bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Optimization of a Reconfigurable Wheel-Tracked Mobile Robot
Authors: Wang Jiaxuan , Liu Cheng , Wei Wei , Yan Qingdong
Published: January 2024

The reconfigurable wheel-track locomotion system integrates wheels and tracks to improve the efficiency and maneuverability of the vehicle. It can dynamically switch between the two locomotion modes based on road conditions, greatly enhancing the vehicle’s adaptability to the environment. Therefore, it has become a hot topic in special ground mobile platforms. This paper first proposes a distributed driving mobile platform. Based on the equivalent reconfiguration principle, a reconfigurable wheel-tracked locomotion system is designed which can transit between wheel mode, half-tracked mode and full-tracked mode. Then the basic structure of its mechanism, reconfiguration principle, and a method for track design are discussed. To minimize the required force capability of the electric actuator of the deformation mechanism, an optimization model for the hinge joint location of the actuator is established considering structure constraints. A Nonlinear programming by quadratic Lagrangian (NLPQL) was adopted to solve the constrained optimization problem. A finite element method (FEM) model was then established to verify the accuracy of the theoretical model. The results indicate that the relative error of actuating force between the theoretical model and the simulation is 13.5%. The optimized actuation mechanism can fulfill the reconfiguration function of the mobile platform. Finally, the mobile robot was built according to the optimization results and an experiment was carried out to test the pivot turning and mode transition functions of the robot. The robot was able to transit between the three modes while it’s in motion, which reveals the feasibility of the reconfigurable system and verifies the optimization model.
Machining-Oriented Contact Analysis Based on the Modeling of the RV Cycloid Planetary Reducer
Authors: Yang Lei , Luo Yu , Luo Yanlei , Du Wei , Zheng Xiang , Li Ya
Published: January 2024

A RV cycloid planetary reducer used in the excavator chassis is studied. A contact model based on impulse function is proposed to define the constraint between the contact parts during the working condition. The contact parameters in the contact model includes: Contact stiffness, index of force, damped coefficient and depth of penetration. Among them the unique undetermined one is contact stiffness, which is studied under two working conditions. These conditions are Convex-Convex Contact (pin-top of cycloid) and Convex-Concave Contact (pin-dedendum of cycloid). Analysis of the contact parameters indicates that the contact stiffness is affected by the contact thickness. The performance of the reducer part material must satisfy these parameters. Then a dynamic model of the RV cycloid planetary reducer is built, in which the contact force model is utilized to realize the constraint of pin-cycloid wheel, planetary wheel-sun wheel. The simulate results of idle load and full load indicate that the deviation of output draft angular velocity between simulation and theoretical is 0.83%. The work envelope of the center of the cycloid mass is a circle, and the circle radius is eccentric distance of the two cycloids. The simulation of contact moment between the pins and cycloid reveals only six contacts exist at any instant, and the maximum moment appears at the middle contact pair. This contact constraint model can be used to direct the machining of the wheels and the process of reducer assembly.
Application of Machine Learning Approach for Controlling the Vehicle Isolation System
Authors: Nguyen Vanliem , Le Vanquynh
Published: January 2024

This investigation proposes a machine learning approach (MLA) to control the isolation system of the vehicle. Based on a dynamic model of the vehicle under the excitation of the random road surface, a random road database built on ISO 8068 (1995) from levels A to D under different speeds of the vehicle is then used as input data for the coaching process to train control rules in MLA and control the damping force in vehicle’s isolation system. The root mean square value of the vehicle acceleration (awb) and deformation of the isolation system (xwz) are used for evaluating MLA’s control efficiency. The simulation result indicates that MLA has superior isolation efficiency compared to using fuzzy logic control or without control. Especially, both awb and xwz with MLA are strongly reduced by 24.5% and 6.6% in comparison to the fuzzy logic control, by 43.4% and 37.1% compared to the passive isolation system. Thus, MLA should be developed and applied to the vehicle isolation system to further enhance the vehicle’s ride comfort.
Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4
Authors: Dhouib Souhail
Published: January 2024

Planning the shortest path for a mobile robot is a hard task. It consists in quickly finding the shortest distance from the starting to the target positions with obstacles collision-free. The performance of the robot mobile will be increased if the optimal shortest path is rapidly planned. Therefore, in this paper the novel optimal method entitled Dhouib-Matrix-SPP (DM-SPP) is enhanced for this problem with four movement directions (namely DM-SPP-4) for an environment represented as a grid map with fixed obstacles. The simulation results on several 41x41 grid maps and the comparison of DM-SPP-4 to different methods (Basic Dijkstra, Modified Dijkstra, Basic A*, Modified A*, Best First Search Algorithm, Breadth First Search, Depth First Search algorithms) show that DM-SPP-4 can realize the path planning more rapidly and accuracy.
Design of a Robotic Vehicle to Avoid Obstacle Using Arduino Microcontroller and Ultrasonic Sensor
Authors: Goswami Shankha Shubhra , Sahoo Sushil Kumar
Published: January 2024

This project depicts an obstacle-evasion robot vehicle restricted by an ultrasonic sensor. The Arduino microcontroller drives the robot prototype car, which employs an ultrasonic sensor for obstacle detection. This sensor is mounted on the vehicle’s front and two sides. The sensor receives data from the robot’s attached sensors once the encircling zone begins. The sensor detects the impediment and proceeds to choose an impediment-free path. The sensor will convey the command to the controller and is distinguished from the controller by selecting the appropriate motion for the robot wheel. The vehicle wheel’s advancement and direction will now be determined by the identification of the ultrasonic sensor and the use of a wheel encoder. This vehicle is used to detect obstructions and avoid their effects.
Plate Visual Recognition Technology of Restaurant Service Robot
Authors: Li Shengqian , Zhang Xiaofan
Published: January 2024

According to visual restaurant service robot application environment under the condition of uneven light and changeful, light and shade and occlusion, make the RGB image noise influence is very big which was collected by the binocular vision, difficult to use conventional image processing method for accurate identification of plate, the plate image is analyzed the characteristics and the traditional image processing technology, a adaptive edge of ellipse fitting method was proposed in this paper. Firstly, the image of dinner plate was preprocessed, and then the image edge information was extracted. Finally, according to the edge information, the dinner plate was identified by fitting ellipse with Hough transform. The experimental results show that under the circumstance of different light and shade in most restaurants, the ellipse feature of the edge of the plate can be accurately extracted by using this method, and the plate can be recognized, the validity of the method was verified.
Active Obstacle Avoidance Method for Robot Based on Deep Visual Perception
Authors: Sun Lixin , Chen Chong , Wang Qi , Geng Qinglin , Zhang Minglu
Published: January 2024

In order to improve the safety of human-machine collaboration of manipulators in complex dynamic environments, an active obstacle avoidance method for manipulators based on depth visual perception was proposed. The depth camera acquired the environmental 3D point cloud information and calculated the nearest distance from the dynamic obstacle to the robotic skeleton model in real time for collision detection. In terms of real-time path planning, an improved artificial potential field-rapid search random tree (APF-RRT) algorithm was proposed. A targeting mechanism was introduced for the local minima problem to speed up the path exploration. Finally, algorithm validation and real-machine dynamic obstacle avoidance experiments were carried out on the ROS system and robot. The experiments results confirm the effectiveness and real-time performance of the proposed robot active obstacle avoidance method.
Research and Design of a Precision Current Source Based on ARM
Authors: Xie Yunxi , Chen Li
Published: January 2024

Because the voltage is affected by the load of the component and the resistance of the field harness, there is a voltage drop loss, resulting in inaccurate terminal data. Measurement and control generally need to measure all kinds of non-electrical physical quantities, such as temperature, pressure, speed, Angle, etc., need to be converted into analog current signals to be transmitted to the control room or display equipment hundreds of meters away, the most widely used in industry is to use 4 ∼ 20mA current to transmit analog quantities. However, in engineering use, such as the outgoing signal used by sensors and the ADC acquisition signal need accurate current signals. In order to solve the problem of precision current source output, a precision 4∼20mA signal output is designed. An ARM-based MCU system is designed to generate an adjustable duty cycle combined GP8301 current chip. The inverse current channel parameters and PWM channel parameters are designed by using fitting algorithm and compensation algorithm. The algorithm is designed by Matlab to generate the parameters of the fitting curve, and the parameters are determined based on the principle of minimum variance. The design accuracy of the current source is one thousandth of the range, and the minimum resolution is 0.02mA. Compared with the current output value of the direct chip, the accuracy is higher, the accuracy is higher, and the linearity of each segment is better.
Parameter Optimization of Passive Suspension Based on MATLAB Simulation
Authors: Deng Mengqi , Gao Zengfa , Xu Chao , Ju Wenhang , Deng Baoqing
Published: January 2024

With the development of the automobile industry and economy, the automobile penetration rate is increasing. Most people are more concerned about the driving comfort of a vehicle, and the quality of suspension system directly affects the stability of a car. Although active suspension offers better control, its complexity and high cost limit its use to premium cars. And most regular saloons, the mainstay of the market, employ passive suspension. Therefore, the optimisation of passive suspensions remains important and marketable. In this paper, Matlab/Simulink is used to model the suspension as it relates to road inputs and the vertical vibration of a 1/4 vehicle with a dual mass. A three-factor, four-level orthogonal test was carried out on various models and road surfaces. The damping coefficient of the shock absorber, spring stiffness, and tyre stiffness were predicted by plotting line graphs, observing the pattern, and carrying out ANOVA using statistic package for social science (SPSS). The simulation results demonstrate that, while maintaining the stability of the suspension structure, a large damping coefficient, as well as small tyre and spring stiffness, effectively reduces the root mean square (RMS) value of body acceleration, suspension dynamic deflection, and RMS value of wheel dynamic load. This achieves a smooth and safe ride. Finally, it has been confirmed through a real vehicle test that reduced stiffness in the small tyre effectively lowers the body acceleration.
Distributed Network Improvement for Efficient Data Aggregation in Consensus-Based Sensor Networks
Authors: Cao Haosen , Sun Siqing , Zhang Hai-Tao
Published: January 2024

In the sensor networks considered in this paper, the topology of agents aggregating neighbors’ data can be locally adjusted by each entity. In the sense of Fiedler value of network, this proper topological adjustment is easy to deploy and greatly benefits the increase of convergence rate in the tasks such as target localization, parameter estimation and data fusion. To this end, a distributed topology-based sensor consensus acceleration algorithm is proposed. By distributed estimating the eigenspaces of Laplacian matrix, this algorithm provides a direction for each sensor adjusting their aggregation weights, such that the Fiedler value is optimized towards a local maxima. Moreover, this method can also tackle the repeated eigenvalues and non-unique Fielder values. A numerical example is also provided to demonstrate the effectiveness of the proposed distributed strategy.
Research of Ship Nesting Based on Maximum Residual Rectangle Strategy Integrated Improved Genetic Algorithm
Authors: Wang Yunlong , Zhang Pengxiang , Gu Yujie , Zhang Xin , Jin Chaoguang , Chen Ming
Published: January 2024

In this paper, a maximum residual rectangle genetic (MRRG) algorithm based on multi-heuristic strategies is proposed, which combines the advantages of heuristic algorithm and intelligent optimization algorithm to improve the material utilization and stability of the solution. In this method, the optimal local solution is obtained by constructing the maximum residual rectangle (MRR) algorithm based on the heuristic algorithm firstly, and the free rectangle area table update method of MRR algorithm is put forward. Secondly, in order to further improve the diversity of solutions, five heuristic strategies which are bottom-left strategy, minimum area difference strategy, minimum short side strategy, minimum long side strategy and maximum contact perimeter strategy are proposed for the MRR algorithm. Lastly, the global solution is calculated by the improved genetic algorithm, in which the five solutions obtained by heuristic MRR algorithm are used as initial solutions. The test results show that the material utilization can be increased from 91.5% to 95.9%, and further to 97.5%, which verifies the feasibility and effectiveness of the proposed algorithm.
An End-to-End Haptic Adjective Recognition Method with Self-Attention Mechanism
Authors: Zhang Yuanpei , Zou Zhuojun , Shu Lin , Hao Jie
Published: January 2024

Human’s ability to describe the tactile sensation of objects has piqued the interest of numerous researchers seeking to augment the dexterity of robots in delicate tasks. However, most existing approaches are limited by their two-stage framework, resulting in low inference efficiency and unsatisfactory performance. To address this challenge, we propose the first end-to-end framework for haptic adjective classification. Specifically, our framework leverages the Space Encoding Module to capture long-term dependencies, and the Order Encoding Module to learn order information explicitly. We conduct experiments on the public PHAC-2 Dataset and the result shows that our method achieves F1 score of 0.759, outperforming previous work in a significant way.
Design and Research of Intelligent Charging Cabinet for Mobile Operations
Authors: Ma Jun , Wang Peng , Qin Wei
Published: January 2024

Under the background of electric power digitization construction, mobile phone back clip operation terminal has been widely used in electric power marketing mobile operations. Aiming at the problems of the traditional terminal charging cabinet, such as low working efficiency, backward management mode and poor equipment status perception ability, this paper puts forward a design scheme of intelligent charging cabinet serving the mobile operation of power marketing, and introduces the overall structure, main technical parameters, software and hardware design of the charging cabinet. The practical application shows that the intelligent charging cabinet can realize the efficient management and real-time monitoring of the mobile terminal equipment, and help to improve the intelligent level of the mobile role of power marketing.
Wind Power Virtual Inertia Frequency Modulation Control Based on Intelligent Swarm Auto-Disturbance Rejection
Authors: Li Tai , Li Mengjie , Yao Chunlin , Ji Zhicheng
Published: January 2024

This paper proposes a wind power virtual inertia control strategy based on the intelligent bee colony active disturbance rejection controller (ABC-ADRC). The proposed control method aims to improve the anti-interference capability of the virtual inertia control system and solve the challenge of tuning the parameters of the active disturbance rejection control (ADRC).The control strategy is developed based on the system frequency dynamic response equation. An active disturbance rejection controller is designed using a nonlinear feedback control law and an extended state observer. This controller aims to enhance the system’s ability to reject disturbances. However, tuning the parameters of the ADRC can be difficult. To address this issue, an ABC algorithm based on nectar collection behavior is proposed to iteratively optimize the ADRC parameters. The proposed control method is verified through simulations using Matlab/Simulink. The results demonstrate that the ABC-ADRC control strategy is more effective compared to traditional algorithms. It successfully controls the rotor speed to adjust the frequency of the power grid system, achieves power sharing, and eliminates adaptive noise. Furthermore, this method reduces the complexity of parameter settings, improves anti-interference ability, and enhances the robustness of the system.
A Slot-Integrated Microstrip Antenna Design for High-Performance Communication Systems, and Wireless Sensing Application
Authors: Kee Joel , Mokayef Mastaneh , Summakieh MHD Amen , Khan M.K.A. Ahamed , Tiang Sew Sun
Published: January 2024

This article introduces a new antenna design and analysis that operates at a frequency of 13.49 GHz. The antenna is specifically created to meet the increasing demand for high-performance communication systems, and wireless sensing and imaging within the 13.49 GHz frequency range. The design process involves careful consideration of important parameters, including antenna size, gain, directivity, impedance matching, and radiation pattern. The proposed antenna exhibits outstanding performance characteristics, such as improved gain, enhanced beamwidth, and efficient signal transmission and reception. Thorough simulations and measurements are conducted to evaluate the antenna’s performance metrics, confirming its suitability for various applications within the 13.49 GHz frequency band. The design and simulation of the antenna are done through CST Studio Suite software. The antenna design contains a slot in the patch and its performance has been tested through its reflection coefficient, VSWR, and far-field.
Ice-Melting Technology Application of Optical Fiber Composite Overhead Ground Wires (OPGW)
Authors: Xu Kehang , Zhang Ye , Chen Zeming
Published: January 2024

The research on the icing disaster treatment of transmission line has been carried out widely,since the large-scale ice and snow disaster happened in our country in 2008. And some feasible methods formed have been applied in the phase conductor of transmission line, for the ground wire ice-melting, which has been a difficult problem. In order to solve the problem of OPGW icing, this paper adopted the technology method based on non-insulating modification to realize OPGW ice-melting, and verified the ice-melting effects by the actual application and field test.
Forked Finger Electrode Based Acquisition Circuit and Humidity Correlation Model Design
Authors: Li Qilin , Yan Ping , Ding Zhuoyue , Cai Junyi , Chen Bingliang , Ye Run
Published: January 2024

With the continuous development of industry, humidity sensors have long been used in many fields such as industrial and agricultural production, public meteorological services, and medical fields. Humidity is a very important environmental parameter that has an impact on production, health and comfort in many fields. Conventional humidity sensors usually use capacitive or resistive measurement principles, which are not very sensitive and accurate to meet the needs of certain high precision and high sensitivity measurements. In addition, high-precision and high-sensitivity humidity sensors are usually expensive, which limits their use in certain applications. First, this paper designs a humidity acquisition hardware circuit based on forked-finger electrodes by taking advantage of their high sensitivity. Second, the data tested by the constant humidity chamber method and the saturated solution method are compared to select a suitable method for the humidity testing environment. Finally, the humidity correlation model design was carried out based on the least squares method. Thus, the humidity sensor based on the forked finger electrode obtained by the design can test the humidity in the environment easily and quickly, and the correlation model of the relative humidity-forked finger electrode capacitance value is obtained at the same time. By evaluating the model and calculating the error between the theoretical capacitance value and the actual capacitance value, it can be concluded that the model is a more reliable model within the error range without overfitting and underfitting problems. In turn, the problem of low sensitivity and high cost of the current humidity sensor can be well solved, providing a basis for relevant academic research and practical applications.
A randomized controlled trial investigating the impact of a single flash cupping session on patients with chronic lower back pain using multichannel surface electromyographic assessment
Authors: Wang Li , Huang Bing-Yao , Xie Xiao-Min , Sang Di , Tan Tian-Hui , Li Guang-Lin , Cao Xue-Mei , Jiang Nai-Fu
Published: January 2024

BACKGROUND: Chronic lower back pain (CLBP) is one of the most common disorders worldwide. Flash cupping has the ability to relieve CLBP; nevertheless, its impact on CLBP and the likely mechanism of action have not been studied. OBJECTIVE: The goal of this study was to assess the impact of a single, brief cupping session on CLBP and low back muscle activity using multichannel surface electromyography (sEMG). METHODS: In this randomized controlled trial, 24 patients with CLBP were enrolled and randomly assigned to the control group (treated by acupuncture) and cupping group (treated by acupuncture and flash cupping). Acupuncture was applied on the shen shu (BL23), dachang shu (BL25), and wei zhong (BL40) acupoints in both the groups. A brief cupping treatment was applied to the shen shu (BL23), qihai shu (BL24), dachang shu (BL25), guanyuan shu (BL26), and xiaochang shu (BL27) acupoints on both sides of the lower back in the cupping group. The numeric rating scale (NRS) was used to assess therapy efficacy for lower back pain (LBP) before and after treatment. Surface EMG data collected during symmetrical trunk flexion-extension movements were utilized to measure lower back muscle activity and the effectiveness of LBP therapy. RESULTS: There was no statistically significant difference (P= 0.63) in pain intensity between the two groups before and after treatment. There was a statistically significant difference (P= 0.04) between the control group and the cupping group in the sEMG topographic map parameter CoGx-To-Midline. CONCLUSION: This study established a connection between the action mechanism of flash cupping and enhanced horizontal synchronization of lower back muscular activity.
Efficacy of ozone injections for reducing musculoskeletal pain in comparison with corticosteroid injections: A systematic review and meta-analysis
Authors: Arias-Vázquez Pedro Iván , Guzzardo Mauro Nicolás , Guzzardo Duilio Román , Castillo-Avila Rosa Giannina , Tovilla-Zárate Carlos Alfonso , Ake Montiel Miguel Angel Nazul
Published: January 2024

BACKGROUND: Corticosteroid injections are frequently used in the short-term treatment of musculoskeletal pain, but their use is controversial as repeated exposures to corticosteroids can lead to deleterious effects on musculoskeletal tissue. Ozone injections have been proposed as a possible treatment for musculoskeletal pain; however, their effectiveness has not been compared with corticosteroids. OBJECTIVE: To evaluate the effectiveness of ozone injections for reducing pain in individuals with musculoskeletal pain in comparison with corticosteroid injections through a meta-analysis. METHODS: An online systematic search was performed using electronic databases up to September 2023. We searched for studies that compared corticosteroid injections with ozone injections in the treatment of musculoskeletal pain of diverse origins. RESULTS: Eleven studies were included comprising a total of 534 individuals. In the overall pooled analysis, a pain reduction in favor of corticosteroid injections was found in the short term (d= 0.31, 95% CI 0.01 to 0.60, p (z) 0.04, I2 = 32%). In the medium term, no significant differences were found in reducing pain between groups (d=-0.17, 95% CI -0.42 to 0.07, p (z) 0.15, I2 = 0%). CONCLUSIONS: Our results suggest that corticosteroids injections are more effective in reducing musculoskeletal pain in the short term, but equally effective in the medium term when compared with ozone injections. Nonetheless, better-quality clinical trials are necessary to corroborate these results.
Joint position sense error in the hip and knee without reference to the joint angle
Authors: Lim Wootaek
Published: January 2024

BACKGROUND: Joint position reproduction measures the angle acuity of reference angle reproduction using an indicator angle. However, reference angles are often not available. OBJECTIVE: This study aimed to examine joint position sense at three different targeted joint angles, which were estimated from the maximum range of motion (maxROM) without a reference angle at each targeted joint angle. METHODS: The maxROM was measured in straight leg raise (SLR) and active knee extension (AKE) positions. In both positions, a targeted joint angle at 75% of the maxROM was assessed first, followed by that at 50% and 25% of the maxROM. A one-sample t-test was used to analyze differences between the targeted and reproduced angles in both positions. RESULTS: All reproduced angles significantly differed from the targeted angle in both SLR and AKE positions except for the reproduced angle measured at 75% maxROM. Overall, position errors in the AKE position were higher than those in the SLR position. CONCLUSIONS: Estimating the angle based on the maxROM without a matched reference angle may lead to significant discrepancies in comparison with the targeted joint angle. In clinical settings, if accurate reproduction of motions is required to improve proprioception, providing a reference angle might be helpful.
Dementia in the Ancient Greco-Roman World Was Minimally Mentioned
Authors: Finch Caleb E. , Burstein Stanley M.
Published: January 2024

Background:

The possibility that Alzheimer’s disease and related dementias (ADRD) is a modern disease arises from the minimal mention of advanced cognitive decline by ancient Greeks and Romans, who were mainly concerned with the physical frailties of older ages.

Objective:

Because standard medical histories of elderly health lacked mention of cognitive decline, we examined texts by Greek and Roman authors that mentioned memory loss and dementia.

Methods:

Primary texts of Greco-Roman authors, 8th century BCE into the 3rd century CE, that mentioned cognitive decline were identified and critically evaluated. Secondary sources were excluded.

Results:

No ancient account of cognitive loss is equivalent to modern clinical data. The term dementia was occasionally used in antiquity, but not invariably linked to old age. Ancient Greeks and Romans expected intellectual competence beyond age 60. While some memory loss was acknowledged, we found only four accounts of severe cognitive loss that might represent ADRD. The possibility of modest ADRD prevalence in ancient Greece and Rome is consistent with its low prevalence in the Tsimane of Bolivia. These contemporary Amerindians live under conditions of high mortality from frequent infections and minimal cardiovascular disease with physically demanding lives. Tsimane after age 60 had increased mild cognitive impairment; the few cases of dementia were not clinically consistent with AD.

Conclusions:

The modern ‘epidemic level’ of advanced dementias was not described among ancient Greco-Roman elderly. The possible emergence of advanced ADRD in the Roman era may be associated with environmental factors of air pollution and increased exposure to lead. Further historical analysis may formulate critical hypotheses about the modernity of high ADRD prevalence.
RETRACTED: Geometric-arithmetic mean inequality for q-rung orthopair fuzzy Hamacher aggregations
Authors: Du Wen Sheng
Published: January 2024

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Object-oriented concept acquisition based on attribute topology
Authors: Pang Kuo , Lu Yifan , Xu Lixian , Yan Wei , Zou Li , Lu Mingyu
Published: January 2024

The research of object-oriented concept is one of the basic contents of formal concept analysis. To overcome the complexity of computing object-oriented concept, this paper proposes an Object-oriented Concept Acquisition model (OCA) based on attribute topology. The object-oriented attribute topology is first proposed to visualize the coupling relationship between attributes. Second, inspired by rough set theory, object-oriented attribute topology is transformed into rough object-oriented attribute topology. Furthermore, based on the weights of the edges in the rough object-oriented attribute topology, object-oriented concepts are obtained by finding reachable paths. Finally, examples and experiments are used to demonstrate the effectiveness of our proposed method.
Intelligent decision support system for pulmonary tuberculosis detection using bipolar fuzzy utility matrix and bipolar Mamdani fuzzy inference system
Authors: Natarajan Ezhilarasan , Augustin Felix
Published: January 2024

Tuberculosis (TB) stands as the second leading global infectious cause of death, following closely behind the impact of COVID-19. The standard approach to diagnose TB involves skin tests, but these tests can yield inaccurate results due to limited access to healthcare and insufficient diagnostic resources. To enhance diagnostic accuracy, this study introduces a novel approach employing a Bipolar Fuzzy Utility Matrix Inference System (BFUMIS) and a Bipolar Mamdani Fuzzy Inference System (BMFIS) to assess TB disease levels. By considering factors associated with the causation of TB, the study devises suitable membership functions for bipolar fuzzy sets (BFS) using both triangular and trapezoidal fuzzy numbers. Using a point factor scale, the study clusters the rules systematically and assesses the level of uncertainty within these grouped rules by utilizing bipolar triangular fuzzy numbers (BTFN). To handle the BTFN, this study proposes converting bipolar triangular fuzzy into bipolar crisp score (CBTFBCS) algorithm as a defuzzification method. The optimal bipolar fuzzy utility sets (BFUS) are determined from the bipolar fuzzy utility matrix to identify patients’ TB disease levels. These sets play a pivotal role in characterizing the severity of TB disease levels in patients. Additionally, rigorous validation of the utility framework is accomplished through measures of bipolar fuzzy satisfactory factors and sensitivity analyses. Furthermore, the study introduces the BMFIS, which presents a novel perspective on the conventional fuzzy inference system. This innovative system integrates the Mamdani fuzzy inference system (MFIS) into a bipolar fuzzy context, enriching the diagnostic process with enhanced insights. To demonstrate the efficacy of the proposed methods, extensive validation is carried out using actual clinical data. The performance metrics used in this validation effectively demonstrate the superiority of the proposed approach.
Handling syntactic difference in Chinese-Vietnamese neural machine translation
Authors: Yu Zhiqiang , Wang Ting , Liu Shihu , Tan Xuewen
Published: January 2024

As the typical distant language pair, Chinese and Vietnamese vary widely in syntactic structure, which significantly influences the performance of Chinese-Vietnamese machine translation. To address this problem, we present a simple approach with a pre-reordering model for closing syntactic gaps of the Chinese-Vietnamese language pair. Specifically, we first propose an algorithm for recognizing the modifier inverse, one of the most representative syntactic different in Chinese-Vietnamese language pair. Then we pre-train a pre-reordering model based on the former recognition algorithm and incorporate it into the attention-based translation framework for syntactic different reordering. We conduct empirical studies on Chinese-Vietnamese neural machine translation task, the results show that our approach achieves average improvement of 2.75 BLEU points in translation quality over the baseline model. In addition, the translation fluency can be significantly improved by over 2.44 RIBES points.
A probability-exponential method of converting Z-numbers and its systematic applications in multi-attribute decision making
Authors: Sun Hong , Zhang Xianyong
Published: January 2024

Z-numbers contain fuzzy restrictions, credibility measures, and probability distributions to effectively represent uncertain information. Converting Z-numbers to fuzzy numbers facilitates extensive applications (such as multi-attribute decision-making (MADM)), thus becoming valuable for research purposes. Regarding Z-number conversions, the original method never considers the association probability, while probabilistic strategies offer better informatization. Recently, a probability-driven conversion starts with a linear transformation of the centroid difference between the fuzzy restriction and probabilistic distribution. However, it has the invalidation weakness of edge information due to underlying non-normalization. To improve this probability-linear conversion, a Z-number conversion is proposed by using underlying probability-exponential descriptions, and this new method is further applied to MADM. At first, the current probability-linear conversion is analyzed based on the initial non-probabilistic conversion, and its intrinsic weakness and correctional improvement are revealed. Then, the novel probability-exponential conversion resorts to an exponential characterization of centroid difference between the restriction and distribution, and it gains information enrichment due to underlying normalization. The refined method preserves the inherent characteristics of Z-numbers more effectively, facilitating their application in subsequent engineering practices. This is especially pertinent in decision-making systems based on expert input and initial value problems. The proposed method for converting Z-numbers aims to minimize information loss in transitions between Z-numbers and classical fuzzy numbers. This approach will be further explored in future research. Furthermore, the probability-exponential conversion induces an ExpTODIM algorithm for MADM, called PE-ExpTODIM. Three Z-number conversions (i.e., the non-probabilistic, probability-linear, and probability-exponential types) and three decision algorithms (i.e., ExpTODIM, EDAS, MOORA) are combined to establish a 3 × 3 framework of Z-number-driven MADM. Finally, the systematical 9 algorithms are applied to the problem of site selection of carbon storage. They are validated by criss-cross contrast analyses and statistical significance tests. Thus, PE-ExpTODIM exhibits the desired optimization. The last technology of statistical testing is original, ingenious, and valuable for MADM.
The COVID-19 pandemic’s influence on employment outcomes of veterans enrolled in VA healthcare vocational rehabilitation
Authors: Sprong Matthew E. , Blankenberger Bob , Pierce Sami M. , Hollender Heaven
Published: January 2024

BACKGROUND: Employment has been shown to be the fourth most commonly reported need for veterans and their families, and unemployment rates have ranged from 1–69% dependent on the mental health diagnosis. Complications from the COVID-19 pandemic have had a significant impact on psychological functioning, and social isolation has led to increased psychiatric symptoms. Vocational rehabilitation is an intervention provided to Veterans in an attempt to remove barriers to employment while also increasing involvement in gainful work activity. OBJECTIVE: The purpose of the current study was to examine the impact that COVID-19 has had on employment rates at discharge for veterans with mental health disorders participating in a VHA vocational rehabilitation program. METHODS: An outcome-based, summative program evaluation design was used to assess the quality of Veterans served (2016-2021) at a vocational rehabilitation program served at a medical center located in VISN 12 of the U.S. Department of Veteran Affairs. RESULTS: Findings showed that veterans with Bipolar and Psychosis were less likely to discharge with employment (not considering COVID-19). CONCLUSION: No significant meaningful differences existed in employment rates when comparing pre/post March 2020 (official start of COVID-19 pandemic) for veterans with psychiatric diagnoses.
The RDF2vec family of knowledge graph embedding methods
Authors: Portisch Jan , Paulheim Heiko
Published: January 2024

Knowledge graph embeddings represent a group of machine learning techniques which project entities and relations of a knowledge graph to continuous vector spaces. RDF2vec is a scalable embedding approach rooted in the combination of random walks with a language model. It has been successfully used in various applications. Recently, multiple variants to the RDF2vec approach have been proposed, introducing variations both on the walk generation and on the language modeling side. The combination of those different approaches has lead to an increasing family of RDF2vec variants. In this paper, we evaluate a total of twelve RDF2vec variants on a comprehensive set of benchmark models, and compare them to seven existing knowledge graph embedding methods from the family of link prediction approaches. Besides the established GEval benchmark introducing various downstream machine learning tasks on the DBpedia knowledge graph, we also use the new DLCC (Description Logic Class Constructors) benchmark consisting of two gold standards, one based on DBpedia, and one based on synthetically generated graphs. The latter allows for analyzing which ontological patterns in a knowledge graph can actually be learned by different embedding. With this evaluation, we observe that certain tailored RDF2vec variants can lead to improved performance on different downstream tasks, given the nature of the underlying problem, and that they, in particular, have a different behavior in modeling similarity and relatedness. The findings can be used to provide guidance in selecting a particular RDF2vec method for a given task.
Relevansi Kesadaran Global terhadap Produk Halal Hubungannya dengan Perilaku Ekonomi Masyarakat Indonesia di Era Revolusi Industri 4.0
Authors: Ahyani Hisam , Putra Haris Maiza , Muharir Muharir , Mutmainah Naeli , Prakasa Armelia
Published: January 2024

Kesadaran Global terhadap Produk Halal Hubungannya dengan Perilaku Ekonomi Masyarakat Indonesia di Era Revolusi Industri 4.0, dewasa ini sudah menjadi tuntutan zaman yang penyebabnya yakni adanya peluang besar eksis dan berkembangnya industry halal (ekonomi syariah) di Indonesia. Dimana yang menjadi indicator kesadaran produk halal di indonesia adalah perilaku konsumen atau masyarakat non muslim dalam mengkonsumsi produk-produk halal. Penelitian kepustakaan ini diperoleh dari berbagai sumber primer dan sekunder dari berbagai literasi seperti buku, jurnal dan internet. Hasil penelitian membuktikan bahwa relevansi kesadaran global terhadap produk halal hubungannya dengan perilaku ekonomi masyarakat Indonesia di era revolusi industri 4.0 seperti sekarang ini dibuktikan dengan banyaknya potensi daya tarik makanan halal di Indonesia yang memiliki varian tersendiri dalam memenuhi permintaan pasar terhadap produk-produk halal sehingga Indonesia sebagai penduduk Muslim terbesar di dunia patut untuk sadar akan perilakunya dalam mengkonsusmi produk-produk halal yang beredar di pasaran, artinya jangan kalah dengan non muslim dalam mengembangkan produk halal tersebut. Yang tidak kalah penting dalam membentuk kesadaran global terhadap produk halal maka perilaku ekonomi masyarakat Indonesia khususnya di era yang serba digital ini (4.0) sudah seharusnya melakukan pelebelan halal dan sertifikasi halal agar mampu bersaing dengan pangsa pasar.
The Strategies of Enhancing Zakat Education in Indonesia
Authors: Santo Hartono Haryani
Published: January 2024

Starting zakat education needs to be pursued as early as possible, continuing at the stages of youth and adulthood, and applying it in old age. Implementing the strategies in zakat education is a long journey. This study describes the strategy used by the National Zakat Board (BAZNAS), as the only Indonesia government zakat agency in improving zakat education in Indonesia. This study uses a descriptive qualitative approach, describing the stages in implementing zakat education. BAZNAS in carrying out its role collaborates with the experts in education to further increase zakat literacy in society. The strategy in educating the public about zakat requires support from all parties, be it the government, educational institutions, and the community itself.
The Affects of wearing Mask on Learning Ability
Authors:   Korean Academy of Cardiorespiratory Physical Therapy, Lee Han-Gyeol , Jung Dae-In
Published: January 2024

Purpose: The purpose of this study is to investigate the affects of wearing mask on learning ability.
Methods: A total of 90 college students were included in this study. The participants were divided into three groups: group 1, KF94 mask(n=30); group 2, Dental mask(n=30), and group 3, No mask(n=30). All groups performed cardiovascular function and class concentration test before and after 4 hours of class. All data were analyzed using SPSS window 22.0 version.
Results: In this study, the difference in cardiovascular function was statistically significant in SpO2 and heart rate(p＜.05). As a result of post-hoc analysis, SpO2 was lower the Dental mask group and the KF mask wearing group than the non-mask wearing group, and lower the KF mask wearing group than the Dental mask group (p<.05). The heart rate was significantly higher in the KF94 mask-wearing group than in the Dental mask-wearing group and the mask-wearing group(p<.05). The difference in class concentration was statistically significant(p＜.05). class concentration was lower the Dental mask group and the KF mask wearing group than the non-mask wearing group, and lower the KF mask wearing group than the Dental mask group(p<.05).
Conclusion: In order to improve students' concentration in class in the current situation of schools where face-to-face classes are becoming active again, it is suggested to remove the mask or wear a low-resistance mask if there are no individual health problems
Is Religiousness an Inevitable Condition of Man or Might It Disappear in Future?
Authors: Oesterdiekhoff Georg
Published: January 2024

Sociology of religion views religion and religiousness as a social phenomenon, something that exists due to alleged social or psychological functions. Religion is believed to exist to sustain social cohesion or to express identity of groups or nations. These widely assumed contentions do not fit the principle of sufficient reason, they do not explain religion and religiousness. The article points out that the laws of psychological development alone account to the existence of the whole phenomenon, Feuerbach being the first to outline this developmental theory of religion. Nowadays sciences have better possibilities to pinpoint a developmental approach with this regard. This cognitive-developmental approach predicts the future of agnosticism and atheism different from views which see religion as an eternal buttress of mind and society.
Creative Learning of Computer Science of Computer Science Professionals: Case University of Matanzas
Authors: González Hernández Walfredo , Petersson Roldán Maritza , Moreno García Marcelina
Published: January 2024

Research on creativity is a frequent topic today, with a strong psychological component influencing its definition. However, few studies have defined creativity in the field of computer science, and even fewer have addressed learning in this area. This paper aims to diagnose creative learning of computer technology in a computer engineering course at the University of Matanzas. To achieve this objective, we first establish the relationship between creative learning and creativity. Then, we describe the basic forms of development of computer technology. Finally, in a theoretical section, we describe the characteristics of creative learning in computer science. A questionnaire will be used to diagnose creative learning in computer science and computer engineering degree programs. The questionnaire will be administered to all 66 final-year students enrolled in the 2022 academic year. The indicators obtained in the theoretical section will be measured using a scale from 0 to 1. The study will first compare the data obtained through qualitative state inference, followed by the application of inferential statistical methods to further analyse the results. Based on the findings, an evaluation of creative learning in computer science will be conducted, indicating that it is generally poor. The hypothesis is rejected based on the data, and the level of development of creative learning in computer science is determined.
On a New Two Point Taylor Expansion With Applications
Authors: Pakdemirli Mehmet
Published: January 2024

A new two point Taylor series expansion is proposed. The expansion is slightly different than the classical definition. The coefficients are calculated as recursive relations in a general form. The two point Taylor expansion is applied to expressing two different functions, one of which has a finite interval of convergence and the other infinite interval of convergence. The conditions for convergence are derived and the results are compared with the results of single point Taylor expansions as well as two point Taylor expansions reported in the literature. It is found that for a finite radius of convergence, two point Taylor expansions can have a single convergence interval as well as two separate convergence intervals. Results of the new expansion are compared with the single point Taylor expansions as well as the classical two point Taylor expansion. Generally speaking two point Taylor expansions better represent the real function when the series is truncated. The new two point expansion and the classical two point expansion produced identical results for the problems treated. An application of the series to solution of a variable coefficient differential equation is also treated.