Miracle-dz/UniFAR-FTUs huggingface dataset:
ATM Intelligent Surveillance Based on Omni-directional Vision

This paper discusses a new intelligently monitoring system for the automatic teller machine (ATM) by using an omni-directional vision sensor (ODVS) and the computer vision technology. It uses ODVS to acquire the omni-directional image. By using perspective algorithm it unwrap the omni-directional image into several separated key surveillance sections and by using the Gaussian skin-color model of face detection algorithm and the kalman filter of face tracking algorithm it detect the ATM users’ faces and the suspected behavior of the voyeur who behind the ATM user. To improve the search efficiency and minimize the storage and data transmission, this paper combines the ATM user’s face image with the time and location information of certain activities. In additional, this paper designs a visualized omni-directional vibration perception device which can recognize the malicious violent behaviors by detecting whether the vibration ball under the irregular outside force or not. The experimental results show that the system has the advantages of widely detecting range, high-level intelligence, high-efficiency storage and searching and high robustness. So it provides a new way for preventing financial crimes.
Engineering judgement in reliability and safety and its limits: what can we learn from research in psychology

Engineering judgement has an important role in safety or reliability assessment. This paper focuses on the use of engineering judgement for integrating diverse evidence into an assessment of the safety or reliability of a product. In many cases of stringent safety requirements, this form of engineering (or "expert") judgement, i.e., "informal inference from complex evidence", is the crucial resource for the decision maker, for lack of more solid, objective evidence. This dependence on judgement is especially evident in the assessment of the unreliability due to possible design faults in complex products, and computer software in particular. Although engineering judgement plays an essential role in the assessment, there are good reasons to doubt the ability of experts in some of the judgement tasks in which they are usually employed. Experimental research both about the way humans think and integrate evidence, and about the performance of experts in tasks similar to engineering judgement, support the idea that the ability of experts may be overrated. This paper summarises some literature about common fallacies and ways to guard against them, and argues for a more disciplined use of expert judgement.
Efficient Top-k Indexing via General Reductions

Let D be a set of n elements each associated with a real-valued weight, and Q be the set of all possible predicates allowed on those elements. Given a predicate in Q and integer k, a top-k query returns the k elements with the largest weights among the elements of D satisfying q. The corresponding data structure problem aims to store D in small space to allow every query to be answered efficiently. It is already known that, before settling the problem, one must be able to solve two degenerated accompanying problems: (i) prioritized reporting: given a predicate q ∈ Q and a real value τ, return all the elements of D satisfying q and having weights at least τ (ii) max reporting: top-k queries with k fixed to 1. In this paper we prove general reductions in external memory that explore the opposite direction. Our first reduction shows that, (under mild conditions) any prioritized reporting structure yields a static top-$k$ structure with only a slow-down in query time by a factor of O(logB n), where B is the block size. Our second reduction shows that if one additionally has a max reporting structure, then combining the two structures yields a top-k structure with no performance slow down (in space, query, and update) in expectation. These reductions significantly simplify the design of top-k structures, as we showcase on numerous problems including halfspace reporting, circular reporting, interval stabbing, point enclosure, and 3d dominance. All the techniques proposed work directly in the RAM model as well.
AGENT BASED CASUALTY CARE – A MEDICAL EXPERT SYSTEM FOR MODERN TRIAGE

Ascertaining physiological state of soldiers deployed in the battlefield is essential for medical and strategic decision making. The diagnostic and treatment methods used in the battlefield are currently sub-optimal due to limited field resources and communication mechanisms . The system described herein is is designed to assess the medical status of deployed soldiers in near real-time in a way that will equal or surpass assessments performed by medics. In addition, this system can organize and distribute status information to appropriate members of the unit and up the chain of command to facilitate critical decision-making. Key among the components of this combat casualty care system are algorithms that assess physiological state. This paper discusses the development and evaluation of two different medical assessment algorithms .
Pronominalization revisited

Pronominalization has been related to the idea of a local focus - a set of discourse entities in the speaker's centre of attention, for example in Gundel et al. (1993)'s givenness hierarchy or in centering theory. Both accounts say that the determination of the focus depends on syntactic as well as pragmatic factors, but have not been able to pin those factors down. In this paper, we uncover the major factors which determine the focus set in descriptive texts. This new focus definition has been evaluated with respect to two corpora: museum exhibit labels, and newspaper articles. It provides an operationalizable basis for pronoun production, and has been implemented as the reusable module gnome-np. The algorithm behind gnome-np is compared with the most recent pronoun generation algorithm of McCoy and Strube (1999).
Event extraction across multiple levels of biological organization

Motivation: Event extraction using expressive structured representations has been a significant focus of recent efforts in biomedical information extraction. However, event extraction resources and methods have so far focused almost exclusively on molecular-level entities and processes, limiting their applicability. Results: We extend the event extraction approach to biomedical information extraction to encompass all levels of biological organization from the molecular to the whole organism. We present the ontological foundations, target types and guidelines for entity and event annotation and introduce the new multi-level event extraction (MLEE) corpus, manually annotated using a structured representation for event extraction. We further adapt and evaluate named entity and event extraction methods for the new task, demonstrating that both can be achieved with performance broadly comparable with that for established molecular entity and event extraction tasks. Availability: The resources and methods introduced in this study are available from http://nactem.ac.uk/MLEE/. Contact: pyysalos@cs.man. ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
Alcohol Use in Emerging Adulthood: Can Moffitt's Developmental Theory Help Us Understand Binge Drinking Among College Students?

ABSTRACT It is well-known that college students are at an increased risk for alcohol use and binge drinking compared to their same-age peers who are not in college. We use Moffitt's developmental taxonomy, specifically, her discussion of adolescence-limited offending, to contextualize this finding regarding this minor form of deviance. We also incorporate Arnett's notion of emerging adulthood to argue that the maturity gap, as described by Moffitt, can extend beyond adolescence. The current research used data from Wave III of the National Longitudinal Study of Adolescent Health (N = 4,264). We examined differences in sample characteristics between respondents who were currently enrolled in college full-time and those who were not. We also estimated several logistic regression models to determine how full-time college status and two measures of maturity were correlated with weekly binge drinking. We found that respondents who were full-time college students had an increased risk for binge drinking and were also less mature than their peers. Further analyses indicated that full-time college students were at an increased risk for binge drinking because they lacked maturity and the lack of adult roles that characterize the college years gives students more freedom to binge drink. These results supported both Moffitt's explanation of adolescence-limited offending and Arnett's notion of emerging adults.
GaussBricks: magnetic building blocks for constructive tangible interactions on portable displays

This work describes a novel building block system for tangible interaction design, GaussBricks, which enables real-time constructive tangible interactions on portable displays. Given its simplicity, the mechanical design of the magnetic building blocks facilitates the construction of configurable forms. The form constructed by the magnetic building blocks, which are connected by the magnetic joints, allows users to stably manipulate with various elastic force feedback mechanisms. With an analog Hall-sensor grid mounted to its back, a portable display determines the geometrical configuration and detects various user interactions in real time. This work also introduce several methods to enable shape changing, multi-touch input, and display capabilities in the construction. The proposed building block system enriches how individuals interact with the portable displays physically.
ESTIMATION OF THE MAIN THERMAL CHARACTERISTICS OF BUILDING COMPONENTS USING PARAMETRIC MODELS IN MATLAB

This paper presents the application of IDENT Graphical User Interface of MATLAB to estimate the thermal properties of building components from outdoors dynamic testing, imposing appropriate physical constraints and assuming linear and time invariant parametric models. Theory is briefly described to provide the background for a first understanding of the used models. The relationship between commonly used RC-network models and the parametric models proposed is deduced. The analysis is generalised for different possibilities in the assignment of inputs and outputs and even multioutput. A step by step guidance illustrated by an example is included. Results obtained using the different possibilities in selecting inputs and outputs are reported.
Breast Density and Risk of Breast Cancer in Asian Women: A Meta-analysis of Observational Studies

Objectives The established theory that breast density is an independent predictor of breast cancer risk is based on studies targeting white women in the West. More Asian women than Western women have dense breasts, but the incidence of breast cancer is lower among Asian women. This meta-analysis investigated the association between breast density in mammography and breast cancer risk in Asian women. Methods PubMed and Scopus were searched, and the final date of publication was set as December 31, 2015. The effect size in each article was calculated using the interval-collapse method. Summary effect sizes (sESs) and 95% confidence intervals (CIs) were calculated by conducting a meta-analysis applying a random effect model. To investigate the dose-response relationship, random effect dose-response meta-regression (RE-DRMR) was conducted. Results Six analytical epidemiology studies in total were selected, including one cohort study and five case-control studies. A total of 17 datasets were constructed by type of breast density index and menopausal status. In analyzing the subgroups of premenopausal vs. postmenopausal women, the percent density (PD) index was confirmed to be associated with a significantly elevated risk for breast cancer (sES, 2.21; 95% CI, 1.52 to 3.21; I2=50.0%). The RE-DRMR results showed that the risk of breast cancer increased 1.73 times for each 25% increase in PD in postmenopausal women (95% CI, 1.20 to 2.47). Conclusions In Asian women, breast cancer risk increased with breast density measured using the PD index, regardless of menopausal status. We propose the further development of a breast cancer risk prediction model based on the application of PD in Asian women.
Which philosophical approach provides the best foundation for the ethics of dementia care

Due to the increasing prevalence of dementia, caring for people with the condition is a global cause for concern. Ethics is an essential part of providing good care. However, ethics applied to dementia care needs to take account of the loss of cognition that results from the condition. There are particular challenges which arise when caring for a human being who has lived a normal life, but in whose current state does not fully resemble the person they were. This thesis aims to establish which philosophical approach provides the best foundation for an ethics of dementia care that can be both inclusive of everyone with dementia and meet these everyday challenges. In order to do this, the methodological approach of philosophical inquiry has been taken. As such, the concepts and arguments employed in the philosophical and empirical work have been critically examined. The results of this inquiry have then been utilised to construct a new pluralistic ethical model. The central argument of the thesis is that ethical approaches based on the moral status of the care recipient are not adequate and therefore should not be the primary focus for dementia care ethics. Instead, it is argued that a more promising approach is to embrace a virtue of receptivity (as advocated by Slote) in order that people are more responsive to the thoughts and feelings of those in their care. The ethical model proposed then combines this with principles to guide the care provider; as well as recognising the essential element of a supportive sociopolitical environment for the provision of ethical care. To implement this change, a suggested programme for ethics education is outlined. Future research will consider both the success of the model and this education programme.
Common Subexpression Elimination in Automated Constraint Modelling

Typically, there are many alternative models of a given problem as a constraint satisfaction problem, and formulating an effective model requires a great deal of expertise. To reduce this bottleneck, automated constraint modelling systems allow the abstract specification of a problem, which can then be refined automatically to a solver-independent modelling language. The final step is to tailor the model to a particular constraint solver. We show that we can eliminate common subexpressions in the tailoring step, as compilers do when compiling source code. We show that common subexpression elimination has two key benefits. First, it can lead to a dramatic reduction in the size of a constraint problem, to the extent that solving time is reduced by an order of magnitude when the number of nodes searched is the same. Second, it can lead to enhanced propagation and reduced search. The effect of this can be even more dramatic, leading to reductions in nodes searched and time taken by several orders of magnitude. Where the technique does not lead to improved search, we have not seen it cause a significant overhead. Therefore, we propose that common subexpression elimination is an important technique for constraint programming.
Data placement in Bubba

This paper examines the problem of data placement in Bubba, a highly-parallel system for data-intensive applications being developed at MCC. “Highly-parallel” implies that load balancing is a critical performance issue. “Data-intensive” means data is so large that operations should be executed where the data resides. As a result, data placement becomes a critical performance issue. In general, determining the optimal placement of data across processing nodes for performance is a difficult problem. We describe our heuristic approach to solving the data placement problem in Bubba. We then present experimental results using a specific workload to provide insight into the problem. Several researchers have argued the benefits of declustering (i e, spreading each base relation over many nodes). We show that as declustering is increased, load balancing continues to improve. However, for transactions involving complex joins, further declustering reduces throughput because of communications, startup and termination overhead. We argue that data placement, especially declustering, in a highly-parallel system must be considered early in the design, so that mechanisms can be included for supporting variable declustering, for minimizing the most significant overheads associated with large-scale declustering, and for gathering the required statistics.
Automatic Extraction of Hypernyms and Hyponyms from Russian Texts

The paper describes a rule-based approach for hypernym and hypo-nym extraction from Russian texts. For this task we employ finite state transducers (FSTs). We developed 6 finite state transducers that encode 6 lexico-syntactic patterns, which show a good precision on Russian DBpedia: 79.5% of the matched contexts are correct.
Determinants of mRNA recognition and translation regulation by Lin28

Lin28 is critical for stem cell maintenance and is also associated with advanced human malignancies. Our recent genome-wide studies mark Lin28 as a master post-transcriptional regulator of a subset of messenger RNAs important for cell growth and metabolism. However, the molecular basis underpinning the selective mRNA target regulation is unclear. Here, we provide evidence that Lin28 recognizes a unique motif in multiple target mRNAs, characterized by a small but critical ‘A’ bulge flanked by two G:C base pairs embedded in a complex secondary structure. This motif mediates Lin28-dependent stimulation of translation. As Lin28 is also known to inhibit the biogenesis of a cohort of miRNAs including let-7, we propose that Lin28 binding to different RNA types (precursor miRNAs versus mRNAs) may facilitate recruitment of different co-factors, leading to distinct regulatory outcomes. Our findings uncover a putative yet unexpected motif that may constitute a mechanistic base for the multitude of functions regulated by Lin28 in both stem cells and cancer cells.
Do good things and talk about them: A Theory of Academics Usage of Enterprise Social Networks for Impression Management Tactics

Enterprise social networks provide benefits especially for knowledge-intensive work as they enable communication, collaboration and knowledge exchange. These platforms should therefore lead to increased adoption and use by knowledge-intensive workers such as consultants or indeed researchers. Our interest is in ascertaining whether scientific researchers use enterprise social networks as part of their work practices. This focus is motivated by an apparent schism between a need for researchers to exchange knowledge and profile themselves, and the aversion to sharing breakthrough ideas and joining in an ever-increasing publishing and marketing game. We draw on research on academic work practices and impression management to develop a model of academics’ ESN usage for impression management tactics. We describe important constructs of our model, offer strategies for their operationalization and give an outlook to our ongoing empirical study of the use of an ESN platform by 20 schools across six faculties at an Australian university.
Estimating Walking Distance with a Smart Phone

The global positioning system (GPS) is widely used for localization. However, GPS does not perform well in an indoor environment due to that it is hard to receive satellite signal inside a building. A huge body of work utilized signal strength of short range signal (such as WiFi, Bluetooth, ultra sound or Infrared) to build a radio map for indoor localization, by deploying a great number of beacon nodes in the building. The drawback of such an infrastructure-based approach is that the deployment and calibration of the system is costly and labor-intensive. To overcome that, some prior studies proposed the use of Pedestrian Dead Reckoning (PDR) for indoor localization. The PDR system does not require to build a beacon-based infrastructure, in which a small number of sensors are put on the pedestrian. These sensors (such as G-sensor and Gyro) are used to estimate the distance and direction that the user traveled. The PDR approach can be generally categorized into two types: foot-mounted and waist-mounted. In general, the foot-mounted system can get accurate step length, but perform poorly in estimated heading direction. On the other hand, the waist-mounted system can estimate direction with high accuracy, but is hard to measure the step length. In this work, we proposed a waist-mounted based PDR using one 3-axis accelerometer and one gyroscope sensor. We utilize vertical acceleration to implement double integral for measuring the userâs instant height change and use some physical features of vertical acceleration during the walking to calibrate the measurement. Then based on the Pythagoras' Theorem, we can estimate each step length based on the userâs height change during his/her walking. Our experiment results show that the accuracy of placing smart-phone on the waist is about 97.35% and placing smart-phone on the chest pocket is about 96.14% in estimating the userâs walking distance.
Engineering High-Performance Community Detection Heuristics for Massive Graphs

The amount of graph-structured data has recently experienced an enormous growth in many applications. To transform such data into useful information, high-performance analytics algorithms and software tools are necessary. One common graph analytics kernel is community detection (or graph clustering). Despite extensive research on heuristic solvers for this task, only few parallel codes exist, although parallelism is often necessary to scale to the data volume of real-world applications. We address the deficit in computing capability by a flexible and extensible clustering algorithm framework with shared-memory parallelism. Within this framework we implement our parallel variations of known sequential algorithms and combine them by an ensemble approach. In extensive experiments driven by the algorithm engineering paradigm, we identify the most successful parameters and combinations of these algorithms. The processing rate of our fastest algorithm exceeds 10M edges/second for many large graphs, making it suitable for massive data streams. Moreover, the strongest algorithm we developed yields a very good tradeoff between quality and speed.
Control of a Hybrid Energy Source Comprising a Fuel Cell and Two Storage Devices Using Isolated Three-Port Bidirectional DC–DC Converters

This paper deals with a hybrid energy source consisting of a proton exchange membrane fuel cell, two storage devices, and a load. Generally, this type of source constitutes of nonisolated dc-dc converters. In order to have galvanic isolation for safety reasons and a high voltage ratio, we introduce another system based on the use of three-port isolated dc-dc converters. The storage device can be either a battery or a supercapacitor. This paper presents a control strategy for the hybrid source and includes a global efficiency analysis of power sharing between modules. The proposed system is validated through different simulation results. Additionally, some experimental results are given for the single module operation.