Reviewerly/exHarmony huggingface dataset:
Attention-based Image Captioning and Evaluation Methods

Image captioning has attracted more and more attention in the field of artificial intelligence. It is a challenging task that involves natural language description generation by automatic visual data analysis. This involves understanding the visual contents of the image and then generating natural language sentences describing the image. A number of techniques have been proposed to solve this problem. This chapter presents a survey on deep learning-based image captioning techniques and the recent advances in this field. An exhaustive explanation of the evaluation metrics is also presented. The focus of this chapter is attention-guided methods since they have shown promising results for image caption generation. The existing evaluation methods are discussed in detail, along with examples to elaborate the mechanism behind them. Furthermore, the most used benchmark datasets – Flickr8k, Flick30k, and MS-COCO – are also described. Image captioning has applications in many areas. In this chapter, the application of image captioning on industrial images is presented.
A Study of Various Cost Estimation Techniques for Software Project Development

The success of the software development project depends on whether the rescued software is Product comply to customer requirements and must be delivered in time and within budget. The standardized method of software development was more evolved to predict the general cost needed for the event before the software is truly engineered. There are several effective factors important and limits in software project development which need to be defined using the accurate estimation. The highest software project costs and complete the increased cost value are related to the workforces. Perhaps the most critical issue in software engineering is the estimate of costs and the necessary effort for software project development. Software development cost estimation has received a significant amount of attention from analysts in recent years and has become a venture for the software development industry. Currently, the project's operation stage on software development is increasingly varied. Cost estimation is the technique used to measure the effort needed for production of software systems. The main impetus for this research area came from the inaccurate estimation found to be present in the development of software. The goal of this research was to provide an overview of what the current state of the art is in estimating the effort and to suggest a new approach. There is no single strategy as such that can be considered in this paper as the leading strategy so. It will be proposed that a combination of the methods should be used to get an accurate cost estimate.
Correlation of Ambiguity of Steganography with Cryptography in Text-Based Data Security

The development of information technology began with advances in the field of computerization. The early use of computers to simply write, create graphics and images and store incredible data has been transformed into a communication tool with a soft network that can cover the entire world. With the advancement of technology, the process of interaction between humans can reach the layers of society in the back of any world becomes increasingly open. Along with the advancement of technology all the information needed can be obtained easily, not least information that is confidential or top secret. Because with the help of technology all confidential information is locked or stored properly even though it can be opened and accessed by irresponsible parties. The most popular methods today are steganography and cryptography. Steganography is where confidential data is hidden or pasted in other data such as images, text, audio, or video so as not to cause suspicion of others or steganalyst. Unlike the cryptographic method, where secret data messages are scrambled or encoded so that they cannot be understood by others. And this raises suspicions from the other party or often called cryptanalyst. Based on the results or outputs of a text-based steganography (stegoteks) process against a message, text steganography in Indonesian patterns can evoke a correlation of ambiguity with cryptography in avoiding disclosure of confidential messages with a 100% accuracy rate.
Peningkatan Pemahaman dan Keaktifan Siswa Kelas V SDN Kalibening Tahun Pelajaran 2017/2018 dengan Model Pembelajaran STAD

The purpose of this study was to increase students' understanding and activeness in science subjects on light material using the STAD model. The type of research used is Classroom Action Research (CAR) which is carried out through III cycles. The research subjects were 15 students of class V of SD Kalibening Kecamatan Dukun Kabupaten Magelang consisting of 9 male students and 6 female students, conducted in the even semester of the 2017/2018 academic year in April. Data collection techniques include observation sheets and test sheets during the action and documentation of learning activities. The results of data analysis showed an increase in student activity in learning from cycle I was quite good, increased to good in cycle II, and increased to very good in cycle III. The results of research using the STAD method have been able to increase students' understanding and activeness even though they have not been maximized. This success is supported by the readiness of teachers in designing learning and learning processes that are carried out according to plan. However, there are still main factors that are felt to be inhibiting, namely not all students are able to work in groups. Therefore, researchers must often train students in group work and make interrogative sentences that help them understand the material.
The use of retelling story Narrative text in reading comprehension in the rural area

This article are be able to describes the findings of a study aimed at retelling stories of students in reading comprehension, Retelling consist of having students orally reconstruct a story that they have read.  There are some problems in the rural area particularly in Lampung during English language learning which is teachers able to creatively and enhance the strategy to teaching English in the rural area for reading comprehension. This research was conducted using retelling story. Data were collected using documentation, observation, and interview. The results of this study are the composition of children's story teaching materials that contain reading comprehension education in learning to read story for seventh graders of junior high school. The results show that students have good abilities in understanding children's stories. Student responses also strongly agree with the children's story material which contains reading comprehension education as teaching material in learning to read children's stories for VII Junior High School. In other words, this research is feasible to be used as teaching material. The feasibility and effectiveness of this research is supporting by the use of language that is relevant to the level of students' ability, the content of the teaching material contains an understanding of the stories, according to the curriculum, and is contextual to students' daily live.
ФОРМУВАННЯ УМІНЬ МАТЕМАТИЧНОГО МОДЕЛЮВАННЯ ЗАСОБАМИ ІНФОРМАЦІЙНО-КОМУНІКАЦІЙНИХ ТЕХНОЛОГІЙ

The article proposes various aspects of forming students' skills of mathematical modeling using ICT. The main approaches to creating mathematical models for problems depending on the method of data representation: verbal-symbolic, visual coding of information, sensory-emotional, subject-practical.The ability to convert oral or written data into a visual form is an important component of the skill of mathematical modeling, in the process of which such important elements of thinking as analysis, systematization and selection of the main content are formed. ICT visualization can be static (models of geometric bodies, posters, diagrams, tables) or dynamic (involves the demonstration of step-by-step changes in the situation, the movement and movement of the object of study, the process in its dynamics). The main functions of ICT visualization are to facilitate the perception, understanding and memorization of material, to ensure the systematization and generalization of material, to improve the reproduction process.The authors identified the main areas of use of ICT in the formation of mathematical modeling skills: the use of ICT as a source of information (search and demonstration of educational material, communication, distance learning); use of ICT as a means to perform calculations, create mathematical models, conduct research; use of ICT to monitor and evaluate learning outcomes. The use of online boards and interactive posters as data visualization tools has been demonstrated. The application of dynamic models developed in the GeoGebra program during the preparation for the EIT is proposed. Describes a number of useful resources that can be used in the educational process both at school and in higher education institutionsThe use of ICT in the process of studying mathematics allows for a person-centered approach based on the student's independent choice of data interpretation method. The student in the process of such educational activities forms a system of subject knowledge, skills and abilities (ICT competencies). The use of ICT in the process of forming mathematical modeling skills has the following advantages: improves the learning process; expands the interdisciplinary links of algebra and computer science through the integration of knowledge during project implementation; provides optimization of the problem-solving process; contributes to the effectiveness of students; stimulates and motivates students to study mathematics, ensures the development of creative abilities; allows students to gain experience working with a variety of software tools.
Study on the Construction of Sponge City Based on the Background of Urban Waterlogging Control

According to urban economic development in recent years, the steps of urbanization in northern cities are becoming faster and faster, which leads to an overall increase in population and the expansion of scale of cities. It is a great challenge to deal with various meteorological disasters. In China, many cities are lack of urban planning. Therefore, it is very difficult to deal with urban waterlogging. In order to solve this problem, the key point is to analyze the reasons of urban waterlogging disaster from various aspects. It is a good method for disaster treatment to find countermeasures through the reasons. This paper analyzed urban waterlogging control measures by using meteorological station, social data, population data, land data, and DEM data. Then, specific solutions were put forward.
Secure Trusted Operating System Based on Microkernel Architecture

Currently, trusted execution environment technologies are widely used to enhance the security of connected devices such as mobile phones and tablets. The trusted operating system is the core component of a trusted execution environment solution, but the trusted operating system itself may face security challenges. The main reason is that the trusted operating system needs to provide different services for different application scenarios, which makes its function more complicated and further increases the code size. In most trusted execution environment solutions, the trusted operating system is based on Monolithic kernel architecture. This will inevitably face security issues such as software defects and lack of isolation between components. In this paper, we propose a scheme for design secure trusted operating system based on a microkernel architecture. In our scheme, we take the modified take-grant model as the system security model and design a discretionary access control mechanism based on the capability system. We implemented our secure trusted operating system on the i.MX6Q platform. The test results show that it works properly and meets the requirements of the GP TEE specifications.
The Algorithm in the C-Suite: Applying Lessons Learned and Information Governance Best Practices to Achieve Greater Post-GDPR Algorithmic Accountability

The General Data Protection Regulation (GDPR) imposes customer-centric regulatory requirements for financial institutions and law firms. This chapter explores the challenges financial crime investigators and litigators alike must navigate to successfully access and process and transfer data subject to GDPR regulations, as well as the opportunities and limitations presented by available technology. Combating financial crime is undeniably predicated on global interconnectedness and the ability of financial institutions to process GDPR-regulated information. Similarly, litigation often requires sharing personal data subject to GDPR. Practitioners in both disciplines face certain implications. For instance, in the financial crime context, Article 23 suspends the application of data privacy principles when the essence of fundamental rights and freedoms is implicated and when it is necessary to prevent threats to public security. In the discovery context, litigators grapple with the subject’s right to erasure under Article 17, and when the U.S.-based duty to preserve data is triggered by a reasonable expectation of litigation. The technology implications are universal: using artificial intelligence and machine learning, single data points such as a customer’s name can be automatically scrubbed against hundreds of international watch lists, court cases and other publicly available information and used to build complex connections and profiles. Within the context of GDPR, it begs the following question: does an individual’s consent to sharing name, and other GDPR protected personal identifiers also extend to having that information amplified in an algorithm to populate, parse and predict potential criminal behavior? This chapter considers when an individual’s right to access may be restricted if a public threat or financial crime nexus is present (i.e. money laundering, fraud, terrorist financing) and how technology can further facilitate the appropriate level of information sharing while still complying with GDPR principles. It also explores conflicts between U.S. discovery rules, Article 15 (Right of Access) and Article 17 (Right to be Forgotten), and finally it reflects upon recent court decisions in the European Union (EU) and U.S. to illustrate how GDPR and increased individual data protection will affect financial crime practitioners and litigators.
Dependable Flow Analysis in Lematang Weir

Water resources are needed currently very much, especially in the area of Kota Pagar Alam for the purposes of rice fields which are planned to be served by Lematang Weir. The purpose of this study is to determine water availability to calculate dependable flow in Lematang Weir by using theHydrology Engineering Center-Hydrologic Modeling System (HEC-HMS) model. The Lematang Weir watershed is influenced by land cover and average monthly rainfall which ranges from 7.13 mm in 2018, based on rainfall data which is taken from satellite rainfall data (TRMM). Based on mapping analysis and Geographical Information System (GIS) software, the Lematang Weir watershed is obtained covers an area is 59.889 km2. By using HECHMS software, the simulation results to show that the Q80 dependable flow in the Lematang Weir watershed is 1 m3 /s and Q90 is 0.70 m3 /s.
A A study of MRI data synthesis with Convolutional Networks, KNN regression and Generative Adversarial Network (GAN)

Magnetic resonance imaging (MRI) is a technology mainly used for disease prediction and treatment. Sometimes doctors advised for computed tomography (CT) for diagnosis or therapy. But, the ionizing radiations for CT are the reason for damaging DNA which become vulnerable for repetition of usage. As, MRI does not use this kind of radiations, so it is quite good and safe for clinical testing. Practically, due to poor quality of MRI images, sometimes it is advised to repeat the scan test again which causes some unavoidable situations with increase of costs. Therefore, only the improvement of the quality of MRI images can give us the relief from these unnecessary problems. Some studies [1-4] have shown that the signal to noise ratio, image resolution, contrast sensitivity and artifacts are the main key factors for enhancing image quality. So, we need an automated supervised machine learning algorithm to generate high resolution data without more efforts.The exponentially growth of uses of MRI data [5] from past 1970’s makes a big platform for the researchers for analysing medical images. Applications of machine learning algorithms in medical field have proven its tremendous successful results to diagnose medical image. The most important is that machine learning algorithms for medical image analysis is able to find the significant relationships among data in a short time and accurate results. The aim of this study is to design a comparative analysis of MRI images for the betterment of image quality for developing treatment procedure in medical field. In this paper, some computational techniques like convolutional networks, KNN regression and generative adversarial network (GAN) are applied on the MRI images to get the high-resolution based MRI images. The methodology follows medical image localization, detection, segmentation and classification. The validation results on real data of MRI data fundamentally determines its usefulness and demonstrates the effectiveness in compared to state-of-the-art super-resolution techniques.
A Precise Lesion Localization System Using a Magnetometer With Real-Time Baseline Cancellation for Laparoscopic Surgery

Laparoscopic surgery is a technique in which surgeons insert laparoscopic instruments into the body through a small incision and conduct surgical operations. It offers a shorter recovery period, less blood loss, and less postoperative pain compared to open surgeries. In order to maximize these benefits of this surgery technique, it is important to localize the lesion accurately without palpation, minimizing the surgical area. It is because surgeons cannot palpate the organ during laparoscopic surgeries. For an accurate localization, we propose a lesion localization system (LLS). This adopts an endoscopic clip with a small-size magnet as a marker and an improved magnetometer as a probe for measuring the magnetic field from the magnet. The magnetometer, which consists of two Hall sensors, can cancel out the fluctuating magnetic baseline mainly caused by external environments so that it can detect a smaller change in the target magnetic field. As a result, the LLS improves the detection range up to 40 mm while using a weak magnet with a small volume of 17.1 mm3, which is compatible with the use of commercial clip appliers. An error of less than 0.1% is achieved at a distance of 40 mm, and the maximum error is kept below 6% even when the rotation angle is varied to ±90°. This LLS does not cause discomfort to the surgery operation because it uses a marker small enough and does not require external coils.
NEURAL NETWORK APPROACH TO ASSESSMENT OF THE EFFICIENCY OF FUNDING SYSTEMS OF SCIENTIFIC RESEARCH

NEURAL NETWORK APPROACH TO ASSESSMENT OF THE EFFICIENCY OF Funding SYSTEMS of SCIENTIFIC RESEARCH Boris Savelyev graduate student, National Research Technological University &quot;MISiS&quot;, Russia, Moscow Sergey Pronichkin cand. t
Evaluation and Customized Support of Dynamic Query form through web search

New sorted out web databases keep up enormous and assorted information and these genuine databases incorporate more than hundreds or even a colossal number of relations and characteristics. Normal predefined request structures are not prepared to satisfy distinctive uncommonly selected inquiries from customers on those databases. Dynamic Question Structure (DQF) is a novel database request structure interface, which can effectively make question shapes. The focal thought of DQF is to get a customer's tendency and rank request structure parts, profitable anyone to choose. The making of an inquiry structure is an iterative strategy and is guided by the customer. At each accentuation, the system subsequently makes situating courses of action of structure fragments and the customer by then incorporates the favoured structure parts into the request structure. The situating framework relies upon the got customer inclination. A customer can correspondingly stack the request structure and submit a request to see the inquiry result at each accentuation. Thusly, a request structure could be viably refined till the customer satisfies with the inquiry results. A probabilistic model is made for measuring the respectability of an inquiry structure in DQF. Exploratory appraisal and customer study demonstrate the sufficiency and adequacy of the structure are finished up with an experimentation results.
On the issue of malarial diseases of the nervous system

Malaria in its various manifestations is currently one of the most acute problems of an applied nature.
MOBILE LEARNING WITH THE DISK-ONLINE APPROACH

Mobile learning has become extremely important.In the challenging times of COVID-19 it is crucial to provide mobile solutions for learners which are easy to access and which provide solutions for direct feedback and interactive learning.The DISK-online approach describes settings that use tablets / laptops on the side of teachers and offers the chance to use any mobile device for the learners.This interaction setting reviewed by learners in a qualitative study in October 2020.
THE LACK OF LANGUAGE ATTITUDE AMONG BATAKNESE TEENAGERS TOWARDS SECOND LANGUAGE ACQUISITION

This research deals with language attitude and language acqusition. One language is different to other languages in this world. It insists the language user have to create the important way to maintain. Language attitude has the important role in maintaining one language. The language acquisition will be also influenced by the language attitude whether it is positive or negative. If one vernacular can be maintained by its user, it will be survived in the society or vice versa it will be lost and its acquisition is affected negatively. In other words, it can be defined that there will be a language sound change of one vernacular and it can make one language has lost its identity if the users has the negative language attitude. Batak language is one of the vernaculars in Indonesian and most dominantly used in North Sumatra. In this mini research, it will be presented that the existence of Batak language is going to be shifted by other language.
Improved Object Tracking Throughout Occlusions

Occlusions present a significant challenge to successfully track objects in video content, even with state of the art tracking algorithms. In this paper, a new tracking system, which utilizes the additional information provided by 3D video content, is presented. The system incorporates a 3D Kalman Filter coupled with occlusion reasoning, based on segmentation of the depth map, to accurately track an object during an occlusion and after it reemerges. Results show an improvement in robustness, over the state of art, especially in videos where the tracked object’s motion is linear.