Miracle-dz/UniFAR-FTUs huggingface dataset:
The combination of ACDA and FCM for Data Association in multi-target tracking

For improving the performance of ACDA(Ant Colony Data Association) for data association in multi-target tracking, we propose the combined method of ACDA and FCM. Since FCM is a determinate algorithm, in nature based on NN(Nearest Neighbor), it could generate reasonable results in any case, which is a backup when ACDA becomes divergent. Experiments have been done in three cases-ACDA as data association method only, FCM only, and the combined method of ACDA and FCM. The results show that the performance of the combined method is superior to the other two methods.
Variance error quantifications that are exact for finite-model order

This paper is concerned with the frequency domain quantification of noise induced errors in dynamic system estimates. Preceding and seminal work on this problem has suggested general expressions that are approximations whose accuracy increases with observed data length and model order. In the interests of improved accuracy, this paper provides new expressions whose accuracy depends only on data length. They are therefore "exact" for arbitrarily small true model order. Other authors have recognized the importance of such expressions and have derived them for the case of finite-impulse response-like model structures in which denominators are fixed at true values and only numerator terms are estimated. This paper progresses beyond this situation to address the more general output-error and Box-Jenkins structures in which full dynamics models (both numerator and denominator terms) and noise models may be estimated. A key aspect of the work here is that it establishes that the variance quantification problem is equivalent to that of deriving the reproducing kernel for a subspace that depends on the model structure being employed.
Approximating a Deep-Syntactic Metric for MT Evaluation and Tuning

SemPOS is an automatic metric of machine translation quality for Czech and English focused on content words. It correlates well with human judgments but it is computationally costly and hard to adapt to other languages because it relies on a deep-syntactic analysis of the system output and the reference. To remedy this, we attempt at approximating SemPOS using only tagger output and a few heuristics. At a little expense in correlation to human judgments, we can evaluate MT systems much faster. Additionally, we describe our submission to the Tunable Metrics Task in WMT11.
PrivGene: differentially private model fitting using genetic algorithms

epsilon-differential privacy is rapidly emerging as the state-of-the-art scheme for protecting individuals' privacy in published analysis results over sensitive data. The main idea is to perform random perturbations on the analysis results, such that any individual's presence in the data has negligible impact on the randomized results. This paper focuses on analysis tasks that involve model fitting, i.e., finding the parameters of a statistical model that best fit the dataset. For such tasks, the quality of the differentially private results depends upon both the effectiveness of the model fitting algorithm, and the amount of perturbations required to satisfy the privacy guarantees. Most previous studies start from a state-of-the-art, non-private model fitting algorithm, and develop a differentially private version. Unfortunately, many model fitting algorithms require intensive perturbations to satisfy -differential privacy, leading to poor overall result quality. Motivated by this, we propose PrivGene, a general-purpose differentially private model fitting solution based on genetic algorithms (GA). PrivGene needs significantly less perturbations than previous methods, and it achieves higher overall result quality, even for model fitting tasks where GA is not the first choice without privacy considerations. Further, PrivGene performs the random perturbations using a novel technique called the enhanced exponential mechanism, which improves over the exponential mechanism by exploiting the special properties of model fitting tasks. As case studies, we apply PrivGene to three common analysis tasks involving model fitting: logistic regression, SVM classification, and k-means clustering. Extensive experiments using real data confirm the high result quality of PrivGene, and its superiority over existing methods.
Modeling VDI Application with Guaranteed Quality of Service

As the rapid development of virtualization technology, traditional data centers are gradually superseding physical machines with virtual machines (VMs) to provide services. Virtual machines hosting different applications (e.g. database server, mail server) run on the same physical host. Apart from improving hardware utilization, virtualization enables migrating applications seamlessly to a different physical host for the purpose of load balancing, planned software/hardware upgrades, etc. To avoid migrating data along with the in memory state of the virtual machines, virtual machine data is stored on shared storage. This enables a virtual machine, irrespective of the physical machine it is hosted on, to access its data over the network from the storage system. Since in the shared storage architecture, multiple VMs/applications will compete with each other for IO resources and capacity resources of the storage system, it is essential to provide minimum guarantees of quality of service (QoS) for VMs.
Poor Perception of Body Weight Category amongst the Overweight and Obese with Chronic Hepatitis C: A Target for Intervention

Obesity in chronic hepatitis C (CHC) is associated with adverse hepatic and metabolic outcomes. This prospective study evaluates the agreement between self-perceived body weight (BW) status and measured body mass index (BMI) category and factors associated with its underestimation in CHC. Body size perception was measured with the Contour Drawing Rating Scale. Two hundred and seventy-three patients with CHC (overweight 45%, obese 18%) participated in this study. Although both overweight and obese demonstrated good body size perception, agreement between perceived BW and measured BMI categories was poor (κ = 0.315, 95% CI 0.231–0.399); 33% of overweight/obese respondents considered themselves normal or underweight. Male gender (OR 2.84) and overweight (OR 2.42) or obese BMI (OR 14.19) were associated with underestimation of BW category. Targeted interventions are needed to improve body weight perception, thereby enhancing the uptake of health advice on management of excess body weight in CHC.
Curvature scale-space of open curves: Theory and shape representation

The problem of extending the curvature scale-space (CSS) technique to represent open curves is addressed. Various approaches for dealing with the endpoint problem of open curves are considered, and one is selected which allows us to handle the evolution of the open curves as a special case of the evolution of closed curves. The convergence theory of evolved open curves is established, and the CSS shape representation is investigated.
Using type analysis in compiler to mitigate integer-overflow-to-buffer-overflow threat

One of the top two causes of software vulnerabilities in operating systems is the integer overflow. A typical integer overflow vulnerability is the Integer Overflow to Buffer Overflow IO2BO for short vulnerability. IO2BO is an underestimated threat. Many programmers have not realized the existence of IO2BO and its harm. Even for those who are aware of IO2BO, locating and fixing IO2BO vulnerabilities are still tedious and error-prone. Automatically identifying and fixing this kind of vulnerability are critical for software security. In this article, we present the design and implementation of IntPatch, a compiler extension for automatically fixing IO2BO vulnerabilities in C/C++ programs at compile time. IntPatch utilizes classic type theory and a dataflow analysis framework to identify potential IO2BO vulnerabilities, and then uses backward slicing to find out related vulnerable arithmetic operations, and finally instruments programs with runtime checks. Moreover, IntPatch provides an interface for programmers who want to check integer overflows manually. We evaluated IntPatch on a few real-world applications. It caught all 46 previously known IO2BO vulnerabilities in our test suite and found 21 new bugs. Applications patched by IntPatch have negligible runtime performance losses which are on average 1%.
Developing aspect–specific assessment criteria for examination answers and coursework essays in psychology

This article describes the development of assessment criteria for specific aspects of examination answers and coursework essays in psychology. The criteria sp cified the standards expected for seven aspects of students’ work: addressing the question, covering the area, understanding the material, evaluating the material, developing arguments, structure and organisation, and clarity in presentation. The criteria were designed to promote student learning, increase the reliability of marking, facilitate research on marking, and promote reflective practice among markers. Student feedback indicated that, despite being published in course materials, the impact of the criteria on students was much less than it could be, but the criteria supported other initiatives to promote student learning, including more structured feedback to students on coursework essays, and generic skills teaching on essay writing. The criteria were used in research to analyse the judgements made by markers of examination answers. That research revealed substantial individual differences among markers and more systematic differences between first and second markers. Some staff had reservations about specifying the assessment criteria in such detail, but the criteria provided a stimulus for staff reflection on the process of marking and agreeing marks. The development of the criteria opened up a number of avenues for further work on student learning and assessment and for further research on the psychology of marking.
Model-based multi-objective reinforcement learning

This paper describes a novel multi-objective reinforcement learning algorithm. The proposed algorithm first learns a model of the multi-objective sequential decision making problem, after which this learned model is used by a multi-objective dynamic programming method to compute Pareto optimal policies. The advantage of this model-based multi-objective reinforcement learning method is that once an accurate model has been estimated from the experiences of an agent in some environment, the dynamic programming method will compute all Pareto optimal policies. Therefore it is important that the agent explores the environment in an intelligent way by using a good exploration strategy. In this paper we have supplied the agent with two different exploration strategies and compare their effectiveness in estimating accurate models within a reasonable amount of time. The experimental results show that our method with the best exploration strategy is able to quickly learn all Pareto optimal policies for the Deep Sea Treasure problem.
Characterizing cascade dynamics in a microblogging system

Online microblogging sites have become increasingly important platforms for information diffusion in today's world, where users post short messages and follow various messages posted by people that they are interested in. It is intriguing to qualitatively study the temporal dynamics of an information cascade in a microblogging system, in terms of the number of users influenced at any given time, which may provide valuable input to facilitate emerging applications such as online advertising and content distribution. In this paper, we model information diffusion in a microblogging network as an age-dependent branching process, based on practical observations from Tencent Weibo, a popular microblogging site in China. This model enables careful characterization of the diffusion topology, the different delays for users to respond to new information, and the evolution of the size of the information cascade over time. We derive the expected cascade size at any time. We validate our model based on Tencent Weibo traces, and demonstrate its effectiveness in capturing information diffusion dynamics in the real world.
Net flux of folates and vitamin B12 through the gastrointestinal tract and the liver of lactating dairy cows

In study 1, four cows had a ruminal canula, a catheter in the right ruminal vein and an ultrasonic flow probe around the right ruminal artery; a catheter was placed in the auricular artery on experimental days. Blood samples were taken every 10 min from -20 to 60 min after ruminal infusion of 5·79 mmol pteroylmonoglutamic acid and cyanocobalamin. There was a net release of these vitamins across the rumen wall following the infusion (P=0·06). In studies 2 and 3, four cows had catheters in the portal, one hepatic and two mesenteric veins and one mesenteric artery. Plasma flow was determined using p-aminohippurate. In study 2, blood samples were taken before and every 30 min for 6 h after feeding 0 or 4 mg of pteroylmonoglutamic acid. Flow of folates through the portal-drained viscera (PDV) and the total splanchnic tissues (TSP) tended to increase with the ingestion of pteroylmonoglutamic acid (P=0·19). In study 3, blood samples were collected every 30 min for the first 3 h to calculate plasma flow and basal net fluxes of folates and vitamin B12. The cows were fed 2·6 g pteroylmonoglutamic acid and 500 mg cyanocobalamin; blood samples were taken every 2 h for 24 h. Vitamin supplements increased the net release of folates and vitamin B12 from PDV (P=0·04) and TSP (P=0·13). The present results demonstrate that, in dairy cows, at doses reported to improve animal performance, passage of pteroylmonoglutamic acid to the portal blood appears during the 6 h following its ingestion, whereas for cyanocobalamin, it is a slow process, not yet completed 24 h after its ingestion.
Characterising and Predicting Haploinsufficiency in the Human Genome

Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.
Vibration energy harvesting in automobiles to power wireless sensors

Automobiles may include sensors for obtaining information regarding various physical parameters, such as ultrasonic sensors for distance detecting during reversing. Usually these sensors are powered by wire connection with the batteries of the automobiles. However, while more and more sensors are installed to the automobiles, the wire connection turns to be troublesome. Furthermore, some embedded sensors cannot be powered by wire connection, such as the tire pressure monitoring sensors. Therefore, powering these distributed or embedded wireless sensors from ambient energy becomes attractive. It will reduce the installment trouble and maintenance costs. This work reports on vibration levels detected in automobiles during road test as a potential energy source for automobile sensors. The measurement results showed that the vibrations in the automobiles are large enough for useful vibration harvesting. A piezoelectric vibration harvester was designed and equipped with a power interface circuit. The test demonstrates that sufficient energy is harvested to possibly supply a wireless sensor. It is also shown that significant increases in harvested energy may be obtained by improving the harvesting device design.
A Comparison of the Inherent Adaptivity Perspective and Functionalist Perspective on Guilt and Shame

Within the field of guilt and shame, two competing perspectives have been advanced. The first, the inherent adaptivity perspective, has been primarily advanced by Tangney and colleagues. This position advocates that guilt is an inherently adaptive emotion and shame is an inherently maladaptive emotion; thus, those interested in moral character development and psychopathology should work to increase an individual’s guilt-proneness and decrease an individual’s shame-proneness. The functionalist perspective, in contrast, has advocated that both guilt and shame can serve a person adaptively and maladaptively—depending on the situational appropriateness, duration, intensity, and so forth. This paper reviews the research conducted supporting both positions, critiques some issues with the most widely used guiltand shameproneness measure in the inherent adaptivity research (the TOSCA), and concludes that the functionalist perspective is more broad in scope and fits the existing research better.
A viral scaffolding protein triggers portal ring oligomerization and incorporation during procapsid assembly

A novel role for scaffolding protein in portal ring formation. Most double-stranded DNA viruses package genetic material into empty precursor capsids (or procapsids) through a dodecameric portal protein complex that occupies 1 of the 12 vertices of the icosahedral lattice. Inhibiting incorporation of the portal complex prevents the formation of infectious virions, making this step an excellent target for antiviral drugs. The mechanism by which a sole portal assembly is selectively incorporated at the special vertex is unclear. We recently showed that, as part of the DNA packaging process for bacteriophage P22, the dodecameric procapsid portal changes conformation to a mature virion state. We report that preformed dodecameric rings of P22 portal protein, as opposed to portal monomers, incorporate into nascent procapsids, with preference for the procapsid portal conformation. Finally, a novel role for P22 scaffolding protein in triggering portal ring formation from portal monomers is elucidated and validated by incorporating de novo assembled portal rings into procapsids.
Knowledge, anxiety and coping level after two approaches to patient education

The framework of this study was based on the con­ cepts of knowledge, anxiety, and coping as they relate to strategies of adaptation in illness. Two approaches to teaching pulmonary outpatients were investigated to ascertain which yielded a greater level of patient knowledge about their disease and its management, and examine these patients' anxiety and coping levels in relation to knowledge and method of instruction. A convenience sample of 35 outpatients diagnosed as having chronic airways obstructive disease (CAOD) was used. Nineteen subjects composing group I received unstructured, individual teaching from health professionals during routine clinic visits. Sixteen patients (group II) received addi­ tional information by attending.a series of structured, small group outpatient classes. Each subject completed a questionnaire consisting of a 20-item investigator-designed knowledge test quesionnaire, the State-Trait Anxiety Inventory, and the Coping Scale. A series of correlation coefficients and analysis of variance were performed on the data. Results demonstrated no significant differences between the two groups in rela­ tion to knowledge, state and trait anxiety levels, and coping ability. The findings did indicate significant
Collaborative Filtering Based on Demographic Attribute Vector

In present recommender systems, users receive items recommended on basis of their purchase records. New user experiences the cold start problem : as there records is very poorly. This paper proposed an NCT/TF(number of common terms / term frequency) collaborate filtering Algorithm Based on demographic vector. First, generates user demographic vector base on the user information (age, occupation, gender). then calculate two users similarity base on previous result. and generate new similar by combine it with cosine or PCC similar And then predict item rates by top N similar neighbors. The experiments show that the quality of recommendations improved, while the new user effort is smaller as no initial rating are asked.
Is dual-source CT coronary angiography ready for the real world?

CT coronary angiography (CTCA) represents one of the major innovations in cardiac imaging over the past 10 years. The introduction of 64-slice and dual-source CT scanners allowed the clinical implementation of this technique in non-invasive coronary artery imaging. The pros of CTCA are: non-invasiveness; the ability to visualize both the lumen and the coronary artery wall, and consequently to identify atherosclerotic plaques; and the ability to investigate the spatial relationships between cardiac structures. More than 5000 scanners with 64 slices are installed around the world and more than 4000 have cardiac imaging capabilities. These figures are continually growing. However, the proper use of this tool is still under discussion and for some researchers is even controversial. Studies dealing with clinical outcome and cost-effectiveness are still lacking, and several limitations and concerns have been raised about the clinical implementation of this imaging modality. Alkadhi et al. report the diagnostic accuracy of dual-source CTCA (DSCT) in a population at intermediate cardiovascular risk, with regard to important parameters such as obesity, calcium load, and heart rate.