Reviewerly/exHarmony huggingface dataset:
PERANCANGAN SISTEM INFORMASI AKUNTANSI PERSEDIAAN BAHAN BAKU DAN BARANG JADI PADA PT. SMU

PT. SMU is a manufacturing business company that produces foods such as cheese. The research conducted found problems with the manual process that is still used to record the inventory of raw materials and finished goods so that the recording process is less effective. The purpose of this design is to create a computerized system to record the inventory of raw materials and finished goods at PT. High school quickly and precisely. The research technique uses qualitative methodology with tools to collect data through observation, interviews and literature review. The waterfall approach is used to develop the software and the stages involved including Flow map, Context Diagram, Data Flow Diagram and Entity Relationship Diagram are then implemented using Microsoft Visual Studio 2012 using Microsoft Access 2019 as a database. The results of the research conducted that with the existence of an accounting information system for raw material and finished goods inventory at PT. SMU can ease the work of employees in inputting raw material and finished goods inventory quickly and more effectively.
RANCANGAN SISTEM INFORMASI MONITORING DAN EVALUASI KIT SANITARIAN PUSKESMAS

Environmental health inspection is part of the environmental health services carried out by the Public Health Center. Environmental health inspections are carried out by observing environmental media using the health center's sanitarian kit to measure the quality of water, air and food. The District/City Health Office is expected to assist the Public Health Center in providing a sanitarian kit as a tool to support environmental health inspections. The Public Health Center that already have a sanitarian kit, need to carry out item management which includes monitoring and evaluating the use of the equipment. Based on this, the design of a monitoring and evaluation information system for the health center sanitarian kit using the Systems Development Life Cycle (SDLC) method with a prototype approach was created. System design stages start from planning, analysis, to design. The end result of this information system is to obtain information related to the utilization of the kit, the condition of the equipment, the obstacles encountered, to the maintenance of the equipment (calibration, availability of reagents and spare parts) which can then be utilized by the District/City Health Office and the Ministry of Health.
DESIGNING IT GOVERNANCE USING COBIT 2019 AT PT UNICHARM INDONESIA

Information technology provides development for companies, with information technology facilitating companies in the work process, starting from managing existing information at the company to employee performance. Therefore, information technology has a good impact on companies. With the existence of information technology, IT Governance is needed to align IT and business in a company, this is done so that work processes in the company run more effectively both for employees and for corporate governance, corporate governance must be managed as well as possible so that it is organized and provides a good impact on the company, for this governance a system called COBIT is needed, because COBIT can manage everything from IT needs and business needs to corporate governance. With COBIT in a company, there will be designs that are in accordance with the wishes of the company and can be controlled more by IT management.
Predict, Identify and Alert on Suspicious Activity by Multiple Zone

Abstract: An active topic of image processing and computer vision research is the detection of suspicious human behaviour in surveillance footage. In order to stop terrorism, theft,accidents, illegal parking, vandalism, fighting, chain snatching, crime, and other suspicious activities, human activity can be observed through visual surveillance in sensitive and public places like bus stations, railway stations, airports, banks, shopping malls, schools, and colleges. It is highly challenging to continually monitor public spaces, thus an intelligent video surveillance system that can track people's movements in real-time, classify them as routine or odd, and send out an alert is needed. The field of visual surveillance to identify aberrant actions has seen a significant amount of publications in the last ten years. Furthermore There are a few surveys that canbe found in the literature for the recognition of various abnormal activities, but none of them have reviewed various abnormal activities. This study presents the state-of-the-art in the field of recognising suspicious behaviour from surveillance recordings during the past tenyears. We give a quick overview of the concernsand difficulties associated in recognising suspicious human activity. This article examines six aberrant behaviours, including the identification of abandoned objects, theft, falls, traffic accidents, and unlawful parking, as wellas the detection of violence and fire. Generally speaking, we have covered all the processes that have been [1] Foreground object extraction, object identification based on tracking or non-tracking approaches, feature extraction, classification, activity analysis, and recognition are some of the techniques that have been used to identify human activity from surveillance movies in the literature. This paper's goal is to give field researchers a literature assessment of six different suspicious activity identification systems together with its broad framework.[1]
MIRNA Adaptive 3D Game to assist children's Distance Learning Difficulties Design and Teachers Intention to use

The global transition from traditional classroom instruction to online learning has been hastened through COVID-19. Notwithstanding its benefits, students were unable to quickly adjust to the difficulties of change. This research offers MIRNA, an assistive 3D instructional tool for slow learners in primary school, mostly for Arabic, English, and Math topics, to address academic issues that develop with online education. The proposed tool can be fully integrated with remedial programs to assist students who struggled to adjust to distant learning during the pandemic, slow learners, or even those who are unable to attend school. This application categorizes students based on academic performance rather than age and automatically adjusts to their limitations. Additionally, MIRNA offers a simple interface that allows teachers to personalize it with their own content and game scenarios. We carried out an empirical investigation to assess teachers' intentions to use MIRNA as an online learning platform in the learning process. The findings of the study show that teachers’ attitude towards the game was positive, and they intended to use the game in the learning process in the future
Basic Laboratory Class for First-Year Students in Science and Engineering School

Three different teaching methods were performed for basic laboratory class of first-year students in science and engineering school at Setsunan university as the infection control of COVID-19. In these classes, questionnaires were conducted to the students taking the class at before and after courses. The results of these questionnaires for three different class methods indicated that it was important for students to carry out face-to-face class. We propose that the information about academic education should be collected and shared for improving educational effects under future pandemics.
Visual secret sharing

Multiple secret sharing (SS) scheme is a cryptosystem which encrypts a secret into multiple shares so that any qualified combination of shares can reconstruct the secret, while any forbidden combination of shares reveals no information about the secret In the existing process, the system has more complex stages by introducing two stages for making secure VSS.The first stage is message based privacy.The Secret Share content was Reversed and content is encrypted with the help of triple DES algorithm.The second stage is image based privacy.The image based privacy is applied by embedding encrypted message and user key into multi-media object(image) using LSB based water marking Techniques and then the image is encrypted using AES algorithm.The encrypted image is segmented into shares by file merge and split algorithm.The user key and shares are sent to receiver through mail.The valid receiver can be able to reconstruct the shares into image.By using the user key encrypted message will be obtained.Then the message will be decrypted and reversed to get the secret message.Through this approach the new system improve our privacy and protection of secret sharing.
Memtrade: Marketplace for Disaggregated Memory Clouds

We present Memtrade, the first practical marketplace for disaggregated memory clouds. Clouds introduce a set of unique challenges for resource disaggregation across different tenants, including resource harvesting, isolation, and matching. Memtrade allows producer virtual machines (VMs) to lease both their unallocated memory and allocated-but-idle application memory to remote consumer VMs for a limited period of time. Memtrade does not require any modifications to host-level system software or support from the cloud provider. It harvests producer memory using an application-aware control loop to form a distributed transient remote memory pool with minimal performance impact; it employs a broker to match producers with consumers while satisfying performance constraints; and it exposes the matched memory to consumers through different abstractions. As a proof of concept, we propose two such memory access interfaces for Memtrade consumers -- a transient KV cache for specified applications and a swap interface that is application-transparent. Our evaluation using real-world cluster traces shows that Memtrade provides significant performance benefit for consumers (improving average read latency up to 2.8X) while preserving confidentiality and integrity, with little impact on producer applications (degrading performance by less than 2.1%).
Supplemental Material: Valanginian climate cooling and environmental change driven by Paraná-Etendeka basalt erosion

&lt;p&gt;Appendices S1–S2, Figure S1, and Tables S1–S2. &lt;/p&gt;
Teaching Autonomous Vehicles at the Graduate Level: Challenges and Efficient Offering

Autonomous vehicles (AVs) are a technological reality with level 2 AVs already on the market for a few years now and level 3 AVs being introduced to the U.S market by Mercedes Benz in 2023. This topic has been strongly present in research efforts. Development of incremental efforts in image recognition, path planning, object detection and response, and control algorithms for AVs represent a vibrant research area. However, on the educational front, teaching Autonomous vehicle technology to students on a large scale has been slow in its adoption. This is due to challenges related to the rapidly moving technology as the standards for AVs are yet to settle. In addition, the interdisciplinary nature of working in the automotive industry posed a challenge on the direction of such degrees at the graduate level. Student backgrounds and previously achieved skills and learning outcomes can come from a wide array of majors. In this work, we strive to tackle these challenges by drawing a clear road map for programs aiming to offer AV graduate studies to multidisciplinary students while being aware of cost. Clear learning outcomes that enable students to achieve success in the field of AVs along with assessment methods are introduced. Technical tools that highly depend on open-source licensing are proposed to form a viable educational solution to the discussed challenges.
Combining Attention Mechanism and Local-Global Features Association Network for Vehicle Re-identification

Vehicle re-identification (Re-ID) aims to retrieve the target vehicle from a large dataset composed of vehicle images captured by multiple cameras. Most vehicles are difficult to recognize in the environment of low resolution, occlusion, and viewpoint change, which brings challenges to vehicle Re-ID. Existing work usually uses additional attribute information to distinguish different vehicles, such as color, viewpoint, and model. However, this requires expensive manual annotation. Therefore, we propose a three-branch network based on attention mechanism and local-global feature association (AM-LGFA) to improve the accuracy of vehicle Re-ID. In the global branch, the global features of the vehicle are extracted. A multi-scale channel attention module is introduced into the attention branch to suppress irrelevant information and extract important channel features. The features extracted from the backbone are divided into different stripe features in the horizontal direction in the local branch. Then connect each stripe feature with the global information to enhance the context between features. Finally, the features extracted from the three branches are concatenated as the feature representation of the test phase. The experimental results show that the features extracted by the AM-LGFA network are complementary. The effectiveness of this method is verified on two challenging public datasets, VehicleID and VeRi-776.
Research on paper influence evaluation based on citation network

In order to better discover high-quality papers, this paper takes the literature in the field of computer vision as the research object to construct a citation network. Aiming at the problems of unreasonable distribution of document weights and high scores of old documents when using the PageRank algorithm to calculate the importance of papers, this paper improves the PageRank algorithm, considering the publication time, citation time and the impact factor of the publication journal, and proposes a new method. A new weighted PageRank algorithm. The experimental results show that the algorithm can better mine high-impact papers from the citation network.
Investigating the Application of Ethereum Smart Contracts in Energy Exchanges

Blockchain technology serves as a sustainable solution to enable decentralised applications. Insufficient research efforts have been directed in the past towards advancing blockchain technology integration in energy systems. This paper demonstrates that the energy exchange transparency and facilitation can be improved by utilising a smart contract deployed on an Ethereum Test network. The capabilities and limitations of the system have been analysed, with suggestions for improvement and potential research areas provided.
“Sonic Spaces for the Stray”: (Dif)Fusing Dis-location in Sound Installation and Performance

This project examines subjectivity and its embodiment through the application of interactive electronics within sound installation and performance. It employs a merging of theory, method and practice that has not been fully researched to date and which represents a valuable addition to sound performance and electroacoustic composition. My artistic research focuses on an ongoing series of improvisational/compositional experiments, moving between a dedicated workspace and sound production studios where I will work with acousticians, engineers, and programmers. The aim is to develop gestural/embodied approaches for applying interactive electronics within sound performance and fixed-media composition—mining tensions between failure and fluency; and diffusion strategies that highlight correspondences between embodiment, sound and space—emphasizing tensions between absence and presence. Foundational research includes studying methods and applications for investigating spatialization and psychoacoustics, employed by artists including Maryanne Amacher. I will also study concepts/methods developed by artists such as George E. Lewis, focusing on interaction between algorithmically-based technology tools and physical gesture in musical improvisation. This research also engages with Julia Kristeva’s psychoanalytically-based writing on abjection and the sublime, grounding my studio-based research in theoretical inquiry that engages with subjectivity and embodiment. Supplementary research will address psychoacoustics, aural architecture, and spatialization theory and technologies. The outcome of the project will be twofold: a body of sound installations and performances demonstrating an interactive approach to addressing relationships between the body, materiality, sound, space and situation; and a set of reflective writings that articulates the poetics and affective aspects of this multi-layered inquiry. The completed project will offer new knowledge production in the field of artistic research, and transmission of interdisciplinary knowledge to creative practitioners.
Metaverse Is the Future of Influencer Marketing

Influencer marketing is expected to undergo a transformation due to the rise of the metaverse. The metaverse is a virtual world where users can interact with each other and digital content in a fully immersive environment. Influencer marketing is predicted to become more important for firms as the metaverse's popularity rises. This new platform offers opportunities for businesses to work with influencers and develop campaigns that benefit from metaverse's immersive qualities. The influencer marketing has advantage to create 3D environments. Interactive experiences to capture the attention of interested audience and connection with global audience to be successful in the metaverse, influencers will need to adapt their strategies that are immersive, engaging, interactive, and building strong communities within the metaverse for loyal following. In conclusion, the metaverse is the future of influencer marketing. As more people spend time in virtual space, influencers need to create immersive and engaging content and building strong communities for their success.
Chicken Menu Sales Forecasting System using Multiplicative Holt-Winters Triple Exponential Smoothing

Forecasting is an art and a science predict events that will occur in the future based on data in the past. The ability of the restaurant in Management shows success in taking advantage of business opportunities optimal for interpreting past performance and planning for the future. This research uses Triple HoltWinters Exponential Smoothing Multiplicative method for sales forecasting. Multiplicative Holt-Winters Triple Exponential Smoothing Method has the smallest percentage error (PE) of 9.946% with parameter values (α=0.1, β=0.1, ϒ=0.3). While the largest percentage error (PE) is obtained Multiplicative models with parameter values (α=0.3, β=0.3, ϒ=0.1) produce percentage error (PE) value of 11.879%. Menu sales forecasting results chickens using the Holt-Winters Triple Exponential Smoothing Method Multiplicative in the next month using parameter values (α=0.1, β=0.1, ϒ=0.3) is 4782 pcs.
Using Edge Computing Technology in Programmable Logic Controller to Realize the Intelligent System of Industrial Safety and Fire Protection

controller (PLC)One reason behind a factory fire is personnel neglecting to pay attention to various details within the factory.For instance, environmental temperature can impact the safety of storage facilities, whereas humidity levels can affect the frequency of electrostatic discharge incidents.However, it is not feasible for workers to continuously monitor the changes in the factory environment and inspect equipment.Therefore, we investigated a method that can help provide intelligent judgments and can assist workers in monitoring the factory environment by using Bluetooth sensors and edge computers.The intelligent fire protection system designed in this study is characterized by the wireless transmission and easy arrangement of Bluetooth sensors, and is equipped with an edge computer on the production line.This system can make intelligent judgment on the environment and send a message to notify the users when the environment changes very rapidly.If the data captured from the environment exceeds a critical threshold requiring a warning, an alarm will notify the users.If required, the edge computer will take control of the programmable logic controller of the production line to implement relevant actions and achieve an intelligent automatic fire protection system.
Looking at Okuda's artwork through GeoGebra: A Citizen Science experience

&lt;abstract&gt;&lt;p&gt;In this paper, we describe an experience to test the predominant presence of Delaunay triangulations in the artwork of Okuda, a quite famous, young, contemporary Spanish artist. We addressed this task involving, as a citizen science activity in a STEAM (Science, Technology, Engineering, Art, Mathematics) education context, several hundreds of students (of different kinds: secondary education, university undergraduates, in particular, following teacher training degrees). Each student was asked to select an Okuda archive and, with the concourse of a dynamic geometry program provided with some computational geometry commands, to measure the ratio of coincident triangles in Delaunay's and artist's triangulations, over an ample region of the chosen artwork. The results show a very large percentage of coincidence ratios. We conclude with some reflections about how to interpret this fact, and about the potential role of future, enhanced, dynamic geometry systems to automatically address similar issues, concerning mathematical properties of figures from the real world.&lt;/p&gt;&lt;/abstract&gt;
Professional Orientation of Library and Information Specialists of The Republic of Tatarstan (Research on the Basis of the Central Library of Kazan)

The article presents the results of a survey conducted on the basis of the Kazan Central Bank in 2022. The study showed that not only the theoretical knowledge acquired at the university and in the course of work, but also the organizational culture, psychological, moral climate of the library staff are of determining significance for the formation of professional orientation and personal development of library specialists. Thus, the importance of professional orientation and relevant competencies for a successful career and the achievement of professional goals are confirmed.
CNN blend ERNIE for sentiment classification

For Chinese text sentiment classification task, this paper propose the CNN blend ERNIE for Sentiment Classification (CSEC) model, it concatenates all CLS vectors from twelve Encode Layers of Enhanced Representation through Knowledge Integration (ERNIE) by introducing Attention Mechanism (AM) then sends the combined vector to Convolutional Neural Networks (CNN). It aims to learn different levels of information from different layers. Through different experiments to validate, CESC achieves the best results.
Supplemental Material: Controls on metal fertility of dioritic intrusions in the Laiwu district, North China craton: Insights from whole-rock geochemistry and mineral compositions

&lt;p&gt;Table S1: Major and trace elements geochemistry of whole-rock samples from the Fe-mineralized and barren dioritic intrusions in the Laiwu district. Table S2: Sr-Nd isotopic compositions of whole-rock samples from the Fe-mineralized and barren plutons in the Laiwu district. Table S3: Major and trace element compositions of amphibole from the Fe-mineralized and barren plutons in the Laiwu district. Table S4: U-Pb age data and trace elements of zircon from the Fe-mineralized and barren plutons in the Laiwu district. Table S5: Major and trace elements of apatite from the Fe-mineralized and barren plutons in the Laiwu district. Figure S1: Hand specimens of diorites were collected from the Kuangshan (A), Jiaoyu (B), Jinniushan (C), and Tietonggou plutons (D). Figure S2: CL images of representative zircons from the Kuangshan (A), Jiaoyu (B), Jinniushan (C), and Tietonggou diorite (D). Scale bar is 100 μm. Figure S3: U-Pb Concordia diagrams of zircons from the Kuangshan (A), Jiaoyu (B), Jinniushan (C), and Tietonggou plutons (D). The insets in each diagram are the weighted mean 206Pb/238U age. Figure S4: Selected oxide element Harker’s plots for the Fe-mineralized and barren plutons 20 in the Laiwu district. &lt;/p&gt;