Reviewerly/exHarmony huggingface dataset:
Design Strategies and Optimizations for Human-Data Interaction Systems in Museums

Embodied interaction is particularly useful in museums because it allows to leverage findings from embodied cognition to support the learning of STEM concepts and thinking skills. In this paper, we focus on Human-Data Interaction (HDI), a class of embodied interactions that investigates the design of interactive data visualizations that users control with gestures and body movements. We describe an HDI system that we iteratively designed, implemented, and observed at a science museum, and that allows visitors to explore large sets of data on two 3D globe maps. We present and discuss design strategies and optimization that we implemented to mitigate two sets of design challenges: (1) Dealing with display, interaction, and affordance blindness; and, (2) Supporting multiple functionalities and collaboration.
Automatic Thresholding Technique Using Reconfigurable Hardware

This research presents an efficient automatic thresholding technique based on Otsu’s method that can be used in edge detection algorithms and then applied as a plug-in for real-time image processing devices. The proposed thresholding technique uses an iterative clustering based method that targets a reduced number of operations. It is well known that the Otsu calculates the global threshold splitting the image into two classes, foreground and background, and choose the threshold that minimizes the interclass variance of the threshold black and white pixels. In this paper, a faster version of Otsu’s method is proposed knowing that the only pixels that have to be moved from one class to another class are the ones with values in between the previous two thresholds. This procedure yields the same set of thresholds as the original method but the redundant computation has been removed and, in this way, only few operations are required. The proposed thresholding technique has been implemented in software using C# programing language and in reconfigurable hardware on a Spartan 3E XC3S500E FPGA board using VHDL. The results obtained, presented for different digital images, confirm that the proposed iterative thresholding algorithm and architecture on FPGA can achieve the requirements to be included in real-time image processing systems.
Fostering Penetrative Thinking in Geosciences Through Immersive Experiences: A Case Study in Visualizing Earthquake Locations in 3D

Thinking in and understanding of three-dimensional structures is omnipresent in many sciences from chemistry to geosciences. Current visualizations, however, are still using two-dimensional media such as maps or three-dimensional representations accessible through two-dimensional interfaces (e.g., desktop computers). The emergence of immersive virtual reality environments, both accessible and of high-quality, allows for creating embodied and interactive experiences that permit for rethinking learning environments and provide access to three-dimensional information through three-dimensional interfaces. However, there is a shortage of empirical studies on immersive learning environments. In response to this shortcoming, this study examines the role of immersive VR (iVR) in improving students' learning experience and performance in terms of penetrative thinking in a critical 3D task in geosciences education: drawing cross-sections. We developed a pilot study where students were asked to draw cross-sections of the depth and geometry of earthquakes at two subduction zones after visualizing the earthquake locations either in iVR or 2D maps on a computer. The results of our study show that iVR creates a better learning experience; students reported significantly higher scores in terms of Spatial Situation Model and there is anecdotal evidence in favor of higher reflective thinking in iVR. In terms of learning performance, we did not find a significant difference in the graded exercise of drawing cross-sections. However, iVR seems to have a positive effect on understanding the geometry of earthquake locations in a complex tectonic environment such as Japan. Our results, therefore, add to the growing body of literature that draws a more nuanced picture of the benefits of immersive learning environments calling for larger scale and in-depth studies.
Interpolation Attacks on Round-Reduced Elephant, Kravatte and Xoofff

Abstract We introduce an interpolation attack using the Moebius Transform. This can reduce the time complexity to get a linear system of equations for specified intermediate state bits, which is general to cryptanalysis of some ciphers with update function of low algebraic degree. Along this line, we perform an interpolation attack against Elephant-Delirium, a round 2 submission of the ongoing national institute of standards and technology (NIST) lightweight cryptography project. This is the first third-party cryptanalysis on this cipher. Moreover, we promote the interpolation attack by applying it to the Farfalle pseudo-random constructions Kravatte and Xoofff. Our attacks turn out to be the most efficient method for these ciphers thus far.
The role of hue in visual search for texture differences: Implications for camouflage design

The purpose of camouflage is to be inconspicuous against a given background. Colour is an important component of camouflage, and the task of designing a single camouflage pattern for use against multiple different backgrounds is particularly challenging. As it is impossible to match the colour gamut of each background exactly, the question arises which colours from the different backgrounds should be incorporated in a camouflage pattern to achieve optimal concealment. Here, we used a visual search paradigm to address this question. Observers searched multi-coloured continuous textures for target regions defined by either the presence or absence of additional hues. Targets could be either a combination of five hues against a four-hued background (“patches”), or a combination of four hues against a five-hued background (“holes”). In Experiment 1, a search asymmetry was observed for the different targets, as observers were less accurate and slower at detecting holes than patches. Additionally, we observed a linear separability effect: search for a target was more difficult when the hue that defined the target was within the gamut of distractor colours (e.g. orange amongst reds and yellows). In Experiment 2, we further investigated “hole” targets designed for two different backgrounds and found that optimal concealment against both backgrounds was achieved by including intermediate colours that represented a compromise between the common colours and the unique colours of each background. The findings provide insights into how search asymmetries can be extended to complex texture properties and help inform the design process of camouflage for multiple backgrounds.
Network Communication: Algorithmic and Risky Connection

The article presents methods of reasoning about the modern algorithmic culture defined by the communicative modes of networks. It is emphasized that, regardless of the biases and accentuations of theoretical thought regarding the information environment and digital communications, the transformation of operator statuses and the mechanics of exchanges, the conceptual space is increasingly leaning towards variations in modeling the interaction of human and non-human agents, in parity or enhancing the privileges of everyone. In support of this, cases of mutual observability of complex algorithms of status online platforms and financial markets, that increases their micro-temporal predictability; the use of botnets of infected computers without the consent of their users in an attack on targeted websites, demonstrating the capabilities of internal machine logic; broadcasting “fake news” in informative practices inspired by human intentionality and adjusted by network generativity are considered. In attempts to discuss socio-technical media reality, discourses of power systems, hierarchical structures and civil society are combined with an understanding of the processes of “social submission” and “machine enslavement”(Deleuze, Guattari), the “technical mentality” (Simondon), as the ontogenetic ability of complex machines to autonomous and self-referential development, that should not be ignored or exaggerated. The search for “non-technical” semantics for describing the media state, updating an acceptable language for sociology, without losing the patterns and facts of media reality, providing a speedy universal connection, producing new solidarity and disunity, changing meanings, but also exuding virulence, remains urgently needed.
Adder Circuit on IBM Universal Quantum Computers

This paper reports the experiments on IBM quantum devices. We design an adder circuit based on Thomas G. Draper proposal. This circuit is a part of a general circuit to build Shor prime number factorization algorithm. We perform the experiments on three IBM quantum devices. The result of the experiment shows that on IBM Essex device, the best possible adder for one qubits has 100% accuracy. However, the results for two qubits adder circuit are much worse. The details analysis of the accuracy of three IBM devices are reported.
Cooking Event Detection from Temporal Thermal Condition of Residential Home

Contact-free activity detection is being used in several domains i.e., healthcare, cyber physical systems for its non-intrusive and flexible characteristics for end users. Thermal condition of residential homes are affected by both the outdoor weather conditions and the inside human activities. The activity of cooking affects the thermal comfort of residents inside the home and incurs a significant amount of electricity consumption in commercial kitchens. Though camera and body sensor based frameworks are proposed in the existing literature to detect cooking activities, contact free activity inference is necessary to non-intrusively assess the daily thermal comfort, monitor building envelope, electricity usage. In this work, we collected thermal condition of an apartment from surface temperature sensors and cooking activity of residents were recorded by visual observations. We avoided other activities i.e., opening doors or windows which can affect the thermal condition of residential home during cooking. We proposed a framework for cooking activity detection using recurrent neural network from surface temperature and humidity signals of residential homes. Our proposed algorithm achieves approximately 93% accuracy in cooking event detection from ambient building thermal condition.
colMOOC – an Innovative Conversational Agent Platform to Support MOOCs A Technical Evaluation

The main goal of this document is to describe the implementation of each component of the colMOOC platform and the integration stage of the operational platform as a whole. Additionally, a first simple operational scenario that has been implemented is also being described, in order to demonstrate the interoperability of the platform. Finally, this paper presents a positive technical assessment of the 1st version of colMOOC platform through performance benchmarking experiments performed on system's components in order to verify its correct operation and interoperability of the different integrated modules to meet the requirements of the use cases for the end users.
Using a Blend of Brassard and Benett 84 &amp; Elliptic Curve Digital Signature for Secure Cloud Data Communication

The exchange of data has expanded utilizing the web nowadays, but it is not dependable because, during communication on the cloud, any malicious client can alter or steal the information or misuse it. To provide security to the data during transmission is becoming hot research and quite challenging topic. In this work, our proposed algorithm enhances the security of the keys by increasing its complexity, so that it can't be guessed, breached or stolen by the third party and hence by this, the data will be concealed while sending between the users. The proposed algorithm also provides more security and authentication to the users during cloud communication, as compared to the previously existing algorithm.
Elaboration with first-class implicit function types

Implicit functions are dependently typed functions, such that arguments are provided (by default) by inference machinery instead of programmers of the surface language. Implicit functions in Agda are an archetypal example. In the Haskell language as implemented by the Glasgow Haskell Compiler (GHC), polymorphic types are another example. Implicit function types are first-class if they are treated as any other type in the surface language. This holds in Agda and partially holds in GHC. Inference and elaboration in the presence of first-class implicit functions poses a challenge; in the context of Haskell and ML-like languages, this has been dubbed “impredicative instantiation” or “impredicative inference”. We propose a new solution for elaborating first-class implicit functions, which is applicable to full dependent type theories and compares favorably to prior solutions in terms of power, generality and simplicity. We build atop Norell’s bidirectional elaboration algorithm for Agda, and we note that the key issue is incomplete information about insertions of implicit abstractions and applications. We make it possible to track and refine information related to such insertions, by adding a function type to a core Martin-L'of type theory, which supports strict (definitional) currying. This allows us to represent undetermined domain arities of implicit function types, and we can decide at any point during elaboration whether implicit abstractions should be inserted.
Natural Language Processing based Rule Based Discourse Analysis of Marathi Text

Indian languages are verb final and morphologically rich. For the present work Marathi language is explored which belongs to Indo Aryan family. The data is collected from the Marathi Balbharati book from standard 1st to 4th. This paper presents challenges of discourse analysis means two or more sentences are linked together which is required for many natural language based applications. Rule based structure is framed to find out the discourse from the dataset. These rules are framed on the basis of the Marathi grammar and world knowledge of the linguistic. With the help of POS tagger identify the tag of each word in the discourse is identified. The discourse anaphora is resolved in various foreign as well as Indian languages but Marathi is one of the languages where the discourse is not resolved uptil now. Discourse means that the some relative sentences or the sub sentences are connected with each-other. An important step in understanding the connected discourse is skill to link the meaning of the successive sentence together. Total 515 discourse sentences are considered here to resolving the anaphora from which 177 are the simple sentence and 338 are the discourse one.
Abstracting Faceted Execution

Faceted execution is a linguistic paradigm for dynamic information-flow control with the distinguishing feature that program values may be faceted. Such values represent multiple versions or facets at once, for different security labels. This enables policy-agnostic programming: a paradigm permitting expressive privacy policies to be declared, independent of program logic. Although faceted execution prevents information leakage at runtime, it does not guarantee the absence of failure due to policy violations. By contrast with static mechanisms (such as security type systems), dynamic information-flow control permits arbitrarily expressive and dynamic privacy policies but imposes significant runtime overhead and delays discovery of any possible violations. In this paper, we present the two different abstract interpretations for faceted execution in the presence of first-class policies. We first present an abstraction which allows one to reason statically about the shape of facets at each program point. This abstraction is useful for statically proving the absence of runtime errors and eliminating runtime checks related to facets. Reasoning statically about the contents of faceted values, however, is complicated by the presence of first-class security labels, especially because abstract labels may conflate more than one runtime label. To address these issues, we also develop a more precise abstraction that relies on an analysis tracking singleton heap abstractions. We present an implementation of our coarse abstraction in Racket and demonstrate its performance on several sample programs. We conclude by showing how our precise domain can be used to verify information-flow properties.
Research on pavement garbage detection based on machine vision

Abstract With the continuous advancement of China’s urbanization process and the continuous development of autonomous driving technology in recent years, it has become a trend to use unmanned garbage sweepers to clean up and maintain the road surface. Garbage detection is an important part of the operation process of unmanned garbage sweeping trucks. It replaces human brains in the process of observing, judging, and locating garbage on the road, which directly affects the efficiency of sweeping trucks. This paper takes Halcon software as the main platform to introduce the research of road garbage detection based on machine vision.
Upper Limbs Motion Tracking for Collaborative Robotic Applications

In the perspective of Industry 4.0, the contemporary presence of workers and robots in the same workspace requires the development of human motion prediction algorithms for a safe and efficient interaction. In this context, the purpose of the present study was to perform an operation of sensor fusion, by creating a collection of spatial and inertial variables of human upper limbs kinematics of typical industrial movements. Spatial and inertial data of ten healthy young subjects performing three pick and place gestures at different heights were measured with a stereophotogrammetric system and Inertial Measurement Units, respectively. Elbow and shoulder angles estimated from both instruments according to a multibody approach showed very similar trends. Moreover, two variables of the database were identified as distinctive features able to differentiate among the three gestures of pick and place.
No More Fear of Every Snake: Applying Chatbot-Based Learning System for Snake Knowledge Promotion Improvement : A Regional Snake Knowledge Learning System

The lack of snake knowledge not only makes humans easily fall into ophidiophobia, but also cause many snakes lose their lives. It is easy to encounter a snake in the countryside. It is necessary to identify whether it is a poisonous snake in the fastest time. In the city, although it is difficult to see the real snake, we have the need to understand the snake. In the future, if we could meet snakes in the mountains or villages, we can effectively activate the snake knowledge we have learned to avoid ourselves from dangerous situations. Based on the above reasons, this study considers a convenient, instant and interesting chatbot to assist the learning of snake knowledge. This study developed a Regional Snake Knowledge Learning System to assist in the promotion of snake-related knowledge, and effectively enhance learners' knowledge acquisition through the process. After the completion of the Snake Knowledge Learning System in this study, the effectiveness of this system on learner knowledge acquisition and memory retention results will be understood through the evaluation of the experimental group and the control group. In addition, this study also found that users have a high degree of satisfaction with the use of this system.
Language-Based Web Session Integrity

Session management is a fundamental component of web applications: despite the apparent simplicity, correctly implementing web sessions is extremely tricky, as witnessed by the large number of existing attacks. This motivated the design of formal methods to rigorously reason about web session security which, however, are not supported at present by suitable automated verification techniques. In this paper we introduce the first security type system that enforces session security on a core model of web applications, focusing in particular on server-side code. We showcase the expressiveness of our type system by analyzing the session management logic of HotCRP, Moodle, and phpMyAdmin, unveiling novel security flaws that have been acknowledged by software developers.
A New Authentication Approach for People with Upper Extremity Impairment

In recent years, people with upper extremity impairment (UEI) have been using wearable Internet of Things (wIoT) devices like head-mounted devices (HMDs) for a variety of purposes such as rehabilitation, assistive technology, and gaming. Often such wIoT devices collect and display sensitive information such as information related to medical care and rehabilitation. It is therefore crucial that HMDs can authenticate the person wearing them so that appropriate access control can be implemented for the sensitive information they manage. In this paper, we explore a new authentication approach for people with upper extremity impairment (UEI) for wIoT devices head-mounted devices (HMDs). The approach works by leveraging ballistocardiograms - representations of the cardiac rhythm - derived from an accelerometer and a gyroscope, mounted on an HMD for authentication. The derived ballistocardiograms are then fed into six participant-specific convolutional neural networks (CNNs) which act as our authentication models. Analysis of our approach shows its viability. Using data from 6 participants with UEI (and 22 able-bodied participants, for evaluation), we show that we can authenticate a participant in 4 seconds with an average equal error rate of 4.02% and 10.02%, immediately after training and ~2 months later, respectively.
Gamified Smart Objects for Museums Based on Automatically Generated Quizzes Exploting Linked Data

Museums have become through time the cultural conscience of nations by preserving cultural heritage. Although cultural heritage provides a valuable form of learning about mankind, the display of exhibits might not pique visitors' interest. In order to provide engaging and appealing experiences, museums have integrated a number of technologies in their environments. Particularly, there are promising results with the emerging Internet of Things (IoT) technology, enabling the implementation of smart objects to grant exhibits advanced capabilities. Gamification techniques are also commonly used in cultural heritage scenarios to further draw visitors' attention. On this sense, several museums offer for example interactive question-based games. However, these questions must be periodically renewed and such task is time-consuming given the lack of automation of this procedure.To address these challenges, this paper proposes a low-maintenance gamified smart object platform to automate the creation of questions about exhibits by exploiting semantic web technologies. The main contributions of this paper are: (i) the design of a gamified smart object platform for museums based on a trivia quiz app; (ii) the automation of question generation schemes for the proposed game; and (iii) the development of a prototype of the proposed platform in a real-life scenario.
Are We Creating Opportunities for Homeless Children to Succeed in the Digital Age?

As society becomes more dependent upon technological resources, to share information and provide education, it is imperative that we ensure inclusive information access and provide resources for digital literacy in order to decrease barriers to information for marginalized communities. This research focuses specifically on the digital literacy needs of homeless youth. The findings presented here will contribute knowledge to the public library sector and allow librarians to develop, improve, and promote digital literacy programming for homeless youth. As a result, public libraries will be better positioned to bridge the digital literacy divide that exists today and begin moving towards a greater level of equity.