Reviewerly/exHarmony huggingface dataset:
Wiki support for automated definition of software test cases

Purpose The design of tests is a very important step in the software development process because it allows us to match the users’ expectations with the finished product. Considered as a cumbersome activity, efforts have been made to automatize and alleviate the burden of test generation, but it is still a largely neglected step. The study aims to propose taking advantage of existing requirement artifacts, like scenarios that describe the dynamic of the domain in a very early stage of software development, to obtain tests from them. Design/methodology/approach In particular, the approach proposed complement the scenarios that are textually described with a glossary, the language extended lexicon. Thus, a set of rules to derive tests from scenarios is also proposed. The tests are then described using the task/method model. Findings The main findings of this study consist of an extension of a previously presented set of rules. And, a tool based on a media wiki platform that makes possible to record scenarios and the language extended lexicon and implement the rules to obtain the tests. Originality/value The main originality of this study is the glossary which complements scenarios, the semantic support to obtain tests and the tool to automatize the approach.
Virtual strategic positioning to create social presence: reporting on the use of a telepresence robot

This qualitative cross disciplinary research examined to what degree social presence was achieved through the use of a telepresence robot by one of the authors, in her capacity as a keynote speaker at an international research symposium. We explored if and how social presence was a factor in her ability to strategically position herself as a notable researcher whilst in ‘telepresence mode’, with the aim of understanding whether one could exercise the same degree of agency in telepresence mode as compared to appearing in person. We were also interested to know how those attending the symposium experienced having a tele present delegate in their midst. The research used an analytic framework based on Hassenzahl’s (2014) ideas of “experience design” and his des cription of the “user experience” and evaluated the tele present person’s ability to strategically position in a virtual environment by applying the analytical lens of Positioning Theory (Harre van Langenhove, 1999).Findings indicated it is possible to establish a high degree of social presence whilst in telepresence mode. This relates to both the telepresence robot product and the phenomenon of telepresence as experienced by the user and symposium attendees. However, while the user was able to position herself successfully all indicators were that social competencies also played a significant role in her being able to interact in telepresence mode. Attending international conferences using telepresence robots is potentially attractive for economic and ti me saving reasons, but little is understood about how delegates experience telepresence and whether conference attendance objectives can be achieved. We demonstrate how social presence is achieved both through the capabilities of the telepresence robot, bu t also through a combination of the amount of symbolic capital possessed by the user and the user’s social competencies. This has implications for decision making in terms of who is likely to be able to successfully operate in tele present mode at such events.
Towards Human-readable Smart Contracts

In the late 90s the author Ian Grigg defined that smart contracts have to be human-readable like paper contracts while remaining processible by computer programs. The Ethereum Foundation has created a new programming language Solidity that can be used to implement smart contracts. However, the contracts are neither easy to implement nor easy-to-use by the common user. In order to enable users without programming skills to take advantage of the new technology, we propose a generator for smart contracts. Our prototype uses a configuration wizard to determine the requirements of the generated contract. Based on the official ERC Standards of the Ethereum community we will implement a prototype that can configure and generate customized contracts. Moreover, we are covering the challenges that we have to face in order to support automated test case generation and automated deployment processes.
A Comprehensive Study of the Functions and Operations of Control Systems

A control system is used to achieve the required feedback by controlling the output.Control systems are widely used in everyday devices such as traffic lights and cars or even processes.These systems help in further understanding and improving the process that is being utilized.It also represents the process in a much more straightforward manner that makes it easier to comprehend.This paper aims to broaden the insight on control systems and to discuss different control systems that are being used.
Computing runs on a trie

A maximal repetition, or run, in a string, is a maximal periodic substring whose smallest period is at most half the length of the substring. In this paper, we consider runs that correspond to a path on a trie, or in other words, on a rooted edge-labeled tree where the endpoints of the path must be a descendant/ancestor of the other. For a trie with n edges, we show that the number of runs is less than n. We also show an O(n sqrt{log n}log log n) time and O(n) space algorithm for counting and finding the shallower endpoint of all runs. We further show an O(n log n) time and O(n) space algorithm for finding both endpoints of all runs. We also discuss how to improve the running time even more.
Convolutional-NN and Word Embedding for Making an Effective Product Recommendation Based on Enhanced Contextual Understanding of a Product Review

E-commerce is one of the most popular service applications in the world in the last decade. It has become a revolutionary model from traditional shopping transaction to entire internet commerce. E-commerce needs essential artificial intelligence (AI) to provide the customer with information about a product, called a recommendation machine. Collaborative filtering is a model of a recommendation algorithm that relies on rating as the fundamental calculation to make a recommendation. It has been successfully implemented in e-commerce. Even so, this model has a weakness in sparse product data in which the rating number is very low or sparse. Mostly, only less than 3% of the total user population rate a product, leading to the rise of sparse data. A text sentence document is a part of customers’ feedback that can be converted into a product rating. According to a traditional approach, bag of word and lexicon model are ignored in a contextual approach. This experiment, it developed a new model to increase the contextuality of text sentences, leading to a more effective rating prediction. We employed a kind of convolutional neural network to generate item latent factor vectors that could be incorporated with probabilistic matrix factorization to make rating prediction. Our method outperformed several previous works based on a metric evaluation using the Root Mean Squared Error (RMSE). In this experiment, we analyzed MovieLens and IMDB datasets, which contained a movie product review.
Using Structured Representation and Data: A Hybrid Model for Negation and Sentiment in Customer Service Conversations

Twitter customer service interactions have recently emerged as an effective platform to respond and engage with customers. In this work, we explore the role of ”negation” in customer service interactions, particularly applied to sentiment analysis. We define rules to identify true negation cues and scope more suited to conversational data than existing general review data. Using semantic knowledge and syntactic structure from constituency parse trees, we propose an algorithm for scope detection that performs comparable to state of the art BiLSTM. We further investigate the results of negation scope detection for the sentiment prediction task on customer service conversation data using both a traditional SVM and a Neural Network. We propose an antonym dictionary based method for negation applied to a combination CNN-LSTM for sentiment analysis. Experimental results show that the antonym-based method outperforms the previous lexicon-based and Neural Network methods.
Security, Trustworthiness and Effectivity Analysis of an Offline E-Cash System with Observers

In our previous paper we presented an offline e-cash system with observers.We have shown that the proposed system satisfies basic requirements for e-cash schemes.We also covered such security issues as chosen message attack resistance and forgery of protocols data.However, in that paper we focused more on the system itself, rather than its analysis.Hence, here we present cryptanalysis of our system.We aim to prove that existential forgery of data is not possible due to complexity of the discrete logarithm problem.Furthermore, we perform the analysis of trustworthiness of the system using the so-called BAN logic.Also, we consider effectivity of the proposed e-cash system in observers with limited computational resources.
Kritik Sastra Ekologis terhadap Novel-novel Terbaru Indonesia

Environmental literary works appear as a form of literary sensitivity to society and the environment which has specific environmental tendencies. Studies using the theory of ecological literature began in around 2008 and above with a very limited number. Therefore, the development of studies of literary works with this theory is very necessary. The creation of public opinion about the importance of protecting the environment to reduce the impact of global warming is very necessary. Later, through several novels, authors have done it. However, not all messages in the novel are clearly conveyed so that they still need ecological literary criticism to understand them. Based on this, the problem raised in this study is "What is the ecological literary criticism of Indonesia's latest novels?". Data collection and data analysis is done by descriptive and content analysis methods. Data are classified and analyzed with ecological literary concepts according to Garrard including (1) pollution; (2) wilderness; (3) disaster; (4) housing / residence; (5) animals; and (6) earth. The research findings and discussion show that Indonesia's latest novels are friendly with their environment, want to describe as much detail as possible about the universe, worship nature, and are always interested in natural changes. Ecological literary concepts are contained in Indonesia's latest novels to describe the natural situation as well as to criticize human treatment of nature. Indonesia's latest novels teach that an attitude of compassion for nature gives rise to desire and behavior to protect and preserve nature as well as possible.
Dealing with Uncertainty in Software Architecture on the Internet-of-Things with Digital Twins

When architecting Software-intensive Systems-of-Systems (SoS) on the Internet-of-Things (IoT), architects face two sorts of uncertainties. First, they have only limited knowledge about the operational environment where the SoS will actually be deployed. Second, the constituent systems which will compose the SoS might not be known a priori (at design-time) or their availability (at run-time) is affected by dynamic factors, due to the openness of the IoT. The consequent research question is thereby how to deal with uncertainty in the design of an SoS architecture on the IoT. To tackle this challenging issue, this paper addresses the notion of uncertainty due to partial information in SoS and proposes an enhanced SoS Architecture Description language (SosADL) for expressing SoS architectures on the IoT under uncertainty. The core SosADL is extended with concurrent constraints and the concept of digital twins coupling the physical and virtual worlds. This novel approach is supported by an integrated toolset, the SosADL Studio. Validation results demonstrate its effectiveness in an SoS architecture for platooning of self-driving vehicles.
Efektifitas Penerapan Perangkat Pembelajaran Fisika Dasar Berbasis Keterampilan Berpikir Kritis Menggunakan Aplikasi Edmodo Berplatform Android

The Effectiveness of the Application of Basic Physics Learning Devices Based on Critical Thinking Skills Using the Edmodo Platform on Android. The purpose of this study is to describe the effectiveness of the application of basic physics learning devices based on critical thinking skills using the Android platform Edmodo application. This research is a pre-experimental study with the research design used namely One Group Pretest Postest Design. The research subjects were 16 second semester students of the 2018 - 2019 academic year STKIP PGRI Mathematics Education Study Program Bangkalan subject matter of temperature and heat. The results of critical thinking skills at the pretest and posttest experienced a significant increase having N-Gain 0.6 in the moderate category. The results of the positive student responses to learning questionnaires were 86.4%. It can be concluded that the application of basic physics learning devices based on critical thinking skills using the android platform EDMODO application can improve students 'critical thinking skills and students' positive responses to learning so that they can be said to be effective.
ZQM at SemEval-2019 Task9: A Single Layer CNN Based on Pre-trained Model for Suggestion Mining

This paper describes our system that competed at SemEval 2019 Task 9 -SubTask A: "Suggestion Mining from Online Reviews and Forums".Our system fuses the convolutional neural network and the latest BERT model to conduct suggestion mining.In our system, the input of convolutional neural network is the embedding vectors which are drawn from the pre-trained BERT model.And to enhance the effectiveness of the whole system, the pretrained BERT model is fine-tuned by provided datasets before the procedure of embedding vectors extraction.Empirical results show the effectiveness of our model which obtained 9th position out of 34 teams with F1 score equals to 0.715.
Overlap analysis, usage statistics, and the evaluation of aggregator databases

In today’s landscape of electronic resources, there are myriad ways for a library to pursue e-resources. Single direct e-journal subscriptions, small journal packages, Big Deals, content aggregator...
Micro-expression recognition using optical flow and local binary patterns on three orthogonal planes

Micro-expression recognition attracts more and more attentions from computer vision due to its wide range of potential applications. This paper proposes an approach for micro-expression recognition, Local Optical Flow Binary Patterns on Three Orthogonal Planes (LOFBP-TOP), by combining optical flow and LBP-TOP. We first compute optical flow on cropped micro-expression videos, then we encode the magnitude and orientation component of optical flow with LBP-TOP to get LOFBP-TOP features. Furthermore, ReliefF is used to do feature selection on LOFBP-TOP features. Finally, SVM is used in classification. Experimental results on two datasets, CASME2 and SMIC, show that our method has better recognition performance than some popular methods in micro-expression recognition, such as LBP-TOP and HOOF.
Weakly-Supervised Network Alignment With Adversarial Learning

Network alignment, the task of seeking the hidden underlying correspondence between nodes across networks, has become increasingly studied as an important task to multiple network analysis.A few of the many recent applications of network alignment include protein network alignment, social network reconciliation, and computer vision.However, traditional methods which are based on matrix factorization directly work on networks themselves rather than exploit their intrinsic structural consistency, and thus their performance is sensitive to structural variations of networks.Recently, many supervised approaches which leverage latent representation have been proposed.Although they can handle large-scale datasets, most of them rely on a large number of parallel anchor links which are unavailable or expensive to obtain for many domains.Therefore, in this paper, we propose the WENA Framework, a representation learningbased network alignment, in which we study how to design weakly-supervised methods to align large-scale networks with a limit of ground truth available.Empirical results show that, with only two anchor links, WENA significantly outperforms existing unsupervised aligners and even outperforms state-of-the-art supervised methods that use richer resources in terms of both noise robustness and accuracy.
Exploration of Physiological Signals Using Different Locomotion Techniques in a VR Adventure Game

In the past few years, Virtual reality gained popularity thanks to advancing technology. Although the consumer head-mounted displays provide affordable access to immersive virtual environments, one of the disadvantages is the induced discomfort during or after exposure, called simulation sickness. Simulation sickness is a condition of physiological discomfort felt during or after exposure to any virtual environment. One of the possible factors inducing simulation sickness could be locomotion, the travel of the user through the virtual space from one point to another. The study presented in this paper aims to expand the knowledge on how the human body responds to different locomotion techniques in a virtual reality environment. A within-subjects design (n = 9) was conducted to explore simulation sickness outbreak, sense of presence and physiological responses induced by free teleportation and indirect locomotion in a virtual reality adventure game. The results showed that participants experienced significantly less simulation sickness while using the free teleportation during the game when compared to indirect locomotion. These findings indicate that simulation sickness symptoms can be reduced using free teleportation in a virtual reality adventure game.
DESIGNING A SECURE BLOCKCHAIN-BASED TRADING PLATFORM FOR INTERNET OF THINGS

Blockchain, a distributed database technology attracts intensive attention recently. It was first described in 1991 by Stuart Haber and W. Scott Stornetta, in order to prevent tampering for document timestamps. After that, Satoshi Nakamoto conceptualized this technology with his work, a peer-to-peer electronic cash system named as Bitcoin. Due to its authenticity, user anonymity and data immutability; this technology has also been applied to different areas ranging from finance, supply-chain managements to social services. In this paper, we propose a blockchain based application for trading data, collected from IoT devices. Our application enables the sellers to commercialize their data in exchange of the currency produced by the application. The application also utilizes smart contracts to establish trust between both sides of the exchange. Furthermore, we discuss the security and reliability of the system components
A Survey on Cloud Computing Risks and Remedies

Cloud computing is sharing of enormous resource with a billing plan creating ease and providing solution for IT needs to a business of any size.Growth of public cloud has contributed widely in making cloud a household name in the field of software use ,creation, deployment or even management but at the same time securing the cloud is most important responsibility of cloud provider to build trust in the customers.This paper talks about most common threats and the strategies to deal with the risks.
A Privacy-Preserving Multi-keyword Ranked Search over Encrypted Data in Hybrid Clouds

Due to the convenience, economy and high scalability of cloud computing, more and more individuals and enterprises are motivated to outsource their data or computing to clouds. In this paper, we propose a privacy-preserving multi-keyword ranked search over encrypted data in hybrid cloud, which is denoted as MRSE-HC. The keyword partition vector model is presented. The keyword dictionary of documents is clustered into balanced partitions by a bisecting k-means clustering based keyword partition algorithm. In accordance with the partitions, the keyword partition based bit vectors are defined for documents and queries which are utilized as the index of searches. The private cloud filters out the candidate documents by the keyword partition based bit vectors, and then the public cloud uses the trapdoor to determine the result in the candidates. The security analysis and performance evaluation show that MRSE-HC is a privacy-preserving multi-keyword ranked search scheme for hybrid clouds and outperforms the existing scheme FMRS in terms of search efficiency.
The Feasibility of Implementing Augmented Reality Technology for Delivering Library Services: A Case Study at the University of Bahrain

Engaging new mobile technology tools, which deliver information and knowledge, become part of our daily life.One of these tools is Augmented Reality (AR), a technology that blends the real world with computer-generated media.Through in-depth analysis, this study investigated the researchers' (academics and students) behavioral intention to use mobile AR technology to access special library services: current awareness service (CAS) and selective dissemination of information service (SDI), provided by University of Bahrain (UOB) library as an example.Technology Acceptance Model (TAM) was used and focused on Perceived Ease of Use and Perceived Usefulness together with Attitude toward using and Behavioral Intention to use new technologies, together with Perceived Behavioral Control to test the factors of using AR technology in accessing UOB library services.A questionnaire was distributed to collect data from targeted sample researchers.Findings revealed that AR technology was accepted by UOB library users in receiving through their mobile an instant and frequent information of the two important tested library services.Results showed that perceived usefulness, perceived behavioral control and attitude toward using AR technology had positive significant effects on the researcher's intention to receive library service using AR technology.
Proof-of-work blockchains and settlement finality: a functional interpretation

In this paper, we aim to provide an interpretation of the legal issue of settlement finality in the context of proof-of-work distributed ledger technology, such as the Bitcoin network. Bitcoin intends to achieve certainty of settlement of its cryptocurrency in a trustless environment, without the need for intermediaries and without recourse to any legal provision. We extend earlier work on functional modeling of the theoretical settlement problem to include blockchains, and we provide a functional interpretation of settlement finality by introducing the notion of degree of settlement finality. In principle, we conclude that functional settlement finality in Bitcoin is preferred to legal enforceability. However, in practice, the Bitcoin blockchain is not suitable for the trusted environment of the regulated financial industry unless well-known issues – such as high energy consumption, low settlement speed, problems with scalability and the 51% attack risk – are resolved.