Reviewerly/exHarmony huggingface dataset:
Quantitative measure for mosaics with dynamic elements using dense optical flow and the structure similarity index measure

Image mosaicking is a combination of multiple algorithms that use a series of images or a video to obtain as a result a single image with a larger field of view. However, in some cases the input data contains dynamic elements that change their position from a frame to another and this results in the appearance of errors like ghosting and parallax effects. In this paper, we will present a method to obtain a quantitative measure for mosaics with dynamic elements and how to determine the areas that create these errors. In fact, this was done by using dense optical flow to estimate the motion of all pixels and by comparing the Structure Similarity Index Measure of these areas obtained between the result mosaic and the input images. The obtained quantitative measures show better results and reflect better the obtained visual results.
Library: Illustration: Getting Started

Illustration is a type of art that is a visual explanation or interpretation of a written text.
A Comparative Analysis of Domain Adaptation Techniques for Recognition of Accented Speech

Addressing the domain mismatch problem has been a long term interest within cognitive infocommunication. In particular, several techniques to compensate for dialectal variations of the same base language in Automatic Speech Recognition (ASR) have been proposed. Conservative retraining, transfer learning, multi-task training, matrix factorization, i-vector based techniques as well as adversarial and teacher-student training, have been proposed for the specific purpose of ASR deep neural acoustic models domain adaptation. Comparing these techniques is often complicated as different experiments are carried out on diverse datasets and within various frameworks. It is also worthwhile analyzing possible combination of such techniques within complex systems. The objective of this work is to systematically compare and analyse a number of domain adaptation techniques for ASR using the same framework, the open-source Kaldi toolkit, in order to allow for a fair comparison on adapting US English acoustic models for the Indian accent. Our results indicate that, when properly hyper-parametrized and carefully regularized, the easiest approaches, requiring less complexity and reduced computational power, can perform equally well as the more complex ones.
PYTHON Language Teaching Reform and Innovation in the Short Semester

In recent years, the Python language, featuring in simplicity, efficiency, flexibility and strong applicability with rich class libraries, has been widely promoted and applied in various industries and the popularity is inevitable due to continuous development of artificial intelligence. Therefore, our school has carried out the intensive training of Python language targeting all freshmen via the innovative utilization of short semester. In view of the faculty, teaching management, supporting teaching materials and assessment methods, this paper discusses the problems and solutions of our Python language teaching reform and innovation in short semester, with the achievements and enlightenment of teaching reform clarified from the perspectives of students and teachers in order to effect certain direction and guidance for the teaching of Python language and computer language programming in colleges and universities.
Configuring Parallelism for Hybrid Layouts Using Multi-Objective Optimization

Modern organizations typically store their data in a raw format in data lakes. These data are then processed and usually stored under hybrid layouts, because they allow projection and selection operations. Thus, they allow (when required) to read less data from the disk. However, this is not very well exploited by distributed processing frameworks (e.g., Hadoop, Spark) when analytical queries are posed. These frameworks divide the data into multiple partitions and then process each partition in a separate task, consequently creating tasks based on the total file size and not the actual size of the data to be read. This typically leads to launching more tasks than needed, which, in turn, increases the query execution time and induces significant waste of computing resources. To allow a more efficient use of resources and reduce the query execution time, we propose a method that decides the number of tasks based on the data being read. To this end, we first propose a cost-based model for estimating the size of data read in hybrid layouts. Next, we use the estimated reading size in a multi-objective optimization method to decide the number of tasks and computational resources to be used. We prototyped our solution for Apache Parquet and Spark and found that our estimations are highly correlated (0.96) with the real executions. Further, using TPC-H we show that our recommended configurations are only 5.6% away from the Pareto front and provide 2.1 × speedup compared with default solutions.
An automated nuclei segmentation of leukocytes from microscopic digital images.

Leukemia is a life-threatening disease. So far diagnosing of leukemia is manually carried out by the Hematologists that is time-consuming and error-prone. The crucial problem is leukocytes' nuclei segmentation precisely. This paper presents a novel technique to solve the problem by applying statistical methods of Gaussian mixture model through expectation maximization for the basic and challenging step of leukocytes' nuclei segmentation. The proposed technique is being tested on a set of 365 images and the segmentation results are validated both qualitatively and quantitatively with current state-of-the-art methods on the basis of ground truth data (manually marked images by medical experts). The proposed technique is qualitatively compared with current state-of-the-art methods on the basis of ground truth data through visual inspection on four different grounds. Finally, the proposed technique quantitatively achieved an overall segmentation accuracy, sensitivity and precision of 92.8%, 93.5% and 98.16% respectively while an overall F-measure of 95.75%.
Maximum Coverage Method Modification with Timeliness in Non-Personalized Recommendation for Pure Cold-Start Users

A recommendation system should be able to provide recommendations to early users who are referred to as pure cold-start because it is related to the main business KPI, which is giving initial impressions to the initial user and increasing the percentage of initial users to be users of the system. To overcome this, the non-personalized approach is applied by using the maximum coverage method to cover users as much as possible and timeliness as an aspect of time to be able to make different items that have higher relevance for the initial user get to the recommendation. The study was carried out on the 100k and 1M movielens datasets using maximum coverage timeliness in 2 scenarios, namely scenario 1 using all item data as input while scenario 2 cutting the number of items based on user coverage of the item. Resulting in the dataset movielens 100k, experiments with the name MaxCovTL_100 in scenario 2 have the best utility in top-15 and top-20 and the best covered users in top-15 compared to other methods. But the improvement was not significant after testing with the Wilcoxon test. In the 1M dataset movielens, the results of recommendations from the maximum coverage timeliness method are very similar to the maximum coverage. so that this experiment can be said to be unsuccessful.
Kanban Systematic Approach in SDLC (Software Development Life Cycle)

Using of Kanban in software development is an emerging topic. This systematic literature review was conducted in order to analyze the current trend of Kanban usage in software development and to identify the obtained benefits and involved challenges. The search strategy resulted in 492 papers, of which 19 were identified as primary studies relevant to our research. The main reported benefits of using the Kanban method were improved lead time to deliver software, improved quality of software, improved communication and coordination, increased consistency of delivery, and decreased customer reported defects. The reported challenges included lack of knowledge and specialized training as well as various organizational issues. Additionally, suggested practices were extracted from the primary studies and summarized for guiding the practitioners interested in adopting Kanban. The findings of thisliterature review are intended for helping researchers and practitioners to gain a better understanding of the current state of Kanban usage in software development.
Algorithm of Pre-judgment NAF Scalar Multiplication on ECC

ECC (Elliptic Curve Cryptography) algorithm is widely used in many field such as smart card due to it's highly security. In some integrated circuits which have poor hardware resource, just like smart card, we need to use a lot of registers to store the temp value of the NAF of k on ECC when we are doing the scalar multiplication. To solve the problem, this paper proposes an algorithm called pre-judgment of NAF base on the general NAF algorithm. It not only inherits the fast computation speed of the general NAF algorithm, and also saves the registers for temp value stored through pre-judge the value of k. It doesn't need to calculate the NAF of k beforehand. It directly calculates the NAF of the k when doing the scalar mutilation in the same state machine. This can help save the hardware resource, and make the low power, low cost IC easy to develop.
Model Shaper Competencies Trainees on the Basis of Block Alternative Networks

The report considers the task of organizing a set of competencies defined by the FSES HE, the University, as well as the employer. This approach makes it possible to consider the needs of key stakeholders in the training of young professionals. Various purposefully formed categories of competencies are considered as a multidimensional complex, and each aspect is represented by attributes, as well as their qualitative and quantitative values. The General architecture of the complex of competencies is formed in the form of a tree of competencies, isostructural corresponding to the tree of content of the discipline. To solve this problem, we propose to use the method of block alternative networks. According to this method, each aspect of competencies is represented in the form of a network block, and the set of blocks forms a complete network – abbreviated BAN. The formation of individual competencies is carried out in the form of a route to the BAN in accordance with the individual learning path, synthesized or given a priori. Applicability theoretical provisions are considered on the example of the embodiment of the synthesis of individual competence trajectory (TIC) of the discipline of the working curriculum, implementing the FSES HE the direction of training 09.03.04 “Software engineering” (bachelor level) in the profile “Engineering of intelligent software systems and complexes”.
Design of Hierarchical Cone Fuzzy System for Nonlinear System Modeling

The use of hierarchical fuzzy systems (HFS) is an effective way to deal with the curse of dimensionality which is the main drawback for the application of fuzzy models in the modeling and control of large-scale systems. This paper proposes the design of HFS which implements T-S type cone fuzzy system (CFS). The performance of the hierarchical fuzzy system is evaluated through time series prediction and function approximation, which demonstrate that the proposed HFS working together with the optimization of parameters by genetic algorithm (GA) and k-means clustering in fuzzy partition provides structurally simple and accurate fuzzy models.
Enhanced SAT Solvers Based Hashing Method for Bitcoin Mining

Blockchain is a new technology that contains a list of blocks; where each one includes a hash value of the previously linked block. Using cryptography in Blockchain prevents manipulating data in any block of the chain that puts time overhead for generating the blocks. It is critical that an efficient method for mining process is essential to reduce the time of generating blocks. To speed up the computations, various special purpose hardware was built with special circuits that are designed based on the problem instance to be solved. Another approach is by using an algorithmic approach. Satisfiability (SAT) Solvers are the recent methods that can be used for mining process efficiently. In this paper, we propose a SAT Solver mining methodology. The main challenges in Blockchain technology is to reduce the mining time. This paper focuses on mining process in Bitcoin, which is the most popular Blockchain based cryptocurrency. A substantial reduction of the mining time has been achieved using the proposed SAT method.
OnBodyVR: Virtual Reality Application with Eyes-free on-Body Interface Based on three Tracked Points

With on-body interaction the body can be used as an interface which is available at any time and it enables eyes-free interaction through proprioception. However, this type of interaction poses a challenge in terms of capturing the position and orientation of body parts. In this work, an application is presented which uses a heuristic method which allows eyes-free on-body interaction using a virtual reality system with 3 tracked points. Via the manner the user carries head-mounted display and the two hand controllers combined with the anthropometric findings on maximum rotations of the involved joints, on-body interaction can be enabled. The heuristic method facilitates on-body interaction with forearms, shoulders and hip. One of our other works has shown that an abstract 2D graphical user interface can be used for this on-body interaction. In this research demonstration a game-like application is presented, where the user can try out the on-body interface and test its robustness.
Multi-model Environment Generation and Tailoring Model for Software Process Improvement

Software development organizations take great risks when are faced with process improvement projects and the inclusion of best practices. Such risks include the selection of a standard, framework or model for the improvement process. Some organizations decide to integrate best practices from different sources to be non-dependent on a particular model, framework or standard. However, the integration of different models is an additional challenge since the complexity of the implementation increases as best practices come from different natures. Hence, we propose a model to generate and customize a multi-model environment for software process improvement. We intend to reduce the complexity of combining agile and traditional frameworks by generating a frameworks integration catalog, which, from heuristics, graphically represents the possible paths to follow for the process improvement project. We use design-based science for this research because of its focus on problem analysis in real-world environments. In this way, we can consolidate the model to customize and generate a multi-model environment for the implementation of best practices of different nature during an improvement process. We also define a proposal of organizational profiles, which will allow us to validate the model in a business case in future work.
Ego-Motion Estimation Using Affine Correspondences

Ego-motion estimation of a moving vehicle is an essential task in modern robotics, autonomous vehicles (self-driving cars), and unmanned aerial drones. There are many ways to accomplish ego-motion estimation, for example by using different sensors such as radar, laser, or LiDAR. However, motion estimation can be accurately achieved using video input. Cameras become more available, affordable, and accurate. Most vision-based solutions for ego-motion estimation depend on matching algorithms that use Point Correspondences (PCs) between images to estimate the motion. However, motion estimation using Affine Correspondences (ACs) requires fewer correspondences; therefore, it takes fewer iterations to converge in the sample-and-test algorithms, such as random sample analysis (RANSAC). Affine-based solutions are faster while possessing similar accuracy to their point-based counterparts. Using affine correspondences to solve geometric computer vision problems is a relatively new practice. This paper is the first to survey the use of ACs for motion and relative pose estimation, as well as to provide an analysis of the proposed affine correspondences-based technique. The experimental results show that ego-motion estimation with ACs is faster than PCs due to the fewer required matches. Using ACs has the potential to solve various computer vision problems since they provide additional valuable information from the scene.
Exploring the role and possibilties of 3D printing in IT studies : Is my curricula good enough?

Emerging technologies attract special attention in the industry by promising the opportunity to overcome long-existing barriers. Education has to respond to the demand of industry and introduce 3D printing and also modeling into the curricula of different courses. Fortunately, more and more institution can possess 3D printers which brings more motivation for educators to enhance their teaching topics and methods. This paper describes a course briefly which was followed by asking the opinion of the students about the course in the form of an online survey. Evaluation of the answers is supposed to be a help to design the next implementation of the course.
Smart Contracts

When Nick Szabo pioneered the idea of a smart contract in the 1990s, the economic and communications infrastructure available at that time could not and did not support the protocols needed to execute and apply smart contracts. While smart contracts may be viewed as an example of the use of blockchain and blockchain technology which offers great opportunities to the field of law; others are more sceptical. The use of smart contracts in law is anything but straightforward, but this should not deter jurists from investigating the opportunities this instrument offers. This chapter aims to provide an overview of smart contacts, explaining how they work, the ways they differ from written contracts, their legal status, and the advantages and disadvantages associated with using them. Finally, it identifies the main challenges facing businesses and the legal profession with regard to the expanding use of smart contacts.
METHODOLOGICAL BASIS FOR ASSESSING THE READINESS OF THE UNIVERSITY TO INTRODUCE DIGITAL TECHNOLOGIES

The effectiveness of professional education substantially depends on the wide use of digital technologies and products in the educational process. However, the effectiveness of the implementation of these technologies largely depends, on the one hand, on the readiness of the digital educational environment, and on the other hand, on the level of digital literacy and the competence of the teachers. So, it is necessary to develop a methodology for assessing the level of preparation of the university for digitalization, the purpose of which is to provide a unified approach to the assessment of the educational information environment and the factors providing it in the educational process, as well as to remove obstacles to the effective implementation of educational programmes and services using digital technologies and products. The analysis of the existing methods has shown that they assess the level of the digital development of various sectors of the economy and society in general, but do not affect the educational system or evaluate the digitalization of the educational process only from the technical point of view. &#x0D; Taking into account all the above-mentioned circumstances, the authors propose to evaluate the readiness of universities for digitalization of the educational process on the basis of the analysis of the factors directly affecting the digitalization of the educational process, such as: digital transformation of the educational environment of the university and the level of preparation of the teachers for the work in the digital environment.
A Comparative Study and Analysis of Classification Methodologies in Data Mining for Energy Resources

Retrieval of right sequence in extensive quantity of records in irrelevant, unreported and concealed data by applying the process of data mining methods. Classification is a procedure used for building classification models for a set of input data. This study is about to compare and analyze the various classification algorithms for energy resources using Weka tool. In this study, it uses five different data mining methods, namely iterative classifier optimizer, Bayes net, classifier via regression, LMT and JRip. The diverse attainment of the algorithm is found by the assess of variables like true conclusive, false conclusive, exactness, reminiscence and ratio. Meticulousness of algorithm is examined using the values of correctly classified occurrences and incorrectly classified occurrences.
English and Javanese greeting expressions: A descriptive qualitative study on pragmatics

Due to the vast studies of cross-cultural pragmatics, a comparison of languages needs more investigation, especially in regard to the influence of culture. The current paper aims to describe various greeting expressions produced by English and Javanese users as well as to compare which language possesses more varied expressions. The main reason triggering the researchers to conduct the study is the emergence of English as a foreign language in Indonesia and the popularity of the Javanese language as the mostly used language in the country. Some factors, including culture, impact the diversity of greeting expressions. Therefore, the researchers conducted the current study to determine how culture influences the English and Javanese languages in expressing greetings. To achieve this goal, a descriptive qualitative study of pragmatics across culture analysis was carried out. The researchers utilized the expressions of greetings and their responses in English and Javanese as the object of the research. The data collection techniques were observations, in depth-interviews and questionnaires. The findings showed that English has a number of strategies to express greetings including formal greetings; informal greetings; the combination between formal and informal greetings; question greetings; statement greetings; the combination between informal greeting and statements; and the combination between informal greeting and questions. For Javanese, there are formal greetings; informal greetings; greeting by question; greeting by statement; greeting by invitation; greeting by complaint; greeting with particular utterances. The study also showed that the expressions produced in the Javanese language are more varied than those in the English language.