Reviewerly/exHarmony huggingface dataset:
Target Tracking Algorithm Based on Mixed Attention and Siamese Network

Siamese convolutional neural network, which is a classic framework for object tracking, has received extensive attention from the research community. The method uses a convolutional neural network to obtain target features and matches them with the search area features to achieve target tracking. Aiming at the problems that multi-layer features are difficult to extract effectively and network model parameters are complex, a target tracking algorithm (MA-SiamRPN++) with mixed attention mechanism is proposed based on SiamRPN++. Firstly, the channel attention mechanism is inserted into the backbone network, and then the output features of the channel attention network are fed into the spatial attention network, so as to improve the efficiency of feature extraction in different convolution layers by using mixed attention. At the same time, the deep cross -correlation network is used to better retain the feature information that is conducive to tracking and reduce the parameter complexity of the network to maintain the tracking speed. Finally, experiments on OTB100, VOT2016, and the long-term tracking dataset LaSOT show that the tracker proposed in this paper achieves higher accuracy and success rate than other state-of-the-art trackers.
A Password and Least Significant Bit Substitution Based Steganography Technique for Image Hiding

The proposed work introduces an image steganography technique using text-based password that acts as the symmetric key of encryption and decryption. It contains two components, an encoder, and a decoder. An encoder takes a secret image that needs to be hidden inside another cover image. The Combined image is encrypted with an eight characters’ password. The starting position of the cover image from where the secret image starts to hide depends on the password. Then the (Least Significant Bit) LSB Substitution technique is used to hide the entire secret image inside the cover image. The decoder takes the encrypted image and the password to retrieve the secret image back. The proposed work produces an encrypted image by keeping 99% information of the cover image and 100% information of the secret image, thus it provides lossless retrieval of the secret image. The proposed work includes dynamicity of position in steganography that ensures more security of image data over the network than the existing state of art methods.
Development of Information Systems in the Jayapura Regency Regional Disaster Management Agency

BPBD Jayapura Regency is a government agency that coordinates and handles disaster issues in the Jayapura Regency. Jayapura Regency has geographical, geological, hydrological, and demographic conditions that have the potential for disasters that need to be handled both pre-disaster, during emergency response, and post-disaster. Disaster information delivery, both knowledge about disaster or disaster reports to the community, information on BPBD activities, and news about BPBD is currently carried out through socialization in the community. So that there are often many conflicts due to incorrect news in the community related to BPBD's work programs, besides that BPBD Jayapura Regency itself does not yet have an integrated communication media that is directly connected to the people of Jayapura Regency. System An Information system in the form of a website was built to help related parties, namely BPBD Jayapura Regency and the community to be directly connected. This system was built using XAMPP as a web server and MySQL as a database server using the SQL programming language, PHP programming language is run on the server side so that the website becomes more dynamic. The analysis method used Use Case Diagram as a description of interactions that occur in the system. This system provides disaster reporting and complaint services This system also helps the BPBD in displaying information related to BPBD and disasters. This system will display information to the community and access to view disaster data reports that occur in the village added by each village or district head in Jayapura Regency.
LoGE: an unsupervised local-global document extension generation in information retrieval for long documents

Purpose This paper aims to manage the word gap in information retrieval (IR) especially for long documents belonging to specific domains. In fact, with the continuous growth of text data that modern IR systems have to manage, existing solutions are needed to efficiently find the best set of documents for a given request. The words used to describe a query can differ from those used in related documents. Despite meaning closeness, nonoverlapping words are challenging for IR systems. This word gap becomes significant for long documents from specific domains. Design/methodology/approach To generate new words for a document, a deep learning (DL) masked language model is used to infer related words. Used DL models are pretrained on massive text data and carry common or specific domain knowledge to propose a better document representation. Findings The authors evaluate the approach of this study on specific IR domains with long documents to show the genericity of the proposed model and achieve encouraging results. Originality/value In this paper, to the best of the authors’ knowledge, an original unsupervised and modular IR system based on recent DL methods is introduced.
Guidance for schoolchildren on artificial intelligence professions

The article actualizes the problem of professional orientation of schoolchildren in professions related to artificial intelligence. At the present time there is a need of society for specialists who could solve problems both on development of artificial intelligence systems, and on operation of already existing ones. The shortage of such specialists is a big problem. The aim of the article is to justify the content of career guidance activities in secondary schools in information technology (IT) professions in general and artificial intelligence (AI) in particular. Methodologically, our study was based on a theoretical analysis of the literature on career guidance for students. In the course of the study, the results of surveys of students were analyzed, documents were analyzed, and observations were made. Based on the analysis of career guidance resources and comparison with real job vacancies the specifics, specification of professions related to AI were considered. Activity-based and project-based learning methods were used in the career guidance activities. Google Klass was used as a learning platform and Google Colab as a development environment. Results. The article presents the content and the results of the career guidance master classes carried out by the authors with the schoolchildren. The results of the input and final surveys (questionnaires) of the students are analysed. Three main professions from Artificial Intelligence and their competences for the initial introduction are highlighted. Analysis of key skills of AI professions is carried out, groups of skills for career guidance are highlighted. Some essential content aspects that can be used in designing different types of career guidance sessions are suggested. In conclusion, it is concluded that the developed and tested materials contribute to professional self-determination of schoolchildren. They can be used for different career guidance activities on artificial intelligence professions.
Application of water resource economic management model in agricultural structure adjustment

Abstract Taking the watershed of Nanchang city as an example, through extensive investigations, the socio-economic status, water environment status, and development status of the agricultural industry in the watershed of Nanchang city were evaluated, and the coupling relationship between industrial structure and water environment was analyzed. The dynamic simulation of agricultural industrial structure adjustment in the Nanchang city basin under the constraints of the water environment was carried out to provide scientific decision-making on water resource shortage and other issues in the Nanchang city basin and to effectively solve the problem of water resource shortage. The research results showed that under the constraints of Scheme 2, the growth rate of agricultural output was in a relatively good development process, which was 8.56% in the short term, 6.65% in the medium term, and 10.33% in the long term. It is necessary to conduct research on the agricultural industrial structure in Nanchang city, which is also conducive to the protection of the water environment.
A Reconfiguration Method for Muti-Robot Monitoring Patrols

AbstractThis paper addresses the problem of multi-robot task allocation and trajectory planning in industrial environments. The objective is to optimize the overall cost of robot surveillance patrols in a dynamic high-risk environment. In this context, a hybrid beam search based approach is proposed to plan the patrol trajectories iteratively to accommodate environmental changes under some functional and operational constraints. Moreover, a real-time based system is introduced for remotely monitoring dynamic surveillance missions with automated mobile agents. Finally, a case study is detailed to show the efficiency of our approach in the case of the industrial port area of Fos-sur-Mer city in France.Keywords: Automated guided vehiclesmonitoring patroloptimizationtasks allocationtrajectory planning Disclosure statementThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Additional informationFundingThis study was supported by the National Research Agency, France, Region Normandie, Region Hauts de France with project ANR-21-SIOM-0009 - APPRENTIS 2021 – 2023 “Formal APPRoach and artificial intElligeNce for the moniToring and Intervention optimization of mobile agents in industrial Sites”.
Peningkatan Prestasi Belajar Matematika melalui Penerapan Metode Numbered Heads Together (NHT) Masa Covid-19 pada Siswa Kelas VIII.A SMPN 3 Masbagik Tahun Pelajaran 2020/2021

This research is a classroom action research (CAR) aimed at improving Mathematics Learning Achievement which is carried out in class VIII-A students of SMPN 3 Masbagik using the Numbered Heads Together (NHT) method. The researcher conducted an action research with the aim of knowing the improvement of Mathematics Learning Achievement in grade VIII-A students of SMPN 3 Masbagik through the application of the Numbered Heads Together (NHT) method. Based on the results of research and discussion of the learning model, the Numbered Heads Together (NHT) method can increase the activity and Mathematics Learning Achievement of class VIII-A students of SMPN 3 Masbagik in the odd semester of the 2020/2021 school year. This increase can be seen from the acquisition of student activity scores and the average class value and the level of classical completeness in each cycle has increased both in cycle I and cycle II. Based on the results of data analysis in each cycle, it appears that the results from cycle I to cycle II have increased. In the implementation of learning and the results of the first cycle of data analysis, for student activities an average value of 2.50 was obtained and student activities in the second cycle obtained an average class value of 3.80 while classical completeness was obtained in cycle 1 of 59% and increased in cycle 2 by 87.5%
Supporting the Exploration of Quality Attribute Tradeoffs in Large Design Spaces

When designing and evolving software architectures, architects need to consider large design spaces of architectural decisions. These decisions tend to impact the quality attributes of the system, such as performance, security, or reliability. Relevant quality attributes might influence each other and usually need to be traded off by architects. When exploring a design space, it is often challenging for architects to understand what tradeoffs exist and how they are connected to architectural decisions. This is particularly problematic in architectural spaces generated by automated optimization tools, as the underlying tradeoffs behind the decisions that they make are unclear. This paper presents an approach to explore quality-attribute tradeoffs via clustering and visualization techniques. The approach allows architects to get an overview of the main tradeoffs and their links to architectural configurations. We evaluated the approach in a think-aloud study with 9 participants from academia and industry. Our findings show that the proposed techniques can be useful in understanding feasible tradeoffs and architectural changes affecting those tradeoffs in large design spaces.
The Curriculum Politics Construction of Mathematical Basic Courses in Private Colleges

The integration of curriculum politics into the curriculum teaching construction in higher education institutions as the important content of curriculum provision, teaching syllabus approval and teaching evaluation should be embodied in such aspects as the design of curriculum objectives, the revision of teaching syllabus, textbook compilation and the design of teaching plan; and it should go through all parts of classroom teaching. Taking the curriculum politics teaching implementation system in the course of probability and statistics of “Tianjin Ren’ai College” as an example, there is a systemic summary of the experience of the curriculum politics construction of the mathematical basic course in private colleges, including the analysis of the nature and curriculum objectives of the course, design of teaching contents and methods, course implementation, teaching evaluation and effect feedback and other relevant methods.
Legal powers, subjections, disabilities, and immunities: Ontological analysis and modeling patterns

The development of dependable information systems in legal contexts requires a precise understanding of the subtleties of the underlying legal phenomena. According to a modern understanding in the philosophy of law, much of these phenomena are relational in nature. In this paper, we employ a theoretically well-grounded legal core ontology (UFO-L) to conduct an ontological analysis focused on fundamental legal relations, namely, the power–subjection and the disability–immunity relations. We show that in certain cases, power–subjection relations are primitive in the sense that by means of institutional acts other legal relations can be generated from them. Examples include relations of rights and duties, permissions and no-rights, liberties, secondary power–subjection, etc. We further show that legal disabilities (and their correlative immunities) are key in constraining the reach of legal powers; together with powers, they form a comprehensive framework for representing the grounds of valid legal acts and to account for the life-cycle of the legal positions that powers create, alter, and possibly extinguish. As a contribution to the practice of conceptual modeling, and leveraging the result of our analysis, we propose conceptual modeling patterns for legal relations, which are then applied to model a real-world case in tax law.
Analisis Sistem Informasi Akuntansi Penjualan Dan Pembelian Bahan Baku Pt Sagitarius

&#x0D; Companies are the forerunner of economic activity. The development of the times makes every company must be more innovative and creative, one of which is in the use of technology. The accounting information system is the main foundation in every business process in order to present information on the company's financial statements. The company makes sales as the company's main goal in seeking profit. Sales is one of the company's business operations which is the core and becomes crucial information for the owners of the company's capital. PT Sagittarius is a company engaged in property and real estate that provides housing development services and is sold either in cash or on credit. Sales on credit are made through the bank, so PT Sagittarius will still receive cash from the bank that has been selected as the lender. In this case, there are several internal control systems on sales that need to be re-analyzed and provide recommendations. The sales accounting information system is the object of research to ascertain how effective and efficient the sales accounting system is for PT. Sagitarius.
INCOME INEQUALITY, CLIENTELISM AND GOVERNANCE: IMPLICATIONS FOR SOCIOECONOMIC DEVELOPMENT IN WEST AFRICA.

Genuine redistribution of income is usually not commonplace in underdeveloped democracies. Instead, politicians in these democracies often target private, excludable and reversible benefits at the poor in exchange for electoral support. This electoral strategy often results in a situation where maintenance of political power or re-election becomes the focus of public policies instead of public welfare. This study investigated the main and interaction effects of income inequality and clientelism on government effectiveness in West African Countries from 1996 to 2020. The study objectives were achieved using pooled mean group (PMG) approach of the panel autoregressive distributed lag (ARDL) estimation technique and the Dumitrescu Hurlin panel causality test. Findings from the study revealed that clientelism enhances government effectiveness at higher levels of income inequality but inhibits government effectiveness at lower levels income inequality. The study findings also revealed positive relationship and uni-directional causality between income inequality and clientelism. The study concluded that government effectiveness which thrives on lower levels of income inequality and clientelism is beneficial to socioeconomic development; and that socioeconomic development and government effectiveness is interdependent and mutually reinforcing.
How to Recognize Arguments? A Study of Human Negotiations

Different kinds of negotiations and presented arguments are considered in the paper. Discussions in the Parliament of Estonia as well as negotiation in telemarketing calls, travel and everyday conversations are studied. In the Parliament, negotiation involves many participants while the other conversations take place between two participants. In the analysed texts, argument components (premises and claims), argument structures (basic, linked, etc.), and relations (support, attack, and rebuttal) are annotated manually. For annotating dialogue acts, a customized typology and custom-made software is used. This preliminary study aims to find cues for recognizing arguments in Estonian texts automatically. It turns out that some dialogue acts and language features contribute to the recognition of arguments and inter-argument relations.
Analysing the Resourcefulness of the Paragraph for Precedence Retrieval

Developing methods for extracting relevant legal information to aid legal practitioners is an active research area. In this regard, research efforts are being made by leveraging different kinds of information, such as meta-data, citations, keywords, sentences, paragraphs, etc. Similar to any text document, legal documents are composed of paragraphs. In this paper, we have analyzed the resourcefulness of paragraph-level information in capturing similarity among judgments for improving the performance of precedence retrieval. We found that the paragraph-level methods could capture the similarity among the judgments with only a few paragraph interactions and exhibit more discriminating power over the baseline document-level method. Moreover, the comparison results on two benchmark datasets for the precedence retrieval on the Indian supreme court judgments task show that the paragraph-level methods exhibit comparable performance with the state-of-the-art methods.
A Systematic Review on Password Guessing Tasks

Recently, many password guessing algorithms have been proposed, seriously threatening cyber security. In this paper, we systematically review over thirty methods for password guessing published between 2016 and 2023. First, we introduce a taxonomy for classifying the existing methods into trawling guessing and targeted guessing. Second, we present an extensive benchmark dataset that can assist researchers and practitioners in successive works. Third, we conduct a bibliometric analysis to present trends in this field and cross-citation between reviewed papers. Further, we discuss the open challenges of password guessing in terms of diverse application scenarios, guessing efficiency, and the combination of traditional and deep learning methods. Finally, this review presents future research directions to guide successive research and development of password guessing.
Large Scale Energy Efficient Sensor Network Routing using a Quantum Processor Unit

The sensor network energy conservation method, which is a usage hybrid of a classical computer and quantum processor, has proved to perform better than the heuristic algorithm using a classical computer. In this manuscript, the technical context for the significance of the method is presented and justified. Then the experimental steps are demonstrated in an operational sequence with illustrations if ever needed. The method has been validated by positive results across a randomly generated sample set of network topologies. The successful experimental results of this method have provided a better approach for sensor network lifetime maximization problems and demonstrated that the current state of art quantum processor has been able to solve large practical engineering problems with merits that override current methods in the literature. In other words, quantum advantage can be exploited to best efforts. It has gone beyond the stage of proof of concept to proof of feasibility.
Multi-User On-Chain and Off-Chain Collaborative Query Optimization Based on Consortium Blockchain

The consortium blockchain based on on-chain and off-chain data storage methods has shared cross-department business data widely. Existing research focuses on using index and other technologies to optimize a single query in the consortium blockchain, needing proper planning and scheduling for multi-user data access on-chain and off-chain. This paper fully considers the cross-department collaborative query requirements of the consortium blockchain and studies the reasonable allocation of nodes on and off the chain for multiple query tasks. The optimization model for cooperative query on and off the chain and the corresponding solution method is proposed. Firstly, the collaborative query optimization problem of on-chain and off-chain is modeled, considering the query processing capabilities of on-chain and off-chain nodes, and minimizes the query time as the optimization goal. Secondly, based on Coyote Optimization Algorithm (COA) and Genetic Algorithm (GA), a Hybrid Coyote Optimization Algorithm HCOA-GA (Hybrid COA-GA) is proposed. The experimental results show that the algorithm proposed can obtain the multi-user collaborative query optimization scheme on and off the chain and has better query time and convergence speed performance than other algorithms.