Reviewerly/exHarmony huggingface dataset:
On the Multisensory Nature of Objects and Language

Infants use exploratory behaviors to learn about the objects around them. Psychologists have theorized that behaviors such as grasping touching, pressing, and lifting, coupled with the visual, tactile, haptic and auditory sensory modalities, enable infants to form grounded object representations. For example, scratching an object can provide information about its roughness, while lifting it can provide information about its weight. In a sense, the exploratory behavior acts as a "question'' to the object, which is subsequently "answered" by the sensory stimuli produced during the execution of the behavior. In contrast, most object representations used by robots today rely solely on computer vision or laser scan data, gathered through passive observation. Such disembodied approaches to robotic perception may be useful for recognizing an object using a 3D model database, but nevertheless, will fail to infer object properties that cannot be detected using vision alone. To bridge this gap, our research has pursued a developmental framework for object perception and exploration in which the robot's representation of objects is grounded in its own sensorimotor experience with them \citesinapov2014grounding. In this framework, an object is represented by sensorimotor contingencies that span a diverse set of exploratory behaviors and sensory modalities. In this talk, I will highlight results from several large-scale experimental studies which show that the behavior-grounded object representation enables a robot to solve a wide variety of perceptual and cognitive tasks relevant to object learning \citesinapov2014learning,sinapov2011interactive. I will discuss recent work on how robots can ground language in multisensory experience with objects \citethomason2016learning and will conclude with a discussion on open problems in multisensory symbol grounding, which, if solved, could result in the large-scale deployment of robotic systems in real-world domains.
Logarithmic Pyramid Vector Quantization—Design and Theoretical Analysis

Vector quantization is an integral part of modern speech and audio codecs. This study proposes the logarithmic pyramid vector quantizer (LPVQ), which is a gain-shape vector quantizer specifically designed for the quantization of Laplace distributed memoryless sources. The objective of the study is a theoretical analysis of the LPVQ: We determine the distortion of the shape quantizer with respect to rate and vector dimension for the quantization of an i.i.d. Laplace source. Furthermore, we derive formulas for the quantization signal-to-noise ratio (SNR) of the shape quantizer and the quantization SNR of the LPVQ, giving reliable results for an effective bit rate per vector coordinate of 2bits and higher. We study the SNR-behavior of the LPVQ for infinite dimensions and compare it with the maximal achievable SNR according to the rate-distortion bound. After having proposed a strategy for the allocation of the bit rate for the gain quantization and the quantization of the shape vector, respectively, we verify the derived formulas by simulations.
Holonic Multi-Agent System for Microgrid Hierarchical Control

This paper proposes a solution for decentralized secondary control system in Microgrid using Holonic Multi-Agent System (HMAS) approach. The model is based on Role-Interaction-Organization (RIO) model and Satisfaction-Affinity compatibility to build the holarchy. To achieve this, 12 modules to manage self-organization mechanism are presented, where different roles of the holons are grouped based on holons interaction. The aims in using holarchy microgrids control are to facilitate the distributed decision making process by improving its learning capability through collaboration and cooperation in a dynamic environment.
Web of Value

Blockchain has redefined the World Wide Web as “Web of Value.” It has empowered people to publish, distribute, and sell information, services, and products of “value” anywhere through this Web without the involvement of any intermediaries. It has become easy for people to build new relationships, businesses, and networks by leveraging the blockchain technology, thereby able to send, share, and receive the value. In this chapter, readers will understand the phenomenon of “Web of Value” and explore the landscape of value generation as driven by the blockchain technology.
The Resolution of Gender Anaphora Reference with the Help of Kernel Trick Mechanisms

Abstract An article represents the results of the experiments constructing of conventional anaphora resolution system for gender-balanced corpora GAP. The main idea behind the conducted set of experiments is taking advantage over the kernel trick mechanism of deep word vectorization for various semantic and syntax features. We will show that it has a positive impact on system performance versus the traditional approach.
Dynamic adaptive streaming over HTTP‐based 3D resource allocation algorithm

With the improvement of people's quality of life, the demand for three-dimensional (3D) video has gradually grown in recent years. However, there are many challenges to providing high-definition and high-fidelity 3D video. One of the most difficult challenges for users to provide 3D video is a large amount of energy lost during 3D video transmission. In this study, the authors present a 3D resource allocation system architecture, which can effectively alleviate the problem of large transmission energy loss. They propose that multiple users in a small cell can share video resources in the downlink from the cloud to the client. In the cloud processing, multiple users can share part of the cloud computing work cycle. In the downlink, multiple users can share part of video resources. They presume that some share output bits can be multicast to overall users, and the other bits can be sent to every user in unicast. They model this and derive the simulation results. The simulation results show that the resource allocation scheme in this study achieves greater energy savings under certain conditions than the traditional case without sharing the resource.
Qualitative Assessment of CogSketch Worksheets in Introductory Geoscience Laboratory Courses: An Argument for Expanded Use

The use of computer-assisted instruction to tutor students in the geosciences is not common, in part because practical programs capable of assessing sketches relevant to introductory geoscience subjects are relatively new. One such program, CogSketch, is an open-domain sketch understanding system that is capable of tutoring students on sketch-based exercises and grading their work. This chapter reports on the mixed use of paper-based exercises and tablet PCs equipped with CogSketch worksheets in introductory geoscience laboratory courses. Potential benefits of using CogSketch worksheets include increased group focus and reduced barriers to starting laboratory exercises. Grading efficiency was not affected. However, increasing the proportion of CogSketch worksheets used during lab sessions will improve grading efficiency and amplify benefits in classroom social dynamics and teaching efficiency that may lead to learning gains.
Resource Scaling in Elastic Clusters with the Hint of Response Time

In a big data environment, elastic clusters are introduced both to fulfill Service Quality Requirements (SQRs) and to save system energy consumption. In most elastic clusters, one or some features of system status are used as the hint for resource scaling. For example, request arrival rate is a widely used feature. Besides, system utilization, mean service time (mean request size) and cache queue length are also common features. However, in elastic clusters where the SQR is referred to the response time of requests, these features are not good choices. For the reason that these features can not well reflect the status of System Service Quality (SSQ). Consequently, it's difficult to achieve an accurate resource scaling, and the system energy-saving efficiency and SSQ can not be well maintained. In this paper, we show that in such type of elastic clusters, the outstanding hint for resource scaling is the request response time. So we propose a resource scaling method which scales resources leveraging the hint of response time. More specifically, our method uses a circular queue to maintain the response time of recent requests, then the mean value is calculated as the hint of response time. Because this hint directly and exactly reflects the status of SSQ, our method can significantly promote system performance on both the SSQ and the energy-saving efficiency. The experimental results validate our point of view and show that our method achieves a good performance by using this hint.
A novel 3D entangled wavelet transformation and its properties

Based on the quantum mechanics representation, we propose a novel 3D entangled wavelet transformation. This kind of three entangled state representation can be generated theoretically by using a two-cascaded beam splitter, which has the completeness and orthogonal property. Some properties of 3D WTs are discussed, including the Parseval theory of 3D WTs, its inverse formula, and the orthogonality of the mother wavelets in parameter space. In addition, the mother wavelet condition for the 3D WTs is also derived.
Context-Free Grammars for Deterministic Regular Expressions with Interleaving

In this paper, we study deterministic regular expressions with interleaving (IDREs). Regular expressions extended with interleaving are good at describing sequential and parallel data patterns. The interleaving makes these expressions exponentially more succinct than standard regular expressions. And when they obey the determinism constraint, they are more efficient for matching and parsing processes than general ones. However, the interleaving also makes the structure of expressions more complex, and the semantic definition of determinism is hard to follow, which prevent users from writing and developing IDREs. We address this problem by proposing a determinism checking method and a syntactic description for IDREs. Our checking method can locate the source of nondeterminism more efficiently and accurately than the existing method when the nondeterminism is caused by unary operators. We prove that the grammars of IDREs are context-free and suggest effective optimization rules to simplify the grammars.
The system of chemical and mathematical problems as a tool for the development of motivation of students of technical universities

The research relevance is connected with the orientation of the modern model of education towards the formation of a competitive creative personality, with the need for constant self-improvement and self-development. It should be noted that the effectiveness of student learning is largely determined by the level of motivation, interest and personal participation of subjects. Therefore, the article is aimed at disclosing mechanisms for the development of students' learning motivation through a system of differentiated tasks. The leading approach to study of a problem was a personal approach, the purpose of which is to identify the issue under discussion from the point of view of dialogism, subjectivity and individuality. This document presents the characteristics of the developed and tested system of differentiated problems of mathematics, focused on the development of student learning motivation, as well as the provision of empirical data on the results of implementation. It also describes the principles on which we defined three levels of tasks in mathematics: “palgorithms”, “tasks of finding tasks” and “creative tasks”.
Arabic-SOS

While morphological segmentation has always been a hot topic in Arabic, due to the morphological complexity of the language and the orthography, most effort has focused on Modern Standard Arabic. In this paper, we focus on pre-MSA texts. We use the Gradient Boosting algorithm to train a morphological segmenter with a corpus derived from Al-Manar, a late 19th/early 20th century magazine that focused on the Arabic and Islamic heritage. Since most of the cultural heritage Arabic available suffers from substandard orthography, we have trained a machine learner to standardize the text. Our segmentation accuracy reaches 98.47%, and the orthography standardization an F-macro of 0.98 and an F-micro of 0.99. We also produce stemming as a by-product of segmentation.
iCanTrace: Avatar Personalization Through Selfie Sketches

This chapter introduces a novel system that allows users to generate customized cartoon avatars through a sketching interface. The rise of social media and personalized gaming has given a need for personalized virtual appearances. Avatars, self-curated and customized images to represent oneself, have become a common means of expressing oneself in these new media. Avatar creation platforms face the challenges of granting user significant control over the avatar creation and of encumbering the user with too many choices in their avatar customization. This chapter demonstrates a sketch-guided avatar customization system and its potential to simplify the avatar creation process.
MORPHOGENESIS OF RULEBASES OF FUZZY INFERENCE SYSTEMS IN TERMS OF CONTRADICTOR EXPERT OPINIONS

The article describes a method of morphogenesis of the rulebase of fuzzy conclusion system in the context of counter-expert opinions. One of the difficulties of the morphogenesis of the rule base, which reflects the result of the collective opinion of the expert group, is processing of counter-narrative conclusions, which are expressed as incompatible rules. The methods used to formulate the rule bases of fuzzy inference systems, in the case of counter-predictive opinions of experts, are based on the removal of incompatible rules, depending on the value of their confidence coefficient. Moreover, the methods for identifying the values of confidence coefficients are not described enough, in addition, the removal of the rules leads to the loss of information about the object that the expert group formed. The proposed method of morphogenesis of rule bases in terms of counter-predictive expert opinions based on the results of the interaction of input variables is based on the identification of the confidence coefficient of each of the rules, depending on the number and level of qualification of the experts who proposed it. To evaluate the effectiveness of the proposed method, a numerical experiment was carried out, based on the study of a typical model for assessing the state of an object, which is used in other examples that demonstrate the principles of the fuzzy inference system. To compare the effectiveness, expert information processing methods containing incompatible rules were used. The performance criterion was the model sensitivity indicator. In the framework of the experiment, sensitivity was understood as the number of various values of the output variable depending on the values of the input parameters. As a result of the experiment, it was shown that the fuzzy inference system using the rule base formed using the proposed method has a noticeably wide variety of input values while maintaining the monotonicity of the change in the values of the output variable. The results of the study allow more advanced methods for identifying the state of elements of socio-economic and organizational-technical systems in which there is terminological uncertainty in the description of critical parameters and the incomplete knowledge of experts on a problem area.
Tekstkenmerken en tekstkwaliteit van leerlingteksten

Text features and quality of learner text: an annotation study Manually annotated corpora of writing products may greatly contribute to writing research: they offer detailed insights in the quality of these texts, in the text features actually attended to by human text raters, in possibilities and difficulties for the use of automatic writing analytics and writing tools, and in the relations between different text quality dimensions. This paper presents the Utrecht System for Annotation of Learner text (USALT), that covers both general features (orthography, punctuation, wording, coherence) and genre-specific elements (such as openings, endings, structuring devices and politeness). The annotations contain up to three items (annotation unit; problem type; part-of-speech tag). USALT reflects various text quality dimensions, notably correctness, comprehensibility and appropriateness (both stylistically and in terms of genre conventions). We present an USALT analysis of 371 texts produced by Dutch students from grades 7-9 (aged 12-15 years), taken from the so-called Schrijfmeters-corpus. The assignment concerned a letter about ‘typically Dutch things’ to a Swedish girl about to emigrate to The Netherlands. USALT reliabilities were adequate. In terms of problem frequency, we were struck by the pervasiveness of punctuation problems. Furthermore, the orthography and punctuation problems together present considerable difficulties for automatic analysis of original learner texts at this level. A remarkable result regarding relations between various text quality dimensions is that the frequency of orthography problems correlates higher with genre convention problems than with lexico-grammatical problems. We also used the annotations as predictors of the holistic scores assigned to the texts by human raters. Standardized annotation frequencies by themselves may account for 45% of the score variance, with a prominent role for annotations regarding genre elements; text length by itself explains 52%. The best model includes both text length and annotations (65% explained variance). In ongoing work, USALT is being extended to handle argumentative writing assignments.
Semantics of Musical Text as a Key Condition for Development of Secondary Musical Personality

From the standpoint of the aesthetic and semiotic approach music is understood as a complex psychosemantic text. Theoretical analysis of studies of the psychological connection between music and speech allowed to develop the concept of secondary musical personality as a sort of secondary linguistic personality. The author has developed a musical-semantic pattern of development of secondary musical personality in the educational process. This theoretical pattern is a system of interrelated conditions and factors of development of secondary musical personality. The author determines complexity, polysemy and semantic diversity of the musical text as the key condition. The author attaches special importance to forming potentials of classical music masterpieces in the musical-semantic pattern. The author identifies the artistic, spiritual and ethical levels of music as the main criteria of the musical masterpiece.
Shakthi, A Mobile Phone Application to Promote Legal Redressal Awareness Among Young Indian Women

Shakthi is a mobile phone application launched for spreading awareness of legal redressal procedures available for women in India. It was designed to gauge the need for legal awareness and was tested on a group of 30 young women between 18 and 25 years old. Many heinous crimes committed against women remain under-reported because of social stigma, illiteracy and lack of reporting knowledge. The application addressed topics such as what is a First Information Report (FIR) and how to file one, the redressal process for sexual harassment at work, etc. The analysis of the tests showed that the participants were keen on learning more information on women’s rights. Future programmes can help equip women with more knowledge on how to address crimes, and a more extensive app can add meaning to the technology-enhanced lives of women in developing countries.
Batch Gradient Training Method with Smoothing $$l_0$$ Regularization for Echo State Networks

The echo state networks (ESNs) have been widely used for time series prediction, due to their excellent learning performance and fast convergence speed. However, the obtained output weight of ESN by pseudoinverse is always ill-posed. In order to solve this problem, the ESN with batch gradient method and smoothing $$\ell _0$$ regularization (ESN-BGSL0) is studied. By introducing a smooth $$\ell _0$$ regularizer into the traditional error function, some redundant output weights of ESN-BGSL0 are driven to zeros and pruned. Two examples are performed to illustrate the efficiency of the proposed algorithm in terms of estimation accuracy and network compactness.
A Range Search Scheme Based on Encrypted Index Hiding Order and Access Patterns

With the development of the Internet of Things, cloud computing plays an important role in addressing the issue of big data. However, the privacy of sensitive data is central to user concerns about the adoption of cloud computing. Range search is a frequently used function, but there is still lack a good range search scheme which can satisfy both security and efficiency. The order-preserving encryption can achieve the maximum of efficiency for range search, but it is vulnerable to inference attacks. In this paper, we propose an encrypted B^+ Tree hiding order information to support range search. Homomorphic encryption can calculate the ciphertext without decryption. We introduce a trusted server, search server, which could obtain just partial order information to support the traversal of the encrypted "B" ^"+" Tree. The index server has two components: storage server and search server. Homomorphic encryption can calculate the ciphertext without decryption, and the search server only gets the perturbed partial order information. To hide the structure of an encrypted index, two different servers should take an oblivious way to travel the encrypted "B" ^"+" Tree. With the help of the search server, the storage server holding the original ciphertext could not obtain the exact knowledge about which data is fall in the search range. we perform an experiment for our proposed scheme, and the experimental results and analysis are presented to illustrate the scheme's effectiveness and security.
The Q*bird Level Designer: User-assisted procedural level design in augmented reality

Augmented reality (AR) gaming is becoming widely available thanks to improvements in hand-held devices such as phones and tablets. In this work, we describe our system for generating levels for the AR game, Q*bird. In Q*bird, the player must visit every cell in the level while avoiding bees and cannon balls, similarly to the 1982 arcade game, Q*bert. To create a new level, designers place game elements using virtual cards. The system then generates the remainder of the level, ensuring that it’s navigable. Designers can edit these levels by dragging and dropping the created geometry. To test, the designer can drop a character into the level and play it. This system aids playtesting and level design by allowing levels to be quickly specified and tested in the same environment in which the game is played. Furthermore, this system offers an example of how the design of AR levels can also be performed in AR.
Heterogeneous Classifier Dynamic Ensemble Algorithm based on Margin

Ensemble learning can improve the generalization ability of the system and improve the classification performance of the system. Although the technology has been widely developed, the generalized ensemble learning algorithm has poor generalization performance, sensitivity to noise, and "false neighborhood" phenomenon. Based on this, a margin-based dynamic ensemble algorithm for heterogeneous classifiers is proposed. Based on the margin-based heterogeneous classifier, the algorithm introduces two prototype selection mechanisms: edited nearest neighbor and adaptive nearest neighbor, which make the algorithm more stable and the classifier's capability evaluation more accurate. The effectiveness of the proposed algorithm is verified by experiments and analysis in the UCI dataset.