Reviewerly/exHarmony huggingface dataset:
Neural Ordinary Differential Equations with Envolutionary Weights

Neural networks have been very successful in many learning tasks, for their powerful ability to fit the data. Recently, to understand the success of neural networks, much attention has been paid to the relationship between differential equations and neural networks. Some research suggests that the depth of neural networks is important for their success. However, the understanding of neural networks from the differential equation perspective is still very preliminary. In this work, also connecting with the differential equation, we extend the depth of neural networks to infinity, and remove the existing constraint that parameters of every layer have to be the same by using another ordinary differential equation(ODE) to model the evolution of the weights. We prove that the ODE can model any continuous evolutionary weights and validate it by an experiment. Meanwhile, we propose a new training strategy to overcome the inefficiency of pure adjoint method. This strategy allows us to further understand the relationship between ResNet with finite layers and that with infinite layers. Our experiment indicates that the former can be a good initialization of the latter. Finally, we give a heuristic explanation on why the new training method works better than pure adjoint method. Further experiments show that our neural ODE with evolutionary weights converges faster than that with fixed weights.
Adding Semantics to Enrich Public Transport and Accessibility Data from the Web

Web technologies and open data practices have now begun to promote new issues and services addressed to both final and specialized users. The smart cities initiative has also introduced new trends and ideas to offer to the public, one of which is the challenge of a more inclusive society that will provide the same opportunities for all. One of the major areas that could benefit from these new initiatives is public transport by, for example, providing open and accessible datasets, which include information by and about people with special needs. In this sense, the Google Transit Feed Specification (GTFS) defines a format to describe public transportation and associated geographic information. It includes details regarding accessibility and what people with special needs might require to get around using public transport. We are, however, of the opinion that this specification has a low granularity and is not sufficient, since it only takes into account only mobility needs. As suggestions for improvement, we propose to enrich GTFS data by combining public transport data from multiple Web sources with semantic metadata techniques. Those data are stored in a public semantic dataset. To define this dataset, we propose a systematic method to extract data from different sources and integrate them. This method is applied to obtain data about the metro system from the website of Metro Madrid and GTFS. Relevant SPARQL queries and two applications are developed to evaluate the usefulness of the dataset obtained.
Approaches and challenges to virtual and augmented reality in health care and rehabilitation

course Share on Approaches and challenges to virtual and augmented reality in health care and rehabilitation: a short course Authors: Joaquim Jorge U Lisboa U LisboaView Profile , Pedro Campos U Lisboa U LisboaView Profile , Daniel Simões Lopes U Lisboa U LisboaView Profile Authors Info & Claims SA '19: SIGGRAPH Asia 2019 CoursesNovember 2019 Article No.: 124Pages 1–85https://doi.org/10.1145/3355047.3359418Published:17 November 2019Publication History 0citation206DownloadsMetricsTotal Citations0Total Downloads206Last 12 Months20Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Service Discovery for the Connected Car with Semantic Accessors.

Connected cars have the potential to transform a vehicle from a transportation platform to a platform for integrating humans with a city. To that end we introduce semantic accessors (actor based local proxies for remote services) as a novel, and powerful discovery mechanism for connected vehicles that bridges the domains of Internet of Things (IoT) composition frameworks and the semantic web of things. The primary components of this approach include a local semantic repository used for maintaining the vehicle's perspective of its real-world context, accessors for querying and dynamically updating the repository to match evolving vehicular context information, accessors for services (such as parking) linked to a service ontology, and a swarmlet controller responsible for managing the above in accordance with user input. We demonstrate this semantic accessor architecture with a prototype Dashboard display that downloads accessors for new services as they become available and dynamically renders their self-described user interface components.
Designing Enterprise Architecture of The Smart Governance of Bogor

Bogor City is one of the one hundred selected cities which are expected to implement Smart City. One component to realize Smart City is the implementation of e-government through the use of Information Technology (IT) through the Smart Governance dimension which is expected to be able to harmonize the implementation of the Bogor ICT integration strategy with the existing ICT masterplans. Based on this case, this study was aimed to make an application of the Enterprise Architecture framework to support the Smart City Masterplan in Bogor City. In addition, a comprehensive analysis of the current ICT conditions, gap analysis, and future targets for Bogor was carried out in this study. The data and information used in this study came from interviews with stakeholders in the Local Government Organization of Bogor, related documents, and information downloaded via the official sites of the Bogor city government. The method applied in this study was TOGAF ADM to design the Bogor Enterprise Architecture framework. The study provides recommendations for the design of Smart Governance Enterprise in the City of Bogor. In addition, based on the results of a gap analysis of business architecture, information systems and, technology, the need for an integrated system, interoperability, budget amount, ICT human resources, and ICT infrastructure needs to be improved, as well as the need for regulations and standards to protect Bogor City e-government products.
High-Resolution Realistic Image Synthesis from Text Using Iterative Generative Adversarial Network

Synthesizing high-resolution realistic images from text description using one iteration Generative Adversarial Network (GAN) is difficult without using any additional techniques because mostly the blurry artifacts and mode collapse problems are occurring. To reduce these problems, this paper proposes an Iterative Generative Adversarial Network (iGAN) which takes three iterations to synthesize high-resolution realistic image from their text description. In the $$1^{st}$$ iteration, GAN synthesizes a low-resolution $$64 \times 64$$ pixels basic shape and basic color image from the text description with less mode collapse and blurry artifacts problems. In the $$2^{nd}$$ iteration, GAN takes the result of the $$1^{st}$$ iteration and text description again and synthesizes a better resolution $$128 \times 128$$ pixels better shape and well color image with very less mode collapse and blurry artifacts problems. In the last iteration, GAN takes the result of the $$2^{nd}$$ iteration and text description as well and synthesizes a high-resolution $$256 \times 256$$ well shape and clear image with almost no mode collapse and blurry artifacts problems. Our proposed iGAN shows a significant performance on CUB birds and Oxford-102 flowers datasets. Moreover, iGAN improves the inception score and human rank as compare to the other state-of-the-art methods.
Inquiry-Based Learning in Computer Science Classroom

Inquiry-based learning in Slovak schools is still considered to be an innovative approach to teaching based on the active exploration of new knowledge by pupils themselves. It allows deeper involvement of pupils in the learning process, encourages motivation and differentiation with respect to individual learning preferences, creates space for pupils to develop cooperation and communication skills. Inquiry is a natural cognitive process for pupils, but its wider application is mostly in biology, chemistry or physics classrooms, while computer science in Slovak schools is still dominated by instructive teaching strategies. In the frame of the National project IT Academy we have focused on different fields of the computer science curriculum and we have implemented the 5E instructional model as an inquiry-based learning approach in 40 primary school lessons and 40 secondary school lessons. We provide teachers with complete lesson plans, including worksheets, supplementary work files and materials, or reference materials. These educational materials are being tested by teachers in Slovak schools. For both primary and secondary school teachers, we organize also professional development courses on innovative teaching strategies in the computer science classroom to make it easier for them to implement these new classroom learning practices. This paper presents the results of a survey on teachers’ perception, attitudes, experiences, misconceptions and barriers to inquiry-based teaching strategies in computer science classrooms as the classroom teacher plays a key role in the successful implementation of these new learning strategies. Our research investigates how different factors affect teachers when considering the inquiry-based learning and its successful implementation in computer science classrooms highlights two major underlying factors, the teacher’s personal contribution factor and a factor representing a collection of the teacher’s readiness and teaching skills, which are further discussed.
A Calibration Algorithm for Real-time Scene-aware Portable Augmented Reality

In order to solve the problem of accurate holographic projection of the point cloud collected by an external high-precision depth camera in HoloLens, we propose an augmented reality calibration algorithm for real-time scene perception. Firstly, we build a portable high-precision real-time sensing system, using external RealSense to collect point cloud data, and the portable host processes and returns the data to HoloLens via a local area network. Secondly, it calibrates the internal parameters of HoloLens' webcam and RealSense depth cameras, then fixed the two cameras for dual purpose calibration, so as to obtain the internal rotation and translation matrix. Finally, the calculated posture computed by the matrix transformation transforms of the virtual object from the RealSense coordinate system displayed in OSG (Open Scene Graph) to HoloLens unified. The Direct X coordinate system is then transformed into the HoloLens Webcam coordinate system, and then the HoloLens API is used to acquire the fixed coordinate system established during the acquisition. At the same time, the virtual object of the holographic projection is accurately merged with the real object, and the spatial anchor is fixed in the real scene, so that the system realizes an accurate and real-time aware augmented reality capability.
Extended abstract - Semantic query languages for knowledge-based web services in a construction context

Since the early 2000s, different frameworks were set up to enable web-based collaboration in building projects. Unfortunately, none of these initiatives was granted a long life. Recently, however, the use of web technologies in the building industry has been gaining momentum again, considered some promising technologies for reaching a more interoperable BIM practice. Specifically, this relates to (1) Linked Data and Semantic Web technologies, and (2) cloud-based applications. In order to combine these into a network of interlinked applications and datastores, an agreed-upon mechanism for automatic communication and data retrieval needs to be used. Apart from the W3C standard SPARQL, often considered too high a threshold for developers to implement, there are some recent GraphQL-based solutions that simplify the querying process and its implementation into web services. In this paper, we review two recent open source technologies based on GraphQL, that enable to query Linked Data on the web: GraphQL-LD and HyperGraphQL
Iberiberism, Leadership and Challenges of Governance in Nigeria

Iberiberism (act of being stupid, especially in leadership) is a monster against leadership and governance. Leadership and governance has been recognized as imperative for the attainment of the political, economic and social objective of any political community. Nigeria is endowed with enormous natural and human resources sufficient to place it among the first 20 developed countries of the world. Despite its huge resource endowment, majority of its population wallow in abject poverty while unemployment and insecurity is growing. The significance of leadership to governance is seen in the fact that good leadership sets the tone and standard of governance. Substantially relying on secondary source of data collection, this paper attempts a conceptual examination of the nexus between iberiberism, leadership and challenges of governance and also analyzes this phenomenon as it pertains to Nigeria. The findings reveal that the history of Nigeria is replete with governance and leadership that in most cases lacked vision and translate into iberiberism, which mostly is engrossed with corruption and political bickering leading to the enthronement of maladministration and mismanagement of public resources, and consequently insecurity, economic setback, and abject poverty.
An Attention-based Recurrent Convolutional Network for Vehicle Taillight Recognition.

Vehicle taillight recognition is an important application for automated driving, especially for intent prediction of ado vehicles and trajectory planning of the ego vehicle. In this work, we propose an end-to-end deep learning framework to recognize taillights, i.e. rear turn and brake signals, from a sequence of images. The proposed method starts with a Convolutional Neural Network (CNN) to extract spatial features, and then applies a Long Short-Term Memory network (LSTM) to learn temporal dependencies. Furthermore, we integrate attention models in both spatial and temporal domains, where the attention models learn to selectively focus on both spatial and temporal features. Our method is able to outperform the state of the art in terms of accuracy on the UC Merced Vehicle Rear Signal Dataset, demonstrating the effectiveness of attention models for vehicle taillight recognition.
Initial Investigation on Affective 4D Mathematics Model for Low Vision Learners (AM4LV)

Towards digital innovation for society 5.0, Mathematics plays roles as a very important subject to trigger critical thinking among students including low vision. Unfortunately, in this digital era, low vision learners still face difficulties in learning Mathematics as they have to adapt the mainstream pedagogical approach, which is totally inappropriate with their learning needs. Most previous studies reveal that low vision learners are lacking in terms of positive interactions that promote two-way communications between teachers and students. The scarcity of this aspect must be challenging for low vision learners because of their limitation in eyesight, which affects their stimulation in learning Mathematics. Therefore, the main aim of this study is to investigate the availability and the needs of affective content particularly in Mathematics specifically for low vision learners. To achieve that, user-centered design approach has been adapted. Mathematics and low vision teachers have been selected as the subjects of this study. Accordingly, the findings of this study reveal that affective content particularly in Mathematics is not yet exist, and that the need for it is urgent.
EFFECT OF ICON MODEL-BASED WHATSAPP MEDIATED INSTRUCTION ON ACHIEVEMENT OF B.ED. STUDENTS DURING CURRICULUM TRANSACTION IN HIGHER EDUCATION

Higher education is the tertiary phase of learning that provides instruction  to the students who are at the  latter adolescents and adulthood stage preparing themselves for the real world of work. Strong higher education in any country prepares competent and skillful citizens and manpower in different streams of education. However without proper facilitation and instruction on the part of college and university teacher, the objectives an goals related to maintaining proper quality at higher education cannot be achieved especially in the college of teacher education during curriculum transaction.. In order to maintain adequate quality at higher education level innovative and effective instructional strategies must be followed by the facilitators in different colleges and universities. It is notable that students of 21 st century are not interested to listen traditional method based lecturers in higher education institutions and demanding for more resourceful environment which must be based on learner centric and learning centric climate. They are taking active participation in different social websites and interacting with ICT based media for the purpose of learning and preparation of their examination. Such frequent use of social websites and Apps like Facebook, Twitter, Whats App  by students at higher education creates an question in the mind of researcher that: Can such websites be used as a media for designing instruction based on Interpretation Construction Model for facilitating students of Higher Education in terms of  improving their achievement by satisfying their learning need and demands in  21 st century ?  As a teacher of Higher education, an experimental  research has been carried out at Nabakrushna Choudhary college of teacher education by  the researcher for  exploring the effectiveness of one  innovative and   instructional strategy i.e. ICON model based Whats App Mediated instruction on achievement B.Ed.students.  The main objective of the study was to find out the effect of ICON Model based Whats App mediated instruction on achievement of B.Ed. students. Post Test only Experimental research methodology has been carried out to conduct the study. It is found that thee exist significant difference in between control group and experimental group with respect to achievement of B.Ed students. It is suggested that in higher  education system Whats App can be utilized as an effective media for using ICON model of constructivism.
La legge n. 219 del 2017 e la disciplina del fine-vita tra principi costituzionali e problemi aperti. Spunti di riflessione

The law no. 219 of 2017 intervened, after an almost thirty-year debate, to introduce a discipline, though still incomplete, of the end of life. It is the first legislative intervention expressed in a matter on which, until recently, there were doubts that the State could intervene. The legislation is constructed by general clauses, which incorporate the jurisprudential right, guaranteeing that the person has possibility for autonomous decisions on how to live the terminal phases of a pathological state that approaches to death. However, it cannot be assumed that it is only a recognition of the already living right, since, in art. 1, the definition of the axiological framework of reference contains important elements, which open the way to further orderly developments. In this sense go the disarticulation of therapeutic self-determination from the right to health, as well as the qualification of the right to life as a subjective right, capable of balancing with the other constitutional rights. This determines new balances between constitutional values, which have immediate repercussions on the legislation in civil and criminal matters, of which, as the Cappato case shows, it becomes necessary to carry out an interpretative or legislative adaptation. The article wants to highlight how the discipline set by the law n. 219 of 2017, from a constitutional point of view, do not limits itself to filling a gap in the legal system by incorporating the interpretation of constitutional principles already established in the courtrooms, but contains elements that could push this interpretation towards further outcomes, with the recognition of new and wider spaces of decision for the individual.
Usability Evaluation of Mobile Learning Applications

Mobile learning is creating new opportunities for learning anytime, anywhere by using mobile devices. Mobile learning supports continuous access to the learning process and with the arrival of mobile learning, educational systems are changing. The availability of mobile applications is increasing speedily and with the increased processing power available with mobile devices, developers are increasing the variety of services. The interface of mobile educational apps ought to be compatible with the cognitive skills of children to provide higher learning expertise. In mobile learning apps, students are provided audios, videos, and texts related to the study material with the help of which they can learn their respective subjects and can acquire more knowledge and understanding about the concept. Therefore, this paper will provide the feedback for mobile learning applications using testing method, that is, think aloud testing methodology. Usability evaluation is done by practitioners to gather feedback from users about a website or application, its focus on how well users are satisfied, how well they can use the product to achieve their goals, how well they can learn from the product, and how well they are able to discover and explore the content. Usability evaluation has a variety of methods to gather feedback from the user. In this paper we are focusing on usability evaluation of mobile learning applications using Think Aloud testing, which is one of the most preferred methods. Think Aloud Testing is one in which the test users are said to verbally express their thoughts, feelings, and opinions while interacting with mobile learning application and a direct observation can be made as the users are asked to think out loud. If a task is complex, then the user can make periodic report to think aloud while performing the task at the same time. Think Aloud is a cheaper method as no special equipment is required for it and the practitioner can simply sit next to the user and can gather the feedback.
Design Science for PhD Research in the Software Engineering Domain

The keynote introduced the principles of Design Science with the perspective developed by Prof. Roel Wieringa in his book "Design Science", clearly distinguishing between questions of knowledge and engineering problems, and introducing the research cycles that correspond to each case. A rigorous framework for the structuring and development of Doctoral Thesis work will be presented from a methodological point of view and with concrete examples, which participants will be able to apply to their Doctoral Thesis work. The final objective is that doctoral students know how to apply the principles of Design Science to the development and management of their scientific work and can use an effective research methodology, well supported by clear concepts and efficient in their application.
Analise Petrofísica da Formação Agua Grande, Bacia do Recôncavo, Bahia, Brasil

This work has as objective to analyze electrical and hydraulic parameters, such as permeability, total and effective porosity, cementation index, conductivity and clay volume, which characterize one of the main hydrocarbon reservoirs of the Rec ôncavo Basin in Brazil: the reservoir associated with the Água Grande formation.Rock samples were obtained in outcrops of Água Grande formation along federal highway BR-101 and the electrical measures were performed in the laboratory of petrophysics of