Reviewerly/exHarmony huggingface dataset:
Agricultural Based Drone

The main vison of our project is to built a drone which can do certain things that is very much impossible by standards of a human in the fields such as locomotion and aerodynamics. The demand for delivery personnel has multiplied due to the significant growth in the use of online ordering. In order to fulfil this demand, drone-based technology is being deployed. A hexacopter can fly vertically in a stable manner and be used to deliver goods or collect data in a certain area. We think delivery drones are poised to disrupt the last mile transportation industry given the development of drone technology and rising commercial usage. Drones can drastically shorten delivery times and lower the cost of delivery for both humans and drone manufacturers.. The value chain and opportunities in the market for delivery drones are examined in this paper. It also talks about adoption's difficulties. Our argument for using drones to deliver the majority of lightweight products for the final mile comes at the end. This study describes the Hexa copter (QC) as a lightweight, inexpensive, autonomous flying capable Unmanned Aerial Vehicle (UAV) for delivering packages ordered online. Its primary on-board computing unit is an android device. This QC can locate and reach its goal by using Google Maps. This experiment showcases QC's ability to deliver an online-ordered package and then return to the starting point. Future studies on the use of QC for parcel delivery are made possible by the method's encouraging results.
El piano un instrumento en la contemporaneidad

&nbsp;This research is divided in two parts, along with the conclusions, bibliography and discography. The first part is an approach of the environment and influences in the piano works done by the author between 2016 and 2020. These works, which will connect with sound design and biographical elements, based on her pedagogical theory. The second part focuses on the analysis of these piano works where Ensaio (2008) is included for piano, voice and live electronics as an antecedent.
SELF-EFFICACY AND MATHEMATICS PERFORMANCE AMONG COLLEGE STUDENTS: BASIS FOR DEVELOPMENT OF MATHEMATICS ENGAGEMENT TRAINING

This descriptive-correlational study aimed to determine the extent of self-efficacy and mathematics performance among College students, which will be the basis for mathematics engagement training.One hundred fifty students chosen randomly were the respondents of the study.Findings revealed that most students rated "moderate" self-efficacy and "very high" mathematics performance.exhibited "extremely high" mathematical proficiency in a category like sex and course.When the respondents were divided by course and sex, there were no discernible variations in their mathematical ability and sense of self-efficacy.Only when performance in mathematics is categorised as to course does a noticeable difference appear.There were significant and adverse associations between respondents' self-efficacy and mathematical performance.
AdaBias: An Optimization Method With Bias Correction for Differential Privacy Protection

A continuous increase in privacy attacks has caused the research and application of differential privacy (DP) to gradually increase. We can improve the efficiency of the DP model by Optimizing its parameters significantly. Inspired by the performance of various optimization methods for differential privacy, this paper proposes an improved RDP-AdaBound optimization method with bias correction, which is called “AdaBias”, to increase the performance of Rényi differential privacy (RDP). The bias correction is used to realize the learning rate and speed up the convergence by upper and lower bound functions. We evaluate our method on the three datasets by training two different privacy model. We further compare three traditional optimization algorithms, namely, RDP-SGD, RDP-Adagrad, and RDP-Adam. And we use AdaBias to verify the performance of privacy protection on the COVID-19 dataset. Experimental results show that the new variant better implements learning rate adjustment to accommodate updates of noisy gradients. As a result, it can achieve higher accuracy and lower losses with a lower privacy budget, thereby better protecting data privacy.
Application of Tsukamoto's Fuzzy Logic in Determining the Level of Service Quality at the Bengkulu Province Library and Archives Service

Fuzzy logic is part of an artificial intelligence system that emulates human ability to think into algorithms which are then run by machines. At the Bengkulu Province Library and Archives Service, there is no application that can help to determine the quality of service based on the value given by the respondent. Service Quality Level Application at the Bengkulu Provincial Library and Archives Service is an application built to facilitate library members in providing value to the quality of services provided by the Bengkulu Provincial Library and Archives Service, and this application applies the Tsukamoto Fuzzy Logic method where the level of service quality is divided into 5 levels, namely Very Good, Good, Fairly Good, Less Good and Not Good. Based on the results of the tests that have been carried out, the functionality of the application has run as expected, and the Service Quality Level Application at the Bengkulu Provincial Library and Archives Service for 2021 is Very Good and this application is able to display the level of service quality every year through the Tsukamoto Fuzzy Logic Method approach.
Exploring the Impact of Blockchain Technology on the Development of Digital Economy

The development of blockchain technology has attracted attention from all walks of life around the world, and at this stage it has promoted the transformation and upgrading of the digital economy.The blockchain is essentially a recording system.Since each recording system needs to be stored in blocks, the ID of each block forms a chain-like structure before and after the recording time.For the development of the digital economy, the blockchain has a more complete system support.With the effective integration of digital technology and the real economy, the position occupied by blockchain technology is becoming more and more important.Therefore, exploring the impact of blockchain technology on the development of the digital economy and building a new infrastructure for the development of the digital economy can ensure the order of the operation of China's digital economy.
Analysis and implementation of SQL injection attack and countermeasures using SQL injection prevention techniques

SQL injection attack is the most critical and very common attack to security of web applications. The paper analyses the vulnerabilities that arise due to SQL injection attacks and presents consolidated prevention techniques which consider all vulnerabilities and identifies the SQL injection attacks. It also provides appropriate solution for safeguarding against SQL injection attacks. While being cost-effective, these prevention techniques are also easy to configure, administer and implement. Experimental results have proven that these prevention techniques efficiently identify and protect against SQL injection attacks. The prevention techniques discussed in this paper have been implemented and tested effectively. The results of testing are satisfactory.
Homomorphic Encryption Approach for String Concatenation

In a modern environment, a large amount of data is generated from various sources like healthcare, government, banking, and other different sectors. The traditional method for storing information is becoming challenging to handle big data. The solution to storing big data is to store data on third-party service providers. Data protection is the primary concern for storing and accessing data due to the emerging rate of data breaches and adversaries in personal data storage. Intruders manage to access sensitive data despite many efforts to protect sensitive data. Homomorphic encryption is a data protection approach in the cryptographic domain that can perform computations on cipher data without decrypting it. The computation outcome is encrypted; the output will be the same when decrypted as if the operations had been performed on the original plaintext data. This encryption method for privacy-preserving outsourced storage and computation permits the data to be encrypted and outsourced to cloud environments for further processing. This paper proposes string concatenation on encrypted data using the Advanced Encryption Standard algorithm with cipher blockchain mode of operation.
Computational Theory of Mind for Human-Agent Coordination

In everyday life, people often depend on their theory of mind, i.e., their ability to reason about unobservable mental content of others to understand, explain, and predict their behaviour. Many agent-based models have been designed to develop computational theory of mind and analyze its effectiveness in various tasks and settings. However, most existing models are not generic (e.g., only applied in a given setting), not feasible (e.g., require too much information to be processed), or not human-inspired (e.g., do not capture the behavioral heuristics of humans). This hinders their applicability in many settings. Accordingly, we propose a new computational theory of mind, which captures the human decision heuristics of reasoning by abstracting individual beliefs about others. We specifically study computational affinity and show how it can be used in tandem with theory of mind reasoning when designing agent models for human-agent negotiation. We perform two-agent simulations to analyze the role of affinity in getting to agreements when there is a bound on the time to be spent for negotiating. Our results suggest that modeling affinity can ease the negotiation process by decreasing the number of rounds needed for an agreement as well as yield a higher benefit for agents with theory of mind reasoning.
Disaster Vulnerability and Resilience of Foreigners in South Korea

The purpose of this study is to assess the level of disaster vulnerability of foreigners in Korea and identify the relationship between economic support, educational support, disaster resource support, information support, psychological support and disaster resilience of foreigners and suggested a strategy to improve disaster resilience. As a result of the analysis, it was found that economic support, educational support, disaster resource support, information support, psychological support has a significant effect on disaster resilience of foreigners. Based on these research results, the policy implications to improve disaster resilience are as follows. First, it is necessary to give disaster relief fund to foreigners. Second, it is necessary to provide disaster information in as many languages as possible. Third, it is necessary to explain the essentials of disaster evacuation and the location of the shelter through the manual. Fourth, it is necessary to provide psychological services to foreigners.
Historical and didactic definition analysis of approaches to the humanities role in the teaching content formation: West European experience

The article is devoted to Philology teachers’ intercultural competence formation. The aim of this article was to review different historical and pedagogical approaches to the understanding of the history of Humanities role in the teaching content choice in modern European research papers as ways of influencing the teaching content Philology teachers’ formation and their intercultural competence. Different understanding of the term “approach” was considered as well as the application of it in Europe. Our research is also based on the idea of uniqueness in the choice of foreign language teaching content and peculiarities of this sphere. The typical choice of the teaching content is teaching in the target language about the country and its habits and traditions. It is multicultural approach. Globalist and antiglobalist approaches to the study of the role of Humanities were briefly defined as contrary. They differ in the description of the history of Humanities, the sources they use as a basis of research, the definition of the notion “Philology” and attitude to comparativism. The authors only agree on the question that subdivision into Humanities and Nature Studies is artificial. Comparison of common and different points of view on the problem in Europe was undertaken. The conclusion was that studying of its role in the history of mankind should be included into content of teaching philologists and chosen for research problems as it can improve the content and quality of teaching. It gives a fine perspective for the professional research formation and future Philology teachers’ intercultural skills.
Hyperspectral Mixed Noise Reduction Using Two-Stage Cascade Refined Network

Hyperspectral images (HSIs) are inevitably influenced by various noise, including Gaussian noise, sparse noise and so on, which could degrade the HSIs and limit their applications greatly. Deep neural network (DNNs) based HSIs denoising methods have been widely used in recent years. However, the existing methods based on deep learning are mainly for Gaussian noise removal, and few are for mixed noise. Accordingly, we propose a two-stage cascade refined network consisting of two subnetworks for hyperspectral mixed Gaussian and sparse noise reduction. In the first stage, the spatial-spectral features are extracted by a feature extraction block based on attentions mechanism firstly. Then the multi-band noise is obtained by feeding the extracted features into the multi-band noise estimation subnetwork with encoder-decoder structure. Finally, the single-band denoising subnetwork in the second stage further refines the output of the previous subnetwork to accomplish single-band noise reduction. The experiments on HSI show that the superiority of the proposed method compared with four typical methods for mixed noise removal.
Research on CT Image Super-resolution Reconstruction with Multi-branch Fusion Network

Low-dose CT scan is an effective way to reduce the radiation risk of patients, but it can reduce the quality of images and affect the accuracy of medical diagnosis. To improve the resolution of CT images, we proposed a multi-branch fusion network to reconstruct CT images. First, the whole network framework is constructed by cascading multiple sub-networks. Local residual learning is introduced into each sub-network to improve the accuracy and convergence speed. Second, three branches of the convolution operation are used to extract the feature information of the image in parallel, the information is fused as the input of the next sub-network, and high-resolution images are reconstructed finally. By extending the depth and width of the network, the extracting feature ability of the network is improved. Meanwhile, global residual learning is introduced to enhance the reconstruction ability of the network. We used the classical LUNA16 datasets to train the model, calculated the loss function between the target image and the ground truth image, updated the weight, and got the optimized network model. We compared the model with related algorithms, the results showed that our method achieves better reconstruction effect, which will improve the accuracy of medical diagnosis.
Automatic Monitoring of Soil Moisture Based on a Resonant Type Information and Measurement System

The paper is devoted to research in the development and improvement of resonance control methods that allow remote monitoring of agricultural land moisture with high accuracy and speed under the influence of interfering factors. Resonant-type information and measurement systems with capacitive measuring transducers, based on the use of frequency methods for measuring humidity, are widely used in remote monitoring systems. This happened because dielcometric methods make it possible to monitor the state of the soil without destroying the fertile layer and other negative impacts on the environment, providing a sufficiently high level of accuracy of the result obtained with minimal costs. The main disadvantage of this class of information and measurement systems is the increased probability of measurement error in conditions of uneven distribution or dynamic change of parameters affecting the active conductivity of the soil, such as the content of bound moisture, the level of mineralization (salinity), etc. The purpose of this research is to study the possibility of reducing the frequency of occurrence and the magnitude of errors associated with the inertia of information-measuring systems of the resonant type. To achieve this goal, an analytical model of a digital exciting signal with a linear frequency sweep was developed, and experimental research was carried out. This made it possible to evaluate the key parameters of the high-frequency signal at the output of the measuring converter using the proposed parametric modulation scheme. To increase the reliability of the measuring system, the authors propose to use multiparameter methods and linear frequency modulation of the signal that excites the measuring transducer. The authors analyzed the processes associated with the appearance of additional measurement errors resulting from active losses in the controlled soil and the inertia of the resonant measuring system, and also identified ways to reduce these errors.
Deep learning approach to control sound through gestures using YOLO algorithm

In the era of machine intelligence, dynamic gesture recognition is assumed to be a difficult and challenging problem because it involves the human element. Moreover, the gestures formed for a particular problem vary from person to person. Therefore, the accuracy of classification sometimes becomes inappropriate. Also, gesture recognition is affected by lag in detection; however, a negative lag is assumed to be favorable. In this paper, an attempt has been made to control the system volume through hand gesture recognition which may help in the remote operation of a device and differently-abled people. The YOLO algorithm will deep learning approach is used in this paper, which detects hand movement and its direction. Based on the direction of hand movement, the volume can be increased or decreased.
On the Language Patterns of TV News Commentary Program Hosts--Take "News 1+1" as an Example

In the context of media integration, TV news commentary programs, as an important part of TV news programs, play an important role in guiding public opinion, and are undergoing changes all the time.The host of news commentary programs is the bridge connecting the program and the audience, and his language style has a profound impact on the communication effect of the program.The study of the language patterns of TV news commentary program hosts is helpful for the development of TV news commentary programs, provides TV news commentary program hosts with ideas for learning and reference, and promotes the development of TV news commentary programs.
A conceptual design for welding training simulation using virtual reality with multiple marker tracking method

This paper presents the use of a vision-based marker with a Virtual Reality (VR) system in welding training simulation to gain psychomotor skills in the welding position for engineering students. Currently, there is a lack of conceptual design and design management framework which leverage the combination of the VR world and tracking technique. This paper aims to explore the area of VR in welding training and how the multiple markers tracking methods can be utilized to overcome the tracking problems in VR for welding training simulation. The prototype system of combined VR and multiple tracking method features will be useful and effective for physical-based VR learning such as welding training simulation.
MITRE att&amp;ckTM based language for effective training in cyber range

Cyber security exercises and training are critical in ensuring that the people protecting systems have the necessary abilities. For this purpose, cyber range is a significant instrument used to educate security professionals, since it provides threat simulation and training material for adversary attack scenarios. However, the majority of current threat scenario generation takes time and results in static scenarios that are both inefficient and unrealistic. We propose the “MITRE ATT&amp;CKTM Based Language (MABL)” which will streamline the cyber range functions by assimilating and portraying knowledge on attack procedures. The proposed language will give information about attack techniques and be dynamic in nature.
The digital culture development problem actualization among pedagogical students

The article is devoted to the concepts “digitalization of education”, “digital culture” analysis and the current trends study in the pedagogical training students digital culture development in higher education. The research relevance stems from the need to connect education with the “real world” and to connect students' everyday experiences in the digital world with their educational activities. The research was conducted using the following methods: theoretical and methodological analysis, pedagogical interpretation, comparison, generalization, concretization, questioning, testing, survey method. The research clarified the concept of “a future teacher digital culture” as values, attitudes, competencies and worldview a set; lifestyle and habits created by the innovation brought by the era in which technology takes an increasing place in everyday life. And the digital culture components are also defined: computer literacy; digital competence; information value and meaning component; information and cultural component. The digital culture components formation process takes place in the students' productive learning and cognitive activities process. Thus, new teaching methods, including modern information technologies, should be involved along with traditional activities. A subject-specific partnership between teachers and students should be formed. Teachers act as managers and consultants for projects and research work. The study results indicate that the transition to the digital education model is accompanied by the educational process subjects qualitatively new changes in multidirectional relations, and students interact in the digital environment generates virtual identity formation new socio-cultural practices in cyberspace. In this connection, a modern education system formation and development is impossible without a high information culture, since education is one of the societies transmitting cultural values main forms.
Mimer Trust: Efficient and Secure Data Processing for Trusted Execution Environment in Automotive Systems

Trusted Execution Environment (TEE) is an effective mechanism to protect sensitive data against adversaries in automotive systems. However, its clear isolation of secured world from the normal world also restricts data sharing between the trusted and normal applications, which is desired in many modern vehicles. We propose Mimer Trust, a solution based on Mimer SQL and Trustonic TEE, to achieve fine-grained access control and efficient data sharing between the two worlds. Our solution builds up a relational storage for the secure data in TEE, which are originally stored as simple binary objects. We provide a high-level API to manipulate the secure data, and introduce SQL extensions to allow normal applications to access the TEE data with ordinary SQL statements and rich data types. Since all data access is made through the database server, privileges can be granted specifically to normal applications, which achieves fine-grained access control over the secure data. We also employ encryption of data as well as of data communication to protect the information. We explain our solution in details, and show how it is integrated in embedded system development. We demonstrate our solution on real devices, and conclude that Mimer Trust can improve the efficiency of data sharing between the secure and the normal worlds, enrich embedded application scenarios, and reduce development costs in the automotive systems.