Reviewerly/exHarmony huggingface dataset:
Towards a Toolbox for the Development of Intercultural User Interfaces

In this paper, a method-mix (cultural dimensions, intercultural variables, user interface characteristics and human machine interaction (HMI) dimensions) for intercultural user interface design (IUID) is explained and discussed based on application examples. These examples elucidate why and how cultural aspects play a role in HMI design and usability/UX engineering. Implications for the consideration of variables such as speed and frequency of information/interaction for dialogue design in the cultural context are also added. The readers are sensitized to the challenges of intercultural usability/UX engineering and intercultural HMI design and will be equipped with methodological knowledge relevant to the derivation of design recommendations for user interface design for and in their desired cultural contexts.
Global path and action planning for mobile robot using a spatiotemporal graph in environments with predictable moving obstacles

Global path planning is often used for initial path planning, as it allows robots to search for the feasible paths. However, it is very difficult to perform global path planning in a dynamic environment because it is hard to predict the behavior of moving obstacles. In this paper, we propose a method to perform a global path plan by using a spatiotemporal graph for environments with moving obstacles that perform predictable behavior. We provide a waiting path in a spatiotemporal graph and setting the waiting cost on it. Then, we show that it is possible to adjust the robot's behavior by using A* algorithm from the balance of moving cost and waiting cost. We also show that the global path from the current position to the goal position can be easily updated by using a spatiotemporal graph, even when moving obstacles change from the scheduled behavior. In order to validate the effectiveness of the proposed method, we apply it for return-path planning of an autonomous tour guide robot in a virtual museum. Finally, we show the simulation results and discuss the applicability of the proposed method in a dynamic environment.
Lithogeochemistry of Intrusive Rocks in the Halo Porphyry Copper-Molybdenum Prospect, Northeast Cambodia

The Halo copper-molybdenum prospect is a porphyry system in Ratanakiri province, northeastern part of Cambodia.There is only one research was carried out on this prospect about geological mapping and short wave infrared (SWIR) spectroscopy on alteration mineral identification.The purpose of this research is to confirm the deposit type from previous Angkor Gold's report and find the centre of porphyry deposit based on characteristic of intrusive rocks at surface and subsurface, characteristics of the intrusive rocks and alteration lithogeochemistry of intrusive and volcanic rocks by using Pearce Element Ratio (PER) analysis.PER analysis was used to examine the nature and extend of the alteration halos in the porphyry Halo copper-molybdenum prospect.The intrusive rocks and volcanic rocks in Halo, range from diorite to granite (quartz feldspar porphyry) in composition as well as dacite to trachyandesite (andesite porphyry) in composition, respectively.They were formed in a subduction-related tectonic setting, likely a volcanic arc.Trace elements spider diagrams were normalized to primitive mantle display strong enrichment in large-ion lithophile elements such as Rb, Ba and K and depletion in some high-field strength elements such as Nb and Ti, suggesting magmas generated in a subduction-related tectonic setting.PER analysis indicates a moderate to high degree of sericite alteration of dacites, quartz feldspar porphyries, andesite porphyries and granodiorite porphyries.Moreover, three alterations in the Halo prospect such as potassic (secondary K-feldspar and biotite), phyllic (sericite) and propylitic (epidote) alteration were identified, which are consistent with petrography analysis.The
No-reference Image Denoising Quality Assessment

A wide variety of image denoising methods are available now. However, the performance of a denoising algorithm often depends on individual input noisy images as well as its parameter setting. In this paper, we present a no-reference image denoising quality assessment method that can be used to select for an input noisy image the right denoising algorithm with the optimal parameter setting. This is a challenging task as no ground truth is available. This paper presents a data-driven approach to learn to predict image denoising quality. Our method is based on the observation that while individual existing quality metrics and denoising models alone cannot robustly rank denoising results, they often complement each other. We accordingly design denoising quality features based on these existing metrics and models and then use Random Forests Regression to aggregate them into a more powerful unified metric. Our experiments on images with various types and levels of noise show that our no-reference denoising quality assessment method significantly outperforms the state-of-the-art quality metrics. This paper also provides a method that leverages our quality assessment method to automatically tune the parameter settings of a denoising algorithm for an input noisy image to produce an optimal denoising result.
Updating Argumentation Frameworks for Enforcing Extensions

There are mainly two research directions for the dynamic of argumentation: revision and enforcement. The former studies how the semantics of an argumentation framework changes when the framework is updated, while the later studies how to enforce a given status of arguments by updating the argumentation framework. In the second direction, little attention has been paid to the problem of providing general rules for updating an argumentation framework aiming to enforce an extension of arguments. In this paper, we address this problem by a notion of characterizing the updated argumentation framework with respect to a given set of arguments.
Towards Visual Data Science - An Exploration

Visual perception is one of the most essential abilities for humans. This ability allows us to discover the world around us and to understand interdependencies with regard to both global context and particular concrete problem statement. We present in this paper an exploration of visualization and visual analytics approaches. Thereby, we focus on the field of data science with data-centric analytic methods and applications. Data science is closing the gap between visualization techniques, traditional hypothesis-driven methods and processing of mostly huge, heterogeneous and noisy data. A combination of smart visualization, advanced analytical methods and additional (domain) knowledge, mostly provided by humans, makes it possible to gain insights and discover new opportunities for problem solving.
Space-Efficient Latent Contracts

Standard higher-order contract monitoring breaks tail recursion and leads to space leaks that can change a program’s asymptotic complexity; space-efficiency restores tail recursion and bounds the amount of space used by contracts. Space-efficient contract monitoring for contracts enforcing simple type disciplines (a/k/a gradual typing) is well studied. Prior work establishes a space-efficient semantics for manifest contracts without dependency [10]; we adapt that work to a latent calculus with dependency. We guarantee space efficiency when no dependency is used; we cannot generally guarantee space efficiency when dependency is used, but instead offer a framework for making such programs space efficient on a case-by-case basis.
Detection of Click Spamming in Mobile Advertising

Most of the marketing expenditures in mobile advertising are conducted through real-time bidding (RTB) marketplaces, in which ad spaces of the sellers (publishers) are auctioned for the impression of the buyers’ (advertisers) mobile apps. One of the most popular pricing models in RTB marketplaces is cost-per-install (CPI). In a CPI campaign, publishers place mobile ads of the highest bidders in their mobile apps and are paid by advertisers only if the advertised app is installed by a user. CPI pricing model causes some publishers to conduct an infamous fraudulent activity, known as click spamming. A click spamming publisher executes clicks for lots of users who have not authentically made them. If one of these users hears about the advertised app organically (say, via TV commercial) afterwards and installs it, this install will be attributed to the click spamming publisher. In this study, we propose a novel multiple testing procedure which can identify click spamming activities using the data of click-to-install time (CTIT), the time difference between the click of a mobile app’s ad and the first launch of the app after the install. We statistically show that our procedure has a false-positive error rate of 5% in the worst case. Finally, we run an experiment with 30 publishers, half of which are fraudulent. According to the results of the experiment, all non-fraudulent publishers are correctly identified and 73% of the fraudulent publishers are successfully detected.
Probabilistic Modeling of Failure

Failure of a system or a component of a system is and has been a major concern to systems’ operators and owners. Failure could be traced back to different causes and may take different forms and shapes. It may result from software malfunction, hardware degraded performance, human error, sabotage, environmental as well as other external factors. There are various techniques found in the literature that can assist in the analysis of failure. These techniques comprise deterministic and probabilistic techniques. Deterministic techniques ignore the variability and uncertainties of the variables in the analysis which may lead to unsatisfactory and inaccurate results. While probabilistic techniques produce accurate and an all-inclusive result because they incorporate the variabilities and uncertainties in the analysis. The focus of this chapter is to present commonly used probabilistic failure analysis techniques and their mathematical derivations. Examples to enhance the understanding of the concept of failure analysis are also presented.
Universal fault-tolerant quantum computation using fault-tolerant conversion schemes

Abstract In this paper, we present the fault-tolerant conversion between quantum Reed–Muller (QRM)(2, 5) and QRM(2, 7), and also the conversion between QBCH(15, 7) and QRM(2, 7). Either of the two schemes provides a method to realize universal fault-tolerant quantum computation. In particular, the gate overhead and logical error rate of a logical T gate are provided, as well as the comparison with magic state distillation scheme. In addition, we propose two other fault-tolerant conversion schemes based on <?CDATA $({\boldsymbol{u}}| {\boldsymbol{u}}+{\boldsymbol{v}})$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo stretchy="false">(</mml:mo> <mml:mi mathvariant="bold-italic">u</mml:mi> <mml:mo stretchy="false">∣</mml:mo> <mml:mi mathvariant="bold-italic">u</mml:mi> <mml:mo>+</mml:mo> <mml:mi mathvariant="bold-italic">v</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:math> and <?CDATA $({\boldsymbol{a}}+{\boldsymbol{x}}| {\boldsymbol{b}}+{\boldsymbol{x}}| {\boldsymbol{a}}+{\boldsymbol{b}}-{\boldsymbol{x}})$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo stretchy="false">(</mml:mo> <mml:mi mathvariant="bold-italic">a</mml:mi> <mml:mo>+</mml:mo> <mml:mi mathvariant="bold-italic">x</mml:mi> <mml:mo stretchy="false">∣</mml:mo> <mml:mi mathvariant="bold-italic">b</mml:mi> <mml:mo>+</mml:mo> <mml:mi mathvariant="bold-italic">x</mml:mi> <mml:mo stretchy="false">∣</mml:mo> <mml:mi mathvariant="bold-italic">a</mml:mi> <mml:mo>+</mml:mo> <mml:mi mathvariant="bold-italic">b</mml:mi> <mml:mo>−</mml:mo> <mml:mi mathvariant="bold-italic">x</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:math> constructions.
Studying forward looking bubbles in Bitcoin/USD exchange rates

Although Bitcoin is a relatively new subject in Economics, contributions in this topic are growing very fast. Several papers evidenced a bubble behaviour in exchange rates between Bitcoin and traditional currencies. In this paper we explore and give validation to such conjecture, proving also that the bubble effect is due to confidence in Bitcoin future values. This means that Bitcoin price/exchange rate is influenced both by future and past events, but that the bubble behaviour is strictly connected to trust on the future of the Bitcoin system.
Optimal prefix codes with fewer distinct codeword lengths are faster to construct

A new method for constructing minimum-redundancy binary prefix codes is described. Our method does not explicitly build a Huffman tree; instead it uses a property of optimal prefix codes to compute the codeword lengths corresponding to the input weights. Let n be the number of weights and k be the number of distinct codeword lengths as produced by the algorithm for the optimal code. The running time of our algorithm is O(k⋅n). Following our previous work, no algorithm can possibly construct optimal prefix codes in o(k⋅n) time. If the given weights are presorted, our algorithm performs O(9k⋅log2k⁡n) comparisons.
Agro Guardian

The mechanization of the process creates agriculture-based jobs for farmers, providing financial support and facilitating affordable agriculture equipment and machineries. Fruits markets are subject of opportunity and it is important to the suppliers to identify the quality of fruits based on the ripeness level of fruits before selling out in order to get higher level of profit. The proposed framework is an Android application in native language of the farmer to help the jobless farmers to find agriculture-based jobs suitable to their skill set and receive investments from various investors across the country. Further, it finds investment for the needy farmers and create suitable agricultural employment for jobless farmers so that there is an increase in the progress in the field of agriculture. It also facilitates the farmers with advanced equipment for performing various agricultural tasks, obtains the land on lease, and determines various stages of ripeness of fruit and provides the information about the government project and funding facilities.
Using Dynamic Real-Time Haptic Mediation in VR and AR Environments

As VR, and AR become more popular forms of interaction with standalone and wearable computing systems, there is an inherent need to redefine the role of haptics in virtual environments. Complex virtual environments require more comprehensive tactile information. For this reason, primitive tactile signals currently being used in most commercial systems, need to give way to more precisely calibrated actuation, which is specifically designed for various applications. In this research we have extended the “Haptic Mediation” concept to test and improve haptic actuation for virtual interaction by developing a Dynamic Self-sensing and Actuation Architecture (DSAA) using Autonomous Haptic Devices (AHD). We have developed autonomous mobile versions of small haptic devices with embedded actuators, sensors, power sources as well as a radio communication channel (transceiver). These haptic devices can be attached to any part of the body to perform sensing and actuation. Our testing shows that this approach can improve users’ overall experience in VR games and that AHDs can create reliable, perceivable actuation signals even when the user is actively moving around.
Non-deterministic Behavior of Ranking-Based Metrics When Evaluating Embeddings

Embedding data into vector spaces is a very popular strategy of pattern recognition methods. When distances between embeddings are quantized, performance metrics become ambiguous. In this paper, we present an analysis of the ambiguity quantized distances introduce and provide bounds on the effect. We demonstrate that it can have a measurable effect in empirical data in state-of-the-art systems. We also approach the phenomenon from a computer security perspective and demonstrate how someone being evaluated by a third party can exploit this ambiguity and greatly outperform a random predictor without even access to the input data. We also suggest a simple solution making the performance metrics, which rely on ranking, totally deterministic and impervious to such exploits.
Categorization for the Security Awareness Domain and Resource (SADAR) Model in the Organization: A Clustering Statistical Analysis

Abstract Employee in the organization or customer from company can significantly affect the overall strength of security of the system as the human factor become the common problem that lead to damage or disaster. Unfortunately, most security solutions offered in the market do not consider user as a critical security element. In this study, it is proposed to evaluate the awareness of the user regarding information security problems from three type of antecedents, which are individual, institutional and environmental. In order to collect data, questionnaires have been sent to the users using systematic sampling based on the domain of pattern concern on the role of responsibility. The cluster analysis method was applied to sample of users in categories related to the various items represented in the type of antecedents. It has objective to place a set of object in such a way that have tendency to be similar to each other in one group and tend to be differ in the opposite group. Then, the development of SADAR emphasized four groups namely define, devote, discover and direct.
Blockchain in Commercial Insurance: Achieving and Learning Towards Insurance That Keeps Pace in a Digitally Transformed Business Landscape

» Insurance is a fundamentally important institution for lowering uncertainty between two parties so that they can exchange value. As such, it is a suitable target for disruption by a technological means of managing risk and minimizing complexity.» Most industries hesitate to blow up their own business models. Decentralized insurance (e.g., social insurance) would do just that—disintermediate many of the functions of the classic insurance company—and so the industry itself will not likely start there. Nor do we foresee blockchain disruption of traditional insurance products.» The commercial insurance sector is ideal for blockchain disruption because it has evolved to underwrite risk in a decentralized way, so as to avoid moral hazard. Its key systems (e.g., claims processing and insurance fraud detection) are already distributed. There is no incumbent system of intermediaries to displace. In the insurance industry’s risk-averse culture, blockchain pioneers would be wise to avoid exotic niche products and focus on use cases that employ blockchain among permissioned partners to gain efficiencies in back-end business processes, such as those in business-to-business property and casualty insurance.» There are blockchain use cases throughout the insurance process flow: in contracting (Maersk’s Insurwave), facility operations management (Willis Re’s shared network state), financial accounting (AIG and Standard Charter’s master policy pilot), claims agreement processing (Suncorp and ANZ bank’s shared network state), payments and treasury management (Allianz’s internal token pilot), and statutory/regulatory reporting (AAIS’ Open Insurance Data Link).» More forward-looking initiatives such as Sweetbridge and Mattereum are insuring the risks inherent in using such blockchain technologies as digital wallets, tokenized assets, and smart contracts. These risk are not yet well understood.As per Blockchain Research Institute policy, this paper is made available in the public domain six months after publication date
An Evaluation Of A Linguistically Motivated Conversational Software Agent Framework

&lt;p&gt;This paper presents a critical evaluation framework for a linguistically motivated conversational software agent (CSA). The CSA prototype investigates the integration, intersection and interface of the language, knowledge, and speech act constructions (SAC) based on a grammatical object, and the sub-model of belief, desires and intention (BDI) and dialogue management (DM) for natural language processing (NLP). A long-standing issue within NLP CSA systems is refining the accuracy of interpretation to provide realistic dialogue to support human-to-computer communication. This prototype constitutes three phase models: (1) a linguistic model based on a functional linguistic theory – Role and Reference Grammar (RRG), (2) an Agent Cognitive Model with two inner models: (a) a knowledge representation model, (b) a planning model underpinned by BDI concepts, intentionality and rational interaction, and (3) a dialogue model. The evaluation strategy for this Java-based prototype is multi-approach driven by grammatical testing (English language utterances), software engineering and agent practice. A set of evaluation criteria are grouped per phase model, and the testing framework aims to test the interface, intersection and integration of all phase models. The empirical evaluations demonstrate that the CSA is a proof-of-concept, demonstrating RRG’s fitness for purpose for describing, and explaining phenomena, language processing and knowledge, and computational adequacy. Contrastingly, evaluations identify the complexity of lower level computational mappings of NL – agent to ontology with semantic gaps, and further addressed by a lexical bridging solution.&lt;/p&gt;
Reed–Solomon Codes over Fields of Characteristic Zero

We study Reed-Solomon codes over arbitrary fields, inspired by several recent papers dealing with Gabidulin codes over fields of characteristic zero. Over the field of rational numbers, we derive bounds on the coefficient growth during encoding and the bit complexity of decoding, which is polynomial in the code length and in the bit width of error and codeword values. The results can be generalized to arbitrary number fields.
A Secure Hybrid RSA (SHRSA)-based Lightweight and Efficient Personal Messaging Communication Protocol

Balancing efficiency, privacy, and security along with strong authentication in the End-to-End (E2E) communication is a burning issue in personal messaging. Rivest–Shamir–Adleman (RSA) algorithm is an omnipresent cryptographic approach, so here we have implemented a Secure Hybrid RSA (SHRSA)-based lightweight and efficient personal messaging communication protocol for E2E secure, authenticated, and efficient messaging. The SHRSA decryption is much more secure and efficient than RSA and Chinese Remainder Theorem (CRT)-RSA. It is protecting the messaging scheme users with a perfect privacy. The SHRSA cipher's communication protocol is resolving many RSA-related issues. Full mesh networked personal messaging communication protocol ensures E2E encryption for all peers. The testing results of the personal messaging communication protocol have proved that this protocol is an efficient and secure personal messaging communication protocol. Also, it occupies very less memory and very less CPU than RSA and CRT-RSA. So high security, decryption efficiency with less memory and less CPU occupancy features make this secure message communication protocol much relevant to the era of Internet of Everything (IoE). Also, it is relevant to other secure and authentic message communications.