nils-herrmann/clean_scirepeval huggingface dataset:
Residential construction lags and the real options channel of housing supply

Housing supply decisions consist of both an extensive margin (new housing starts) and an intensive margin (construction intensity of incomplete houses) While it is well known that housing starts have declined dramatically during the 2006 2009 housing bust, the intensive margin of residential investment has not been studied in the literature. In this paper, we document that construction intensity of incomplete houses has also fallen significantly during the bust. Using the Census micro data for construction lags of single family houses across the US, we show that average construction lags for completed houses increased during the bust, and that this increase comes from long deferrals of several houses under construction, especially those that were unsold at the early stage of construction. Motivated by these new facts, we study a time to build model of residential construction where investment in each stage is irreversible. The model predicts that as the level of uncertainty increases, the "wait and see" channel becomes relatively more important for the intensive margin than for housing starts. Calibrated and estimated to match the house price dynamics and the construction lag distribution during the recent recession, the model suggests that the realoptions mechanism played an important role in the dynamics of residential investment during the recent bust. Several housing supply implications based on the model follow.
Residential construction lags across the US and their implications for housing supply

Housing supply decisions consist of both an extensive margin (new housing starts) and an intensive margin (construction intensity of incomplete houses) While it is well known that housing starts have declined dramatically during the 2006 2009 housing bust, the intensive margin of residential investment has not been studied in the literature. In this paper, we document that construction intensity of incomplete houses has also fallen significantly during the bust. Using the Census micro data for construction lags of single family houses across the US, we show that average construction lags for completed houses increased during the bust, and that this increase comes from long deferrals of several houses under construction, especially those that were unsold at the early stage of construction. Motivated by these new facts, we study a time to build model of residential construction where investment in each stage is irreversible. The model predicts that as the level of uncertainty increases, the `wait and see' channel becomes relatively more important for the intensive margin than for housing starts. Calibrated to match the house price dynamics during the recent recession, the model accounts for the majority of the observed increase in construction lags, which suggests that the real options mechanism played an important role in the dynamics of residential investment during the recent bust. Several housing supply implications based on the model follow.
A psychophysiology based driver model for the design of driving assistance systems

Lane departures while driving a car may be caused directly by errors in steering behaviour and indirectly as a consequence of driver distraction. Designing advanced driving assistance systems (ADAS) is a way to avoid these situations. One of the key problems is to monitor and predict driver behaviour in order to make the ADAS intervene in a timely and efficient way. Our approach to achieve this goal is to incorporate a driver model in the design process. The model represents the visual and motor determinants of steering control. It has been used as the foundation of two types of ADAS: 1. a haptic shared control system that exerts forces on the steering wheel in such a way that the automation blends into the driver's sensorimotor control loop, providing continuous support to lane keeping, and 2. a method of distraction estimation based on the comparison between steering behaviour and the model prediction.  Based on current knowledge of human sensorimotor functions, the model represents the visual anticipation of the road curvature fed by the angular deviation of a far point, the visual compensation of lateral position error fed by the angular deviation of a near point, and a neuromuscular system that transforms the output of the visual subsystem into a steering wheel torque. For haptic shared control, the approach consisted in designing a control law that optimizes performance and cooperation criteria, taking into account the predictions of the driver model. A comparison was performed between the driver behaviour when using this system and when using a shared control law that did not incorporate a driver model. For distraction estimation, an identification of the driver model's parameters was conducted in five different distraction conditions: no distraction and cognitive, visual, motor and visuomotor distractions. The torque prediction error and the parameters values were analysed.  The results concerning haptic shared control suggest that cooperation between the driver and the automation can be improved by the inclusion of the driver model in the control law. In particular, when the level of haptic authority was set at a high level, the driver acted 27% more in coherence with the system. For the second application, the results show that the model prediction error is commensurate to a modification of steering behaviour caused by distraction. The parametric analysis suggests that an online identification of the model may be used to some extent to discriminate between different types of distraction.  Adopting a model based approach to design ADAS is promising. The current model is limited to the representation of sensorimotor processes in humans. As such, it is adapted to be used in the context of real time control embedded systems. In the future, it could be extended by incorporating a tactical analysis of the driving context.
A Novel Method for Smoothing Raw GPS Data with Low Cost and High Reliability
Venue: 2016 IEEE 84th Vehicular Technology Conference (VTC Fall)

The precise spatio temporal position data of vehicles is useful for most studies, such as wireless link lifetime and node degree in vehicular ad hoc networks. However, due to the system errors and random errors, the existing Global Positioning System (GPS) only provides the positional accuracy about 10m or even worse. In this paper, to address the issue of positional accuracy, a Clustering and Approximating (C A) algorithm is proposed. We first divide each road into several small parts which are described by linear functions. Then a linear regression algorithm is utilized to approximate traces under system errors, which is reliable for reducing GPS errors. Particularly, when two roads are very close, GPS points may be mapped on adjacent roads. A clustering algorithm is taken to separate GPS points and their positions are revised by the iterative utilization of the linear regression algorithm. In the end, the method mentioned above smoothes raw GPS data of buses in Taiwan to make it available for further researches. Compared with existing methods, the method described in this paper characterized with low cost and high reliability in different situations. Besides, its simple model will make the process of revising data more convenient.
A novel secure message delivery and authentication method for vehicular ad hoc networks
Venue: 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI)

In large scale vehicular ad hoc networks, in order to speed up the anonymous message authentication and realize scalability, the forwarding node combined signatures and with the help of the Road Side Units (RSU) for quick authentication and dissemination method still some key questions: when the vehicle sends a message to RSU authentication and dissemination, the forwarding nodes using combined signature mechanism sign messages greatly increases the transmission overhead message; RSU after verifying the authenticity and integrity of messages, it may dissemination a false authentication message to the vehicle in appropriate regions without being detected. To solve these problems, we propose a novel secure message delivery and authentication method. By using aggregate message authentication code technology to verify the authenticity and integrity of messages, reducing communication overhead; at the same time set up a pseudo RSU in the vicinity of RSU, to ensure the correctness of the authentication message transmission. Through the security analysis and simulation experiments show that the proposed method can significantly reduce the communication overhead of message transmission and improve the authenticity of the message, prove its validity.
Pengaruh Endorphin Massage Terhadap Penurunan Intensitas Nyeri Punggung Ibu Hamil

Keluhan yang paling sering terjadi pada ibu hamil trimester 3 adalah nyeri punggung. Apabila tidak segera diatasi dapat berakibat nyeri kronis. Salah satu cara mengatasi nyeri punggung adalah dengan teknik pijatan lembut yang disebut Endorphin massage untuk melepaskan senyawa endorfin yang merupakan pereda rasa sakit alami di dalam tubuh. Survey awal yang dilakukan peneliti didapatkan sebagian besar ibu hamil mengalami nyeri berat. Tujuan penelitian ini untuk mengetahui pengaruh pemberian Endorphin massage terhadap penurunan intensitas nyeri punggung pada ibu hamil trimester 3. Desain yang digunakan adalah pra eksperimen dengan pendekatan one grup pretest posttest design. Sampel diambil dari populasi yang memenuhi kriteria inklusi di BPS Ny. Khusnul Imarwatin pada bulan April sampai Mei 2016 sebanyak 28 responden dengan consecutive sampling. Variabel independen yaitu teknik Endorphin massage sedangkan variabel dependen yaitu nyeri punggung. Instrument menggunakan SOP teknik Endorphin massage dan lembar observasi Skala Bourbanis. Hasil penelitian menunjukkan bahwa sebelum dilakukan Endorphin massage sebagian besar ibu hamil trimester 3 mengalami nyeri berat dan setelah dilakukan Endorphin massage berkurang menjadi nyeri sedang. Hasil uji Wilcoxon sign rank test dengan =0,05 menunjukkan p=0,000 sehingga p<0,05 artinya ada pengaruh Endorphin massage terhadap penurunan intensitas nyeri punggung. Endorphin massage merupakan salah satu alternatif nonfarmakologi untuk mengatasi nyeri sehingga disarankan agar Bidan memberikan Health education dan mengajarkan pasangan ibu hamil Endorphin massage untuk meringankan gejala nyeri punggung.  Endorphin massage, Nyeri punggung, Kehamilan
Micro macro modeling of brittle creep and progressive failure subjected to compressive loading in rock
Venue: Environmental Earth Sciences

A major challenge of rock mechanics is to link the time dependent crack growth with macroscopic mechanical behavior. A new micro macro method is presented to model the brittle creep and progressive failure of rock in compression. The Ashby's microcrack model, Charles' crack growth law and a new theoretical relation are incorporated into this method. This new relation is suggested to establish the linkage between microcrack growth and macroscopic strain based on the macroscopic and micromechanical definition of rock damage in this paper. The long term strength of rock could also be calculated using this suggested micro macro method. Rationality of the suggested method is verified through the theoretical and experimental results. Furthermore, effects of confining pressure on brittle creep and progressive failure of Sanxia granite is investigated. Theoretical corresponding relation between crack growth, damage and strain is investigated. And theoretical foundation of deep buried construction design is also discussed in this paper.
A Micromechanical Method to Predict Macroscopic Behavior of Brittle Creep Failure in Rock

Brittle creep in rock has great significance for the prediction of important geohazards and stability of deep underground excavations. A major challenge in this area is to link the time dependent cracking with macroscopic mechanical behavior. In this paper, Ashby and Sammis' microcrack model and Charles' crack growth law are employed to investigate the time dependent cracking during brittle creep in rock. Based on the macroscopic and micromechanical definition of damage in rock, a new theoretical model is suggested to establish the linkage between microcrack length and macroscopic strain. In order to verify the rationality of the suggested model, comparison between theoretical and experimental results is presented. Using this new model, brittle creep of Sanxia granite is investigated and discussed in detail. It is found that evolutions of wing crack length, strain, and damage perform a similar process during brittle creep and could be divided into three phases. Effects of model parameters on creep failure behaviors also are studied.
The Evolutionary Ecology of Plant Disease: A Phylogenetic Perspective.
Venue: Annual review of phytopathology

An explicit phylogenetic perspective provides useful tools for phytopathology and plant disease ecology because the traits of both plants and microbes are shaped by their evolutionary histories. We present brief primers on phylogenetic signal and the analytical tools of phylogenetic ecology. We review the literature and find abundant evidence of phylogenetic signal in pathogens and plants for most traits involved in disease interactions. Plant nonhost resistance mechanisms and pathogen housekeeping functions are conserved at deeper phylogenetic levels, whereas molecular traits associated with rapid coevolutionary dynamics are more labile at branch tips. Horizontal gene transfer disrupts the phylogenetic signal for some microbial traits. Emergent traits, such as host range and disease severity, show clear phylogenetic signals. Therefore pathogen spread and disease impact are influenced by the phylogenetic structure of host assemblages. Phylogenetically rare species escape disease pressure. Phylogenetic tools could be used to develop predictive tools for phytosanitary risk analysis and reduce disease pressure in multispecies cropping systems.
PROPOSED DISTRIBUTED DATA MINING IN CREDIT CARD FRAUD DETECTION

Mining is popularly used to combact frauds because of its effectiveness. Using data mining techniques or model the Credit card fraud can be detected. The Credit card provides cashless shopping all over the world. Hence the risk of fraud using Credit card is been increasing. The clustering model used to classify the legal and fraudulent transaction using data cauterisation of region of parameter. Hidden Markov Model can detect whether an incoming transaction is fraudulent or not with low false alarm. HMM does not require fraud signatures and still it is capable to detect the frauds by bearing in mind a cardholder's spending habit. An HMM is initially trained with the normal behaviour of a cardholder. If an incoming credit card transaction is not accepted by the trend HMM with sufficiently high probability, it is consider to be fraudulent. At the same time, try to ensure that genuine transactions are not rejected. The financial losses due to Credit card fraud effect not only the individuals but also the merchants. Therefore the security measures need to be taken to detect the Credit card fraud.
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect Related Applications
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.
Hyperspectral Face Databases for Facial Recognition Research
Venue: Face Recognition Across the Imaging Spectrum

Spectral imaging (SI) enables us to collect various spectral information at specific wavelengths by dividing the spectrum into multiple bands. As such, SI offers a means to overcome several major challenges specific to current face recognition systems. However, the practical usage of hyperspectral face recognition (HFR) has, to date, been limited due to database restrictions in the public domain for comparatively evaluating HFR. In this chapter, we review four publically available hyperspectral face databases (HFDs) CMU, PolyU HSFD, IRIS M, and Stanford databases toward providing information on the key points of each of the considered databases. In addition, a new large HFD called IRIS HFD 2014, is introduced. IRIS HFD 2014 can serve as a benchmark for statistically evaluating the performance of current and future HFR algorithms and will be made publicly available.
Stellar laboratories VII. New Kr iv vii oscillator strengths and an improved spectral analysis of the hot, hydrogen deficient DO type white dwarf RE 0503 289

For the spectral analysis of high resolution and high signal to noise (S/N) spectra of hot stars, state of the art non local thermodynamic equilibrium (NLTE) model atmospheres are mandatory. These are strongly dependent on the reliability of the atomic data that is used for their calculation.  New Kr iv vii oscillator strengths for a large number of lines enable us to construct more detailed model atoms for our NLTE model atmosphere calculations. This enables us to search for additional Kr lines in observed spectra and to improve Kr abundance determinations.  We calculated Kr iv vii oscillator strengths to consider radiative and collisional bound bound transitions in detail in our NLTE stellar atmosphere models for the analysis of Kr lines that are exhibited in high resolution and high S/N ultraviolet (UV) observations of the hot white dwarf RE 0503 289.  We reanalyzed the effective temperature and surface gravity and determined T eff 70000 2000 K and log g cm s 2 7.5 0.1. We newly identified ten Kr v lines and one Kr vi line in the spectrum of RE 0503 289. We measured a Kr abundance of 3.3 0.3 (logarithmic mass fraction) We discovered that the interstellar absorption toward RE 0503 289 has a multi velocity structure within a radial velocity interval of 40 km s 1 v rad 1  Reliable measurements and calculations of atomic data are a prerequisite for state of the art NLTE stellar atmosphere modeling. Observed Kr v vii line profiles in the UV spectrum of the white dwarf RE 0503 289 were simultaneously well reproduced with our newly calculated oscillator strengths.
Preparing For Crises In The Schools A Manual For Building School Crisis Response Teams

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A hybrid approach to Vietnamese word segmentation
Venue: 2016 IEEE RIVF International Conference on Computing Communication Technologies, Research, Innovation, and Vision for the Future (RIVF)

Word segmentation is the very first task for Vietnamese language processing. Word segmented text is the input of almost other NLP tasks. This task faces some challenges due to specific characteristics of the language. As in many other Asian languages such as Japanese, Korean and Chinese, white spaces in Vietnamese are not always used as word separators and a word may contain one or more syllables. In this paper, we propose an efficient hybrid approach to detect word boundary for Vietnamese texts using logistic regression as a binary classifier combining with longest matching algorithm. First, longest matching algorithm is used to catch words that contain more than two syllables in input sentence. Next, the system utilizes the classifier to determine the boundary of 2 syllable words and proper names. Then, the predictions having low confidence conducted by the classifier are verified by a dictionary to get the final result. Our system can achieve an F measure of 98.82% which is the most accurate result for Vietnamese word segmentation to the best of our knowledge. Moreover, the system also has a high speed. It can run word segmentation for nearly 34k tokens per second.
A Character Level Based and Word Level Based Approach for Chinese Vietnamese Machine Translation
Venue: Comput. Intell. Neurosci.

Chinese and Vietnamese have the same isolated language; that is, the words are not delimited by spaces. In machine translation, word segmentation is often done first when translating from Chinese or Vietnamese into different languages (typically English) and vice versa. However, it is a matter for consideration that words may or may not be segmented when translating between two languages in which spaces are not used between words, such as Chinese and Vietnamese. Since Chinese Vietnamese is a low resource language pair, the sparse data problem is evident in the translation system of this language pair. Therefore, while translating, whether it should be segmented or not becomes more important. In this paper, we propose a new method for translating Chinese to Vietnamese based on a combination of the advantages of character level and word level translation. In addition, a hybrid approach that combines statistics and rules is used to translate on the word level. And at the character level, a statistical translation is used. The experimental results showed that our method improved the performance of machine translation over that of character or word level translation.
From plastic bottle recycling to policy support: An experimental test of pro environmental spillover

Little research has investigated the extent to which performance of one pro environmental behavior (PEB) spills over to increase or decrease support for pro environmental policies or the mechanisms underlying spillover effects. In this study, 283 U.S. university students were randomly assigned via situational manipulations to either recycle a water bottle, throw the bottle in the trash, or a control condition. All participants then completed surveys assessing environmental identity, guilt, and environmental worry, as well as support for a pro environmental campus green fund. Results showed evidence for negative spillover among Democrats only, which was mediated by environmental identity: Democrats who recycled the water bottle had lower environmental identities and were less supportive of the green fund than those in the control condition. Neither Republicans nor Independents displayed spillover. The results have implications for those interested in increasing small, easy PEBs in hopes of gaining future support for environmental policies.