bluuebunny/crossref_metadata_2025 huggingface dataset:
The problem of Russian identity formation in social and philosophical understanding
Authors:   Academy of Marketing and Social and Information Technologies — IMSIT, Petrakova Anna S.
Published: March 2023

The problem of identity formation is, of course, important for every individual. The process of constructing an identification basis is influenced by many factors, among which the main ones are belonging to an ethnic group, state, religion, culture. The article deals with the problem of understanding and formation of modern Russian identity. The author argues that its basis is a constructive synthesis of ethnic and national elements, since the former are dictated by a common origin, territory of residence, language, culture, and the latter, in turn, go back to statehood and citizenship, and are also conditioned by a single value-semantic and legal field. The author pays special attention to the consideration of Russian identity in a civilizational aspect, pointing out that the identification basis for Russian citizens is the spiritual and moral values inherent in the Russian people in their multicultural totality, namely collectivism, catholicity, mutual assistance, mutual assistance, a sense of civic solidarity. At the same time, a special specific feature of the Russian identity, according to the author, is also the belief in the absolute social organizing principle of the state, which explains the inclination of citizens to put, first of all, the administrative decisions of the authorities at the forefront.
Social, ethical, medical and psychological aspects of gender reassignment in children
Authors:   A.I. Evdokimov Moscow State University of Medicine and Dentistry of the Ministry of Healthcare of Russian Federation, Zorin Konstantin V.
Published: March 2023

The author analyzes the socio-ethical and medical-psychological aspects of gender ideology taking the example of gender reassignment in children. The following research methods were used in the work: study and analysis of the professional literature, synthesis, modeling, comparison, generalization, observation, system analysis and theoretical knowledge. The introduction of ultra-liberal concepts in the West in bioethics, philosophy, cultural studies, medicine, pedagogy and psychology leads to dangerous consequences. All traditional values will either be deformed or reformatted and will contribute to the destruction of human health and life. This will inevitably reduce the quality of the doctor's training, increase the number of diagnostic, therapeutic and ethical-deontological errors. In order to treat the gender identity disorder, it is not necessary to change sex. Instead, psychological correction and psychotherapeutic methods aimed at accepting one’s gender and increasing social adaptation when communicating with peers might be used.
The degree to which faculty members in Palestinian universities possess digital competence in light of the Corona pandemic
Authors: Abu Aqil Ibrahim Ibrahim
Published: March 2023

This research aims to Identified to the extent to which faculty members in Palestinian universities possess digital competence in light of the Corona pandemic, as a stratified sample of (300) faculty members was selected, and the questionnaire that he made (Sangeetha and Saileela, 2021) was developed and used to detect Digital competence, and the results showed that the degree of possession of digital competencies by faculty members in Palestinian universities came to a medium degree, and they use e-mail and browsing, social media and to direct students to follow the course, and their ability to prepare electronic lecture files and upload documents and videos necessary for the lecture. On the other hand, it was also found that there were no statistically significant differences attributable to the variables of sex and university, while it was found that there were statistically significant differences due to the variable of academic rank and in favor of the highest rank, and in the variable of years of service and in favor of the least years of service.
The impact of social media on the behaviour and values of university youth in the Sultanate of Oman
Authors: الحضرمي د. أحمد بن سعيد بن ناصر , السناني د. محمد بن خليفة , الصقري د. محمد خلفان
Published: March 2023

The study aimed to identify the impact of social media on the behaviour and values of university youth in the Sultanate of Oman with a field study on Al Sharqiya University. Third, the study reached the following results:   There is a wide impact of social media on the behaviours of students at A'Sharqiyah University, as these effects tended to the negative side more than the positive in general, and the effects were in the following aspects: increasing students’ isolation, and staying up all night due to integration with some programs, and the effect was also on emotion to a high degree, while the effects of social media on the values of university students tended to be positive, there are several values that interacted positively, including: expanding social relations, the recipe for cooperation and helping others, and empathy greatly with others. The study also confirmed the absence of significant differences. A statistic at the level of (0.05) in the impact of social media on the axes of values and behaviours attributed to the school year. The study recommends intensifying legal and self-censorship and spreading network culture, whether through various programs or lectures.
Highlights about Talents Development: The Future of Improving Higher Education Quality
Authors: Yousof Shimaa M. , Almohamadi Manar M. , Alsouri Mohammed T. , Salem Iman M.
Published: March 2023

The concept of talent development (TD) has emerged in the last few decades and has been discussed in many reports. The internationalization of higher education institute programs has obliged the universities to search for different strategies to update and enrich the academic performance at the level of employees, staff, and students. Talent development became necessary for many institutions to attract individuals with higher competencies and promote their performance. This review aims to highlight the importance of talent development in Higher education practice and achievement.
Global Mental Health Movement: Need for a cultural perspective
Authors: Sinha Nidhi
Published: March 2023

The present commentary reviews the goals and differing positions on the Movement for Global Mental Health (GMH), with a distinct emphasis on the cultural differences in the understanding of the aetiology of mental health issues. The proponents and advocates of GMH support its intentions and primary agenda of scaling up mental health services, especially in low-income and middle-income countries where the prevalence of mental health disorders is continually rising. However, many cultural psychologists and sociologists critique the movement for universalising psychiatric symptoms, as this universalisation could actually suppress local voices and might also undermine the significance of culture and political and psychosocial predictors which may contribute to mental health challenges. After discussing the pros and cons of the GMH movement, this commentary concludes with a conceptual analysis of the GMH position and offers predictions about its future discourse.
Positioning Method of Four-Wheel-Steering Mobile Robots Based on Improved UMBmark of Michigan Benchmark Algorithm
Authors: Wang Dianjun , Xu Meng , Chen Ya , Zhong Haoxiang , Zhu Yadong , Wang Zilong , Gao Linlin
Published: March 2023

To reduce the error of the odometer positioning system and improve the positioning accuracy of four-wheel-steering mobile robots, three types of coupling errors are considered, based on the University of Michigan Benchmark (UMBmark) method: unequal track width, unequal wheel diameter, and speed difference of ipsilateral wheels. A “dual direction square path experiment” is designed to decouple the error, a new system error model is defined, and an improved UMBmark method for a four-wheel mobile robot is proposed. In the mobile robot positioning system, a laser tracker is used to measure the absolute positions of the starting and ending points of the robot. The positioning test results of the robot using the improved UMBmark method show that the odometer system error is 69.103 mm, which is 2.6 times less than that in the traditional UMBmark method. Hence, the improved UMBmark can better compensate for the system error of four-wheel-steering mobile robots.
Design of Fast Green Distribution Route Based on Greedy Algorithm
Authors: Nie Xiuwu , Zhang Kaihui
Published: March 2023

This study focused on the fast vehicle route optimization issue with carbon emission and time window constraints for on-time consumer demand based on the greedy approach. A greedy algorithm was established to rapidly plan the distribution route to obtain the lowest distribution cost and shortest distribution time to achieve a green distribution. The distribution cost model covering the costs of vehicle transportation time, time window deviation, fossil consumption, and PM2.5 emission was established based on on-time demand and green distribution characteristics. This study analyzed the milk distribution route for Guangxi A Diary Co., Ltd. based on the greedy algorithm. The results show that compared with the genetic algorithm, the algorithm running time is reduced by 2 s, although the greedy algorithm requires an additional cost of 21.73 CNY.
Effect of Alcohol Consumption on the Frequency of Microsaccades
Authors: Ohara Toumi , Kinoshita Fumiya
Published: March 2023

In recent years, as eye movement measurement devices have become relatively cheap, many attempts have been made to quantitatively evaluate covert attention by focusing on microsaccades. However, the measurement of microsaccades still has many unclear points, and a unified analysis method is still lacking. As such, the interpretation of results differs among different research groups. To solve this problem, it is important to conduct empirical studies on microsaccades to evaluate them using a unified method. In this study, we conducted an empirical experiment on the effects of alcohol consumption on microsaccades by temporarily suppressing cerebellar activity with alcohol consumption. The results showed that the frequency of microsaccades was significantly reduced after 30, 50, and 70 min of drinking compared to after drinking (p< 0.05). These results suggest that the decrease in brain function caused by alcohol consumption suppresses the frequency of microsaccades, and that this may be the cause of constriction in the peripheral visual field when drinking.
Mediating Role of Self-Esteem in Activity Participants’ Passion for Exercise and Psychological Well-Being by Jogging in Fu Jen Catholic University
Authors: Kuo Ming-Yun , Tien-Liu Tsung-Kuo , Chang Wen-Lin
Published: March 2023

This study investigated the relationship between passion for exercise, self-esteem, and well-being of participants of jogging activities. Purpose: The purpose of this study was to explore the relationship between passion for exercise, self-esteem, and psychological well-being of participants with different backgrounds and determine whether self-esteem affects the relationship between participants’ passion for exercise and well-being. Design/methodology/approach: A total of 344 valid questionnaires were employed, which included 164 males and 180 females of the jogging activities held by Fu Jen Catholic University. Descriptive statistics, independent sample t-test, one-way analysis of variance, Pearson product-difference correlation, regression, and other statistical methods were performed on the questionnaire to test the correlation between variables. Findings: (1) Different sexes had differences in obsessive passion, (2) different jogging groups had differences in obsessive passion, (3) different grades had differences in negative self-esteem, (4) different ages had harmonious passion, and there were differences in positive self-esteem, (5) the frequency of exercising with peers exhibited differences in psychological well-being and positive self-esteem, (6) there was a correlation between passion, psychological well-being, and self-esteem, and (7) positive self-esteem had a mediating effect on harmonious passion and psychological well-being. Conclusions: Participants of jogging activities are willing to spend time and effort in jogging activities, participate with an open and flexible attitude, and enjoy the process, thus improving positive self-evaluation and achieving a satisfied self-feel. Originality/value: There is less research on the relationship between passion and self-esteem in Taiwan. In addition, the authors not only found the relationship between passion, self-esteem, and psychological well-being from the data, but also found that self-esteem has a mediating effect on the relationship between passion and psychological well-being. Therefore, when organizing similar activities in the future, in addition to using attractive conditions that are more favorable to the participants, attention should be given to conditions that can enhance the self-worth of participants and increase the motivation and number of participants. In addition, participants performing activities with their peers will have more positive self-evaluations and feelings and happier and more satisfied.
Particle Swarm Optimization-Based Convolutional Neural Network for Handwritten Chinese Character Recognition
Authors: Dan Yongping , Li Zhuo
Published: March 2023

Recently, handwritten Chinese character recognition has become an important research field in computer vision. With the development of deep learning, convolutional neural networks (CNNs) have demonstrated excellent performance in computer vision. However, CNNs are typically designed manually, which requires extensive experience and may lead to redundant computations. To solve these problems, in this study, the particle swarm optimization approach is incorporated into the design of a CNN for handwritten Chinese character recognition, reducing redundant computations in the network. In this approach, each network architecture is represented by a particle, and the optimal network architecture is determined by continuously updating the particles until a global particle is identified. The experimental validation resulted in a network accuracy of 97.24% with only 1.43 million network parameters. Therefore, it is demonstrated that the proposed particle swarm optimization method can quickly and accurately find the optimal network architecture.
Capsule Network Extension Based on Metric Learning
Authors: Ohta Nozomu , Kawai Shin , Nobuhara Hajime
Published: March 2023

A capsule network (CapsNet) is a deep learning model for image classification that provides robustness to changes in the poses of objects in the images. A capsule is a vector whose direction represents the presence, position, size, and pose of an object. However, with CapsNet, the distribution of capsules is concentrated in a class, and the number of capsules increases with the number of classes. In addition, learning is computationally expensive for a CapsNet. We proposed a method to increase the diversity of capsule directions and decrease the computational cost of CapsNet training by allowing a single capsule to represent multiple object classes. To determine the distance between classes, we used an additive angular margin loss called ArcFace. To validate the proposed method, the distribution of the capsules was determined using principal component analysis to validate the proposed method. In addition, using the MNIST, fashion-MNIST, EMNIST, SVHN, and CIFAR-10 datasets, as well as the corresponding affine-transformed datasets, we determined the accuracy and training time of the proposed method and original CapsNet. The accuracy of the proposed method improved by 8.91% on the CIFAR-10 dataset, and the training time reduced by more than 19% for each dataset compared with those of the original CapsNets.
Research on Image Inpainting Algorithms Based on Attention Guidance
Authors: Shen Yankun , Su Yaya , Wang Lin , Jia Dongli
Published: March 2023

In recent years, the use of deep learning in image inpainting has yielded positive results. However, existing image inpainting algorithms do not pay sufficient attention to the structural and textural features of the image when inpainting, which leads to issues in the inpainting results such as blurring and distortion. To solve the above problems, a channel attention mechanism was introduced to emphasize the importance of structure and texture after extraction by the convolutional network. A bidirectional gated feature fusion module was employed to exchange and fuse the structural and textural features, ensuring the overall consistency of the image. In addition, the features of the image were better captured by selecting a deformable convolution that can adapt the receptive field to replace the ordinary convolution in the contextual feature aggregation module. This resulted in highly vivid and realistic restoration results with more reasonable details. The experiments showed that, compared with the current mainstream network, the repair results of this algorithm were more realistic, and the superiority of this algorithm was proved by qualitative and quantitative experiments.
3D Street Object Detection from Monocular Images Using Deep Learning and Depth Information
Authors: Liu Wei , Zhang Tao , Ma Yun , Wei Longsheng
Published: March 2023

In this study, we present a three-dimensional (3D) object detection algorithm based on monocular images by constructing an end-to-end network, that incorporates depth information. The entire network consists of three parts. The first part includes the basic object detection neural network as the main body, that uses the region proposal network to obtain the two-dimensional (2D) region proposal of the object. The second part is the depth estimation branch network, that obtains the depth information of the object pixels and calculates the corresponding 3D point cloud. In the last part, concatenated features obtained from the aforementioned two parts are fed into the fully-connected layers. Subsequently, 2D and 3D detection results are obtained. Compared with certain existing methods, the accuracy of the detection results is improved in this study.
Research on Texture Classification Based on Multi-Scale Information Fusion
Authors: Wang Lin , Li Lihong , Su Yaya
Published: March 2023

Texture feature is an important visual cue for an image, which is the unified description of human visual attributes and sensory attributes. The inherent problem of texture image is that the difference of intra-class images is large and the disparity of inter-class images is small. This problem increases the difficulty of texture image recognition. Therefore, improving the relevance embedding of intra-class images can reduce the classification errors caused by this problem. To solve this problem, this paper proposes a multi-scale information fusion network algorithm, which adopts a cascade structure. It combines multi-scale feature information with the corresponding background information. The shallow background information guides the next stage of feature formation and enhances the similarity of intra-class images. The intra-class feature information obtained is more general. The algorithm has been tested on data sets describable texture database (DTD) and Flickr material dataset (FMD), which has achieved good results.
Relations Among Curriculum Governance Model, Teacher Work Settings, and Teacher Perceptions on the Professional Learning Community
Authors: Juan Hsiao-Chi
Published: March 2023

Following the education reform occurring worldwide, the professional learning community has been seen as a crucial factor in changing the teaching practice on site. However, empirical research has failed to deal with multicollinearity under a social context. This study examines the effect of curriculum development policy and leadership on the professional learning community of teachers. The regularized linear regression method is used to identify the precise effect on the professional learning community in two ways, i.e., ridge and least absolute shrinkage and selection operator regressions. The results show that the main variance comes from teacher actions at the school level and that the collaborative sense of teachers has the most significant effect. This study contributes to existing knowledge on the professional learning of teachers by providing distinguished view of governance model.
Extracting Branch Factors of Scenarios from a Gaming Simulation Using Log-Cluster Analysis
Authors: Sakata Akinobu , Kikuchi Takamasa , Kunigami Masaaki , Yoshikawa Atsushi , Yamamura Masayuki , Terano Takao
Published: March 2023

This study proposes a method for analyzing gaming simulation results. The gaming simulation we focus on intends to be played by both human and computer agent players. To extract the knowledge of what and how they have played, we must determine what type of decision-making process leads to specific scenarios. Such simulation results, however, tend to have so many branch factors of scenarios that it is hard to understand by manual operations. To deal with the issues, we have developed a method for obtaining the branch factors of scenarios from gaming simulation results. We have demonstrated the effectiveness of the proposed method by identifying the branching factors of scenarios as follows. First, software agents were asked to play a gaming simulation for career education. Next, logs acquired through gaming were classified into multiple scenarios using machine learning techniques. Finally, decision-making factors separating the scenarios were identified using a decision tree.
Modeling and Control Strategies for Liquid Crystal Elastomer-Based Soft Robot Actuator
Authors: Wu Jundong , Wang Yawu , Ye Wenjun , She Jinhua , Su Chun-Yi
Published: March 2023

Liquid crystal elastomer is a type of soft material with unique physical and chemical properties that offer a variety of possibilities in the growing field of soft robot actuators. This type of material is able to exhibit large, revertible deformation under various external stimuli, including heat, electric or magnetic fields, light, etc., which may lead to a wide range of different applications such as bio-sensors, artificial muscles, optical devices, solar cell plants, etc. With these possibilities, it is important to establish modeling and control strategies for liquid crystal elastomer-based actuators, to obtain the accurate prediction and description of its physical dynamics. However, so far, existing studies on this type of the actuators mainly focus on material properties and fabrication, the state of art on the modeling and control of such actuators is still preliminary. To gain a better understanding on current studies of the topic from the control perspective, this review provides a brief collection on recent studies on the modeling and control of the liquid crystal elastomer-based soft robot actuator. The review will introduce the deformation mechanism of the actuator, as well as basic concepts. Existing studies on the modeling and control for the liquid crystal elastomer-based actuator will be organized and introduced to provide an overview in this field as well as future insights.
Flexible Hyperspectral Anomaly Detection Using Weighted Nuclear Norm
Authors: Li Lei , Ren Yuemei , Ma Jinming
Published: March 2023

It has been demonstrated that nuclear-norm-based low-rank representation is capable of modeling cluttered backgrounds in hyperspectral images (HSIs) for robust anomaly detection. However, minimizing the nuclear norm regularizes each singular value equally during rank reduction, which restricts the capacity and flexibility of modeling the major structures of the background. To address this problem, we propose detection of anomaly pixels in HSIs using the weighted nuclear norm, which can preserve the major singular values during rank reduction. We present a down-up sampling scheme to remove plausible anomaly pixels from the image as much as possible and learn a robust principal component analysis (PCA) background dictionary. From a dictionary, we develop a weighted nuclear-norm minimization model to represent the background with a low-rank coefficients matrix that can be effectively optimized using the standard alternating direction method of multipliers (ADMM). Due to the flexible modeling capacity using the weighted nuclear norm, anomaly pixels can be distinguished from the background with the reconstruction error. The experimental results on two real HSIs datasets demonstrate the effectiveness of the proposed method for anomaly detection.
Digital Inclusive Finance and Industrial Structure Upgrade —Based on Nonlinear Relationship Perspective
Authors: Lin Shuping , Ma Wenhui
Published: March 2023

Compared with traditional finance, digital inclusive finance involves particular policies, different targeting, and wider coverage, plays a positive role in promoting the development of the real economy, and upgrades to industrial facilities. Based on the panel data of 288 prefecture-level cities in China from 2011 to 2019, in this study, we empirically examined the impact of digital inclusive finance on upgrades to industrial structures. The experimental results showed a “U”-shaped nonlinear relationship between the development of digital inclusive finance and the upgrades to industrial structure. In particular, this conclusion remained valid after citing instrumental variables, replacing core explanatory variables, and performing other robustness tests. Furthermore, we used the threshold model to test the influence of digital inclusive finance on industrial structure upgrade, and observed a double threshold effect based on digital inclusive finance and local levels of economic development. Therefore, in the dynamic transformation towards digital inclusive finance and continuing economic development, the role of digital inclusive finance in promoting industrial structure upgrade continues to strengthen.
Underdetermined Blind Source Separation Method for Speech Signals Based on SOM-DPC and Compressed Sensing
Authors: He Tao , Li Hui , Cheng Zeyu
Published: March 2023

Underdetermined blind source separation has received increasing attention in recent years as an effective method for speech-signal processing. Hence, a self-organizing mapping-density peak clustering and compressed sensing approach, which is a two-step approach, is proposed herein to improve the accuracy of underdetermined blind source separation. The approach features the following two aspects: (1) A mixing matrix estimation method based on self-organizing mapping and density peak clustering, which can intuitively determine the number of source signals, remove outliers, and determine the column vector of the mixing matrix based on local density; (2) a compressed sensing-based source signal reconstruction method, which can exploit the sparsity of signals in the frequency domain and use a hierarchical coupling method to reconstruct the source signal accurately and efficiently under the premise that the prior knowledge of the signal is unknown. The proposed method does not require the number of source signals and exhibits excellent performance under different noise conditions. Theoretical analysis and experimental results demonstrate the effectiveness of the proposed method.
Design and Implementation of a Recommendation System for Buying Fresh Foods Online Based on Web Crawling
Authors: Ou Tsung-Yin , Lee Yi-Chen , Chang Tien-Hsiang , Lee Shih-Hsiung , Tsai Wen-Lung
Published: March 2023

As shopping patterns have gradually shifted from offline to online mode, and with recent lockdowns during the coronavirus disease 2019 (COVID-19) pandemic restricting foreign trade and accelerating the growth of the domestic economy, digital transformation has become a major strategy for many retailers to support and expand their businesses. With the pandemic becoming a turning point, the business of major e-commerce companies in Taiwan in the retail of dry goods has grown significantly, and it has driven the online sales of fresh products as well. In this era of fierce competition, it is especially important to find a way that enables consumers to quickly find ideal fresh products on multiple platforms, shortens the time for price comparison, and improves the efficiency of online shopping. This study uses the Python programming language to write a web crawler program that captures product information from fresh food e-commerce platforms, including product introduction, price, origin, and sales volume, and then defines the relevant status of the product, such as product popularity. Accordingly, through Chinese text segmentation and term-frequency calculation, it aims to classify the product names and introductions into frequently occurring words and use them as product-related labels. Finally, the program combines the product information processing results and product-related labels to construct an online fresh food recommendation system. The results of the proposed system show that it reduces the time and energy spent comparing prices. It can also guide consumers to browse products that may be of interest using relevant tags and increase consumption efficiency by helping them find the ideal item when shopping.
The Impact of Field-Flipped Courses on College Students’ Self-Regulated Learning and Learning Performance Take a National University in Central Taiwan as an Example
Authors: Chen Yu-Ling , Lo Shihmin , Cheng Jen-Son
Published: March 2023

Objectives: In the past, an inherent dilemma in the education field was the difficulty in stimulating self-regulated learning. Flipped education, i.e., flipped teaching and learning, changed the teaching model, with a strategy of increasing students’ active learning during class time through a transformation of teaching and learning methods that enable students to build learning and knowledge on their own. This study investigates the impact of field-based flipped courses on college students taking up self-regulated learning and their learning performance. Methods: This study considers a national university in central Taiwan that adopts 34 field flipped teaching courses and 796 non-degree students from four colleges across all grades as the research objects, and conducts statistical analysis using descriptive statistics, t-test, ANOVA, Pearson’s correlation, and regression analysis on questionnaires to evaluate the association among variables. Findings: 1. With respect to the understanding of the uniqueness of field-based flipped teaching before and after the courses, there were differences among students in the Colleges of Education, Humanities, and Management. 2. In terms of students’ learning performance in the course pertaining to mastery over core literacy, there were differences between students of the Colleges of Education and Humanities at the beginning of the flipped-learning course. 3. There were differences among the students of Colleges of Education, Humanities, and Science and Technology in the later stage of the flipped-learning course. 4. Differences were found in the pre-test of learning performance at the grade level. 5. Self-regulated learning correlated with learning performance. 6. Field-based flipped teaching correlated with learning performance. 7. Self-regulated learning had a mediating effect on field-based flipped teaching and learning performance. Innovations: There is a little systematic discussion on the emergence and impact of flipped teaching in higher education currently in Taiwan. The authors found correlations among flipped teaching, self-regulated learning, and learning performance from the data, as well as discovered that self-regulated learning had a mediating effect on learning performance in field-based flipped teaching. Value: Making the university, when the curriculum arrangement and the development of the unique curriculum map of higher education in the future, possible to be linked with the local revitalization thinking in addition to the general curriculum, as well as being closely integrated with the local people and matters through field-flipped courses, and sustainably interacting therewith to practice university social responsibility.
Synchronization of Hyperchaotic Systems Based on Intermittent Control and its Application in Secure Communication
Authors: He Jianbin , Qiu Wenlan , Cai Jianping
Published: March 2023

The synchronization of master-slave hyperchaotic systems is investigated by intermittent control and proved by the Lyapunov stable theory. Meanwhile, a new secure communication scheme is designed for the continuous and digital information. The encrypted information is transmitted to receiver through the intermittent controller, which reduces the disturbance to the synchronization of master-slave systems and improves the security and reliability of secure communication. Before transmitting to the receiver, the continuous signal is firstly modulated and masked by the chaotic signals. Furthermore, an encryption algorithm for the digital information of color image is proposed by the pseudo-random sequences of Chen hyperchaotic system, and then the encrypted image is modulated and masked by the variables of the master system. The original image can be decrypted successfully at the receiving end after the slave system is synchronized with the master system. Finally, the feasibility and effectiveness of this scheme are verified by simulation experiments. In addition, the security analysis of the image encryption algorithm is also discussed, such as key sensitivity, correlation coefficient, NIST test, and return map.
A Data-Driven Prediction Model of Blast Furnace Gas Generation Based on Spectrum Decomposition
Authors: Feng Lili , Peng Jun , Huang Zhaojun
Published: March 2023

Blast furnace gas (BFG) is an important secondary energy in the iron and steel industries, and its efficient and reasonable utilization is the key to improving the economic efficiency of enterprises and the level of energy conservation and emission reduction. Aiming at the problems of difficult accurate modeling on the generation process and difficult prediction of real-time flow, this paper proposes a generation prediction model based on spectrum decomposition. Firstly, the major chemical reactions, production process, and data characteristics of blast furnace are analyzed, and the input variables for the prediction model are reasonably selected based on the correlation analysis results. Then, according to the spectrum characteristics, the BFG data is decomposed into low-frequency and medium-frequency parts by two finite impulse response filters. Next, for the low- and middle-frequency components of data, a low-frequency component prediction model based on the support vector regression, and a middle-frequency component prediction model based on the Elman neural network (ENN) are designed respectively. Finally, we decompose the spectrum of the actual industrial production data and find that the spectrum of the decomposed data basically meets the expected target, which verifies the effectiveness of the finite impulse response filters. In addition, we compare the prediction effect of the designed combined model with other models, such as the support vector regression, the back-propagation neural network, and the ENN. The final experimental results show the correctness, effectiveness, and superiority of the combined model and the spectral decomposition method proposed in this paper.
Drill-String Dynamics Model of Horizontal Coal Mine Wells Considering Intermittent Borehole Wall Contact
Authors: Huang Jie , Lu Chengda , Chen Luefeng , Li Quanxin , Li Wangnian , Wei Hongchao , Wu Min
Published: March 2023

During the drilling process, horizontal drill strings are often subject to stick-slip and back-pressure phenomena, which undermine drilling safety and affect drilling costs. However, most of the models proposed in the existing literature apply only to the analysis of the drill string motion state and are irrelevant to the rotary drilling process in coal mines. This paper presents a lumped-mass model of a drill string in a horizontal coal mine well. First, based on reasonable assumptions, the drill-string system was considered as four lumped-mass units. The lateral-torsional dynamics model was established based on the Lagrange dynamics theory. Further, combined with lateral movement, the intermittent contact between the drill string and borehole wall is described, and the friction torque due to this intermittent contact is calculated. Combined with the Karnopp bit-rock interaction, a drill-string dynamics model of horizontal wells that considers intermittent contact friction was developed. The proposed horizontal well drill-string model is more suitable for rotary drilling in a coal mine, and the nonlinear influencing factors are considered more comprehensive.
The Effects of Different Item Selection Methods on Test Information and Test Efficiency in Computer Adaptive Testing
Authors: ŞAHİN KÜRŞAD Merve
Published: March 2023

The purpose of this study is to examine the effect of different item selection methods on test information function (TIF) and test efficiency in computer adaptive testing (CAT). TIF indicates the quantity of information the test has produced. Test efficiency resembles the amount of information from each item, and more efficient tests are produced from the smallest number of good-quality items. The study was conducted with simulated data, and the constants of the study are sample size, ability parameter distribution, item pool size, model of item response theory (IRT) and distribution of item parameters, ability estimation method, starting rule, item exposure control and stopping rule. The item selection methods, which are the independent variables of this study, are the interval information criterion, efficiency balanced information, matching -b value, Kullback-Leibler information, maximum fisher information, likelihood-weighted information, and random selection. In the comparison of these methods, the best performance in the aspect of TIF is provided by the maximum fisher information method. In terms of test efficiency, the performances of the methods were similar, except for the random selection method, which had the worst performance in terms of both TIF and test efficiency.
Finger Necrosis After Cutaneous Wart Intralesional Injection with Candida albicans Antigen
Authors: Graham Jack G. , Tosti Rick
Published: March 2023

Case:

A 25-year-old man presented 18 hours after Candida albicans antigen injection into a left index finger cutaneous wart by his dermatologist. He experienced a rapid-onset inflammatory response, which was indistinguishable from gangrenous infection. Urgent incision and drainage was performed; however, no purulent collection was noted and no organism isolated. At 1-year follow-up, he made a full recovery.

Conclusion:

Intralesional C. albicans antigen injection in digital cutaneous warts may cause an exaggerated immune response resulting in partial necrosis of the finger pulp. The clinical presentation may be difficult to distinguish from coexisting infection, but in some cases, observation may be an appropriate course of action.
A career research module promotes career exploration and understanding of the labour market and transferable skills
Authors: Julien Brianna , Lexis Louise , Church Jarrod
Published: March 2023

Students, the public, and government expect university graduates to find meaningful employment and contribute to the economic and social prosperity of society. Universities have a responsibility to support students to develop their career management skills. An assessed career research module was embedded into a second-year human physiology subject taken by students in health-science related undergraduate STEM degrees. Students conducted research on the logistics of entering their preferred career, the Australian labour market for this career, and the transferable skills and personal attributes required. They communicated their learnings in a video and completed reflection activities comprised of Likert-scale and open-ended questions. The aims of this study were to determine students’: 1) ability to research the logistics of entering their preferred career and the labour market; 2) perceptions of the most important skills and attributes for their preferred career, and development of these; 3) perceptions of module activities and career planning, and perceived career management skills. To address the aims of the study, 265 student videos and reflection activities were analysed. Results indicate that the module supported students in gaining career management skills that were a focus of the curriculum. Most students identified their current university course as the main way they were developing important skills and attributes, with their course, volunteering and further study the main ways they planned to continue skill and attribute development. In conclusion, a career research module is an effective career development tool for students in a range of undergraduate courses.
STEM students see the value of LinkedIn as a career development tool and continue to use it in the long-term post-assignment
Authors: Lexis Louise , Weaver Debbi , Julien Brianna
Published: March 2023

Some empirical case studies provide support for using LinkedIn as a 21st century career development tool; however, little is known about the long-term impact on students’ use of LinkedIn. A LinkedIn assignment was implemented in a third-year subject taken by students in non-specialist science, technology, engineering and mathematics (STEM) degrees. The study aimed to determine: 1) Student use of LinkedIn prior to, and during the four months after the assignment was completed; 2) Student intentions to use LinkedIn as a career development tool in the long-term future; 3) Student perceptions of a LinkedIn assignment and associated employability skills; 4) Changes to students’ LinkedIn profiles and professional connections in the two years following completion of the assignment. Four months after the assignment, students completed an anonymous and voluntary questionnaire comprised of open-ended and Likert-scale questions. Descriptive statistical analysis was conducted on the Likert-scale responses and content analysis was conducted on the open-ended responses. Students’ LinkedIn profiles were analysed upon completion of the assignment and two years post-assignment to determine changes during this time. Students saw value in the assignment and LinkedIn as a career development tool, and many thought they had developed skills in building a connected identity and social network literacy. Students were less confident in their ability to build and engage with professional networks, although they thought this was important. Most students continued to use LinkedIn in the two years post-assignment. In conclusion, a LinkedIn assignment is an effective career development tool for students in non-specialist STEM degrees.
Causa versus efeito. Do que se trata?
Authors: Martins Oliva , Marques Henrique , Marques Ana , Coelho Ana
Published: March 2023

A relação dos indicadores com o respectivo construto pode ser considerada de causa ou efeito. Considerando que o construto possa ser definido como formativo ou reflexivo, dependendo da análise teórica que antecede a análise estatística dos dados, torna-se fulcral compreender este processo. A importância desta conceitualização teórica é justificada pelas implicações na definição e análise do modelo estrutural. Neste sentido, definiu-se dois objetivos para este artigo: i) através de uma revisão da literatura, apresentar como se desenvolve um processo de validação teórica dos construtos no âmbito da modelagem de equações estruturais; e ii) desenvolver uma aplicação prática do processo a um modelo estrutural do comportamento do aleitamento materno no âmbito do marketing social. Foram ainda considerados os seguintes pressupostos: i) a intenção precede o comportamento voluntário; ii) a intenção é cognitiva; iii) a intenção é influenciada por vários fatores, o que permite ser avaliada por diferentes modelos, em função do contexto, o que quer dizer que a definição teórica deve ser o mais assertiva possível. Por fim, ressaltar a dificuldade de encontrar um único modelo para ser aplicado a todos os comportamentos.
Oil Production and CCUS Potential in La Luna Shale in Colombia
Authors: Herrera Tellez Claudia Marcela , Fragoso Alfonso , Aguilera Roberto
Published: March 2023

La Luna Shale in Colombia is the main source rock in the Middle Magdalena Valley (MMV) and the Catatumbo Basins. La Luna shale is a high-quality source rock and its potential has been investigated by several authors. This paper presents geological, geochemical, and petrophysical description of La Luna shale with the dual objective of (1) utilizing CO2 for improving oil recovery through Huff-n-Puff (HnP) gas injection, and (2) storing CO2 safely and without leaks.

The overall approach includes verifying that geologic fluid containment exists in the shale reservoir. The present work shows that this is indeed the case in La Luna shale. Geologic containment is valuable as it permits maximizing oil recovery from La Luna shale and safe storage of CO2 with negligible possibilities of fluid leakage, thus providing a valuable contribution to solve problems related to climate change. Consequently, the procedure described in this paper conforms well to CCUS: Carbon capture, utilization and storage of CO2.

The Eagle Ford shale in Texas is a good analog of La Luna shale. In both reservoirs, sedimentation and development of the source rock start at about the same time in the late Cretaceous, about 93 million years ago. It is not surprising then that in both Eagle Ford and La Luna shales, oil, condensate and natural gas are in the same location where they were generated, gas is at the bottom, condensate in the middle and crude oil at the top of the structure. Thus, the hydrocarbon fluids have been upside down or inverted position through millions of years. This constitutes geologic containment.

The paper describes the following activities once geologic containment is established: (1) drill a pilot horizontal well (HW), (2) stimulate the HW with multi-stage hydraulic fractures and investigate the environmental impact (if the pilot is successful, drill another pilot(s)), (3) produce oil by primary means for a maximum of 2-3 years, (4) implement HnP CO2 injection, (5) store the CO2 in the shale reservoir once the HnP reaches economic limit. Regular pressure monitoring throughout the life of the HnP project guarantees the lack of leaks, a major concern when CO2 is stored in other types of depleted reservoirs or aquifers.

The novelty of the paper is demonstrating geologic containment in La Luna shale in both the MMV and Catatumbo Basins of Colombia. This provides the basis for implementing CCUS. The geological, geochemical and petrophysical description allow to construct a simulation model to investigate primary recovery as well as EOR by HnP CO2 injection. CO2 can be stored safely, without leaks, in the shale reservoir once the HnP project reaches economic limit.