Reviewerly/exHarmony huggingface dataset:
An Energy-saving Oriented Air Balancing Method based on the Extreme Learning Machine

This paper proposes an energy-saving oriented air balancing method based on the extreme learning machine. First, the relationship between the design airflow and the damper angles of all terminals is modeled by the extreme learning machine. Then, a top-down searching method for the minimal required fan voltage is proposed. The optimal damper angles and the minimal required fan voltage can be determined. Under the minimal fan voltage, the energy consumption of the air balancing system can reach the smallest value for each case. This air balancing method can accurately adjust the airflow in each terminal to the design value. The effectiveness of this method is verified by the experiments.
M-GBDT2NN: A more generalized framework of GBDT2NN for online update

The large-scale, scalable, flexible characteristics make the researches of online update more important in the Internet of Things (IoT). Gradient Boosting Decision Tree (GBDT) is commonly used to deal with the numerical data, while it cannot be updated online. To better solve the prediction problems, we propose a more generalized approach, M-GBDT2NN, based on GBDT2NN. Compared with GBDT2NN, the new method is also applicable to the multi-classification problems, besides binary classification, regression. In the new framework, it takes the iteration of GBDT as the smallest unit to ensure the additive relation among the distilled models, and it predicts a probability vector rather than a numerical value. This paper analyzes the generalization and the ability of online update of M-GBDT2NN. The experimental results demonstrate that the proposed method can perform better than the other methods in both multi-classification problems and online update.
How to Think About Third Wave HCI that Questions the Normative Culture in Computer Science?

Think about normative culture in computer science and question it based on third wave Human-Computer Interaction also involves problematizing our culture, our society and us as part of livelihood. The Science, Technology and Society studies that are basing our work by feminists’ optics reveal that there is no way to think about technoscience without thinking about people who are the reason for its existence. Our objective is highlight plural approaches in the computer science graduate courses documents in Brazilian Computer Science and in Bachelor in Information Systems and Computer Engineering from a public institution in Brazil based on feminist theories of Science, Technology and Society. The work results are: a) structural barriers in low women participation; b) gender disparities are not even mentioned in Computer Engineering documents; c) intersection of race, class and gender are present only in Bachelor in Information Systems documents; d) power relations in macro axes reveal intentions of those who create computer science documents in Brazil.
Rethinking Education in a Crisis: How New Is a New Common Really?

Abstract The COVID-19 pandemic has disrupted the status quo in many areas of society, including education. At all educational levels, on-site lecturing had to switch instantaneously to an online mode of instruction. This transition was so straightforward, that the argument could be made for online education to become a permanent fixture, particularly if it is more efficient, cheaper, and more effective than traditional education. Extensive meta-analyses, however, show that most online teaching practices do not lead to better educational outcomes than the on-site alternatives. Worse yet, the traditional face-to-face mode of lecturing is ineffective in the absence of personalized interactions. The proposed solutions are offered by artificial intelligence research, including virtual reality, intelligent tutoring systems, and serious games—solutions that have so far not been extensively implemented in practice. The current health crisis provides our educational professionals with an opportunity to rethink their teaching practices and focus on applying these promising new alternatives.
Computationally efficient Bayesian quantum state tomography

We describe a method for Bayesian quantum state estimation combining efficient parameterization, a pseudo-likelihood, and advanced numerical sampling techniques. Examples reveal significant computational speedup, indicating the approach's promise in practical quantum state tomography.
Blockchain technology: Theory and practice

In the physical world, money exchange between two persons can happen without notice and intervention of a trusted third party. Such a money exchange transaction is called peer-to-peer transaction. When it comes to digital world, money exchange between two on-line entities is always monitored by a trusted third party like bank. The cryptographic research community constantly asked for over two decades the question: “can the concept of peer-to-peer transactions be introduced into the digital world?” The landmark proposal of Bitcoin crypto-currency (Nakamoto, 2009) provides a perfect answer to the question. However, Bitcoin suffers from criticism from many, given its uncontrollable nature. Despite this setback, what has caught more attention of the community is its underlying technology: Blockchain. The blockchain technology is touted to be the next big wave in industry as it promises the features: transparency of data, accountability of transactions, transactions without intermediary, and data symmetry. The banking sector and supply chain systems are two fields that benefit most from this new technology and will witness a dramatic transformation. In addition to these two fields, blockchain has potential to show its implications to water management, health analytics, and several other areas. However, from a development point of view, the technology is still in rudimentary stage. It demands expertise in the subjects: distributed networking and cryptography. The features promised by the technology seek a new type of cryptographic algorithms, which are sort of open issues to be resolved. These open issues form the current active research of the cryptographic community. The main focus of the present chapter is to teach the fundamentals of the blockchain technology and its use cases. The use cases are discussed through the blockchain platforms: Hyperledger, Ethereum, and other upcoming platforms. The chapter discusses the open research problems that are to be solved in having a full-fledged blockchain environment.
Audience Tracking and Cheering Content Control in Sports Events

Swearing cheers encountered in sports competitions do not comply with sports ethics and morals. Even if this kind of cheering is a group, the entire tribune block is penalized in accordance with the current rules. This method is not preventive and individual punishment should be used. The aim of this study is to determine the individuals who cheer with swearing content. In this study, the person detection is made with the multi-task cascaded convolutional neural network. Moreover, facial landmarks representing the facial regions and the regions related to them are determined as a result of this process. The mouth region is also determined by means of these important points removed, and finally the mouth is determined according to the equation. The face recognition is carried out because the person would be in a state of yelling if the mouth opening ratio exceeds the threshold value by determining the rate of opening. Landmarks extracted from the facial regions for the face recognition are transformed into feature vectors by FaceNet, and the model is created by classifying these vectors with classifiers to use in recognition process. When evaluated in terms of industry, face recognition and detection systems find a wide field of study.
Grapheme to Phoneme Conversion of Norwegian using Hidden Markov Models

In this paper, the applicability of Hidden Markov Models to the grapheme-to-phoneme (GTP) problem of Norwegian is explored. The grapheme-to-phoneme problem, is part of the problem of converting sequences of graphemes to sequences of phonemes. This is an important issue in both text-to-speech and speech recognition systems. With the assistance of established toolkits like CMU-Cambridge Language Modeling Toolkit and Hidden Markov Model Toolkit (HTK), an approach based on Hidden Markov Models (HMM) is presented and implemented. By such an approach every phoneme is modeled by a HMM that generates the graphemes. This approach has previously been tested on English data. By using HMM for Norwegian, a phoneme accuracy of 94%, and a word accuracy of 68% is obtained. This is slightly better than similar results obtained for English.
Feature Extraction and Research Based on MRI Image of Cerebral Hemorrhage

MRI is a kind of biological magnetic spin imaging technology. Making full use of MRI images is of great significance for improving the accuracy of medical image diagnosis process for the diagnosis of diseases. In the diagnosis of cerebral hemorrhage, the location and size of the hemorrhage area are meaningful indicators for diagnosing the severity of cerebral hemorrhage. In order to assist the doctor's diagnosis, we have proposed an automatic detection method based on the combination of morphology and threshold segmentation to calculate the location and size of the bleeding point according to the characteristics of the image of different sequences in the magnetic resonance image. : (1) Pre-process the MRI image; (2) Remove the skull part by morphology and leave only the brain soft tissue image; (3) Use Oust and morphology to extract the suspected lesion parts in the brain image; (4) Finally, The longitudinal relaxation time (T1 image) and transverse relaxation time (T2 images) were fused to locate the bleeding point. The experimental results show that the algorithm has high feasibility and accurate positioning of bleeding points.MRI is a kind of biological magnetic spin imaging technology. Making full use of MRI images is of great significance for improving the accuracy of medical image diagnosis process for the diagnosis of diseases. In the diagnosis of cerebral hemorrhage, the location and size of the hemorrhage area are meaningful indicators for diagnosing the severity of cerebral hemorrhage. In order to assist the doctor's diagnosis, we have proposed an automatic detection method based on the combination of morphology and threshold segmentation to calculate the location and size of the bleeding point according to the characteristics of the image of different sequences in the magnetic resonance image. : (1) Pre-process the MRI image; (2) Remove the skull part by morphology and leave only the brain soft tissue image; (3) Use Oust and morphology to extract the suspected lesion parts in the brain image; (4) Finally, The longitudinal relaxation time (T1 image) and transverse relaxation time (T2 images) were fused to locate the bleeding point. The experimental results show that the algorithm has high feasibility and accurate positioning of bleeding points.
Fault-insertion and fault-fixing: analysing developer activity over time

Developers inevitably make human errors while coding. These errors can lead to faults in code, some of which may result in system failures. It is important to reduce the faults inserted by developers as well as fix any that slip through. To investigate the fault insertion and fault fixing activities of developers. We identify developers who insert and fix faults, ask whether code topic `experts' insert fewer faults, and experts fix more faults and whether patterns of insertion and fixing change over time. We perform a time-based analysis of developer activity on six Apache projects using Latent Dirichlet Allocation (LDA), Network Analysis and Topic Modelling. We show that: the majority of the projects we analysed have developers who dominate in the insertion and fixing of faults; Faults are less likely to be inserted by developers with code topic expertise; Different projects have different patterns of fault inserting and fixing over time. We recommend that projects identify the code topic expertise of developers and use expertise information to inform the assignment of project work. We propose a preliminary analytics dashboard of data to enable projects to track fault insertion and fixing over time. This dashboard should help projects to identify any anomalous insertion and fixing activity.
Contingent Claims

Technocapitalism acts through micro-performative mechanisms which escape human cognition and sense perception but at the same time influence individual behaviour and social conduct. Automated finance and corporate surveillance are both leveraged by proprietary tools operating in the invisible realm of microseconds. While its immediate agency colonizes the future at present, it escapes our phenomenological scope. In fact, technocapitalism operates on a new level of exercising power by shifting its language from representative to performative speech. Hence, data-driven performativity has very material consequences on our real biological and social lives – we are losing our senses in more than one way. How can we move and see through the maze of finance and other data-driven performativity?This essay argues that the performative arts are well situated to create participative situations and alliances that allow for embodied awareness to reveal and resist these infrastructures. However, such art needs to translate technocapitalism beyond cognition, speech and rationality. And such counter-performative aesthetics are to be situated in the field of consequences and take performance outside the metaphoric spaces of the (live) arts. The essay therefore proposes a new reading of the term ‘resolution’ and its semantic field – ranging from perception and visualization to knowledge production and (joint) decision making – to counter the non-transparency of black box exploitation. But there is an urgency to go a step further and transgress the realm of critique and representation towards performative engagements in insurrection if we want to claim an agency in which all the senses of resolution come to bear. Activating the potential of resolution as an alternative to the rather passive notion of transparency calls for ‘renegade activism’ as a strategy of resistance that makes the black box speak from inside.
Parameter Based Abstraction For a Modular Software

Main idea of modular software is to define the interfaces of each software component clearly and design the system flow through these interfaces. As long as these interface definitions remain unchanged, a modification in a component would not affect one another. However; in a system evolving with changing user requirements and hardware, it is impossible to avoid changes in the requirements of software components. This article focuses on parameter based abstraction approach, which aims to minimalize the amount of change in software components and interfaces in such systems. Primary philosophy of this approach is to abstract characteristic variables used system-wide as parameters and express the inter-component interaction as parameter updates instead of function calls.
Limit distribution of a time-dependent quantum walk on the half line

We focus on a 2-period time-dependent quantum walk on the half line in this paper. The quantum walker launches at the edge of the half line in a localized superposition state and its time evolution is carried out with two unitary operations which are alternately cast to the quantum walk. As a result, long-time limit finding probabilities of the quantum walk turn to be determined by either one of the two operations, but not both. More interestingly, the limit finding probabilities are independent from the localized initial state. We will approach the appreciated features via a quantum walk on the line which is able to reproduce the time-dependent walk on the half line.
The history of Blitz/Cray-Blitz/Crafty

This article is a series of anecdotes about the development of several programs that advanced the state of the art in computer chess. The best known is Cray Blitz, which won the 1983 and 1986 World Computer Chess Championships. However, in terms of overall impact, perhaps Crafty is the most important. As a high-performing open-source program, it has been used by countless number of researchers and hobbyists to develop computer chess programs for competitions, research, and for fun.
Development of pedagogical thinking in the professional training of a future teacher

The article deals with an urgent problem – the development of pedagogical thinking as one of the main components of teachers’ professional activity. The characteristics included in the concept of „pedagogical thinking” are presented their essence and features are revealed. Those types of thinking which are reflected in the structure and content of pedagogical thinking are considered. The main attention is paid to the organization of work on the development of pedagogical thinking, which ensures the increase of efficiency of the future teacher’s professional activity. The ways of development of pedagogical thinking are specified. The classification of pedagogical problem situations suggested by the author and the ways of their presentation in the educational process are given. The necessity of solving future teachers’ pedagogical problems, tasks and analysis of pedagogical situations as the main means of developing pedagogical thinking is underlined.
Exploring Spatiotemporal Features for Activity Classifications in Films

Humans are able to appreciate implicit and explicit contexts in a visual scene within a few seconds. How we obtain the interpretations of the visual scene using computers has not been well understood, and so the question remains whether this ability could be emulated. We investigated activity classifications of movie clips using 3D convolutional neural network (CNN) as well as combinations of 2D CNN and long short-term memory (LSTM). This work was motivated by the concepts that CNN can effectively learn the representation of visual features, and LSTM can effectively learn temporal information. Hence, an architecture that combined information from many time slices should provide an effective means to capture the spatiotemporal features from a sequence of images. Eight experiments run on the following three main architectures were carried out: 3DCNN, ConvLSTM2D, and a pipeline of pre-trained CNN-LSTM. We analyzed the empirical output, followed by a critical discussion of the analyses and suggestions for future research directions in this domain.
LSH high dimension index algorithm based on thumbnails

Aiming at the hierarchical index method of large image features, the hierarchical index structure of large image is established by using the global position constraint information of large image. This method combines LSH algorithm and KD tree algorithm based on location information. It can control the space complexity of LSH algorithm and the time complexity of KD tree algorithm in high-dimensional feature retrieval. It can speed up the search speed and improve the accuracy of finding the nearest neighbor features, so as to obtain the best comprehensive search performance compared with LSH algorithm and KD tree algorithm. This method mainly includes: extracting thumbnail to build two-layer pyramid image index structure, using LSH algorithm to search rough location for thumbnail, and using KD tree algorithm based on location information to search feature points near neighbor for original image.
Experimentation of digital multimedia forensics: State of the art and research gaps

Abstract Digital multimedia forensics (DMF) plays an outstanding role in digital forensics (DF) area as it encompasses solutions for promoting image, audio, and video evidence to be used in court. As every science, one straightforward way of evolving is conducting formal experiments and providing reliable and auditable evidence. Therefore, in this article, we systematically map and analyze how experiments in DMF have been conducted and whether data‐based evidence has been provided. This article presents a subset of results on DMF from a wider mapping study on DF experimentation. We then analyzed 49 experiments resulting from electronic and manual searches in widely known electronic databases and conferences/workshops on DF. We used them to answer six research questions. We demonstrated that DMF needs to improve the way experiments are reported, especially how data are shared to allow reproducibility and, consequently, evolution of the research topic. We show that experimental elements, for example, hypothesis, variables, design, instrumentation, validity evaluation, setup, training, data sets and benchmarks, statistical techniques (descriptive, hypothesis, and effect size test), and limitations, should be better reported. As a general result, we understand DMF formal experimentation needs to evolve toward providing useful, reliable, auditable, and reproducible experimental evidence as both academia and practitioners might straightforward benefit from such evolution. This article is categorized under: Digital and Multimedia Science &gt; Multimedia Forensics
The Strategy of Personal Customization and Method of Collecting Professional Dynamic Information

Abstract The need for personal customization in professional dynamic information collection requires crawling information that is published within specified time durations, extracting accurate and interest-focused information, and assuring the completeness of the information. By combining the technology of jsoup and Lucene as well as the extensibility research on Heritrix, this paper proposes a set of personal customization strategies and methods for professional dynamic information collection: analyze the composition of the URL link to filter out information beyond a specified time window according to different URL types; set up different cleaning templates to extract the attribute items for different styles of websites; establish user personalization blacklist to filter out the information with poor relevance to user interests; apply correction function to improve the robustness of the crawler and guarantee the completeness of the information. Using the collection part of the Dynamic Information Collecting System of Oil and Gas Resources project as a case verification, the results show that the strategies and methods can be used to achieve the three objectives: timeliness; accuracy and interest-focus; and completeness. The proposed strategies and methods may be applied to the construction of an industrial dynamic information collection system.
Features of Controlling the Large-Scale Cyber-Physical Water Supply Systems in Cities of Different Countries

This paper describes control models of large-scale cyber - physical water supply systems in cities of various countries-Asia (China and Singapore), the United States, England and Europe, and Russia are analyzed. Deficiencies in control models were identified due to current potential threats of water scarcity, degradation of water sources, and risks of chemical and biological contamination.
A New Mathematical Model to Improve Encryption Process Using Taylor Expansion

Data transmission through channels is gaining upsurge, and there has been a need to protect data from hackers (which may cause hacking, fabrication or modification, etc.), also to protect the transmission channels themselves. Encryption is one of the techniques to protect data. In this research, a new method of data ciphering is proposed. The proposed method bases on the Taylor series and it works by choosing a constant value and a Taylor formula as two keys. Then, the first key (the constant value) substitutes the plain text in the Taylor formula. Decoding phase is required to compute Taylor inversion. Several types of attack, such as ADFGVX dictionary attack, frequency attack, and autocorrelation attack, are used to evaluate the results of the proposed method. The use of Taylor series adds more complexity to the ciphertext. The probability of breaking cipher wm increase because of the values range used in x-value substituting, where the range is from 0 to n, so the proposed cryptosystem wm be n*n!..