Reviewerly/exHarmony huggingface dataset:
Conceptual Foundations of the Use of Formal Models and Methods for the Rapid Creation of Web Applications

The problem of the rapid creation of effective web applications of one class using formal means is considered. A conceptual approach to its solution is offered based on an analysis of the peculiarities of the construction of web applications. Our approach is based on defining the standard web application architecture and selecting its components using formal methods in accordance with user requirements. A formal logical system is proposed that uses the design of web applications as a process of outputting a formula specified according to the needs of the user, which defines the schemes of execution of the modules of the system. An important feature of this approach is the ability to visualise the process of designing the system in 3D, which creates the conditions for effective interaction between developers and machine development tools.
Modified union feature selection method on English translation of hadith text clustering

Abstract The high feature space (dimension) is one of the main issues to be considered in the text clustering process. Therefore, various dimensional reduction methods have been introduced for selecting informative sub feature. Each method uses a different strategy to select sub feature, and the results are different even if using the same data set. Typically, union methods and intersection methods are used to combine selected sub feature with different reduction methods. The union method selects all feature and intersection only selects the general feature under consideration. Thus, the union approach causes an increase in feature dimensions and the intersection approach causes the loss of some important feature. Therefore, in order to take advantage of a method and reduce its weaknesses, this research proposes new approach, which are called modified union. This approach applies the union methods to select top ranking feature and applies intersection methods to the rest of the feature. In this case, feature selection uses the Term Variance (TV) and Document Frequency (DF) methods to calculate the relevance value of each feature. The effectiveness of the proposed method is tested on the data set of Hadith Shahih Bukhary. The results show that the proposed method improves clustering accuracy over other methods with DB index is 2.7.
Characterizing Project Evolution on a Social Coding Platform

Social coding platforms (SCPs) have realized spontaneous software evolution, where new source code and ideas are spontaneously proposed by altruistic developers. Although there are many projects operated by active communities performing spontaneous evolution, it is yet unclear that how such successful projects and communities have been formed and governed. In this paper, we propose a method that can investigate the history of every project in the SCP. Introducing the concept of project as a city, we consider every project in the SCP as a city, where a government and citizens develop a city through collaborative activities. We then identify essential attributes that characterize a state of a city. For each attribute, we develop metrics that quantity the state S(p, t) of a project p at time t. An experimental evaluation investigating GitHub projects of famous code editors shows that the proposed metrics well visualize the history of the projects from essential perspectives of a city.
Pesantren-based disaster mitigation strategy : case study pondok pesantren Darunnajah Cipining Bogor

Abstract This study aims to analyze the pesantren-based drought disaster mitigation strategy. This research method is a descriptive research method with a qualitative approach to describing drought disaster mitigation in pesantren. To get the right and appropriate informants, the sampling technique in this study used a purposive sample system. Data collection is done by using interview techniques, documentation, literature study, and observation. Mitigation in this research refers to mitigation theory which divides mitigation into 2 (two) forms of strategy, namely: first, structural mitigation, in the way of infrastructure development as a driver to minimize the impact of disasters through the use of technological approaches. The symptoms observed were a compilation of a database of potential landslides and the creation of an early warning system. Second, non-structural mitigation, in the form of management and spatial training to improve community capacity. This research concludes: Mitigation of drought in the Cipunn Darunnajah Islamic Boarding School in Bogor is carried out structurally and non-structurally. Structural mitigation is done by compiling a database of potential hazard areas and installing an Early Warning System (EWS). Non-structural mitigation is carried out by providing information, outreach and training and disaster simulation. Efforts have been made to improve the effectiveness of disaster mitigation through the establishment of Disaster Response Students and Disaster Resilient Alumni.
Design and Implementation of Communication Data Quality Analysis Software System

This paper mainly introduces the design method of communication data quality analysis software based on Linux system, and implements the software under Qt environment. The software can automatically analyze the communication data generated by the ocean-going survey ship. It can automatically check the abnormal situation of communication data (including re-frame and frame loss) and identify the abnormal situation according to the content transcribed by users' needs. It can also provide the drawing function of specified format data and the auxiliary function of data analysis. The application results show that the data quality analysis software system can meet the daily use needs, greatly reduce the time of manual data analysis and improve the accuracy of the results.
Predicting Bid Success with a Case-Based Reasoning Approach: Explainability and Business Acceptance

With an ever growing demand for providing AI solutions within business there is a tendency to expect end to end standardised solutions to problems. These solutions are expected to be accurate and to be seamlessly integrated within existing business processes. However, achieving higher accuracy could be detrimental not only to explainability (if a blackbox solution is provided) but also need to be accepted and used within existing business processes. This paper describes a Case-Based Reasoning (CBR) solution to a real problem within a telecommunications company together with the reasoning behind selecting this particular approach. The solution has been integrated within existing business processes which has been a real challenge besides satisfying all the technical ability criteria.
Naturalness evaluation of synthetic speech based on residual learning networks

With the emergence of text-to-speech (TTS) systems, the synthetic speech have been widely applied. But the quality evaluation method of the synthetic speech is still away from an agreement. This paper presents a novel method based on residual learning networks, which was trained on the databases of Blizzard Challenge and our own corpus. The effect of the proposed architecture was compared with the LSTM networks and VGG networks. According to the results of experiments, the architecture based on the ResNet gives root mean square error (RMSE) of 0.40 and the correlation coefficient of 0.82, which is better than the other two networks.
Determination of competences that take affect the formation of creative capabilities of team of managers

The main objective of the paper is to identify key competencies that influence the development of creative capabilities for managers in the current economic problems, the study of opportunities for improving competencies through various methods, and development of a mathematical model for forming the necessary set of competencies and determining their priority.
Transition Detection for Automatic Segmentation of Wrist-Worn Acceleration Data: A Comparison of New and Existing Methods

Introduction : Data from wrist-worn accelerometers often has an inherent natural segmentation that reflects transitioning from one activity to another. The aim of this study was to develop an activity transition detection method to realize this natural segmentation. Methods : Data was gathered from 16 participants who wore triaxial wrist accelerometers in a lab-based protocol and 47 participants in a free-living protocol. Change point detection was used to create a method for detecting activity transitions. The agreement between observed and predicted transitions was assessed by the Matthews Correlation Coefficient (MCC), Root Mean Squared Error (RMSE), and two additional metrics created for this task; the Ratio of Minimum Mean Distance (RMMD) and the Ratio of Sensitivity (RoS). The effects of varying combinations of acceleration axes were also investigated to determine the most effective set of axes. A novel post-processing technique was developed to mitigate a major limitation identified in current transition detection methods. Results : The developed transition detection method achieved a MCC of 0.763, a RMSE of 3.17, a RoS of 2.40, and a RMMD of 3.21, outperforming existing techniques. The post-processing technique developed improved the performance of all methods when identifying transitions. It was found that using solely the y -axis (vertical acceleration) allowed for optimal performance. Conclusion : Change point detection is a valid method for identifying transitions in activity using wrist-worn accelerometer data. The new post processing technique developed improves the performance of transition detection methods.
Implementation of High speed, Low PowerModified Vedic Multiplier and Its Application in Lifting based Discrete Wavelet Transform

Implementation of 9/7 Lifting based 2D Discrete Wavelet Transform with the use of high speed and low power Modified Vedic Multiplier is proposed in this paper. Number of adders used in conventional multiplier is reduced in the design of modified Vedic multiplier. The architecture has been designed in VHDL language in Xilinx ISE design suit 14.7. The maximum frequency of the proposed multiplier is 83.012 MHz and power is 60.87 mW for Spartan 3E FPGA. The DWT has power dissipation of 1.161 mW for 180 nm Technology.
Effects of Different Environmental noises and Sampling Frequencies on the performance of MFCC and PLP based Bangla Isolated Word Recognition System

The paper has observed that different environmental noises and sampling frequencies severely affect the performance of the MFCC and PLP based Bangla Isolated Word Recognition System. We have observed the effects of different environments on MFCC and PLP for 39 and 52 coefficients for 8 kHz, 16 kHz, 32 kHz, and 44.1 kHz sampling frequencies. From the experimental results, we have observed that for different sampling frequency both in noiseless and noisy medium PLP models detect better than MFCC except in CLASSROOM environment where different types of noise are present simultaneously.
Special Issue of Selected Contributions from the Seventh Swedish Language Technology Conference (SLTC 2018)

This Special Issue contains three papers that are extended versions of abstracts presented at the Seventh Swedish Language Technology Conference (SLTC 2018), held at Stockholm University 8-9 November 2018.1 SLTC 2018 received 34 submissions, of which 31 were accepted for presentation. The number of registered participants was 113, including both attendees at SLTC 2018 and two co-located workshops that took place on 7 November. 32 participants were internationally affiliated, of which 14 were from outside the Nordic countries. Overall participation was thus on a par with previous editions of SLTC, but international participation was higher.
Secure communication in E-health care system monitoring

In this paper, we will discuss the requirements of security that should be included in any system of e-health care based on the internet of things. Then we study the possibility of secure communication between medical tools inside a hospital, using a secure structure for its interfaces, taking advantage of the security mechanisms offered by the communication technology, networks, and protocols exist, according to the construction, and energetic properties of medical objects connected. This paper can answer to the question, how to apply a secure interface communication between e-health care system monitoring devices while ensuring a reliable, efficient and security of transmission of data on each transmission related to this kind of objects.
Open our visualization eyes, individualization: On Albrecht Dürer’s 1515 wood cut celestial charts

The position that visualization is an intimate part of human existence and associated with the human species is advanced in this work: visualization abounds delimited by the space of individuality across human history. Visualization involves two complementary aspects of the uniqueness deemed of individuals: individualization reflects individuals’ capabilities and personalization reflects designs that seek compatibility with individuals’ capabilities. This has a number of implications upon the design and evaluation of visualizations. For one, a suitable visualization model that expresses individualization and personalization is needed: a brief survey of models is presented. For another, addressing intellectual uniqueness requires deep analysis and selective objective balance due to the potentially humongous number of unique ideas that support visualization design and viewer experiences. The Engineering Insightful Serviceable Visualizations model is selected as a guide for a comprehensive visualization evaluation of Albrecht Dürer’s 1515 celestial charts. Motivating this choice of visualization is its significance as the first notable and influential European star chart intended for scientific use and mass viewership, and as a blending of science and art. In addition, there is a lack of discussion concerning this particular visualization in the visualization literature. Concluding remarks suggest the significance of approaching visualization from this point-of-view.
Data Based Reward Formulation of BELBIC for DC Motor Position Control

This paper presents data based Reward Formulation for bio-inspired emotional learning controller. Brain emotional learning (BEL) control paradigm has gathered increased interest as controller with high cognitive intelligence. Currently, mathematical formulations and algorithms are being investigated to enhance the applications across various domains. In this article data based tuning algorithm is presented, for tuning the reward and learning factors in BEL. The approach can be generalized for system controllers design, and is applied for DC motor position control as the case study. The controller design is structure independent and is based on the data obtained from PID controllers. The formulation of data based reward shows improvement in transient and steady state responses.
Demonstrating the Distinctions Between Persuasion and Deliberation Dialogues

A successful dialogue requires that the participants have a shared understanding of what they are trying to achieve, individually and collectively. This coordination can be achieved if both recognise the type of dialogue in which they are engaged. We focus on two particular dialogue types, action persuasion and deliberation dialogues, which are often conflated because they share similar speech acts. Previously, a clear distinction was made between the two in terms of the different pre- and post-conditions used for the speech acts within these dialogues. This prior work gave formal specifications of the dialogue moves within the dialogues but offered no evaluation through implementation. In this paper, we present an implementation to demonstrate that the two dialogue types described in this way can be realised in software to support focussed communication between autonomous agents. We provide the design and implementation details of our new tool along with an evaluation of the software. The tool we have produced captures the distinctive features of each of the two dialogue types, to make plain their differences and to validate the speech acts for use in practical scenarios.
Optimization BM3D Algorithm Based on Pseudo-3D Transform

A optimization BM3D algorithm based on pseudo-3D transformation (incomplete 3D transformation) is proposed to solve the problem of huge computational of BM3D image denoising algorithm. Firstly, one-dimensional wavelet transform was carried out on the third dimension of 3D similar blocks to get one-dimensional coefficient blocks. Then the lowest-frequency coefficient block gotten above was transformed by two-dimensional transformation. Following, two-dimensional inverse transformation was performed on the lowest-frequency coefficient blocks after hard threshold filtering or Wiener filtering. And finally, one-dimensional inverse transformation was carried out on the third dimension to get the noise reduced image. The performance of the proposed optimization method is very closed to the original BM3D algorithm, but the computation of pseudo-3D transformation is only 1/3 of that of 3D transformation.
Visualization of Software Quality Expert Assessment

Methodology for visualization of software quality expert assessment by different criteria with radar charts using has been elaborated. Under visualization of software quality expert assessment means showing of information in the graphical view for maximal usability and understanding. The algorithm for calculation of sectoral polygons area in the polar coordinate system has been elaborated, with using of its relative software quality by corresponding criteria can be calculated and assessed. Diagram's sectoral areas help to define part of software quality by whole criteria according to one expert at the moment and part of software quality which should be achieved for completeness. Summarized software quality indicators for each expert and general quality indicator were defined.
Visualization of MRI Datasets for Anatomical Brain Segmentation by Pixel-level Analysis

In this paper, segmentation of the brain MRI images are carried out by performing pixel-level analysis with deep learning approaches. Image segmentation is often used for medical image analysis and is an early diagnosis tool for clinical applications. Brain images acquired by MRI machines need to be segmented into anatomical structures for detecting morphological changes. One can then visualize the anatomical structures and take quantitative measurements if required. This allows surgeons to plan out surgeries and the method of approach when removing tumors or other lesions. As large MRI datasets become available, deep learning can be used to carry out pixel-level analysis for determining its class in the brain anatomical structure, which can enhance visual intelligence. This paper aims to use the latest deep learning techniques like dropout, batch normalization and data preprocessing to accurately segment images based the MICCAI 2012 dataset, which contains 35 manually segmented MRI into 134 anatomical brain structures. The segmented result into 134 classes/regions are then visualized in colored images. The model uses a multi-patch data extraction algorithm which helps to classify the center voxel of the extracted patches. The result obtained reaches a mean dice coefficient of 76.2%, which has outperformed the best previous result of a mean dice coefficient of 72.5%.
How to choose adaptively parameters of image denoising methods?

The problem of adaptive choice of strength parameters for wide class of mathematical image ridge and edge preserving denoising algorithms is considered. It arises now in hybrid denoising algorithms containing a combination of convolutional neural networks (CNNs) and these classical methods. The problem is considered for the case of additive white Gaussian noise. We find the denoising method parameters to maximally suppress the image noise while retaining important image structures. Multiscale ridge based approach is used to analyze presence of regular structures in the ridge areas at the difference between noisy and filtered images. Hybrid methods using Deeply-Recursive Convolutional Network and Non-Local Recurrent Network are developed. CNNs are used in combination with total variation based method with adaptive parameter choice.
Determination of the Shortest Route Towards the Tourist Destination Area Using the Ant Algorithma

Abstract There are so many tourism objects in the world, especially in Indonesia. One of the most famous tourist attractions in Indonesia including Bali, Borobudur, Lake Toba, and many others. The tourist attraction is not only famous in Indonesia but also famous to foreign countries, because one of them is a relic of the wonders of the world. In addition, these tourist attractions also have natural beauty and uniqueness, which is different from other countries, so that it attracts local tourists and foreign tourists to visit the place. However, there are several routes to get to these tourist attractions, so that local tourists and foreign tourists who want to visit have a little trouble having to go through which route to get to their destination. Surely they want the closest travel route. Therefore the purpose of this study is to use the ant algorithm to determine the shortest route to the tourist area. The ant algorithm is adopted based on the behavior and habits of the ant colony. In general, ant colonies can find and find the fastest and shortest route or route to food sources from their nests, based on footprints on traversed trails. This study uses 5 cities for example, including C1, C2, C3, C4 and C5, with the starting point of C1 and C5 destination point. Based on calculations using the ant algorithm to determine the shortest route, the shortest and fastest route obtained by ant 4 is route C1 → C4 → C5 with a distance of 140 KM.
Russian Higher Education and Science on the Intellectual Property Market

The article considers the results of the Russian universities’ and scientific institutions’ activities on the intellectual property market in Russia and abroad. The authors provide the various statistic data for complete and accurate analysis of the functioning of Russian universities and scientific institution as the subjects of intellectual property. The article examines the current factors influencing the educational and scientific institutions’ activities on the formation and replication of intellectual property, and identifies the scientific and educational institutions’ potential opportunities to develop the international intellectual property market. The analysis of international experience shows that by the beginning of the XXI century, the intellectual property as a commercial product becomes the determining factor in the world leadership. However, Russia has a modest position on this market. The intellectual products which have a considerable potential are not promoted on the market, therefore they do not manage to be competitive. The article makes the case for developing methods and means that will stimulate the creation and promotion of existing and future intellectual products on the market. In conclusion, the article outlines the main areas of work for the development of intellectual property market in the Russian Federation to overcome the monopoly of Western countries and China on the scientific production and high technologies market.