Reviewerly/exHarmony huggingface dataset:
Hardware-Based Emulator for Building Energy Cyber-Physical Control with Occupancy Sensing

Heating, ventilation and cooling (HVAC) is the largest source of residential energy consumption. Occupancy sensors’ data can be used for HVAC control since they indicate the number of people in the building. HVAC/sensor interactions show the essential features of a typical cyber-physical system (CPS). However, there are communication protocol incompatibility issues in the CPS interface between the sensors and the building HVAC server. Through either wired or wireless communication links, the server always needs to understand the communication schedule to receive occupant number from sensors. In this paper, we will use hardware-based emulators to investigate all wired and wireless communication interfaces for occupancy sensor-based building CPS. The typical synchronization between sensors and HVAC server requirements will be introduced. We have built two hardware/software emulation platforms to investigate the sensor/HVAC integration strategies. The first emulator demonstrates the residential building’s energy control using sensors and Raspberry pi boards to represent the functions of a static thermostat. In this case, room HVAC temperature settings could be changed in real-time with a high resolution with the collected sensor data. The second emulator is built to show the energy control in commercial building by transmitting the sensor data and control signals via BACnet in HVAC system. Additionally, sensor data can also be transmitted in a large build’s multi-hop wireless network. Both emulators discussed above are portable (i.e., all hardware units can be easily taken to a new place) and have extremely low cost.
Research on health management requirements of information communication system based on SWOT

The development analysis model of health management of information communication system is established by using SWOT quantitative analysis method. The internal advantages and disadvantages of health management in information communication system are analyzed. External opportunities and threats are analyzed through SWTO model and a series of data are quantified. According to the quantification results, the quadrilateral diagram and the intensity spectrum coordinate system of the health management development strategy of the information communication system are generated. Finally, some Suggestions on the future development of health management of information communication system are put forward.
The Tutoring Influences in Distance Education at El Oro Province Ecuador

&lt;p&gt;El Oro province undergoes a high rate of student’s withdrawal from distance courses offered by the local university. The distance education model gives for granted that the regular teachers are proficient for remote tutoring. This research attempts to reveal the state-of-art of this educative model in a provincial university. The study focused on a quantitative-qualitative explorative approach to determine, whether, if withdrawal is more frequent in introductory courses or not. Among the main causes for withdrawal were found: (1) the naive of learners in high education programs, (2) the inconsistency of the university proposals (academic and administrative) and; (3) the most important, the deficiencies in remote tutoring.&lt;/p&gt;
Interdisciplinary Aspects of Development and Software Implementation of Electronic Textbooks for Students of Technical Universities

The emergence of electronic textbooks as a means of teaching in the real educational process of the school and university necessitates scientific research in the field of their design and application. These scientific researches, which are currently conducted in didactics, psychology, information technology, computational mathematics, are inherently polydisciplinary, since didactic problems are solved by means of other scientific directions. At the same time, there are all prerequisites for conducting interdisciplinary research, the subject of which can be an electronic textbook. The purpose of this article is to substantiate the need for interdisciplinary research in the field of building electronic textbooks. In the main part of the work, the specific mathematical algorithms implemented in practice in the programming of the e-textbooks of the learning management system of the Moscow Aviation Institute are described. New mathematical approaches to designing an electronic textbook, in particular, a graph-oriented approach, are proposed. The model of forming a time-limited test is considered, where the weighted convolution of the normalized values is carried out by an optimization criterion: deviations of the test complexity from a given level and quantiles of the test execution time. The modern software technologies are used in the development of mathematical algorithmic module. In conclusion, we described the effectiveness of the joint research of specialists from different scientific fields, which has been confirmed by the practical implementation of this project.
Evaluating the performance and improving the usability of parallel and distributed Word Embeddings tools

The representation of words by means of vectors, also called Word Embeddings (WE), has been receiving great attention from the Natural Language Processing (NLP) field. WE models are able to express syntactic and semantic similarities, as well as relationships and contexts of words within a given corpus. Although the most popular implementations of WE algorithms present low scalability, there are new approaches that apply High-Performance Computing (HPC) techniques. This is an opportunity for an analysis of the main differences among the existing implementations, based on performance and scalability metrics. In this paper, we present a study which addresses resource utilization and performance aspects of known WE algorithms found in the literature. To improve scalability and usability we propose a wrapper library for local and remote execution environments that contains a set of optimizations such as the pWord2vec, pWord2vec MPI, Wang2vec and the original Word2vec algorithm. Utilizing these optimizations it is possible to achieve an average performance gain of 15x for multicores and 105x for multinodes compared to the original version. There is also a big reduction in the memory footprint compared to the most popular python versions.
The Role of Industry Partnerships and Collaborations in Information Technology Education

Information technology education is in high demand, including a significant and fast-growing workforce shortage of and demand for well trained and qualified cybersecurity professionals. Postsecondary education institutions are expected to play a key role in relieving the shortage and meeting the workforce demand. The information technology and cybersecurity industry and professional task areas need comprehensive academic, technical and professional competencies and knowledge, skills and abilities (KSAs) that may not be adequately addressed by the traditional college classroom activities. This study proposes close collaborations and partnerships between information technology (IT) education providers, programs and industry organizations to improve cyber defense education and serve the needs of the industry. There could be various types of collaborations between the industry and education providers, and this research proposes a taxonomy of activities for collaborations. The proposition in this study is based on an established cybersecurity industry competency model with multiple tiers of competencies expected for the cybersecurity workforce. This research study uses sample case discussions of industry collaborations and partnerships at a selected cyber defense education program from a National Center of Academic Excellence in Cyber Defense Education (CAE-CDE) designated by the United States National Security Agency and Department of Homeland Security. Experienced IT and cybersecurity industry professionals and educators participate in this study and share their experiences and insights on the benefits, challenges and strategies for establishing and maintaining partnerships and collaborations between higher education and cybersecurity industry organizations.
MaxWhere VR Learning at the Patrona Hungariae Secondary School

The goal of our presentation is to show how Patrona is moving from e-learning to 3D digital learning.
The information manifold: Why computers cannot solve algorithmic bias and fake news. AntonioBadiaCambridge, UK: The MIT press, 2019. 352 pp. $50.00 (hardcover). (ISBN 9780262043038)

Journal of the Association for Information Science and TechnologyVolume 72, Issue 3 p. 357-361 BOOK REVIEW The information manifold: Why computers cannot solve algorithmic bias and fake news. Antonio Badia Cambridge, UK: The MIT press, 2019. 352 pp. $50.00 (hardcover). (ISBN 9780262043038) Marc Kosciejew, Marc Kosciejew Department of Library Information and Archive Sciences, University of Malta, Msida, MaltaSearch for more papers by this author Marc Kosciejew, Marc Kosciejew Department of Library Information and Archive Sciences, University of Malta, Msida, MaltaSearch for more papers by this author First published: 13 May 2020 https://doi.org/10.1002/asi.24365Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume72, Issue3March 2021Pages 357-361 RelatedInformation
Mobile Technologies Course Design

Mobile learning has the potential to increase the opportunities to make teaching and learning available beyond the traditional classroom. The main aim of this study was to develop a mobile technologies course delivered online and explore the effects of this online course designed on mobile technologies on the use of ICT skills, attitudes, and views of EFL instructors. While employing mixed methodology, explanatory sequential research design was applied. In this study, participants were selected through convenient sampling and the data were collated through a questionnaire used as pre- and post-tests, followed by semi-structured interviews and class observations. The results of this study indicated that the online training course on mobile technologies had a positive impact on the use of ICT skills and EFL teachers' views in general. Further, attending the mobile technologies course delivered online was very beneficial and effective for the instructors in that it helped them to develop their skills on the use of mobile technologies in English language teaching.
Hierarchical age estimation mechanism with adaBoost-based deep instance weighted fusion

Age estimation can obtain biological age which is helpful for diagnosis of healthy status and disease. The current age estimation methods do not consider the deep relationships of instances, which limits the potential improvement of the age estimation performance. A hierarchical age estimation mechanism with adaboost-based deep instance weighted fusion is proposed to solve this problem. First, a circulation iterative means clustering (CIMC) algorithm is designed for constructing the hierarchical instance space (multiple-layer instance spaces) and obtain multiple trained base regression models. Second, an adaboost-based deep instance weighted fusion (ADIWF) mechanism is designed to fuse the results of the trained regression models. Several representative age-related datasets are used for verification of the proposed method. The experimental results show that the mean absolute error (MAE) can be decreased apparently, by 6.86% and 1.42% on the Heart and Diabetes Dataset, respectively. Besides, some factors that may influence the performance of the proposed mechanism are studied. In general, the proposed age estimation mechanism is effective. In addition, the mechanism is a kind of framework mechanism, so it can be used to construct different concrete age estimation algorithms, and is helpful for related studies.
Study on the Construction Specifications of Campus Card in Universities under the New Situation

This paper introduces the construction specifications of campus card in universities under the new situation of the technology development, including general design requirements, technical standards, card medium selection and design, application systems and application of new technologies. It mainly elaborates the top-level design, user experience, open platform, security system, the intelligent operations, and data analysis, etc., which are applicable to the planning, construction, implementation and operational process of the campus card in universities.
Design and Evaluation of a VR Training Simulation for Pump Maintenance Based on a Use Case at Grundfos

Figure 1: Based on a use case at Grundfos, we implemented a virtual training simulation of a structured maintenance task for training of novice technicians.In a user study, we evaluated the potential of this VR Training simulation (C), in comparison to two traditional training methods: (A) Pairwise Training, (B) Video Training.
SSEIM: An Efficient Search Scheme over Encrypted Data with Indexing on Mobile Cloud

Mobile Cloud Computing (MCC) is a smart way to reduce IT cost, provide services anywhere, and any time. Encrypting the outsourced data is one way of enhancing the privacy from the owner point of view. Mobile devices consumes more resources when workload is heavy. In order to reduce, computation, communication and searching time of related files based on keyword query “An Efficient Search Scheme over Encrypted Data with Indexing on Mobile Cloud” (SSEIM) is proposed. The SSEIM uses the keyword-based search that includes Order Preserving Encryption (OPE) to order the encrypted data and makes use of indexing the record to search the related files. Thus, the proposed scheme is more efficient with respect to retrieval time as compared to the existing scheme TEES (Traffic and Energy saving Encrypted Search).
Deep Metacyclic Parameter Search: Non-Convex optimization Based on Evolutionary Computing with a Few Twists

This paper proposes a new framework for non-convex optimization referred to as Metacyclic Parameter Search (MEPS). The framework combines several approaches that are well known from the field of artificial intelligence-namely the iterative update of generations of candidate solutions prevalent in evolutionary computing and particle swarm optimization, as well as metacognitive approaches implementing reward-based improvement such as (deep) reinforcment learning-resulting in a gradient-free approach to non-convex optimization that combines the benefits (and alleviates the mutual shortcomings) of each of these individual approaches. Following an overview of the framework, its workings are demonstrated on three rudimentary examples.
A Low-cost Approach Towards Streaming 3D Videos of Large-scale Sport Events to Mixed Reality Headsets in Real-time

Watching sports events via 3D- instead of two-dimensional video streaming allows for increased immersion, e.g. via mixed reality headsets in comparison to traditional screens. So far, capturing 3D video of sports events required expensive outside-in tracking with numerous cameras. This study demonstrates the feasibility of streaming sports content to mixed reality headsets as holographs in real-time using inside-out tracking and low-cost equipment only. We demonstrate our system by streaming a race car on an indoor track as 3D models, which are then rendered in an Magic Leap One headset. An onboard camera, mounted on the race car provides the video stream used to localize the car via computer vision. The localization is estimated by an end-to-end convolutional neural network (CNN). The study compares three state-of-the-art CNN models in their respective accuracy and execution time, with PoseNet+LSTM achieving position and orientation accuracy of 0.35m and 3.95°. The total streaming latency in this study was 1041ms, suggesting technical feasibility of streaming 3D sports content, e.g. on large playgrounds, in near real-time onto mixed-reality headsets.
Accelerated Stereo Rendering with Hybrid Reprojection-Based Rasterization and Adaptive Ray-Tracing

Stereoscopic rendering is a prominent feature of virtual reality applications to generate depth cues and to provide depth perception in the virtual world. However, straight-forward stereo rendering methods usually are expensive since they render the scene from two eye-points which in general doubles the frame times. This is particularly problematic since virtual reality sets high requirements for real-time capabilities and image resolution. Hence, this paper presents a hybrid rendering system that combines classic rasterization and real-time ray-tracing to accelerate stereoscopic rendering. The system reprojects the pre-rendered left half of the stereo image pair into the right perspective using a forward grid warping technique and identifies resulting reprojection errors, which are then efficiently resolved by adaptive real-time ray-tracing. A final analysis shows that the system achieves a significant performance gain, has a negligible quality impact, and is suitable even for higher rendering resolutions.
Complex Human Emotions in Alzheimer’s Interviews: First Steps

In this paper, we intended to test the hypothesis that there is a common denominator in complex emotions which human experts can identify, specifically in determining target scenarios. The underlining concept behind our work is that the system aims to compose complex emotions from simplex emotions. Our propose does not completely ignore the need for human operators since they (the human operators) make the final decision to confirm that the input video sequence corresponds to the simplex and complex emotion. However, the proposed system is designed in such a way that, theoretically once it is fully installed and operational, it would work on its own by automatically generating message alerts for the human operator. This entire process is based on the identification and labelling of what we call elementary or basic activities, namely events that are recognizable by artificial vision algorithms in this case HER. To test our hypothesis, we carried out an experiment on human emotions in Alzheimer’s interviews video. The results of experimentation showing that is possible identify complex emotions in video, include in important context how Alzheimer.
Improving Project Management Practices in a Software Development Team

Software development projects continue to deliver results that fall short on organization’s expectations. The present research was carried out at InfoPortugal, a technological company specialized in Geographic Information Systems and Tourism and Leisure Solutions, where project management practices were underuse. Therefore, the focus of this paper is to describe the proposals and their implementation to enable the improvement of project management practices in a software development team. Guidelines are provided by a matrix with key areas to be improved and related proposed improvement initiatives. The definition and application of a hybrid project management methodology was the most important improvement initiative to address some of the key problems identified in case under study. Traditional plan-oriented methodologies do not have the flexibility to dynamically adjust to the software development process. While, agile methodologies combine iterative and incremental approaches to adapt to high levels of change, with early and continuous delivery.
Towards GPU-Accelerated PRM for Autonomous Navigation

Sampling based planning is an important step for long-range navigation for an autonomous vehicle. This work proposes a GPU-accelerated sampling based path planning algorithm which can be used as a global planner in autonomous navigation tasks. A modified version of the generation portion for the Probabilistic Road Map (PRM) algorithm is presented which reorders some steps of the algorithm in order to allow for parallelization and thus can benefit highly from utilization of a GPU. The GPU and CPU algorithms were compared using a simulated navigation environment with graph generation tasks of several different sizes. It was found that the GPU-accelerated version of the PRM algorithm had significant speedup over the CPU version (up to 78×). This results provides promising motivation towards implementation of a real-time autonomous navigation system in the future.
Influence Across Agents and Issues in Combinatorial and Collective Decision-Making

We consider settings of combinatorial and collective decision-making where a set of agents make choices on a set of issues in sequence based on their preferences over a set of alternatives for each issue. While agents have their initial preferences on issues, they may influence others and be influenced by others, consequently changing their preferences or choices on these issues in the process of decision-making. Though the influence among multiple agents making decisions on one issue and the dependency (influence) among multiple issues decided by one agent have been fully discussed in previous work, the influence from multiple sources across both agents and issues in the context of combinatorial and collective decision-making has been ignored. In this paper, we proposed a preliminary framework to address the influence transcending multiple agents and multiple issues with two rules: weighted influence and one dominant influence.
Library: Illustration: Find Articles

Illustration is a type of art that is a visual explanation or interpretation of a written text.
Developing Cryptography Key Management Plans for Healthcare Institutions

To secure patient ePHI, healthcare institutions must ensure that a qualified key management plan is implemented within their organization. Selecting and properly maintaining cryptography keys and hash functions can prevent critical healthcare systems from being compromised.
Using Data Mining to Explore Calmodulin Bibliography

In this chapter, we present a strategy and the techniques to approach a scientific field from a set of articles gathered from the bibliographic database “Web of Science.” The strategy is based on methods developed to analyze social networks. We illustrate its use in studying the calmodulin field. The method allows to structure a huge number of articles when writing a review, to detect the key opinion leaders in a given field, and to locate their own research topic in the landscape of themes deciphered by our own community. We show that the free software VOSviewer may be used without knowledge in computing science and with a short learning period.