Reviewerly/exHarmony huggingface dataset:
Dewey’s Pragmatism as a Philosophy for Practice in Design Research Practice

In this chapter I offer a conclusion for the book as a whole at the same time as aiming to trace a forward path. I open with a general summary of the books’ argumentative arc, lining up the key points of the preceding discussions. Next, based on these key points, I explore the potential methodological implications of Dewey’s pragmatism for design research involving practice. The aim here is to draw out the relevant considerations and questions that might guide a project’s advance. Lastly, in the final section, I offer a statement on the potential value of adopting Deweyan pragmatism as a philosophy for design research involving practice and, as such, installing Dewey as an ‘intellectual underwriter’ of ‘designerly knowledge production’.
Multiple Information Fusion and Encryption Using DWT and Yang-Gu Mixture Amplitude-Phase Retrieval Algorithm in Fractional Fourier Domain

A new multiple information fusion and encryption using a wavelet transform and Yang-Gu mixture amplitude-phase retrieval algorithm in fractional Fourier domain are proposed. In this scheme, four color images are decomposed by using DWT and then the four LL sub-bands are fused to form an input color image. R, G, and B channels of input image are encoded individually by Yang-Gu mixture amplitude-phase retrieval algorithm in fractional Fourier domain together with coupled logistic maps. The individual binary random key and parameters of coupled logistic maps are used as decryption keys. The chaotic phase mask reduces the intricacy of the scheme. The multiple-decryption keys can evade various types of attacks. Numerical simulation results prove the security and feasibility of the strategy.
IoT-Controlled Railway Gate System With ML Object Detection Approach

The growing demand of internet of things (IoT) has rendered advancement in the practical fields towards society. In spite of recent advancements and cost effective IoT solutions for smart railway infrastructure, presently, most of the railway gates in India are opened and closed manually. This is a time-consuming process. It is an error-prone system and raises the accident probability. This chapter evaluates and demonstrates the applicability of IoT to resolve the problem of unmanned automatic railway crossing. The aim is to propose a prototype that will control with the help of microcontroller board, IoT sensor integration, and integrating it to machine learning-based image analysis to detect the intermediate real time obstacle (obstacle on the track). This kind of IoT system will also invite potential attacks, and traditional security countermeasures can be inefficient in dynamic IoT environments. So open challenges related to IoT security threats and emerging security mechanisms for security of the proposed smart railway crossing system are also elaborated.
The Inclusion Zone: Grounded Speculations in Chernobyl

The Chernobyl nuclear disaster of 1986 inspired this pictorial, which weaves together a number of technologies to tell a story about life in the Chernobyl Exclusion Zone in the aftermath of the nuclear meltdown. The artifacts included here run the gamut from functional to speculative and focus on how humans, plants, and animals can cope with the challenges of living in a disturbed landscape. They are designed to inspire conversation about the larger world to which they belong. Grounding speculative design in Chernobyl invites us to revisit the relationship between technology and ecology in sites of exclusion and abandon. What happens if we return, or are forced to return, to these hitherto excluded sites? What is it like to live in the aftermath of a disaster whose invisible effects continue for thousands of years? What are some of the technologies that might be seen in such a world and how do they facilitate cohabitation between the humans, plants, and animals of the Zone, and radiation? These questions blur some of the boundaries that can sometimes become too rigid in design fictions, such as the fixed present vs. the flexible future, or diegetic vs. speculative vs. functional prototypes. Moreover, while the Chernobyl Exclusion Zone is in many ways unique, Chernobyl is by no means the only Exclusion Zone. It is joined by a growing number of abandoned spaces, from shuttered reactors like Fukushima Daiichi, to nuclear waste sites like Hanford, US, and toxic e-waste sites like Agbogbloshie, Ghana. We propose that grounding speculations in such exclusion zones can contribute to more than human-centered design and post-humanist discourse.
Tech for Hire: Data Science-Related Jobs Signal Economic Growth

The Gross Domestic Product (GDP) of a certain country can be a window to a massive amount of information, as many assumptions can be made regarding economical, educational and technological aspects of said country with this value. However, a formal definition of said correlation is not always known in certain topics, such as technological advancements and job offer disponibility. In this study, we aim to compare technology-related job offers such as Data Scientist and Artificial Intelligence (AI) designer on various cities in the US with their respective GDP. To this aim, we collect data from the Indeed website about said job offers in different US cities, as well as their respective GDP values retrieved from the US Bureau of Economic Analysis (BEA) platform. Next we define a correlation matrix between job offers and GDP by metropolitan area, as well as implement a temporal analysis on the amount of said offers. Our results show an high increase in job offers on Machine Leaning (ML) compared to other jobs skills, in addition to establishing a strong positive correlation between Business Intelligence (BI), Data Analytics (DA) and Internet of Things (IoT) skills looked for in a metropolitan area with the GDP of said area.
Research on Edge Network Resource Allocation Mechanism for Mobile Blockchain

The blockchain mining process needs to solve a proof-of-work problem (PoW). Due to insufficient computing resources of the mobile device itself, as well as the insufficient computing power, the demand for computing power of the mining process cannot be met. In this paper, by constructing the mobile blockchain application model, aiming at maximizing system revenue and using the constraints of network resources as constraints, the paper allocates the network resource allocation mechanism to the mobile blockchain and realizes the effective use of blockchain technology in mobile applications. The resource allocation between adjacent devices can be modeled as a two-way auction model, and the optimal price can be determined by solving Bayes–Nash equilibrium. In addition, the credible value evaluation model is also introduced in this mechanism to solve the trusted value of the node.
Subway Rail Fastener Locating Based on Visual Attention Model

Fastener defects detection based on computer vision is an important task in subway rail inspection systems, in which the first step is fastener location. In this paper, a fastener locating method based on visual attention model for subway track is presented, which can implement fastener location in the subway track mixed with ballast-less track in the main line and ballast track on turnout region. Firstly, rail location is obtained by the vertical projection algorithm. Secondly, the image is classified into ballast or ballast-less based on visual attention model with the fractal dimension. Thirdly, ballast image and ballast-less image are treated separately. On one hand, in the ballast image, the sleeper is located with the line segment detector algorithm, and then fastener can be located by the sleeper location combined with the rail location. On the other hand, in the ballast-less image, the fastener is located with horizontal projection algorithm combined with the rail location. Experimental results demonstrate that the proposed method can locate the fastener accurately.
RtD in Situ

This workshop aims to bring together Research through Design (RtD) practitioners in the DIS community, giving them a space to present, debate, and discuss issues emerging from their work. In particular, our goal is to catalyze a focused conversation on contexts and specific situations of research through design, discussing the ins-and-outs of working in a specific context and with particular issues of consequence. Building on the success of prior RtD and design research workshops at HCI conferences, this workshop will focus on how RtD artifacts operate in these contexts, with the goal of connecting diverse artefacts with broader methods in HCI and Design.
Towards Extracting Structured Drug Information from Raw Texts using Deep Learning

This paper presents a technique that extracts relevant information from a medical prescription. In order to solve this problem we have approached the problem from Name Entity Recognition (NER) perspective, which aims to label each word with a specific tag. The NER problem is solved using Deep Learning (DL) techniques combined with Conditional Random Fields (CRF). The final model is tested using 5-fold cross-validation technique, and it achieves around 91% F1-measure. The training and testing is done on our corpus, which was manually annotated.
Classification of a Pedestrian’s Behaviour Using Dual Deep Neural Networks

Vulnerable road user safety is of paramount importance as transport moves towards fully autonomous driving. The research question posed by this research is of how can we train a computer to be able to see and perceive a pedestrian’s movement. This work presents a dual network architecture, trained in tandem, which is capable of classifying the behaviour of a pedestrian from a single image with no prior context. The results show that the most successful network was able to achieve a correct classification accuracy of 94.3% when classifying images based on their behaviour. This shows the use of a novel data fusion method for pedestrian images and human poses. Having a network with these capabilities is important for the future of transport, as it will allow vehicles to correctly perceive the intention of pedestrians crossing the street, and will ultimately lead to fewer pedestrian casualties on our roads.
Contracts for Clouds, Revisited: An Analysis of the Standard Contracts for 40 Cloud Computing Services

In this paper, we report the results of a detailed survey of the standard contracts for 40 major cloud computing services, including Amazon Web Services, Google Cloud, and Microsoft Azure. We cover a broad range of contractual issues, including clauses dealing with choice of law, termination, data retention, liability, and intellectual property. We compare the results to those of previous surveys conducted in 2010, 2013, and 2015 to show how cloud contracts have developed over time. In particular, we identify changes with regard to choice of law and of forum, and warranty and liability provisions. We conclude that over the past ten years, standard cloud contracts have become more tailored to customer location, for instance by having distinct terms for US and European customers, and more in line with European consumer protection law, including by having distinct terms for businesses and consumers.For a related survey of the privacy policies of 40 cloud services, see “Privacy in the Clouds, Revisited: An Analysis of the Privacy Policies of 40 Cloud Computing Services” on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3823424
Research on Intelligent Control Based on Multi-Agent Technology and Its Application in Robot Field

Abstract Firstly, the definition and characteristics of multi-agent technology are described. By analyzing the application research literature of multi-agent technology at home and abroad, the basic research of multi-agent system is analyzed and the technological development in the direction of multi-agent consistency and control is combed. Then the technical methods of intelligent control are analyzed, and the application of intelligent control in robot field is analyzed and explored. It is pointed out that the advantages of intelligent control are open, hierarchical and distributed structure, strong comprehensive information processing ability, and good at handling uncertain, highly nonlinear and complex control tasks of the model. Its shortcomings are that the theoretical basis is still in the development stage, the control accuracy is not high, and the real-time performance is poor. Finally, the development direction of intelligent control is expounded in combination with the above contents, hoping to create conditions for the overall improvement of Chinese intelligent control technology.
THE DEVELOPMENT OF CRITICAL THINKING FOR HIGHER STUDENTS: NOTES OF THE ENGLISH TEACHER

The paper is devoted to critical thinking development techniques in the process of teaching and learning English at the University. A wide range of “critical thinking” definitions and interpretations was studied to single out those ideas that help to form the basis for choosing particular critical thinking development techniques. In this paper we focus on our didactic experience in developing critical thinking skills of law students.
Analysis of The Application of Fuzzy Logic and Levenberg-Marquardt in The Calculation of Used Car Prices

Abstract In this study using two methods, namely Sugeno Fuzzy Logic and Levenberg-Marquartd methods. The data to be used is data from used Toyota Avanza cars for Medan and surrounding areas. The use of the fuzzy method in this study is based on its superiority in solving vague problems so that it is considered to be suitable for the condition of a used car in which each unit has different conditions. The results of the use of Sugeno fuzzy data obtained will be used as input into the levenberg-marquardt (LM) network which has a fairly good ability to perform calculations, especially to predict an output with a more efficient time. LM produces an output with a small Minimun Square Error (MSE) value of 3.64 in testing with 9 hidden layers. On the other hand, to analyze the resulting error, a comparison is made between networks that have 9 hidden layers, 27 hidden layers and 81 hidden layers with the smallest MSE results obtained on a network with 9 hidden layers.
Rap Lyrics Generation Using Vowel GAN

Despite the success of recent rap and poetry generations using neural models, many of them do not consider vowels of the entire lyrics. Also, in many cases it is virtually impossible to generate completely new lyrics, because only existing rap lyrics are used as data sets. This paper proposes a new method of rap lyrics generation using a large amount of text such as novels in addition to rap lyrics. We divided the generation of rap lyrics into two steps; first, Generative Adversalial Net (GAN) generates rhymes and flows. Second, sequence-to-sequence converts them into rap lyrics. In addition, this method refers to the generation style of rap songs. In other words, they determine the music and rhythm first and apply the words second. We evaluated our method based on BLEU that can be measured mechanically.
Capsule Networks for Semantic Segmentation

The importance of scene understanding as a core computer vision problem is highlighted by the fact that an increasing number of applications nourish from inferring knowledge from the problem statement of scene parsing and understanding the context and relations between all the objects involved. These problems are majorly being tackled by using deep neural network architectures, usually Convolutional Neural Networks, which are surpassing other approaches by a large margin in terms of accuracy. But there remain quite a few drawbacks and limitations to this approach in terms of efficiency. Therefore, we review a newly introduced concept of encapsulation of auto-encoders, to give a multi-dimensional representation to the given scene, as an efficient alternative to Convolutional Neural Networks. This paper also proposes a novel use case for Capsule Networks to be used in Semantic Segmentation, a possibility which has never been solitarily explored before.
Analysis of Tactile Display Designs on Philippine Money for the Blind and Visually Impaired

According to the World Health Organization, at least 2.2 billion people have a vision impairment or blindness. In the Philippines, the number of people who are bilaterally blind was estimated at 332,150 from a report of the Department of Health in 2017. These number of people face a lot of challenges when living independently, one of which is handling money. The aim of the study is to analyze the effectiveness in aiding the blind and visually impaired of the current Philippine banknote together with four other tactile designs. A tactile test with the goal of identifying a specific banknote and discriminating between banknotes was conducted with twenty blindfolded participants. Metrics of the test include: (1) number of banknotes incorrectly identified and discriminated, and (2) average time of correctly identifying and discriminating banknotes, for each tactile design. Two-way Analysis of Variance and the Fisher’s LSD tests were used to analyze the results of the test.
Generalized Cyclotomic Double Circulant Self-Dual Codes of Length 4<i>p</i>

Constructions of some double circulant self-dual codes on the residue ring Z <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2ρ</sub> , where p is a prime and satisfies p ≡ 3 mod 4, are proposed. Two new structures of these codes are formed from the theory of generalized cyclotomy. Moreover, both [12, 6, 4] and [44, 22, 8] optimal self-dual codes over GF(2) and a family of [28, 14, 9] highest known self-dual codes over GF(4) are given.
Failure of the MacWilliams identities for the Lee weight enumerator over <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e22" altimg="si3.svg"><mml:msub><mml:mrow><mml:mi mathvariant="double-struck">Z</mml:mi></mml:mrow><mml:mrow><mml:mi>m</mml:mi></mml:mrow></mml:msub></mml:math>, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e32" altimg="si4.svg"><mml:mrow><mml:mi>m</mml:mi><mml:mo linebreak="goodbreak" linebreakstyle="after…

In this paper we show the nonexistence of any version of the MacWilliams identities for Lee weight enumerators over Zm, m⩾5.
Key-Recovery Security of Single-Key Even-Mansour Ciphers

In this paper, we explore the security of single-key Even-Mansour ciphers against key-recovery attacks. First, we introduce a simple key-recovery attack using key relations on an n-bit r-round single-key Even-Mansour cipher (r-SEM). This attack is feasible with queries of DTr=O(2rn) and $2^{\frac{2r}{r + 1}n}$ memory accesses, which is $2^{\frac{1}{r + 1}n}$ times smaller than the previous generic attacks on r-SEM, where D and T are the number of queries to the encryption function EK and the internal permutation P, respectively. Next, we further reduce the time complexity of the key recovery attack on 2-SEM by a start-in-the-middle approach. This is the first attack that is more efficient than an exhaustive key search while keeping the query bound of DT2=O(22n). Finally, we leverage the start-in-the-middle approach to directly improve the previous attacks on 2-SEM by Dinur et al., which exploit t-way collisions of the underlying function. Our improved attacks do not keep the bound of DT2=O(22n), but are the most time-efficient attacks among the existing ones. For n=64, 128 and 256, our attack is feasible with the time complexity of about $2^{n} \cdot \frac{1}{2 n}$ in the chosen-plaintext model, while Dinur et al.'s attack requires $2^{n} \cdot \frac{{\rm log}(n)}{ n} $ in the known-plaintext model.
Research and Design of the Mutual Aid Tokenized Economy Structure Based on Blockchain Technology

In the current time bank system, problems such as difficult time token to circulate, difficult to trust data, and insecure data exist. In order to solve these problems, a design and implementation of a time bank system architecture based on blockchain technology is proposed. Firstly, analyze the business process of the time bank system and draw the use case diagram; then layer the overall architecture of the system: the application interface layer and the blockchain layer; then carry out a detailed architecture design, including the division of system functional modules: login registration module, publishing service requirements module, accepting service requirements module, managing service recipients, performing public service module, token management module, and drawing the main function flow chart of the system, and the design of the table in the server database of the system. The time bank system based on blockchain technology reduces the difficulty of time token flow, realizes data tamper-resistance through timestamp technology, distributed storage guarantees data security, and reduces the difficulty of time banking system operation.
Evaluating Solar Energy Harvesting using Artificial Neural Networks: A Case study in Togo

The work sought to develop a model for the evaluation of solar energy harvesting potentials in Togo using an approach based on artificial neural networks (ANNs) in order to predict the daily irradiation for some areas under climatic conditions. Two types of ANN architecture were evaluated the radial basic function (RBF) and multi-layer perceptron (MLP). The data were collected in 28 cities, and data from of 8 cities were used for the training stage in order to come with the suitable model for the other cities. The results indicated that the ANN-MLP model 8 has provided the best performance and its accuracy was tested. Furthermore, the solar generation potential was evaluated. The sites in the study have exhibited a high potential for solar energy generation.
Assessing Centrality Without Knowing Connections

We consider the privacy-preserving computation of node influence in distributed social networks, as measured by egocentric betweenness centrality (EBC). Motivated by modern communication networks spanning multiple providers, we show for the first time how multiple mutually-distrusting parties can successfully compute node EBC while revealing only differentially-private information about their internal network connections. A theoretical utility analysis upper bounds a primary source of private EBC error---private release of ego networks---with high probability. Empirical results demonstrate practical applicability with a low 1.07 relative error achievable at strong privacy budget $\epsilon=0.1$ on a Facebook graph, and insignificant performance degradation as the number of network provider parties grows.
Affective Words and the Company They Keep: Studying the Accuracy of Affective Word Lists in Determining Sentence and Word Valence in a Domain-Specific Corpus

In this article, we explore whether and how linguistic and pragmatic context can change individual word valence and emotionality in two parts. In the first part, we investigate whether sentence contexts retrieved from a domain-specific corpus (soccer) bias individual word affect. We then examine whether word valence with and without context accurately indicates sentence valence. In the second part, we compare word ratings from the first part to four different existing affective lexicons, with different levels of sensitivity to semantic and pragmatic context, and examine their accuracy in determining sentence valence. Results show a significant difference between words with and without context, the former more accurate in determining sentence valence than the latter. The preexisting lexicons were found to be similar to the individual word ratings collected in the first part of the study, with human-evaluated, context-sensitive lexicons being the most accurate in determining sentence valence. We discuss implications for emotion theory and bag-of-words approaches to sentiment analysis.