Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-Modality Submodular Dictionary Learning for Information Retrieval

This paper addresses the problem of joint modeling of multimedia components in different media forms. We consider the information retrieval task across both text and image documents, which includes retrieving relevant images that closely match the description in a text query and retrieving text documents that best explain the content of an image query. A greedy dictionary construction approach is introduced for learning an isomorphic feature space, to which cross-modality data can be adapted while data smoothness is guaranteed. The proposed objective function consists of two reconstruction error terms for both modalities and a Maximum Mean Discrepancy (MMD) term that measures the cross-modality discrepancy. Optimization of the reconstruction terms and the MMD term yields a compact and modality-adaptive dictionary pair. We formulate the joint combinatorial optimization problem by maximizing variance reduction over a candidate signal set while constraining the dictionary size and coefficients' sparsity. By exploiting the submodularity and the monotonicity property of the proposed objective function, the optimization problem can be solved by a highly efficient greedy algorithm, and is guaranteed to be at least a (e - 1)=/e≈0.632- approximation to the optimum. The proposed method achieves state-of-the-art performance on the Wikipedia dataset.
Science and Technology Teachers’ Views About the Causes of Laboratory Accidents

Aim of this study was to determine science and technology teachers’ views about the causes of the problems encountered in laboratories. In this research, phenomenology, a qualitative research design, was used. 21 science and technology teachers who were working in elementary schools in Eskisehir during the 2010–2011 spring semester were the participants of this study. A semi-structured interview form was prepared to collect data. The interview form included three sections. Content analysis was used to deeply analyze and understand the written answers which were obtained from open ended questions. Approxiamately half of teachers expressed that, lack of caution and lack of necessary safety precautions were the causes of laboratory accidents. Moreover, they also expressed that, insufficient science content knowledge and lack of knowledge were influential in the problems encountered. It is thought that, the findings of this study will contribute to determining the causes of problems encountered in laboratories
A framework for on-demand classification of evolving data streams

Current models of the classification problem do not effectively handle bursts of particular classes coming in at different times. In fact, the current model of the classification problem simply concentrates on methods for one-pass classification modeling of very large data sets. Our model for data stream classification views the data stream classification problem from the point of view of a dynamic approach in which simultaneous training and test streams are used for dynamic classification of data sets. This model reflects real-life situations effectively, since it is desirable to classify test streams in real time over an evolving training and test stream. The aim here is to create a classification system in which the training model can adapt quickly to the changes of the underlying data stream. In order to achieve this goal, we propose an on-demand classification process which can dynamically select the appropriate window of past training data to build the classifier. The empirical results indicate that the system maintains an high classification accuracy in an evolving data stream, while providing an efficient solution to the classification task.
Description of the Google update summarizer at TAC-2011

In this paper we describe the system with which we have participated at TAC-2011 in the task of update summarization. This is our first participation in TAC, and we have started exploring the use of topic models for summarization. We have participated with a lightweight system that is an extension of TOPICSUM (Haghighi and Vanderwende, 2009), which we are currently extending for update summarization. The system had almost no pre-processing nor post-processing. The resulting scores rank as average across all participants. In this paper we analyze the results and outline some ideas for improvement.
What are the affordances of information and communication technologies ?

The paper examines the notion that Information and Communication Technologies (ICT) have affordances that epitomize the features of our late modern age (Giddens, 1991) and explores whether these affordances (Salomon, 1993, p. 51) can be used to facilitate particular approaches to educational practice. It argues that a clear articulation of these affordances would enable us to understand how these technologies can be most effectively used to support learning and teaching. We believe that any one affordance can be considered to have both positive and negative connotations and the paper draws on social and educational theory to provide an initial taxonomy of these affordances.
Solving the Least Squares Method problem in the AHP for 3 × 3 and 4 × 4 matrices ⋆

The Analytic Hierarchy Process (AHP) is one of the most pop- ular methods used in Multi-Attribute Decision Making. The Eigenvector Method (EM) and some distance minimizing methods such as the Least Squares Method (LSM) are of the possible tools for computing the prior- ities of the alternatives. A method for generating all the solutions of the LSM problem for 3 × 3 and 4 × 4 matrices is discussed in the paper. Our algorithms are based on the theory of resultants.
The outcome of children with Fanconi anemia given hematopoietic stem cell transplantation and the influence of fludarabine in the conditioning regimen: a report from the Italian pediatric group

Background and Objectives Hematopoietic stem cell transplantation (HSCT) still represents the only treatment potentially able to prevent/rescue the development of marrow failure and myeloid malignancies in patients with Fanconi anemia (FA). While in the past HSCT from an HLA-identical sibling was proven to cure many patients, a higher incidence of treatment failure has been reported in recipients of an unrelated donor (UD) or HLA-partially matched related allograft. Design and Methods We analyzed the outcome of 64 FA patients (age range, 2–20 years) who underwent HSCT between January 1989 and December 2005. Patients were transplanted from either an HLA-identical sibling (n=31), an UD (n=26), or an HLA-partially matched relative (n=7). T-cell depletion of the graft was performed in patients transplanted from an HLA-disparate relative. Results The 8-year estimate of overall survival (OS) for the whole cohort was 67%; it was 87%, 40% and 69% when the donor was an HLA-identical sibling, an UD and a mismatched relative, respectively (p<0.01). The outcome of recipients of grafts from an UD improved over time, the probability of survival being 10% and 72% for patients transplanted before and after 1998, respectively (p<0.05). The OS probability of children who did or did not receive fludarabine in preparation for the allograft was 86% and 59%, respectively (p<0.05). Interpretation and Conclusions These data, useful for counselling, provide support to the concept that a relevant proportion of FA patients undergoing HSCT can now be successfully cured, even in the absence of an HLA-identical sibling, especially if the conditioning regimen includes fludarabine.
Static-Dynamic Control Flow Integrity

CCFIR (Compact Control Flow Integrity and Randomization) has low performance overhead as an exploit mitigation, but it is hard to mitigate exploits by hijacking virtual function pointer, which are emerging in recent years. Because of the polymorphism of virtual functions, CCFIR can't determine a unique spring board stub. We propose a new practical protection method named SDCFI (Static-Dynamic Control Flow Integrity), whose goal is to protect virtual function pointers from hijacking. Taking advantage of static analysis result of IDA and PIN dynamic instrumentation, SDCFI improves the accuracy of the disassembly and identifies indirect call target addresses at runtime. We observe that there are always double 0x90 bytes for alignment in the gap between two functions, which can be substituted by a two-byte checkmark. Using the checkmark, SDCFI can validate a target more simply and faster than traditional CFI. Based on these approaches, SDCFI can prevent control-flow hijacking attacks including ROP, because the gadgets of stack pivot can't pass the validation. We evaluate our prototype implementation for Internet Explorer8 browser on Windows XP, which faces serious security threats since April 8, 2014. SDCFI protects most indirect call instructions in msthml.dll, and has low runtime overhead of 1.48% on average. Experiments on real-world exploits for IE8 browser also show that SDCFI can effectively mitigate exploits by hijacking virtual function pointer.
Discrepancies between lung function and asthma control: Asthma perception and association with demographics and anxiety

Understanding asthma symptom perception is necessary for reducing unnecessary costs both for asthma sufferers and society and will contribute to improving asthma management. The primary aim of this study was to develop and test a standardized method for classification of asthma perceiver categories into under-, normal, and overperceiver groups based on the comparison between self-report and lung function components of asthma control. Additionally, the degree to which demographic variables and anxiety contributed to the classification of patients into perceiver groups was examined. Patients underwent methacholine or reversibility testing to confirm asthma diagnosis. Next, participants completed lung function testing over 3 days before their next appointment. Finally, patients filled out demographic and self-report measures including the Asthma Control Test (ACT). Each self-report category of control assessed by the ACT (interference, shortness of breath, nighttime awakenings, rescue inhaler usage, and a composite total score) was compared with lung function measurements using a modified version of the asthma risk grid. Using the modified asthma risk grid to determine perceiver categorization, this sample included 14 underperceivers, 29 normal perceivers, and 36 overperceivers. A discriminant analysis was performed that indicated that a majority of underperceivers were characterized by being African American and having low asthma-specific anxiety. Normal perceivers in this sample tended to be older. Overperceivers tended to be female. Our findings encourage further research using the reported method of classifying asthma patients into perceiver categories.
A General Hybrid Clustering Technique

Abstract Here, we propose a clustering technique for general clustering problems including those that have nonconvex clusters. For a given desired number of clusters K, we use three stages to find clusters. The first stage uses a hybrid clustering technique to produce a series of clusterings of various sizes (randomly selected). The key step in this stage is to find a K-means clustering using clusters where and then join these small clusters by using single linkage clustering. The second stage stabilizes the result of stage one by reclustering via the “membership matrix” under Hamming distance to generate a dendrogram. The third stage is to cut the dendrogram to get clusters where and then prune back to K to give a final clustering. A variant on our technique also gives a reasonable estimate for KT, the true number of clusters. We provide arguments to justify the steps in the stages of our methods and we provide examples involving simulated and published data to compare our technique with other techniques. An R library, GHC, implementing our method is available from Github.
Study on the Division and Indentification of the Stages of Chinese Enterprise Overseas M&As

The M&A stage identification of enterprises refers to the systematic analysis on various activities in the overseas M&As of Chinese enterprises. As a growth means for Chinese enterprises, the overseas M&As of Chinese enterprises can be divided as three stages according to their characteristics, i.e. the early stage of M&As, middle stage of M&As, late stage of M&As. The early stage of M&As includes strategy making and overseas M&A target selection; the middle stage of M&As includes negotiation; the late stage of M&As mainly refers to the integration
Incorporating Qualitative Information for Credit Risk Assessment through Frequent Subtree Mining for XML

Credit risk assessment has been one of the most appealing topics in banking and finance studies, attracting both scholars’ and practitioners’ attention for some time. Following the success of the Grameen Bank, works on credit risk, in particular for Small Medium Enterprises (SMEs), have become essential. The distinctive character of SMEs requires a method that takes into account quantitative and qualitative information for loan granting decision purposes. In this chapter, we first provide a survey of existing credit risk assessment methods, which shows a current gap in the existing research in regards to taking qualitative information into account during the data mining process. To address this shortcoming, we propose a framework that utilizes an XML-based template to capture both qualitative and quantitative information in this domain. By representing this information in a domain-oriented way, the potential knowledge that can be discovered for evidence-based decision support will be maximized. An XML document can be effectively represented as a rooted ordered labelled tree and a number of tree mining methods exist that enable the efficient discovery of associations among tree-structured data objects, taking both the content and structure into account. The guidelines for correct and effective application of such methods are provided in order to gain detailed insight into the information governing the decision making process. We have obtained a number of textual reports from the banks regarding the information collected from SMEs during the credit application/evaluation process. These are used as the basis for generating a synthetic XML database that partially reflects real-world scenarios. A tree mining method is applied to this data to demonstrate the potential of the proposed method for credit risk assessment.
Historical Aspects of Propolis Research in Modern Times

Propolis (bee glue) has been known for centuries. The ancient Greeks, Romans, and Egyptians were aware of the healing properties of propolis and made extensive use of it as a medicine. In the middle ages propolis was not a very popular topic and its use in mainstream medicine disappeared. However, the knowledge of medicinal properties of propolis survived in traditional folk medicine. The interest in propolis returned in Europe together with the renaissance theory of ad fontes. It has only been in the last century that scientists have been able to prove that propolis is as active and important as our forefathers thought. Research on chemical composition of propolis started at the beginning of the twentieth century and was continued after WW II. Advances in chromatographic analytical methods enabled separation and extraction of several components from propolis. At least 180 different compounds have been identified so far. Its antibacterial, antiseptic, anti-inflammatory, antifungal, anesthetic, and healing properties have been confirmed. Propolis has been effectively used in treatment of dermatological, laryngological, and gynecological problems, neurodegenerative diseases, in wound healing, and in treatment of burns and ulcers. However, it requires further research that may lead to new discoveries of its composition and possible applications.
Detecting Faults in Context-Aware Adaptation

Internetware applications are context-aware. They adapt their behavior based on environmental changes. However, faulty adaptation may arise when these applications face unanticipated situations. Such adaptation faults can be difficult to detect at design time. One promising approach is to statically analyze model-based context-aware applications exhaustively for all potential faults. However, it suffers from expressiveness and precision problems. To address these limitations, we propose in this paper a dynamic adaptation model (AM) approach. AM offers increased expressive power to model complex adaptation rules, and guarantees soundness in its fault detection. In addition, AM deploys an incremental rule evaluation (IRE) technique to cater for context-aware applications, such that it can efficiently handle environmental changes in its fault detection. We evaluated AM using both simulated and real-world experiments with two context-aware applications. The experimental results confirmed that AM can detect real faults missed by existing work, and avoid numerous false warnings that were misreported otherwise.
Predictors and Clinical Impact of Inappropriate Implantable Cardioverter-Defibrillator Shocks in Korean Patients

Limited data are available on inappropriate shocks in Korean patients implanted with an implantable cardioverter-defibrillator (ICD). We investigated the impact of inappropriate shocks on clinical outcomes. This retrospective, single-center study included 148 patients treated between October 1999 and June 2011. The primary outcome was a composite event of all-cause mortality or hospitalization for any cardiac reason. The median follow-up duration was 29 months (interquartile range: 8 to 53). One or more inappropriate shocks occurred in 34 (23.0%) patients. A history of atrial fibrillation was the only independent predictor of inappropriate shock (hazard ratio [HR]: 4.16, 95% confidence interval [CI]: 1.89-9.15, P < 0.001). Atrial fibrillation was the most common cause of inappropriate shock (67.7%), followed by supraventricular tachycardia (23.5%), and abnormal sensing (8.8%). A composite event of all-cause mortality or hospitalizations for any cardiac reason during follow-up was not significantly different between patients with or without inappropriate shock (inappropriate shock vs no inappropriate shock: 35.3% vs 35.4%, adjusted HR: 1.06, 95% CI: 0.49-2.29, P = 0.877). Inappropriate shocks do not affect clinical outcomes in patients implanted with an ICD, although the incidence of inappropriate shocks is high.
A resonant power factor conditioner

The applicability of a current-fed push-pull parallel-resonance power converter to power factor conditioning was investigated theoretically and experimentally. The experimental switching frequency was in the range 300-860 kHz. The basic features of soft switching, inherent high power factor and simple control, make the proposed approach a viable design alternative for power input stages. <<ETX>>
PAC-Bayes-Empirical-Bernstein Inequality

We present PAC-Bayes-Empirical-Bernstein inequality. The inequality is based on combination of PAC-Bayesian bounding technique with Empirical Bernstein bound. It allows to take advantage of small empirical variance and is especially useful in regression. We show that when the empirical variance is significantly smaller than the empirical loss PAC-Bayes-Empirical-Bernstein inequality is significantly tighter than PAC-Bayes-kl inequality of Seeger (2002) and otherwise it is comparable. PAC-Bayes-Empirical-Bernstein inequality is an interesting example of application of PAC-Bayesian bounding technique to self-bounding functions. We provide empirical comparison of PAC-Bayes-Empirical-Bernstein inequality with PAC-Bayes-kl inequality on a synthetic example and several UCI datasets.
Petri Net and Probabilistic Model Checking Based Approach for the Modelling, Simulation and Verification of Internet Worm Propagation

Internet worms are analogous to biological viruses since they can infect a host and have the ability to propagate through a chosen medium. To prevent the spread of a worm or to grasp how to regulate a prevailing worm, compartmental models are commonly used as a means to examine and understand the patterns and mechanisms of a worm spread. However, one of the greatest challenge is to produce methods to verify and validate the behavioural properties of a compartmental model. This is why in this study we suggest a framework based on Petri Nets and Model Checking through which we can meticulously examine and validate these models. We investigate Susceptible-Exposed-Infectious-Recovered (SEIR) model and propose a new model Susceptible-Exposed-Infectious-Recovered-Delayed-Quarantined (Susceptible/Recovered) (SEIDQR(S/I)) along with hybrid quarantine strategy, which is then constructed and analysed using Stochastic Petri Nets and Continuous Time Markov Chain. The analysis shows that the hybrid quarantine strategy is extremely effective in reducing the risk of propagating the worm. Through Model Checking, we gained insight into the functionality of compartmental models. Model Checking results validate simulation ones well, which fully support the proposed framework.
Execution Control Lists: An Approach to Defending Against New and Unknown Malicious Software

A study released by InformationWeek Research and PricewaterhouseCoopers in July, 2000 estimates that the cost of malicious software, or malware for short, will exceed US $1.5 trillion worldwide this year. 1 The impact on US businesses with more than 1000 employees is estimated to be $266 billion or approximately 2.7% of the Gross Domestic Product (GDP). Most of the costs were estimated to be in lost productivity as a result of downtime and in lost sales opportunities. The study estimates that approximately 40,000 person years of productivity will be lost worldwide this year alone. Today's approaches to dealing with malware are not e ective. The most common approach to dealing with viruses is to use a signature-based virus detection tool. Unfortunately, this approach will not detect the next variation of the same attack. Because these viruses spread so quickly, the reactive approach to virus detection is not e ective in stopping a Melissa-style virus. Other approaches such as ltering content at the rewall have proved to be largely ine ective in the past and will be rendered obsolete in the future by end-to-end encryption. In the following, we describe a novel approach to addressing malicious software by controlling its ability to execute. We omit implementation details for brevity. The approach has been developed into a working software prototype.
Prior fusion based salient object detection

Object level saliency detection is useful for many content-based computer vision tasks. In this letter, we present a novel bottom-up salient object detection approach by exploiting contrast, and center priors. In the past, the algorithms of saliency detection are generally based on the contrast of the priors, but only using a prior that there are still many problems, if not uniformly outstanding goals. Currently, a lot of work introduce center prior to significant target detection. However, the center prior is very sensitive to the position of the target that once deviation from the center, the center prior will no longer be established. In this paper, we explore the surroundedness cue for saliency detection. The essence of surroundedness is the enclosure topological relationship between the figure and the ground, which is achieved by random threshold color channel of the image. in order to enhance robustness and effectiveness of the center prior. Then fusion contrast prior and new center prior to generate a new saliency map.