Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure Communication Scheme for IRS-UAV Enabled Cognitive Network

In this paper, the secure communication model is considered in cognitive relay network. An intelligent reflecting surface (IRS) which is deployed on unmanned aerial vehicle (UAV) is applied to cognitive relay of communication link between secondary internet of things (SIoT) devices and secondary user (SU). However, the presence of secondary eavesdropper (SE) causes security issue for cognitive communication network. Therefore, the problem of average secrecy rate maximization is formulated through the joint design of UAV trajectory, SIoT signal transmission power and IRS passive beamforming without affecting the communication quality among primary users (PUs). Nevertheless, it is infeasible to obtain optimal solution directly for original problem which is non-convex. An efficient algorithm is proposed to solve complex and non-convex problem. Simulation result demonstrates that the proposed algorithm can enhance the average secrecy rate more effectively, and can maximally rise by approximately 108% in comparison with other schemes.
A comparative study of stereopsis measurements: analyzing natural conditions versus dichoptic presentation using smartphones and ultraviolet printer technology

Background Accurate differentiation between stereopsis assessments in the natural and dichoptic presentation states has proven challenging with commercial stereopsis measurement tools. This study proposes a novel method to delineate these differences more precisely. Methods We instituted two stereopsis test systems predicated on a pair of 4K smartphones and a modified Frisby Near Stereotest (FNS) version. Stereoacuity was evaluated both in the natural environment state (via the modified FNS) and the dichoptic state (via smartphones). Thirty subjects aged 20 to 28 years participated in the study with the best-corrected visual acuity (VA) of each eye no less than 0 logMAR and stereoauity of no worse than 40″. Varying degrees of monocular VA loss were induced using the fogging method, while this study does not explore conditions where the VA of both eyes is worse than 0 logMAR. Results When the VA difference between the two eyes did not exceed 0.2 logMAR, the modified FNS produced lower stereoacuity values compared to the 4K smartphones (Wilcoxon signed-rank test: difference = 0 logMAR, Z = −3.879, P < 0.001; difference = 0.1 logMAR, Z = −3.478, P = 0.001; difference = 0.2 logMAR, Z = −3.977, P < 0.001). Conversely, no significant differences were observed when the binocular vision difference exceeded 0.2 logMAR (difference = 0.3 logMAR, Z = −1.880, P = 0.060; difference = 0.4 logMAR, Z = −1.784, P = 0.074; difference = 0.5 logMAR, Z = −1.812, P = 0.070). Conclusion The findings suggest that stereoacuity values measurements taken in the natural environment state surpass those derived from the dichoptic presentation. However, the observed difference diminishes as stereopsis decreases, corresponding to an increase in induced anisometropia.
An Inverse Study of Centrality Measures for Node Groups: Application to Brain Networks

The brain network has led to various applications in neuroscience, focusing on the essential properties of brain connections through the quantification of network measures and topologies. Recently, brain network measures have been developed for a group of nodes to address brain network analysis problems related to the group context. Group centrality measures are defined for a group of nodes and reflect the importance of the group in transferring information to other nodes. In this paper, we employ group centrality measures to address the inverse query: How can we identify a group of nodes that achieves maximum centrality within a given brain network? This outcome gives rise to an optimal highly central group of nodes referred to as the “Group Hub”. Exhaustive search methods to solve the inverse problem are often infeasible due to their exponential complexity, particularly when navigating extensive permutation search spaces. We introduce a novel algorithm to address this optimal inverse problem, named “Progressive Aggregation for Optimal Node Group Maximization (PANGM)”, which is enhanced through parallel computation. We extensively apply this algorithm to a wide array of structural connectomes from older adults and individuals with Alzheimer's disease. The results underscore the effectiveness of our proposed algorithm in revealing Group Hubs within these populations and discerning their differences. The ensuing analysis unveils numerous noteworthy clinical insights, highlighting the potency of our methodology.
Effects of rhythmic visual cues on cortical activation and functional connectivity features during stepping: an fNIRS study

Introduction Rhythmic visual cues (RVCs) may influence gait initiation by modulating cognition resources. However, it is unknown how RVCs modulate cognitive resources allocation during gait movements. This study focused on investigating the effects of RVCs on cortical hemodynamic response features during stepping to evaluate the changes of cognitive resources. Methods We recorded cerebral hemoglobin concentration changes of 14 channels in 17 healthy subjects using functional near-infrared spectroscopy (fNIRS) during stepping tasks under exposure to RVCs and non-rhythmic visual cues (NRVCs). We reported mean oxygenated hemoglobin (HbO) concentration changes, β-values, and functional connectivity (FC) between channels. Results The results showed that, the RVC conditions revealed lower HbO responses compared to the NRVC conditions during the preparation and early stepping. Correspondingly, the β-values reflected that RVCs elicited lower hemodynamic responses than NRVCs, and there was a decreasing trend in stimulus-evoked cortical activation as the task progressed. However, the FC between channels were stronger under RVCs than under NRVCs during the stepping progress, and there were more significant differences in FC during the early stepping. Discussion In conclusion, there were lower cognitive demand and stronger FC under RVC conditions than NRVC conditions, which indicated higher efficiency of cognitive resources allocation during stepping tasks. This study may provide a new insight for further understanding the mechanism on how RVCs alleviate freezing of gait.
Hearing aid Battery Charger Cum Tester

In India hearing aid users are increasing every year. It could be because of the awareness created among the population, enhanced literacy rate, awareness created by NGO’s and ASHA workers. According to the statistical data out of 100 people 13 are born with disability of which 3 would be hearing impaired. The Hearing aid users are classified based on the severity of impairment. They could be mild, moderate, moderately – severe and profound hearing loss. Hearing aid is used as amplifying devices for their impairment. To make them work efficiently, hearing aid with proper battery power level plays a vital role as they are power sources. Hearing aid users purchase batteries which are the essential spares. These if not used properly may drain out the energy immediately. Replacement of batteries will cost more to a wearer. This used battery after use may pile up as e-waste adding to environment pollution (Land pollution). This project will be focusing mainly in reducing buying more batteries for the wearer. Helps to save money as the charger designed will be of indigenous and low cost. Therefore, contributing in reducing e-waste and
Overview of Smart City Rankings and Their Evaluation Criteria: European Perspective

The aim of this article is to supply an overview of the available rankings That take European smart cities into account, and to identify the most relevant ones along with their evaluation criteria. The scope of the article was the study of international rankings That presented results no more than 3 years old (2020-2022) in order to ensure as much objectivity as possible. The research method was the content analysis of the latest available international rankings, which included European cities. The results indicate That the highest rated European smart cities include cities such as London, Paris and Berlin. Another important conclusion is That the position of smart cities was significantly influenced by factors such as the presence of the city on the ranking list of a given ranking in previous years or the inclusion of the city’s response to COVID19 crisis. A key limitation of the article is That it is based on an analysis of only five rankings and the specificity of content analysis as a research method.
Energy Control in Smart-Grid Powered Edge Computing Systems with Massive Connectivity

A novel smart grid-powered communication system is presented to minimize energy costs for edge computing servers and their connected devices and reduce reliance on non-renewable energy. An online joint optimization approach is developed to coordinate renewable energy-powered edge servers, the energy generation of different renewable sources, and energy storage charging/discharging processes to effectively minimize the system energy costs. The alternating direction method of multipliers (ADMM) and dual decomposition are employed to implement the online optimization, resulting in reduced network complexity and preserving user privacy. Simulation results demonstrate the merit of the proposed approach in the utilization efficiency of renewable energy for edge computing systems.
A Self-correcting Cooperative Spectrum Sensing for Cognitive Radio Networks in Low SNR Region

Within the domain of cognitive radio (CR), cooperative spectrum sensing (CSS) is employed to identify available spectrum bands for dynamic spectrum access, leveraging the spatial diversity of secondary users (SUs). However, the existing CSS methods have proven inadequate in effectively protecting the primary user (PU) from harmful interference, particularly in low signal-to-noise ratio (SNR) region. In this paper, we propose a self-correcting cooperative spectrum sensing (SC-CSS) by incorporating an error correction bit into each SU's sensing result. Under the proposed CSS mechanism, the PU's current state is determined by comparing the variation in the energy value of the received PU signal between the preceding and subsequent frames. Further, the closed-form expressions of the overall error probability of SC-CSS are also derived by analyzing a discrete Markov chain process and use it as a cost function in an optimization problem to find out the optimal sensing parameter. At last, numerical simulation results show the effectiveness and robustness of SC-CSS, establishing its superiority in CSS system operating under low SNR conditions.
Effect of Spatter Behavior on Mechanical Properties and Surface Roughness of Printed Parts during PBF-LM of 316L

The spatter generated by the interaction between laser and powder during Powder Bed Fusion-Laser Melting (PBF-LM) can significantly affect the quality of printed parts. A high-speed camera is used to observe the dynamic process of spatter’s behavior under different layer thickness and laser powers during the printing process, and to analyze the printed samples’ surface roughness, microstructure, and mechanical properties. In terms of spatter image processing, employing an optical flow approach to track and quantify the number of spatters efficiently eliminates statistical redundancy and improves statistical correctness. It is found that under the same laser power, the number of spatters produced by the laser scan direction with the gas flow (LSD-W) is more than that by the laser scan direction against the gas flow (LSD-A), and the number of spatters produced increases with the increase of laser power. Analyzing the mechanical properties and surface roughness of the printed samples under different process parameters quantitatively reveals that differences in the spatter amount generated under different process parameters in the PBF-LM process is not the determining factor affecting the difference in tensile strength of printed parts. During LSD-W, the number of spatters generated at laser power of 170 W and layer thickness of 0.03 mm is 87, and the tensile strength of the printed sample is 618 MPa. During LSD-W, the number of spatters generated at laser power of 320 W and layer thickness of 0.05 mm is 211, and the tensile strength of the printed sample is 680 MPa. Instead, spatter generation has a more direct impact on the surface roughness of printed parts. The layer thickness is 0.03 mm, the laser power is 170 W, and (Ra = 2.372 μm) is the surface roughness of the sample. The layer thickness is 0.05 mm, the laser power is 320 W, and (Ra = 8.163 μm) is the surface roughness of the sample.
Repeatable Acoustic Vaporization of Coated Perfluorocarbon Bubbles for Micro-Actuation Inspired by Polypodium aureum

Polypodium aureum, a fern, possesses a specialized spore-releasing mechanism like a catapult induced by the quick expansion of vaporized bubbles. This study introduces lipid-coated perfluorocarbon droplets to enable repeatable vaporization–condensation cycles, inspired by the repeatable vaporization of Polypodium aureum. Lipid-perfluorocarbon droplets have been considered not to exhibit repeatable oscillations due to bubble collapse of the low surface tension of lipid layers. However, a single lipid-dodecafluoropentane droplet with a diameter of 9.17 µm shows expansion–contraction oscillations over 4000 cycles by changing lipid composition and applying a low-power 1.7 MHz ultrasound to induce the partial vaporization of the droplets. The optimal combinations of shell composition, droplet fabrication, and acoustic conditions can minimize the damage on shell structure and promote a quick recovery of damaged shell layers. The highly expanding oscillatory microbubbles provide a new direction for fuel-free micro- or nanobots, as well as biomedical applications of contrast agents and drug delivery.
To Ghost or To Be Ghosted: An Examination of the Social and Psychological Correlates Associated with Ghosting

This paper examines the modern phenomenon known as “ghosting,” which can be defined as avoiding another individual (such as a family member, friend, or partner) by suddenly cutting off communication without providing an explanation. From an evolutionary perspective, given that our ancestors lived in small-scale societies, cutting ties with others would have had devastating consequences. To address variables connected with this kind of outcome, we conducted a study with 292 participants ( M age = 21.45, SD = 4.19; 26% male, 72.6% female, .3% not listed, 1% preferred not to say). Significant correlations were found between scales measuring particular psychological constructs (e.g., adult attachment, sociosexuality) and ghosting experiences. A regression analysis found that specific constructs independently predicted ghosting experiences. A notable finding was that the more one has ghosted, the more they have been ghosted themselves, with the reverse also being true that the more one has ghosted, the more they ghost others. Overall, in examining the social and psychological correlates associated with ghosting, our findings suggest that those who had been ghosted and those who had ghosted others had a proclivity toward relatively difficult social, emotional, and psychological functioning compared to those with fewer ghosting experiences.
Causes of Resistance Decrease of Corona Protection Materials in Thermal Aging Process

During the operation of the high-voltage electrical machine partial discharge (PD) may occur in the slot of stator winding. A resistance conductive coating based on graphite is applied to the surface of wall insulation to eliminate PD. The coating resistance decreases rapidly when high temperature impact to insulation system. Low value of resistance can lead to the appearance of vibration sparking (VS). In our work, we consider a different factor affected to quality of conductive coating which include the chemical nature of the polymer matrix, the degree of curing of the binder, the degree of grinding of the filler (graphite) and the technological process of manufacturing enamel for a conducting coating. This paper shown that the unfinished process of forming the polymer matrix structure is the most probably cause of resistance instability.
Research on Intelligent Control Method of Rock Drilling Manipulator Based on Force Control Sensor

Rock drilling is a difficult, time-consuming, poor working conditions, and very critical operation process. In modern mining and large-scale infrastructure construction, the use of traditional drilling equipment has gradually exposed many disadvantages, such as increased labor costs, poor construction environment, the proficiency of operators has a great impact on the quality and duration of rock drilling, and the safety of construction personnel is not effectively guaranteed. Under this background, the rock drilling robot emerged to meet the requirements of modern society for high-efficiency excavation and intelligent rock drilling equipment. This paper summarizes the research status of rock drilling manipulator, analyzes the development status of rock drilling manipulator, describes the typical products and models, analyzes the existing kinematics solution methods of rock drilling manipulator, and further compares the advantages and disadvantages of various force position control methods.
Study of Factors Influencing on Mental Health and Their Relationships, of IT Sector Employees in Colombo District, Sri Lanka

This study focused on the mental health of IT sector employees in Colombo, using quantitative research methods and data from 300 participants (162 males and 138 females) using the DASS 21 questionnaire and self-administered surveys through convenience sampling. Correlation analysis, chi-square tests, and regression analysis were utilized to examine the data. It found significant correlations between mental health outcomes (stress, anxiety, and depression) and factors like work-life balance, workload, working conditions, and physical fitness. Work-life balance, working environment, and workload were identified as the most significant predictors of mental health outcomes. Physical fitness was associated with stress, depression, and anxiety but had a limited overall impact on mental health. Differences in depression, stress, and anxiety levels were observed based on marital status, age group, work experience, salary, and gender. These findings emphasize the importance of addressing work-life balance and working conditions to enhance the mental health of IT sector employees in Colombo. They provide valuable insights for organizations and policymakers to develop strategies and interventions that promote employee well-being and productivity, underscoring the need to prioritize mental health and create a supportive work environment.
Energy-AOI-Aware UAV-Assisted Data Collection: A Multi-Agent Deep Reinforcement Learning-Based Trajectory Optimization

With the development of Internet of Things (IoT) technology, sensor networks are widely used for data collection in various IoT scenarios. Traditional sensors use multi-hop communication to transmit data back to the data center, which can lead to excessive energy consumption in some nodes and cause the collapse of sensor networks. Solving the data transmission problem in sensor networks has become a critical issue. In recent years, unmanned aerial vehicles (UAVs) capable of hovering have been increasingly applied in military and civilian fields, such as smart logistics, edge computing, and wireless power transfer (WPT). UAVs, with their strong controllability and high mobility, can effectively perform the task of data transmission in sensor networks. In the task of UAV -assisted sensor data collection, UAVs can establish communication connections with ground sensors through small communication devices and act as mobile aggregation nodes to collect data from the ground wireless sensor network. To achieve energy balance among sensor network nodes as much as possible while ensuring service quality based on information age, we propose a combinatorial optimization problem. Ultimately, we solve the combinatorial optimization problem by optimizing the trajectory of UAV flight. As the problem is a mixed-integer non-convex optimization which is difficult to solve, we propose a UAV swarm-based sensor trajectory planning algorithm using multi-agent reinforcement learning. Simulation results show that the proposed algorithm has a better effect than baseline approaches on optimization objective.
Sub-Nyquist Sampling-Based Wideband Spectrum Pre-Sensing via Branch-to-Maximum Energy Ratio

Sub-Nyquist sampling-based wideband spectrum sensing has attracted considerable attention due to its potential of significantly reducing the sampling rate. However, most existing methods assume the presence of primary users, focus solely on support recovery, and disregard the possibility that the concerned spectrum band may be free, leading to high false alarm rate and computational complexity. This paper proposes a novel pre-sensing algorithm called the branch-maximum energy ratio (BMER) detection algorithm, which uses sub-Nyquist samples drawn from the modulated wideband converter to calculate the ratio of branch-maximum energy. We provide a theoretical development to calculate the false alarm probability and detection probability of the proposed BMER algorithm. Simulation results indicate that the proposed BMER algorithm is robust against noise uncertainty and significantly improves the sensing performance with low computational complexity.
Leveraging Food Security Challenges in South Eastern Nigeria Using GIS and Geospatial Education

SUMMARY Achieving food security can be a herculean task as it is dependent on agriculture, trade, health and the environment as a whole. A number of climatic changes occur in our environment which have adverse effects on agricultural production both directly and indirectly as a whole thus leading to some worth of “food insecurity”. It is very essential that citizens of every nation are catered for judiciously with respect to its growth and all developmental processes. The South Eastern Nigeria is generally densely populated and in order to measure the state of deprivation which may arise, proximity analysis will be undertaken with respect to the population, food availability, accessibility and utilization. This study tries to define the concept of food security, the reviews of food security situation in South Eastern Nigeria and also hopes to highlight the importance of Geographical Information System (GIS) approach to food security scenarios and its associated benefits with respect to South Eastern geo-political zone and Nigeria generally. Consequently conclusion is drawn by highlighting the adoption of precision Agriculture (precision farming) to improve food production in South Eastern Nigeria.
An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality

The ambition of our contribution is to show how an interdisciplinary framework can pave the way for the deployment of innovative virtual reality training sessions to improve anticipation skills in top-level athletes. This improvement is so challenging that some authors say it is like “training for the impossible”. This framework, currently being implemented as part of a project to prepare athletes for the 2024 Olympic Games in Paris, based on the ecological-dynamics approach to expertise, is innovative in its interdisciplinary nature, but also and above all because it overcomes the limitations of more traditional training methods in the field designed to optimize anticipation skills in top-level athletes. The ambition is to tackle successive challenges ranging from the design of virtual partners and opponents to the deployment of training programs in virtual reality, while ensuring the acceptability and acceptance of such innovative virtual reality training protocols and measuring associated workloads.