Miracle-dz/UniFAR-FTUs huggingface dataset:
A Depth Extraction Method Based on Motion and Geometry for 2D to 3D Conversion

With the development of 3DTV, the conversion of existing 2D videos to 3D videos becomes an important component of 3D content production. One of the key steps in 2D to 3D conversion is how to generate a dense depth map. In this paper, we propose a novel depth extraction method based on motion and geometric information for 2D to 3D conversion, which consists of two major depth extraction modules, the depth from motion and depth from geometrical perspective. The H.264 motion estimation result is utilized and cooperates with moving object detection to diminish block effect and generates a motion-based depth map. On the other hand, a geometry-based depth map is generated by edge detection and Hough transform. Finally, the motion-based depth map and the geometry-based depth map are integrated into one depth map by a depth fusion algorithm.
Implementing a fixed point semantics for a constraint deductive database based on hereditary harrop formulas

This work is aimed to show a concrete implementation of a deductive database system based on the scheme HH_(C) (Hereditary Harrop Formulas with Negation and Constraints) following a fixpoint semantics proposed in a previous work. We have developed a Prolog implementation for this scheme that is constraint system independent, therefore allowing to use it as a base for any instance of the formal scheme. We have developed several specific constraint systems: Real numbers, integers, Boolean and user-defined enumerated types. We have added types to the database so that relations become typed (as tables in relational databases) and each constraint is mapped to its corresponding constraint system. The predicates that compute the fixpoint giving the meaning to a database are described. In particular, we show the implementation of a forcing relation (for derivation steps) and highlight how the inherent difficulties have been overcome in a system allowing hypothetical queries, which make the database dynamically grow.
A survey of user classification in social networks

Social networks is a virtual communities and networking platform, where people can create and share views, ideas and experiences freely. Social networks like the real world, filled with colorful crowd. How to use user behavior attributes, basic information, and interactive content in social media to classify users has become a hot topic in the field of social network analysis. In this paper, we present a detailed review in various types of user classification in social networks. We present most common methods based on machine learning and non-machine learning in user classification. The algorithms based on machine learning includes: Bayesian, Decision Tree, Logistics, SVM and KNN. The method of non-machine learning includes: concept of entropy and based on user similarity.
Prospective identification and treatment of children with pediatric autoimmune neuropsychiatric disorder associated with group A streptococcal infection (PANDAS).

BACKGROUND The current diagnostic criteria for pediatric autoimmune neuropsychiatric disorder associated with group A streptococcal infection (PANDAS) are pediatric onset, neuropsychiatric disorder (obsessive-compulsive disorder [OCD]) and/or tic disorder; abrupt onset and/or episodic course of symptoms; association with group A beta-hemolytic streptococcal (GABHS) infection; and association with neurological abnormalities (motoric hyperactivity or adventitious movements, including choreiform movements or tics). OBJECTIVE To assess new-onset PANDAS cases in relation to acute GABHS tonsillopharyngitis. DESIGN Prospective PANDAS case identification and follow-up. RESULTS Over a 3-year period (1998-2000), we identified 12 school-aged children with new-onset PANDAS. Each patient had the abrupt appearance of severe OCD behaviors, accompanied by mild symptoms and signs of acute GABHS tonsillopharyngitis. Throat swabs tested positive for GABHS by rapid antigen detection and/or were culture positive. The GABHS serologic tests, when performed (n = 3), showed very high antideoxyribonuclease antibody titers. Mean age at presentation was 7 years (age range, 5-11 years). In children treated with antibiotics effective in eradicating GABHS infection at the sentinel episode, OCD symptoms promptly disappeared. Follow-up throat cultures negative for GABHS were obtained prospectively after the first PANDAS episode. Recurrence of OCD symptoms was seen in 6 patients; each recurrence was associated with evidence of acute GABHS infection and responded to antibiotic therapy, supporting the premise that these patients were not GABHS carriers. The OCD behaviors exhibited included hand washing and preoccupation with germs, but daytime urinary urgency and frequency without dysuria, fever, or incontinence were the most notable symptoms in our series (58% of patients). Symptoms disappeared at night, and urinalysis and urine cultures were negative. CONCLUSION To our knowledge, this is the first prospective study to confirm that PANDAS is associated with acute GABHS tonsillopharyngitis and responds to appropriate antibiotic therapy at the sentinel episode.
Mining for similarities in aligned time series using wavelets

Discovery of non-obvious relationships between time series is an important problem in many domains, such as financial, sensory, and scientific data analysis. We consider data mining in aligned time series, which arise, e.g., in numerous online monitoring applications, and we are interested in finding time series which reflect the same external events. The time series can have different vertical positions, scales and overall trends, however still show related features at the same locations. The features can be short-term, such as small peaks and turns, or long-term, such as wider mountains and valleys. We propose using a wavelet transformation of a time series to produce a natural set of features for the sequence. Wavelet transformation yields features which describe properties of the sequence, both at various locations and at varying time granularities. In the proposed method, these features are processed so that they are insensitive to changes in the vertical position, scaling, and overall trend of the time series. We discuss the use of these features in data mining, in tasks such as clustering. We demonstrate how the features allow a flexible analysis of different aspects of the similarity: we show how one can examine how the similarity between time series changes as a function of time or as a function of time granularity considered. We present experimental results with real financial data sets. Experiments indicate that the proposed method can produce useful results. For instance, important similarities can be found in time series, which would be considered unrelated by visual inspection. Experiments with compression give encouraging results for the application of the method in mining massive time series data sets.
Running Head : A METHOD ENGINEERING APPROACH FOR DEFECT TAXONOMIES 1 Defect Taxonomies for Requirements Validation : A Method Engineering Approach

Recently, defect taxonomies have been shown to be useful for improving requirements validation and testing activities. This paper presents a method engineering approach for defect taxonomies based on the work of Felderer and Beer (2013b). Specifically, a method fragment for performing requirements validation through defect taxonomies is proposed. We show how this technique can be assembled and used in conjunction with other requirements-related activities such as requirements quality reviews and testing through a hypothetical example in the mobile IT sector. Since this technique has only been studied in the context of a public health insurance organization, more research is needed to verify the applicability of this technique to other domains. A METHOD ENGINEERING APPROACH FOR DEFECT TAXONOMIES 3
Political motherhood and a spectacular resistance: (Re) examining the Kangla Fort Protest, Manipur

ABSTRACT This essay is a (re)examination of the Kangla Fort protest in Manipur (2004), where 12 imas (mothers) enacted a spectacular nude protest, with banners reading ‘Indian army rape us/Indian army take our flesh’. Based on interviews with the imas, I examine how the notion of ‘political motherhood’, along with a shared affective economy of hurt and pain produced a protest, both spectacular and singular, in its symbolic, as well as actual resistance against the atrocities of the Indian army. The 12 women who protested are members of the Meira Paibis (torch bearers), who draw their strength from their identity as mothers. Thus, their narratives, memories and articulations of the nude protest is saturated and conditioned by patriarchal idioms of ‘motherhood’, and how the ‘mothers of Manipur’ had to rise up, to save Manipuri people from the masculine Indian state. The essay grapples with the double bind that the notion of ‘political motherhood’ poses: on the one hand, the imas operate within the paradigm of benevolent patriarchy, drawing their strength from sacred and religious traditions that legitimise their roles as peacemakers; on the other hand, the event of the protest destabilizes and ruptures all social, historical, and cultural norms that constitute the members of the Meira Paibis as grieving mothers. In this essay, I argue that the spectacular and radical act of protesting nude in broad daylight speaks to the crux of recent feminist theorizations on subjectivities, where agency is understood as something that is not pre-discursive and prior to power, but produced by historically specific, concrete contexts. I argue that the singular and the spectacular act of protest gives a completely new meaning to agency, and even if momentarily, redefines the politics of resistance within a field over determined by social, political, and ideological constructions of normative femininity.
Lazy Toggle PRM : An Efficient Motion Planning Strategy for Task Sequences

Probabilistic RoadMaps (PRMs) are quite successful in solving complex and high-dimensional motion planning problems. While particularly suited for multiple-query scenarios and expansive spaces, they lack efficiency in both solving a small number of queries in an environment and mapping narrow spaces. Two PRM variants separately tackle these gaps. Lazy PRM reduces the computational cost of roadmap construction for single-query scenarios by delaying roadmap validation until query time and Toggle PRM is well suited for mapping narrow spaces through a coordinated mapping both Cfree and Cobst. However, fully validating the two roadmaps can be costly. A recent strategy, Lazy Toggle PRM, integrated these two approaches into a method which is suited for efficient single-query planning. In this paper, we extend this approach to plan for difficult task sequences in environments with narrow passages and of high descriptive complexity (e.g., those described by many triangles). We conclude that Lazy Toggle PRM efficiently plans for complex task sequences compared with PRM, Lazy PRM, Toggle PRM, all suited for planning for multiple queries.
Clustering on Web usage data using Approximations and Set Similarities

: Web usage mining is the application of data mining techniques to web log data repositories. It is used in finding the user access patterns from web access log. User page visits are sequential in nature. In this paper we presented clustering web transactions based on the set similarity measures from web log data which identifies the behavior of the users page visits, order of occurrence of visits . Web data Clusters are formed using the Similarity Upper Approximations. We present the experimental results on MSNBC web navigation dataset which are sequential in nature. clustering in web usage mining is finding the groups which share common interests and behavior by analyzing the data collected in the web servers. This study contributes the topic clustering of web usage data and shows the interests and behaviors of the various user visits .
DNA Sequence Variation and Selection of Tag Single-Nucleotide Polymorphisms at Candidate Genes for Drought-Stress Response in Pinus taeda L.

Genetic association studies are rapidly becoming the experimental approach of choice to dissect complex traits, including tolerance to drought stress, which is the most common cause of mortality and yield losses in forest trees. Optimization of association mapping requires knowledge of the patterns of nucleotide diversity and linkage disequilibrium and the selection of suitable polymorphisms for genotyping. Moreover, standard neutrality tests applied to DNA sequence variation data can be used to select candidate genes or amino acid sites that are putatively under selection for association mapping. In this article, we study the pattern of polymorphism of 18 candidate genes for drought-stress response in Pinus taeda L. , an important tree crop. Data analyses based on a set of 21 putatively neutral nuclear microsatellites did not show population genetic structure or genomewide departures from neutrality. Candidate genes had moderate average nucleotide diversity at silent sites (πsil = 0.00853), varying 100-fold among single genes. The level of within-gene LD was low, with an average pairwise r2 of 0.30, decaying rapidly from ∼0.50 to ∼0.20 at 800 bp. No apparent LD among genes was found. A selective sweep may have occurred at the early-response-to-drought-3 (erd3) gene, although population expansion can also explain our results and evidence for selection was not conclusive. One other gene, ccoaomt-1, a methylating enzyme involved in lignification, showed dimorphism (i.e., two highly divergent haplotype lineages at equal frequency), which is commonly associated with the long-term action of balancing selection. Finally, a set of haplotype-tagging SNPs (htSNPs) was selected. Using htSNPs, a reduction of genotyping effort of ∼30–40%, while sampling most common allelic variants, can be gained in our ongoing association studies for drought tolerance in pine.
Improved OnThe-Fly Livelock Detection : Combining Partial Order Reduction and Parallelism for dfs fifo

Until recently, the preferred method of livelock detection was via LTL model checking, which imposes complex constraints on partial order reduction (por), limiting its performance and parallelization. The introduction of the dfsfifo algorithm by Faragó et al. showed that livelocks can theoretically be detected faster, simpler, and with stronger por. For the first time, we implement dfsfifo and compare it to the LTL approach by experiments on four established case studies. They show the improvements over the LTL approach: dfsfifo is up to 3.2 times faster, and it makes por up to 5 times better than with spin’s ndfs. Additionally, we propose a parallel version of dfsfifo, which demonstrates the efficient combination of parallelization and por. We prove parallel dfsfifo correct and show why it provides stronger guarantees on parallel scalability and por compared to LTL-based methods. Experimentally, we establish almost ideal linear parallel scalability and por close to the por for safety checks: easily an order of magnitude better than for LTL.
An Inference-Based Approach to the Interpretation of Discourse

In the present paper, we describe a theoretical approach to the interpretation of utterances in spoken language dialogue systems. We also hint at our implementation of a prototype dialogue system that realizes the outlined approach. The paper draws a comparison with keyword spotting techniques and shows how the need for more complex inference processes evolves from problems that remain unsolved within the framework of keyword spotting. A partial logic is introduced that is used for semantic interpretation and dialogue strategy selection. Finally, a DRT-based approach to constructing semantic representations used as input to the dialogue manager is also presented.
Improving End-to-end Packet Delivery in High Traffic Multi-hop Wireless Ad Hoc Networks

Accurate link quality estimation is an important building block in quality aware routing. In an inherently lossy, unreliable and dynamic medium such as wireless, the task of accurate estimation becomes very challenging. Over the years ETX has been widely used as a reliable link quality estimation metric. However, more recently it has been established that under heavy traffic loads ETX performance gets significantly worse [4, 18, 19]. Contributions made in this paper are twofold. Firstly, we examine the ETX metric's behavior in detail with respect to the MAC layer and UDP data; and identify the causes of its unreliability. Secondly, we present the design and implementation of the xDDR link quality measurement metric -- a variation of ETX - motivated by the observations made in our analysis. Our experiments show that xDDR substantially outperforms minimum hop count, ETX and HETX in packet delivery ratio.
Improving and complementing virtual memory using hardware techniques

OF THE DISSERTATION Improving and Complementing Virtual Memory Using Hardware Techniques by GUILHERME MOTA CAVALCANTI DE ALBUQUERQUE COX Dissertation Director: Abhishek Bhattacharjee Virtual memory is a classic computer science abstraction and is ubiquitous in all scales of computing today. However, despite years of research, virtual memory faces critical performance and security challenges. This thesis aims to address these challenges. The first challenge we address is the growing performance overheads faced by virtual memory as workloads continue demanding ever-increasing amounts of memory. The key culprit of these overheads is address translation, the mechanism by which virtual memory translates a program’s virtual addresses to physical addresses. Performing fast address translation requires the design of fast and efficient hardware translation lookaside buffer (TLB) caches. Unfortunately, TLBs struggle to perform efficiently for “big data” workloads. This thesis proposes a range of hardware mechanisms to improve TLB performance. The second challenge we address pertains to the security mechanisms offered by the virtual memory abstraction through memory protection and process isolation. Despite their utility, protection/isolation are insufficient to avoid important classes of remote attacks. Attackers can corrupt the operating system and thereby gain control of the entire machine. Therefore, there is a need for security mechanisms complementary to those provided by virtual memory. We propose lowoverhead mechanisms achieve this. Our approach is to build hardware that can snapshot
Influence of Research Methods and Statistics Courses on Everyday Reasoning, Critical Abilities, and Belief in Unsubstantiated Phenomena

Do undergraduate courses in psychology Research Methods (RM) and Statistics (STAT) improve general reasoning skills and scientific "critical abilities"? Psychology students concurrently enrolled in introductory RM and STAT were randomly assigned to one of three conditions: a baseline group was tested at the beginning of the semester; another group was tested after completion of KM and STAT; and a third group completed R M and STAT and also received 3 tutorial sessions that specifically emphasized transfer of the course material to reasoning in a more general context. A group of students in a humanities programme provided a general comparison group. All participants were assessed on tests of general reasoning and of critical abilities. Respondents also completed a questionnaire that assessed their willingness to endorse scientifically unsubstantiated phenomena. The KM and STAT courses by themselves did not enhance students' general reasoning or critical ability. The group receiving tutorial sessions in addition to the RM and STAT did, however, perform significantly better than the baseline group. Willingness to endorse belief in unsubstantiated phenomena was not affected by the courses.
Structural Studies of Yeast Δ1-Pyrroline-5-carboxylate Dehydrogenase (ALDH4A1): Active Site Flexibility and Oligomeric State

The proline catabolic enzyme Δ1-pyrroline-5-carboxylate dehydrogenase (ALDH4A1) catalyzes the NAD+-dependent oxidation of γ-glutamate semialdehyde to l-glutamate. In Saccharomyces cerevisiae, ALDH4A1 is encoded by the PUT2 gene and known as Put2p. Here we report the steady-state kinetic parameters of the purified recombinant enzyme, two crystal structures of Put2p, and the determination of the oligomeric state and quaternary structure from small-angle X-ray scattering and sedimentation velocity. Using Δ1-pyrroline-5-carboxylate as the substrate, catalytic parameters kcat and Km were determined to be 1.5 s–1 and 104 μM, respectively, with a catalytic efficiency of 14000 M–1 s–1. Although Put2p exhibits the expected aldehyde dehydrogenase superfamily fold, a large portion of the active site is disordered in the crystal structure. Electron density for the 23-residue aldehyde substrate-binding loop is absent, implying substantial conformational flexibility in solution. We furthermore report a new crystal form of human ALDH4A1 (42% identical to Put2p) that also shows disorder in this loop. The crystal structures provide evidence of multiple active site conformations in the substrate-free form of the enzyme, which is consistent with a conformational selection mechanism of substrate binding. We also show that Put2p forms a trimer-of-dimers hexamer in solution. This result is unexpected because human ALDH4A1 is dimeric, whereas some bacterial ALDH4A1s are hexameric. Thus, global sequence identity and domain of life are poor predictors of the oligomeric states of ALDH4A1. Mutation of a single Trp residue that forms knob-in-hole interactions across the dimer–dimer interface abrogates hexamer formation, suggesting that this residue is the center of a protein–protein association hot spot.
Individually Tailored Screening of Susceptibility to Sarcopenia Using p53 Codon 72 Polymorphism, Phenotypes, and Conventional Risk Factors

Background and Aim. p53 activity plays a role in muscle homeostasis and skeletal muscle differentiation; all pathways that lead to sarcopenia are related to p53 activities. We investigate the allelic frequency of the TP53 codon 72 in exon 4 polymorphism in the Italian female population and the association with appendicular skeletal muscle mass index in normal weight (NW), normal weight obese (NWO), and preobese-obese (Preob-Ob) subjects. Methods. We evaluated anthropometry, body composition, and p53 polymorphism in 140 women distinguished in NW, NWO, and Preob-Ob. Results. *Arg/*Arg genotype increases sarcopenia risk up to 20% (*Arg/*Arg genotype OR = 1.20; 95% CI = 0.48–2.9; *proallele carriers OR = 0.83; 95% CI = 0.83–2.06). The risk of being sarcopenic for *Arg/*Arg genotype in NWO and Preob-Ob is 31% higher than NW carriers of *proallele (RR = 0,31, 95% CI = 0,15–0,66, P = 0,0079). We developed a model able to predict sarcopenia risk based on age, body fat, and p53 polymorphism. Conclusion. Our study evidences that genotyping TP53 polymorphism could be a useful new genetic approach, in association with body composition evaluations, to assess sarcopenia risk.
Surface Deformation on MULTI

A major component of 3D design involves the manipulation of curved surfaces or the complex triangle meshes which approximate them. In the specific case of land-use planning design, these surfaces often represent the underlying terrain. Many techniques exist for the deformation of terrain surfaces for a single user. Building on existing work in the use of laser pointers for shared display groupware, we present a system using laser pointers on the MULTI platform to manipulate terrain in a 3D scene. The system provides several different tools for terrain manipulation. We provide a usability study on this system running on MULTI, comparing the laser pointer to the mouse, and the wall display to the tabletop. The factors compared include accuracy, speed, visibility, comfort and overall preference/ease of use. Our goal was to determine an optimal usage of MULTI’s screens and input devices for the purpose of 3D surface deformation.