Reviewerly/exHarmony huggingface dataset:
Measure and Predict the Receiver's Electromagnetic Susceptibility Fast

Evaluating and predicting rapidly and accurately a high sensitivity receiver's adaptability in complex electromagnetic environments is a tough job. To solve this problem, a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone test. An experiment performed on a radar receiver confirms the reliability of the method proposed in this paper. It shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity model. Based on this, fast and comprehensive evaluation and prediction of the receiver's electromagnetic susceptibility in complex environment can be efficiently realized.
Blockchain, IoT Applications and Industry 4.0

The Internet of Things (IoT) has been extensively employed in numerous fields of the industry as a crucial component of Industry 4.0. Nevertheless, in the IoT, cloud-based storage capacity, computation, and communication cause a slew of issues, notably transmission delays, single points of failure, and privacy breaches. Moreover, the IoT’s centralized access control limits its flexibility and reliability. It is where blockchain, a decentralised, trust - free, accessible, and irreversible append-only database appears. Smart home, smart vehicle, smart cities, smart industry, smart appliances, and smart control systems have all benefited from the combination of Blockchain and IoT technologies.
The decoherence effect of qubit in 1D transverse Ising model

With the development of lab technology, the low-order correlation function can no longer describe the main effect of decoherence in quantum many-body system, so it is imperative to study the higher-order correlation function of the system. In this paper, we study the changes of the correlation functions in the decoherence effect, analytically. And explore when it is possible to approach the qubit decoherence process only by low-order correlation function, and when third-order or higher correlation functions are needed in 1D transverse Ising model. It indicates that, under strong coupling and long coherence time, the effect of high-order correlation functions can not be ignored, and the approximation of classical Markov process is limited. But, in the case of weak coupling and short coherence time, low-order correlation function can describe well.
Geo-analytical hierarchy process for flood risk mapping using moderate resolution of satellite images

Career prospect, education and facilities attract more people gravitate toward urban areas. The population rate has increased significantly, placing a demand on metropolitan regions which become major drivers of natural hazard growth, including flood events. Satellite technology offers good services for flood mitigation and provides precautionary measures in a particular area. Thus, this study aims to produce flood risk map area in Kuantan using moderate- resolution satellite images and Digital Elevation Model (DEM) dataset was integrated with GIS tools to conduct flood risk analysis. The study found that the Kuantan city centre with low drainage capacity and high paved area is the highest risk flood zone, whereas Gambang with a huge green corridor and good drainage system is the lowest risk flood zone. These findings can provide the communities in this area with the required details and understanding of the type of floods normally occurring in study areas. This study is crucial to propose a solution to mitigate flood occurrences based on the satellite-based risk map analysis. This study supports the agenda of SDG13: Climate Action; where flood risk analysis serves to determine awareness and early warning to prevent loss of human life, biodiversity, crops and damage to property.
Instructional-learning design according to the creativity theory of investment and its impact on the achievement of second grade intermediate students

Research extractThis research aims to recognize an educational design -learning according to the theory of investing creativity and its impact on the attainment of middle-grade students.The researcher adopted the experimental curriculum with the experimental design of two equal groups, and the researcher deliberately selected the (middle of Iraq for boys) distributed to two divisions (a).b) The division (a) was selected in a random manner to represent the experimental group.In the same way, the division (b) was selected to represent the control group.The researcher was statistically rewarded among the members of the two groups in the following variables: (Chronological age calculated by months, degrees of science, test of intelligence Raven).The researcher identified the subject matter of the science book for the middle second grade, and then the researcher formulated behavioral goals as many as (180) behavioral goals representing the first four levels of Bloom's cognitive classification, as for the research tool, the researcher built an attainment test consisting of (40) Objective test paragraph of multi-quadrilateral choice of alternatives according to (Table of Standards) verification of honesty, differentiation, difficulty, effectiveness of alternatives and stability; Its stability has been verified in a halfway form of fragmentation; The researcher used appropriate statistical means to extract data, and the results showed that the pilot group outweighed the control group, in the light of which the researcher formulated a number of recommendations and proposals mentioned in chapter IV.
Digital literacy as a key factor in educating intellectual youth

This research paper investigates the Digital Literacy as a key factor in educating intellectual youth and its successful adaptation to digital realities.It also analyzes the importance of development of Digital Literacy competences in society as one of the main indicators of their successful adaptation in virtual and real realities.This investigation was conducted by using the online method (Google forms) and direct personal interviews through a pre-designed questionnaire.The questionnaire consisted of five sections which covered a set of questions focused on different computer literacy and internet use skills.The study revealed that the development of Digital Culture in Uzbekistan depends on the level of digital competencies that are necessary for adaptability in the digital space, that is, the ability and use of modern digital devices, the active use of digital channels for communication, digital understanding, the preferred direction of using digital technologies in resolution tasks, a correct understanding of the principles of action in the digital space, possession of the principles of digital security and digital data.
Study on optimization of multi-UAV nucleic acid sample delivery paths in large cities under the influence of epidemic environment

In the context of global novel coronavirus infection, we studied the distribution problem of nucleic acid samples, which are medical supplies with high urgency. A multi-UAV delivery model of nucleic acid samples with time windows and a UAV (Unmanned Aerial Vehicle) dynamics model for multiple distribution centers is established by considering UAVs' impact cost and trajectory cost. The Golden Eagle optimization algorithm (SGDCV-GEO) based on gradient optimization and Corsi variation is proposed to solve the model by introducing gradient optimization and Corsi variation strategy in the Golden Eagle optimization algorithm. Performance evaluation by optimizing test functions, Friedman and Nemenyi test compared with Golden Jackal Optimization (GJO), Hunter-Prey Optimization (HPO), Pelican Optimization Algorithm (POA), Reptile Search Algorithm (RSA) and Golden Eagle Optimization (GEO), the convergence performance of SGDCV-GEO algorithm was demonstrated. Further, the improved RRT (Rapidly-exploring Random Trees) algorithm is used in the UAV path planning, and the pruning process and logistic chaotic mapping strategy are introduced in the path generation method. Finally, simulation experiments are conducted based on 8 hospitals and 50 randomly selected communities in the Pudong district of Shanghai, southern China. The experimental results show that the developed algorithm can effectively reduce the delivery cost and total delivery time compared with simulated annealing algorithm (SA), crow search algorithm (CSA), particle swarm algorithm (PSO), and taboo search algorithm (TS), and the developed algorithm has good uniformity, robustness, and high convergence accuracy, which can be effectively applied to the multi-UAV nucleic acid sample delivery path optimization in large cities under the influence of an epidemic environment.
Object-tracking gimbal for projection mapping

In this paper, we investigate a simple movable projection mapping system which can reduce distortion and fluctuation of a projected image by assisting a gimbal device by geometric image transformation. Since a conventional gimbal device can compensate the movement of a mounted projector only, we design a new gimbal device which can compensate the relative geometrical relationship between the projector and the screen as well. The proposed method stabilizes a projected image using the newly designed gimbal which tracks the screen with a visual marker placed at each vertex and transforms the shape of image. Through an experiment, we evaluate the performance of the proposed projected image stabilization technique.
Semiotic Explication of Models of Ideologically Alternative Societies in E.I. Zamyatin’s Dystopia «We»

Based on the material of value judgments contained in the narrator D-503’s diary entries, the publication carries out the semiotic reconstruction of models of ideologically incompatible societies, traces the possibilities of transition from one model to another model as a way of developing humanity in the author’s imaginary reality. As the research methodology, A.J. Greimas’s concepts of the actanial scheme and the semiotic square are used, which recognize the importance of the dichotomy of polar linguistic signs in the process of interpreting their semantics. The author analyzes the relations of contrarity established between the models of impeccable and imperfect (ancient and oppositional) societies based on the extraction of deep meanings from the surface narrative structure. It is established that each of these models, functioning as the semiotic construct, is filled with specific semantics against the background of the opposition of another model. The concept of an actanial scheme turns out to be relevant when identifying the specifics of the narrator’s assessment of social structure models. The antonymic content of these schemes is analyzed based on the Benefactor and ancient ancestors’ position. The holders of these positions change the actanial roles of the subject and the antisubject. A multiple interpretation of the semiotic square of the Benefactor’s impeccable society is given as a formed community of people against the background of the opposition of the model of a formless society, assuming both a positive and negative perspective of development. Accordingly, these models are investigated in terms of positive and negative deixis, as well as implicative and suppositional relations. Relevant / irrelevant strategies of transition from one model to another model are traced, which can be either straight-line or assume an intermediate stage. The concept of the semiotic square underlies the analysis of the development of models of societies on the dystopian narrative historical axis. The ideas of models reflecting the immediate period of the narrative and potential future events, as well as the imagined past, are systematized. It is concluded that the models of society related to the current moment of the narrative are in a state of formation, however, they have formed ideological attitudes, which increases the antagonism between them.
Ordinal Regression With Pinball Loss

Ordinal regression (OR) aims to solve multiclass classification problems with ordinal classes. Support vector OR (SVOR) is a typical OR algorithm and has been extensively used in OR problems. In this article, based on the characteristics of OR problems, we propose a novel pinball loss function and present an SVOR method with pinball loss (pin-SVOR). Pin-SVOR is fundamentally different from traditional SVOR with hinge loss. Traditional SVOR employs the hinge loss function, and the classifier is determined by only a few data points near the class boundary, called support vectors, which may lead to a noise sensitive and re-sampling unstable classifier. Distinctively, pin-SVOR employs the pinball loss function. It attaches an extra penalty to correctly classified data that lies inside the class, such that all the training data is involved in deciding the classifier. The data near the middle of each class has a small penalty, and that near the class boundary has a large penalty. Thus, the training data tend to lie near the middle of each class instead of on the class boundary, which leads to scatter minimization in the middle of each class and noise insensitivity. The experimental results show that pin-SVOR has better classification performance than state-of-the-art OR methods.
Detection of Salient Objects in a Video using a Hybrid Neural Network Model

Salient detection is an active and critical area that is designed within the detection of items of a video recording, nonetheless, it attracts elevated interest among scientists. With rising powerful video clip information, the overall performance of saliency item detection techniques is degrading with typical item detection techniques. The problems lie with blurry moving goals, super-fast motion of items as well as dynamic background or background occlusion alteration on foreground areas within the video clip frames. This kind of obstacle leads to bad saliency detection. This paper models a full mastering design to deal with the difficulties, and that works on an advanced framework by merging the thought of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) with firefly Optimization technique for video clip saliency detection. Good utilization of the firefly algorithm together with CRNN is completed for the removal of characteristics by the video clips for item recognition. The primary objective of this newspaper is to present an effective hyperparameter choice framework for Convolution Recurrent Neural Networks (CRNNs) that employ one of the more popular swarm intelligence methods, the firefly algorithm. The suggested technique goals at creating a spatiotemporal design that exploits temporal, local, and spatial restriction cues to attain worldwide SEO. The process of locating the salient items in deep benchmark powerful video recording datasets will be completed by recording the temporal, local, and spatial restriction characteristics with all the CRNN. The CRNN is examined on benchmark datasets from typical video clip salient item detection techniques within the terminology of accuracy and load of Computation. The tests show that the proposed design accomplishes enhanced overall performance compared to some other existing versions which prove to significantly satisfy all the traditional object detection models.
FACE RECOGNITION ATTENDANCE SYSTEM USING MACHINE LEARNING

Face is the representation of one's identity.As a result, we have suggested a face recognition-based automatic student attendance system .In face recognition stage, enhanced local binary pattern (LBP) and principal component analysis (PCA) is applied correspondingly in order to extract the features from facial images.The facial images are then classified and recognized based on the best result obtained from the combination of algorithm, enhanced LBP and PCA.Finally, the attendance of the recognized student will be marked and saved in the excel file.The student who is not registered will also be able to register on the spot and notification will be given if students sign in more than once.
INTERESTS OF DIGITAL NATIVES IN LEARNING BUSINESS INFORMATICS: WHAT DIFFERENCE DO 5 YEARS MAKE?

Appears in: INTED2023 Proceedings Publication year: 2023Pages: 338-346ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.0124Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
TECHNOSPHERE OF THE XXI CENTURY AND HUMANITARIAN ASPECTS OF ENGINEERING EDUCATION

The analysis of the main trends in the transformation of the technosphere of modern civilization, which manifest themselves in the XXI century as a result of the rapid development of the scientific and technological revolution and man-made human activity. It is shown that these trends pose a global threat to the further development of civilization. If these trends persist in the future, humanity may perish as a result of the destruction of vital ecosystems of the planet and the global ecological crisis, which is rapidly growing. It is expected that it will reach its apogee in the middle of the XXI century. The transformation of the information sphere entails deep destructive changes in the social, psycho-logical and intellectual qualities of the individual. And it is also a new threat to global security. The article shows the negative impact on people of modern high rates of transformation of the technosphere. It causes them to feel fear of the future, which is approaching too quickly. The forecast of the dynamics of the main components of the techno-sphere for the period up to 2050 is presented. It is shown that the most rapid and radical changes occur in the infor-mation sphere of society. A new habitat forms a new person, changes his psychological, social and physiological properties and qualities. If this process continues to be carried out uncontrollably, then in the second half of the XXI century, humanity may become like a global anthill. People's lives in it will be strictly regulated, and their own intelligence will be lost. The article raises the problem of moral responsibility of engineers for the humanitarian consequences of their professional activities. To solve it, it is necessary to increase the level of modern humanitarian knowledge among representatives of the engineering corps of Russia.
MOBILE TECHNOLOGY FOR PROFESSIONAL DEVELOPMENT AND WELLBEING: THE REFLECTA PROJECT

Appears in: INTED2023 Proceedings Publication year: 2023Pages: 8074-8078ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.2189Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
IMPLEMENTATION OF THE PROTON MODEL IN IMPROVING ELEMENTARY SCHOOL STUDENTS WRITING SKILLS

Appears in: INTED2023 Proceedings Publication year: 2023Pages: 5168-5175ISBN: 978-84-09-49026-4ISSN: 2340-1079doi: 10.21125/inted.2023.1341Conference name: 17th International Technology, Education and Development ConferenceDates: 6-8 March, 2023Location: Valencia, Spain
Application of Chatgpt in Soil Science Research and the Perceptions of Soil Scientists in Indonesia

Since its arrival in late November 2022, chatGPT has rapidly gained popularity and significantly impacted how research is planned, conducted, and published. This article presents the findings of a brief study investigating the responses and perceptions of soil scientists in Indonesia towards chatGPT. This artificial intelligence application facilitates conversation-based interactions in text format. The study evaluated ten chatGPT answers to fundamental questions in soil science, which has developed into a normal science with a mutually agreed-upon paradigm. The evaluation was carried out by five soil scientists recognized for their expertise in Indonesia, using a scale of 1 to 100. In addition, a questionnaire was distributed to soil scientists at the National Research and Innovation Agency (BRIN), universities, and members of the Indonesian Soil Science Association (HITI) to gauge their perception of chatGPTâ€™s presence in the research field. The study results indicate that the level of trust of soil science experts in Indonesia to chatGPT answers has reached above 80%. However, there are no significant of different of chatGPT answers free chat GPT and paid chatGPT. There is only a significant difference between the answers to long answer of paid chatGPT in Bahasa Indonesia and long answer of chatGPT in English. On the other hand, the perception of general soil scientist about level of trust only 55%. Furthermore, 80% of soil scientists believe that chatGPT can only be used as a digital tool to assist research in soil science and cannot be used without the involvement of soil scientists.
Ship scene vehicle location method based on multi-source information fusion

This paper proposes a real-time vehicle location method based on multi-source information fusion of vehicle wheel speed features and visual images for the problems of weak texture features, high similarity of regional features, low accuracy of feature recognition and detection, and jump of vehicle location results in ship scene. Firstly, in order to solve the problem of inertial navigation sensor failed and get accurate pose estimation of vehicle motion, the article builds a vehicle motion prediction model based on vehicle wheel speed features. Secondly, according to the significant geometric features of the actual scene, Hough transform, edge extraction, template matching and inverse projection transform algorithms are used to identify and detect visual features of the scene. Thirdly, an extended Kalman filter is used to fuse vehicle wheel speed pose estimation and visual features to identify and detect the results to obtain reliable and high-precision real-time location of the vehicle. Finally, experiments are employed to verify the real-time vehicle location method based on multi-source information fusion of vehicle wheel speed features and visual images. The experimental results show that this method can effectively achieve vehicle localization in weak texture, similar regional features, and non-stationary road scenes.
Multi-scale context-aware segmentation network for medical images

Aiming at the problems that the method based on U-shaped network for medical image segmentation cannot capture the long-range dependencies and could lose some detail information, a multi-scale context-aware segmentation network for medical images is proposed. The model extracts the last three layer features of the encoder, and then introduces a global circular convolution transformer module to solve the problem of long-range dependencies capturing by modeling the global context information. Then, an attention guidance module is introduced to fuse features of different scales, so as to solve the problem of losing details while reducing the introduction of noise information in the low level features. The experimental performance on Synapse multi-organ segmentation datasets indicates that the model produces more precise segmentation results.
A method for wireless communication interference signal identification based on extreme learning machine

Intelligent anti-jam communication is a new generation of anti-interference technology combined with artificial intelligence, and the identification of interference signals is the basis of the technology. It is required to achieve better identification results with lower computational complexity in engineering applications. However, previous research has shown that they cannot balance these two sides. Here, we report an interference signal identification algorithm based on Extreme Learning Machine (ELM). Five typical oppressive interference signals were recognized based on ELM which is based on feature extraction. The overall correct identification rate is more than 96% under the condition of 40 neurons in a single hidden layer, and it has certain generalization ability. This study objectively promotes the engineering application of this technology.