Reviewerly/exHarmony huggingface dataset:
Construction and analysis of hidden Markov model for piano notes recognition algorithm

In this subject, the model recognition method was adopted, namely, the multi-note model based on the hidden Markov process was established by using the multi-note as the basic modeling unit. And the related modules in HTK were recompiled to build a multi-note recognition model, thus the features o f a multi-note audio file were extracted; An optimization and updating scheme was proposed from the algorithm flow and evaluation model. By effectively evaluating the data state of the piano note model, an effective recognition model was established, and the corresponding recognition results were given. Then based on the analysis of the principle of commonly used audio file parameterization and combined with the characteristics of multi-note audio, the existing feature extraction modules in HTK were optimized; finally, the real time robust recognition of single notes, the HMM modeling of multi-note and the recognition of multi-note HMM model were successfully realized.
Fast non-uniform radiance probe placement and tracing

Light field probes extend standard precomputed light probes to reduce light leaks and enable efficient filtered world-space ray tracing queries. When probes are placed uniformly in the scene volume, they permit an efficient querying algorithm. Manually increasing the grid resolution, however, is the only way to eliminate geometric feature undersampling, increasing the memory and computation cost of the approach. We present an automatic non-uniform probe placement method to correctly sample visibility information and eliminate superfluous probes. We organize non-uniform probes in an efficient structure for fast run-time ray tracing. Our probe placement relies on 3D scene skeletons and a gradient descent-based refinement to achieve full geometric coverage and reduce grazing angle sampling biases. Our adaptive probe ray tracer caches visibility information in a sparse voxel octree, augmenting probes with metadata used to apply a hierarchical-Z acceleration when marching rays in distant probes. We benchmark our approach on a variety of scenes and consistently demonstrate better performance, and fewer probes, in equal-quality comparisons to the state-of-the-art.
Comparison of Agile Method and Scrum Method with Software Quality Affecting Factors

The software industry used software development lifecycle (SDLC) to design, develop, produce high quality, reliable and cost-effective software products.To develop an application, project team used some methodology which may include artifacts and pre-defining specific deliverables.There are different SDLC process models such as waterfall, iterative, spiral and agile model available to develop a quality product.In this paper we focus only on agile software development model, and Scrum model and their techniques.There are many papers and books written on agile methodologies.We will also use their knowledge in this paper.To collect data for comparison of agile method with software quality affecting factors, an online questionnaire survey was conducted.The survey sample consisted of software developers with several years of industry experience using agile methodologies.The main purpose of this study is to compare soft-ware quality affecting factors with agile and scrum model.
Innovative activity of teachers - myth or reality?

Introduction. The innovative activity of teachers is usually described as the creative activity of a sole inventor and the activity of mass teachers, who follow prepared algorithms in the framework of large-scale innovative projects. It is obvious that these types of activity differ considerably. More accurate structuring of innovative activity of the teacher will allow experts to describe more precisely objective essence of innovative processes and to find out more effective means of their stimulation both at the individual level of the teacher and at the level of a national educational system. The aim of the publication was to discuss the questions of what is innovative activity of the teacher; whether innovative activity really exists in mass practice; how innovative activity can be stimulated. Methodology and research methods. The research was based on the systematic approach. In the course of the research, the analysis of scientific and methodological literature and the survey among the teachers aimed at identifying the characteristics of their innovative activity were employed. Results and scientific novelty. The whole cycle of promoting the use of innovations into practice is thoroughly examined: from subjectivity to objectivity; from creativity to reproductive activity; from objectively new result to the product of a sample; from resistance of environment against innovation to stimulation and coercion to its realisation. Characteristics of innovative activity of the teacher are determined and described by the level of distribution of the forthcoming innovation and the attitudes of professional community towards it. It is proposed and proved that the innovation activities of the teachers should be separated into three types: (type I) creative activity of the individual aimed at development of means, methods and technologies to obtain objectively new results; (type II) activities of the teachers focused on the implementation of ready tested innovations, but new for teacher-friendly professional environment, (start-up); (type III) innovative activity of the teachers as a routine operation in the innovation system as its element. The activity of the type I is not widespread; such activity cannot and should not be mass - not everyone can be engaged in it. Design activity corresponds to the type II; type III - activity of performers with the total development of innovation becoming the accepted norm. Mass introduction of a novelty is an innovative process, but not at the level of a certain subject, since a teacher, who acts (often involuntarily) on well-developed samples and algorithms, is not an innovator. Practical significance. The dependence of efficiency of pedagogical innovations on the model of state policy in education is demonstrated. The reasons of the development gap of the Russian educational system in the field of innovations from the systems of other countries are disclosed. The conditions specific to each type of a teacher’s innovative activity, which need to be created for successful and more rapid implementation of progressive innovations, are allocated.
Detection of Social Network Toxic Comments with Usage of Syntactic Dependencies in the Sentences

Social networks sometimes become a medium for threats, insults and other components of cyberbullying.A huge number of people are involved in online social networks.Hence, a protection of network users from anti-social behavior is an important activity.One of the major tasks of such activity is automated detecting the toxic comments with threats, insults, obscene etc.The bag of words statistics and bag of symbols statistics are typical features for the toxic comments detection.The effect of syntactic dependencies in sentences on the quality of detection of the social network toxic comments is studied in the article for the first time.Syntactic dependences are relationships with proper nouns, personal pronouns, possessive pronouns, etc. Twenty syntactic features of sentences have been verified in the total.The paper shows that 3 additional specific features significantly improve the quality of toxic comments detection.These three features are: the number of dependences with proper nouns in the singular, the number of dependences that contain bad words, and the number of dependences between personal pronouns and bad words.The experiments are based on data from kaggle competition "Toxic Comment Classification Challenge".For our experiments, the original dataset with 159751 comments was reduced to 106590 comments due to problems with human-free extraction of the syntactic features.We use mean of the error rates for each types of misclassification as the metric of quality due to unbalanced dataset.A decision tree is used as a classifier.The decision trees were synthesized for two splitting rules: Gini index and deviance criterion.
Designed with Me: Empowering People Living with Dementia

This paper presents on- going research that adopts an open and truly collaborative approach to working with people living with dementia by recognising and utilising the inherent personal creative abilities that every individual possesses no matter their cognitive ability. The research project entitled  Designed with Me, via a series of carefully developed innovative co- design workshops, supports people living with dementia to express themselves fully in  live design collaborations. Every individual's input in this research is highly valued and is held in the same esteem as any other collaborator. In this project, participants become collaborative designers helping to propose possibilities, evaluate and select solutions, give their knowledge and skills freely, and generally make things happen.  Designed with Me highlights clearly that people living with dementia can continue to make a significant contribution to society long after a diagnosis of dementia.
Designing Cognitive Ergonomics Features of Medical Devices. Aspects of Cognitive Interaction

(2019). Designing Cognitive Ergonomics Features of Medical Devices. Aspects of Cognitive Interaction. The Design Journal: Vol. 22, Running with Scissors: 13th International Conference of the European Academy of Design, Dundee, 10-12th April, 2019, edited by Louise Valentine, Joanna Bletcher and Leon Cruickshank, pp. 463-474.
New Ternary Power Mapping with Differential Uniformity Δ&lt;i&gt;&lt;sub&gt;f&lt;/sub&gt;&lt;/i&gt;≤3 and Related Optimal Cyclic Codes

In this letter, the differential uniformity of power function f(x)=xe over GF(3m) is studied, where m≥3 is an odd integer and $e=\frac{3^m-3}{4}$. It is shown that Δf≤3 and the power function is not CCZ-equivalent to the known ones. Moreover, we consider a family of ternary cyclic code C(1,e), which is generated by mω(x)mωe(x). Herein, ω is a primitive element of GF(3m), mω(x) and mωe(x) are minimal polynomials of ω and ωe, respectively. The parameters of this family of cyclic codes are determined. It turns out that C(1,e) is optimal with respect to the Sphere Packing bound.
Heuristics for Two Depot Heterogeneous Unmanned Vehicle Path Planning to Minimize Maximum Travel Cost

A solution to the multiple depot heterogeneous traveling salesman problem with a min-max objective is in great demand with many potential applications of unmanned vehicles, as it is highly related to a reduction in the job completion time. As an initial idea for solving the min-max multiple depot heterogeneous traveling salesman problem, new heuristics for path planning problem of two heterogeneous unmanned vehicles are proposed in this article. Specifically, a task allocation and routing problem of two (structurally) heterogeneous unmanned vehicles that are located in distinctive depots and a set of targets to visit is considered. The unmanned vehicles, being heterogeneous, have different travel costs that are determined by their motion constraints. The objective is to find a tour for each vehicle such that each target location is visited at least once by one of the vehicles while the maximum travel cost is minimized. Two heuristics based on a primal-dual technique are proposed to solve the cases where the travel costs are symmetric and asymmetric. The computational results of the implementation have shown that the proposed algorithms produce feasible solutions of good quality within relatively short computation times.
Information-seeking behaviour of security studies students: A case study

Background: Undergraduate students need information for various reasons. However, it is not a straightforward activity in retrieving the relevant information for accomplishing various needs. This research is therefore justified as it aims at understanding information needs of undergraduate students who are drawn from security organisations. Objectives: The main objective of this study was to analyse information needs, sources and seeking patterns of security studies at Mzuzu University. Method: The study adopted a mixed methods approach by sending a questionnaire to 108 students and conducting a set of three focus group discussions. The study was informed by Kuhlthau's information search process model. Results: The study finds that most students preferred Internet as a source of information. The study further finds that most students need information mainly for academic activities, accomplishing assignments, preparing examinations and completing research projects. Most students preferred the search engines as the starting point for an information search. Feelings proposed by Kuhlthau's information search process model, which include anxiety, optimism, uncertainty and excitement, were experienced by most of the students as they started an information search for completing an assignment. However, there exist a number of challenges that affect students' information behaviour, such as the lack of online information literacy skills, poor Internet access and shortage of computer laboratories. Conclusion: Unlike previous studies, this study establishes that the information needs of upgrading security studies students are focussed more on academic and work-related purposes. Information seeking and gathering is a key component of their work, as they gather information related to criminal activities and general intelligence. Upgrading undergraduate students have additional information needs that go beyond their academic needs. There is a need to design information interventions that would enhance their information search experience based on some of the pointers provided by Kuhlthau's model. In view of the above, it can be argued that Internet is becoming a popular source of information in the 21st century; hence, there is a need to provide e-support that would reduce students' negative feelings and enhance their Internet search process, thereby improving the overall quality of education.
Debate through design. Incorporating contrary views on new and emerging technologies

(2019). Debate through design. Incorporating contrary views on new and emerging technologies. The Design Journal: Vol. 22, Running with Scissors: 13th International Conference of the European Academy of Design, Dundee, 10-12th April, 2019, edited by Louise Valentine, Joanna Bletcher and Leon Cruickshank, pp. 723-735.
Modeling of the hourly horizontal solar diffuse radiation in Sanliurfa, Turkey

Horizontal diffuse solar radiation has been calculated over various models by using the total radiation data obtained from the horizontal surface due to reasons such as lack of adequate measurements and expensive measuring instruments. In this study, the measurements were calculated using the obtained data between the years 2009 and 2016 from solar radiation measurement system with solar tracking system, which belongs to the Department of Mechanical Engineering, Sanliurfa Harran University, Turkey. Three horizontal solar diffuse radiation models have been proposed by using the relationship between the diffuse radiation ratio and the clarity index obtained by eight years? data. Horizontal solar diffuse radiation values were calculated and compared with the measurement data for Sanliurfa by using 15 models of diffuse radiation given in the literature and the results obtained from the models. The statistical errors of the proposed models and 15 different diffusive radiation models were calculated. As diffuse radiation varies with time, it is determined that modelling of Model 1 and Model 2 obtained from Sanliurfa data gives better results in terms of clarity index constraints. Furthermore, although the desired success cannot be achieved with Model 2 in terms of tstat, it has been determined that the relevant model provides better results than many models when compared to statistical errors. With the improvements to be made on Model 2, a local estimation model is thought to give better results.
Stochastic Optimization of Quantum Programs

We introduce Markov chain Monte Carlo quantum (MCMCQ), a novel compiler-level optimization of quantum programs that accounts for the emerging quantum programming mode. MCMCQ is the first systematic approach for stochastic quantum-program optimization, targeting program performance, correctness, and noise tolerance. An evaluation of MCMCQ over 500 quantum programs confirms its effectiveness.
Majority Rule in Harmonic Serialism

Majority Rule is an unattested process where agreement is controlled by the largest class in the input. As a function from inputs to outputs, Majority Rule requires more computational expressivity than do attested phonological transformations. This paper examines how Majority Rule arises in parallel Optimality Theory and Harmonic Serialism. It is shown that in HS, Majority Rule relies on globally evaluated output constraints, which are known to produce computationally complex pathologies. However, without them, HS is unable to produce iterative harmony at all. We propose adopting directional constraint evaluation in HS as a way of modeling harmony while maintaining local representations.
PLANETARY3D: A PHOTOGRAMMETRIC TOOL FOR 3D TOPOGRAPHIC MAPPING OF PLANETARY BODIES

Abstract. Planetary remote sensing images are the primary datasets for high-resolution topographic mapping and modeling of the planetary surfaces. However, unlike the mapping satellites for Earth observations, cameras onboard the planetary satellites generally present special imaging geometries and configurations, which makes the stereo photogrammetric process difficult and requires a large number of manual interactions. At the Hong Kong Polytechnic University, we developed a unified photogrammetric software system, namely Planetary3D, for 3D topographic mapping modeling of various planetary bodies using images collected by various sensors. Planetary3D consists of three modules, including: (1) the pre-processing module to deliver standardized image products, (2) the bundle adjustment module to alleviate the inconsistencies between the images and possibly the reference frame, and (3) the dense image matching module to create pixel-wise image matches and produce high quality topographic models. Examples of using three changeling datasets, including the MRO CTX, MRO HiRISE and Chang’E-2 images, have revealed that the automatic pipeline of Planetary3D can produce high-quality digital elevation models (DEMs) with favorable performances. Notably, the notorious jitter effects visible on HiRISE images can be effectively removed and good consistencies with the reference DEMs are found for the test datasets by the Planetary3D pipeline.
Category-Level Adversaries for Semantic Domain Adaptation

Recent advances in deep learning, especially deep convolutional neural networks, have led to great performance improvement over semantic segmentation systems.Unfortunately, training deep neural networks (DNNs) requires a humongous amount of labeled data, which is laborious and costly to collect and annotate.Thus, plenty of works have proposed an alternative solution to ease the training set creation by using synthetic data.However, models trained on these kinds of data usually under-perform on real images due to the well-known issue of domain shift.To address it, we propose a generative adversarial network (GAN)-based framework called category-level adversarial adaptation networks (CAA-Nets) for domain adaptation in the context of semantic segmentation.Considering semantic predictions that contain spatial and structure information of images, our idea is to make use of this character by imposing discriminators on the semantic predictions.Different from existing works, the proposed framework utilizes a category-level discriminator in the output space to shrink the gap between real and synthetic images.Similar to reinforcement learning, we take final results as a guide to update parameters in the right direction by use of the output-based discriminator.Moreover, to further enhance the performance, we construct an image-based generator and discriminator pair to distill the feature representations obtained by a DNN.Taking advantage of these modules, our model can achieve competitive performance compared with some existing methods.To showcase the generality and scalability of our approach, we evaluate the proposed method on the Cityscapes dataset by adapting from GTAV and SYNTHIA datasets, where the results demonstrate the effectiveness of our method.
Adults’ readiness for online learning in the Czech Republic and Latvia (digital competence as a result of ICT education policy and information society development strategy)

The study examined adults' readiness for online learning in the Czech Republic and in Latvia. This paper describes and compares the research results in the Czech Republic and Latvia. The outcomes of the study show that there is no statistically significant difference in adults' readiness to study online between both countries. Statistically significant differences were found in the Czech Republic – adults in the age group 18-29 had higher results in the "Readiness to study online", while adults in the age group 50-58 had the lowest result. Also statistically significant differences were found in relation to previous activities – people, who had enrolled and completed online learning courses previously, had significant higher rate of "Readiness to study online". This was observed both in Latvia and the Czech Republic. Collecting data from online readiness survey tool before the course would give useful information to the faculty to plan specific activities for specific groups of learners, to customize their learning path during the progress of the course.
An Acoustic-Based Feature Extraction Method for the Classification of Moving Vehicles in the Wild

The acoustic classification technology of moving vehicles is a significant application in wireless sensor networks (WSNs). However, the wild environment makes it more intractable for the acoustic target classification owing to the complicated interference noise. The widely used mel-frequency cepstral coefficients (MFCCs) are somewhile contaminated by the acoustic noise, resulting in degrading the classification performance in real environments. To increase the classification accuracy of the moving vehicles, this paper presents an acoustic feature extraction method, which integrates the nonlinear function with the MFCC method, termed as NMFCC. Through nonlinear transformation, the proposed method could amplify the acoustic features in a nonlinear way, and obtain more robust acoustic features, thereby achieving a superior classification performance. Comparing the NMFCC with the baseline feature extraction method, experimental results not only demonstrate the viability of the proposed algorithm but also show a satisfactory performance of the moving vehicle classification for diverse practical scenarios in the wild.