Reviewerly/exHarmony huggingface dataset:
The role of the relationship between planning systems and open accounting records in the hotel systems in terms of the quality of accounting information

The research aims to identify the effect of the integrative relationship between the system used in planning the resources in the hotels and the operations of accounting for open records and their relationship to the quality of information obtained from the accounting records throughout the year 2020. To do so, the descriptive research method that describes the phenomenon is utilized. The research shows that the accounting system for open records on the hotels depends on the integration into the project resource planning system in the company to overcome the problem of difficulty and complexity in data management. The lack of comprehensiveness of information, as well as of the systems related to planning the resources for the project, is one of the most important factors that impacts the success of the application of accounting for open records can lead to information on project costs and other available information. The companies under research have a high level of awareness that the use of the open records system will lead to numerous benefits both for the companies and the workers. The focus of this study is on a high level of awareness of the importance of the project resource planning system.
A Network Investigation Framework Based on Deep Learning for Fraud Transaction Detection

The online banking system has made a way for the customers to make transactions from anywhere in the world with the availability of network. The banking sectors even communicate with the other branches by having an online banking management system. This management system communicates through network which seeks interest of many fraudsters and attackers. Therefore, to strengthen and implement the defense strategies, these suspicious activities need to be investigated. The paper discusses a case study, different risk factors and their investigation techniques. This work proposes a deep learning-based investigation framework for the online transaction system to detect fraud cases. The framework successfully detects the cases with an accuracy of 99.64%. The detailed process flow is discussed to explain the detailed work flow. In conclusion, future work is highlighted to give researchers direction in this area.
Sistem Informasi Laporan Kegiatan Harian Siswa Berbasis Android Di Sekolah Dasar Purba Adhi Suta Purbalingga

Student daily activity records are kept as documentation tools to monitor the development of students' academic and non-academic abilities in capturing the learning process. The student's daily activity record is carried out by Purba Adhi Suta Elementary School. Purba Adhi Suta Elementary School is located in Purbalingga Regency which is located at Jalan Letnan Jenderal S.Parman Number 19 B Purbalingga. The obstacles faced by Purba Adhi Suta Elementary School in the form of the process of recording student activities are still done manually so that there is often a delay in managing the data of students' daily activity records and delays in the collection of student activity record recap books. The software development method used is a prototype. In this method the steps taken are the identification of user needs, making prototypes, adjusting prototypes, creating new systems, testing the system and using the system. From the results of the benefit test it can be concluded that functionally the system has produced the output as expected. Thus it can be concluded that the Android-Based Student Daily Activity Report Information System at Adhi Suta Elementary School purbalingga regency can help improve time efficiency in the creation of recap of student activity reports.
Mereosemiotics: Parts and signs

For descriptions of cognitive processes, including process models for research data provenance and simulation workflow metadata, a formal notation is developed on the basis of the foundational ontological paradigm of mereosemiotics, i.e., the combination of mereotopology with Peircean semiotics. To demonstrate the viability of the approach, this is applied to extend the pre-existing OWL ontology for a physicalistic interpretation of modelling and simulation - interoperability infrastructure (PIMS-II) by a modal first-order logic axiomatization.
Current challenges and applications of DeepFake systems

Chapter Contents: Abstract 7.1 Introduction to DeepFake 7.1.1 Scenario 7.2 Various DeepFake detection methods available and their limitations 7.2.1 Traditional detection methods 7.2.1.1 Blind methods 7.2.1.2 One-class and model-based time series approaches 7.2.1.3 Supervised approaches with changed functionality 7.2.2 Methods based on deep learning 7.2.2.1 Supervised CNNs looking at specific clues 7.2.2.2 Generic supervised CNNs 7.2.2.3 One-class training 7.3 Applications used to forge the multimedia 7.4 Current challenges and future of the technology 7.4.1 Quality of DeepFake dataset 7.4.2 Performance evaluation 7.4.3 Explainability of detection results 7.4.4 Temporal aggregation 7.4.5 Social media laundering 7.4.5.1 Fusion 7.4.5.2 Interpretability 7.5 Conclusion References
Internally Generated Revenue, Corruption, Governance And Economic Growth In Nigeria

Economic growth of Nigeria has been acclaimed to be affected by the inability to raise enough internally generated revenue to provide economic growth stimulus. Studies have shown that economic growth can be stimulated by internally generated revenue, corruption and governance. Ex post facto research design was adopted using Nigerian economy while internally generated revenue, corruption, governance and economic growth were modeled using Autoregressive Distributive Lag Model (ARDL). The study found that IGR, CPI and GI jointly had positive and significant effect on economic growth. It recommended that government should establish policies that will drive internally generated revenue, reduce corruption and enhance governance to attain economic growth.
Offensive Advertisements Influence You More Than Me: An Examination of the Third-Person Effects in the Chinese Cultural Context

This study examined the third-person effect (TPE) hypothesis (Davison, 1983) in offensive advertising in the Chinese cultural context. Based on a survey of 1,539 Chinese Internet users about the third- and first￾person effects among offensive ads, neutral ads, and public service ads, the study inquires into the relationship between the TPE and respondents’ levels of acceptance toward advertising. Besides confirming the TPE existence in an Eastern cultural context, the results suggest that the TPE predict word￾of-mouth (WOM) spreading for both offensive and neutral product ads, but not for PSAs. Theoretical contributions and managerial implications of these findings are discussed.
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias

We consider the problem of learning the causal MAG of a system from observational data in the presence of latent variables and selection bias. Constraint-based methods are one of the main approaches for solving this problem, but the existing methods are either computationally impractical when dealing with large graphs or lacking completeness guarantees. We propose a novel computationally efficient recursive constraint-based method that is sound and complete. The key idea of our approach is that at each iteration a specific type of variable is identified and removed. This allows us to learn the structure efficiently and recursively, as this technique reduces both the number of required conditional independence (CI) tests and the size of the conditioning sets. The former substantially reduces the computational complexity, while the latter results in more reliable CI tests. We provide an upper bound on the number of required CI tests in the worst case. To the best of our knowledge, this is the tightest bound in the literature. We further provide a lower bound on the number of CI tests required by any constraint-based method. The upper bound of our proposed approach and the lower bound at most differ by a factor equal to the number of variables in the worst case. We provide experimental results to compare the proposed approach with the state of the art on both synthetic and real-world structures.
The Design of Directions and Shot Sound Distance Using Fuzzy Logic Method Based on Raspberry Pi

Abstract - The rise of a shooting incident that occurred in the border areas of the Republic of Indonesia is a big loss for the state in terms of personnel. Technological developments can be used as an alternative in the military world to help the role of soldiers so as to reduce personnel losses. This study aims to create a system for detecting the direction and distance of gunshots. This study uses an experimental method. This gunshot detection system also applies the Fuzzy Logic Method which is applied to the Raspberry Pi 4 and Microphone Max 4466 which is expected to detect the direction and distance of gunshots. This Fuzzy Logic method is used as an inference system or decision maker according to the input given. Fuzzy Logic broadly consists of fuzzification, rule base, and defuzzification. Fuzzification is useful for input normalization, so that the input quantity is in accordance with the fuzzy magnitude, namely the value in the range 0 to 1. After that, enter the rule base where in this step, the input set is compared with the rules or provisions of sound decibels so that it can be classified whether the distance and the direction of the captured sound is in the data range that has been programmed, in this step the signal is analyzed how much decibel sound SS2-V1 is by the MAX 4466 sensor. The conclusion is done by defuzzification, so the final result is that the closest distance to a gunshot at 1 meter is 250 Decibels.
Design e bem-estar: uma abordagem hedônica e eudaimônica para CPS

Design for well-being, conceptual model, values, CPS This article is part of an ongoing multidisciplinary research on the values and risks of cyber-physical systems (CPS).Here we present a snapshot of it, from the design point of view.With this focus in mind, we seek to understand how CPS, as the foundations of Industry 4.0, can be projected in a way that not only works, but also contributes, to people wellbeing.A semantic parallel was made from the bibliographical survey on the most important values in a design project, and in a CPS project specifically, with the HEMA wellbeing scale.As a result, a conceptual theoretical model is proposed with 12 values that serve as a basis for the development of the CPS with a focus on people wellbeing.Finally, we present an overview of future steps of the research.
LibGuides: System Wide Holds - Training Guide: Request List / Queue

The purpose of this guide is to provide staff a reference resource for processing Requests and Holds on NLPL materials.
ENHANCE SECURITY IMAGE ON PASSENGER COMBINATION ALGORITHM ARNOLD CAT MAP (ACM) AND RIVEST SHAMIR ADLEMAN (RSA)

At present, the security and confidentiality of the data or information is a critical thing and the increasingly widespread use of image data in a variety of fields. Therefore, the security of image data from unauthorized access becomes necessary. There are a variety of techniques to improve the safety of the data or information has been developed, one of which is Cryptography technique or so-called encryption/decryption technique. Cryptography is the science of keeping messages by changing the data or information into a form that is different or can not be recognized. To increase security on the image we can take more than one encryption algorithm, and a second cryptography algorithm to do encryption and decryption can be the way. Cryptographic algorithms commonly used today and proved its strength especially for the digital image is Algorithm with Chaos system. Arnold's Cat Map (ACM) is one of a chaos-based algorithm that can be used to encrypt the image file and to improve security on that image then use new algorithms are algorithms Rivest Shamir Adleman (RSA) algorithm, known as the standard in the field of cryptography. This research aims to optimize the security image jpg format by combining two cryptographic algorithms are algorithms ACM and the RSA algorithm so expect the strength of the encrypted with the algorithms are complicated to be solved.The aims of the comparison MSE showed good results where quality RGB original image with the image of an encrypted does not show error , but the value of PSNR between the original image with the image of the encoded still showed noise where PSNR finally to red (r) = 16.8955, green (g) = -1.9952, blue (b) = -7.1882. Comparison of the time required for each encryption-decryption is approximately 0.1 seconds to 0.4 seconds.
Application of the MLWE in the cryptosystem CRYSTALS – KYBER as KEM and Dilithium as signature

Quantum computers, but still with a low number of qubits, are starting to emerge as we write. It is more crucial than ever to work on new cryptosystems. Cryptosystems that will be based on mathematical problems that are robust enough to withstand the increased computational power that these new types of computers will provide. In the course of our research, we came across the mathematical object that is the Lattice. The latter is one of the promising candidates in terms of fundamental problem for post-quantum cryptosystems. But the mathematical tool on which we will open this article is the MLWE or Module Learning With Error. The LWE (or Learning With Error), in the first instance, is a generalization of the problem Learning from parity with error. It has been shown that this problem is equivalent, in terms of difficulty, to the SIVP or Shortest Independent Vector Problem of a lattice. Coming back to MLWE, we have another designation, Learning With Error other Module Lattices. Module lattices can be considered as lattices between those used in the LWE problem definitions and those used for the R-LWE problem (Ring LWE). The Module-LWE offers a compromise between the two extremes of the LWE and the R-LWE. Thereafter we will focus on the CRYSTALS cryptosystem, a cryptosystem based on the MLWE. Our choice to study this cryptosystem is based on the fact that it was submitted to the NIST (National Institute of Standards and Technology) project of post-quantum cryptosystem standardization. CRYSTALS was able to progress to step 3 of the project. But above all, it is the only one among the few that have progressed to this final stage, to have both a KEM type cryptosystem (Key Encapsulation Mechanism) and another signature type one.
[Epidemic Characteristics of the Novel Coronavirus Delta Variant in Guangzhou and Grid Crowd Management Based on Public Security Forensic Perspective].

Abstract： Objective To analyze the first epidemic spread of the novel coronavirus Delta variant in China based on public security forensic perspective, investigate its transmission characteristics, contributing factors, and epidemiologic research experience, and provide a reference for the prevention and control of the epidemic caused by the novel coronavirus variant. Methods Based on the information that public security forensic experts obtained from front-line epidemiologic research, the gender, age, place of residence, transmission route and infectivity of the coronavirus disease 2019 （COVID-19） confirmed cases, asymptomatic infected persons and their close contacts in Guangzhou caused by the novel coronavirus Delta variant were analyzed. The basic reproduction number （R0） during this epidemic in Guangzhou was calculated. Results Among the 153 cases infected with novel coronavirus Delta variant in the epidemic, 63 cases were male and 90 cases were female, their age ranging from 1 to 92 years, with a median age of 49 years. The main route of transmission was close contact, including dining together, co-living, and close contact in the same residential building. There were 31 cases of family clusters, 25 of which were in Liwan District. The epidemic lasted from May 26 to May 29, and the R0 remained above 4.0. After May 30, R0 began to decline and remained below 1.0 from June 7. Conclusion The novel coronavirus Delta variant is highly infectious, the crowd is generally susceptible to infection and family cluster cases are easy to occur. So, it is necessary to precisely prevent and control this strain. Public security forensic experts have both medical literacy and criminal investigation capabilities, they can play a more professional role in epidemic prevention and control.基于公安法医视角的新型冠状病毒Delta变异株广州疫情特点及网格化人群管理.目的 基于公安法医视角，对新型冠状病毒Delta变异株在我国首次传播的疫情进行分析，探讨其流行传播特点、影响因素及流行病学调查经验，为新型冠状病毒变异株引发的疫情防控提供借鉴。 方法 基于公安法医参与流行病学调查一线工作获得的信息，对新型冠状病毒Delta变异株引发的广州市新型冠状病毒肺炎确诊病例、无症状感染者及其密切接触者的性别、年龄、居住地、传播途径、传染性等进行分析，并计算本次广州疫情期间的基本传播指数（basic reproduction number，R0）。 结果 本次疫情新型冠状病毒Delta变异株引发的153例感染病例中，男性63例，女性90例，年龄范围为1~92岁，中位年龄为49岁。传播途径以密切接触传播为主，包括聚餐、共同居住以及同栋住宅楼密切接触。家庭聚集性病例事件共31件，其中荔湾区25件。疫情自2021年5月26日至5月29日，R0维持在4.0以上，5月30日R0开始下降，并从6月7日起维持在1.0以下。 结论 新型冠状病毒Delta变异株的传染性强，人群普遍易感，易发生家庭聚集性病例事件，针对该毒株进行精准防控十分必要。公安法医兼具医学素养和刑侦业务能力，在疫情防控工作中可发挥更为专业的作用。.法医学；流行病学；新型冠状病毒肺炎；病毒变异；Delta变异株；密切接触者；疾病预防控制；网格化管理.
UTEP Library Research Guides: Library Workshops: Intro to Copyright

This guide provides all the information used in Library Skills Lab or the Library Workshops.
COMPARATIVE ANALYSIS OF PRODUCTION PREDICTION OF SILUNGKANG SONGKET AND PANDAI SIKEK SONGKET WITH MAMDANI FUZZY INFERENCE SYSTEM (FIS) METHOD

Fuzzy logic is widely applied in various fields, such as industry, communications, etc. Fuzzy logicwas developed to solve an obscure problem. The problem that arises in the production at MSMEsSongket Silungkang and Songket Pandai Sikek at this time is that there is no system used as areference in determining the amount of production in the future. Where this method can utilizedemand and supply data in the past which is then processed with fuzzy stages so as to produceproduction figures. The government has prioritized the development of the Silungkang songkethandicraft business, which is a regional specialty, in order to enter the export market. In the earlystages, the priority of the regional government was to increase the production of craftsmen byfacilitating coaching for micro, small and medium enterprises (MSMEs), especially those engaged insongket crafts, to continue to be developed by increasing quality and creativity. By applying theFuzzy Inference System method in predicting the production of Songket Silungkang KotaSawahlunto and Songket Pandai Sikek Kota Agam can help several parties such as the government,micro, small and medium enterprises in making efforts to handle and make good decisions towardsincreasing the production of Songket MSMEs in each region. and can provide a comparison of thepredicted results of production for the coming period so that it can produce the optimal number ofsongket based on market demand.
Implementation of Steganographic Algorithms Based on Exact Histogram Matching and Colour Visual Cryptography

Sensitive secret data transmission through internet has been of great security concern which can be overcome by steganographic methods achieved through secret image sharing. Two novel steganographic secret algorithms based on colour visual cryptography and exact histogram specification is proposed in the present study. The former approach combines colour visual cryptography with a secret key to produce less distorted meaningful share images. A specified histogram acts as the key for the second approach and provides better security and data obscurity compared to conventional approaches. A novel histogram specification method is also proposed which exactly matches the histogram of an image to a specified histogram.
Smart Forgery Detection for Signatures Using Deep Learning and Neural Networks

Smart forgery detection for signatures using deep learning and neural networksis a system that will play an important role in authentication of an individual‟s signature. Hence for various security purposes, the above stated system will be useful for instance at banks, legal documentations, government organizations, investigation purposes, business, automatic data entry etc.This system is trained on Convolutional Neural Network (CNN) that works well with the data set of 300 images. CNN has been implemented in Python using Keras with TensorFlow backend. It will compare the data set images with the image (of signature) provided by the user and hence output will be predicted whether the given image is authentic or forged.This system is expected to yield an accuracy of 80-85%. Also this system is practical and accurate enough to be deployed. Hence the above stated system successfully recognizes and identifies the signature of and individual. The planned system is highly economical and its accuracy can be increased by training this model on more data set.
Monitoring of active volcanoes in Peru by the Instituto Geofísico del Perú: Early warning systems, communication, and information dissemination

Volcano monitoring in Peru is carried out by the Instituto Geofisico del Peru (IGP), through its Centro Vulcanologico Nacional (CENVUL). CENVUL monitors 12 out of 16 volcanoes considered as historically active and potentially active in southern Peru and issues periodic bulletins about the volcanic activity and, depending on the alert-level of each volcano, also issues alerts and warnings of volcanic unrest, ash dispersion, and the occurrence of lahars. The information generated by CENVUL is disseminated to the civil authorities and the public through different information media (newsletters, e-mail, website, social media, mobile app, etc.). The IGP volcanology team was formed after the eruption of Sabancaya volcano in 1988. Since then, geophysical and geological studies, volcanic hazards assessments, and multidisciplinary monitoring realized by the IGP, have provided a comprehensive understanding of volcanic activity in Peru and forecast future eruptive scenarios. Currently, 80% of the historically active and potentially active volcanoes in Peru are equipped with networks of multiparameter instruments, with the seismic monitoring being the most widely implemented. In this report, we present the situation of volcanic monitoring in Peru, the monitoring networks, the techniques employed, as well as efforts to educate and inform the public and officials responsible for disaster risk management.
Using Extra Weight in Machine Learning Algorithms for Clickbait Detection of Indonesia Online News Headlines

Nowadays, large numbers of Indonesian people access news using online platforms. The large population makes them the target of clickbait news for publishers to gain ad revenue from clickbait. For languages such as Indonesian, there is still a lack of analysis of clickbait tasks [1]. This paper proposes machine learning with extra weight to detect clickbait from Indonesia Online News Headlines. We used 400 out of the 15,000 documents of local online news headlines randomly. The small dataset is used for better understanding and faster calculation. In pre-processing, documents of labeled clickbait are compared with documents of labeled non-clickbait. The result shows few characters which only appear in the specific label. These few characters become extra weight for the TF-IDF weighting term. 10-Fold cross-validation is used for data validation. In the classification process, we use four different algorithms (SVM, K-NN, NB, and Decision Tree). Finally, we conclude that using extra weight gives a maximum of 6&#x0025; better performance results rather than without extra weight.