Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition

Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to recognize and classify different vehicle models. Several approaches have been proposed to address this challenge, however they can perform in restricted conditions. Here, we formulate the vehicle make and model recognition as a fine-grained classification problem and propose a new configurable on-road vehicle make and model recognition framework. We benefit from the unsupervised feature learning methods and in more details we employ Locality constraint Linear Coding (LLC) method as a fast feature encoder for encoding the input SIFT features. The proposed method can perform in real environments of different conditions. This framework can recognize fifty models of vehicles and has an advantage to classify every other vehicle not belonging to one of the specified fifty classes as an unknown vehicle. The proposed MMR framework can be configured to become faster or more accurate based on the application domain. The proposed approach is examined on two datasets including Iranian on-road vehicle dataset and CompuCar dataset. The Iranian on-road vehicle dataset contains images of 50 models of vehicles captured in real situations by traffic cameras in different weather and lighting conditions. Experimental results show superiority of the proposed framework over the state-of-the-art methods on Iranian on-road vehicle datatset and comparable results on CompuCar dataset with 97.5% and 98.4% accuracies, respectively.
How robust is familiar face recognition? A repeat detection study of more than 1000 faces

Recent theories suggest that familiar faces have a robust representation in memory because they have been encountered over a wide variety of contexts and image changes (e.g. lighting, viewpoint and expression). By contrast, unfamiliar faces are encountered only once, and so they do not benefit from such richness of experience and are represented based on image-specific details. In this registered report, we used a repeat detection task to test whether familiar faces are recognized better than unfamiliar faces across image changes. Participants viewed a stream of more than 1000 celebrity face images for 0.5 s each, any of which might be repeated at a later point and has to be detected. Some participants saw the same image at repeats, while others saw a different image of the same face. A post-experimental familiarity check allowed us to determine which celebrities were and were not familiar to each participant. We had three predictions: (i) detection would be better for familiar than unfamiliar faces, (ii) detection would be better across same rather than different images, and (iii) detection of familiar faces would be comparable across same and different images, but detection of unfamiliar faces would be poorer across different images. We obtained support for the first two predictions but not the last. Instead, we found that repeat detection of faces, regardless of familiarity, was poorer across different images. Our study suggests that the robustness of familiar face recognition may have limits, and that under some conditions, familiar face recognition can be just as influenced by image changes as unfamiliar face recognition.
Neuroanatomy of Gryposuchus neogaeus (Crocodylia, Gavialoidea): a first integral description of the braincase and endocranial morphological variation in extinct and extant gavialoids

ABSTRACT Morphological studies of the braincase and cranial endocast of fossil crocodylians, especially gavialids, are scarce. Here, we present a detailed description of the neuroanatomy of Gryposuchus neogaeus from the Miocene of Argentina, based on CT scans. The cranial endocast is sub-horizontal and the angle formed between the mid-brain and the hind-brain is poorly marked. When compared with Gavialis gangeticus, the mid-brain of G. neogaeus is relatively shorter, although the distribution of cranial nerves is similar. In the floor of the endocranial cavity, posterior to the dorsum sellae, there is a median foramen that leads into a canal that runs anteroventrally through the basisphenoid to penetrate the posterior wall of the pituitary fossa (open foramen for the basilar artery? ). The same structure is present in G. gangeticus, but is absent in other living crocodylians, suggesting a potential synapomorphy of Gavialoidea. The pneumaticity of the skull roof and the lateral branches of the pharyngotympanic system in G. neogaeus are markedly reduced when compared with the extant species. Comparisons with the living Gavialis indicate that the pattern of braincase morphology of Gavialidae was present in the Miocene; however, the internal morphology, including brain shape, pneumaticity of the skull roof and basicranium, is different in the two species. This work is the first step to understand the variation of the neuroanatomy in this group of archosaurs and its palaeobiological implication.
Watch-Learning: Using the Smartwatch for Secondary Language Vocabulary Learning

Many long-term goals, such as second language vocabulary learning, can be achieved by leveraging one's fragmented time in daily life. In this paper, we explore Watch-Learning: using a smartwatch with speech recognition for learning and reviewing second language vocabulary. To evaluate the feasibility and efficiency of Watch-Learning, two studies were performed. One is to find out the differences in time overhead for vocabulary search on smartwatches and smartphones, and the other is to evaluate the frequency and the time cost of the "review" function on smartwatches and smartphones. The results show that, compared to smartphones, a smartwatch with speech recognition can save about 30 % time for vocabulary searching and can save approximately 70 % time when reviewing. Our findings are meaningful for designs of language-learning applications on smartwatches and can be extended to more micro-learning projects.
Translation, Cultural Adaptation of Spiritual Needs Questionnaire in Pakistan

The current study was conducted with the aim of translating, adapting, and exploring the factor structure of Spiritual Needs Questionnaire (SpNQ) in chronically ill patients. To meet this objective, the English-version SpNQ was translated into Urdu for Pakistan following standard methods of translation and adaptation. The Urdu version was then used to collect data from a sample of 150 chronically ill patients. The results showed that spiritual needs were significantly associated with each other. Compared to the previous English-version that proposed a four-factor solution, the exploratory factor analysis revealed a three-factor structure for the Urdu version with good internal consistency coefficients, indicating the new version to be a reliable measure.
Design Artefacts to Support People with a Disability to Build Personal Infrastructures

A person with a disability has to assemble support services and technologies from different organisations in order to live well, which may require help from family. We call this assembling of services and technologies personal infrastructuring, the process of learning about how to navigate the world, what support is available, and how to obtain and design new support through various organisational infrastructures. Such infrastructures include disability services organisations, the health sector, community organisations, and friend and family networks. Our vision was to explore how a person with a disability might engage in design with volunteer designers to meet their unique needs that were not met by their existing infrastructure of organisations, products and services. Through codesign with two people and their families, we developed design artefacts such as user profiles and video stories to support communication, mutual learning, need finding and need expression. We discovered that these design artefacts were used beyond their immediate purposes of design to further support their personal infrastructuring. In this paper, we discuss how understandings of infrastructure and infrastructuring from Science and Technology Studies and Information Systems translate into familial contexts and the concept of personal infrastructuring.
Adaptive control charts for skew‐normal distribution

The standard Shewhart‐type X¯ chart, named FSS‐ X¯ chart, has been widely used to detect the mean shift of process by implementing fixed sample and sampling frequency schemes. The FSS‐ X¯ chart could be sensitive to the normality assumption and is inefficient to catch small or moderate shifts in the process mean. To monitor nonnormally distributed variables, Li et al [Commun Stat‐Theory Meth. 2014; 43(23):4908‐4924] extended the study of Tsai [Int J Reliab Qual Saf Eng. 2007; 14(1):49‐63] to provide a new skew‐normal FSS‐ X¯ (SN FSS‐ X¯ ) chart with exact control limits for the SN distribution. To enhance the sensitivity of the SN FSS‐ X¯ chart on detecting small or moderate mean shifts in the process, adaptive X¯ charts with variable sampling interval (VSI), variable sample size (VSS), and variable sample size and sampling interval (VSSI) are introduced for the SN distribution in this study. The proposed adaptive control charts include the normality adaptive charts as special cases. Simulation results show that all the proposed SN VSI‐ X¯ , SN VSS‐ X¯ , and SN VSSI‐ X¯ charts outperform the SN FSS‐ X¯ chart on detecting small or moderate shifts in the process mean. The impact of model misspecification on using the proposed adaptive charts and the sample size impact for using the FSS‐ X¯ chart to monitor the mean of SN data are also discussed. An example about single hue value in polarizer manufacturing process is used to illustrate the applications of the proposed adaptive charts.
Exploiting Mobility in Cache-Assisted D2D Networks: Performance Analysis and Optimization

Caching popular content at mobile devices, accompanied by device-to-device (D2D) communications, is one promising technology for effective mobile content delivery. User mobility is an important factor when investigating such networks, which unfortunately was largely ignored in most previous works. Preliminary studies have been carried out but the effect of mobility on the caching performance has not been fully understood. In this paper, by explicitly considering users’ contact and inter-contact durations via an alternating renewal process, we first investigate the effect of mobility with a given cache placement. A tractable expression of the data offloading ratio, i.e., the proportion of requested data that can be delivered via D2D links, is derived, which is proved to be increasing with the user moving speed. The analytical results are then used to develop an effective mobility-aware caching strategy to maximize the data offloading ratio. Simulation results are provided to confirm the accuracy of the analytical results and also validate the effect of user mobility. Performance gains of the proposed mobility-aware caching strategy are demonstrated with both stochastic models and real-life data sets. It is observed that the information of the contact durations is critical to design cache placement, especially when they are relatively short or comparable to the inter-contact durations.
Detailed heap profiling

Modern software systems heavily use the memory heap. As systems grow more complex and compute with increasing amounts of data, it can be difficult for developers to understand how their programs actually use the bytes that they allocate on the heap and whether improvements are possible. To answer this question of heap usage efficiency, we have built a new, detailed heap profiler called Memoro. Memoro uses a combination of static instrumentation, subroutine interception, and runtime data collection to build a clear picture of exactly when and where a program performs heap allocation, and crucially how it actually uses that memory. Memoro also introduces a new visualization application that can distill collected data into scores and visual cues that allow developers to quickly pinpoint and eliminate inefficient heap usage in their software. Our evaluation and experience with several applications demonstrates that Memoro can reduce heap usage and produce runtime improvements of 10%.
Searching and Matching Texture-free 3D Shapes in Images

The goal of this paper is to search and match the best rendered view of a texture-free 3D shape to an object of interest in a 2D query image. Matching rendered views of 3D shapes to RGB images is challenging because, 1) 3D shapes are not always a perfect match for the image queries, 2) there is great domain difference between rendered and RGB images, and 3) estimating the object scale versus distance is inherently ambiguous in images from uncalibrated cameras. In this work we propose a deeply learned matching function that attacks these challenges and can be used for a search engine that finds the appropriate 3D shape and matches it to objects in 2D query images. We evaluate the proposed matching function and search engine with a series of controlled experiments on the 24 most populated vehicle categories in PASCAL3D+. We test the capability of the learned matching function in transferring to unseen 3D shapes and study overall search engine sensitivity w.r. t available 3D shapes and object localization accuracy, showing promising results in retrieving 3D shapes given 2D image queries.
"More than just Space": Designing to Support Assemblage in Virtual Creative Hubs

This paper aims to understand interactions at creative hubs, and how this understanding can be used to inform the design of virtual creative hubs -- i.e., social-technical infrastructures that support hub-like interactions amongst people who aren't spatially or temporally co-located. We present findings from a qualitative field study in UK creative hubs, in which we conducted seventeen observations and ten interviews in three sites. Our findings reveal a range of key themes that define interactions within creative hubs: smallness of teams; neutrality of the hubs; value of the infrastructure; activities and events; experience sharing; and community values and rules. These interactions together form a network and elements that influence one another to make a creative hub more than just physical space. We employ the concept of Assemblage introduced by Deleuze and Guattari to explore this network of interactions and, in doing so, reveal implications for the design of virtual creative hubs that seek to replicate them.
Joint Beamforming and Power Allocation in Downlink NOMA Multiuser MIMO Networks

In this paper, a novel joint design of beamforming and power allocation is proposed for a multi-cell multiuser multiple-input multiple-output non-orthogonal multiple access network. In this network, base stations adopt coordinated multipoint for downlink transmission. We study a new scenario where the users are divided into two groups according to their quality-of-service requirements, rather than their channel qualities as investigated in the literature. Our proposed joint design aims to maximize the sum rate of the users in one group with the best effort while guaranteeing the minimum required target rates of the users in the other group. The joint design is formulated as a non-convex NP-hard problem. To make the problem tractable, a series of transformations is adopted to simplify the design problem. Then, an iterative suboptimal resource allocation algorithm based on successive convex approximation is proposed. In each iteration, a rank-constrained optimization problem is solved optimally via semidefinite program relaxation. Numerical results reveal that the proposed scheme offers significant sum-rate gains compared to the existing schemes and converges fast to a suboptimal solution.
Predicting double negativity using transmitted phase in space coiling metamaterials

Metamaterials are engineered materials that offer the flexibility to manipulate the incident waves leading to exotic applications such as cloaking, extraordinary transmission, sub-wavelength imaging and negative refraction. These concepts have largely been explored in the context of electromagnetic waves. Acoustic metamaterials, similar to their optical counterparts, demonstrate anomalous effective elastic properties. Recent developments have shown that coiling up the propagation path of acoustic wave results in effective elastic response of the metamaterial beyond the natural response of its constituent materials. The effective response of metamaterials is generally evaluated using the ‘S’ parameter retrieval method based on amplitude of the waves. The phase of acoustic waves contains information of wave pressure and particle velocity. Here, we show using finite-element methods that phase reversal of transmitted waves may be used to predict extreme acoustic properties in space coiling metamaterials. This change is the difference in the phase of the transmitted wave with respect to the incident wave. This method is simpler when compared with the more rigorous ‘S’ parameter retrieval method. The inferences drawn using this method have been verified experimentally for labyrinthine metamaterials by showing negative refraction for the predicted band of frequencies.
An Experience Using On-Computer Programming Questions During Exams

Exams in programming intensive computer science courses are often completed on paper. While a variety of question types may be used, it is common to require students to write short programs on paper without the aid of the development tools and reference materials that they have used throughout the semester. Our students have expressed concerns that such exams are not reflective of the "real world" and that they believe that their grade on such exams is not an accurate reflection of their programming ability. In this paper we report on our recent experience using exams that include a closed book multiple choice portion answered on paper and an on-computer programming portion where students were asked to create small programs using their usual development tools and reference materials, including full internet access. Students' experience with such exams is reported for a class of 126 students, and a number of advantages and challenges observed by the course instructor are also discussed. Overall, both the students and the course instructor found that on-computer programming questions were preferable to answering such questions on paper.
Hierarchical Clustering with Prior Knowledge

Hierarchical clustering is a class of algorithms that seeks to build a hierarchy of clusters. It has been the dominant approach to constructing embedded classification schemes since it outputs dendrograms, which capture the hierarchical relationship among members at all levels of granularity, simultaneously. Being greedy in the algorithmic sense, a hierarchical clustering partitions data at every step solely based on a similarity / dissimilarity measure. The clustering results oftentimes depend on not only the distribution of the underlying data, but also the choice of dissimilarity measure and the clustering algorithm. In this paper, we propose a method to incorporate prior domain knowledge about entity relationship into the hierarchical clustering. Specifically, we use a distance function in ultrametric space to encode the external ontological information. We show that popular linkage-based algorithms can faithfully recover the encoded structure. Similar to some regularized machine learning techniques, we add this distance as a penalty term to the original pairwise distance to regulate the final structure of the dendrogram. As a case study, we applied this method on real data in the building of a customer behavior based product taxonomy for an Amazon service, leveraging the information from a larger Amazon-wide browse structure. The method is useful when one wants to leverage the relational information from external sources, or the data used to generate the distance matrix is noisy and sparse. Our work falls in the category of semi-supervised or constrained clustering.
Open Source Barriers to Entry, Revisited: A Sociotechnical Perspective

Research has revealed that significant barriers exist when entering Open-Source Software (OSS) communities and that women disproportionately experience such barriers. However, this research has focused mainly on social/cultural factors, ignoring the environment itself — the tools and infrastructure. To shed some light onto how tools and infrastructure might somehow factor into OSS barriers to entry, we conducted a field study with five teams of software professionals, who worked through five use-cases to analyze the tools and infrastructure used in their OSS projects. These software professionals found tool/infrastructure barriers in 7% to 71% of the use-case steps that they analyzed, most of which are tied to newcomer barriers that have been established in the literature. Further, over 80% of the barrier types they found include attributes that are biased against women.
Optimizing Worst-Case Execution Times Using Mainstream Compilers

Compiler optimizations are widely used to enhance the average case performance of software, and these techniques are very effective and advance with every compiler version. However, in realtime systems, it is the worst-case performance that matters. While there are techniques that aim at reducing the worst-case execution time (WCET), most of them are specific to certain targets and not implemented in mainstream compilers. In this paper, we present our ongoing work for a generic approach to harness the power of existing compiler optimizations for WCET reduction. Our approach is based on an existing compiler technology called Feedback-Directed Optimization (FDO), which can reduce the execution time of a program by making use of profiling data, and recently became popular due to major improvements. We first introduce a static analysis to efficiently compute a worst-case timing profile based on control flow dominators. During this analysis we perform a minimal number of automated calls to a WCET analyzer. The resulting profile contains basic block and branch execution counts, which then can be used in the regular FDO workflow. Preliminary results show that significant WCET reductions are possible, but depend on many factors that need more investigation.
COMPARATIVE MACROSCOPIC STuDY ON OSTEOCHONDRAL DEFECTS PRODuCED IN FEMuRS OF RABBITS AND FILLED WITH SugAR CANE BIOPOLYMER gEL

Objective: To study the surface, coloring, consistency, continuity and healing of osteochondral defects produced in the femoral condyles of rabbits and filled with sugar cane biopolymer gel (SCBg), after 90, 120 and 180 days, and in comparison with a control group. Method: Sixteen adult New Zealand white rabbits aged 6 to 7 months, weighing between 2 and 2.5 kg and without locomotor system abnormalities were studied. In all the animals, a defect was made in the femoral condyles of the right and left knees, measuring 3.2 mm in diameter and 4 mm in depth, using a trephine. The animals were divided into two groups: study group formed by the right knees, in which the medial and lateral condyles received implants of SCBg; and control group formed by the left knees, in which the medial and lateral condyles were allowed to Rev Bras Ortop. 2011;46(5):577-84 heal naturally. The knees were assessed 90, 120 and 180 days after the operation. After the animals had been sacrificed, the anatomical specimens were resected and placed in Bouin’s solution. They were then photographed with a Nikon Coolpix 5400® coupled to a Nikon SM2800® stereoscopic loupe, to analyze the surface, coloring, consistency, continuity and healing. Results: The results were evaluated using the chi-square test. There were no significant differences in the macroscopic assessments of healing between the study and control groups. Conclusion: With regard to the surface, coloring, consistency, continuity and healing of the defects, the macroscopic appearance of the tissue repaired with SCBg was similar to that of the control group.