Reviewerly/exHarmony huggingface dataset:
Digital transformation in the Hungarian banking industry – Experiences with Design Thinking

The study examines the possibilities of the digital transformation of the Hungarian banking industry through the “One Week Sprint” method, derived from general design thinking methodology. In our research, we cooperated with two domestic banks and focused on real estate related opportunities and SME offerings. The methodological focus was on how to use customer journeys and personas for supporting digital efforts, as design thinking places a great emphasis on these elements. The paper has two goals: 1) present the findings of this innovative project with the two banks using design thinking; 2) describe our experience with customer journeys and personas in consumer- and corporate-facing innovation projects in the two banks. To our knowledge, there is no practical experience in the literature regarding the usage of these tools. We found that the usage of customer journeys and personas are much easier and evident if the project tries to develop consumer products or solutions. If the solutions are for corporate use, personas lose the added value of empathy (without the human connection) and the creation of customer journeys needs deeper experience from consultants.
Comparative Evaluation of Anisotropic Filters Used to Reduce Speckle in Ultrasound Images

Image denoising in medical image processing is essential to improve the visual quality of the image and, consequently, the diagnosis. Speckle, a multiplicative noise that degrades the image, is common in ultrasound imaging as it tends to degrade the resolution and contrast in the image. Several filters have been developed to reduce this kind of noise. This paper presents a comparative evaluation of some anisotropic filters used to reduce the speckle noise in ultrasound images. The evaluated filters were Coherence-Enhancing Diffusion (CED), Speckle Reducing Anisotropic Diffusion (SRAD), Detail-Preserving Anisotropic Diffusion (DPAD), and Anisotropic Diffusion Filter with Memory Based on Speckle (ADMSS). The filters processed four phantom ultrasound images with speckle noise. The comparison performances of filters occurred by using Mean Square Error, Signal to Noise Ratio, Peak Signal Noise Ratio, and Structure Similarity Index. The results showed that ADMSS better reduces speckle noises in ultrasound images, compared to the other filters evaluated.
Color Scheme Learning System of Clothes

Color scheme is an indispensable existence from our lives, and clothes are also important for the formation of impressions. The problem with the conventional learning method was that after actually coloring, feedback on that answer could not be obtained. In order to solve this problem, in this research, we have developed a computer system that can color interactively in clothes shaped figures. In addition, in this system, we have developed PCCS, coloring technique and its judgment function, answer advisory function, answer preservation function for more effective learning. As an application of this system, we have developed a method using a personal color was also shown. From the evaluation experiments, we have verified the validity, usability and operability of the system.
Applying a Novel Feature Set Fusion Technique to Facial Recognition

An important use of facial recognition is the Take Me Home project. In this project, people with disabilities (PWD) are voluntarily registered so that law enforcement officers can identify them and bring them home safely when they are lost. In an application like Take me Home, optimization of person recognition is of prime importance. While facial recognition models have seen huge performance gains in recent years through improvements to the training process, we show that accuracy can be improved by combining models trained for different recognition objectives. Specifically, we find that the accuracy of facial recognition model is higher when its output is fused with the output of model trained to recognize specific attributes such as hair color, age, lighting, and picture quality. The fusion is performed with a linear regression that can be applied to countless other machine learning tasks. The main contribution of our methodology is the mathematical formulation and a neural network using the Inception Net architecture that enables the recognition of the person using up to 40 attributes. In addition, we designed a framework that uses a joint linear regression scheme to combine the facial feature vectors produced by the facial recognition module and the attribute vectors produced by the attribute recognition module. The result is an efficient solution in which a lost person is more accurately identified by police officers even under unideal conditions.
Architectures for Blockchain in the Management of Medical Records: A Comparison

The use of electronic medical records represents a breakthrough in the health sector by having the digitized information. However, there are aspects where privacy can be compromised, since it has sensitive information. The use of Distributed Accounting Technology (DLT) decentralizes the data to have the most secure information in a network of encrypted nodes. Solutions like blockchain and cloud services approach both security and data collaboration. However, it remains to know the variables of efficiency and scalability that compromises a blockchain solution for the health sector. We compare two blockchain architectures to measure the efficiency in the response time of medical records and we evaluate some factors such as availability, interoperatbility, integrity, collaboration, multiplatform, resistance to attacks to rate which is better in the context of medical records.
Aggregation of Word Embedding and Q-learning for Arabic Anaphora Resolution

In many linguistic situations, the repetitions of objects and entities are reduced to the pronoun. The correct interpretation of pronouns plays an important role in the construction of meaning. Thus, the resolution of the pronominal anaphors remains a very important task for most natural language processing applications. This paper presents a novel approach to resolve pronominal anaphora in Arabic texts. At first, we identify non-referential pronouns by using an iterative self-training SVM method. After, we resolve the antecedents by combining a Q-learning method with a Word2Vec based method. The Q-learning method seeks to optimize, for each anaphoric pronoun, a sequence of criteria choice to evaluate the antecedents and look for the best. It uses syntactic criteria as preference factors to favor candidate antecedents over others. The Word2Vec method uses the word embedding model AraVec 3.0. It provides the semantic similarity measures between antecedent word vectors and pronoun context vectors. To combine Q-learning and Word2Vec results, we use a ranking aggregation method. The resolution system is evaluated on literary, journalistic and technical manual texts. Its precision rate reaches until 80.82%.
Guessing the Code: Learning Encoding Mappings Using the Back Propagation Algorithm

Error correction codes such as low density parity check (LDPC) codes are popularly used to enhance the performance of digital communication systems. The current decoding framework relies on exchanging beliefs over a Tanner graph, which the encoder and decoder are aware of. However, this information may not be available readily, for example in covert communication. The main idea of this paper is to build a neural network to learn the encoder mappings in the absence of knowledge of the Tanner graph. We propose a scheme to learn the mappings using the back propagation algorithm. We investigate into the choice of different cost functions and the number of hidden neurons for learning the encoding function. The proposed scheme is capable of learning the parity check equations over a binary field towards identifying the validity of a codeword. Simulation results over synthetic data show that our algorithm is indeed capable of learning the encoder mappings and identifying the parity check equations.
MCAMC: minimizing the cost and makespan of cloud service using non-dominated sorting genetic algorithm-II

The number of cloud users and their aspiration for completion of tasks at less energy consumption and operating cost are rapidly increasing. Hence, the authors of this paper aim to minimize the makespan and operating cost by optimally scheduling the tasks and allocating the resources of cloud service. The optimum task scheduling and resource allocation are obtained for each objective function using the simple genetic algorithm. Further, the non-dominated solutions of the dual objectives are obtained using the non-dominated sorting genetic algorithm-II, the most successful multi-objective optimization technique. A complex cloud service problem consisting of ten tasks, fifteen subtasks and fifteen heterogeneous resources is considered to investigate the proposed method. The numerical results obtained in the single objective and multi objective optimization problems show that the makespan and the operating cost are significantly reduced using the simple genetic algorithm and a wide range of non-dominated solutions are obtained in the multi-objective optimization problem, by which the cloud users shall be benefitted to choose the most appropriate solution based on the other design constraints they have.
Comparison Of RSA Algorithm & Hybrid RSA-OTP Algorithm For Image Security

Abstract Transferring an image is one of the common processes. The image transferring, the sender wants to send a picture by maintaining the security and integrity and even the confidentiality of an image. One of the techniques to manage that aspect is cryptography – hybrid cryptosystem and Rivest-Shamir-Adleman algorithm. Hybrid cryptosystem uses RSA-OTP algorithm for its combination. Hybrid cryptosystem has the strength to secure an image because of its combination of the algorithm. A hybrid use symmetric algorithm to encrypt the image and asymmetric algorithm to encrypt the key from a symmetric algorithm. Rivest-Shamir-Adleman algorithm is an asymmetric algorithm which is hard to guess because of its different key. Rivest-Shamir Adleman Algorithm has a public key to encrypt and private key to decrypt; also prime test was implemented using the Agrawal-Kayal-Saxena algorithm. One-Time-Pad algorithm is a symmetric algorithm that is too hard to guess because this algorithm must have a key which length must be similar to plain’s length, the more length of the plain, the harder key to guess.
Innovative Application of Big Data Technology in Southwest Pipeline Information System

With the in-depth construction of the “digital pipeline”, the full pipeline system has digitally upgraded various systems through the use of advanced information networking technologies, such as the Internet of Things and mobile Internet, and gradually realized production automation, unattended operation valve room, flat management of the labor organizations architecture, digital pipeline construction has entered the stage of operation management and maintenance. However, the traditional manual maintenance and passive maintenance methods cannot satisfy the needs. It is urgently necessary to rationally plan, develop, and optimize the pipeline support system, and to use the big data technology to establish standardized and unified pipeline Internet of things protection system specifications and to create efficient intelligent management platform. The purpose is to achieve standardized, scientific, intelligent, and high-efficient pipeline operation and maintenance.
The National Library of China is the research and methodological center for public libraries

The structure of the network of public libraries inChina, their place in the unified library system of the country are discussed: their material, technical, resource and service potential is characterized as the basis for building a knowledge-based economy inChinaby 2050. The content of the first in the history of Chinese librarianship the national legislative act on libraries – Chinese People’s Republic Law on Public Libraries, which came into effect in January 2018, is disclosed. The role of the Central National Library of China as a scientific and methodological center for managing public libraries is identified, and the main directions of its scientific and methodological activities are described; in particular, building the legislative corps for the Chinese library system, standardization of information services and technologies; corporate cataloguing, implementation of innovative (network, mobile, virtual) services, aspirations for innovative experiments, the acquisition of practical skills in working with high-tech equipment, building the organizational foundations for acquiring Chinese National Digital Library and National Digital Children’s Library; preservation and conservation of library collections, including their digitization, and participation in various forms of professional development.
Content and methodical features of studying the elective course "Computer Architecture" using WEB 2.0 educational services

The article analyzes the real state of student training in the subject area "Informatics" and substantiates the need to increase the attention of teachers and authors of textbooks to the section "Computer Hardware and Software", which has important didactic and applied importance. The solution of this task is based on the development and implementation of the elective course "Computer Architecture" for students in grades 10–11 of information and technological or physical and mathematical profiles. A significant part of the course is devoted to learning the basics of programming on low-level languages. Software and methodical support for the course includes a target unit, thematic planning, a fund of assessment tools (diagnostic tasks, tests, interview questions, topics for educational projects), theoretical information, and task material for laboratory work. The course features are multi-format work with students, providing for the implementation of educational projects, organization of role games, students’ learning and research activities in solving individual tasks. It is proposed to widely use public educational Web 2.0 services (Tiki-Toki.com, Google services, LearningApps.org and etc.) as methodological support. Particular attention is paid to the study of low-level machine-oriented programming language Assembler. Students solve special tasks using the analogy with the algorithmic structures of high-level languages, learn to compose, translate, and test a program in the specified language. The presented methodical solutions were successfully tested in real educational practice.
THE CONCEPTS OF DESIGNING COMPETENCE IN THE CONDITIONS OF THE MEDICAL COLLEGE ENVIRONMENT

This article identifies the primary objectives of education development in Ukraine for 2012-2021. It is established that the formation of modern logistical support for the educational sector, support for the development of electronic educational tools, implementation of ICT training of teachers, ie, in general, providing the necessary prerequisites for the modernization of the education system on an innovative technological basis are among the top priorities. The contradictions in the field of potential opportunities for increasing the effectiveness of the educational process in practice are highlighted. It is determined that the educational and information environment can be called distributed on the territorial and level principle of the mastery of information and educational spaces, which aims to create conditions conducive to the emergence and progress in the processes of educational and network relationships between objects and entities environment, and to shape the activity of objects, to stimulate educational and social initiatives so that competence develops as a significant value for both society and the individual. It has been found out that the application of step-by-step integration of OIs can contribute to the natural formation and development of educational and information environment with the direct participation of teaching staff. In this case, the conceptual cascade-loop diagram illustrates the system of interconnections between each of the main elements (stages) of this process. The factors that led to a significant expansion of the scope of electronic resource in the educational process have been identified. A number of designing skills necessary for the formation of a design competency in the teacher were identified, the structure of which includes the knowledge, skills and professionally significant personality qualities required for the design activity. The requirements for the organization and preparation of medical college students for the development of electronic educational resources are defined. It is found that the introduction of the latest information and communication technologies in the educational process has led to significant changes in the didactic system. It is proved that mobility determines the success of each of the graduates in the conditions of the digital and technological society, the possibility of effective cooperation, solving
Priority Based Virtual Machine Allocation and Scheduling for Security in Cloud Computing

Cloud computing relies on the advancement of distributed computing and virtualization technologies to achieve cost efficiency in the consumption of computing resources. Efficient resource allocation is one of the important concerns for cloud users. To satisfy the need of each cloud user in an efficient manner, provision has to be made to make sure that the resources are available to them at all the time. Optimal resource allocation with minimum wastage and maximizing the profit is considered to be challenging. Also once the resources are allocated, isolation among them is critical from security point of view as there exits various kinds of adversary attacks in the real world. In this paper a novel method has been proposed for priority based dynamic Virtual Machine (VM) allocation on the basis of various parameters such as No. of nodes or processor’s request, Time of execution, Importance of user, Amount of storage required etc. and isolation among the allocated virtual machines since the virtualized services, hardware, software and infrastructures share the same physical resources. Also there are chances of adversary users hosted on the same hardware which may lead to various kinds of cross VM attacks and security threats. Finally an approximation technique for resource allocation problem has been addressed which consider each unallocated resource request from user that may lead to penalty for cloud administrator which increases as time elapses. As the resource allocation problem is considered for various applications, particularly for emergency service allocations such as scientific simulations related to cyclone prediction, monsoon prediction, rainfall etc. which needs high performance computational power. Thus allocating the resource request within the predetermined time limit is of primary concern otherwise it may lose its purpose.
“AlkhalilDWS”: An Arabic Dictionary Writing System Rich in Lexical Resources

In the classical lexicography, making dictionary was accomplished with pen and paper which increases the effort and the time spent by editors. To avoid this challenge, the modern lexicography resort to computer linguistics technologies. As a consequence, many software programs called Dictionary Writing Systems (DWS) were developed to simplify the work of editors, to guarantee the compilation of dictionaries in a structured data allowing the publication of interactive versions of produced dictionaries and to allow the exchange of lexical data in other natural language processing applications like automatic translation and semantic web. The purpose of this paper is to describe the Arabic Dictionary Writing System “AlkhalilDWS”, a new web application used to edit and publish monolingual Arabic dictionaries. It provides many functionalities that minimize the time and the efforts spent to make an Arabic dictionary. Also, using “AlkhalilDWS” guarantees the exportation of the dictionary in the standard format Lexical Markup Framework (LMF) which is recognized by the International Standards Organization (ISO).
Static Crowd Scene Analysis via Deep Network with Multi-branch Dilated Convolution Blocks

In this paper, we have proposed a static crowd scene analysis network via multi-branch dilated convolution block, called MDBNet. It focuses on a joint task of estimating crowd count and high-quality density map from static single image. The proposed MDBNet follows one-stage object detection framework, and consists of two parts: pre-trained convolutional layers as the front end for high-level feature extraction and cascaded multi-branch dilated convolution block as the back end for context information aggregation on different ranges. Pixel-wise objectness probabilities are predicted and regressed to generate density map. The proposed MDBNet is an easy training model with strong learning ability. We have tested it on two public datasets (ShanghaiTech dataset and the UFC_CC_50 dataset). On almost all evaluation criterions, the proposed method has achieved superior performance. Especially on structure quality criterions, including our newly introduced spatial adjusted mutual information measurement, the MDBNet reports a new state-of-the-art performance. The source code will be distributed depending on publication of our work.
Research On An Intelligent Atomic Clock System

As an important timing and punctuality equipment, atomic clocks have many limitations in their use. Most of existing clocks are monitored by local computer terminals, but for user parameter adjustment and fault diagnosis are both professional and difficult to complete. Moreover, for maintenance personnel, it's hard to grasp the situation of problematic clocks. It also increases the difficulty of fault location, consumes more time and effort.This article puts forward an idea of realizing parameter control digitization through improved control system, remote monitoring through the Internet of Things, and intelligent diagnosis of fault diagnosis through Artificial Neural Network(ANN). Taking hydrogen maser as an example, it can only be manually adjusted. So we digitized the manual circuit and wrote program on it, letting hydrogen maser intelligently judges the current running state and automatically adjusts its internal parameters. For problems which are difficult to adjust by itself, the pre-judgment can also be carried out to a certain extent, which is convenient for the technician to fix. In addition, hydrogen maser has an embedded web server, uses the Internet of Tings(IoT) to deliver parameters, state analysis results, historical data in real time, then performs device identification and data sorting. User can access it by any browser-equipped terminal, instantly view the data and command hydrogen maser, thereby realizing the real-time, unlimited geographical area, and intelligent analysis of remote monitoring atomic clock system.
Effects of WER on ASR Correction Interfaces for Mobile Text Entry

Speech is increasingly being used as a method for text entry, especially on commercial mobile devices such as smartphones. While automatic speech recognition has seen great advances, factors like acoustic noise, differences in language or accents can affect the accuracy of speech dictation for mobile text entry. There has been some research on interfaces that enable users to intervene in the process, by correcting speech recognition errors. However, there is currently little research that investigates the effect of Automatic Speech Recognition (ASR) metrics, such as word error rate, on human performance and usability of speech recognition correction interfaces for mobile devices. This research explores how word error rates affect the usability and usefulness of touch-based speech recognition correction interfaces in the context of mobile device text entry.