Reviewerly/exHarmony huggingface dataset:
Deep networks trained to recognize facial expressions spontaneously develop representations of face identity

According to the dominant account of face processing, recognition of emotional expressions is implemented by the superior temporal sulcus (STS), while recognition of face identity is implemented by inferior temporal cortex (IT) (Haxby et al., 2000). However, recent patient and imaging studies (Fox et al., 2011, Anzellotti et al. 2017) found that the STS also encodes information about identity. Jointly representing expression and identity might be computationally advantageous: learning to recognize expressions could lead to the emergence of representations that support identity recognition. To test this hypothesis, we trained a deep densely connected convolutional network (DenseNet, Huang et al., 2017) to classify face images from the fer2013 dataset as either angry, disgusted, afraid, happy, sad, surprised, or neutral. We then froze the weights of the DenseNet and trained linear layers attached to progressively deeper layers of this net to classify either emotion or identity using a subset of the Karolinska (KDEF) dataset. Finally, we tested emotion and identity classification in left out images in the KDEF dataset that were not used for training. Classification accuracy for emotions in the KDEF dataset increased from early to late layers of the DenseNet, indicating successful transfer across datasets. Critically, classification accuracy for identity also increased from early to late layers of this DenseNet, despite the fact that it had not been trained to classify identity. A linear layer trained on the DenseNet features vastly outperformed a linear layer trained on pixels (98.8% vs 68.7%), demonstrating that the high accuracy obtained with the DenseNet features cannot be explained by low-level confounds. These results show that learning to recognize facial expressions can lead to the spontaneous emergence of representations that support the recognition of identity, thus offering a principled computational account for the discovery of expression and identity representations within the same portion of STS.
Comparing the categorical structure of perceived and recalled images in visual cortex and hippocampus

When we view an image, visual regions of the brain automatically respond to various properties of the image, including its category, size, and content. Recent work has shown that the visual information we freely recall from memories is highly detailed (Bainbridge et al., 2018). However, it is still largely unknown how content-based representations of stimuli during perception compare to those of free recall in the brain. In this study, participants (N=22) in a 7T MRI performed a free recall task in which they studied an image for 6s, followed by a 6s distractor task with separate images, and then were asked to freely recall the original image (6s) and then indicate vividness of their memory. In contrast to many prior studies, the recall did not require the learning of any stimulus associations and all stimuli were trial-unique. The 192 stimuli were organized in nested categorical structure: objects varying along two factors of big/small and tool/non-tool, and scenes varying along the factors of open/closed and natural/manmade. Each of these categories contained three object or scene types (e.g., guitar, living room), with eight exemplars of each type. Following the scan, participants were given a surprise recognition memory test. We find that key visual regions (e.g., the parahippocampal place area, lateral occipital cortex) contained information during encoding predictive of recognition and recall performance, while the hippocampus reflected recall vividness. Visual regions also showed categorical structure at all levels (object vs. scene; open vs. closed; guitar vs. cupcake) during both encoding and recall. Interestingly, while the hippocampus showed sensitivity to broad stimulus category during encoding, it did not show clear evidence for sub-categorical structure. In sum, we find preserved fine-grained categorical representations in visual regions during both encoding and recall, while the representational structure may change in more memory-related regions.
Double Cold Reception Endangering Cultural Security: The Lack of Chinese Culture in Foreign-related Discipline Education

The weakening or even lack of Chinese culture has become a practical problem in foreign-related discipline education, including college foreign languages and teaching Chinese as a foreign language, and the Chinese cultural security is worrying. Since foreign-related discipline education directly or indirectly affects China's cultural security, soft power, or even its comprehensive national strength, we should strengthen the education of Chinese culture in the teaching practice of foreign languages and Chinese as a foreign language. That is to say, two things should be done pertinently. One is to highlight the differences between Chinese and Western cultures in college foreign language education, while teaching Western cultures to students, we should focus on sticking to the position of Chinese culture; the other is to highlight the charm of Chinese culture to foreign students in teaching Chinese as a foreign language, and consciously carry out the influence and dissemination of Chinese culture.
Cognitive and Perceptual Influences on Eye Movements and Object Memory in Real Environments

Our everyday experience is shaped by the interplay between our cognitive processes and the perceptual characteristics of our surroundings. However, cognitive and perceptual influences have been examined mostly in laboratory settings, while little is known about how they act in real environments. We studied these influences on eye-movement behaviour and on memory representation of color and position of objects placed in different types of real rooms. In Experiment 1 we used a memorisation task. We manipulated object-context semantic association (consistent, inconsistent) and objects’ perceptual salience (low, high). Recognition memory was tested with a four-AFC paradigm. Perceptual salience had no effect. Inconsistent objects were not selected earlier than consistent ones, but they were fixated for longer. Memory for color and position was better for inconsistent than consistent objects, but this arose from the longer inspection. In Experiment 2 we aimed to disentangle the role of semantic association and task relevance of memory encoding. We used a visual-search task and an object counting task (this latter to encourage fixation of all objects), followed by a surprise four-AFC memory test. All tested objects were of low perceptual salience, and could be consistent or inconsistent and searched or non-searched. Semantics had no effect. Memory for color was enhanced by longer object inspection and was better for searched than non-searched objects. This memory benefit of object search was enhanced for the latest selected objects. Our results suggest that, in the real world, cognitive guidance overrides perceptual guidance and that, within sources of cognitive guidance, task relevance overrides semantics. Moreover, they suggest that any benefit for recognition memory related to cognitive guidance either is a by-product of (case of semantic association) or is modulated by (case of task relevance) how this guidance acts on viewing behaviour during encoding.
A Basic Study on Cavin Comfortability Using EEG Measurement

Since the ultra-compact electric vehicle does not generate an engine sound, an interior noise caused by road and wind noise have a large impact on user comfort in the interior space. In previous study, we proposed a system whereby giant magnetostrictive actuator is installed on the roof of an ultra-compact electric vehicle to actively cut interface vibration noise. A road noise transmitted to the interior of the vehicle and we aim to reduce the noise level in an interior of a vehicle using this proposed active noise control system. In this study we considered comfort evaluation by brain wave measurement using a simulator with respect to improving passenger's in-car comfort and tendency of passenger's favorite in-vehicle environment．
I Phonogrammarchive di Berlino e Vienna: un banco di prova per i linguisti

At the end of the 19th century, linguists interested in language teaching, dialectology and language classification devoted themselves to the study of spoken languages. Field research was facilitated by the use of new phonographic technologies and phonographic archives were created, with the first ones in Berlin and in Vienna. These archives organised the systematic collection of world language records in the prison camps of the two central empires during the First World War. Thanks to these pioneering efforts it is now possible to recover the first sound documentation of numerous Italian dialects.
Word Embedding Models for Query Expansion in Answer Passage Retrieval

With the increasing popularity of mobile and voice-assisted, extracting short and precise answer passages to open-domain questions is becoming an increasingly important information retrieval (IR) task. The recently released large-scale corpus for answer passage retrieval—WikiPassageQA—was shown to be challenging for both traditional retrieval models and neural architectures. One of the classic approaches to improving retrieval effectiveness across tasks is automatic query expansion (QE). QE is the process of reformulating a user’s query by adding more terms with the goal of retrieving more relevant information. Word embeddings are commonly employed to obtain QE terms by taking advantage of the low dimensional semantic space formed by these embeddings. Recently, Diaz et al. showed that QE using word embeddings trained on a local query-specific corpus performed better than embeddings that were trained on an entire global corpus for document ranking tasks. We aim to examine the effectiveness of QE, specifically using locally-trained word embeddings, in this new context of answer passage retrieval. Additionally, a query-specific corpus can be small in size with limited vocabulary which forms a challenge for training word embedding models. Since the extent to which limited vocabulary influences the semantic information captured by word embeddings is relatively unexplored, we compare two word embedding models—CBOW and IWE—in this thesis. Having the same underlying training philosophy, the IWE model differs from CBOW in two aspects—it incorporates sub- word information of words and uses a convolutional neural network to learn context representation. Our results corroborate the findings of Diaz et al.—query-specific data is also beneficial in the task of retrieving passages to open-domain questions. Word embeddings trained on a global corpus fail to capture the nuances of query-specific language present in the answer passages. We also found out that IWE word embeddings capture more semantic information than CBOW word embeddings when trained on local data with a limited vocabulary. Our experiments show that both the IWE model components contribute to the improved quality of word embeddings and consequently better QE terms. Our work can be extended by using the same methodology in other domains or by using different word embedding models to obtain QE terms. The insights from our thesis can help researchers to make an informed decision while choosing word embedding models and training data for their IR and natural language understanding tasks.
Tail redundancy and its characterizations of universal compression

We completely characterize the asymptotic per-symbol average case redundancy of any collection P of i.i.d. distributions over a countably infinite alphabet. We prove that universal compression of length-n i.i.d. sequences from a class P is characterized by how well the tails of of the single letter marginals of P can be universally described. We capture this notion by the tail redundancy of a class P$ of distributions, and develop on the properties of tail redundancy.
A study of prevalence of anemia in pediatric population in a tertiary care hospital in Amritsar

A study of prevalence of anemia in pediatric population in a tertiary care hospital in Amritsar - IJCBR- Print ISSN No: - 2394-6369 Online ISSN No:- 2394-6377 Article DOI No:- 10.18231/j.ijcbr.2019.085, International Journal of Clinical Biochemistry and Research-Int J Clin Biochem Res
Stereoscopic color transfer and disparity remapping based on selected object

Color transfer has been a hot research issue in the field of image processing and computer vision in recent years. The main purpose is to transfer the color of a target image to source image so that the source image has the same or similar color features with the target image. In practical applications for the color transfer of binocular stereoscopic images, the user may only need to transfer the color of the selected object while keeping the background color unchanged. For this purpose, a color transfer method based on the selected object is proposed in this paper. In the method, by assigning the object of the image by user, the accurate object is segmented via graph cut, and the probability density curves of color distribution between the selected object and the target image are matched to accomplish the color transfer. In order to enhance the viewing experience provided for the user, a non-linear disparity optimization is performed after the color transfer operation. According to the histogram feature of disparity map, the disparity mapping function is calculated, and the target disparity is obtained to enhance the depth sensation of the selected object. The experimental results demonstrate that the combination of stereoscopic color transfer and disparity remapping effectively enhances the stereoscopic viewing experience.
PENGARUH PENERAPAN ELINA MATA KULIAH BUSINESS ENGLISH UNTUK KELAS MAHASISWA PEKERJA DI UNIVERSITAS NAROTAMA

Narotama University has two classes for employee class. They are Class B and Class C. Class B get classic learning. On the other hand, Class C get classic learning and e-learning, it is called as Elina. This research is quasi experimental. The author tests the scores in the business English course on the midterm, final exam, assignments, attendance and total scores for the semester using the t-test method. The result is that there is no significant difference between mixed learning classes and classical learning classes for total scores and attendance. On the other hand, specifically there are two significant differences. First, in midterm grades, mixed learning classes have lower grades than classical learning classes. Second, in the final examination and assignment grades, mixed learning classes have higher grades than classical learning classes
Minat Belajar Ditinjau Dari Kreativitas Belajar Dan Intensitas Pemanfaatan Internet Pada Mata Pelajaran IPS Siswa Kelas VIII SMP Negeri 4 Randudongkal Tahun Ajaran 2017-2018

Agung Prasetyo / A210130066. INTEREST OF LEARNING REVIEWED FROM LEARNING CREATIVITY AND INTENSITY OF INTERNET UTILIZATION IN SOSIAL STUDIES SUBJECT OF STUDENTS CLASS VIII JUNIOR HIGH SCHOOL 4 RANDUDONGKAL YEAR 2017-2018. Essay. Accounting Education Study Program, Faculty of Teacher Training and Education, Muhammadiyah University, Surakarta. June, 2019.The purpose of this study was to find out: (1) the effect of learning creativity on learning interest. (2) the influence of the intensity of internet use on interest in learning. (3) the influence of learning creativity and the intensity of internet use on interest in learning.This study includes the type of associative quantitative research with data obtained from numbers that aim to determine the effect or relationship between two or more variables. The population in this study were all eighth grade students of Junior High School 4 Randudongkal in 2017-2018 which amounted to 184 students. Samples were taken as many as 123 students with the SimpleRandom Sampilng technique. Techniques for collecting data using questionnaires and documentation. The analysis technique used is multiple regression analysis.The results of the regression analysis obtained the regression line equation: Y = 7.114 + 0.612X1 + 0.318X2. The equation shows learning creativity and the intensity of internet use has an influence on learning interest. Based on the analysis and discussion it can be concluded that: 1) learning creativity has a positive effect on learning interest in social studies subjects of class VIII of Junior High School 4 Randudongkal in the school year 2017-2018. Based on t test obtained tcount> ttable10,571> 1,980 and probability value ttable 5,364> 1,980 and probability value Ftable, which is 103,397> 3,072 and the significance value <0,05, which is 0,00. 4) R2 = 0.633, this can be interpreted that 63.3% change / variation Y (interest in learning) is caused by a change / variation in variable x (learning creativity and internet utilization intensity) while the remaining 26.7% is influenced by other variables that are not researched by researchers.
Object detection for small pixel in urban roads videos

Small pixel targets in video images are difficult to detect. Aiming at the small pixel target in urban road video, this paper proposed a novel detection method named Road_Net based on the YOLOv3 convolutional neural network. Firstly, based on the improved YOLOv3, a new convolutional neural network Road_Net is designed. Secondly, for small pixel target detection depending on shallow level features, a detection method of 4 scales is adopted. Finally, combined with the improved M-Softer-NMS algorithm, it gets higher detection accuracy of the target in the image. In order to verify the effectiveness of the proposed algorithm, this paper collects and labels the data set named Road-garbage Dataset for small pixel target object detection on urban roads. The experimental results show that the algorithm can effectively detect objects such as paper scraps and stones, which are smaller pixel targets in the video relative to the road surface.
Azure Functions Programming

This chapter discusses the programming model of Azure Functions and enables you to increase your development productivity.
LibGuides: HONORS 205: Aesthetic Creations: Modalities in Therapeutic Music: Home

This research guide is designed to point towards library resources that will support your therapeutic drumming research.
The Alabama Human Life Protection Act: criticità giuridiche, contraddizioni assiologiche e dinamiche politiche evolutive

SOMMARIO : 1. Oggetto del presente contributo e metodologia di ricerca - 2. Analisi giuridica e rilievi critici - 3. Il paradigma morale interno - 4. La dinamica evolutiva - 5. Conclusioni. The Alabama Human Life Protection Act: juridical criticisms, moral contradictions and policy implications ABSTRACT: The paper aims at analyzing and highlighting potential juridical criticism of the recent abortion law referred to as The Alabama Human Life Protection Act and verifying if the positive judgments, expressed by the international pro-life movement, and the potential legal, social and policy developments, triggered by this legislation, are consistent with the moral principles of the movement itself.
Prediction Method of Manganese Tuberculosis Resources Content in Deep Seafloor Based on Multiple Regression

Kuang, Y.; Yuan, J., and Chen, Z., 2019. Prediction method of manganese tuberculosis resources content in deep seafloor based on multiple regression. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 90–96. Coconut Creek (Florida), ISSN 0749-0208.In order to improve the prediction accuracy of deep seafloor manganese nodule resource content, a prediction method of deep seafloor manganese nodule resource content based on multiple regression analysis is proposed. The big data model for statistical analysis of deep seafloor manganese nodules is constructed. The deep seafloor manganese nodules are extracted by mining and feature extraction methods. Combined with the artificial intelligence optimization method, the characteristics of the deep seafloor manganese nodules are classified and studied, and the information fusion is carried out according to the extraction values of the characteristic parameters of the deep seafloor manganese nodules. A statistical analysis and regression analysis model for predicting the content of manganese nodules in deep seafloor is established, and the multivariate linear fitting and recurrent analysis methods are used to predict the content of manganese nodules in deep seafloor. The simulation results show that the method has high accuracy in predicting the content of manganese nodules in the deep seafloor, and improves the statistical analysis ability of the manganese nodules in the deep seafloor.
Discrimination Assessment for Saliency Maps

Saliency methods can effectively mark which patterns in the input have higher impacts in model decision, and highlight the relationship between the features and inference results. However, different saliency maps have different performance in classification tasks. Through experiments, we find that some saliency maps show more discriminative ability, while others do not. Saliency methods with higher discrimination ability will be more helpful to human while making final decision, for example, the dominant features of malignant area are expected to be identified in medical diagnosis. In this work, a method is proposed to evaluate whether the saliency methods can provide effective discriminant information. In addition to giving intuitive judgment, we will also introduce a quantitative measurement method. We regard the saliency map as a weighting vector in class discrimination, which is analogue to the projection direction of Linear Discriminant Analysis (LDA) [12], and measure the discriminant ability of saliency map by comparing the difference between the vector direction of saliency map and the projection direction of LDA. Through this metric, our experiments will present the ranking of popular saliency map methods, in terms of discriminative ability.
Hiding in Plain Sight: Enabling the Vision of Signal Rich Art

Digital watermarking technologies are based on the idea of embedding a data-carrying signal in a semi covert manner in a given host image. Here we describe a new approach in which we render the signal itself as an explicit artistic pattern, thereby hiding the signal in plain sight. This pattern may be used as is, or as a texture layer in another image for various applications. There is an immense variety of signal carrying patterns and we present several examples. We also present some results on the detection robustness of these patterns.
Sensor Communication Model Using Cyber-Physical System Approach for Green Data Center

Energy consumption in distributed computing system gains a lot of attention recently after its processing capacity becomes significant for better business and economic operations. Comprehensive analysis of energy efficiency in high-performance data center for distributed processing requires ability to monitor a proportion of resource utilization versus energy consumption. In order to gain green data center while sustaining computational performance, a model of energy efficient cyber-physical communication is proposed. A real-time sensor communication is used to monitor heat emitted by processors and room temperature. Specifically, our cyber-physical communication model dynamically identifies processing states in data center while implying a suitable air-conditioning temperature level. The information is then used by administration to fine-tune the room temperature according to the current processing activities. Our automated triggering approach aims to improve edge computing performance with cost-effective energy consumption. Simulation experiments show that our cyber-physical communication achieves better energy consumption and resource utilization compared with other cooling model.