Reviewerly/exHarmony huggingface dataset:
A Knowledge-Driven Enhanced Module for Visible-Infrared Person Re-identification

Visible-infrared person re-identification (VI-ReID) is a task in computer vision that has gained increasing importance in today’s social surveillance systems. VI-ReID suffers from additional cross-modality variance caused by the inherent heterogeneous gap between the visible and infrared modality compared with previous person re-identification. This paper aims to reduce the difficulty of cross-modality shared feature learning through a knowledge-driven modality. From a novel perspective, we focus on explicitly modeling an appropriate knowledge-driven modality to narrow the cross-modality difference. Specifically, we propose a Knowledge-driven Enhanced Module (KDEM) to synthesize the feature of the knowledge-driven modality and help the model accumulate transitional knowledge. The synthetic feature distribution is controlled by two modality influencing factors generated by KDEM. To this end, for better characterizing knowledge-driven modality in a diverse way, we enforce a diversity loss on the two modality influence factors, which is instrumental in the knowledge accumulation of the model. Meanwhile, the Consistency loss is proposed to maintain the similarity between the knowledge-driven modality and the other two modalities, thereby can avoid knowledge accumulation of the knowledge-driven modality impacts on the performance of the model. In all the common VI-REID tasks, Our proposed method performs state-of-the-art. The code will be announced at https://github.com/SWU-CS-MediaLab/KDEM .
Face Super-Resolution with Spatial Attention Guided by Multiscale Receptive-Field Features

Face super-resolution (FSR) is dedicated to the restoration of high-resolution (HR) face images from their low-resolution (LR) counterparts. Many deep FSR methods exploit facial prior knowledge (e.g., facial landmark and parsing map) related to facial structure information to generate HR face images. However, directly training a facial prior estimation network with deep FSR model requires manually labeled data, and is often computationally expensive. In addition, inaccurate facial priors may degrade super-resolution performance. In this paper, we propose a residual FSR method with spatial attention mechanism guided by multiscale receptive-field features (MRF) for converting LR face images (i.e., $$16\times 16$$ ) to HR face images (i.e., $$128\times 128$$ ). With our spatial attention mechanism, we can recover local details in face images without explicitly learning the prior knowledge. Quantitative and qualitative experiments show that our method outperforms state-of-the-art FSR methods.
FOTODEGRADASI ZAT WARNA METHYLENE BLUE DENGAN SINAR UV DAN FOTOKATALIS NANOPARTIKEL PERAK

The textile industry is one of the producers of liquid waste that contains many synthetic dyes and difficult to decompose such as methylene blue (MB). Approximately 15-20% of the MB products that cannot be reused will go into the wastewater which eventually be drained into the catchment waters. This causes a variety of negative impacts, especially in the water environment. One way to prevent this problem is by decomposing the dye using UV light and accelerating the decomposition process with the photocatalysts, namely silver nanoparticles. The purpose of this study is to determine the optimal conditions for the photodegradation process of MB dyes, and the effectiveness of the degradation of MB dye under optimal conditions. The search was conducted by firstly finding the optimal conditions of the photocatalyst / NPAg volume, irradiation time, and pH. The optimal condition was then applied to photodegrade various concentrations of MB to determine the effectiveness of the process. The results showed the optimal condition of MB photodegradation was 10 mL of photocatalyst / NPAg, 60 minute irradiation time at pH 4. Under such condition, the method effectively degraded 98.21% of100 ppm MB. The method used is also effective for MB up to 150 ppm because it is able to degrade almost 100%.&#x0D; Keywords: photocatalyst, photodegradation, NPAg, methylene blue, plumeria rubra.
Prefabricated House Development With Tetra Pak Carton Recycling Processing

Damage to the environment due to the increasing volume of waste every day causes concern about the impact that will be caused and felt later, in addition, the need for shelter recently has increased in line with the growth of the population in Indonesia. So not a few people who do not have a decent place to live and a lot of garbage that is not recycled properly. This is nothing to worry about if it can create a system that can reduce the potential for environmental damage caused by garbage that continues to increase and can also be a solution to provide a decent place to live. Therefore, this study made a system that can process the waste into a material that can be used as a sturdy building material and does not require much cost. The novelty of this system is in the ability to provide solutions to the problem of environmental damage caused by waste that is not recycled as well as solutions for people who do not have a place to live because of the limitations of expensive costs. Prefabricated houses also mean cutting the time in house construction to be more efficient because the design components of the house have been made outside the construction site, the material components are then brought to the construction site to be arranged modularly. According to statistics from the Brazilian government of Curitiba, waste consists mostly of organic materials, wood, glass, and fabric, and 31.7% of it can be recycled. Therefore, there is an opportunity to use these materials in developing and applying them to building construction. In addition, the cost tends to be lower when compared to conventional construction materials.
Literature About Maintaining Physical Fitness Through Digital in Community

This study aims to educate the public on how to maintain good and correct physical fitness, starting from the basic understanding, to how important it is, to how to implement it in everyday life where using digital methods in society. Education was carried out to the community members in RT 04, RW 02, Cibabat output, using the digital literacy method, namely providing information and learning through digital media to explain to the subject. The information given to the community subjects is made as concise as possible and interesting so that it is easily understood by the community. The education process is carried out online by using whatsapp and zoom meetings, while offline by conducting direct socialization to the community. The understanding of the community was analyzed through pretest and posttest questions, totaling 20 questions. The results of this study indicate that there is an increase in the score from pretest to posttest. The education provided is able to make the public understand the subject of the given theme. This shows that educational activities are successful because the information conveyed to the public can generate public interest in understanding the information that has been provided. This research can provide information that digital media can be used both as a tool for education and can increase public interest in adding new knowledge
Utilization of Augmented Reality Technology as an Interactive Learning Media

This study discusses the use of augmented reality technology as an interactive learning medium. Innovative learning media at this time have a very important role in terms of improving the quality of learning. The main point in the use of information and communication technology, especially on mobile devices such as smartphones and android tablets which of course have camera features so that they can run augmented reality (AR) application technology. The purpose of this study was to analyze how the use of augmented reality technology in education midwives as an interactive learning medium that can support the learning process of students. This study uses qualitative research methods using data collection techniques through literature studies or commonly known as library research. In the research the results obtained are analytical descriptive because this research is a qualitative research. The results of this study are the application of information and communication technology in the form of augmented reality applications in the field of education as a learning medium that can help students in facilitating learning and creating a pleasant learning atmosphere.
Meaningful Secret Image Sharing with Uniform Image Quality

In meaningful secret image sharing (MSIS), a secret image is divided into n shadows. Each shadow is meaningful and similar to the corresponding cover image. Meaningful shadows can reduce the suspicion of attackers in transmission and facilitate shadow management. Previous MSIS schemes always include pixel expansion, and cross-interference from different shadows may exist when cover images are extremely unnatural images with large black and white blocks. In this article, we propose an MSIS with uniform image quality. A threshold t is set to determine the absolute salient regions. More identical bits are allocated according to saliency values in the absolute saliency region, which can improve image quality. In addition, the new identical bits allocation strategy also adjusts the randomness of the shadow images, generating shadows with uniform image quality and avoiding the cross-interference between different shadows. Experimental results show the effectiveness of our proposed scheme.
OLCE: Optimized Learning-based Cost Estimation for Global Software Projects

Abstract Software Cost Estimation (SCE) is an integral part of pre-development stage of software project with a target to accomplish a better visibility towards possible risk while gaining more information towards reaching success rate to meet the deadline of delivery. Irrespective of multiple research contribution model towards SCE, the problem and challenges towards accurate cost estimation in presence of dynamicity and uncertainty is yet not reported to be accomplished. Apart from this, learning-based models are slowly gaining pace in almost every field and yet it is still in nascent stage of progress in software engineering. Therefore, the proposed manuscript introduces Optimized Learning-based Cost Estimation (OLCE) which is a novel learning-based model capable of accurate prediction considering global and large scale software project. The proposed system harnesses the learning potential from artificial neural network integrated with novel search-based approach for optimizing the learning method considering the benchmarked COCOMO NASA 2 dataset. The study outcome shows OLCE offers 50% faster response time with approximately 73% of accuracy compared to existing models that are reportedly found to be adopted for SCE. Hence, OLCE is found to offer a balance between accuracy and computational efficiency during SCE.
Efficient Ontology Meta-Matching Based on Interpolation Model Assisted Evolutionary Algorithm

Ontology is the kernel technique of the Semantic Web (SW), which models the domain knowledge in a formal and machine-understandable way. To ensure different ontologies’ communications, the cutting-edge technology is to determine the heterogeneous entity mappings through the ontology matching process. During this procedure, it is of utmost importance to integrate different similarity measures to distinguish heterogeneous entity correspondence. The way to find the most appropriate aggregating weights to enhance the ontology alignment’s quality is called ontology meta-matching problem, and recently, Evolutionary Algorithm (EA) has become a great methodology of addressing it. Classic EA-based meta-matching technique evaluates each individual through traversing the reference alignment, which increases the computational complexity and the algorithm’s running time. For overcoming this drawback, an Interpolation Model assisted EA (EA-IM) is proposed, which introduces the IM to predict the fitness value of each newly generated individual. In particular, we first divide the feasible region into several uniform sub-regions using lattice design method, and then precisely evaluate the Interpolating Individuals (INIDs). On this basis, an IM is constructed for each new individual to forecast its fitness value, with the help of its neighborhood. For testing EA-IM’s performance, we use the Ontology Alignment Evaluation Initiative (OAEI) Benchmark in the experiment and the final results show that EA-IM is capable of improving EA’s searching efficiency without sacrificing the solution’s quality, and the alignment’s f-measure values of EA-IM are better than OAEI’s participants.
Effectiveness of Multimedia and Text-Based Reading Approaches to Grade 10 Students’ Reading Comprehension Skills

Reading Comprehension skill is essential for learners to achieve a certain standard level. It is multifaceted that it connects to all other skills like writing, listening, and speaking. Thus, the interconnectedness of reading and comprehension encapsulates the students’ overall reading abilities. The core of this study was to find out whether multimedia and text-based reading approaches are effective in improving Grade 10 students’ reading comprehension skills. The participants were 132 Grade 10 students in a public school in Misamis Oriental. Sixty-six (66) students were exposed to multimedia reading (experimental group) and sixty-six (66) students to text-based reading (control group). The study yielded the following findings: (1) Reading comprehension skills of both groups increased gradually in all reading comprehension components as revealed in the post-test data reflected in the overall mean; (2) there is a significant difference in all reading comprehension components Identifying vocabulary, Sequencing events, Identifying main idea and key details, and Making inferences; in the overall skills of both groups with the post-test having higher means; (3) both groups revealed a significant difference in the overall result increment. This study further claims that multimedia and text-based reading approaches contribute to the enhancement of the participants’ reading comprehension skills. For the suggestion, having a variety of techniques to teach reading will be quite beneficial to improve students’ reading comprehension skills, especially in this time of pandemic where alternative delivery modalities had been implemented.
Financial Innovation, Technological Innovation and Economic Growth

By selecting 31 provinces and cities in China as samples, we constructed a panel data model from 2011 to 2019, and empirically analysed the impact of financial innovation and technological innovation on economic growth through regression analysis of fixed effects models.The results show that financial innovation and technological innovation have a positive role in promoting economic growth, and the interaction of financial innovation and technological innovation has a greater contribution to economic growth.Making full use of foreign businessmen and maintaining the increase in natural population growth is also conducive to economic growth.
The Scenario Analysis for NPV and IRR in Mutually Exclusive Projects

In the real world, the project of business decision is relatively long and requires more capital investment, which leads to higher requirements for the feasibility of project investment and scientific decision-making.To improve the science of business decision-making, the application of a series of evaluation indicators and analysis methods to quantitatively analyze the feasibility of the project is a reliable measure.Among countless evaluation indexes, the dynamic indexes are usually more superior when it refers to help make comparisons and decisions between different business projects.The net present value (NPV) and internal rate of return (IRR) are the most used indexes due to their reliability, scientific and representativeness.Normally, the application of both indexes in evaluating the feasibility of an independent project leads to the same conclusion.However, in mutually exclusive projects, the use of these two indexes may result in contradictory results, this thesis aims to analyze the cause of this contradiction from the angle of theory and practice.Compare the advantages, disadvantages, and differences of both indexes.By giving the example of two mutually exclusive projects, analyze how NPV and IRR change under different discount rates, find out the connection among them.In the end, discuss the application of these indexes and ponder the defect of this finding, investigate the future development.
Two Different Types of Verb Phrase Fronting Constructions in Korean

In this paper, I attempt to investigate two forms of verb phrase fronting constructions in Korean: 1) verb doubling VP fronting and 2) do-support VP fronting constructions.First, I lay out common properties of the two constructions and show that verb phrase fronting constructions in Korean involve verb phrasal movement rather than being base-generated in the left-periphery.Furthermore, I observe that the two VP fronting constructions exhibit differences regarding the verb types and negation.I argue that these differences are caused by the variation in the size of the targeted materials for fronting and its interaction with the syntactic constraint, a type of the Condition of the Extraction Domain (CED).
Path planning for mobile robots based on the Time&amp;Space-Efficient improved A* algorithm

Aiming to solve the problems of low search efficiency, more redundant nodes and path turning points in the traditional A* algorithm for mobile robot path planning, an improved time and space efficient A* algorithm called <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{TSE}_{-}\mathbf{A}^{\ast}$</tex> algorithm is proposed. Firstly, an adaptive heuristic function is designed according to the number of environmental obstacles, the starting point and the ending point of the path, which makes the algorithm perform well in different environments. Then, by optimizing the node selection strategy, we can improve the efficiency of the algorithm and reduce the running time of the algorithm, reduce redundant nodes and optimize the path, so as to make the path more smooth. The results show that the proposed <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{TSE}_{-}\mathbf{A}^{\ast}$</tex> algorithm is much better than the traditional <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{A}^{\ast}$</tex> and the Time-Efficient <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{A}^{\ast}$</tex> algorithm not only in path length and the number of turning points, but also in search time.
Design of anti-counterfeiting system based on blockchain and NFC tag

In order to solve the problems of centralized anti-counterfeiting system and illegal merchants copy authentic commodities at low cost and with low difficulty. This paper proposes an anti-counterfeiting system design based on the combination of blockchain and NFC tag. This system uses the Hyperledger Fabric blockchain development platform, Anti-counterfeiting certificates are used to prove that the commodities are genuine, encrypting the anti-counterfeiting certificate with ECC (Elliptic Curve Cryptography) public key forms ciphertext, then store the ciphertext in the blockchain ledger. Write the SHA256 value of the anti-counterfeiting certificate and the ECC private key, which can transform from ciphertext to anti-counterfeiting certificate, into the NFC tag. the query times can be recorded through MySQL database. It ensures the uniqueness and non replicability of the anti-counterfeiting certificate of the product, greatly improves the anti-counterfeiting performance and the difficulty of counterfeiting.
The Mathematics Teaching Performance of Scholar Education Graduates in Selected Public Schools in the Philippines: An Explanatory Sequential Mixed Method Study

This explanatory sequential mixed method study aimed to determine the mathematics teaching performance of Bachelor of Secondary Education (BSEd) major in Mathematics scholar education graduates for the period 2010-2015 of a certain state university in Western Visayas region in the Philippines. Eight BSEd major in Mathematics scholar education graduates and their eight department heads were included in the study purposively. The researcher adopted the Results-Based Performance Management System (RPMS) tool of the Department of Education (DepEd) and utilized interview guide and observation guide as data gathering instruments. Moreover, the statistical tools used were mean and standard deviation to analyze and interpret quantitative data. On the other hand, thematic analysis was used to analyze qualitative data. The study revealed that the overall performance of the scholar education graduates was very satisfactory. Moreover, the scholar graduates manifested the following in their teaching performance: a) content knowledge and relevance through mastery of the content; b) instructional strategies by using game-based strategy; c) learning activities and instructional materials by using ICT-based instructional materials; d) lesson organization and presentation by using 4A’s Model and DepEd’s format in lesson planning; e) classroom management by imposing rules and practicing routines; and f) evaluation by using authentic assessment. This shows that the scholar graduates have discovered new teaching strategies, different ways of teaching mathematics, used innovative materials and assessed students in various means not just to make themselves productive and excellent in mathematics education but to achieve quality learning for the students. It’s only then that teaching becomes rewarding.
OCLC Annual Report 2020–2021 Translated

The abridged translation into Russian of the annual report of OCLC (Rise beyond OCLC Annual Report 2020–2021) is offered. The traditional vectors of expanding accessibility and functionality of the company’s core product, namely WorldCat, and increasing focus on document delivery and professional partnerships with publishers’ are demonstrated. Special attention is given to linked data and project to involve wide public worldwide in cataloguing.The majority of public and academic libraries prefer using the world catalog WorldCat thus avoiding large scale cataloguing processes. Unfortunately, this country drags heels about using this treasure: Cyberleninka joined the WorldCat in 2016; the Russian union catalog Libnet comprises 13.6 mln recors (as for 2020), and the Union Catalog of sci-tech literature – 1.2 mln entries (as for 2022). At the same time, based on OCLC Annual Report 2020–2021 data, the WorldCat embraces 515 mln records reflecting 3.1 billion items in library collections. Such impromptness may be due to Russian professionals’ ignorance of the English language.