Reviewerly/exHarmony huggingface dataset:
Analysis of unstructured content using state of the art technology in NATO environment

It is estimated that over 80% of the information within organization is held as unstructured content, this includes valuable assets such as documents, emails, customer correspondence, free-form fields on applications, wikis, blobs of text in a database, content in enterprise content repositories, social media posts, and other messages. Given the inherent lack of structure, analysing and searching unstructured content demands extensive effort and is difficult and error prone without automation. Generally, for a human to perform any analysis they must read and understand the content, making human involvement an expensive and time-consuming part of the overall process. That humans have a limited concentration time on any given task complicates matters further so over long periods, accuracy of human based classification and annotation become lower and lower.This paper summarises use of IBM's Watson Explorer (WEX), one of the most well-known Data Science tools specifically supporting extraction of valuable insights from unstructured content.
Multi-occluded pedestrian real-time detection algorithm based on preprocessing R-FCN

One of main challenges of driver assistance systems is to detect multi-occluded pedestrians in real-time in complicated scenes, to reduce the number of traffic accidents. In order to improve the accuracy and speed of detection system, we proposed a real-time multi-occluded pedestrian detection algorithm based on R-FCN. RoI Align layer was introduced to solve misalignments between the feature map and RoI of original images. A separable convolution was optimized to reduce the dimensions of position-sensitive score maps, to improve the detection speed. For occluded pedestrians, a multi-scale context algorithm is proposed, which adopt a local competition mechanism for adaptive context scale selection. For low visibility of the body occlusion, deformable RoI pooling layers were introduced to expand the pooled area of the body model. Finally, in order to reduce redundant information in the video sequence, Seq-NMS algorithm is used to replace traditional NMS algorithm. The experiments have shown that there is low detection error on the datasets Caltech and ETH, the accuracy of our algorithm is better than that of the detection algorithms in the sets, works particularly well with occluded pedestrians.
Reliability-Weighted Template Matching Predicts Human Detection Performance in Natural Scenes

In a recent study, using a constrained image sampling approach, Sebastian et al. (PNAS, 2017) found that the thresholds of the template-matching (TM) observer in natural backgrounds are the separable product of the local background luminance (L), contrast (C) and cosine similarity to the target (S): threshold is proportional to L × C × S. Further, they found that human thresholds matched those of the TM observer over the range of conditions tested in the humans. However, in natural scenes these background properties are often not homogenous across the target region, potentially impacting the visibility of different parts of the target. The approximately-optimal strategy for dealing with inhomogeneous backgrounds is to normalize the template by the estimated local variance at each pixel location within the template. The threshold of the resulting reliability-weighted, template-matching (RWTM) observer is proportional to (L × C × S) / E, where E is the square root of the energy of the reliability-weighted template. To test this prediction, calibrated natural image patches were sorted into 3D histograms based on their luminance, contrast and similarity. Within 4 of these bins, image patches were further divided into 5 sub-bins based on their reliability weighted template energy. For all the sub-bins within a bin, the values of L, C and S are approximately constant, and hence the TM observer predicts approximately constant thresholds, whereas the RWTM observer predicts thresholds to fall inversely with E. Across all 20 (4 × 5) conditions, the RWTM observer accounts for 89% of the variance in the human thresholds, whereas the MT observer for only 11% of the variance. Furthermore, the RWTM observer was a better predictor of trial-by-trial responses in human observers (i.e., larger decision-variable correlations). We conclude that a RWTM observer based directly on natural scene statistics predicts human detection performance in natural backgrounds.
Image processing technique in the study of cell structures of biomedical data

Image processing methods are used in all areas of research. These methods provide additional information, a better understanding of the object that is being studied. Among the areas of using image processing methods, medicine occupies a special place. Biomedical data allow us to assess human health, to identify diseases in the early stages. Images of cellular structures of cytological preparations are one of the examples of biomedical data. Based on image analysis methods, we can isolate various components of cellular structures of cytological preparations. To do this, we apply the methods of wavelet analysis for different color components of the input image. Applying morphological analysis, we can identify individual cellular structures. The results are shown on the example of images of cellular structures of cytological preparations.
ZoomMaps: Using Zoom to Capture Areas of Interest on Images

Eye movements can help localize the most attention-capturing, interesting, or confusing regions of images or user interfaces (Jacob & Karn, 2003). Consequently, there have been significant efforts to find more scalable alternatives for collecting user attention, including moving-window methodologies (e.g., BubbleView, see Kim, Bylinskii, et al., 2017). In this work, we propose an extension of the moving-window methodology, by taking advantage of user viewing behavior on mobile screens. A mobile screen provides a naturally restricted window to explore multiscale content with the help of the zoom functionality. In this work, we present an approach to capture zoom behavior using a mobile interface, we use the collected spatial zoom patterns as a proxy for attention that we call ZoomMaps (which can be visualized as heatmaps), and we propose applications that can be built on top of zoom data. In one set of experiments, we collected the ZoomMaps of 14 participants using our zoom interface on mobile devices with a set of natural images from the CAT2000 dataset (Borji & Itti, 2015). We found that ZoomMaps are highly correlated with image saliency and ground truth eye fixation maps. In a separate set of experiments on academic posters, 10 participants spent 30 minutes exploring 6 posters. We found that zoom data could be used to generate personalized GIFs of subjects’ viewing patterns that were more effective at eliciting subsequent memory than static thumb-nails. These experiments suggest that ZoomMaps provide an effective and natural interface for collecting coarse attention data that can be harnessed for a variety of applications. For instance, zoom can be used to measure the natural scale of visual content, to summarize visual content, or to act as a debugging tool for designs.
Frame memory compression for high-resolution video coding

This chapter presents a frame memory compression method used in video coding. Frame memory compression compresses the data to be stored in the frame memory in order to reduce the external bandwidth and the related power consumption, as shown in Figure 7.1. When the pixels of a motion-compensated frame have to be written into external DRAM, the frame memory compression engine compresses those pixels. During motion estimation (ME), the frame memory compression engine decompresses the compressed pixels of previous frames and passes them to the video codec. As shown in Figure 7.2, most of the frame memory compression algorithms are composed of three stages: prediction, entropy coding and memory organization [1], which are respectively introduced in Sections 7.1, 7.2 and 7.3.
Putting Data Before Theory

The traditional statistical analysis of data follows what has come to be known as the scientific method: collecting reliable data to test plausible theories. Data mining goes in the other direction, analyzing data without being motivated or encumbered by theories. The fundamental problem with data mining is simple: <italic>We think that data patterns are unusual and therefore meaningful. Patterns are, in fact, inevitable and therefore meaningless.</italic> This is why data mining is not usually knowledge discovery, but noise discovery. Finding correlations is easy. Good data scientists are not seduced by discovered patterns because they don’t put data before theory. They do not commit Texas Sharpshooter Fallacies or fall into the Feynman Trap.
Estudo de tipologia documental em arquivos pessoais: contribuições para a organização do conhecimento arquivístico

The development and partial results of the master's research developed in Line 1 - Policies and Information Technologies, of the Post-graduate Program in Information Science, Federal University of Bahia, about the identification of the types of textual documents in the personal archive of Thales de Azevedo. In the context of the organization of archival knowledge, the identification of documentary typology is fundamental for the development of other physical and intellectual operations in order to organize the archives, among which stand out the classification and the description. The objective is, therefore, to address issues that involve the identification of documentary typology in personal archives, evidencing its characteristics in relation to documentary production and the diversity of typologies resulting from the historiographical practice undertaken by the owner. To do so, we present a review of the literature on the status of personal archives in Archives, and a brief history, conceptualization and analysis of Documentation Identification in national and international literature. Finally, we highlight the role of identification of documentary typology in the treatment of information in personal archives as an essential process of archival practice, which includes a set of activities aimed at providing access to documents and the memory in them.
Applications of a 3-revolute orientation sensing mechanism (3-ROSM) in controlling a camera

In controlling the orientation of an object, it is always desired to have a more intuitive form of controller or an input device as it helps the user adapt to it at a faster pace, hence making it more productive. This paper focuses on the development of a prototype and application of an intuitive serial chain mechanism to measure orientation. This user driven mechanism, referred to as 3-Revolute Orientation Sensing Mechanism (3-ROSM), proposed elsewhere by the authors, is a serial chain mechanism with three intersecting axes and has rotary encoders to measure the joint angles. It is also gravity balanced to prevent reorientation of its links due to the action of gravity. This reduces the effort needed by the user to move its links and also its dependence on load bearing servo motors. It also emulates the joint system in a human wrist and reduces the overall load acting on the user’s hand while gripping the end-effector. The gravity compensation is achieved through the placement of counterweights along and orthogonal to the joint axis under consideration. This makes the 3-ROSM more adaptable to desirable or undesirable load variations. The additional features of this device are its simplicity, low cost, energy efficiency and wide available workspace with which the user can operate this device. To demonstrate its usability and versatility, an easy to assemble physical prototype of the 3-ROSM was designed and developed, which has encoders mounted on its joint axes and was used in two different applications. First, in controlling a 3-axis motorized camera mount and second, navigating the position and orientation of the view-camera in a CAD software.
On the Introduction of the Teaching Model of “Research Learning”

“Research-based Learning” is aimed at stimulating innovative thinking, taking the basic structure of the subject as its content, taking independent thinking as the learning essentials, and fully performing the teaching principles of students as the main body, in order to train students to learn knowledge and to create for the purpose of improving students’ independent thinking ability, inductive application ability, mind-imagining, and problem-solving skills.
A model that recovers depth from stereo without using any oculomotor information

The stereo pair of a human’s eyes is spatially separated and their retinal images of a 3D scene are slightly different from one another. This difference is referred to as binocular disparity. Humans can perceive depth within a scene by using binocular disparity. Many believe that the perception of depth requires oculomotor information about the relative orientation of the two eyes. The visual system can obtain such oculomotor information from the efference copy of the oculomotor signal, or from the spatial distribution of the vertical disparity, specifically, the vertical component of the binocular disparity. Note, however, that the oculomotor information provided by these two sources is too restricted or unreliable to explain the reliable depth perception humans have under natural viewing conditions. In this paper, I will describe a computational model that can recover depth from a stereo-pair of retinal images without making any use of oculomotor information or a pirori constraints. This depth recovery model is based entirely on the geometry of the optics of the eyes, which means that I am treating this as a Direct rather than an Inverse problem, according to Inverse Problem Theory. The input to this model is the stereo-pair of retinal images represented as two sets of visual angles between pairs of points in the individual retinal images. The recovered depth is represented in a head-centered coordinate system. Both the representations of the retinal images and of the recovered depth do not change when the eyes rotate. Oculomotor information can be recovered after depth is recovered if it is needed. Note that the model proposed in this study can explain many psychophysical results better than the conventional formulation, which assumes that the visual system requires oculomotor information to use binocular disparity to perceive depth.
A Method for Contour Detection of Water Areas

Contour pixels distinguish objects from the background. Tracing and extracting contour pixels are widely used for smart/wearable image sensor devices, because these are simple and useful for detecting objects. This article provides an algorithm for detecting contours in an image and calculating the contour area. Edge detection method Canny is used for segmenting the image.
Eye Movements Are Required to Process Spatial Configurations in Visual Working Memory

[Introduction] Previous research showed that object locations are not memorized independently but in relation to the global spatial configuration formed by the objects. It is possible to subset a global configuration into a task relevant partial one while encoding. With the present experiments, we investigated the flexibility of the memory representation underlying this spatial configuration effect. Thus, we studied the following research question: Is it possible that spatial configurations can be reorganized to a subset of objects by shifting attention to these objects only during encoding or also in visual working memory (VWM)? [Methods] Participants encoded the locations of six objects (first experiment) or twelve objects (second experiment) and performed a location change detection task for one object probed during retrieval. This object was displaced in half of the trials. We cued the side (left/right) of the object probed either during encoding or afterwards (retro-cue), thus allowing for the reorganization of spatial configurations either during encoding or in VWM. During retrieval, either a complete (all objects), a congruent (cued objects), an incongruent (non-cued objects) or no (probed object only) configuration was shown. In a third experiment, we manipulated eye movements and presented a retro-cue only. One group had to fixate the center of screen during a trial while the other group could move their eyes. [Results] The successful reorganization of spatial configurations was indicated by a higher change detection performance for both the complete and the congruent configuration condition as compared with the no configuration condition. We observed a reliable reorganization both when cued during encoding and also under some retro-cue conditions. Importantly, configuration effects disappeared with enforced fixation. [Conclusion] Our findings provide evidence for the reorganization of spatial configurations and indicate the requirement of eye movements for processing spatial configurations in VWM, which is contradictory to previous snapshot hypotheses.
Different types of response feedback in perceptual training are necessary to improve the detection of different types of breast cancer

Perceptual learning (PL) is not only a strong tool for understanding visual plasticity (Sasaki, Nanez and Watanabe, 2011; Watanabe & Sasaki, 2015) but also for reducing symptoms of eye diseases. Here, we show that PL can also be a strong tool to increase the detectability of breast cancers in mammography scans only if an appropriate response feedback during training is given for different types of breast cancer. Response feedback is known to facilitate PL (Herzog and Fahle, 1998; Shibata et al., 2011), although a detailed role of feedback remains unclear. We examined the role of response feedback for two types of breast cancer: calcification cancer and architectural distortion cancer. The former is easier to detect than the latter. Thus, we examined how different contents of feedback are effective on PL for different breast cancers. Three 30-min long training sessions were conducted on separate days. Detection performance was measured in pre-training and post-training tests. Three different groups of participants (N = 48 subjects in total) without medical training background were trained with different contents of feedback. In the detailed feedback condition, participants were given feedback regarding the location of cancer as well as the correctness of detection. In the partial feedback condition, participants were provided with feedback only about the correctness of detection. In the no feedback condition, participants received no feedback. In the detailed condition detectability improved for architectural distortion and calcification cancers, whereas in the partial feedback condition detectability improved only for calcification. No learning for either cancer was observed in the no feedback condition. These results suggest that PL significantly improves the detectability of breast cancers in mammograms. More importantly, the content of feedback leads to different learning outcomes for different breast cancers, indicating the importance of future studies on the effect of content of feedback on PL.
Processing capacity for moving objects in artificial worlds

Substantial research over the last 30 years of vision science has illuminated how we understand a dynamic world. Studies of ensemble processing tell us what kinds of motion, like linear translation and global optic flow, can be easily used by human vision perceive coherent object trajectories and estimate time-to-contact (Whitney & Leib, 2018; Van den Berg, 1992). Studies of multiple object tracking tell us how we use information to know that a given object is the same one over space and time (Flombaum, 2009; Scimeca & Franconeri, 2014). Every one of these studies has been inspired by the dynamic natural world that the visual system evolved in. But we also spend several hours daily immersed in artificial worlds that use moving displays for information. Dynamic data visualizations, map transformations, and diagrams are used for data analysis, navigation, and education. These dynamic displays are comprised of multiple dynamic objects that, across domains, demand many of the same visual processing capacities we have long studied in the lab. Empirically determining when these dynamic displays are (and aren’t) effective allows us a fresh scenario for understanding how we process dynamic scenes, while at the same time allowing research outputs to inspire interventions to help create more effective displays for students, scientists, and the general public. We present a theory-driven analysis of these displays and the visual processing demands they invoke. We show that visual processing capacities in perception and attention (ensemble processing, tracking object individuals and groups) are what help us see patterns in artificial displays, and that we fail to see patterns when processing capacity is exceeded. Visualizations that defy categorization within this framework can uncover new basic research directions. This domain presents use-inspired basic research by vision scientists to test visual thinking in the constructed, dynamic displays of everyday visual experience.
Reading and Writing Files

Reading data from and writing data to a file is very common within many programs. Python provides a large amount of support for working with files of various types. This chapter introduces you to the core file IO functionality in Python.
Impact of Bitcoin on the World Economy

Bitcoin has brought a revolution in digital market. Bitcoin doesn't follow any supervisory body or central authority to control it. Unlike any country's currency, it is not supervised by a government. It flows on networks and is managed by decentralized actors. Like any other innovation, bitcoin also has pros and cons associated with it. In this chapter, the authors discuss all the opportunities and challenges related to bitcoin and its impact on the world economy.
Does Global Precedence Occur with Displays of Multiple Hierarchical Objects?

The present study revisits the global precedence literature by examining search through multiple hierarchical objects (e.g. G made of small H’s). Are global advantages prominent when the display contains multiple hierarchical objects? In the study, each object was a large letter (one of a set of ten) made of smaller letters (one of the same ten), thus having a global and local level of structure. Display set size varied from one to four of these hierarchical objects, and observers searched for one letter at a specified level (large or small). At display size one, the study replicates traditional global precedence displays. Consistent with many previous studies, there was a substantial global advantage — faster searches at the global level compared to the local level. At larger display set sizes, search continued at a faster rate (lower slope) for global letters than for local letters. Reasons for the global advantages will be discussed. The present study helps to extend the global precedence literature into the world of multiple hierarchical objects.