Reviewerly/exHarmony huggingface dataset:
Extracting image statistics by human and machine observers

Machine learning has found many applications in research for higher visual functions. However, few studies have applied machine learning algorithms to understand early visual functions. We applied a deep convolution neural network (dCNN) to analyze human responses to basic image statistics. The stimuli were band-passed random dot textures whose pixel luminance distribution was modulated away from uniform by a linear combination of Legendre polynomials with orders i and j, where i = 2 or 3, and j was from 1 to 8 but not i. There were 30 modulation depths from 0 (uniform distribution) to 1 (some luminance level had zero probability) for each polynomial pair. The Gaussian spatial frequency bands had peaks that ranged from 2 to 32 cyc/deg and a half-octave space constant. Each of six observers classified 7500–22500 textures by contrast, skewness, glossiness, naturalness or aesthetic preference. The psychophysical results served as ground truth for a VGG16 dCNN pretrained for Imagenet. The decisive layer was identified by removing the convolution layers one by one and observing the point when validation accuracy of the network, with retrained output layer, dropped below 80%. The decisive layer for contrast discrimination contained filters with a profile that consisted of repeated geometric patterns, suggesting a general texture processing mechanism. The decisive layer was the same for all of glossiness, naturalness, and aesthetic preference and comprised filters whose profiles looked like parts of objects. The spatial frequency tuning function, assessed by the validation accuracy with one spatial frequency band left out from the training set was low-pass for all properties except contrast, which showed an inverted-W shape peaked at 4 and 16 cyc/deg. Our results suggest possible properties of the visual mechanisms used to sense texture qualities, and our analysis also shows that dCNN can be a useful tool for early vision research.
Item-based and feature-based selection in working memory

The capacity of our brain to maintain visual information in working memory (WM) is limited. One of the ways in which the brain compensates for these limited resources is by employing selective attention. Selective attention serves to prioritise information during perception and also acts on mental representations maintained in WM. So far, studies have shown that retrospectively attending the spatial location of one of the items in WM improves performance on the subsequent recall when asked about a feature of that item. One recent study has shown a performance benefit by selectively attending feature dimensions of items in WM (Niklaus et al., 2017, Scientific reports). However, no study to date has directly compared item-based and feature-based attention nor their neural correlates, and much remains unknown about feature-based attentional cueing. We tested and compared the benefits of retrospective cues (retro-cues) orienting attention to an item location or feature dimension of the memoranda in WM in 30 participants. To chart neural effects, we recorded electroencephalography (EEG). Behavioural results show attentional benefits in both recall accuracy and response onset time following both item and feature cues. We used the EEG data to decode the 4 presented features on every trial and trace sensory and mnemonic representations of each feature following the item-based and feature-based retro-cues. Preliminary data analysis suggests that both item-based and feature-based attention upregulate representations of the task-relevant features compared to task-irrelevant features. The results challenge the strict notion of object binding, where upregulating one feature of an item necessarily upregulates the other feature of the same item in tandem. We argue that WM representations are stored in a goal-oriented format where relevant information – at both the item or the feature-level – can be prioritised in a format that optimises ensuing/anticipated task performance.
DETERMINATION OF ACETIC AND PROPANOIC ACIDS CONCENTRATION IN NIGERIAN KEROSENE

&lt;p&gt;The paper aims to determine acetic and propanoic acid concentrations in some selected samples of kerosene used in Nigeria. The Armfield Liquid-Liquid Extraction Unit was employed to carry out the study. Distilled water and kerosene samples from five different sources were used for the investigation. The parameters taken into consideration during the course of the experiments were time, thermal conductivity, temperature, flow rates and concentration of the acid. It was deduced from the research that the temperature and the conductivity decreased with significant decrease in concentration of the acid and vice versa. The results gotten from the extraction of the kerosene samples also showed that sample A, sample D, and sample E did not contain acetic acid while sample B and sample C had traces of acetic acid, with sample C having traces of propanoic acid. After comparing the values with the standard classification of acetic acid, it was discovered that the concentration of both acetic and propanoic acid in the samples were not significantly sufficient to harm human beings.&lt;/p&gt;
Taking a machine’s perspective: Humans can decipher adversarial images

How similar is the human visual system to the sophisticated machine-learning systems that mirror its performance? Models of object categorization based on convolutional neural networks (CNNs) have achieved human-level benchmarks in labeling novel images. These advances not only support new technologies, but may also serve as candidate models for human vision itself. However, unlike human vision, CNNs can be “fooled” by adversarial examples — carefully crafted images that appear as nonsense patterns to humans but are recognized as familiar objects by machines, or that appear as one object to humans and a different object to machines. This extreme divergence between human and machine classification challenges the promise of these new advances, both as applied image-recognition systems and as models of human vision. Surprisingly, however, little work has empirically investigated human classification of adversarial stimuli; do humans and machines fundamentally diverge? Here, we show that human and machine classification of adversarial stimuli are robustly related. We introduce a “machine-theory-of-mind” task in which observers are shown adversarial images and must anticipate the machine’s label from a set of various alternatives. Across eight experiments on five prominent and diverse adversarial imagesets, human subjects reliably identified the machine’s preferred labels over relevant foils. We observed this result not only in forced-choice settings between two candidate labels, but also when subjects freely chose among dozens of possible labels. Moreover, this pattern persisted for images with strong antecedent identities (e.g., an orange adversarially perturbed into a “power drill”), and even for images described in the literature as “totally unrecognizable to human eyes” (e.g., unsegmented patterns of colorful pixels that are classified as an “armadillo”). We suggest that human intuition may be a more reliable guide to machine (mis)classification than has typically been imagined, and we explore the consequences of this result for minds and machines alike.
The experience of municipal district libraries of the russian federation in creating literary maps

The article deals with the experience of creating specific electronic literary and local history resources in the libraries of the Russian Federation literary maps as a form of literary local history. They allow modern and visual representation of the literary heritage of the region. The article objective is a systematic description of the experience on creating literary maps in libraries in rural municipalities, the most numerous ones in the Russian Federation. To achieve the research purpose, the author selected the most popular resources via search engines Yandex, Google, Rambler. The study of 12 literary maps of the highest demand on a number of criteria allowed the following conclusion: in most cases, the literary and local history resource of the municipal district has a geographic map, which indicates the preference of visual navigation in geographic space; all resources provide information on local writers and poets including photos, bioand bibliographic data; resources contain news feed; more than half of the literary maps contains bibliographic information on local literary publications; all special sites on literary and local history resources contain full-text literary collections; half of the resources contains information on literary awards and competitions. The study has shown that the library community of municipal districts is working on creating literary maps and looking for the best way to preserve and provide literary and local history information. The revealed problems are typical for the majority of unprofessionally designed sites (redundancy and incompleteness of information, unformalized texts, lack of internal links, settlement on free hostings and, as a result, lots of aggressive advertising, etc.).
Multi-Context Information for Word Representation Learning

Word embedding techniques in literature are mostly based on Bag of Words models where words that co-occur with each other are considered to be related. However, it is not necessary for similar or related words to occur in the same context window. In this paper, we propose a new approach to combine different types of resources for training word embeddings. The lexical resources used in this work are Dependency Parse Tree and WordNet. Apart from the co-occurrence information, the use of these additional resources helps us in including the semantic and syntactic information from the text in learning the word representations. The learned representations are evaluated on multiple evaluation tasks like Semantic Textual Similarity, Word Similarity. Results of the experimental analyses highlight the usefulness of the proposed methodology.
Research and Implementation of Vehicle Tracking Algorithm Based on Multi-Feature Fusion

The main task of multi-object tracking is to associate targets in diverse images by detected information from each frame of a given image sequence. For the scenario of highway video surveillance, the equivalent research issue is vehicles tracking, which is necessary and fundamental for traffic statistics, abnormal events detection, traffic control et al. In this paper, a simplified and efficient multi-object tracking strategy is proposed. Based on the position and intersection-over-union (IOU) of the moving object, the color feature is derived, and unscented Kalman filter is involved to revise targets’ positions. This innovative tracking method can effectively solve the problem of target occlusion and loss. The simplicity and efficiency make this algorithm applicable for the perspective of real-time system. In this paper, highway video recordings are explored as data repository for experiments. The results show that our method outperforms on the issue of vehicle tracking.
A Study on Inferential Characteristics of “Hazuda”

There are many inferential forms which show a speaker’s uncertain perception on a thing or a situation in the Japanese language. In the previous studies of the Japanese language, an inferential form ‘hazuda’ has been known as a form which means logical inference based on an objective evidence or the naturalness of the occurrence of a thing based on a solid evidence. This paper purports to review the characteristics mentioned above and clarify the essential features of ‘hazuda’ in its meaning or usage. This paper focuses on the fact that the previous studies generally emphasized the visible surface features and overlooked the invisible aspects of the form. To reach the goal, this paper seeks to analyze carefully and comprehensively many actual usages of the form ‘hazuda’. As a result this paper can clarify the essential inferential meaning or usage of the form. First of all, ‘hazuda’ can get a firm position within the inferential modality system through this study. In the previous studies, this form was not placed in the inferential modality but in the other category of evidential modality. That is, the position of this form in the modality system has been very flexible. In this paper, the meaning, usages, morpo-syntactic characteristics, etc. of ‘hazuda’ provided reliable evidences which position this form within the inferential modality system. And various data and analyses of the usages clarified the fact that ‘hazuda’ has entirely different two-sided characteristics. One of them is that this form basically has the characteristics of a quasi-inferential form. It also has the characteristics of real inferential form whose typical form is ‘darou’ in the other side. As a result it can be argued that ‘hazuda’ is a ‘real quasi󰠏inferential form placed between quasi󰠏inferential and real inferential form in the inferential modality system in the Japanese language.
Graphing, graph interpretation, managing undifferentiated data

This chapter addresses Level 5 of the functional analysis (FA) training curriculum. It covers procedures for graphing FA data, graph interpretation through visual analysis, designing graphs according to measurement methods, and managing undifferentiated data.
Accessing Cosmos DB in Azure Functions

NoSQL databases have been extremely popular in recent years. In this chapter, you will learn how to access Cosmos DB, the primary NoSQL database in Azure Functions.
More on Optimization Techniques

In this chapter, we’ll go over some other optimization techniques for improving the ability of a neural network to learn complex patterns in a dataset.
7. Rights akin to copyright: database right and performers’ rights

This chapter considers two rights similar to copyright in many ways, in terms of both subject matter and the substantive contents of the rights: (1) the special or <italic>sui generis</italic> database right, which operates alongside the copyright in databases; and (2) performers’ rights. Both rights have been relatively recently introduced into the armoury of intellectual property law. The chapter gives an account of each of these rights, comparing them with copyright but also underlining the differences between the regimes, and the reasons behind these differences. The chapter considers relevant the relevant international and EU frameworks and also highlights the nature and importance of these rights.
Breaking HK17 in Practice

In November 2017, Hecht and Kamlofsky submitted HK17, a quaternion(octonion)-based Diffie-Hellman key exchange protocol, to NIST post-quantum cryptography project, and thought that at least O(p8) arithmetic operations are needed for a passive adversary to recover the shared key where p is the modulo used in the scheme. Later, Bernstein and Lange pointed out that the shared key can be recovered with O(p) arithmetic operations, which implies that HK17 with small p is not secure. However, their attack does not work in practice for the scheme with sufficiently large p, although the scheme is still efficient. In this paper, we propose an attack to show that just constant arithmetic operations, or $\tilde O\left( {\log p} \right)$ bit operations, are enough to recover the shared key for a passive adversary. Note that even the legal party in the protocol needs at least $\tilde O\left( {\log p} \right)$ bit operations to establish the shared key. We break HK17 completely in the practical sense.
Social Audit And Panchayati Raj

Social audit can be used in the various sectors like health, water, financial institution, organizations, companies, public and private sectors. With the help of social audit, industries can measure their performance. The social audit got a legal statue after incorporation of the 73rd amendment to the Indian constitution regarding panchayati raj institutions. This amendment gave power to gramsabha to conduct social audits and it has with this historic amendment that the concept of social audit gained importance in our country. The gramasabha shall conduct regular social audit of all the projects under the scheme taken up with in gram panchayat. So this study analyzed the performance of PRIs through social audit practice. It is purely based on primary data which has used convenient method of sampling method. The result has contributed that, social audit practice through gramsabha has developed the rural area but still there is a need for effective implementation of social audit practice. So government should provide training to panchayat raj employees to effectively carry social audit apart from this other institutions such as NGOs need to support villagers to conduct social audit.
Research Guides: SJU Library Streaming Video Resources: Find Streaming Video

Overview of the streaming video content providers currently available for SJU campus members through the library.
The Google Cloud SDK and Web CLI

GCP provides a command-line interface (CLI) for interacting with cloud products and services. GCP resources can be accessed via the web-based CLI on GCP or by installing the Google Cloud software development kit (SDK) on your local machine to interact with GCP via the local command-line terminal.
How to Promote Teaching Quality and Efficiency in University Quantification Technology

This paper presents a new method for solving teaching problems under the background of different teachers teaching various special courses to promote teaching quality and efficient in university, which uses advanced Quantification Technology. It is important to help some teachers promote teaching quality and solve teaching problems. For validating the method, the paper chooses computer science and technology professional courses in a university as study object. Firstly, this paper deeply analyzed examination results in a term and got the relation among these professional courses by Quantification Technology. Secondly, according to this finding, it can get the prediction expression further. Finally, it is very effective to help teacher put forward a good teaching plan by some experiments in fact, after knowing student’s state about learning previous course through prediction expression computed. This method can provide access to training, museums of science, and individuals as well.
Combining Asymmetric and Symmetric Algorithms

In this chapter, we’ll spend time getting familiar with how asymmetric encryption is typically used, where it is a critical part of communication privacy, but not responsible for all of it. Typically, asymmetric encryption, also known as “public key cryptography”, is used to establish a trusted session between two parties, and the communication while within that session is protected with much faster symmetric methods.
Gaze control by Compensatory Camera Movement on Visual-Space Visual Servoing

This paper proposes a camera gaze control by camera motion compensation. Visual servoing becomes uncontrollable when the target is framed out. Also in robot vision system it is important to move the camera like a human being. There is the inertial sensor as a method of detecting the motion of the camera, but there is an influence of a measurement error of the sensor. Therefore, we proposed to detect motion of the camera using visual space coordinates obtained from the camera image. The effectiveness of the proposed method is shown by simulation.
Finding Needles in Haystacks

In this chapter we introduce regular expressions, one of the most powerful text-handling features of Python and show how we use it to analyze and process genomics and next-generation sequencing data.
Response identification of air flow sensors using fuzzy system for embedded electronics

This paper shows the development of a fuzzy system applied to low-cost microcontroller to assist in the identification of different intensities of air flow from the AWM2100 sensor, whose operation presents variation in the output voltage due to the variation of the external temperature and also a nonlinear response of the output voltage as function of the variation of the air flow. In order to verify the operation of the proposed work, the fuzzy system was developed in C language for the PIC18F4550 microcontroller using techniques that guarantee great precision in the defuzzification process and the results were obtained by practical tests and PROTEUS software simulations.
JPEG Steganography Using BPCS

Steganography is the art of camouflage: its purpose is to make a message go unnoticed within another message. It differs from cryptography, the "art of secrecy", which seeks to make a message unintelligible to anyone other than the lawful. The concept of steganography could split into three parts: the cover object, the hidden message and the process performed to hide. The JPEG is one of the most commonly used formats for images because it combines image quality and limited size on the disk thanks to the good compression of the algorithm. Therefore, that makes it a prime candidate to hide a message in it. Furthermore, there are many algorithms to hide a message in the cover image, but the result remains not very high in terms of payload capacity, even though the type of embedding was easily detectable. Bit Plane Complexity Segmentation (BPCS) steganography is a technique to hide data inside an image file. BPCS was originally developed in 1988 by Kawaguchi and Eason as a steganography technique for bitmap images. One of the reason is that traditional techniques, LSB (Least Significant Bit) for instance, have limited information hiding capacity. This paper describes, analyzes and implements a BPCS steganography technique that embeds a payload into a lossy format JPEG using Matlab. This technique takes advantage of the human eye limitation where a human cannot identify any information in a very complicated binary pattern. The main principle of BPCS technique is that the bit planes of the binary image are divided into the informative region and the noise-like region. The criteria to divide them is the complexity of each bit plane. The noise-like regions in the bit planes of the vessel image can then be replaced with secret data without affecting the image quality. In our method, a color vessel image or a grayscale vessel image in JPEG could be used to hide the secret information. The secret data is hidden into noise-like region of the cover or vessel image without any distortion. Finally, this paper performs some steganalysis techniques to analyze the accuracy and security of our implementation of the BCPS algorithm over a JPEG image.
Python at the Lab Bench

Python is definitely your friend in the lab, so in this chapter we start off with that simple, daily lab stuff for which you would once have whipped out your electronic calculator with its tiny buttons seemingly designed for the fingers of children too young to even care about arithmetic. These days, it’s more likely to be your smartphone you reach for, but you can put that away as well (that paused game of Clash Of Empires III will still be there at your next coffee break).