Reviewerly/exHarmony huggingface dataset:
Humanities Between the Digit and the Meaning: the Role of Humanistic Disciplines in Digital Society

In the modern world of digital culture, the issue of the future of humanitarian knowledge is becoming more acute. Critics of traditional humanitarianism accuse it of inefficiency and inability to adapt to modern society; proponents argue that it is humanitarian knowledge combined with practice that can help solve the problems of a digital society. The article deals with several interrelated aspects of this problem, including issues of critical evaluation of technical systems, interaction of humanitarian and technical knowledge, the role of digital culture and digital positivism.
An Ensemble Integrated Security System with Cross Breed Algorithm

Blockchain and IoT are two technologies are most widely popular in present scenario, but technologies are more complicated. The blockchain used to transforms storage and data analysis. In recent years, the blockchain is at the heart of computer technologies. It is a cryptographically secure distributed database technology for storing and transmitting information. Various attacks are done in many networks. Many research articles discussed about the security issues over the IoT based secure using block chain technology. In this paper, an Ensemble Integrated Security System (EISS) is introduced to improve the security for the heterogeneous network which consists of normal and abnormal nodes which is processed with the block chain, IoT. Resultsshow the performance of the OUATH-2 and EISS algorithm.
Prosody, syntax, macrosyntax

Most of research work on French intonation has been conducted on prepared speech data (i.e.read speech), with various approaches ranging to purely syntactic (Rossi), Autosegmental-Metrical (Sun and Fougeron) or Phonosyntactic (Martin).This paper examines the bases of the phonosyntactic approach extended to spontaneous (non-prepared) speech data, described syntactically from a macrosyntactic point of view (Blanche-Benveniste, Deulofeu).
Adaptive wavelet schemes and finite volumes

We consider a procedure for combining high order finite volumes and tree-based nonuniform grids. Especially, we focus on efficient algorithms for third order multidimensional volume interpolation and communication between levels of refinement. In the end, numerical results are reviewed to validate our approach.
Speaker based segmentation on broadcast news- on the use of ISI technique

In this paper we propose a new segmentation technique called ISI or "Interlaced Speech Indexing", developed and implemented for the task of broadcast news in-dexing.It consists in finding the identity of a well-defined speaker and the moments of his interventions inside an audio document, in order to access rapidly, directly and easily to his speech and then to his talk.Our segmentation procedure is based on an interlaced equidistant segmentation (IES) associated with our new ISI algorithm.This approach uses a speaker identification method based on Second Order Statisti-cal Measures.As SOSM measures, we choose the "µGc" one, which is based on the covariance matrix.However, experiments showed that this method needs, at least, a speech length of 2 seconds, which means that the segmentation resolution will be 2 seconds.By combining the SOSM with the new Indexing technique (ISI), we dem-onstrate that the average segmentation error is reduced to only 0.5 second, which is more accurate and more interesting for real-time applications.Results indicate that this association provides a high resolution and a high tracking performance: the in-dexing score (percentage of correctly labelled segments) is 95% on TIMIT database and 92.4% on Hub4 Broadcast news 96 database.
A Novel Multisupervised Coupled Metric Learning for Low-Resolution Face Matching

This paper presents a new multisupervised coupled metric learning (MS-CML) method for low-resolution face image matching. While coupled metric learning has achieved good performance in degraded face recognition, most existing coupled metric learning methods only adopt the category label as supervision, which easily leads to changes in the distribution of samples in the coupled space. And the accuracy of degraded image matching is seriously influenced by these changes. To address this problem, we propose an MS-CML method to train the linear and nonlinear metric model, respectively, which can project the different resolution face pairs into the same latent feature space, under which the distance of each positive pair is reduced and that of each negative pair is enlarged. In this work, we defined a novel multisupervised objective function, which consists of a main objective function and an auxiliary objective function. The supervised information of the main objective function is the category label, which plays a major supervisory role. The supervised information of the auxiliary objective function is the distribution relationship of the samples, which plays an auxiliary supervisory role. Under the supervision of category label and distribution information, the learned model can better deal with the intraclass multimodal problem, and the features obtained in the coupled space are more easily matched correctly. Experimental results on three different face datasets validate the efficacy of the proposed method.
Designing Educational Analytics Tools Using Visualization Based on Behavioral, Motivational, and Social Network Data

The article presents a description of the approach to the use of data visualization in various educational Analytics tools when building University courses. In addition to the analysis of educational behavior, socio-psychological approaches, including the theory of expectations and social values, and the social network approach, are separately considered as prospects for analysis. An example of designing training Analytics using modern data analysis and visualization tools is analyzed.
Short Paper: A Multistage Backward Differentiable Method for Constructing Light Convolutional Neural Networks

We propose a multistage differentiable method to select convolutional channels and construct light neural networks from a heavy network for inference on a subset of a big data set. The selection proceeds backward in layers and utilizes sparse penalty to diversify channel scores. The resulting light network gains sizable accuracy over the baseline heavy network.
Image Matching Using Phase Congruency and Log-Gabor Filters in the SAR Images and Visible Images

SAR and visible image matching provides many applications in remote sensing, image fusion and image guidance with laborious problems with regard to the potential nonlinear intensity differences between two images. This paper proposes an image matching approach which use the phase congruency (PC) to detect corners and log-gabor filters for obtaining feature descriptor in the SAR and visible images. PC can provide inherent and rich image textures for the images with intricate grayscale changes or noise, which is utilitized to detect the corners. The moments of PCs for the images are calculated to obtain the keypoints and the log-gabor filters are employed to acquire the feature descriptors. Five evaluation methods are used for testing the results of the algorithm for three pairs of images and its result is compared to the SIFT algorithm. The experiment performance show that the advocated algorithm is better than the SIFT algorithm.
GRAMMATICALIZING “WELL” IN CONTEXTS

This paper is focused will be on the adverb well which underwent grammaticalization [Lehmann, 1985] in the text fragments from the British National Corpus and 100 fragments retrieved from the novel "Theatre" by W. Somerset Maugham.According to Hopper and Traugott grammaticalization and lexicalization are the two phenomena developing the language referring mostly to the steps whereby particular items become more grammatical through time.They add that reanalysis modifies underlying representations, whether semantic, syntactic, or morphological, and brings about rule change [Hopper 2003; see also Mykhaylenko, 2015].There is a discussion whether grammaticalization and reanalysis are independent or designate the same change [Detges, 2002].We shall consider grammaticalization as a feature of language evolution, a semantic change in particular, and reanalysis as a method of investigation on any synchronic plane.Traditionally it is designated as an open part of speech.However, the discourse analysis of well reveals its various functions -an adverbial modifier, a conjunction, a particle, an interjection, and a pause filler.Such an array of functions of well is proved by the British National Corpus analysis where its frequency is 141 317.Evidently, that its high frequency is caused by the processes in the class of adverbs revealed in different types of context.Most English parts of speech are demorphologized and their syntactic positions confirm their part of speech status [Hengeveld, 2010; Jezek, 2009].We assume that the change primarily occurring in discourse and then permeating the system within the time is grammaticalization -an evolutionary process caused by syntactic reanalysis and semantic bleaching.In the following section we shall examine the text fragments with the unit well to define the shift of its open part of speech category to the close class of words: particles, interjections, conjunction, discourse marker, and pause filler.etc.Adverbs with the complex semantic structure can be transposed into particles, interjections, etc. (see Shigurov, 2016) which are used by the author/speaker to express his/her intentional meaning or for the discourse cohesion.
توظیف الإعلام الرقمی المعماری فی البناء المعرفی ولتحسین الأداء الأکادیمی لطلاب العمارة بإستخدام تقنیة رمز الأستجابة السریع QR.CODEد ا رسة تطبیقیة: ترمیز لقاعدة بیانات معماریة بالمسطرة الإعلامیة الخماسیة FYPGQ

The research aims to apply the QR code technology as a media tool in calculating the academic performance of architecture students. An exploratory study was conducted on a sample of students of the Bachelor of Architecture at Assiut University to clarify the role of the FYPGQ social media network in the architectural design studios.
Study of anaemia profile in a tertiary care hospital in Karnataka, India

Background: Anaemia is a major public health problem worldwide especially in developing countries like India. Nutritional cause of anaemia continues to predominate as the most common cause of anaemia. Objective of this study is to determine the clinical and laboratory profile of anaemia among patients admitted to our hospital.Methods: Our study was a prospective study in which thirty nine patients of anemia admitted to Medicine ward in SNMC and HSK hospital were studied for their clinical and laboratory characteristics. Duration of the study was 7 months from July 2019 to January 2020.Results: Anaemia was more common among females (65.1% of total patients). Patients aged less than 60 years contributed to 85% of patients. Pallor was the universal finding present in 100% of patients. On systemic examination haemic murmurs on auscultation was the most common finding present in 28.2% followed by hepatomegaly (17.94%). Microcytic and dimorphic anaemia constitute the bulk of anaemia.Conclusions: Nutritional anaemia particularly iron deficiency anaemia is the most common cause of anaemia. It tends to affect the working age group and females predominantly. Patients continue to present with severe anaemia to the hospital.
A Methodology for Assessing Security Vulnerability of Cloud Services

Cloud services continue to change the business paradigm to use computing resources such as infrastructure, platform and application using the network access.They have created new security threats and challenges.When large amounts of data are saved in the cloud, the cloud is naturally exposed to attack.In cloud services, analysis and evaluation of security vulnerability should be made with protection plans that provide the objective data and information necessary to establish measures for information protection for each business of firms and take into account the impact on their respective responsibilities.This paper presents a framework to evaluate security vulnerability that reflects the business impacts.Through this framework, it is possible to evaluate vulnerability items of cloud services.Eventually, the proposed methodology will help establish security policies for both cloud service providers and users.
FUZZY DIAGNOSTİCS OF SOİLS ACCORDİNG TO THE WORLD REFERENCE BASE FOR SOİL RESOURCES

Soil classification remains one of the most controversial topics in the world soil science because of differences in the principles underlying it. As of today, many countries have developed and use their own national classifications. Since scientific classification facilitates successful investigation and proper use of soils, the issue arises of representation of one classification in another. In the paper the possibility of applying fuzzy technologies to soil diagnostics based on the World Reference Base for Soil Resources is considered. A trapezoidal form of membership functions of the parameter set of diagnostic horizons is proposed. The algorithm of fuzzy diagnostics is presented on the basis of the proposed functions. Conclusion. The paper proposes a fuzzi fication mechanism for the set of indicators of diagnostic parameters and describes the algorithm of the system of fuzzy inference about the identification of the values of the corresponding parameters in accordance with the compositional inference rule. Thus, the effectiveness of the use of fuzzy technologies in soil diagnostics by the World Reference Base for Soil Resources is demonstrated.
The Design of Interplay Between Virtual Reality and Augmented Reality: A Case Study and Post Mortem of VRsus guARdian

VRsus guARdian is the result of an amalgamation of two different gameplay mediums that challenged the gap separating different mixed reality platforms, namely virtual reality (VR) and augmented reality (AR). The game utilized each medium’s approach towards immersion as a design principle in building a natural, asymmetric play for both players. The game also constructed a compelling fantasy atop each medium’s unique interactive capability to build a dynamic narrative. Lastly, the cross-platform nature of VRsus guARdian caused the game to be highly dependent upon Unity, a game engine with highly accessible, platform-agnostic development capabilities.
Story of Artificial Intelligence: research and publications behind

Artificial intelligence (AI) is now one of the most popular areas of Information technology (IT). While “a classical” problem solving is based on algorithm approach, AI offers systems which simulate human intelligence. Along with IT, AI has experienced extremely rapid development of tools, methods and applications. Nowadays AI is a buzz word, for some people a hope to solve their problems, for others a danger with negative impact on their life. AI, despite its current popularity, is nothing new. It has a long and rich history and a rich structure as well. In our paper we will show “what is behind” popularity of AI by bibliometric analysis of publications presented in SCOPUS up to the year 2019. We will show an evolution of structure of AI in particular periods of time, number of publications, the most active countries and research disciplines. We will present the results of keyword analysis using thematic maps to visualize main trends and topics of AI for each particular time period.
GA-ML-PDA Based Track Initialization with Passive Multistatic Radar (Poster)

In order to address the problem of track initialization in the presence of clutter with passive multistatic radar, a genetic algorithm based maximum likelihood probabilistic data association (GA-ML-PDA) algorithm is proposed in this paper. First, the log-likelihood ratio (LLR) function is established from multiframe measurements. Then, the track is initialized by maximizing the LLR function with the genetic algorithm (GA). Last, the extreme value theory (EVT) is used for the track acceptance test. Simulation results verify the effectiveness of the algorithm.
Design and Installation of Street Light for Public Lighting Business in Industrial 4.0

Industry development 4.0 makes every company always make continuous innovation so that it can provide satisfaction to each of its customers. In addition, it can increase the improvement in income obtained from the company. The aesthetics of the location of the company and the appearance of industrial sites will be able to attract customers to be able to increase the ordering of these industrial products. Calculation and installation of public street lighting around the location of the industry will be able to provide customer interest to come and be able to provide benefits to the company's production. The design and the installation of public street lighting will provide solutions for business feasibility in increasing revenue in the industrial era 4.0 by increasing financial and economic aspects.
Does Auditing Committee Characteristics Enhance Corporate Value? Evidence From Jordan

The study aims to investigate the effect of auditing committee characteristics, represented in the auditing committee characteristics (size, independence, activity, financial expertise) on the enhancement of corporate value, for a sample of 47 Jordanian industrial companies listed at Amman Stock Exchange (ASE) during the period of (2014-2018). To achieve this goal, corporate value was measured using the return on assets (ROA) in addition to using the Pooled Data Regression. Study found a positive relationship between the auditing committee characteristics (size, activities, independence) and corporate value in the Jordanian industrial Companies, but didn't find a positive relationship between the financial expertise variable of auditing committee and the corporate value. Based on the study results, researchers made a number of recommendations that include: researchers and academic staffs must study in the future researches some of the other variables, such as the diversity of management committee, disclosure, transparency, and auditing fees in order to enhance corporate value.
UDPP: Blockchain based Open Platform as a Privacy Enabler

Data privacy has drawn a lot of attention from people in sectors of commerce, data processing and credit reporting, especially with the adoption of GDPR, CCPA, PIPA, GB/T35273 and ISO27701 etc. These regulations aim to give people the ownership of data they produce by law, however, due to the lack of standards, tools, and best practices, many enterprises struggle to adapt their workflow and database to ensure that the data processing is in compliance with the data owner's consent and suffer from heavy fines. In light of this challenge, we develop a blockchain based platform to enable both privacy preserving and privacy compliance. UDPP (User Data Privacy Protection) platform is constructed on an immutable blockchain system, including the compliance module and the privacy tool set. UDDP provides utilities and tools to make desensitization, encryption and self-check process easier. The compliance module can assist companies to self-check on the privacy policy as well as the data processing both in their apps and backend services, while the tool set provides multiple combinations of privacy protection schemes to solve different privacy preserving and user authorization cases. Moreover, UDPP will provide the user with a “token”, which represents the permissions of the data ownership. The token can be viewed as a privacy badge, and it records hash of all the data processing and storage infos as well as the update of user consents.
On learnability and naturalness as constraints on phonological grammar

We report six experiments on learnability of four non-adjacent phonotactic con-straints which differ in their attested frequency and phonetic conditioning factors; liquid harmony, liquid disharmony, backness harmony, and backness disharmony.Our results suggest that such phonotactic constraints can be implicitly learned from brief experience and that learnability of a phonological grammar may be independ-ent of its attested frequency and phonetic basis.
THE IMPLEMENTATION OF MAKE A MATCH METHOD TO IMPROVE WRITING DESRIPTIVE TEXT AT TENTH GRADE STUDENTS IN SMK JABIR AL-HAYYAN

Based on the phenomena that students have difficulties in writing descriptive text, the students could not write because do not have any ideas when they are asked to write. So, they need some ways which could help them in writing. The problems in writing can be solved by implementing some strategies in teaching writing. One of approach that teacher can use to help students write a good text is MAM. The main objective of this study is find out if MAM can improve students’ ability in writing descriptive text. The research method used is quantitative research, specifically quantitative with one group pretest-posttest design. The sample take two class at tenth grade students of SMK Jabir Al-Hayyan in academic year 2019/2020. The data had been obtained in post-test of experimental class were: the highest score was 96, the lowest score was 62, and the mean score was 80.50. Post-test of control class were: the highest score was 89, the lower score was 60, and the mean score was 71.54. It can be seen from the data showed that students’ score in experimental class was highest than control class. It means that using make a match method was effective, easier, and more understable to be applied in teaching and learning process, especially in writing descriptive text. Keywords: Improve, Make A Match Method, Writing Descriptive Text
Case Study about efficient AI(Artificial Intelligence) Implementation Strategy

The main purpose of this paper is to study about efficient AI project implementation as a case study.For the purpose of successful AI implementation, the project plan should be robust with long term view.This implementation strategy include top management decision, organization and human resource, infra structure for AI system, end user support, and company strategy.In this study, the performance index in analyzed from the view point of ROI and business priority.
National Cyber Safety and Security: Healthcare using IoT

Internet of Things (IoT) integration with different domains provides strategic benefits to organizations and people at large.However, when it comes to security, it is linked with national cyber safety and security in one way or other.The rationale behind this is that IoT combines physical and digital worlds and the whole digital infrastructure may be linked with IoT.Thus, it is important to leverage IoT integrations to have cyber safety and security.In this paper we considered healthcare unit as case study for IoT integration and security verification.We proposed a methodology with underlying mechanisms for searching and data sharing with end to end security.We built a prototype application realized with Things Board IoT platform and Jelastic cloud platform integrated with healthcare infrastructure.Our empirical results revealed that the proposed methodology is able to provide secure data sharing and searching in such distributed environment.