Reviewerly/exHarmony huggingface dataset:
A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms

This paper proposes a generative model for discovering user roles and community role compositions in Community Question Answering (CQA) platforms. While past research shows that participants play different roles in online communities, automatically discovering these roles and providing a summary of user behavior that is readily interpretable remains an important challenge. Furthermore, there has been relatively little insight into the distribution of these roles between communities. Does a community’s composition over user roles vary as a function of topic? How does it relate to the health of the underlying community? Does role composition evolve over time? The generative model proposed in this paper, the mixture of Dirichlet-multinomial mixtures (MDMM) behavior model can (1) automatically discover interpetable user roles (as probability distributions over atomic actions) directly from log data, and (2) uncover community-level role compositions to facilitate such cross-community studies.&#x0D; A comprehensive experiment on all 161 non-meta communities on the StackExchange CQA platform demonstrates that our model can be useful for a wide variety of behavioral studies, and we highlight three empirical insights. First, we show interesting distinctions in question-asking behavior on StackExchange (where two distinct types of askers can be identified) and answering behavior (where two distinct roles surrounding answers emerge). Second, we find statistically significant differences in behavior compositions across topical groups of communities on StackExchange, and that those groups that have statistically significant differences in health metrics also have statistically significant differences in behavior compositions, suggesting a relationship between behavior composition and health. Finally, we show that the MDMM behavior model can be used to demonstrate similar but distinct evolutionary patterns between topical groups.
Construction of the English Teaching Model Based on the Interactive Network Streaming Media

There are limitations in the time, regions and contents in the traditional English teaching, and there are some limitations in the traditional multimedia network teaching. The design of the English teaching mode based on the interactive network streaming media has brought a profound change to the English teaching. As the interactive network streaming media provides a good platform for people's communication, the role of teachers in the English teaching based on the interactive network streaming media is no longer the "leader" of the teaching, but the "guide" of the teaching. Teachers provide the hardware conditions, the learning resources and the communication objects. Students can choose their own way of learning. When they encounter problems, they can consult their teachers or their friends through the network streaming media platform.
Phonological Fossilisation of EFL Learners: The Interference of Phonological and Orthographic System of L1 Javanese

This paper discusses the interference of phonological and orthographic systems of the mother tongue on phonological fossilisation of English on Foreign Language learners in Javanese contexts. 25 fourth-semester university students were selected as respondents. The data were collected by means of pre-test and post-test on pronouncing isolated words, continuous speeches, and reading aloud on manipulated short text. Contrastive analysis reveals that the phonological fossilisation among Javanese students commonly occurred in continuous speech rather than isolated words when they pronounced vowels /æ/, /ɪ/, /ə/, /ʌ/, /i:/ in initial and middle position; diphthongs /əʊ/, /eɪ/, /aʊ/ in initial and middle; as well as consonants /dʒ/, /ʧ/, /θ/, /ð/, /ʃ/, /v/, /ʒ/, /z/, /k/, /t/ in initial, middle and final ones. The students tended to omit ‘/θ/’,‘/d/ and /t/’in final position, ‘consonant clusters in initial, mid, final position’, and /j/ after plosive bilabial’. Those phonological fossilisations were due to the interference of the phonological and orthographic systems of their mother tongue. Keywords : EFL learners; interference; fossilisation; phonological system; orthographic system
Reading Attitude and Its Influence on Students’ Reading Comprehension

This paper investigated the level of the students’ reading attitude and examined its influence on their reading comprehension in undergradute program of English Education Muhammadiyah Purworejo University. Sixty two students participated in the study. Two types of instruments were used to collect the data, namely reading attitude questionnaire and reading test. The questionnaire is in Likert-scale type with five responses in term of agreement with the score starts from 5 – 1. The reading test consists of 40 of multiple-choice type items assessing the students reading skills. Descriptive and inferensial statistics were used to analyze the data, including testing the linearity as the assumption of one set data. For doing the analyses, SPSS version 22 was used. The finding showed that the students’ reading attitude was high as the mean was 78.66 while, the reading comprehension is sufficient as the mean was 64.02. Reading attitude had significant correlation toward reading comprehension as the r-value was 0.568. In addition, reading attitude had positive and significant influence on students’ reading comprehension as the R-square= 0.322 with sig. 0.000. Reading attitude influenced reading comprehension as much as 32.2%, while 67.8% was influenced by other factors.
Development of an Expert System-Oriented Service Support Help Desk Management System

With the recent advancements of artificial intelligence, automation has been making its way into various systems that previously could only be operated by humans. Hence, these systems are getting more autonomous and taking control off from the human operators gradually. On the other hand, service centers are found to be subunits of almost all companies. However, a process at such service centers becomes slower and inefficient once the center is completely operated by humans. On the contrary, considering the functionalities of the center, complete automation is not either effective in certain centers. This triggers the necessity of a semi-automated center where a framework for such service center is proposed in this paper. While analyzing, it has been observed that the performance of the existing system is heavily hampered due to the absence of dynamicity. Therefore, the proposed framework attempts to make the center dynamic by introducing certain automated behaviors. The proposed system discussed in this paper comprises of all features in that are present in the current system but in an automated way. Furthermore, the proposed system extends the functionalities of a service center that could not be achieved by humans only. The proposed system also incorporates AI to a part of it making it semi-AI driven. A further description is also given in this paper of what needs to be done in order to accomplish a completely AI-driven system.
A Classification Method of Photos in a Tourism Website by Color Analysis

The number of Foreign Independent Tour (FIT) is increasing in the world. This research aims to develop a personal adaptive tourism recommendation system (PATRS) for FIT. This paper describes the concept of PATRS and related researches. In order to develop the PATRS, an easy feature extraction method from a tourism website is required. The classification of photos of tourism spots is an important technology to realize the feature extraction from numerous information in the website. This paper proposes a classification method of photos in a major tourism website by color analysis. From the results on the experiments, we confirmed that the photos in a tourism website can be classified into four classes by the proposed method.
Searching Long Repeats in Streams

We consider two well-known related problems: Longest Repeated Substring (LRS) and Longest Repeated Reversed Substring (LRRS). Their streaming versions cannot be solved exactly; we show that only approximate solutions by Monte Carlo algorithms are possible, and prove a lower bound on consumed memory. For both problems, we present purely linear-time Monte Carlo algorithms working in O(E + n/E) space, where E is the additive approximation error. Within the same space bounds, we then present nearly real-time solutions, which require O(log n) time per symbol and O(n + n/E log n) time overall. The working space exactly matches the lower bound whenever E=O(n^{0.5}) and the size of the alphabet is Omega(n^{0.01}).
Language Proficiency and Smartphone‑aided Second Language Learning: A look at English, German, Swahili, Hausa and Zulu

Use and development of applications for smartphones (so‑called ‘apps’) continue to rise, and it comes as no surprise that language learning apps (such as Google Translate) are immensely popular among the younger generation. But, do these apps actual help students learn a language and, if so, how is apps usage influenced by the proficiency of the language learner? Our research focused on the use of apps related to language learning in two major Korean universities. Koreans are known to be high‑tech users and avid language learners, and Korea can therefore provide a good model for how education and technology intersect. We asked students studying German, Swahili, Hausa, and Zulu to inform us about the role that smartphone apps play in their language learning, both at home and in a formal education setting (e.g., classroom). Results showed that one important determiner for how apps were used was language proficiency. We further found an interaction effect between proficiency in English and the other languages, which directly impacted app use. Our findings suggest that these rather sophisticated digital and language learning students make sophisticated choices of apps based on knowledge of apps and the language learning task at hand.
Design of Multi-Purpose Heavy-duty Scanning Robot with Spray Mechanism

A mini multi-purpose heavy-duty scanner robot was designed and built for the purpose of scanning open fields that can be used in different applications such as metal detection, mine detection and similar sensing activities.It can also be used in other agricultural purposes such as seed planting in small farms, fertilizer and pesticides spray and by adding some electronic mechanisms, it can also be used in fruit harvesting and the like.The scanner robot uses a DFRobot Mega 2560 microcontroller that can operate in an autonomous mode and in manual mode using Zigbee as the communications interface between the controller and the robot.This robot also has a GPS tracking system and obstacle avoidance features that makes it very efficient in its intended activity.Experiment results show the capabilities and effectiveness of the robot functionalities.This robot design, when upgraded to full size version, can be used as a model in remote activities in the field of agriculture, military and other commercial purposes.
Beijing Internet Court denies copyright to works created solely by artificial intelligence

Abstract Beijing Feilin Law Firm v Baidu Corporation, No 239 [2019], Civil First Instance, Beijing Internet Court, 25 April 2019
Sentiment Independent Topic Detection in Rated Hospital Reviews

We present a simple method to find topics in user reviews that accompany ratings for products or services.Standard topic analysis will perform sub-optimal on such data since the word distributions in the documents are not only determined by the topics but by the sentiment as well.We reduce the influence of the sentiment on the topic selection by adding two explicit topics, representing positive and negative sentiment.We evaluate the proposed method on a set of over 15,000 hospital reviews.We show that the proposed method, Latent Semantic Analysis with explicit word features, finds topics with a much smaller bias for sentiments than other similar methods.
A self-switching multi-strategic pedagogical agent

Multi-Strategic Pedagogical Systems (MSPSs) integrate multiple Pedagogical Strategies (PSs) and a Switching Logic (SL). They trigger the PS appropriate regarding the Student State (StS). However, the hard-coding and the monolithic integration of multiple PSs and a SL highly increase the complexity of the MSPSs. To overcome this deficiency, we recourse to the Self-* and the Component-Based Agents design approaches to engineer a Self-Switching Multi-Strategic Pedagogical Agent (Self-S MSPA). It is designed as two distinct interacting Manager (MrSS) and Managed (MdSS) Sub-Systems. The MdSS implements the PSs. The MrSS implements the SL in the form of an Autonomic Control Loop (ACL) to (re)configure the MdSS. To experiment the usefulness of the proposed model, a framework is constructed using SAFRAN.
Testability Increasing Method by Introducing Hardware Redundancy in the Easy-tested Finite State Machines

Testability increasing methods by introducing hardware redundancy into the circuit implementation are sufficiently developed and widely used in the design.Since the construction of the testing sequence is based on the use of automaton diagrams, it eliminates the need to analyze the circuit implementation of the remote control when building a diagnostic experiment.This approach allows us to extend the class of detectable faults, which in structural-analytical test generation methods is limited, as a rule, to a multitude of single constant faults.The use of automaton models in the construction of tests allows to detect any malfunction that changes the automaton diagram of a serviceable remote control and does not increase the number of states of remote control memory elements.There was described finite state machine using hardware description language.The method of computer-aided design of the easytested control FSM by introducing the hardware redundancy is presented in the paper.The FSM model is represented in VHDL in the form of the FSM template.The solution way is to add additional fragments of the VHDL code, which ensure the forced setting of the FSM into an arbitrary state without the use of synchronizing sequences.The use of the shift register in the memory part of the control FSM for organizing the path scanning was considered.The method of FSM state table expansion, which ensures the mode of bypassing all nodes of the FSM' state diagram in the diagnostic mode was proposed.
Location Based Encryption

We first propose a 2D Location Based Encryption (LBE) scheme, where the setting includes a geography center system and the 2D triangle area including the set of locations. A user joining in the system is provided with a pre-arranged key, which belongs to her/his location. If the user’s location is belonging to this area, he/she can decrypt the message. Our proposed scheme achieves a constant ciphertext size in encryption algorithm and decryption cost. Beyond the 2D-LBE scheme, we explore the 3D-LBE scheme; whereby the location is set up in the 3D dimensions. This proposed scheme is an extension of 2D-LBE scheme, which the ciphertext is also constant. Both two schemes are proved in the selective model under the decisional $$\ell -$$ wBDHI assumption.
Evolving Programs to Build Artificial Neural Networks

In general, the topology of Artificial Neural Networks (ANNs) is human-engineered and learning is merely the process of weight adjustment. However, it is well known that this can lead to sub-optimal solutions. Topology and Weight Evolving Artificial Neural Networks (TWEANNs) can lead to better topologies however, once obtained they remain fixed and cannot adapt to new problems. In this chapter, rather than evolving a fixed structure artificial neural network as in neuroevolution, we evolve a pair of programs that build the network. One program runs inside neurons and allows them to move, change, die or replicate. The other is executed inside dendrites and allows them to change length and weight, be removed, or replicate. The programs are represented and evolved using Cartesian Genetic Programming. From the developed networks multiple traditional ANNs can be extracted, each of which solves a different problem. The proposed approach has been evaluated on multiple classification problems.
In-circuit Signal Analysis in the Development of Digital Devices in Vivado 2018

Considered the implementation of in-circuit analysis of logical signals in digital devices synthesized in Xilinx Field-Programmable Gate Array.Designed a digital control device streaming analog-to-digital converter.An analysis of the results of the analog-digital conversion was carried out and measures were taken to smooth out the false results of the conversion.
Science in Your Pocket: Leaving High School Students to Their Own 'Devices' While Designing an Inquiry-Based Investigation.

Smartphones are increasingly used in schools to achieve a number of educational outcomes; from developing measurement skills to enabling collaborative learning. When used as a measurement device in science classrooms, a few questions emerge. How good are the measurement capabilities of smartphones? Can smartphones lead to a more positive learning experience? What are students' and teachers' attitudes to investigations when smartphones are used to take measurements? This study investigated the use of smartphones as measurement devices in a classroom hands-on investigation to probe the complex phenomenon of light intensity. The investigation was implemented in nine workshops with a total of 93 students and 118 teachers. We report on the design and evaluation of the investigation using a survey consisting of Likert-style questions, measures of mental effort and open-ended responses. Results show that the design features were critical to the success of the investigation and participants found the investigation to be interesting and a valuable learning experience.
STUDYING OPEN BANKING PLATFORMS WITH OPEN SOURCE CODE

Intensive growth of public web interfaces started early in 2010; and if initially API was a procedure of interaction of various software tools, then at present web interfaces are genuine digital products on the basis of which companies, especially major companies, can derive profits while providing their internal services to third parties via open API. Banks are not an exception. They also can derive profits by providing access to their internal services for third-party developers. The advantage of banking enterprises is that they possess unique data and services, which can hardly be competed. As a consequence, there appeared the software market for the development of open source API and provision of access to them with monetization capabilities. API management platform is comprised generally of three components: developer site, API development tools, and API gateway. API gateway is the most important component since it is responsible for interface operation; hence, this work is aimed at the determination of the most efficient API gateways. Three software variants have been considered: Gravitee API Platform, APIMan, and WSO2 API Manager, which meet two preset criteria: Java product implementation, open source code of the product. The study has been performed in comparison environment with three coordinates: intensity of performed functions for API development, labor intensity of API implementation, the performance of API gateway. During the experiments, Gravitee.io API Platform was the best software with regard to each coordinate.
Interacting with Maps in Virtual and Augmented Reality

Abstract. Augmented reality (AR) and virtual reality (VR) technology are increasingly used for the analysis and visualisation of geospatial data. It has become simple to create an immersive three-dimensional AR or VR map with a combination of game engines (e.g., Unity), software development kits for streaming and rendering geospatial data (e.g., Mapbox), and affordable hardware (e.g., HTC Vive). However, it is not clear how to best interact with geospatial visualisations in AR and VR. For example, there are no established standards to efficiently zoom and pan, select map features, or place markers on AR and VR maps. In this paper, we explore interaction with AR and VR maps using gestures and handheld controllers.As for gesture-controlled interaction, we present the results of recent research projects exploring how body gestures can control basic AR and VR map operations. We use motion-tracking controllers (e.g., Leap Motion) to capture and interpret gestures. We conducted a set of user studies to identify, explore and compare various gestures for controlling map-related operations. This includes, for example, mid-air hand gestures for zooming and panning (Satriadi et al. 2019), selecting points of interest, adjusting the orientation of maps, or placing markers on maps. Additionally, we present novel VR interfaces and interaction methods for controlling the content of maps with gestures.As for handheld controllers, we discuss interaction with exocentric globes, egocentric globes (where the user stands inside a large virtual globe), flat maps, and curved maps in VR. We demonstrate controller-based interaction for adjusting the centre of world maps displayed on these four types of projection surfaces (Yang et al. 2018), and illustrate the utility of interactively movable VR maps by the example of three-dimensional origin-destination flow maps (Yang et al. 2019).
Contribute for an Ontology for Smart Homes and their Conversational Assistants

Despite the improved capabilities of recent Assistants, control and access to the information regarding Smart Homes stills limited. More information is needed on what should be a Smart Home Assistant and how-to have the structured semantic information to support their answers and actions, i.e., how to structure the knowledge and make it simple to use by current approaches to Assistants, based commonly in intentions and entities. As contribute to increase Assistants capabilities in Smart Homes environments, based on analyses of the domain and user enquiries, we propose the basis for an ontology to support both, the interaction and the Smart Home knowledge base. The proposed ontology is being used to support the creation of an enhanced version of a Conversational Assistant for the Smart Green Homes project with novel functionalities, aligned with advanced user needs and expectations.
A Joint Semantic Vector Representation Model for Text Clustering and Classification

Text clustering and classification are two main tasks of text mining. Feature selection plays the key role in the quality of the clustering and classification results. Although word-based features such as term frequency-inverse document frequency (TF-IDF) vectors have been widely used in different applications, their shortcoming in capturing semantic concepts of text motivated researches to use semantic models for document vector representations. Latent Dirichlet allocation (LDA) topic modeling and doc2vec neural document embedding are two well-known techniques for this purpose. In this paper, we first study the conceptual difference between the two models and show that they have different behavior and capture semantic features of texts from different perspectives. We then proposed a hybrid approach for document vector representation to benefit from the advantages of both models. The experimental results on 20newsgroup show the superiority of the proposed model compared to each of the baselines on both text clustering and classification tasks. We achieved 2.6% improvement in F-measure for text clustering and 2.1% improvement in F-measure in text classification compared to the best baseline model.