Miracle-dz/UniFAR-FTUs huggingface dataset:
T WIN DNN: A T ALE OF T WO D EEP N EURAL N ET - WORKS

Compression technologies for deep neural networks (DNNs), such as weight quantization, have been widely investigated to reduce the DNN model size so that they can be implemented on hardware with strict resource restrictions. However, one major downside of model compression is accuracy degradation. To deal with this problem effectively, we propose a new compressed network inference scheme, with a high accuracy but slower DNN coupled with its highly compressed DNN version that typically delivers much faster inference speed but with a lower accuracy. During inference, we determine the confidence of the prediction of the compressed DNN, and infer the original DNN for the inputs that are considered not confident by the compressed DNN. The proposed design can deliver overall accuracy close to the high accuracy model, but with the latency closer to the compressed DNN. We demonstrate our design on two image classification tasks: CIFAR-10 and ImageNet. Our experiments show that our design can recover up to 94% of accuracy drop caused by extreme network compression, with more than 90% increase in throughput compared to just using the original DNN. This is the first work that considers using a highly compressed DNN along with the original DNN in parallel to improve latency significantly while effectively maintaining the original model accuracy.
Evaluation of Algorithms for Sequential Decision in Biosonar Target Classification

identifying the species of trees given acoustic echo data collected from them, is considered with well-known stochastic classifiers, including single and mixture Gaussian models. Echoes are processed with a preprocessing stage based on a model of mammalian cochlear filtering, using a new discrete low-pass filter characteristic. Stopping time performance of the sequential decision process is evaluated and compared. It is observed that the new low pass filter processing results in faster sequential decisions.
End of year report for parallel vision algorithm design and implementation : January 15, 1986-January 14, 1987

The parallel vision algorithm design and implementation project was established to facilitate vision programming on parallel architectures, particularly low-level vision and robot vehicle control algorithms on the Camegie Mellon Warp machine. To this end, we have (1) demonstrated the use of the Warp machine in several different algorithms; (2) developed a specialized programming language, called Apply, for low-level vision programming on parallel architectures in general, and Warp in particular; (3) used Warp as a research tool in vision, as opposed to using it only for research in parallel vision; (4) developed a significant library of low-level vision programs for use on Warp.
Duality in information retrieval and the hypergeometric distribution

Duality is an important topic in informetrics, especially in connection with the classical informetric laws. Yet, this concept is less studied in information retrieval. It deals with the unification or symmetry between queries and documents, retrieval versus indexing, and relevant versus retrieved documents. These ideas are elaborated in this note and the connection with the hypergeometric distribution is highlighted.
SWAG: Superpixels Weighted by Average Gradients for Explanations of CNNs Supplementary Material

This supplementary material contains elements that were withheld from the main paper due to space constraints. The first is a brief discussion on the hyper-parameter search used to determine the SWAGI+G hyper-parameters, this can be found in Section 4. Secondly we provide many more qualitative examples for explanations generated with both VGG16 and ResNet50 for ImageNet, Stanford Dogs, CUB Birds, and Oxford Flowers. These can be found in Sections 6.1, 6.2, 6.3, and 6.4 respectively. As with the main paper we recommend viewing these images in colour.
A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream

A lot of research has been devoted to identity documents analysis and recognition on mobile devices. However, no publicly available datasets designed for this particular problem currently exist. There are a few datasets which are useful for associated subtasks but in order to facilitate a more comprehensive scientific and technical approach to identity documents recognition more specialized datasets are required. In this paper we present a Mobile Identity Document Video dataset (MIDV-500) consisting of 500 video clips for 50 different identity document types with ground truth which allows to perform research in a wide scope of document analysis problems. Since an important feature of identity documents is their sensitiveness as they contain personal data, all source document images used in MIDV-500 are either in public domain or distributed under public copyright licenses. The dataset is available for download at ftp://smartengines.com/midv-500/.
Analysis of 19 Heliconiine Butterflies Shows Rapid TE-based Diversification and Multiple SINE Births and Deaths

Transposable elements (TEs) play major roles in the evolution of genome structure and function. However, because of their repetitive nature, they are difficult to annotate and discovering the specific roles they may play in a lineage can be a daunting task. Heliconiine butterflies are models for the study of multiple evolutionary processes including phenotype evolution and hybridization. We attempted to determine how TEs may play a role in the diversification of genomes within this clade by performing a detailed examination of TE content and accumulation in 19 species whose genomes were recently sequenced. We found that TE content has diverged substantially and rapidly in the time since several subclades shared a common ancestor with each lineage harboring a unique TE repertoire. Several novel SINE lineages have been established that are restricted to a subset of species. Furthermore, the previously described SINE, Metulj, appears to have gone extinct in two subclades while expanding to significant numbers in others. Finally, a burst of TE origination corresponds temporally to a burst of speciation in the clade, potentially providing support to hypotheses that TEs are drivers of genotypic and phenotypic diversification. This diversity in TE content and activity has the potential to impact how heliconiine butterflies continue to evolve and diverge.
Are Web Applications Ready for Parallelism?

In recent years, web applications have become pervasive. Their backbone is JavaScript, the only programming language supported by all major web browsers. Most browsers run on desktop or mobile devices with parallel hardware. However, JavaScript is by design sequential, and current web applications make little use of hardware parallelism. Are web applications ready to exploit parallel hardware? We answer the question in two steps: First, we survey 174 web developers about the potential and challenges of using parallelism. Then, we study the performance and computation shape of a set of web applications that are representative for the emerging web. Our ﬁndings indicate that emerging web applications do have latent data parallelism, and JavaScript developers’ programming style is not a signiﬁcant impediment to exploiting this parallelism.
Query Evaluation and Web Recognition in Document Databases

A Web and Document Database (WDDB) is a system to manage efficiently local documents and their semantic connection to remote ones. The general objective of a WDDB is to facilitate web search and internet navigation. Abstractly, a WDDB can be defined as a triple <D, U, W>, where D stands for a local document database to store XML documents structurally, U for a set of URLs with each pointing to a remote database which shares common data with the local one, and W for a Web recognizer that identifies information sources related to data items in the local database. Then, a query against a WDDB normally consists of two parts: a local query and a set of remote queries. A local query can be considered as tree-embedding problem and can be sped-up using the so-called signature technique. A remote query has to be sent to another database which may not be available locally. To decide where to send a query, an address book has to be maintained, which can be established manually or automatically using Web recognizer.
Neuromorphic vision: Sensors to event-based algorithms

Regardless of the marvels brought by the conventional frame-based cameras, they have significant drawbacks due to their redundancy in data and temporal latency. This causes problem in applications where low-latency transmission and high-speed processing are mandatory. Proceeding on this line of thought, the neurobiological principles of the biological retina have been adapted to accomplish data sparsity and high dynamic range at the pixel level. These bio-inspired neuro-morphic vision sensors alleviate the more serious bottleneck of data redundancy by responding to changes in illumination rather than to illumination itself. This paper reviews in brief one such representative of neuromorphic sensors, the activity-driven event-based vision sensor, which mimics human eyes. Spatio-temporal encoding of event data permits incorporation of time correlation in addition to spatial correlation in vision processing, which enables more robustness. Henceforth, the conventional vision algorithms have to be reformulated to adapt to this new generation vision sensor data. It involves design of algorithms for sparse, asynchronous, and accurately timed information. Theories and new researches have begun emerging recently in the domain of event-based vision. The necessity to compile the vision research carried out in this sensor domain has turned out to be considerably more essential. Towards this, this paper reviews the state-of-the-art event-based vision algorithms by categorizing them into three major vision applications, object detection/recognition, object tracking, localization and mapping. This article is categorized under:
Increasing the tracking region of an eye-in-hand system by singularity and joint limit avoidance

A control strategy is presented that visually tracks objects using a manipulator/camera system while simultaneously avoiding kinematic singularities and joint limits by moving in directions along which the tracking task space is unconstrained or redundant. A manipulability measure is introduced into the visual servoing objective function in order to derive the control law. The algorithms developed are experimentally verified on an eye-in-hand system. Results demonstrate the effectiveness of the method by showing that the tracking region of a manipulator tracking objects with planar motion can be greatly increased. <<ETX>>
The Honeynet Project: Trapping the Hackers

What specific threats do computer networks face from hackers? Who's perpetrating these threats and how? The Honeynet Project is an organization dedicated to answering these questions. It studies the bad guys and shares the lessons learned. The group gathers information by deploying networks (called honeynets) that are designed to be compromised.
Submission to J. Functional Programming Special Issue on Theorem Proving & Functional Programming Automatic Veri cation of Functions with Accumulating Parameters

Proof by mathematical induction plays a crucial role in the veriication of program transformations. This paper focuses on the automatic veriication of transformations which introduce accumulating parameters. Such veriication eeorts typically require a generalization step. In earlier papers we presented a technique for automating the generalization step by analysing failed proof attempts. Through empirical testing a natural generalization and extension of the basic technique emerged. Here we describe our extended generalization technique together with some promising experimental results.
Submission to J. Functional Programming Special Issue on Theorem Proving & Functional Programming Automatic Veriication of Functions with Accumulating Parameters

Proof by mathematical induction plays a crucial role in reasoning about functional programs. A generalization step often holds the key to discovering an inductive proof. We present a generalization technique which is particularly applicable when reasoning about functional programs involving accumulating parameters. We provide empirical evidence for the success of our technique and show how it is contributing to the ongoing development of a parallelising compiler for Standard ML.
Smith ScholarWorks Smith ScholarWorks

While the Internet and social media help keep today’s youth better connected to their friends, family, and community, the same media are also the form of expression for an array of harmful social behaviors, such as cyberbullying and cyber-harassment. In this paper we present work in progress to develop intelligent interfaces to social media that use commonsense knowledge bases and automated narrative analyses of text communications between users to trigger selective interventions and prevent negative outcomes. While other approaches seek merely to classify the overall topic of the text, we try to match stories to ﬁner-grained “scripts” that represent stereotypical events and actions. For example, many bullying stories can be matched to a “revenge” script that describes trying to harm someone who has harmed you. These tools have been implemented in an initial prototype system and tested on a database of real stories of cyberbullying collected on MTV’s “A Thin Line” Web site.
Terminological cycles in a description logic with existential restrictions

Cyclic definitions in description logics have until now been investigated only for description logics allowing for value restrictions. Even for the most basic language FL₀, which allows for conjunction and value restrictions only, deciding subsumption in the presence of terminological cycles is a PSPACE-complete problem. This report investigates subsumption in the presence of terminological cycles for the language EL, which allows for conjunction and existential restrictions. In contrast to the results for FL₀, subsumption in EL remains polynomial, independent of wether we use least fixpoint semantics, greatest fixpoint semantics, or descriptive semantics. These results are shown via a characterization of subsumption through the existence of certain simulation relations between nodes of the description graph associated with a given cyclic terminology.
Affective and behavioural computing: Lessons learnt from the First Computational Paralinguistics Challenge

TaggedP Abstract In this article, we review the INTERSPEECH 2013 Computational Paralinguistics ChallengE (ComParE) (cid:1) the ﬁrst of its kind (cid:1) in light of the recent developments in affective and behavioural computing. The impact of the ﬁrst ComParE instal D85X X ment is manifold: ﬁrst, it featured various new recognition tasks including social signals such as laughter and ﬁllers, conﬂict in dyadic group discussions, and atypical communication due to pervasive developmental disorders, as well as enacted emotion; second, it marked the onset of the ComParE, subsuming all tasks investigated hitherto within the realm of computational paralinguistics; ﬁnally, besides providing a uniﬁed test-bed under well-deﬁned and strictly comparable conditions, we present the deﬁnite feature vector used for computation of the baselines, thus laying the foundation for a successful series of follow-up Challenges. Starting with a review of the preceding INTERSPEECH Challenges, we present the four Sub-Challenges of ComParE 2013. In particular, we provide details of the Challenge databases and a meta-analysis by conducting experiments of logistic regression on single features and evaluating the performances achieved by the participants. machine approaches for holistic speech analysis in computational paralinguistics.
Concern and Difficulties in a Rural District with a Low ELL Population

The objective of this thesis is to investigate the effectiveness of the ESL service provided to ELLs in a particular rural school with a small ELL population. The focus is to gather information from teachers, parents, and administrators, in order to figure out the gaps, weaknesses and difficulties when considering six important points to a fair and balanced introduction to curriculum: positive and welcoming learning environment, appropriate curriculum, full delivery of service, equitable assessment of ELLs, ELL parental involvement and professional development that best fits ELLs, their parents and their teachers. The data collected reveals a school district that doesn’t meet any of these standards. The outcome shows that in this particular small, rural and remote districts with a small ELL population, federal guidelines are not being followed, ELL parents are not being considered and that ELLs needs are not being met in order for them to become successful academically and socially.
Using the Forest to See the Trees : A Graphical Model Relating Features , Objects , and Scenes

We consider the problem of detecting several types of objects (cars, desks, bookshelves, pedestrians, etc.) simultaneously. We treat the objects as if they were parts of a scene, and perform joint scene and object recognition. We show that this results in better performance on both tasks. We also introduce a new set of features that can be used for recognizing both objects and scenes.
Using the Forest to See the Trees : A Graphical Model Relating Features , Objects , and Scenes DRAFT

We consider the problem of concurrent scene classification (is this a street scene, office scene, etc.) and object detection (finding all the cars, faces, etc. in an image). The scene can be recognized holistically, using global image features, but also by recognizing its parts (the objects in the scene). We model the synergistic relationship between scenes and objects using a graphical model. Isolated object detection and scene classification is performed using boosting applied to a novel set of features. We show results on a challenging set of indoor and outdoor images collected with a wearable camera.
1 Basic Lower Bounds on Approximability Via PCP and Gap Reductions 2

For most of this book we have looked at decision problems where every instance has a yes or no answer. For example, TSP is a YES-NO question. In the real world TSP is not a decision problem; indeed, in the real world one wants to find the optimal (minimum weight) cycle. This is the function version of TSP. We touched on this distinction in Chapter ? and concluded (correctly) that, with regard to polynomial time, the decision problem and the function problem are equivalent. But let’s get back to the real world. One way to cope with a problem being NP-hard is to approximate it. This concept only makes sense if we are talking about a function, not a set. In this chapter we will look at functions that are naturally associated to NP-complete problems and show that they are NP-hard to approximate. In this chapter we will show how to use Gap Reductions to get lower bounds on approximations contingent on P 6= NP. We will then touch upon the Unique Games Conjecture, a point of great debate in modern times. There are lower bounds contingent on the Unique Games Conjecture (UGC) being true; however, the evidence for UGC is not as compelling as the evidence that P 6= NP.
TOWARDS HIERARCHICAL IMPORTANCE ATTRIBU-

Deep neural networks have achieved impressive performance in handling complicated semantics in natural language, while mostly treated as black boxes. To explain how the model handles compositional semantics of words and phrases, we study the hierarchical explanation problem. We highlight the key challenge is to compute non-additive and context-independent importance for individual words and phrases. We show some prior efforts on hierarchical explanations, e.g. contextual decomposition, do not satisfy the desired properties mathematically, leading to inconsistent explanation quality in different models. In this paper, we propose a formal way to quantify the importance of each word or phrase to generate hierarchical explanations. We modify contextual decomposition algorithms according to our formulation, and propose a model-agnostic explanation algorithm with competitive performance. Human evaluation and automatic metrics evaluation on both LSTM models and fine-tuned BERT Transformer models on multiple datasets show that our algorithms robustly outperform prior works on hierarchical explanations. We show our algorithms help explain compositionality of semantics, extract classification rules, and improve human trust of models 1.
AIS Electronic Library (AISeL)

Satisfying Quality of Service (QoS) of multimedia traffic has been gaining more attentions recently. Data, voice and video share the same communication channel but have significantly different traffic characteristics and performance requirements in terms of packet loss, delay, etc. Self-similarity also imposes some new challenges for network dimensioning as more buffer and bandwidth are expected to accommodate the extra burstness of self-similarity of multimedia application. However, previous studies did not investigate how much extra bandwidth is needed to meet QoS requirements of self-similar multimedia traffic. In this study, we model delay and loss requirements of interactive voice as the constraints to simulate the maximum allowable link loads. Results of this study suggest that under a self-similar input traffic, most of the bandwidth resources of slow links will be wasted to accommodate the traffic burstness if quality requirements of voice traffic are to be satisfied in a best-effort manner. For fast links (>10Mbps), self-similarity seems to have little impact on the maximum allowable load, which is above 82%.
Measurement of simulated drop size distribution with an optical spectro pluviometer: sample size considerations

Knowledge of drop size distributions is important for deriving various rain erosivity parameters. This study investigates the potential of an optical spectro pluviometer (OSP) to measure drop size distributions. Particular attention is paid to the impact of drop sample size and derived erosivity parameters. An experimental set-up using a rainfall simulator and an OSP is described. The OSP allows a continuous real-time sampling of the drops. Results on drop size distributions and sampling effects are discussed. A simulation aimed at reproducing the sampling made with the widely used flour-pellet or filter-paper method is described. From this simulation, recommendations on the sample size of the collected drops needed for an accurate determination of median drop size and kinetic energy are given. Past studies reporting drop size characteristics have often used too small a sample for an adequate description of rain erosivity. Copyright © 1999 John Wiley & Sons, Ltd.