Reviewerly/exHarmony huggingface dataset:
Comparison Study of the Actual Method and the Economic Order Quantity (EOQ) Method in Controlling Food Raw Materials Inventories at Royal Tulip Gunung Geulis Resort &amp; Golf

The aim of this study is to determine the effect of the Economic Order Quantity (EOQ) method in inventory control, in terms of inventory profitability and non-financial performance (production efficiency, timely delivery, product quality). The research is descriptive with a quantitative approach. This study calculates the optimal inventory raw materials of chicken, beef, and lamb. The EOQ is more optimal and efficient, showed by the ordering cost difference is Rp 702,000,-, the total storage cost difference is Rp 2,863,917, -, the difference between the total purchase cost is Rp 57,278,334, -, and the difference in the total cost of inventory is Rp. 3,565,917,-. By using the EOQ method, Royal Tulip can save a total cost of Rp 64,410,168,-.
Designing Strongly-decoupled Industry 4.0 Applications Across the Stack: A Use Case

Loose coupling of system components on all levels of automated production systems enables vital systems-of-systems properties such as simplified composition, variability, testing, reuse, maintenance, and adaptation. All these are crucial aspects needed to realize highly flexible and adaptable production systems. Based on traditional software architecture concepts, we describe in this chapter a use case of how message-based communication and appropriate architectural styles can help to realize these properties. A building block is the capabilities that describe what production participants (machines, robots, humans, logistics) are able to do. Capabilities are applied at all levels in our use case: describing the production process, describing machines, transport logistics, down to capabilities of the various functional units within a machine or robot. Based on this use case, this chapter aims to show how such a system can be designed to achieve loosely coupling and what example technologies and methodologies can be applied on the different levels.
Penerapan Model Pembelajaran Direct Instruction Untuk Meningkatkan Motivasi Berprestasi Siswa Kelas X Multimedia di SMK Ketintang Surabaya

The learning models becomes an important tool in the learning process. The abilities that students are expected to have will be determined by using appropriate learning models. The study aims to determine how the application of direct instruction and e-learning learning models in basic programming subjects can increase achievement motivation. This research used Quasi-Experiment approach. The design used anon-euivalent control group. The number of research samples consisted of 70 students of class X MM SMK Ketintang Surabaya. The independent variable in this studies was application of direct instruction (X1), E-learning (X2) while the dependent variable used is achievement motivation (Y). Multiple regression used for analyze data. The results showed that tcount = 5.5924 and ttable = 1.371 for dk = 5, at significant level 5%. Test criteria show that tstatistic&gt; ttable (4.5924 &gt; 5.371) then H0 rejected, meaning H1 accepted. It can be interpreted that difference between the Direct Instruction learning model and e-learning is significant.
RANCANG BANGUN SISTEM INFORMASI PENJUALAN CREAM SMILAX BERBASIS WEBSITE PADA PT.CENDRAWASIH EMAS KONSTRUKSI

Abstract &#x0D; Website-based Smilax cream sales information system at PT. Cenderawasi emas construction of an online and computerized sales system that is expected to be able to reach sales broadly making it easier to promote products to consumers' sales management. Making this information system uses the waterfall research method, in the stages of analysis, design, coding, testing to maintenance, this information system is made using the programming languages PHP, JavaScript, HTML, CSS, and MySQL. The system built can provide complete information about sales, product stock, and customers. So that the system that is built becomes a company tool for conducting sales activities. Based on the results of testing and implementation, it can be concluded that the Sales Information System for Cream Smilax at PT. Cendrawasih Emas Construction can be managed properly and meet the needs of the company.
A Novel Approach for Visualizing Medical Big Data Using Variational Autoencoders

Big data are enormous amounts of information that may accomplish marvels. This has been a topic of special interest over the past two decades due to its tremendous development. In the medical sector, a different large data resource include medical files, patient hospital information, and clinical exam reports and Internet-based equipment. Data visualization may utilize the human vision system fully to lead people throughout statistical analyses and intuitively and easily relay the message buried while behind the data. The Big Data Medical Care Platform is designed based on the system needs and operational position, from collecting and exchange of health information, analysis, and knowledge management level. In this study, the VAE utilized to visualize big data for the administration of large data in the health sector is analyzed. Experimental findings show that in comparison to traditional methods, VAE can provide outstanding prediction performance, along with PCA speedily ICA, feature analysis, nonnegative matrix factor, latent Dirich allocation in terms of AUROC and accuracy.
Can Bitcoin be subject to an ESG analysis?

Bitcoin is a crypto asset with claims that under certain circumstances it can grant anonymity and potential freedom from government oversight. This crypto asset can be subject to an ESG analysis for potential investors. In terms of the environment, Bitcoin generates a large carbon footprint due to mining and high waste generation. In terms of social and governance, Bitcoin generates risks regarding the potential for illegal use such as money laundering and terrorism, safety and suitability for investors. The technology behind Bitcoin – Blockchain – however, has positive ESG contribution, and is currently being used to increase validation and traceability in activities such as health records, food security, and secure voting, among others.
Preferences and Perceptions of Resumes Among Chinese People: A Visualization Study Based on Gaze Plot

This study uses the visualisation method of the gaze plot in eye-tracking technology to analyse how the physical characteristics of a CV, such as its layout, content ratio, and blankness rate, af ect the attention of dif erent Chinese people during the CV screening process. The study aims to summarise the focus, characteristics, and patterns of dif erent people's attention when browsing CVs to provide some references for CV creation for job seekers with dif erent needs. The study found that: 1. Regardless of the type of CV, the subjects would first pay attention to the image information in the CV; 2. The CV with a relatively open and organised text layout and a moderate/low amount of text would be more preferred by the subjects; 3. Appropriate blank space would attract the attention of the viewers more and faster, and a reasonable amount of blank space would also have a buf ering ef ect on the reception of new information; 4. Dif erent types of CV layout can have dif erent psychological implications for specific groups of people.
Design and Research of Agent-based Personalized Recommendation System

In recent years, with the continuous development of multi-agent technology and distributed artificial intelligence, the requirement for agents to have autonomous decision-making ability is also getting higher and higher. The application of multi-agent technology to the decision-making of complex problems under distributed structure has become an important research direction. This paper mainly studies the design of agent-based personalized recommendation system. This paper first analyzes the concept of agent, and expounds the basic model of collaborative filtering algorithm. On this basis, a multi-agent based recommendation framework model is designed, which uses multiple agents to build a large and complex system into a small subsystem that communicates and coordinates with each other and is easy to manage. This paper makes an experimental analysis of the constructed model. Through the experimental results, we can know that the performance of the multi-agent recommendation model constructed in this paper is better than the other two models.
Pelatihan Pengolahan dan Visualisasi Data dengan Bahasa Pemrograman Python untuk Siswa SMK Ciracas

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Streamlining models with explanations in the learning loop

Several explainable AI methods allow a Machine Learning user to get insights on the classification process of a black-box model in the form of local linear explanations. With such information, the user can judge which features are locally relevant for the classification outcome, and get an understanding of how the model reasons. Standard supervised learning processes are purely driven by the original features and target labels, without any feedback loop informed by the local relevance of the features identified by the post-hoc explanations. In this paper, we exploit this newly obtained information to design a feature engineering phase, where we combine explanations with feature values. To do so, we develop two different strategies, named Iterative Dataset Weighting and Targeted Replacement Values, which generate streamlined models that better mimic the explanation process presented to the user. We show how these streamlined models compare to the original black-box classifiers, in terms of accuracy and compactness of the newly produced explanations.
Model Checking the Reliability of Blockchain-based Edge Computing Network

In recent years, the development of blockchain and edge computing is very quickly. Compared with centralized cloud scenario, edge computing help to improve the efficiency of it. The end devices can undertake some of the work load to reduce the pressure of centralized cloud devices. Blockchain technology help to enhance the security of the whole network, and it is also an emerging technology. However, the reliability of blockchain-based edge computing network (BBECN) is still a challenge, few of the recent research focus on the reliability evaluation of it. To make up the research, in this paper, a continuous-time Markov chain (CTMC) model is proposed to calculate the reliability of BBECN. In this paper, 4 experiments are proposed to evaluate the influence of different influence factors and compare them. The research work of this paper will help to optimize the architecture design of BBECN.
Research on Coarse Granularity Data Sample Completion Method for District Heating System

Abstract The heating system is an essential part of China’s urban energy system. However, the heating systems in China have varying levels of hardware and software, informationization, and intelligence. The coarse time granularity of actual system data and the missing data brings significant challenges to system analysis and diagnosis. This paper proposes to study the sample completion and granularity refinement of the time-series data of heating systems based on Wasserstein Generative Adversarial Networks (WGAN). The method is validated based on the field data from 2019 to 2020 of a district heating system in Zhengzhou. Besides, the key features affecting the quality of the completion are discussed. After introducing the data processing method of Empirical Modal Decomposition (EMD), the results show that historical data and climate data dominate the quality of the generated samples. The WGAN can generate the samples accurately. When comparing the real data under the same conditions, the accuracy rate reaches 96.4%. This study further refines the sampling granularity of the existing heating system based on the WGAN to provide more accurate samples for system analysis and diagnosis. Overall, the study provides a new data analysis method for theoretical and technical studies under data deficiency scenarios for heating systems.
Research on the Establishment of the Mutual Trust Mechanism of the International Trade Alliances for Commodities Based on the Blockchain Technology–A Case Study of Iron Ore

Commodity is an important lifeline in a country’s economic system, and the mutual trust between international trade alliances of commodities has always been an issue that annoys China. The rise of blockchain technology has revolutionized the mechanism of mutual trust between international trade alliances of commodities. Blockchain technology equalizes the power among international trade alliances with its unique decentralization. The features of consensus mechanism, distributed ledger, and global certification make the international trade alliances of commodities no longer have to worry about the previous mutual trust issues. Taking iron ore as an example, this paper will use blockchain technology to rebuild the mutual trust mechanism between international trade alliances of commodities.
Vulnerability of CAPTCHA Systems Using Bots with Computer Vision Abilities

CAPTCHA stands for Completely Automated Public Turing test to tell Computers and Humans Apart. They are machine-controlled challenge-response tests used to determine when the user is a human or an automatic program (bot). Attacks perpetrated by malicious bots are one of the most common problems in web systems. To counter these attacks, CAPTCHA systems can be implemented. However, the growth of technologies such as Artificial Vision has caused many of the CAPTCHAS systems to be broken very easily. On the other hand, the implementation of automated processes in computer security has marked an additional complement in the process of searching for vulnerabilities in web systems. In this context, this article aims to automate searching tasks and analyze web systems vulnerabilities through Robotic Process Automation (RPA) tools and artificial vision techniques. As part of the bot development, the UiPath tool in its Community Edition version and the Google Cloud Platform API for artificial vision techniques were used. In the results, the functioning of the developed bot was systematically evaluated by broken the CAPTCHA system based on images of a test page. This proposal is intended to demonstrate that CAPTCHA systems, specifically of the hCAPTCHA type, can be broken using artificial vision techniques in conjunction with the automated processes of a bot.
Grounded Theory Study on Non-face-to-face Class Adaptation of University Students

This study tried to develop a practical theory that can explain the experience of the adaptation process to the sudden non-face-to-face class situation caused by the COVID-19 pandemic. For this purpose, in-depth interviews were conducted with 14 students from the 20 ~ 21st grades, and the collected data were analyzed by applying the grounded theory method proposed by Strauss and Corbin (2001/2001). As a result of the analysis, 104 concepts, 20 subcategories, and 6 final categories were finally derived. As a result of this study, the core category was found to be ‘Overcoming the culture shock of remote classes independently. The causal condition is‘freshman looking forward to college life’, the central phenomenon is ‘non-face-to-face college life with COVID-19', the contextual condition is‘go to school in the corner of the room', the mediating condition is‘introspection and Finding Supporting Resources’, and the action/interaction is ‘efforts to adapt to remote class situations’. The result of 'adapting to life' was a face-to-face class waiting with half expectations and half concerns. And as a result of this study, the core category,‘Independently overcoming the culture shock of non-face-to-face class situations’was progressing in four stages according to the passage of time: excitement stage, confusion stage, adaptation stage, and acceptance stage. The results of this study are meaningful as basic data to prepare for the substantialization of future new normal distance education.
O’Reilly for Higher Education

O’Reilly for Higher Education is a new online learning platform and branding on the topics of information technology and business, with a focus on academic materials. Books (e-books and audiobooks), videos, courses (live and on-demand), and online conference access are available not only from O’Reilly but also from 250 other top publishers. With quality content that is easily searchable, readable, watchable, and listenable, and an intuitive and accessible interface on both a regular computer browser and mobile devices, this is an excellent choice for supporting higher education students and faculty in their technology learning and research.
Developing Teachers’ Soft Skills within the New Educational Paradigm: Competences, Values, Indicators, Results

This paper deals with theoretical models of soft skills development in teacher education. The immediate purpose of this consideration is to develop a model for the development of a teacher’s soft skills as a competent, innovative, motivated, and competitive specialist in the labor market in the present time. The role of soft skills in the process of professional development of employees in all organizations has been increasing in recent times. However, the importance and necessity of teachers’ soft skills and, therefore, their formation among students studying in pedagogical areas are not yet adequately realized by many participants in the educational process. This paper examines the concept of soft skills and identifies the importance of these skills for the development of a specialist in the pedagogical field. In addition, a comparative analysis of hard skills and soft skills was conducted, and their components, namely competences, values, and behavioral indicators were evaluated. An analysis was conducted to assess the labor market needs for new qualifications. This made it possible to design a model of the modern teacher with skills reflective of their real environment. The results of this study can be further used in the improvement of lifelong learning and adult education.
Design of a Purple Team for the Colombian Financial Sector Focused on Stock Brokerage Companies (SBK)

Private and public sector companies are suffering cyber attacks globally, so the need to invest in cybersecurity has become a priority. In this sense, several supervisors have formulated regulations around cybersecurity, with a particular emphasis on banks and their challenges but not much on the Stockbrokers (SBK) entities that are the subject of this research work. Although one of the most common methodologies is the simulation of offensive (red team) and defensive (blue team) security, purple teams are emerging as an alternative that enables a broader spectrum of learning and analysis for companies, particularly SBKs This article details a methodological guide for the design and implementation of a purple team in SBKs in order to strengthen cybersecurity governance in the face of contemporary cyber threats.
Hyosung Advanced Materials develops ultra-high-tensile carbon fiber

On December 10, 2022, Hyosung Advanced Materials announced it had succeeded in the development of ultra-high-tensile carbon fiber, taking one step closer to standing completely on its own in the production of aeronautic materials.
Improving Object Detection in VHR Aerial Orthomosaics

In this paper we investigate how to improve object detection on very high resolution orthomosaics. For this, we present a new detection model ResnetYolo, with a Resnet50 backbone and selectable detection heads. Furthermore, we propose two novel techniques to post-process the object detection results: a neighbour based patch NMS algorithm and an IoA based filtering technique. Finally, we fuse color and depth data in order to further increase the results of our deep learning model. We test these improvements on two distinct, challenging use cases: solar panel and swimming pool detection. The images are very high resolution color and elevation orthomosaics, taken from plane photography. Our final models reach an average precision of 78.5% and 44.4% respectively, outperforming the baseline models by over 15% AP.
Cryptanalysis of a Public Cloud Auditing Scheme

Cloud data integrity verification is an important means to keep data security. Many integrity verification schemes were proposed for cloud storage. In 2019, Zhang et al. proposed a conditional identity privacy-preserving public auditing (CIPPPA) mechanism. We found that the signature algorithm is insecure because the Cloud Service Provider (CSP) can modify the user's outsourced data, while it can generate a correct proof.
UAV Swarm Cooperative Search Based on Extended Differential Evolution Optimization

To improve the efficiency of unmanned aerial vehicle (UAV) swarm in cooperative search for moving targets, a search method based on extended differential evolution optimization (EDEO) algorithm is proposed. The mapping probability map and certainty map to hormone map are utilized. Based on the rolling horizon optimization (RHO) and hormone map, a revenue function for UAV swarm cooperative search is given. Simulation results can indicate the proposed cooperative search method has the stronger universality and stability and the improved optimization algorithm has a faster converge ability.
Resource Modeling and Capability Assessment for Space-Based Information System

For the space-based information system with a large scale, a wide variety of nodes, complex connection relationships and dynamic structural changes, a multi-level system resource model is firstly established and a combined qualitative and quantitative assessment index system based on expert knowledge is proposed. Finally, a space-based information system capability assessment method is established by combining hierarchical analysis methods, and the results of calculation examples show the correctness and reasonableness of the method.
Collision-Free Motion-Primitive-Based Motion Planning Algorithm for Fixed-Wing Robotic Aircraft

This paper presents a collision-free motion-primitive-based motion planning algorithm for a fixed-wing robotic aircraft. The motion primitives are parameterized in the space of the control input vector, under the consideration of time-delay caused by actuator dynamics and the inherent nonlinearity of the aircraft, which providing a practical way to enable a fast and efficient flight. The corresponding control input vector are obtained through algebraic calculation based on waypoint’s location and flight parameters. Then, considering the dense obstacles in the field, a modified algorithm is developed to generate safe bearings towards the next waypoint. The effectiveness of proposed algorithm is verified in a simulated obstacle-rich field.
Unmanned Underwater Vehicle Path Planning Based on Improved Hybrid A* Algorithm

In the marine environment, unmanned underwater vehicle (UUV) path planning is a prerequisite for other scientific research tasks. Aiming at the low search efficiency of many current path algorithms and the fact that the planned path does not meet the kinematic constraints, this paper makes corresponding improvements based on the hybrid A* algorithm to enhance the algorithm search efficiency and make the planned path meet the kinematic constraints. This paper first introduces the basic principle and heuristic function of the hybrid A* algorithm, the basic form of the cost function, and then redesigns the heuristic function and cost function to reduce the number of invalid node extensions in the algorithm. Finally, through three sets of simulation experiments, it is verified that the improved hybrid A* algorithm can plan a safe and working path for UUV with higher search efficiency.