Reviewerly/exHarmony huggingface dataset:
Neural control of balance in increasingly difficult standing tasks

For almost 150 years, researchers have been intrigued by the complex neural control of standing balance. Despite accumulating evidence showing cortical involvement, much is yet to be learnt about the nuances of how the motor cortex (M1) tunes muscle activation in standing. This thesis examined the neural input to leg muscles in increasingly difficult standing tasks. It was found that the net output from M1 sets the activation of leg muscles and consequently influences postural sway. This net M1 output is determined by a combination of inhibitory and facilitatory processes which likely account for different aspects of postural control like cognitive influences, planning and preparation for perturbations. Additionally, examination of the synchronized output from the cortex to multiple muscles showed that the cortex favors reciprocal control, which is mechanically advantageous and also costs less energy. Also, such synchronized outputs are tailored to the biomechanical demands of each task. Finally, a preliminary examination of the factors contributing to individual differences in neural control of standing was conducted. Each individual’s intrinsic neural excitability (possibly driven by genetics or plasticity due to previous experiences) influenced how they controlled balance in the increasingly difficult tasks. Additionally, cortical excitability was associated with self-reported balance confidence and likely mediates the effect of this cognitive attribute on motor performance. In conclusion, the findings of this thesis suggest that the cortex plays a role in the higher order planning and processing required for determining muscle activation patterns and maintaining balance in standing.
More efficient optical sectioning structured illumination microscopy

In this paper, a structural illumination based technology for microscopic surface topography measurement is investigated, in which only one shot structural illumination image is grabbed and a more efficient optical sectioned image reconstruction algorithm based on Hilbert transform was proposed. Compared with other methods, the technology can avoid strip artefacts problems of in-focus images resulting from the sinusoidal phases mismatch in spatial domain in conventional three-step phase-shifting since the phase-shifting steps decreases from three to one, and the measurement time is decreased effectively. The experimental testing is carried out to verify the feasibility and its measurement accuracy.
Evaluation of an Agile Maturity Model: Empirical Evidences for Agility Assessments

Software process reference models (such as Capability Maturity Model Integration – CMMI–DEV) have been used for years for software process evaluation and improvement. However, when a team uses agile methods for software development, these models hinder sustaining agility in higher maturity levels. This is the reason why some agile maturity models have been proposed in the last years. Although there are some models suggested in literature, few studies actually evaluate these models with real teams. The objective of this study is thus to evaluate an agile maturity model – the Agile Compass – creating empirical results for agile teams in the process improvement field. We conducted this research with two field studies in two different agile teams: an ethnographic study and a focus group. Our findings confirmed the need for empirical validation of academically–proposed models. The Agile Compass was effective in creating a maturity picture for the teams, but both teams seemed to prefer a more “objective” evaluation.
Towards an Agile Development Environment

The demand for software engineering support environment was evident since the 70s. It was necessary to control the integration between processes, tools and developers in order to increase software quality and productivity. Research projects produced several environments which introduced important concepts such as central artefact repository, well-defined and enactable software processes, as well as supporting tools. Later, agile methods emerged as a solution to overcome strict software processes, however it also demanded support tools to facilitate its adoption in software organizations. Several works report the use of agile practices and support tools, however, they do not bring about the structure of a software engineering environment that integrates the managerial cycle and agile practices. This paper presents the design of a software engineering environment which is based on Application Life Cycle (ALM) and SCRUM principles integrated with management and construction tools. The proposed design was validated with practitioners and a comparison with previous development environment is also presented. This work contributes to support novel enterprises to set up a work environment for agile practices.
TRANSCENDENTAL MATERIALISM OF METHOD

The classical concept of method is based on the cognitive ability of the “object of the living” and serves as a rationale for the relationship between the phenomena of sensation and thinking in the processes of interaction of the thinking being with an indefinitely large number of objects in a given area of existence. At the same time, knowledge of the signs of the existence of any object of concrete existence, which has a complex structure of regular signs of changes in the states and properties of its existence, is difficult in knowledge. In this regard, the subject of “pure abstraction” should be considered as the simplest in knowledge, knowledge of the signs of changing states and properties of which cannot be represented in the experience of sensations and thinking of the “object of the living”. In addition, in the worldview of a specific existence in a given area, the concept of a method is defined as a path from ignorance to knowledge, from simple knowledge to complex knowledge. And as a way to overcome this path is the “ascent” from the “abstract knowledge” to the “knowledge of the concrete”. However, the accepted terminology in the definition of the method shows a sign of contradiction due to the fact that in the concept of “abstract knowledge” there can be no signs of changes in the states and properties of the object, which could be felt and conceivable in the experience of the “living thing”. Because “abstract knowledge” by its definition can only be an attribute of the subject of “pure abstraction”, knowledge of the signs of changing states and properties of which are impossible in the experience of sensations and thinking of the thinking being. Moreover, the term “abstract”, which determines the knowledge of the “object of the simple” in the experience of thinking beings, can only be a term that defines the ratio of the ability of the representations of the being thinking about the object of “simple knowledge”, showing signs of concrete existence in a given area. Therefore, in the representation of transcendental materialism in the concept of the method is the possibility of “mental reincarnation” of complex knowledge about the signs of changes in the states and properties of the object of concrete existence, by “descending” to its “sources” in the signs of changes in the states and properties of the object “pure abstraction”. From the “knowledge of the complex” to the “knowledge of the simple”.
The effectiveness of android-based physics interactive media to train students’ thinking and process skills

The purpose of the research is to describe the effectiveness of Android-based Physics interactive media to train students' thinking and process skills. The thinking defined are: analysing, evaluating, applying, generating ideas, expressing ideas. The process skills defined are: observing, classifying, inferring, predicting and communicating. The type of research is pre-experiment by using a one-shoot case study design. The effectiveness of the media is reviewed from the success of training thinking and process skills, as well as student responses. The subject of this research is 40 high school students. The measurement of thinking, process skills, and student response use a Likert scale. Data analysis used is descriptive statistics and correlation. Android-based physics interactive media is effective if the percentage of thinking, process skills, and student response ≥ 61%, and the correlation coefficient between thinking and process skills r ≥ 0.7. The results obtained are 1) the score of students' thinking is categorized good, 2) the score of process skills are categorized good, 3) Students' response is categorized very good, and 4) the correlation coefficient between thinking and process skills is r = 0.73. The results showed that Android-based physics interactive media is effective to train students' thinking and process skills.
Chaos Theory and Systems in Cloud Content Security

Cloud computing involves storing data using a third party that ensures that confidential data cannot be accessed even by the cloud itself. Thus, security is one major issue in cloud computing. Recent advancements in exploiting chaotic systems' sensitivity to initial conditions, and their ability to extract strings of random numbers for confusion and diffusion have helped enhance security. They can provide resistance from statistical attack and protection against reconstruction dynamics. However, the concept of chaos for security is still in its emerging stages. This chapter presents how chaos theory can be used for random number generation to further secure data in the cloud. The authors have discussed and compared some popular methods for authentication and encryption of data, images, and videos. The overview of chaos engineering discusses the discipline of experimenting on multi-server systems to ensure its ability to tackle glitches.
Eye positioning based on windowed gray-scale integral projection algorithm

Eye positioning is an important prerequisite for vehicle-mounted fatigue driving monitoring. In this paper, a windowed gray-scale integral projection algorithm based eye-positioning method is introduced. Firstly, the human eye is positioned by Adaboost algorithm, then the eyebrows are separated by the windowed gray-scale integral projection algorithm, consequently, the accurate positioning of human eye parts is achieved. The experimental results show that the separation effect is obvious and the speed of human eye positioning is significantly improved.
Cascading BGP face recognition method based on heuristic information

Binary gradient Pattern (BGP) is a simple and effective face recognition descriptor that is robust to illumination, expression, and occlusion. It has achieved excellent results in face recognition applications. However, there are two shortcomings in the BGP operator: Firstly, the BGP operator is a universal operator, which does not reflect the particularity of human faces in the process of identifying faces. Secondly, the feature extraction of BGP is performed once on the face, and the texture information obtained is not rich enough. In this paper, we propose a cascading BGP method based on heuristic information. The improved algorithm is fully verified in the Yale library and the ORL library, and the recognition accuracy is significantly improved compared with the original BGP algorithm.
MUAVET – An Experimental Test-Bed for Autonomous Multi-rotor Applications

Multi-rotor flying vehicles (referred as UAVs here) are well suited for many applications, including patrolling, inspection, reconnaissance or mapping and they are already used in many cases. In most cases they are used in manual mode, mainly due to legal issues, but autonomous methods and algorithms for UAV navigation are under extensive development nowadays. This article describes a test-bed system for development of the fully autonomous multi-UAV systems called MUAVET (Multi-UAV Experimental Test-bed). The system incorporates several UAVs, communicating with the base station, able to be controlled either locally from the on-board-running control application, centrally from the base station, or by any combined approach. The system provides basic safety features and autonomous/automatic functions which significantly reduce the risks of crash or loosing the UAV, even in case of wrong command from the user application. The function and the performance of the MUAVET system is demonstrated in the search-and-rescue scenario of multiple UAVs searching for the visually-marked ground objects placed in the designated area and cooperating with the autonomous ground vehicle supposed to reach the found targets on ground.
Social Media and Social Networking in Digital Libraries

The modern knowledge economy has transformed library and information organizations to adopt and embrace digital social media platforms. Proliferation and growth of social media and social networking technologies continue to play pivotal roles in establishment and operation of digital library and information systems in organizations. The purpose of the chapter is to examine the extent to which information professionals and practitioners understand the impact of social media and social networking technologies on digital library and information systems. The author also analyzes how information professionals manage and promote the adherence to copyright and intellectual property laws in digital library contexts. This chapter specifically discusses the rationale for social media and social networking in digital library and information systems; emerging social media platforms and their applications; legal aspects of social media, copyright and intellectual property protection, and risk management; as well as professional ethics and guidance on social media.
Nar-A-Viz: A methodology to visually extract the narrative structure of text

Being able to tell and understand stories is a key component for efficient communications. The narrative structure is the structural framework that underlies the order and manner in which this story is presented to a reader, listener, or viewer, this work presents a novel visualization methodology that can be used to extract the narrative structure of texts and present in a visual, immediate and intuitive manner. This tool efficiently summarizes the content of a text, and it also allows in depth analysis of the narrative structure. The characteristics and use of the tool are exemplified using a TED talk by Hans Rosling. Its potential then is shown using two historical speeches: President Donald Trump’s inaugural speech and I Have a Dream by Dr. Martin Luther King Jr.
“Almost there”: sonically controlled vibrators, sound, and emotions

Purpose The purpose of this paper is to demonstrate how practice-led research within the sonic practice references what Smith and Dean (2009) describe as the “The Iterative Cyclic Web,” and oscillations between different modes of research and practice throughout the methodology. Design/methodology/approach This paper uses this process to document the construction of a sonically based erotic artwork, “Almost there,” which used sonically controlled vibrators in order to generate vocal content. Findings The paper found that it was important to oscillate between modes of research and practice in order to create a conceptually concise artwork that functioned as a Gestalt of both practice and research. Originality/value The unique approach to audio collection within this sonic artwork, and the time taken to collect this source material, makes it a unique vehicle for the consideration of “The iterative Cyclic Web.”
User Profile in Absence of Ground Truth for Mobile Users

Mobile user personalization is used to increase user engagement on many platforms. One way to achieve personalization is by building user profiles, which encompass certain attributes of mobile phone users. Mobile manufactures and service providers often collect data of their users in order to provide personalized services. This collected data is rich in user behavior, but seldom has enough ground truth information collected directly from users to build a user profile. In this paper, we address this problem and provide a framework for developing user profile of mobile users in absence of ground truth data. Our approach consists of a one-class classification technique to address this issue. We test our method on data of one million mobile phone users and show that the predicted accuracy is close to that achieved using a supervised model. We further extend this method to predict other attributes of the user, again getting a good accuracy.
A Hybrid Multilingual Sentiment Classification Using Fuzzy Logic and Semantic Similarity

Classifying tweets into classes (Positive, Negative or neutral) or extracting their sentiments know in recent years a great development, and researchers try to find new methods and approaches that give good results. In this paper, we propose a new hybrid approach based on the semantic similarity using the WordNet dictionary and the fuzzy logic with its three important steps (Fuzzification, Rule Inference/aggregation and Defuzzification) for classifying tweets into three classes: positive, negative or neutral. The experimental results show that our approach outperforms some other methods from the literature.
Smart Enhanced Context-Aware for Flipped Mobile Learning: SECA-FML

Today, thanks to the development of mobile technologies, mobile learning has become widespread. New methods of mobile learning have emerged; we have heard lately by the flipped classroom. This method involves reversing the task traditionally performed in class with the task traditionally performed at home. When we talk about mobile learning, we are talking about a learner who learns in a mobile context and in different situations. Hence, the need for adapting educational content and contextual mobile learning becomes critical. Several research studies have been performed taking into account the context notion. According to our research few scientific works have been proposed taking into account the context in the flipped classroom. In this paper, we present the model of our approach, called Smart Enhanced Context-Aware for Flipped Mobile Learning: SECA-FML. This approach takes into account the different context dimensions in order to provide learners with a content format adapted to their contexts.
Active Learning by Clustering for Drifted Data Stream Classification

Usually, during data stream classifier learning, we assume that labels of all incoming examples are available without any delay and they are used to update employing predictive model. Unfortunately, this assumption about access to all class labels is naive and it requires relatively high budget for labeling. It causes that methods which can train data stream classifiers on the basis of partially labeled data are highly desirable. Among them, active learning [1] seems to be a promising direction, which focuses on selecting only the most valuable learning examples to be labeled and used to produce an accurate predictive model. However, designing such a system we have to ensure that a chosen active learning strategy is able to handle changes in data distribution and quickly adapt to changing data distribution. In this work, we focus on novel active learning strategies that are designed for effective tackling of such changes. We propose a novel active data stream classifier learning method based on query by clustering approach. Experimental evaluation of the proposed methods prove the usefulness of the proposed approach for reducing labeling cost for classifier of drifting data streams.
Protocols for Secure Management of Multidimensional Data Arrays

Popular technologies such as data mining and online analytical processing are widely known as technologies heavy-based on the usage of multidimensional data structures. However, at the same time, development of the security countermeasures leaves much to be desired. Currently, there is no complex multidimensional data processing system capable to ensure proper security levels exist. In the paper, we propose security protocols which formed the basis of our solution aimed to provide security for multidimensional data storage and processing. We describe basic protocols for data read and write operations adopted for the features of multidimensional data structures and security assumptions.
Averaged Logits: An Weakly-Supervised Approach to Use Ratings to Train Sentence-Level Sentiment Classifiers

As an important aspect of review mining, sentence-level sentiment classification has received much attention from both academia and industry. Many recently developed methods, especially the ones based on deep learning models, have centred around the task. In a majority of the existing methods, training sentence-level sentiment classifiers require sentence-level sentiment labels, that are usually expensive to obtain. In this research, we propose a novel approach, named 'Averaged logits', that uses the prevalently available ratings, instead of sentence-level sentiment labels to train the classifiers. In the approach, the rating of a review is assumed to be the 'average' of the sentiments of the individual sentences. We experiment with this idea under the framework of the recurrent neural network model. The results show that, the performance of the proposed approach is close to that of the traditional SVM and Naive Bayes classifiers trained by labelled sentences when their training sizes are approximately equal, and close to that of the neural network based classifiers trained by labelled sentences when the proposed approach uses approximately 5 times more training samples.
High-speed multichannel MAÉS analyzers based on BLPP-2000 and BLPP-4000 photodectector arrays

The main directions in the development of the spectral systems for scintillation atomic emission analysis of powdered geological samples are aimed at increase in the sensitivity, spectral resolution, and speed of the spectrum analyzers to reduce the detection limits. The goal of the study is developing of high-speed MAÉS analyzers with hybrid assemblies of the arrays of 14 multichannel photodetectors of two types: high-sensitivity BLPP-2000 and BLPP-4000 photodetector array with high spatial resolution and theoretical estimation of the signal-to-noise ratio when recording scintillation and integral spectra with aforementioned photodetectors. The high-speed MAÉS analyzers with BLPP-2000 and BLPP-4000 photodetector arrays are designed so as to provide parallel readout of photodetectors in hybrid assemblies. They consist of 14 BLPP 2000 or BLPP 4000 photodetectors and records the spectra in the 190 – 350 nm wavelength range on a «Grand» spectrometer. The minimum exposure time is 0.9 and 1.7 msec, respectively. It is shown that in measurements of spectral-line intensities using BLPP-2000, the signal-to-noise ratio is 3 times higher in integral analysis and 5 times higher in scintillation analysis compared to measurements with BLPP-4000 photodetector array.
JSON-based Apparel Fabric Query Micro-program Application

With the continuous development of information technology, the application market has also gradually innovated. Light applications are favored by people because of its small footprint, easy to use, and fast running. JSON (JavaScript Object Notation) is considered by developers to be an ideal data exchange language because of its simplicity and ease of use, and is widely used in Web development.Compared with XML, JSON has more advantages in Web data exchange processing. JSON is used to cache data, which is convenient for storing complex data, and is more conducive to client parsing and use.
Yacht Roaming Simulation Algorithm based on ELM

This paper used Google earth as data source, used the extreme learning method to establish yacht motion equations, and used PC as a platform to build a yacht simulator. The motion equations could make the virtual scene in simulator conform to the actual motion state of yacht. This method provides a new idea to realize navigation simulator. That will make the ship driving simulation training more realistic, more efficient and low cost.