Reviewerly/exHarmony huggingface dataset:
Balancing Policy Coherence in Socio-hydrology

&amp;lt;p&amp;gt;Renewed global mandates have encouraged widespread use of nature-based solutions (NBSs) for addressing overlapping benefits of hydro-environmental impact, social conditions (mental and physical health, sense of well-being, food security), biodiversity, and ecosystem restoration. However, the decision to implement nature-based solutions is posed with challenges regarding policy effectiveness and stakeholder buy-in. Such complexities may be assessed through the lens of socio-hydrology with enhanced approaches for incorporating human behavior into the modeling paradigm. Here, a novel framework is presented and demonstrated that applies stakeholder cognitive mapping and feedback loop analysis through a series of soft-systems approaches to elicit an understanding of the complex interactions between the physical processes served by NBSs and their human-directed management opportunities. The community-led application reveals a means for balancing complex governmental structures across multiple agencies toward policy coherence, where we identify synergies and conflicts between disparate management strategies regarding optimal allocation of NBS socio-hydrological benefits. A demonstrated case study in Houston, Texas reveals unexpected feedbacks resulting from interacting causal influences across the social and hydrological domains according to the norms in a given locale, such as the influence of climate, flood memory, advocacy, and benefit visualization. The flows of information throughout the cycle are transformed by belief systems embedded within the stakeholder cognition, which may be used to perform a semi-quantitative scenario-based assessment for identifying and better-understanding policy coherence amongst a plethora of NBS decision-making options. Typically, sole reliance upon scenario-based modeling obscures the feedback loop logic embedded within the system. Conversely, causal loop diagrams alone may quickly become convoluted, which are difficult to decipher from human visualization, particularly as we encounter double and triple loop influences. By combining both loop analysis with scenario-based modeling within one framework, we are better able to &amp;lt;em&amp;gt;identify&amp;lt;/em&amp;gt; areas of policy coherence while also &amp;lt;em&amp;gt;explaining &amp;lt;/em&amp;gt;the emergence of synergies and trade-offs according to causal loop logic. Such a framework is applicable to a variety of complex systems with overlapping socio-hydro-environmental processes that are influenced by political decision-making across institutional scales.&amp;lt;/p&amp;gt;
Implementation of the advanced encryption standard algorithm on an FPGA for image processing through the universal asynchronous receiver-transmitter protocol

&lt;span lang="EN-US"&gt;Communication among end users can be based either on wired or wireless technology. Cryptography plays a vital role in ensuring data exchange is secure among end users. Data can be encrypted and decrypted using symmetric or asymmetric key cryptographic techniques to provide confidentiality. In wireless technology, images are exchanged through low-cost wireless peripheral devices, such as radio frequency identification device (RFID), nRF, and ZigBee, that can interface with field programmable gate array (FPGA) among the end users. One of the issues is that data exchange through wireless devices does not offer confidentiality, and subsequently, data can be lost. In this paper, we propose a design and implementation of AES-128 cipher algorithm on an FPGA board for image processing through the &lt;a name="_Hlk107307233"&gt;&lt;/a&gt;universal asynchronous receiver transmitter (UART) protocol. In this process, the advanced encryption standard (AES) algorithm is used to encrypt and decrypt the image, while the transmitter and receiver designs are implemented on two Xilinx BASYS-3 circuits connected with a ZigBee RF module. The encrypted image uses less memory, such as LUTs (141), and also consumes less chip power (0.0291 w), I/O (0.003), block RAM (0.001 w), data, and logic to provide much higher efficiency than wired communication technology. We also observe that images can be exchanged through the UART protocol with different baud rates in run time.&lt;/span&gt;
Does the Solution to the Non-linear Diophantine Equation 3&lt;sup&gt;x&lt;/sup&gt;+35&lt;sup&gt;y&lt;/sup&gt;=Z&lt;sup&gt;2&lt;/sup&gt; Exist?

This paper investigates the solutions (if any) of the Diophantine equation 3x + 35y = Z2, where , x, y, and z are whole numbers. Diophantine equations are drawing the attention of researchers in diversified fields over the years. These are equations that have more unknowns than a number of equations. Diophantine equations are found in cryptography, chemistry, trigonometry, astronomy, and abstract algebra. The absence of any generalized method by which each Diophantine equation can be solved is a challenge for researchers. In the present communication, it is found with the help of congruence theory and Catalan’s conjecture that the Diophantine equation 3x + 35y = Z2 has only two solutions of (x, y, z) as (1, 0, 2) and (0, 1, 6) in non-negative integers.
A Framework of Automatic Ontology Construction based on Scene Graph Generation Model for Analysis of Story Video Contents

In this paper, we propose an extended ontology automatic construction framework based on multiple deep learning models as part of an effective analysis of story video content. Semi-automatic techniques using image processing techniques have been the mainstream for the existing ontology construction methods for moving pictures, but there is a problem that human intervention is required and the accuracy is low due to the limitations of image processing techniques. To overcome this, in this paper, we propose an auto mated method based on the deep learning scene graph generation technique. In particular, in the case of video content with a story, the relationship between characters is a very important factor in understanding the scene, so deep learning-based object relationship creation model, character identification model, and important area caption generation model are applied to extract objects and recognize their relationships. And design a framework that automatically builds a domain ontology dependent on the story through procedural fusion between each model and module function. In addition, the proposed framework suggests a method for efficiently processing system requirements and system resources through meta control in the condition that requires simultaneous operation of multiple deep learning models to analyze story video content. Through this, the proposed framework effectively identifies critical region captions and object relationships in a scene in story-telling video content, and executes three types of models simultaneously. Finally, we conduct an experiment to automatically build an ontology by applying the proposed framework to specific video content, and check the effectiveness of the proposed framework.
Anonymous Traceback for End-to-End Encryption

As secure messaging services become ubiquitous, the need for moderation tools that can function within these systems without defeating their purpose becomes more and more pressing. There are several solutions to deal with moderation on a local level, handling harassment and personal-scale issues, but handling wider-scale issues like disinformation campaigns narrows the field; traceback systems are designed for this, but most are incompatible with anonymity. In this paper, we present Anonymous Traceback, a traceback system capable of functioning within anonymous secure messaging systems. We carefully model security properties, provide two provably secure and simple constructions, with the most practical construction able to preserve anonymity for all but the original source of a reported abusive message. Our implementation shows integration to messaging systems such as Signal is feasible, with client-side overhead smaller than Signals’ sealed sender system, and low overhead overall.
Study on Organizational Response Management to System Failures

Critical infrastructures are interdependent, and among them, information and telecommunications tend to have a wide range of influence in that they are responsible for the neural functions of other critical infrastructures. Therefore, reducing the occurrence of information and communication failures is a highly important issue for maintaining a safe and secure social life. To solve this problem, in addition to improving system reliability and preventing system failures from occurring, emphasis is being placed on the concept of reducing the magnitude of damage and the time required for recovery, based on the assumption that system failures will occur. Specifically, companies and local governments have embodied this concept in BCP (Business continuity planning) and BCM (Business continuity management), which are mechanisms to prevent the suspension of operations. The information system has been conventionally considered to be a "business continuity plan" or "business continuity management. In the past, there have been examples of preparing emergency manuals for information systems as a way to deal with system failures. However, there was a possibility of ad hoc management in the event of unexpected situations, such as deviations from the assumed plan. This paper discusses how to improve the management of emergency response after a system failure by introducing the concept of project management. The effectiveness of the proposed method will be examined through case studies of system failures.
Senior Learning JAYA With Powell’s Method and Incremental Population Strategy

JAYA algorithm is one a recently developed meta-heuristic algorithm that does not require algorithm-specific parameters. It is an algorithm based on the fact that the solutions always go towards the best when searching. This paper proposes a JAYA variant (JAYA-SIP) with three improvements to the Original JAYA algorithm. It has incorporated the senior learning strategy, the incremental population strategy, and Powell’s local search method into JAYA. The improvements were tested with IEEE Congress on Evolutionary Computation (CEC) benchmark set for 30 and 50 dimensions, and the benchmark functions set from a special issue of the Soft Computing journal (SOCO) for 500 and 1000 dimensions. In addition to benchmark sets, the performance of JAYA-SIP was evaluated with nine CEC 2011 real-world test functions. The results of the proposed algorithm are compared with JAYA variants and some meta-heuristic algorithms. According to the results of the experiment and the analysis, the proposed improvements increased the performance of the JAYA algorithm. JAYA-SIP achieved better results than the other algorithms it was compared with.
PEMBUATAN EMBEDING/BIOPLASTIK HEWAN INVERTEBRATA DI BAKAL SEKOLAH ALAM “ISYO HILLS” KAMPUNG WISATA RHEPANG MUAIF NIMBOKRANG, KABUPATEN JAYAPURA

The high biodiversity in Papua can be used as biology learning material and an educational laboratory model for students in Repang Muaif Village. The diversity of animals, plants and microorganisms can be introduced or shown easily in the classroom to students with a learning medium. Facts in the field show that most teachers still provide biology material verbally without adequate media or teaching aids. This kind of learning model will inhibit the development of reasoning, interest and motivation of children to learn biology. Most biology teachers carry out learning without props because they do not have much time to provide it or do not have adequate tools / materials in school. Teachers at the nature school in the Rhepang Muaif should be able to take advantage of the existence of invertebrates in the forest around the school as learning media or teaching aids for their students. One effort that can be made to develop instructional media in schools is to introduced a technique for making invertebrate bioplastics/embedding. The purpose of this training was to introduce and practice directly the collection techniques and to introduced a technique for making invertebrate bioplastics/embedding to participants in Rhepang Muaif. This training was held on 7-9 September 2020 in Rephang Muaif Village, Nimbokrang, Jayapura-Papua. The target audience involved in this activity are young people who will become prospective teaching staff at this natural school. They come from the Rhepang Muaif and from several communities in Jayapura. The training was held for 3 days, involving 53 participants. The material provided was a technique of collecting invertebrate animals in the environment around the house yards, forests and gardens in Rhepang Muaif Village. Furthermore, making invertebrates bioplastic/embedding media obtained from the field by following the existing procedures to produce bioplastic/embedding media. The training which was conducted for the teaching staff and management of the Nature School in Rephang Muaif Village has been going well. The enthusiasm of the participants in participating in this training was very high. This indicates that the training participants have responded positively to the activities that have been carried out. Keywords: : Training, Embedding/Bioplastics, Invertebrate Animals, Rephang Muaif
Knowledge Fusion Analysis and Research Based on Knowledge Graph

With the rapid popularization of Internet technology, it is a new challenge to mine the hidden knowledge behind the data in an organized and directed way. Knowledge graph not only describes the content of semantic associations and entities existing in the objective world, but also uses graph structure to visually present the structured knowledge system for system users. Therefore, in the development of modern technology, knowledge graph has been widely concerned by industry and academia. In the era of big data, in order to build high-quality knowledge graph, knowledge fusion is very critical, among which entity alignment and entity link are important parts of knowledge fusion task. Starting from the field of film and television, this paper uses the entity alignment technology of NovEA model and the candidate entity ranking structure based on CNN-DSSM to deeply discuss the key technologies of knowledge fusion during the construction of multi-level film and television knowledge graph. The final experimental results prove that, compared with other models of the same task, the NovEA model studied in this paper has higher alignment accuracy, and the candidate entity ranking structure based on CNN-DSSM is better designed.
The Reform and Practice of Level-based English Teaching Based on POA

The level-based English teaching has always been a hot issue in the teaching reform. Based on the practice and reform of level-based English teaching in Xi’an Fanyi University, this paper discusses the teaching model which is in line with the students’ actual situation, and takes the theory of POA as a guide. At the same time, it puts forward the strategies to solve the potential problems in order to further optimize the teaching model, meet the demands of students at different levels and improve the quality of college English teaching.
Innovation of Teaching Methodology Based on Maximizing Learning Opportunities--A Case Study of a Private College in Guangzhou

Basic English, which aims to train the basic English abilities in a comprehensive way, is one of the main courses for English majors. In teaching this course, conventional methods like the grammar translation method and the lecture method are widely employed, which have caused problems like repressed student agency, low learning efficiency, and imbalanced development of students’ English abilities. In the case of the College of FF, these problems are also prominent. To solve these problems, a teacher in the English department carried out his teaching reform when he was teaching Basic English. His reform was very much like the flipped classroom, and received varied acceptance. To make further reforms in teaching Basic English and other courses which share similar features, a new teaching model is proposed. This model is based on a subjective evaluation of the reform carried out by this teacher and a thorough examination of the context of the College of FF, especially that of the English department. The fundamental rule of this model is maximizing learning opportunities in class. It is hoped that by applying this model, the efficiency and effect in English teaching can be improved.
Intelligent Conception and Development Path of "Education Meta Universe"

"Education meta universe" is an intelligent education integrating multiple technologies and an upgrade of educational informatization. Through the "education meta universe" platform, we can achieve multi scene teaching, diverse interaction and 10000 people online at the same time, so as to achieve education fairness and knowledge sharing. "Education meta universe" can strengthen the construction of education and teaching resources and innovative application research through online and offline integrated teaching methods; Improve the construction and research of smart campus, smart classroom and smart classroom through the construction of new educational infrastructure; Through the joint construction between urban and rural areas and schools and the sharing of high-quality digital resources, we can cultivate and build a high-quality, professional and innovative teaching team. Through the design of the virtual scene of the education meta universe, the educational participants can construct virtual identities in the meta universe education, so as to realize the symbiosis of digital twins and virtual reality.
Movies in the Metaverse Perspective

The year 2021 is the year of metaverse. Ever since mankind moved towards the digital information age, people have been living, playing and working in the digital world. More than twenty years have passed since the movies "The Matrix" and "Avatar" unknowingly. Watching these two movies again today, there is no lack of seeing the metaverse, and the world envisioned by the metaverse can find traces in the movies. In addition to the human and mechanical, real world and virtual reality that the movies themselves are about, the metaverse movies to a certain extent give the meta-universe a figurative and deeper meaning.
Generic Framework Related to Database Forensics and Security Countermeasures

Governments and private organizations are rapidly moving on cloud and storing their private and business information on cloud databases. And currently cloud system is not much secure and different types of attacks are happening on databases. Databases store an expansive scope of private and open data, making them a practical objective for abuse by foes who are hoping to bargain the secrecy of information just as harm the respectability of the information or make it inaccessible to its client. It builds the establishment for the advancement and foundation of key standards in investigation of database forensics and case for forensic management. This research study strives to highlight the different vulnerabilities which are exploited by hackers and afterwards if there is intrusions how one can assess the amount of damage that has been done to the system by forensic analysis. This study also focuses on different solutions which can be used to secure the system so that the integrity of data is made possible. To further explore the forensic auditing process, the research shows the plan of assessing and developing a procedure to start with forensic analysis process. This is made sure following standard operating procedures which are used in forensic analysis and afterwards an investigation is conducted which results in determining the flaws in security and solutions to make them more protected. To sum up, this research study explores and follows a framework that can be used for analysis in a standard procedure which can be used to prove a case through legal channels. This further enables the authorities to proceed and set up a criminal case against the intruders using forensic audit.
Pengembangan Access Open Journal System (AOJS) sebagai Sistem Indeksasi dan Manajemen Pengelolaan Publikasi Jurnal

Open Journal Systems (OJS) is a web-based content management system specifically designed to handle the entire scientific publication management process. The Ministry of Research, Technology and Higher Education has also developed its own index, namely the SINTA (Science and Technology Index) which is expected to not only refer to the Scopus journal index. The relationship between Access Indexing and OJS is inseparable where OJS is a facility in managing journal publications and Access Indexing is a feature for disseminating journal articles in journal searches. This study tries to build an Access Open Journal Systems (AOJS) model that can be used as a form of publication and publishing management in international indexing. The application allows updating of data/content and sharing from various online journal sources. Access Open journal systems (AOJS) can allow end users, and still refer to international publishing management standards. Broadly speaking, this research is divided into three stages, namely pre-development data collection, development and implementation, and post-development data collection. From the results of the study, it has succeeded in developing an Access Open Journal System (AOJS) application by promoting simple features so that journal managers can manage journals well. We also removed the quick publish/submit module which we felt could worsen journal management properly. The OAI feature is also used for indexing so that metadata can be retrieved by multiple indexers. The Access Open Journal System (AOJS) that was built has a fairly easy configuration for its application and service modules, this configuration can make it easier for journal managers to create dynamic content and can be tailored to the needs of each manager.
DEEP-SEA MINING FOR RENEWABLE TECHNOLOGIES: A CASE STUDY FOR USING BIG DATA

Depleting terrestrial deposits and rising demand for metals in this time of climate change are stimulating interest in the deep sea — the area of the ocean below 200[Formula: see text]m — with commercial mining of mineral deposits imminent. Environmental impact assessments, effective regulation and mitigation strategies are needed to limit the impacts of deep-sea mining. This is a potential catastrophe for marine biodiversity, and use of Big Data will be needed to follow mining activities as well as chart impacts on known and unknown marine species and their habitats.
Deep learning recommendation algorithm based on semantic mining

This paper proposes Deep Semantic Mining based Recommendation (DSMR), which can extract user features and item attribute features more accurately by deeply mining the semantic information of review text and item description documents recommend. First, the proposed model uses the BERT pre-training model to process review texts and item description documents, and deeply mine user characteristics and item attributes, which effectively alleviates the problems of data sparseness and item cold start; Then, the forward LSTM is used to pay attention to the changes of user preferences over time, and a more accurate recommendation is obtained; finally, in the model training stage, the experimental data are randomly divided into 1 to 5 points, 1:1:1:1:1. Extraction ensures that the amount of data for each score is equal, so that the results are more accurate and the model is more robust. Experiments are carried out on four commonly used Amazon public data sets, and the results show that with the root mean square error as the evaluation index, the error of DSMR recommendation results is at least 11.95% lower on average than the two classic recommendation models based only on rating data. At the same time, it is better than the three latest recommendation models based on review text, and it is 5.1% lower than the best model on average.