Miracle-dz/UniFAR-FTUs huggingface dataset:
Train Repathing in Emergencies Based on Fuzzy Linear Programming

Train pathing is a typical problem which is to assign the train trips on the sets of rail segments, such as rail tracks and links. This paper focuses on the train pathing problem, determining the paths of the train trips in emergencies. We analyze the influencing factors of train pathing, such as transferring cost, running cost, and social adverse effect cost. With the overall consideration of the segment and station capability constraints, we build the fuzzy linear programming model to solve the train pathing problem. We design the fuzzy membership function to describe the fuzzy coefficients. Furthermore, the contraction-expansion factors are introduced to contract or expand the value ranges of the fuzzy coefficients, coping with the uncertainty of the value range of the fuzzy coefficients. We propose a method based on triangular fuzzy coefficient and transfer the train pathing (fuzzy linear programming model) to a determinate linear model to solve the fuzzy linear programming problem. An emergency is supposed based on the real data of the Beijing-Shanghai Railway. The model in this paper was solved and the computation results prove the availability of the model and efficiency of the algorithm.
Classifying Educational Lectures in Low-Resource Languages

Classifying educational resources such as videos and articles can be challenging in low-resource languages due to lack of appropriate tools and sufficient labeled data. To overcome this problem, a crosslingual classification method that utilizes resources created in one high-resource language, such as English, to perform classification in many low-resource languages, is proposed. Data scarcity issue is prevented by transferring information from highresources languages to the low-resources ones. First, word embeddings are extracted using one of the frameworks proposed previously, then classifiers are trained using the highresource language documents. Two versions of the method that use different higher-level composition functions are implemented and compared.
Shared Book Reading Interventions With English Learners: A Meta-Analysis

The present meta-analysis was conducted to examine how shared book reading affects the English language and literacy skills of young children learning English as a second language. The final analysis included 54 studies of shared reading conducted in the United States. Features of the intervention and child characteristics were tested as potential moderators, and the impact of methodological criteria was examined using sensitivity analyses. Results revealed an overall significant, positive effect of shared reading on English learners’ outcomes. Children’s developmental status moderated this effect, with larger effect sizes found in studies including only typically developing participants than in studies including only participants with developmental disorders. No other significant moderators were identified. The main positive effect was robust to the application of more stringent methodological inclusion criteria. These results support shared book reading as an early educational activity for young English learners.
SparkXS: Efficient Access Control for Intelligent and Large-Scale Streaming Data Applications

The exponential data growth in intelligent environments fuelled by the Internet of Things is not only a major push behind distributed programming frameworks for big data, it also magnifies security and privacy concerns about unauthorized access to data. The huge diversity and the streaming nature of data raises the demand for new enabling technologies for scalable access control that can deal with the growing velocity, volume and variety of volatile data. This paper presents SparkXS, an attribute-based access control solution with the ability to define access control policies on streaming latent data, i.e. hidden information made explicit through data analytics, such as aggregation, transformation and filtering. Experimental results show that SparkXS can enforce access control in a horizontally scalable way with minimal performance overheads.
Visual Storytelling of Development Sessions

Most development activities, like program understanding, source code navigation and editing, are supported by Integrated Development Environments (IDEs). They provide different tools and user interfaces (UI) to interact with the source code, such as browsers, debuggers, and inspectors. It is uncertain how and when programmers use different UI elements of an IDE and to what extent they appropriately support development. Previously we developed DFLOW, a tool that seamlessly records and processes interaction data. Our long-term goal is to assess to what extent the UIs of IDEs support the workflow of developers and whether they can be improved. As a first step we present our approach to analyze development sessions in the form of visual storytelling. We illustrate our initial catalogue of visualizations through two development stories.
Synchronization of Mechanical Systems with a New Van der Pol Chaotic Oscillator

By applying the twisting algorithm, synchronization between a DC motor and a new chaotic Van der Pol oscillator is presented. A state of the proposed new chaotic oscillator is synchronized with the shaft position of a DC motor. Applications of tracking control of mechanisms with chaotic signals (the synchronization problem) have been of interest in many areas where some mechanical vibrations are required, like: washer machines, mixing liquids, blender machines, vibration bands for transportation, etc. This, because the performance task is improved by the richness of frequency contents on chaotic signals. Experimental results are shown to support our main results, where a DC Pitman motor is synchronized with an analog circuit implementation of the proposed chaotic oscillator
The ACGT Master Ontology on Cancer – A New Terminology Source for Oncological Practice

We present a new source of terminology for transnational data exchange in oncology, emphasizing the integration of both clinical and molecular data. In order to achieve best results in semantic interoperability, the ACGT project provides an ontology on cancer research and management. Besides examining pre-existing sources of terminology, were view methods of ontology development, and present best practices to be employed in the development of the ACGT Master Ontology. The clinical trial management system that is currently developed within ACGT constitutes a central use of the ontology at this point.
An ultra-low-power medium access control protocol for body sensor network

In this paper, BSN-MAC, a medium access control (MAC) protocol designed for Body Sensor Networks (BSNs) is proposed. Due to the traffic coupling and sensor diversity characteristics of BSNs, common MAC protocols can not satisfy the unique requirements of the biomedical sensors in BSNs. BSN-MAC exploits the feedback information from the deployed sensors to form a closed-loop control of the MAC parameters. A control algorithm is proposed to enable the BSN coordinator to adjust parameters of the IEEE 802.15. 4 superframe to achieve both energy efficiency and low latency on energy critical nodes. We evaluate the performance of BSN-MAC by comparing it with the IEEE 802.15. 4 MAC protocol using energy efficiency as the primary metric.
Exploiting Solution Clusters for Coarse-Grained Distributed Search

We consider distributed environments with high communication costs and complex local problems and argue that search can benefit from the exchange of messages containing relatively deep semantic information about the structure of the problems at each node. Specifically, we consider the case that messages contain compact representations of large clusters of solutions from each node. The intention being to weaken the constraints passed between nodes and so reduce the chance of failure in the receiving nodes. We make some first steps towards such a distributed search method. We define clusters as appropriate for both sequential and distributed problems. Finding optimal (largest possible) clusters turns out to be NP-hard. However, optimality is not necessary for the search, and so we give some heuristic constructive algorithms for producing clusters of varying sizes. Initial experimental studies on the utility of clusters are made in a distributed domain based on random SAT problems. We find evidence that the use of clusters has the potential to greatly reduce the chance of the distributed search failing unnecessarily.
Estimation of net primary productivity using multi-scale remote sensing data in Xuzhou, China

An improved Carnegie Ames Stanford Approach model based on two kinds of remote sensing data, Landsat ETM+ and MODIS, and climate variables was applied to estimate the net primary productivity (NPP) of Xuzhou in the June of 2006,2008 and 2010. The NPP of the study area decreases with the spatial scale expanding; The average NPP of terrestrial vegetation in Xuzhou shows decreasing trend in recent years because of the changes in climate and environment; The whole study area was plotted out four sub-regions, which were NPP higher sub-region, NPP high sub-region, NPP low sub-region and NPP lower sub-region. The average NPP of every sub-region was decreasing and the area percentage of lower sub-region was increasing with the scale expanding, so the NPP structure is various in different spatial scales. The NPP of the different vegetation types is significantly influenced by scale effect. In particular, the NPP of urban woodland was estimated lower value because of mixed pixel, it was increasing with the scale expanding.
Reach and Cost-Effectiveness of the PrePex Device for Safe Male Circumcision in Uganda

Introduction Modelling, supported by the USAID Health Policy Initiative and UNAIDS, performed in 2011, indicated that Uganda would need to perform 4.2 million medical male circumcisions (MMCs) to reach 80% prevalence. Since 2010 Uganda has completed 380,000 circumcisions, and has set a national target of 1 million for 2013. Objective To evaluate the relative reach and cost-effectiveness of PrePex compared to the current surgical SMC method and to determine the effect that this might have in helping to achieve the Uganda national SMC targets. Methods A cross-sectional descriptive cost-analysis study conducted at International Hospital Kampala over ten weeks from August to October 2012. Data collected during the performance of 625 circumcisions using PrePex was compared to data previously collected from 10,000 circumcisions using a surgical circumcision method at the same site. Ethical approval was obtained. Results The moderate adverse events (AE) ratio when using the PrePex device was 2% and no severe adverse events were encountered, which is comparable to the surgical method, thus the AE rate has no effect on the reach or cost-effectiveness of PrePex. The unit cost to perform one circumcision using PrePex is $30.55, 35% ($7.90) higher than the current surgical method, but the PrePex method improves operator efficiency by 60%, meaning that a team can perform 24 completed circumcisions compared to 15 by the surgical method. The cost-effectiveness of PrePex, comparing the cost of performing circumcisions to the future cost savings of potentially averted HIV infections, is just 2% less than the current surgical method, at a device cost price of $20. Conclusion PrePex is a viable SMC tool for scale-up with unrivalled potential for superior reach, however national targets can only be met with effective demand creation and availability of trained human resource.
Combining Punctuation and Disfluency Prediction: An Empirical Study

Punctuation prediction and disfluency prediction can improve downstream natural language processing tasks such as machine translation and information extraction. Combining the two tasks can potentially improve the efficiency of the overall pipeline system and reduce error propagation. In this work 1 , we compare various methods for combining punctuation prediction (PU) and disfluency prediction (DF) on the Switchboard corpus. We compare an isolated prediction approach with a cascade approach, a rescoring approach, and three joint model approaches. For the cascade approach, we show that the soft cascade method is better than the hard cascade method. We also use the cascade models to generate an n-best list, use the bi-directional cascade models to perform rescoring, and compare that with the results of the cascade models. For the joint model approach, we compare mixedlabel Linear-chain Conditional Random Field (LCRF), cross-product LCRF and 2layer Factorial Conditional Random Field (FCRF) with soft-cascade LCRF. Our results show that the various methods linking the two tasks are not significantly different from one another, although they perform better than the isolated prediction method by 0.5‐1.5% in the F1 score. Moreover, the clique order of features also shows a marked difference.
Spectral quantities associated to pairs of matrices are hard, when not impossible, to compute and to approximate

Spectral quantities associated to pairs of matrices are hard-when not impossible-to compute and to approximate* Abstract We analyse the computability and the complexity of various definitions of spectral radii for sets of matrices. We show that the joint and generalized spectral radii of two integer matrices are not approximable in polynomial time, and that two related quantities-the lower spectral radius and the largest Lyapunov exponent-are not algorithmically approximable.
Face Recognition Based on Sub-image Feature Extraction and LS-SVM

Based on sub-image feature extraction method of face images and least square support vector machine (LS-SVM) classifier, a face recognition model is proposed. In this model, face images are divided into sub-images firstly, then the discrete cosine transform is operated on each sub-image and the optimal coefficients are selected to denote the sub-image, and combine them into a single feature vector of the whole face image, finally LS-SVM is employed as a classifier with its optimized parameters. On ORL face database, experimental results show the proposed method is effective and has fast recognition speed.
The design of expressive intelligent agent for human-computer interaction

Now a day, people are getting intensely attached to communicate with others in virtual environments using various virtual agents due to their popularity. Most of these environments used emoticon for displaying emotion of interacting partners to each other. However, emoticon based systems often makes the interaction lifeless and monotonous. This paper focus on developing a human-like virtual agent that produces facial expressions with motions (such as head movement and eye blinks) during human-computer interaction scenarios through analyzing the input text messages of users. This agent is capable to display six facial expressions namely, happy, sad, angry, disgust, fear, and surprise based on the chatting partner's input text that makes the interaction enjoyable. Experimental evaluation reveals that the proposed agent can display emotive expressions correctly 92% of the times from the users' text input and it creates a better feeling of making interaction to the partners than the emoticon bases systems.
Neighbor Perceptions of Psychiatric Supportive Housing : the Role of Knowledge, Attitudes, and Behaviors

Purpose: Historically, communities have opposed the development of residential programs for adults with psychiatric disabilities. In the last two decades, national and local campaigns have made targeted efforts to improve public knowledge about mental illness, and attitudes and behaviors towards mental health clients. Supportive housing policies have also been revised to better facilitate integration and independence for clients with psychiatric disabilities. Despite these changes, the number of studies on perceptions of psychiatric supportive housing has dramatically declined in recent years. Little is known about how neighbors currently perceive psychiatric housing and neighbors with mental illness, or the role that mental health knowledge, attitudes, and behaviors play in neighborhoods where housing clients live. Methods: Knowledge, attitudes, and behaviors of 139 neighbors living in close proximity to psychiatric supportive housing sites were assessed. Follow up qualitative interviews were conducted with 16 neighbors who correctly identified the housing site in their neighborhood to understand the perceived impact of the housing site and elicit suggestions for improving relations between clients and their neighbors. Individual and neighborhood social experiences of neighbors are compared with those of 68 clients living in the referent housing sites. Results: Neighbors had high rates of personal experience with mental illness and were familiar with mental health diagnoses and facts. Neighbors had positive opinions about and neighboring intentions towards neighbors with mental illness. Increased mental health knowledge and close relationships with individuals with mental illness were NEIGHBOR PERCEPTIONS OF SUPPORTIVE HOUSING ii associated with decreased stigma. Being able to correctly identify the housing and population was not associated with differences in opinions about individuals with mental illness. Compared to clients, neighbors perceived the neighborhood as being less safe. Clients were lonelier than their neighbors. Neighbors reported the housing had a positive impact on the neighborhood and had few concerns. They suggested awareness, education, and social contact strategies to improve relations with housing clients. Conclusions: Suggestions for improving client integration and public acceptance of psychiatric supportive housing are discussed, as well implications in light of recent policy changes and ongoing public anti-stigma campaigns. NEIGHBOR PERCEPTIONS OF SUPPORTIVE HOUSING iii
Lipoperoxidation Is Selectively Involved in Progressive Supranuclear Palsy

Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by extensive neurofibrillary tangle (NFT) formation and neuronal loss in selective neuronal populations. Currently, no clues to the biological events underlying the pathological process have emerged. In Alzheimer disease (AD), which shares with PSP the occurrence of NFTs, advanced glycation end products (AGEs) as well as oxidation adducts have been found to be increased in association with neurofibrillary pathology. The presence and the amount of lipid and protein oxidation markers, as well as of pyrraline and pentosidine, 2 major AGEs, was assessed by biochemical, immunochemical, and immunocytochemical analysis in midbrain tissue from 5 PSP cases, 6 sporadic AD cases, and 6 age-matched control cases. The levels of 4-hydroxynonenal (HNE) and thiobarbituric acid reactive substances (TBARS), 2 major products of lipid peroxidation, were significantly increased by 1.6-fold (p < 0.04) and 3.9-fold (p < 0.01), respectively, in PSP compared with control tissues, whereas in AD only TBARS were significantly increased. In PSP tissue the intensity of neuronal HNE immunoreactivity was proportional to the extent of abnormal aggregated τ protein. The amount of protein oxidation products and AGEs was instead similar in PSP and control tissues. In AD, a higher but not significant level of pyrraline and pentosidine was measured, whereas the level of carbonyl groups was doubled. These findings indicate that in PSP, unlike in AD, lipid peroxidation is selectively associated with NFT formation. The intraneuronal accumulation of toxic aldehydes may contribute to hamper τ degradation, leading to its aggregation in the PSP specific abnormal filaments.
Order Reduction of Linear Interval Systems Using Particle Swarm Optimization Devender

In recent years, genetic algorithms (GA) and particle swarm optimization (PSO) techniques have attracted considerable attention among various modern heuristic optimization techniques. In this paper PSO is employed for finding stable reduced order models of large-scale linear Interval systems. In this algorithm the numerator and denominator polynomials are determined by minimizing the Integral square error (ISE) between original and reduced model pertaining to unit step input by using PSO. The algorithm is simple, rugged and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. A numerical example illustrates the proposed algorithm.
Detecting Infeasibility in Infeasible-Interior-Point Methods for Optimization

We study interior-point methods for optimization problems in the case of infeasibility or unboundedness. While many such methods are designed to search for optimal solutions even when they do not exist, we show that they can be viewed as implicitly searching for well-defined optimal solutions to related problems whose optimal solutions give certificates of infeasibility for the original problem or its dual. Our main development is in the context of linear programming, but we also discuss extensions to more general convex programming problems. ∗School of Operations Research and Industrial Engineering, Cornell University, Ithaca, New York 14853, USA (miketodd@cs.cornell.edu). This author was supported in part by NSF through grant DMS-0209457 and ONR through grant N00014-02-1-0057.
Very high speed link emulation with TLEM

In this work we discuss the limitations of link emulators based on conventional network stacks, and present our alternative architecture called TLEM, which is designed to address current high speed links and be open to future speed improvements. TLEM is structured as a pipeline of stages, implemented with separate threads and with limited interactions with each other, so that high performance can be achieved. Our emulator can handle bidirectional traffic at speeds of over 18 Mpps (64 byte packets) and 40 Gbit/s (1500 byte packets) per direction even with large emulation delays. Even higher performance can be achieved with shorter delays, as the workload fits better into the L3 cache of the system. TLEM is distributed as BSD-licensed opensource as part of the netmap distributions, and runs on any system that supports netmap (this includes FreeBSD, Linux and now even Windows).