Miracle-dz/UniFAR-FTUs huggingface dataset:
3D model retrieval with morphing-based geometric and topological feature maps

Recent advancement in 3D digitization techniques have prompted the need for 3D object retrieval. Our method of comparing 3D objects for retrieval is based on 3D morphing. It computes, for each 3D object, two spatial feature maps that describe the geometry and topology of the surface patches on the object, while preserving the spatial information of the patches in the maps. The feature maps capture the amount of effort required to morph a 3D object into a canonical sphere, without performing explicit 3D morphing. Fourier transforms of the feature maps are used for object comparison so as to achieve invariant retrieval under arbitrary rotation, reflection, and non-uniform scaling o the objects. Experimental results show that our method of retrieving 3D models is very accurate, achieving a precision of above . 086 even at a recall rate of 1.0.
Reduced reference IQA based on structural dissimilarity

Distortion estimation in objective domain plays an important role during Image Quality Assessment (IQA). Reduced Reference IQA requires only partial information about the reference image which can be transmitted through an ancillary data channel and is useful where complete image cannot be accessed (as reference for IQA). In this paper, IQA is performed based on a reduced reference approach with minimal complexity. The proposed evaluation methodology involves decomposition of images into sub-bands using a suitable wavelet family for features extraction. These extracted features are then used to obtain a `structural dissimilarity measure' sensitive towards structural distortions. The computational complexity during estimation of features is reduced in this method by using combinations of integral image and gradient magnitude approaches. The aim of this approach is to analyse different distortions with a single reduced reference metric and maintaining its coherence with the Human Visual System (HVS). This has been justified in simulations by the healthy correlation of IQA between proposed reduced reference metric and human opinion.
A Cache Replacement Policy Using Adaptive Insertion and Re-reference Prediction

Previous research shows that LRU replacement policy is not efficient when applications exhibit a distant re-reference interval. Recently proposed RRIP policy improves performance for such workloads. However, RRIP lacks of access recency information, which may confuse the replacement policy to make accurate prediction. Consequently, RRIP is not robust for recency-friendly workloads. This paper proposes an Adaptive Insertion and Re-reference Prediction (AI-RRP) policy which evicts data based on both re-reference prediction value and the access recency information. To make the replacement policy more adaptive across different workloads and different phases during execution, Dynamic AI-RRP (DAI-RRP) is proposed which adjusts the insertion position and prediction value for different access patterns. Simulation results show DAI-RRP reduces CPI over LRU and Dynamic RRIP by an average of 8.3% and 4.1% respectively on a single-core processor with a 1MB 16-way set last-level cache (LLC). Evaluations on quad-core CMP with a 4MB shared LLC show that DAI-RRP outperforms LRU and Dynamic RRIP (DRRIP) on the weighted speedup metric by an average of 13.2% and 26.7% respectively. Furthermore, compred to LRU, DAI-RRP requires similar hardware, or even less hardware for high-associativity cache.
Predicting Sports Scoring Dynamics with Restoration and Anti-Persistence

Professional team sports provide an excellent domain for studying the dynamics of social competitions. These games are constructed with simple, well-defined rules and payoffs that admit a high-dimensional set of possible actions and nontrivial scoring dynamics. The resulting gameplay and efforts to predict its evolution are the object of great interest to both sports professionals and enthusiasts. In this paper, we consider two online prediction problems for team sports: given a partially observed game Who will score next? and ultimately Who will win? We present novel interpretable generative models of within-game scoring that allow for dependence on lead size (restoration) and on the last team to score (anti-persistence). We then apply these models to comprehensive within-game scoring data for four sports leagues over a ten-year period. By assessing these models' relative goodness-of-fit we shed new light on the underlying mechanisms driving the observed scoring dynamics of each sport. Furthermore, in both predictive tasks, the performance of our models consistently outperforms baselines models, and our models make quantitative assessments of the latent team skill, over time.
Projected clustering with subset selection

It has always been a major challenge to cluster high dimensional data considering the inherent sparsity of data-points. Our model uses attribute selection and handles the sparse structure of the data effectively. The subset section is done by two different methods. In first method, we select the subset which has most informative attributes that do preserve cluster structure using LASSO (Least Absolute Selection and Shrinkage Operator). Though there are other methods for attribute selection, LASSO has distinctive properties that it selects the most correlated set of attributes of the data. In second method, we select the subset of linearly independent attributes using QR factorization. This model also identifies dominant attributes of each cluster which retain their predictive power as well. The quality of the projected clusters formed, is also assured with the use of LASSO.
Do Teen Births Keep American Crime High?*

The United States has a high teenage birth rate relative to other developed countries. Children of teenagers experience more difficult childhoods than other children and hence may be more likely subsequently to be victims or perpetrators of crimes. I assess to what extent international patterns in teenage birth rates can explain why the United States had the highest crime rates of developed countries in the 1980s and why U.S. relative crime rates subsequently fell. Using internationally comparable crime rates spanning 1989–2000, I find that assault rates are increased by an increase in the proportion of young adults who were born to a teenage mother. Intimate‐partner assault, a crime most commonly occurring among young adults, is most affected. Variation in teenage birth rates fully explain the initially high U.S. assault level and prevented the subsequent fall in assault rate from being 20 percent greater. I also present evidence on larceny and burglary.
Cloud seeding as a technique for studying aerosol‐cloud interactions in marine stratocumulus

Giant hygroscopic aerosols were introduced into a solid marine stratocumulus cloud (200 m thick) by burning hygroscopic flares mounted on an aircraft. The cloud microphysical response in two parallel seeding plumes was observed using an instrumented aircraft making 16 transects of the plumes. The cloud drop size distribution width increased in the plumes due to an increased number of small cloud drops (3–5 μm) on the earlier transects and a 5‐fold increase in the number of large drops (20–40 μm) relative to the background cloud 30 minutes later. The cloud effective diameter increased from about 11 μm in the background to 13 μm in the plumes. Although the giant nuclei were only a small fraction of the total aerosols produced by the flares, they dominated the cloud response. The merit of the seeding approach for controlled observational studies of aerosol‐cloud interactions in marine stratocumulus was demonstrated.
Reducing Auditory Hypersensitivities in Autistic Spectrum Disorder: Preliminary Findings Evaluating the Listening Project Protocol

Auditory hypersensitivities are a common feature of autism spectrum disorder (ASD). In the present study, the effectiveness of a novel intervention, the listening project protocol (LPP), was evaluated in two trials conducted with children diagnosed with ASD. LPP was developed to reduce auditory hypersensitivities. LPP is based on a theoretical “neural exercise” model that uses computer altered acoustic stimulation to recruit the neural regulation of middle ear muscles. Features of the intervention stimuli were informed by basic research in speech and hearing sciences that has identified the specific acoustic frequencies necessary to understand speech, which must pass through middle ear structures before being processed by other components of the auditory system. LPP was hypothesized to reduce auditory hypersensitivities by increasing the neural tone to the middle ear muscles to functionally dampen competing sounds in frequencies lower than human speech. The trials demonstrated that LPP, when contrasted to control conditions, selectively reduced auditory hypersensitivities. These findings are consistent with the polyvagal theory, which emphasizes the role of the middle ear muscles in social communication.
Intact implicit memory for novel patterns in Alzheimer's disease.

Repetition priming is a kind of implicit memory (learning without awareness) that does not depend on the medial temporal-lobe system. For example, the amnesic patient H.M. , who underwent bilateral medial temporal-lobe resection, shows intact priming with novel patterns, suggesting that perceptual priming with nonverbal material does not depend on areas critical for explicit memory. A logical candidate for the neural substrate that supports this kind of priming is the peristriate cortex, an area that is relatively spared in Alzheimer's disease (AD). We therefore predicted that AD subjects would be unimpaired on pattern priming. Subjects copied each of six target figures onto dot patterns. After performing a 3-min distractor task, they were given the same dot patterns (without lines) and asked to draw the first figure that came to mind by connecting the dots with straight lines. Subsequently, in a test of recognition (explicit) memory, subjects viewed each of the six patterns of dots that they had copied previously and were asked to indicate which of four possible completions corresponded to the figure that they had copied 3 min earlier. The AD and control groups achieved comparable priming scores, but AD subjects were significantly impaired in recognizing the patterns explicitly. Our finding of intact pattern priming in AD provides, for the first time, evidence that pattern priming depends on the peristriate cortex.
Simulation of Incremental Conductance MPPT based two phase interleaved boost converter using MATLAB/Simulink

The Photovoltaic power generation systems are connected to the load via DC-DC converters. The DC-DC converter circuits are controlled by Maximum Power Point Tracking (MPPT) controllers to extract maximum power from the source. Modeling and simulation of Interleaved Boost converter (IBC) with Incremental Conductance (InC) MPPT algorithm for PV application is discussed in this paper. The mathematical model of PV module, interleaved boost Converter and MPPT controller are simulated using MATLAB/Simulink. The PV system is simulated for various temperature and irradiation level and the results are obtained.
Online multi-task collaborative filtering for on-the-fly recommender systems

Traditional batch model-based Collaborative Filtering (CF) approaches typically assume a collection of users' rating data is given a priori for training the model. They suffer from a common yet critical drawback, i.e., the model has to be re-trained completely from scratch whenever new training data arrives, which is clearly non-scalable for large real recommender systems where users' rating data often arrives sequentially and frequently. In this paper, we investigate a novel efficient and scalable online collaborative filtering technique for on-the-fly recommender systems, which is able to effectively online update the recommendation model from a sequence of rating observations. Specifically, we propose a family of online multi-task collaborative filtering (OMTCF) algorithms, which tackle the online collaborative filtering task by exploiting the similar principle as online multitask learning. Encouraging empirical results on large-scale datasets showed that the proposed technique is significantly more effective than the state-of-the-art algorithms.
Edinburgh Research Explorer a New Approach for Testing Properties of Discrete Distributions a New Approach for Testing Properties of Discrete Distributions

General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact openaccess@ed.ac. uk providing details, and we will remove access to the work immediately and investigate your claim. Abstract—We study problems in distribution property testing: Given sample access to one or more unknown discrete distributions, we want to determine whether they have some global property or are epsilon-far from having the property in L1 distance (equivalently, total variation distance, or " statistical distance "). In this work, we give a novel general approach for distribution testing. We describe two techniques: our first technique gives sample–optimal testers, while our second technique gives matching sample lower bounds. As a consequence, we resolve the sample complexity of a wide variety of testing problems. Our upper bounds are obtained via a modular reduction-based approach. Our approach yields optimal testers for numerous problems by using a standard L2-identity tester as a black-box. Using this recipe, we obtain simple estimators for a wide range of problems, encompassing many problems previously studied in the TCS literature, namely: (1) identity testing to a fixed distribution, (2) closeness testing between two unknown distributions (with equal/unequal sample sizes), (3) independence testing (in any number of dimensions), (4) closeness testing for collections of distributions, and (5) testing histograms. For all of these problems, our testers are sample-optimal, up to constant factors. With the exception of (1), ours are the first sample-optimal testers for the corresponding problems. Moreover, our estimators are significantly simpler to state and analyze compared to previous results. As an important application of our reduction-based technique , we obtain the first adaptive algorithm for testing equivalence between two unknown distributions. The sample complexity of our algorithm depends on the structure of the unknown distributions – as opposed to merely their domain size – and is significantly better compared to the worst-case optimal L1-tester in many natural instances. Moreover, our technique naturally generalizes to other metrics beyond the L1-distance. As an illustration of its flexibility, we use it to …
A principal palm-line extraction method for palmprint images based on diversity and contrast

Line feature is one of the most important features of palmprint image. A novel approach of principal palm-line extraction is proposed in this paper based on their characteristics of ridge edges. First, gray adjustment and median filtering are used to enhance contrast and weaken noise. Then, palm-lines are detected based on diversity and contrast. After this step, an improved Hilditch algorithm is used to do thinning, an edge tracking approach is applied to get rid of twigs and short lines, and then, the broken lines are connected. Finally, the single pixel principal palm-line image is obtained. The experiment results show that the principle palm-lines of most pictures can be detected correctly by using this algorithm referred above. Moreover, the algorithm can provide effective and accurate statistics for palmprint identification.
Findings of the 2016 Conference on Machine Translation

This paper presents the results of the WMT16 shared tasks, which included five machine translation (MT) tasks (standard news, IT-domain, biomedical, multimodal, pronoun), three evaluation tasks (metrics, tuning, run-time estimation of MT quality), and an automatic post-editing task and bilingual document alignment task. This year, 102 MT systems from 24 institutions (plus 36 anonymized online systems) were submitted to the 12 translation directions in the news translation task. The IT-domain task received 31 submissions from 12 institutions in 7 directions and the Biomedical task received 15 submissions systems from 5 institutions. Evaluation was both automatic and manual (relative ranking and 100-point scale assessments). The quality estimation task had three subtasks, with a total of 14 teams, submitting 39 entries. The automatic post-editing task had a total of 6 teams, submitting 11 entries.
Markers of kidney function in the elderly in relation to the new CKD-EPI formula for estimation of glomerular filtration rate

Introduction Neutrophil gelatinase-associated lipocalin (NGAL) has been recently proved useful in the quantitation of chronic kidney disease (CKD). The aim of the study was to assess prevalence of CKD according to the Modification of Diet in Renal Disease (MDRD), Cockcroft-Gault, and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulae in 412 patients with normal serum creatinine and markers of kidney function/injury such as NGAL, cystatin C, and kidney injury molecule-1 (KIM-1) in these patients in relation to age (below and over 65 years). Material and methods We included in the study 1005 patients with coronary artery disease and normal serum creatinine. However, markers of kidney function/injury were assessed in 412 patients. The NGAL, cystatin C and KIM-1, were assessed using commercially available kits. Results Patients over 65 years had significantly lower estimated glomerular filtration rate (eGFR) than their younger counterparts despite identical creatinine. They also had significantly lower haematocrit, despite similar Hb, lower platelet count, higher serum fibrinogen, higher systolic (SBP) and lower diastolic blood pressure, higher serum NGAL and cystatin C, but similar urinary NGAL and KIM-1. Serum NGAL correlated with age, haematocrit, leukocyte, platelet and erythrocyte count, eGFR, creatinine, fasting glucose, HbA1c, fibrinogen, SBP, and diabetes duration. In multiple regression analysis kidney function (eGFR, creatinine clearance or creatinine), cystatin C and SBP were predictors of serum NGAL. Conclusions In our study we found a very high prevalence of CKD up to 61% in elderly patients with coronary artery disease and normal serum creatinine. Neutrophil gelatinase-associated lipocalin could be a sensitive marker of kidney function, particularly in elderly patients with another risk factor for kidney damage, i.e. hypertension.
Preference elicitation in combinatorial auctions

Combinatorial auctions (CAs) where bidders can bid on bundles of items can be very desirable market mechanisms when the items sold exhibit complementarity and/or substitutability, so the bidder's valuations for bundles are not additive. However, in a basic CA, the bidders may need to bid on exponentially many bundles, leading to difficulties in determining those valuations, undesirable information revelation, and unnecessary communication. In this paper we present a design of an auctioneer agent that uses topological structure inherent in the problem to reduce the amount of information that it needs from the bidders. An analysis tool is presented as well as data structures for storing and optimally assimilating the information received from the bidders. Using this information, the agent then narrows down the set of desirable (welfare-maximizing or Pareto-efficient) allocations, and decides which questions to ask next. Several algorithms are presented that ask the bidders for value, order, and rank information. A method is presented for making the elicitor incentive compatible.
Design of observer-based controllers for LPV systems with unknown parameters

Output-based feedback control of LPV systems is an important problem, as in practice it is rarely the case that the full state variable is available for feedback. In this paper we consider this problem in the case of discrete-time LPV systems for which the parameters are not exactly known, but only available with a finite accuracy or affected by noise during their measurement. The controllers are obtained using a separate design of an observer and a state feedback and the interconnection is proven to stabilize the LPV system despite the mismatch between the true and available parameters. The approach allows to maximize the parameter uncertainty while still guaranteeing closed-loop stability. In addition, it is possible to make tradeoffs between the admissible level of mismatch on the one hand and the performance in terms of decay factors on the other. All the design conditions will be formulated in term of LMIs, which can be solved efficiently, as is also illustrated by a numerical example.
Phase noise suppression algorithm for OFDM-based 60 GHz WLANs

In this paper, we investigate the OFDM-based wireless local area networks (WLANs) operating in the 60 GHz frequency band. The performance of OFDM system is severely degraded by the local oscillator phase noise, which causes both common phase error (CPE) and inter-carrier interference (ICI). We analyze the impact of phase noise on OFDM systems. Moreover, in order to reduce the phase noise problem, we consider the phase noise suppression (PNS) algorithm. Some numerical results are presented to illustrate the effectiveness of the PNS algorithm for OFDM-based 60 GHz WLANs.
The Challenges of Teaching EFL Listening in Iraqi (Kurdistan Region) Universities.

The article is dedicated to the issue of teaching EFL listening in Kurdistan region of Iraq. The important role of listening skills in a FL learning is presented, and the difficulties of listening are analyzed, including language (vocabulary, grammar) and psychological (low motivation and self-confidence as well as a high level of listening anxiety) factors. The article involves a questionnaire survey with participation of 98 students from 8 universities in Kurdistan Region of Iraq and 28 teachers from 7 universities in the same region (universities mostly overlap, so totally 9 universities are involved). The survey shows that the level of listening anxiety among the students is quite high.
Some Mathematical Facts About Optimal Cache Replacement

This article exposes and proves some mathematical facts about optimal cache replacement that were previously unknown or not proved rigorously. An explicit formula is obtained, giving OPT hits and misses as a function of past references. Several mathematical facts are derived from this formula, including a proof that OPT miss curves are always convex, and a new algorithm called OPT tokens, for reasoning about optimal replacement.