Reviewerly/exHarmony huggingface dataset:
Text-to-Voice and Voice-to-Text Software Systems and Students with Disabilities: A Research Synthesis

The use of text-to-voice and voice-to-text software systems is becoming more popular to aid students with disabilities in general education classrooms. These systems allow students with disabilities to access content and learn classroom material more effectively and efficiently. The software systems are a subset of systems that should be considered in smart universities and smart classrooms. They will allow instructors to better educate local and distant college students. In addition, college students are more technological than ever before and are demanding new and innovative ways to learn. This paper presents the results from a comprehensive literature search on text-to-voice and voice-to-text software systems. A total of 20 articles were located which included 4 position papers, a meta-analysis, and 15 research studies with students with disabilities. Articles ranged from 1995 to 2018 and included elementary to college-aged student and adults. Each paper that was located will be described and results and conclusions will be provided. Even though students with disabilities are not the majority of learners in our classes, by incorporating university-wide smart systems and technologies, we believe many of these students will also benefit. This paper also addresses the potential impact these software systems could have on the learning of students with disabilities and how this software could aid universities to a possible transformation from a traditional university into a smart one.
Bi-dimensional Empirical Mode Decomposition Based Contrast Enhancement Technique for UAV Thermal Images

In this paper, a new contrast enhancement technique based on bi-dimensional empirical mode decomposition (BEMD) is proposed to enhance the target details in low contrast thermal images captured by unmanned aerial vehicle (UAV). Initially, thermal image acquired from UAV is separated into intrinsic mode functions (IMFs) and residue using BEMD. Then, local standard deviation based method is employed to the IMFs to improve the details of the image and histogram modification function is employed to the residue to enhance the contrast. The processed IMFs and residue are reconstructed to obtain the enhanced image using inverse BEMD. The performance of the proposed technique is analysed using quantitative and visual quality measures with the well-known histogram equalization, dynamic range partitioning and wavelet-based enhancement methods. Experimental results demonstrate that the proposed technique effectively enhances the contrast and details in the image with less noise and visual artefacts than other methods.
GeoGCD

Gaze-Contingent Displays (GCDs) can improve visual search performance on large displays. GCDs, a Level Of Detail (LOD) management technique, discards redundant peripheral detail using various human visual perception models. Models of depth and contrast perception (e.g., depth-of-field and foveation) have often been studied to address the trade-off between the computational and perceptual benefits of GCDs. However, color perception models and combinations of multiple models have not received as much attention. In this paper, we present GeoGCD which uses individual contrast, color, and depth-perception models, and their combination to render scenes without perceptible latency. As proof-of-concept, we present a three-stage user evaluation built upon geographic image interpretation tasks. GeoGCD does not impair users' visual search performance or affect their display preferences. On the contrary, in some cases, it can significantly improve users' performance.
Robust Face Tracking Using Siamese-VGG with Pre-training and Fine-tuning

In order to analyze facial expression in human-computer interaction, real time face-tracking has become significant research problem. Traditional face tracking methods have achieved good results in some constrained environments (such as good illumination, no background interference, etc.) However, these methods require to design manual facial features depending on researcher's experience. In addition, lacking ability for generalization problems is worthy of study. The robustness of face tracking in complex scenes is challenging due to fast moving, multi-scale changes, rotation and occlusion, illumination changes, etc. In view of the above considerations, this paper proposes an improved method based on Siamese-Net to optimize for face tracking tasks. Our work mainly includes four aspects. First, the first two convolutional layers of deeper VGG-16 are used to extract feature. So we call our method Siamese-VGG. Second, we report experiment on face tracking using a pre-trained VGG-Face model which is trained by 2.6M images for face recognition and then fine-tuning to acceleration convergence. Third, in this research the same size crops are input to two branches in the framework and then the inner smaller template feature maps are extracted during training. The proposed method in this paper reduce offset losses by this way. Finally, L2 regularization add to the loss function to improve the generalization ability of the model. The experiment results show better robustness and generalization performance over the original algorithm. In complex scenes, the proposed improved method have achieved the great improvements by almost 11% on average overlap. But, the frame rate of improved method is still 18.5fps on the Nvidia GTX1070Ti GPU.The improved method proposed in this paper is more practical in terms of speed and accuracy.
Use of Virtual Environment and Virtual Prototypes in Co-Design: The Case of Hospital Design

Co-design is used for improving innovation, obtaining better solutions, and higher user satisfaction. In this paper we present how the use of a walk-in virtual environment and actual-size virtual prototypes support co-design. Unlike in most studies we presented the prototypes to users in an early phase of the design process. This study examines the co-design of healthcare facilities with multi-occupational groups. The practical case examines designing single-patient rooms for an intensive care unit. In this design process 238 participants of different hospital professions evaluated virtual prototypes in three iterative rounds. The participants improved the design by discussing their work practices. The virtual environment situation and actual size virtual prototypes make an easy environment for users to discuss and evaluate the design without any design knowledge. In addition to describing the co-design results we also outline some important issues and guidelines about creating the virtual prototypes and organizing the participants’ visits in a virtual environment.
Bridging the divide

Purpose The purpose of this paper is to present an analysis of the development of a new graduate certificate course in Petroleum Data Management. The course was developed in response to an identified gap in skills and training in data management that was perceived to be a substantial risk in terms of: industry sustainability, efficiency and potentially wider implications of safety as assets are transferred between operators and for decommissioning. The aim of this paper is to critically reflect on how academia and industry can work together to support emerging professions in information management. Design/methodology/approach The paper draws on observations and interviews from key stakeholders involved in the course development. Findings The course development process was ultimately successful but also challenging and lessons have been learned which will be of interest to the wider professional and academic body. These include: securing resources and industry engagement for course development, negotiating cultural differences between academic and industry and managing stakeholder relationships throughout the lifecycle of the course development. Originality/value The paper demonstrates the challenges and opportunities of developing a university course in collaboration with industry partners. Oil and gas exploration and production is a data-intensive industry but it was only relatively recently that attempts have been made to set industry standards and roles of “data manager” or “data analyst” have been created to manage these. This paper has wider implications for understanding the professionalisation of the nascent data management disciplines and contributes to the ongoing dialogue around the changing library and information science profession.
Calibration-free text entry using smooth pursuit eye movements

In this paper, we propose a calibration-free gaze-based text entry system that uses smooth pursuit eye movements. We report on our implementation, which improves over prior work on smooth pursuit text entry by 1) eliminating the need of calibration using motion correlation, 2) increasing input rate from 3.34 to 3.41 words per minute, 3) featuring text suggestions that were trained on 10,000 lexicon sentences recommended in the literature. We report on a user study (N=26) which shows that users are able to eye type at 3.41 words per minutes without calibration and without user training. Qualitative feedback also indicates that users positively perceive the system. Our work is of particular benefit for disabled users and for situations when voice and tactile input are not feasible (e.g., in noisy environments or when the hands are occupied).
Trading Privacy for Utility in Database-Assisted Dynamic Spectrum Access

In dynamic spectrum access, commercially operated database servers are often used to assist opportunistic users (OUs) to query and access spectrum vacancies of incumbent users (IUs). This query and answer process introduces significant privacy concerns due to the potential leakage of sensitive operational details about IUs, especially their locations. Existing privacy-preserving mechanisms, such as spatial obfuscation, k-anonymity and cryptographic approaches, can be used to hide IU locations. They, however, cannot guarantee that the interference level caused by OU activity remains under required limits. Moreover, privacy mechanisms do not account for spectrum efficiency (i.e., the loss of OU transmission opportunities) in their designs. The complex three-way tradeoff between privacy, interference, and utility has not been systematically studied in the literature. In this paper, we tackle this challenge by formalizing the relationship between privacy and spectrum efficiency using the concept of a privacy zone (PZ) contained in an exclusion zone (EZ). Within the PZ, IU location is indistinguishable, whereas the EZ guarantees an interference limit for any IU located within the PZ. By fixing either the privacy or the interference requirement, we formulate and solve corresponding optimization problems that maximize utility under fixed and probabilistic OU location deployments, respectively. Our formulations can accommodate the privacy requirements of multiple IUs. Simulation results using real-world maps/parameters show that the IU's privacy increases with decreasing OUs' utility, given a fixed allowable interference for the IUs. Furthermore, we show that this paper outperforms the work of Bahrak et al.
Cooperative Manipulation of an Unknown Payload With Concurrent Mass and Drag Force Estimation

In this letter, we consider a team of robots that cooperatively transport a payload with an unknown mass in the presence of unknown drag forces. We develop a concurrent learning-based adaptive control algorithm that estimates the drag forces and the unknown mass and drives the agents and the payload to a common desired velocity. The algorithm also regulates the contact forces on the payload. We prove that the estimated parameters, including the mass of the payload, converge to their true values. We validate the effectiveness of the proposed algorithm using two simulation examples.
Map-Side Join Processing of SPARQL Queries Based on Abstract RDF Data Filtering

The amount of RDF data being published on the Web is increasing at a massive rate. MapReduce-based distributed frameworks have become the general trend in processing SPARQL queries against RDF data. Currently, query processing systems that use MapReduce have not been able to keep up with the increase of semantic annotated data, resulting in non-interactive SPARQL query processing. The principal reason is that intermediate query results from join operations in a MapReduce framework are so massive that they consume all available network bandwidth. In this article, the authors present an efficient SPARQL processing system that uses MapReduce and HBase. The system runs a job optimized query plan using their proposed abstract RDF data to decrease the number of jobs and also decrease the amount of input data. The authors also present an efficient algorithm of using Map-side joins while also using the abstract RDF data to filter out unneeded RDF data. Experimental results show that the proposed approach demonstrates better performance when processing queries with a large amount of input data than those found in previous works.
Information Technology and Teaching Culture: Application in Classroom

With the changes in linguistic theory and pedagogical practice, culture has been regarded as an essential element in language classrooms. Thanks to the potential of information technology (IT), teaching, including learning English in general and subjects related to culture, in particular, has been supported and enhanced significantly. The study aims to investigate the effects and approaches of employing IT in teaching culture to enhance Intercultural Communication Competence (ICC) of Vietnamese tertiary students of English as well as the students’ and teachers’ perceptions toward using IT in teaching culture. In order to collect the data, an IT-assisted teaching project was applied for 40 English major students at Hanoi Law University in 8 weeks to an ICC subject. In addition, a set of questionnaires were delivered to the participants, plus 13 teachers who taught culture-related subjects from three universities. The findings revealed that although there were certain challenges, using IT in teaching culture had satisfying effects on students’ intercultural competence, problem- solving skills, assessment, and motivation to discover a new language in a new culture and suitable pedagogical strategies are suggested.
Effects of Relationship Goal on Linguistic Behavior in Online Dating Profiles: A Multi-Method Approach

This study uses two methods to examine whether online daters looking for a long-term relationship behave linguistically different in their profile texts compared to daters seeking casual relationships. To investigate these linguistic differences, 12,310 existing Dutch dating profiles were analyzed using the Linguistic Inquiry and Word Count (LIWC) program and a word-based classifier. Results of both methods suggest there are reliable differences in the linguistic behavior long-term and casual relationship seekers employ in their dating profiles: long-term relationship seekers mention more topics that are relevant when looking for a long- term relationship, such as internal personality traits and qualities. Additionally, long-term relationship seekers seem to self-disclose more in their profile texts by providing more personal information and using more I-references. Profile texts of casual relationship seekers are more diffuse and harder to classify. Moreover, the study demonstrates that using a multi-method approach, with LIWC and a data-driven word-based classifier, provides a deeper understanding of linguistic differences between the two relationship seeking groups.
Use of Blockchain in Governance: A Systematic Literature Review

Blockchain is a distributed network based ledger that is secured by the methods of cryptographic proof.It enables the creation of self-executable digital contracts i.e. smart contracts.This technology is working in collaboration with major areas of research including governance, IoT, health, banking and education.It has anticipated revolutionary ways, which helps us to overcome the problems of governance such as human error, voting, privacy of data, security and food safety.In governance, there is a need to ameliorate the services and facilities with the assistance of blockchain technology.This paper aims to explore the issues of governance which can be resolved with the assistance of Blockchain features.Furthermore this paper also provides the future work directions.
On MILP-Based Automatic Search for Differential Trails Through Modular Additions with Application to Bel-T

Using modular addition as a source of nonlinearity is frequently used in many symmetric-key structures such as ARX and Lai–Massey schemes. At FSE'16, Fu et al. proposed a Mixed Integer Linear Programming (MILP)-based method to handle the propagation of differential trails through modular additions assuming that the two inputs to the modular addition and the consecutive rounds are independent. However, this assumption does not necessarily hold. In this paper, we study the propagation of the XOR difference through the modular addition at the bit level and show the effect of the carry bit. Then, we propose a more accurate MILP model to describe the differential propagation through the modular addition taking into account the dependency between the consecutive modular additions. The proposed MILP model is utilized to launch a differential attack against Bel-T-256, which is a member of the Bel-T block cipher family that has been adopted recently as a national standard of the Republic of Belarus. In particular, we employ the concept of partial Differential Distribution Table to model the 8-bit S-Box of Bel-T using a MILP approach in order to automate finding a differential characteristic of the cipher. Then, we present a $$4\frac{1}{7}$$ -round (out of 8) differential attack which utilizes a 3-round differential characteristic that holds with probability $$2^{-111}$$ . The data, time and memory complexities of the attack are $$2^{114}$$ chosen plaintexts, $$ 2^{237.14} $$ $$4\frac{1}{7}$$ -round encryptions, and $$2^{224}$$ 128-bit blocks, respectively.
Accessible control of telepresence robots based on eye tracking

Gaze may be a good alternative input modality for people with limited hand mobility. This accessible control based on eye tracking can be implemented into telepresence robots, which are widely used to promote remote social interaction and providing the feeling of presence. This extended abstract introduces a Ph.D. research project, which takes a two-phase approach towards investigating gaze-controlled telepresence robots. A system supporting gaze-controlled telepresence has been implemented. However, our current findings indicate that there were still serious challenges with regard to gaze-based driving. Potential improvements are discussed, and plans for future study are also presented.
Real World Hand Gesture Interaction in Virtual Reality

Abstract With the development of virtual reality, the appropriate interaction technology has become the focus of practitioners. Today’s virtual reality interaction is mostly through the interaction of traditional electronic devices, such as handles and other products, temporarily solve the problem of interaction, but also make the user from the virtual world is taken out, immersion greatly reduced. The paper uses hand gestures to interact with virtual reality. By using skin detection in YCbCr color space and indicates the location of hand to determine the approximate range of hand. Then, the histograms of oriented gradient (HOG) which has been widely used in target detection research in recent years is used to extract gesture features, and applies support vector machine (SVM) method to achieve the real-time hand gesture recognition. Finally, experiments prove that the proposed method is accurate and stable in virtual reality interaction.
A bilateral Hilbert-style investigation of 2-intuitionistic logic

Abstract We develop a bilateral Hilbert-style calculus for 2-intuitionistic logic of Heinrich Wansing. This calculus is defined over signed formulas of two types: formulas signed with plus correspond to assertions, while formulas signed with minus correspond to rejections. In this way, the provided system is a Hilbert-style calculus, which does take rejection seriously by considering it a primitive notion on par with assertion. We show that this presentation is not trivial and provide two equivalent axiomatizations obtained by extending intuitionistic and dual intuitionistic logics, respectively. Finally, we show that 2-intuitionistic logic is in some sense definitionally equivalent to a variant of Nelson’s logic with constructible falsity.
AOH-Map: A Mind Mapping System for Supporting Collaborative Cyber Security Analysis

Cyber Security Operations Centers (CSOCs) have been widely built in organizations for intrusion detection and incident response. Cyber security analysts play a critical role in CSOCs as they continuously monitor network activities to achieve cyber situational awareness. These analysts are tasked with poring over massive network monitoring data collected by various cyber defense technologies, such as Intrusion Detection System (IDS) alerts and firewall logs. To achieve awareness of the potential attacks and to have an effective real-time response, cyber security analysts need to work in teams and must be able to quickly exchange their findings and divide tasks among each other. Currently the information sharing and task division are done inefficiently which negatively impacts the response and decision-making time. To this end, we propose a collaborative analysis support system that can record, represent and reveal the analytical reasoning process of analysts. The system consists of tracing modules, a trace parser and an interactive visual map, named “AOH-Map”. This map integrates all the captured traces of analysts' analytical reasoning process, and analysts can directly interact with the AOH-Map to review past analysis, share their findings and divide tasks in a timely manner. The system has been implemented and evaluated in a two-phase human subject experiment. The results show that the proposed system is effective in supporting collaboration among cyber analysts in terms of information sharing and task division.
Healthier Life with Digital Companions: Effects of Reflection-Level and Statement-Type of Messages on Behavior Change via a Perceived Companion

Quantified-self tools track personal data as well as emotional and psychological scores, in real time, of people who use such tools. Such data have potential uses for initiating interactions to induce personal health-related behavior changes. However, notwithstanding this potential, not much benefit has been derived from the data tracked using various devices such as smartphones and fitness trackers. The main research goal of this study is to investigate how interactions of quantified-self tools should be designed for inducing user perception and behavior change. Particularly, this study uses two message representation formats (MRF) for users to perceive self-tracking tools as companion devices because the MRFs of smartphones and fitness trackers are important to interact with users in conversational interaction. This study developed a message expression algorithm, “Samantha,” to deliver personalized-messages automatically in real time about the values tracked by these devices to their users. The study studied the effect of the four message representation formats on the perception of companion and to induce behavior change.