrating major cultural changes taking place within the last 600–800 years. These changes herald the emergence of ethnographically-known social arrangements marked by a rapid phase of site establishment and intensified site use consistent with population increase. Paralleling these changes was the appearance of new ritual sites linked spiritually to seascapes such as dugong bone arrangements, stone arrangements and shell arrangements. Such changes may have represented in part socially-mediated responses to a local expression of the Little Ice Age global climatic phenomenon.
Active-Model-Based Control for the Quadrotor Carrying a Changed Slung Load

In this paper, a simple active-model-based control scheme is developed for the quadrotor slung load (QSL) system. The scheme works to improve the rejection of the influences caused by the abruptly changed load as a complementary enhancement while maintaining the structure and parameters of the original controller. A linearized model is first constructed with respect to the hovering state of a quadrotor. Modeling error is then introduced to describe the uncertainties caused by the load change and the simplified model. The modeling error is actively estimated by a Kalman filter (KF), while the estimation is further integrated into a normal controller, to enhance its performance of disturbance rejection. Experiments are conducted on a quadrotor controlled by the Pixhawk, which is one of the most popular controllers commercially available on the market. The improvements of the proposed scheme are shown by the comparisons between the controls with and without the active-model-based enhancement. The experiments also indicate that, with its simple structure and less computational algorithm, this active-model-based enhancement would be a feasible approach to enhance the commercial UAV controller to handle more uncertainties.
Modeling the impact of VANET-enabled traffic lights control on the response time of emergency vehicles in realistic large-scale urban area

In the last decade, intelligent transportation systems (ITS) have progressed at a rapid rate, which aim to improve transportation activities in terms of safety and efficiency. Car-to-car and car-to-infrastructure communications are important components of the ITS architecture. Communication between cars and traffic lights is one of the important V2I applications which helps to have dynamic and automatic traffic lights that can create several benefits such as minimizing the traffic jam, reducing fuel consumption and emissions, etc. This paper deals with decreasing the response time of the emergency cars by changing the traffic lights status with employing the communication technologies. The contribution of this paper is twofold: First, the effect of the changing traffic lights status to green for emergency cars is investigated by using traffic simulator (SUMO). Second, this paper uses OMNET++ (Network Simulator) in order to simulate the mentioned scenario as a VANET (with 802.11p standard) by using Veins framework to run SUMO and OMNET++ in parallel. This study has developed the Veins framework by adding a new module to OMNET++ to consider the traffic lights which are simulated in SUMO. Moreover this study has developed a new program written in Python which is connected to SUMO and controls the traffic simulation. This program uses SUMO to simulate a microscopic traffic (by considering every single vehicle movements) and also a city with intelligent traffic lights. Additionally, several statistics about traffic simulation is created for each car such as traveling time, waiting time, emissions, fuel consumption; or complete amount of car emissions in the street during the simulation, fuel consumption, number of vehicles and so on, for each street. This paper uses Manhattan realistic map to describe the mentioned program, then uses realistic map and realistic traffic demand of Cologne, Germany, to obtain a realistic and reliable result.
Smoothing method for minimizing the sum of the r largest functions

Given a collection of m functions defined on ℜ n , we consider the problem of minimizing the sum of the r largest functions of the collection. This problem has significant applications in the science of facility location. In this article, we reformulate this problem as a nonsmooth problem only involving the maximum function max{0, t} and then develop a globally convergent smoothing method for the case that all of g i (x) are convex functions. This method is specifically applied to the collection of Euclidean distance functions defined by location models. Our computational experiments and numerical comparisons with the successful SeDuMi software indicate that the method is very promising and is able to solve problems of dimension n up to 10,000 efficiently.
Potential impacts of different spring grazing strategies on lamb finishing in hill country

How does the pasture cover at the beginning of lambing and the grazing strategy used in early spring influence the ability of a hill country sheep and beef farm to finish lambs? The results from an intensive pasture-mowing trial investigating three defoliation intensities (Lax, Moderate and Intense) starting from two herbage masses (1200 or 1500 kg DM/ha) during early spring were used to provide data on potential pasture consumption and feed quality from lambing to weaning for a breeding ewe flock. Using simulation modelling, this pasture data was used to estimate the potential lamb and ewe liveweight changes from birth to weaning at each of three different stocking rates (4.5, 8 and 10.5 twin-bearing ewes/ha) that closely represented the three defoliation intensities originally studied in a mowing trial. The impacts of these early-spring herbage masses and grazing intensities/ stocking rates on subsequent feed requirements and potential lamb finishing during the later summer and autumn period in four contrasting geo-climatic regions of New Zealand were then further investigated using simulation modelling. Variations in ewe and lamb weaning weights were evident and reflected the amount of pasture available through the different grazing management approaches. For all four geoclimatic regions studied, the Intense grazing, high stocking rate strategy generally produced the greatest gross revenue per ha from lamb sales out of the three grazing strategies investigated, though not significantly greater than the moderate stocking rate in summer dry environments. However, under Intense grazing, a high pasture cover (1500 kg DM/ha), in comparison to a low pasture cover (1200 kg DM/ha) at the start of ewe lactation further improved the gross revenue received from lamb sales, especially in the Canterbury and Waikato environments but less so in the Hawke’s Bay and Southland environments. These variations demonstrate how iterations based on the same starting properties impact on weaning weight of lambs and post-weaning pasture growth and/or feed quality.
Natural Language Web Interface for Database (NLWIDB)

It is a long term desire of the computer users to minimize the communication gap between the computer and a human. On the other hand, almost all ICT applications store information in to databases and retrieve from them. Retrieving information from the database requires knowledge of technical languages such as Structured Query Language. However majority of the computer users who interact with the databases do not have a technical background and are intimidated by the idea of using languages such as SQL. For above reasons, a Natural Language Web Interface for Database (NLWIDB) has been developed. The NLWIDB allows the user to query the database in a language more like English, through a convenient interface over the Internet.
Gossip-based Computation of Average: a Closest Point Search Approach

Due to simplicity and robustness, gossip based algorithms for data aggregation have recently received significant attention for applications in ad hoc and wireless sensor networks. Nodes in such networks operate under limited communication, computation, and energy resources. However, a common drawback of many gossip based protocols is the waste of energy in passing around redundant information multiple times. Thus gossip algorithms need to be re-designed in order to be applicable for energy constraint networks. In this paper, we study the averaging problem under the gossip constraint. In a network of n nodes, each node ui holds a value xi at the beginning and the objective is to compute the global average of these values in a distributed manner, while consuming least amount of energy. By formulating the problem as a closest point search in a n- dimensional cube, we demonstrate that the true average can be computed in the optimal O(log n) rounds without any probability involved. Moreover, the proposed algorithm is shown to outperform existing approaches for wireless sensor network in terms of the number of radio transmissions.
Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China

The improvement of pedestrian safety plays a crucial role in developing a safe and friendly walking environments, which can contribute to urban sustainability. A preliminary step in improving pedestrian safety is to identify hazardous road locations for pedestrians. This study proposes a framework for the identification of vehicle-pedestrian collision hot spots by integrating the information about both the likelihood of the occurrence of vehicle-pedestrian collisions and the potential for the reduction in vehicle-pedestrian crashes. First, a vehicle-pedestrian collision density surface was produced via network kernel density estimation. By assigning a threshold value, possible vehicle-pedestrian hot spots were identified. To obtain the potential for vehicle-pedestrian collision reduction, random forests was employed to model the density with a set of variables describing vehicle and pedestrian flows. The potential for crash reduction was then measured as the difference between the observed vehicle-pedestrian crash density and the prediction produced by the random forests models. The final hotspots were determined by excluding those with a crash reduction value of no more than zero. The method was applied to the identification of hazardous road locations for pedestrians in a district in Shanghai, China. The result indicates that the method is useful for decision-making support.
Kobe University Repository : Kernel タイトル Tit le A hybrid approach to protein name ident ificat ion in biomedical texts

This paper presents a hybrid approach to identifying protein names in biomedical texts, which is regarded as a crucial step for text mining. Our approach employs a set of simple heuristics for initial detection of protein names and uses a probabilistic model for locating complete protein names. In addition, a protein name dictionary is complementarily consulted. In contrast to previously proposed methods, our proposed method avoids the use of natural language processing tools such as part-of-speech taggers and syntactic parsers and solely relies on surface clues, so as to reduce the processing overhead. Moreover, we propose a framework to automatically create a large-scale corpus annotated with protein names, which can be then used for training our probabilistic model. We implemented a protein name identification system, named P, based on our proposed method and evaluated it by comparing with a system developed by other researchers on a common test set. The experiments showed that the automatically constructed corpus is equally useful in training as compared with manually annotated corpora and that e ffective performance can be achieved in identifying compound protein names with P.