Reviewerly/exHarmony huggingface dataset:
Discriminative Label Relaxed Regression with Adaptive Graph Learning

The traditional label relaxation regression (LRR) algorithm directly fits the original data without considering the local structure information of the data. While the label relaxation regression algorithm of graph regularization takes into account the local geometric information, the performance of the algorithm depends largely on the construction of graph. However, the traditional graph structures have two defects. First of all, it is largely influenced by the parameter values. Second, it relies on the original data when constructing the weight matrix, which usually contains a lot of noise. This makes the constructed graph to be often not optimal, which affects the subsequent work. Therefore, a discriminative label relaxation regression algorithm based on adaptive graph (DLRR_AG) is proposed for feature extraction. DLRR_AG combines manifold learning with label relaxation regression by constructing adaptive weight graph, which can well overcome the problem of label overfitting. Based on a large number of experiments, it can be proved that the proposed method is effective and feasible.
PENERPAN ALGORITMA BINARY SEARCH DALAM PENCARIAN DATA POTENSI INVESTASI DI KABUPATEN SELUMA DENGAN SMARTPHONE

Seluma Regency has several attractive investment sectors to develop, such as coal mining, shrimp ponds, oil palm plantations, weaving and tourism, the Seluma Government has tried to collect this potential data and package it in the form of a regional book and the limited costs do not allow to produce the book en masse so that digitalization of the data is needed but the data is large, difficult to access with keywords. Search Algorithm In general, search is defined as looking for data by tracing where the data is stored, Searching is the process of searching or searching, Binary search is a method of searching data that has been ordered. In this method all ordered data elements will be tested one by one until the desired element is found. Searching for sorted data will result in a fast search. This algorithm is used for fast search times. The test results are the largest potential area in Seluma Regency is the agriculture and animal husbandry sector (fisheries), then followed by mining and tourism sectors. Efficient and faster Binary Search Algorithm if looking for a value in a large amount of data, Because these data have been sorted first first and the complexity of the algorithm is smaller, the first drawback of Binary Search is that data must be sorted first so that the search process can run well and is more complicated.
A Face Recognition System Based on Deep Learning (FRDLS) to Support the Entry and Supervision Procedures on Electronic Exams

The novelty of this paper is represented in using some artificial intelligence techniques in the entry control to the electronic exams (E-exam) in addition to monitoring students and distinguish the situation they are during the E-exam. Therefore, the proposed system divides into two main parts, the first part to support E-exams to handle some of the weaknesses points such as validation from students' entry by using deep learning. The Self-Organized Maps (SOM) neural network was used to recognition on students' faces. SOM is characterized by its efficient for faces' image data management, as well as it's the closest technique to match inputted untrained faces' images with a database of trained faces' images accurately. On the other part, the Bag of Words model (BoWM) is used to discriminate the status of students during the exam process. The BoWM is based on Speeded-Up Robust Features (SURF) that building on the strengths of the leading existing detectors and descriptors by using a Hessian matrix. Then extracts a report showing the status of the student such as confusion, concentration, cheating ... etc. From the experimental results, the proposed system was verified images of students' faces with high accuracy and execution time have a significant indication. Determining the status of the student during the exam by adopting the technique of retrieving documents known as the bag of word model, which proved the accuracy of determining the status of the student arrived in some cases to 100%.
Foreign Language Learning As A Component Of Personnel Training In Corporate Education

The article deals with fundamental issues of forming foreign language competence in the system of corporate education, which will improve the quality of professional training.The importance of developing foreign language competence of highly qualified personnel working in many areas of the economy and socio-cultural sphere where solving professional problems is mediated by instrumental function of a foreign language has been emphasized in the conclusion.The authors prove that foreign language competence, which is now called one of the most important competencies of a specialist, should become one of the main goals of vocational education, a tool for solving professional problems for specialists working in many areas of the economy and socio-cultural sphere.They attempt to create a goal and content component of the model of foreign language teaching in the system of corporate vocational education, integrating professional and language training by creating content and procedure environment modelling situations in which professional tasks are mediated by instrumental function of a foreign language.
A No-reference Image Quality Assessment Method for Real Foggy Images

The image quality assessment results for foggy images are of great significance in the objective measurement of image quality and the design and optimization of dehazing algorithm. Initially, to address the issue that there are few no-reference evaluation algorithms for foggy image quality in real scenes, this paper proposes a no-reference quality assessment method for foggy image quality in real scenes. Firstly, we establish a real scene foggy image database and evaluate it subjectively to obtain the mean opinion score (MOS). Then, we propose a feature selection method combining correlation coefficients and union ideas, which can pick out features positively correlated with haze image quality, to simplify the features without affecting the prediction accuracy of the model. Finally, we use the support vector regression method to learn the regression mapping between features and subjective scores of the foggy images, by which we can obtain the image quality assessment results. The experimental results on the database show that the algorithm in this paper is better than other algorithms. The objective image quality evaluation results of the proposed algorithm are in good agreement with the human eye's subjective perception results. Besides, the experimental results prove that the model in this paper has better performance in predicting the quality of the image after defogging.
Sketch Based Data Retrieval Using Reversible Data Hiding on Images

Sketch Based Image Retrieval as name suggests is a branch of image retrieval that searches the images based on sketches. The sketches bridge the gap between imagination and real images. Sketches act as powerful searching tool in image retrieval. It efficiently uses the data hiding technique, which is a watermarking technique and can be used for embedding messages into images. A message can be embedded into color images without changing its grayscale version. Embedding of messages was thus done using unchanged gray version. It can also extract the messages. This unchanged grayscale version is maintained from message embedding to extraction process. This concept of watermarking generates SBIDR valuable, because many applications or algorithms for color images are based on its corresponding grayscale version. Embedding of data is carried out into in three-color channels of color image and in gray value of Sketch Image. Sketch image is encrypted with key, which will be required at the time of message extraction process after SBIR. In this way grayscale invariance is maintained which made the Sketch Based Retrieval more effective.
EXPLORING TIMEOUT AS A PERFORMANCE AND AVAILABILITY FACTOR OF DISTRIBUTED REPLICATED DATABASE SYSTEMS

A concept of distributed replicated data storages like Cassandra, HBase, MongoDB has been proposed to effectively manage the Big Data sets whose volume, velocity, and variability are difficult to deal with by using the traditional Relational Database Management Systems. Trade-offs between consistency, availability, partition tolerance, and latency are intrinsic to such systems. Although relations between these properties have been previously identified by the well-known CAP theorem in qualitative terms, it is still necessary to quantify how different consistency and timeout settings affect system latency. The paper reports results of Cassandra's performance evaluation using the YCSB benchmark and experimentally demonstrates how to read latency depends on the consistency settings and the current database workload. These results clearly show that stronger data consistency increases system latency, which is in line with the qualitative implication of the CAP theorem. Moreover, Cassandra latency and its variation considerably depend on the system workload. The distributed nature of such a system does not always guarantee that the client receives a response from the database within a finite time. If this happens, it causes so-called timing failures when the response is received too late or is not received at all. In the paper, we also consider the role of the application timeout which is the fundamental part of all distributed fault tolerance mechanisms working over the Internet and used as the main error detection mechanism here. The role of the application timeout as the main determinant in the interplay between system availability and responsiveness is also examined in the paper. It is quantitatively shown how different timeout settings could affect system availability and the average servicing and waiting time. Although many modern distributed systems including Cassandra use static timeouts it was shown that the most promising approach is to set timeouts dynamically at run time to balance performance, availability and improve the efficiency of the fault-tolerance mechanisms.
Correction to: Low-dose CT lung images denoising based on multiscale parallel convolution neural network

The publication of this article unfortunately contained mistakes. The photos of Xiaoben Jiang and Yu Yao were exchanged. The corrected assignment is given below.
English Reading Literacies to Improve Values Among Teenagers

People with high levels of literacy usually have low crime rates and high intelligence. It is expected that the school community itself will happen in the school environment like teachers and students. The purpose of this research is to collect information on the learning styles and preferences of young junior high school students who are curious and critical. It is very useful to cultivate interest in reading English literature books in order to increase the cultural and social value of students who intend to apply for school literacy campaigns. The reading literacy development model used is the Plomp model: preliminary research, prototyping and evaluation. Science books such as textbooks recommended by the Cambridge Courses may have a major and popular impact because they can increase their value in various courses that use English. Educators are expected to use related books in their learning and lead the school's reading and writing movement. The result of validation of teaching materials indicates that reading literacy material with the use of English-language publications is important and can be tested.&#x0D;
Image Intensifier Upgraded Performance and Evaluation Standard

The Gen 2 image intensifier is keeping a parallel technology development status with the Gen 3 image intensifier and the debate over the generation division and performance upgrade is also accompanying their development.Over time,as substantial breakthroughs for multi-alkali photocathode in the extended spectral range occur,as well as the development of filmless micro-channel plates(MCP)in some GaAs photocathodes image intensifiers,the term"Generation"for image intensifiers has arguably lost meaning.However,there is still lack of accurate comparison assessments for the filed performance that both generations have achieved.Though the existing military specification cannot fully reflect the upgraded image intensifier characteristic and its actual field performance,standards updates as well as investigations of the link between these characteristic parameters and the actual field performance are necessary.
Analysis of Objects Information to Create Unique Features for Color Images

Color digital images are widely circulated in various means of communication, and these images are used in multiple and vital applications, which forces us to search for easy and effective ways to represent the digital image with a set of unique values that facilitate the process of retrieving or recognizing the digital image. A digital image is mostly made up of a group of objects that can be used to generate a features vector for an image that can be used as an image identifier. In this paper, we will present a set of easy procedures through which it is possible to retrieve objects in a digital image and how to use the information of these objects to form the properties of the image. We will also demonstrate the flexibility of the presented procedures in using a wide range of object information to formulate unique image values that can be used as properties for digital image retrieval or recognition.
4 Exploiting Temporal Properties

This dissertation deals with the problem of capturing human motions and poses using a single camera. The frst part of the thesis proposes two closely related approaches for the 3D reconstruction of human motions from image sequences. To resolve inherent ambiguities in monocular 3D reconstruction the main idea of this part is to exploit temporal properties of human motions in combination with a human body model learned from training data. The second part of the thesis tackles the problem of reconstructing a human pose from a single image. A human body model is learned by training a deep neural network that covers nonlinearities and anthropometric constraints.
ICT, Financial Development And Economic Growth in ASEAN Countries

This paper examines the impact of and relationship between ICT diffusion, financial development and economic growth in selected ASEAN countries.In order to investigate this query, panel data estimations are used by utilizing data from 2003 to 2017.The finding indicates that ICT diffusion and financial development have an impact on economic growth of ASEAN countries.Consequently, the findings of the study could be an aid for the future researcher to study deeper in this research.The policymakers need to take a further initiative to improve the information technology and its applications in these countries.To gain benefit from the ICT drivers of economic growth, policymakers should enact several important policies that permit the development of financial sectors, provide a more convenient regulatory and institutional environment, increase economic openness, prioritize the allocation of resources to the development of ICT infrastructure, and contain the negative effects of inflation and government consumption.
Sedimentological Characterization of Alluvial Gold Deposits of Betrare-Oya and Its Surroundings (Cameroon Eastern Region)

Sedimentological methods such as granulometry, morphoscopy and heavy minerals analysis have been carried out to characterize alluvial gold deposits of Betare-Oya and its surroundings, with the aim to determine their origin and conditions in which they are formed and also to determine the mineralogical content of these deposits, their nature and distribution.It came out from this study the following: The alluvial deposits studied are sand, constituting of coarse fraction (grains), medium grains in abundant and fine grains.The average values of sorting index (S0) and coefficient of asymmetry (A) are respectively 2.53 and 0.73.These values indicate that the sand is poorly arranged and poorly sorted with a better classification or arrangement in the coarse fraction (grains).These are sediments that are deposited together by high competent currents.It would therefore probably be torrential deposits and or streams from short transport.Unused grains are dominating (80.5%) which translate a proximal source of the sediments.So it would be probably from the dismantling of the surrounding landforms.The heavy minerals studied revealed the presence of the following minerals; zircon, gold, sphene, green hornblende, tourmaline, rutile, augite, hypersthene, sillimanite, glaucophane, biotite, staurotide, and the opaque.These minerals belong to the cortege of plutonic and metamorphic rocks from a single proximal distributing province.
Regular Expressions and Math with Python

In this chapter, we discuss two modules in Python: re, which contains functions that can be applied for regular expressions, and SymPy, for solving mathematical problems in algebra, calculus, probability, and set theory. Concepts that we will learn in this chapter, like searching and replacing strings, probability, and plotting graphs, will come in handy for subsequent chapters, where we cover data analysis and statistics.
Developing Smart City 5.0 Framework To Produce Competency

Abstract - Smart cities are essential things that must be applied in the face of globalization and competition. In smart city 5.0, three important things discussed are human resource development, smart marketing, and information technology. These three things cannot be separated from each other because they are related. Furthermore, the smart city 5.0 article is a development from the previous article, namely smart city 1.0-3.0. Smart City 5.0 provides four important formulas for developing a smart city and a framework to guide its implementation. The four formulas and the resulting framework will develop in the next article, namely intelligent intelligence. It will continue to make prototypes and smart city intelligence applications. The result of this article is a framework that is a concept and strategy in developing a smart region that is part of a smart city. This article is still under development and research will continue. Furthermore, the development of this research will certainly require several more stages in reaching the top of the research, namely a big picture of a smart city and performance measurement for each process contained in a smart city. Therefore, it takes the right steps and formulas to produce a smart city 5.0 framework Keywords - Smart city, Human resource, Marketing, Technology, Innovation
#andràtuttobene: Images, Texts, Emojis and Geodata in a Sentiment Analysis Pipeline

This research investigates Instagram users’ sentiment narrated during the lockdown period in Italy, caused by the COVID-19 pandemic. The study is based on the analysis of all the posts published on Instagram under the hashtag #andràtuttobene on May 4, May 18 and June 3, 2020. Our research carried out a view on a national, regional and provincial scale. We analyzed all the different languages and forms (i.e. captions, hashtags, emojis and images) that constitute the posts. The aim of this research is to provide a set of procedures revealing the different polarity trends for each kind of expression and to propose a single comprehensive measure.
Research on Teaching Reform of Sewage Treatment Plant Engineering Design

In the teaching of water pollution control theory, the design of sewage treatment plant engineering is a very important practical teaching link. This teaching practice project has a very important guiding role in cultivating students' engineering practice ability. This article first analyzes the current teaching status of sewage treatment plant engineering design, expounds some problems in the teaching process, and proposes targeted reform measures to improve sewage treatment plant engineering design teaching, aiming to improve the quality of sewage treatment plant engineering design teaching .
Greenfield Projects in the Higher Education Ecosystem: The Case of Baikal School of BRICS

The ideas of global education and changes in the educational paradigm have determined new paths for the development of higher education, which are based on the creation and use of educational innovations, and have led to the emergence of greenfield projects as a new educational initiative. In this paper, we analyze the prerequisites and practices of greenfield-based modernization in Russia’s higher education. Specifically, the study’s goal is to elaborate on the role of greenfield projects in the transformation of the higher education ecosystem.University is a key element of the education ecosystem, and its greenfield projects are drivers that foster educational initiative and technology innovation, transform the ecosystem and create conditions for its further development.The method of case study made it possible to analyze the mechanism of initiating change in a particular university, identify the specific development aspects of the local greenfield project, Baikal School of BRICS, and demonstrate its systemic influence not only on the university but also on the region as a whole.Greenfield projects help universities engage actively in the formation of modern higher education landscape rather than just get passively integrated, thus extending the ecosystem’s opportunities for collaborations and innovation funding.
Empathy as a professionally significant quality of a modern blogger’s personality

This article considers empathy as a professionally significant personal quality of a modern blogger, analyses theoretical approaches of domestic and foreign researchers to the study of empathy, characterizes forms and types of empathy. The paper gives definition of blogging, describes the specifics of the blogger’s activities, taking into account the peculiarities of the online environment, and analyses the most successful bloggers of Russia. The authors describe a theoretical model of empathy and carry out an empirical study aimed at identifying professionally significant qualities of a blogger’s personality. The study considers such characteristics of a blogger as interesting content, successfulness, popularity, awareness of the topic, emotional closeness, common interests, values with subscribers and others
Bridge the Gap: High-level Semantic Planning for Image Captioning

Recent image captioning models have made much progress for exploring the multi-modal interaction, such as attention mechanisms.Though these mechanisms can boost the interaction, there are still two gaps between the visual and language domains: (1) the gap between the visual features and textual semantics, (2) the gap between the disordering of visual features and the ordering of texts.To bridge the gaps we propose a high-level semantic planning (HSP) mechanism that incorporates both a semantic reconstruction and an explicit order planning.We integrate the planning mechanism to the attention based caption model and propose the High-level Semantic PLanning based Attention Network (HS-PLAN).First, an attention based reconstruction module is designed to reconstruct the visual features with high-level semantic information.Then we apply a pointer network to serialize the features and obtain the explicit order plan to guide the generation.Experiments conducted on MS COCO show that our model outperforms previous methods and achieves the state-of-the-art performance of 133.4% CIDEr-D score.