Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-Dimensional Reconstruction of Building Roofs from Airborne LiDAR Data Based on a Layer Connection and Smoothness Strategy

A new approach for three-dimensional (3-D) reconstruction of building roofs from airborne light detection and ranging (LiDAR) data is proposed, and it includes four steps. Building roof points are first extracted from LiDAR data by using the reversed iterative mathematic morphological (RIMM) algorithm and the density-based method. The corresponding relations between points and rooftop patches are then established through a smoothness strategy involving “seed point selection, patch growth, and patch smoothing. ” Layer-connection points are then generated to represent a layer in the horizontal direction and to connect different layers in the vertical direction. Finally, by connecting neighboring layer-connection points, building models are constructed with the second level of detailed data. The key contributions of this approach are the use of layer-connection points and the smoothness strategy for building model reconstruction. Experimental results are analyzed from several aspects, namely, the correctness and completeness, deviation analysis of the reconstructed building roofs, and the influence of elevation to 3-D roof reconstruction. In the two experimental regions used in this paper, the completeness and correctness of the reconstructed rooftop patches were about 90% and 95%, respectively. For the deviation accuracy, the average deviation distance and standard deviation in the best case were 0.05 m and 0.18 m, respectively; and those in the worst case were 0.12 m and 0.25 m. The experimental results demonstrated promising correctness, completeness, and deviation accuracy with satisfactory 3-D building roof models.
Prioritized network-based vertical handover decision in multi-access wireless networks

The integration of wireless worldwide interoperability for microwave access network (Wi-MAX and Long Term Evolution (LTE) in an all IP based heterogeneous networks that require seamless mobility is predicated on enabling the connection and retrieval of data by a mobile user not mindful of the medium or technology used. This phenomenon facilitates freedom of movement while maintaining service continuity. However, the interoperability between multiple access technologies should be able to realize the vision of 4G technology and beyond to allow mobile user equipment (UE) to roam freely when intersecting the cell-boundaries of different network platforms without losing the service. To achieve such task, a proposed mobility management system designed to detect conditions of the network early enough and effect changes to handover parameters while maintaining the network connectivity is being highlighted. The proposed system investigates how the signal strength threshold (RSSTh) influences handover decision for a prioritized network with regards to distance and velocity. Computer simulation based on a designed algorithm for vertical handover optimization is being implemented to trigger the inter-radio access technology (RAT) handover for evaluating the performance of next generation wireless network systems. The results show that the prioritized network stand to be the preferred network as the UE is connected to it most of the time.
Modeling and Control of Aggregated Heterogeneous Thermostatically Controlled Loads for Ancillary Services

This paper presents a novel modeling and con- trol approach for the aggregation of large numbers of hetero- geneous thermostatically controlled loads, such as refrigera- tors, electric water heaters, and air conditioners, and their usage for Demand Response. Unlike traditional Demand Re- sponse methods that act on time scales of hours, this ap- proach is able to provide short-term (e.g., second-to-second) ancillary services, such as balancing and frequency control. A statistical modeling approach based on Markov Chains is used to describe the evolution of probability mass in a tem- perature state space. The Markov state transition matrix is identified using state information from the population of thermostatically controlled loads. A predictive controller is used to control the aggregate population of loads such that it tracks a signal. A simulation example shows the applicabil- ity of the approach to realistic systems, and includes a com- parison of control performance depending on available state information and controller parameterization.
The Influence of Partners? Views on Chinese Auditors? Judgments Related to Professional Scepticism

Professional scepticism remains one of the most important and controversial topics in auditing. This study examines the influence of partners? views on auditors? professional scepticism in China. This examination is important given the hierarchical structures of audit firms, and even more important in China given the strong cultural emphasis on subordination and obedience. Specifically, this study invokes social contingency theory to provide insights into partner influences on auditors from an accountability perspective. It is expected that auditors with knowledge of partners? views are likely to be susceptible to pressure to align their judgments to the partners? views, and such pressure influences auditors? professional scepticism when exercising judgments. A between-subjects experiment was conducted with practicing auditors in China. The independent variable, partners? views on professional scepticism, was manipulated across three groups: (1) a control group, in which there is no information about partners? view, (2) a group in which partners? known views reflect low emphasis on professional scepticism, or (3) a group in which partners? known views reflect high emphasis on professional scepticism. The results provide evidence that when partners? views on professional scepticism are known, auditors perceive considerable amount of pressure to follow the partners? views. Further, the results show that when partners? views reflect low emphasis on professional scepticism, auditors? levels of professional scepticism are significantly lower compared to when partners? views are unknown. However, when partners? views reflect high emphasis on professional scepticism, auditors? levels of PS do not significantly differ from when partners? views are unknown. Furthermore, the results show that when auditors learn partners? views, increased intensity of perceived pressure can strengthen the effects of partners? influences on auditors? professional scepticism. The findings of this study have important implications for auditing regulators, professionals, and audit firms.
The MD-join: an operator for complex OLAP

OLAP queries (i.e. group-by or cube-by queries with aggregation) have proven to be valuable for data analysis and exploration. Many decision support applications need very complex OLAP queries, requiring a fine degree of control over both the group definition and the aggregates that are computed. For example, suppose that the user has access to a data cube whose measure attribute is Sum(Sales). Then the user might wish to compute the sum of sales in New York and the sum of sales in California for those data cube entries in which Sum(Sales)>$1,000,000. This type of complex OLAP query is often difficult to express and difficult to optimize using standard relational operators (including standard aggregation operators). In this paper, we propose the MD-join operator for complex OLAP queries. The MD-join provides a clean separation between group definition and aggregate computation, allowing great flexibility in the expression of OLAP queries. In addition, the MD-join has a simple and easily optimizable implementation, while the equivalent relational algebra expression is often complex and difficult to optimize. We present several algebraic transformations that allow relational algebra queries that include MD-joins to be optimized.
Simultaneous planning and mapping (SPAM) for a manipulator by best next move in unknown environments

In this paper, we propose a SPAM (Simultaneous Planning and Mapping) technique for a manipulator type robot working in an uncertain environment via a Best Next Move algorithm. Demands for a smart decision to move a manipulator such as humanoid arms in uncertain or crowded environments call for a simultaneous planning and mapping technique. We assume no a priori knowledge of either the obstacles or the rest of the environment exits. For rapid map building and path planning, we use a skin type setup based on 3D depth camera sensors that completely encompass the entire body of a manipulator. The 3D sensors capture the point clouds used to create an instantaneous c-space map whereby a Best Next Move algorithm directs the motion of the manipulator. The Best Next Move algorithm utilizes the gradient of the density distribution of the k-nearest-neighborhood sets in c-space. It has tendency to travel along the direction by which the point clouds spread in space, thus rendering faster mapping of c-space obstacles. The proposed algorithm is compared with several sensor based algorithms for performance measurement such as map completion rate, distribution of samples, total nodes, etc. Some improved performances are reported for the proposed algorithm. Several possible applications include semi-autonomous tele-robotics planning, humanoid arm path planning, among others.
An Investigation of Cell Efficiency of Pathor Kuchi Leaf (PKL) Cell for Electricity Generation

In recent times, there has been a increasing trend towards attention for the production of electricity from alternate/innovative sources of renewable energy due to the everincreasing need for sustainable yet environment-friendly and lowcost production approaches (i.e., solar, wind, wave, hydro-power etc.). Pathar Kuchi Leaf (PKL) is one such promising source of electricity generation where electro-chemical conversion of energy provide the means to work as an alternate source of cell/battery. Especially in the context of a developing country like Bangladesh, this new form of biomass energy (PKL) possesses a great potential to fulfill the energy demand of rural people, who live under the poverty line. However, the key performance criteria for PKL cell is the assurance of efficient generation of electricity, since it plays a key role in supplying cleaner and proficient electric power to the consumers. Therefore, this paper proposes an experimental study of cell efficiency of PKL (Pathor Kuchi Leaf), on top of the previous analysis provided on this topic in the literature. To be precise, a thorough analysis has been performed in this paper to assess the performance of PKL cell in terms of voltaic efficiency, coulombic efficiency, and energy efficiency. The results from experimental data suggests a nearperfect energy efficiency of PKL cell for our proposed test-bed. With respect to the scope of the work, the overall aim has been to introduce/establish this emerging form of biomass energy to the modern world and discuss it’s important characteristics.
Model-based diagnosis of hybrid dynamical networks for fault tolerant control

A method for determining (diagnosing) the operational mode of a hybrid dynamical network using model based diagnosis is presented. This methodology unifies discrete diagnosis capabilities with the continuous time dynamics of hybrid dynamical networks. This method is novel in that the diagnosis is not performed on the output trajectory of the network but rather on the fundamental governing dynamics of the network. This novelty allows for the diagnosis of arbitrary switching events in the network. The chosen methodology can be partially decentralised and provides optimal diagnoses even when only a portion of the network can be observed. This offers performance and implementation benefits for large distributed networks. Computational results are presented for the case where the mode changes are purely structural. That is, where only the interconnection structure of the network is changing. The results indicate that this methodology has some benefits for the faulttolerant control of hybrid dynamical networks.
Sparse Data and Smoothing in Statistical Part-of-Speech Tagging*

This article reports on a series of experiments in statistical part-of-speech tagging of Swedish texts, with different probabilistic models and different smoothing schemes for both lexical and contextual probabilities. The most important conclusions are that lexical and contextual probabilities require different smoothing methods and that smoothing is only crucial for lexical probabilities. Of the particular smoothing methods tested in the experiments, Good-Turing estimation achieves the best results for the lexical model, while a simple additive smoothing scheme gives the best performance for the contextual model.
Metamaterial Apertures for Computational Imaging

Compressed Sampling It is often said that a picture is worth a thousand words. But images often contain a lot of redundant information—effectively creating huge data files of meaningless information. While algorithms can compress the size of a file without loss of information, such processing is done after the picture has been taken. Hunt et al. (p. 310) used a metamaterial sensor to compress the sampled scene directly, obviating the need for postprocessing. Tuning the response of the metamaterial allowed imaging of a scene with a 40:1 compression ratio, which may mean that finding that needle in a haystack may be much easier using a metamaterial camera. Metamaterial-based sensors can be used for compressive image reconstruction. By leveraging metamaterials and compressive imaging, a low-profile aperture capable of microwave imaging without lenses, moving parts, or phase shifters is demonstrated. This designer aperture allows image compression to be performed on the physical hardware layer rather than in the postprocessing stage, thus averting the detector, storage, and transmission costs associated with full diffraction-limited sampling of a scene. A guided-wave metamaterial aperture is used to perform compressive image reconstruction at 10 frames per second of two-dimensional (range and angle) sparse still and video scenes at K-band (18 to 26 gigahertz) frequencies, using frequency diversity to avoid mechanical scanning. Image acquisition is accomplished with a 40:1 compression ratio.
Arteries provide essential guidance cues for lymphatic endothelial cells in the zebrafish trunk

The endothelial cells of the vertebrate lymphatic system assemble into complex networks, but local cues that guide the migration of this distinct set of cells are currently unknown. As a model for lymphatic patterning, we have studied the simple vascular network of the zebrafish trunk consisting of three types of lymphatic vessels that develop in close connection with the blood vasculature. We have generated transgenic lines that allow us to distinguish between arterial, venous and lymphatic endothelial cells (LECs) within a single zebrafish embryo. We found that LECs migrate exclusively along arteries in a manner that suggests that arterial endothelial cells serve as the LEC migratory substrate. In the absence of intersegmental arteries, LEC migration in the trunk is blocked. Our data therefore demonstrate a crucial role for arteries in LEC guidance.
The Effects of Performance Expectations on Total Compensation of Division I–Football Bowl Subdivision Head Coaches

The literature examining executive and upper management compensation has looked at a variety of factors. Within sport, coaches are equivalent to these positions, with one of the major factors determining total compensation being on-field performance. However, little is known on how expectations of on-field performance compared with actual performance affect compensation. The purpose of this study is to analyze the effect of performance expectations on Division I–Football Bowl Subdivision head football coaches’ total compensation. Using data from 2006 to 2013, compensation increases when on-field performance expectations are exceeded. The impact of an additional on-field win relative to performance expectations is between 5.0 and 5.5% in terms of additional compensation. However, no statistically significant effect exists when comparing coaches at automatic qualifying versus nonautomatic qualifying schools. In addition, off-field measures of performance as well as individual and university characteristics affect total compensation.
The endocytic control of JAK/STAT signalling in Drosophila

Domeless (Dome) is an IL-6-related cytokine receptor that activates a conserved JAK/STAT signalling pathway during Drosophila development. Despite good knowledge of the signal transduction pathway in several models, the role of receptor endocytosis in JAK/STAT activation remains poorly understood. Using both in vivo genetic analysis and cell culture assays, we show that ligand binding of Unpaired 1 (Upd1) induces clathrin-dependent endocytosis of receptor-ligand complexes and their subsequent trafficking through the endosomal compartment towards the lysosome. Surprisingly, blocking trafficking in distinct endosomal compartments using mutants affecting either Clathrin heavy chain, rab5, Hrs or deep orange led to an inhibition of the JAK/STAT pathway, whereas this pathway was unchanged when rab11 was affected. This suggests that internalization and trafficking are both required for JAK/STAT activity. The requirement for clathrin-dependent endocytosis to activate JAK/STAT signalling suggests a model in which the signalling `on' state relies not only on ligand binding to the receptor at the cell surface, but also on the recruitment of the complex into endocytic vesicles on their way to lysozomes. Selective activation of the pool of receptors marked for degradation thus provides a way to tightly control JAK/STAT activity.
Competitive comparison in music: influences upon self-efficacy beliefs by gender

This study profiles gender differences in instrumental performance self-efficacy perceptions of high school students (N = 87) over the course of a three-day orchestra festival in which students competed against one another for rank-based seating and then rehearsed and performed as a group. Reported self-beliefs rose significantly for the sample over the course of the festival. Self-efficacy beliefs of females were significantly lower than those of males before the seating audition and first rehearsal, but were no longer different by the midpoint of the festival. Survey free-response data were coded according to Bandura's (1997) four sources of self-efficacy. A 52% drop in the frequency of student comments regarding competitive comparison appeared at the same point in which female self-efficacy beliefs were no longer different from those of males. Results support past research to suggest that males and females may respond differently to rank-based competition versus social support.
The TXM Platform: Building Open-Source Textual Analysis Software Compatible with the TEI Encoding Scheme

This paper describes the rationale and design of an XML-TEI encoded corpora compatible analysis platform for text mining called TXM. The design of this platform is based on a synthesis of the best available algorithms in existing textometry software. It also relies on identifying the most relevant open-source technologies for processing textual resources encoded in XML and Unicode, for efficient full-text search on annotated corpora and for statistical data analysis. The architecture is based on a Java toolbox articulating a full-text search engine component with a statistical computing environment and with an original import environment able to process a large variety of data sources, including XML-TEI, and to apply embedded NLP tools to them. The platform is distributed as an open-source Eclipse project for developers and in the form of two demonstrator applications for end users: a standard application to install on a workstation and an online web application framework.
Global term weights for document retrieval learned from TREC data

A key element in modern text retrieval systems is the weighting of individual words for importance. Early in the development of document retrieval methods it was recognized that performance could be improved if weights were based at least in part on the frequencies of individual terms in the database. This observation led investigators to propose inverse document frequency weighting, which has become the most commonly used approach. Inverse document frequency weighting can be given some justification based on probabilistic arguments. However, many different formulas have been tried and it is difficult to distinguish between these on a purely theoretical basis. Witten, Moffat and Bell, have proposed a monotonicity condition as fundamental: ‘a term that appears in many documents should not be regarded as more important than a term that appears in a few’. Based on this monotonicity assumption and probabilistic arguments we show here how the TREC data can be used to learn ideal global weights. Using cross-validation we show that these weights are a modest but statistically significant improvement over IDF weights. One conclusion is that IDF weights are close to optimal within the probabilistic assumptions that are commonly made.
RealCatch: A community-based real-time platform for financial fraud protection on smartphones

In light of the rapid growth of smartphones, there are unrelenting malicious attacks on smartphones from voice phishing to mobile malwares. However, our protection against the various types of malicious attacks is much slower than the rapid evolution of the attacks since the analysis of the malicious attacks on smartphones usually takes much more time and efforts than hackers evolve their attack methods. To address the issue, we propose a community-based real-time platform that gathers malicious attack information, which is selected from anonymized communication records transferred from users' smartphones. We then share the information with users in realtime. Our platform also features that it supports the real-time analysis of Android applications which are driven to be installed by URLs in SMS messages. It also presents a unique feature that the downloaded apps can be compared with known malwares at runtime. It is realized by our hash-valued n-g ra m search index built on top of conventional databases by exploiting facilities already available in the off-the-shelf database systems.
Facial Expression Synthesizer with The Chinese Text-to-Speech Function

The proposed system is named Image Talk: a realtime synthetic talking head using one single image with Chinese text-to-speech capability. Image Talk uses one single image to automatically create video-like talking sequences in real time. The image can be acquired from photographs, video clips, or hand drawn characters. This interactive system accepts Chinese text input and talks back in Mandarin Chinese, generating facial expression in real time. Image Talk analyzes Chinese text by converting it to a standard Pinyin system used in Taiwan and fetches the associated facial expressions from an expression pool dynamically. The expressions are synchronized with the synthetic speech and played back in the video-like talking sequence in real time. Image Talk also incorporates eye blinking, small-scale head rotation and translation perturbations, to make the results more natural. The generic Talk Mask is also easy to switch to any other facial or non-facial images, such as dogs, for special effects. The result is quite entertaining, and can easily be used as a new humanmachine interface, as well as for lip synchronization for computer animated characters.