Reviewerly/exHarmony huggingface dataset:
A Comparative Analysis of Industrial Cybersecurity Standards

Cybersecurity standards provide a structured approach to manage and assess cybersecurity risks. They are the primary source for security requirements and controls used by organizations to reduce the likelihood and the impact of cybersecurity attacks. However, the large number of available cybersecurity standards and frameworks make the selection of the right security standards for a specific system challenging. The absence of a comprehensive comparison overlap across these standards further increases the difficulty of the selection process. In situations where new business needs dictate to comply or implement additional security standard, there may be a risk of duplicating existing security requirements and controls between the standards resulting in unnecessary added cost and workload. To optimize the performance and cost benefits of compliance efforts to standards, it is important to analyze cybersecurity standards and identify the overlapping security controls and requirements. In this work, we conduct a comparative study to identify possible overlaps and discrepancies between three security standards: ETSI EN 303 645 v2.1.1 for consumer devices connected to the internet, ISA/IEC 62443-3-3:2019 for industrial automation and control systems, and ISO/IEC 27001:2022 for information security management systems. The standards were carefully chosen for their broad adoption and acceptance by the international community. We intentionally selected standards with different areas of focus to illustrate the significant overlaps that can exist despite being designed for different environments. Our objective is to help organizations select the most suitable security controls for their specific needs and to simplify and clarify the compliance process. Our findings show a significant overlap among the three selected standards. This information can help organizations gain a comprehensive understanding of common security requirements and controls, enabling them to streamline their compliance efforts by eliminating duplicated work especially when meeting the requirements of multiple standards.
GBForkDet: A Lightweight Object Detector for Forklift Safety Driving

The importance of object detection in intelligent logistics applications is increasingly recognized.However, current detector models suffer from challenges such as high computational cost and low detection accuracy, which limit their deployment on edge devices with limited computational power in logistics scenarios.To address these issues, this paper proposes a novel lightweight detector model (GBForkDet) based on YOLOv8 for forklift safety driving.Firstly, the Ghost module is integrated into YOLOv8 to optimize the Backbone feature extraction process, reducing the computational cost of the model.Then, a Bi-directional Omni-Dimensional Dynamic Neck (BiODNeck) is designed to fuse feature information in complex logistics scenarios.GBForkDet significantly improves the capture of contextual logistics background information by reconstructing the Neck of YOLOv8 with BiODNeck.This is attributed to cross-layer weighted feature fusion and a complementary focus on learning convolutional kernels in any convolutional layer along all four dimensions of the kernel space.Furthermore, the introduction of the Normalized Wasserstein distance (NWD) as an enhanced loss function improves the detection of small distant objects in logistics scenarios.Experimental results show that GBForkDet achieves a mAP of 92.7% and 95.3% on the established Forklift-3k and KITTI datasets while reducing the model parameters by 17.9% and the computational cost by 22.5% compared to the baseline YOLOv8s model.Under the Jetson Nano edge platform and 640×640 input size, the GBForkDet model achieves a remarkable inference time of 108.2 ms using TensorRT acceleration.
Voxel Graph Attention for 3-D Object Detection From Point Clouds

Recently, 3D object detection from LiDAR point clouds has advanced rapidly, but the detection performance still has shortcomings in complex scenarios. In this paper, we introduce a novel two-stage 3D object detector that utilizes only raw point clouds as input. Specifically, we propose two novel strategies that can effectively enhance the detection performance: the Feature Interpolation Aggregation (FIA) and Graph Attention Pooling (GAP). The former is used to initialize the graph centroid features across different resolutions, which is essential for constructing local graphs. The latter constructs hierarchical local graphs on multi-scale voxels to extract region of interest (RoI) features by considering the contributions of neighboring voxels. This enables the aggregation of more effective and robust features for detection. The proposed innovations enhance the detector’s feature extraction capability and improve its robustness in complex scenarios. Experimental results on the KITTI and Waymo datasets demonstrate that VoxelGraph-RCNN achieves competitive performance compared with state-of-the-art detectors. Specifically, the proposed model surpasses the baseline Voxel R-CNN by 0.43%, 1.04%, and 0.87% in detecting objects with easy, moderate, and hard difficulty levels on the KITTI datasets, respectively.
A Survey Paper on the Latest Techniques for Sarcasm Detection Using BG Method

Sentiment Analysis is gathering a lot of attention nowadays as a lot of online data is gathered through blogs, ecommerce websites, product reviews, etc. which people are expressing online. This data is extracted by companies to judge if their products are having a positive outlook or a negative outlook. Sarcasm is a problem faced in sentiment analysis as it flips the polarity of the sentence. This paper provides a survey on different techniques used by researchers to detect sarcasm. At the end, we propose a methodology to detect sarcasm. The proposed framework will give suggestions to different researchers in the detection of sarcasm.
Doubly and triply extended MSRD codes

In this work, doubly extended linearized Reed–Solomon codes and triply extended Reed–Solomon codes are generalized. We obtain a general result in which we characterize when a multiply extended code for a general metric attains the Singleton bound. We then use this result to obtain several families of doubly extended and triply extended maximum sum-rank distance (MSRD) codes that include doubly extended linearized Reed–Solomon codes and triply extended Reed–Solomon codes as particular cases. To conclude, we discuss when these codes are one-weight codes.
Reflections on the Graduates of the educational environment of the university: Assessment through the prism of practice and employment

Introduction. The article indicates a problem related to the need to obtain an assessment of the educational environment and the organization of the educational process from the position of using the obtained educational results in labor and the absence of such an emphasis in research practice. It is emphasized that the perspective of the existing evaluations of the educational environment by students studying in universities does not give objective information about the practical orientation and demand for the results of education outside this environment. In connection with the identified problem, it is proposed to consider the possibility of using the results of such monitoring among university graduates as the basis for making management decisions to change the educational environment of a modern university. Purpose of this article — methodical search for indicators of the university environment and evaluation of them by university graduates, to determine the problematic aspects of the organization of the educational process from the position of ensuring labor competitiveness and professional success of students. Materials and Methods. The article presents the materials of three-year surveys among graduates of higher education institutions (N=480 (2019), 530 (2020), 610 (2021), conducted on the example of a regional university. The sampling error in relation to the possible alumni community during the university's existence amounted to 3.96% with a confidence probability of 95%. The areas of preparation of graduates act as a quota indicator. Results and their Implication. As indicators in the research model proposed to assess satisfaction with the results of professional training among graduates, assessment of the university's influence on the professional qualities and competence of graduates, assessment of indicators of the educational environment, satisfaction of graduates with the process and result of employment, practical orientation and relevance of training, commitment of graduates to the university. The conducted research and retro-evaluation of graduates of the educational process and its results showed problematic moments related primarily to the organization of the student support system in employment, as well as ensuring the necessary level of practical skills and digital literacy. The difference between the evaluations of graduates and studying students established a gap between the perceptions of usefulness and the level of the educational result, actualizing the need for special attention to the opinion of graduates in the improvement and transformation of the university environment.
Digital services in the study of geometry in basic school

The article presents approaches to understanding the essence of digital services, show their adventures in education and the possibility of their application in the study of geometry in grades 7-9. The text include examples of the use of word clouds and intelligence maps when studying geometry in basic school.
An Empirical Framework for Understanding a Player’s Sense of Agency in Games

AbstractThis study investigates players' sense of control over a game, referred to as the sense of agency (SoA). While prior research has addressed the importance of control in game interactions, understanding the factors that constitute players' SoA remains limited. Using a mixed methods approach, we conducted interviews (n = 18) and surveys (n = 654) to gain qualitative and quantitative insights into this unique perceptual phenomenon. Multidimensional scaling analysis revealed a two-dimensional space comprising five clusters that shape players' SoA. We then developed and tested a 12-item Game Sense of Agency questionnaire which, through exploratory and confirmatory factor analysis, measures four factors: Multisensory Presentation, Feedback Reasoning, Virtual Realism and Control Smoothness. This research identifies the multifaceted nature of players' SoA and offers practical suggestions for how it could be measured. The outcomes contribute an empirically-driven framework for understanding and evaluating the factors that influence players' SoA in games.Keywords: Game controlsense of agencyuser researchuser metrics Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsZixuan GuoZixuan Guo, a doctoral student at the School of Advanced Technology, Xi'an Jiaotong-Liverpool University, China. Her research interest focus on Human-Computer Interaction, Virtual Reality/Augmented Reality, and Games.Cheng-Hung LoCheng-Hung Lo is a design researcher, educator, and digital artist working in the intersections of Arts, Culture, and Technology. His major research interests are Design Visualization, Virtual Reality, User Experience-Driven Design, Cultural Heritage and Computational Arts.
Dual discriminators generative adversarial networks for unsupervised infrared super-resolution

The breakthrough of sensor resolution has always been focused on the computer vision area, which is an urgent need when infrared sensor technology progresses slowly. We propose a novel unsupervised infrared super-resolution (UISR) method based on the photoelectric characteristics of infrared images. The UISR, without high-resolution ground truth, establishes a fully unpaired generative adversarial framework to enrich the image details and improve the visual perception of human eyes. In the process of SR, UISR corrects the abnormal pixel values, blurred edges, and mosaic effect by maintaining the image style uniformity and mining the texture distribution characteristics in the image domain. Specifically, the dual discriminator module is designed to enhance both global structures and local textures. The style discriminator captures the natural structure characteristics of large image patches to control the authenticity. In contrast, the texture discriminator captures the texture characteristics of small image patches to improve the detail generation performance. Besides, the content constraint module is designed to maintain the basic content of the image. Experiments show that, compared to the supervised algorithm, the proposed UISR presents more real SR infrared images and is simpler to generalize in higher scales beyond sensor resolution.
Voice assistant technology applied to populations with developmental and physical disabilities

ABSTRACTEmerging assistive technologies (AT), such as voice assistants (VA), impact the citizenry and organisations. Amongst those affected, there is a group of people with developmental and physical disabilities that have been impacted the most. As the use of technology evolves, more studies analysing the impact of VA on these populations are emerging. However, there is still a dearth of studies congregating results systematically, in which it would be possible to understand the impact of VA technologies on different contexts. Thus, our study aims to understand the applicability and impact of VAs on the lives of people with disabilities and the perspectives of this emerging AT. Drawn on a rigorous systematic literature review using the PRISMA protocol, we included 68 articles for analysis after applying the inclusion and exclusion criteria. We identified seven intertwined themes related to the benefits and challenges of VA technologies. The emergent benefits are the impact on users' ecosystem and well-being and economic and social benefits; conversely, the challenges are inherent issues related to technology, financial and social challenges. We contribute to theory and practice by understanding the impact of VAs on populations with disabilities' ecosystem and well-being at the micro, meso and macro-levels of the phenomena. HIGHLIGHTSVA technology transforms the way people with disability interact in their ecosystemVA technology positively impacts people with disabilities' well-being and ecosystemVA issues are related to data privacy and technology accessibilityBenefits and challenges of the VA adoption touches the micro, meso and macro-levels of the ecosystemPerformance analysis, diverse populations and understanding of social aspects, are the trending topics for future researchKEYWORDS: Assistive technologydevelopmental disabilitydisabilitiespeople with disabilityphysical disabilityvoice assistant AcknowledgementsWe would like to acknowledge the generosity of the e-Healthcare Research Group, and the Federal University of Technology Paraná's Biomedical Engineering Postgraduate Research Programme – the support of both has been invaluable in putting this theme together.Disclosure statementNo potential conflict of interest was reported by the author(s).
Geometry‐based flipper motion planning for articulated tracked robots traversing rough terrain in real‐time

Abstract Tracked robots operating on rough terrain are often equipped with controllable flippers to help themselves overcome large obstacles or gaps. How to automate the control of these auxiliary flippers to achieve autonomous traversal remains an open question, which still necessitates inefficient manual teleoperation in practice. To tackle this problem, this article presents a geometry‐based motion planning method for an articulated tracked robot to self‐control its flippers during autonomous or semiautonomous traversal over rough terrain in urban search and rescue environments. The proposed method is developed by combining dynamic programming with a novel geometry‐based pose prediction method of high computational efficiency, which is applicable for typical challenging rescue terrains, such as stairs, Stepfields, and rails. The efficient pose prediction method allows us to make thousands of predictions about the robot poses at future locations for given flipper configurations within the onboard sensor range. On the basis of such predictions, our method evaluates the entire discretized configuration space and thereby determines the optimal flipper motion online for a smooth traversal over the terrain. The overall planning algorithm is tested with both simulated and real‐world robots and compared with a reinforcement‐learning‐based method using the RoboCup Rescue Robot League standard testing scenarios. The experimental results show that our method enables the robots to automatically control the flippers, successfully go over challenging terrains, and outperform the baseline method in passing smoothness and robustness to different terrains.
On safe and usable chatbots for promoting voter participation

Abstract Chatbots, or bots for short, are multimodal collaborative assistants that can help people complete useful tasks. Usually, when chatbots are referenced in connection with elections, they often draw negative reactions due to the fear of mis‐information and hacking. Instead, in this work, we explore how chatbots may be used to promote voter participation in vulnerable segments of society like senior citizens and first‐time voters. In particular, we have built a system that amplifies official information while personalizing it to users' unique needs transparently (e.g., language, cognitive abilities, linguistic abilities). The uniqueness of this work are (a) a safe design where only responses that are grounded and traceable to an allowed source (e.g., official question/answer) will be answered via system's self‐awareness (metacognition), (b) a do‐not‐respond strategy that can handle customizable responses/deflection, and (c) a low‐programming design‐pattern based on the open‐source Rasa platform to generate chatbots quickly for any region. Our current prototypes use frequently asked questions (FAQ) election information for two US states that are low on an ease‐of‐voting scale, and have performed initial evaluations using focus groups with senior citizens. Our approach can be a win‐win for voters, election agencies trying to fulfill their mandate and democracy at large.
A novel algorithm for imputing the missing values in incomplete datasets

In today’s world, our heavy reliance on digital devices for data collection has become the norm. However, when these devices fail, there is a significant risk of losing valuable information, making data mining an arduous task for data analysts. The presence of a substantial amount of missing data within a dataset leads to inappropriate results and incomplete data analysis. Consequently, there is a pressing need to develop an algorithm capable of efficiently and accurately predicting missing values. This research paper introduces a new algorithm, known as the IMV-RE (imputing the missing values in real-time environment) algorithm, which is based on a novel splitting approach. The IMV-RE algorithm addresses the challenge of imputing various missing values within a dataset. To enhance prediction accuracy, the algorithm sets an upper limit for each class that contains missing values, providing valuable assistance in accurately predicting these values. To evaluate the efficacy of the IMV-RE algorithm, we conducted experiments using ten benchmark datasets comprising both numerical and mixed data. The results of our comparative analysis demonstrate that the proposed IMV-RE algorithm outperforms existing techniques in terms of sensitivity to accuracy, root mean square error (RMSE), and coefficient of determination (R2).
Path planning of unmanned surface vehicle based on artificial potential field approach considering virtual target points

Aiming at the local minimum problem and target unreachable problems in the path planning of unmanned surface vehicle (USV), a path planning algorithm of USV considering virtual target point is proposed. For the target unreachable problem, a repulsive force potential field function is created. According to the measured distance between the target and the obstacle, the repulsive force of the target is zero, so that the USV can reach the target point. For the local minimum problem, the local minimum caused by various obstacles is analyzed, simulated annealing (SA) and artificial potential field approach (APFA) are combined to solve the minimum point problem caused by general obstacles. For the local minimum problem caused by special U-shaped obstacles, a virtual target point algorithm (VTPA) is established to solve this problem. The simulation results prove that this algorithm solves the problem of long path caused by too large repulsive force. Compared with Dual-Tree Rapidly exploring Random Tree (DT-RRT) algorithm, the efficiency of this algorithm has been significantly improved. Algorithm running time was reduced by 33.4%. Path length was reduced by 17.8%. Not only the time is saved, but also the path planning is optimized, so that the speed of the algorithm is accelerated.
Distribution of Potentially Toxic Elements in the City of Zintan and Its Surroundings (Northwestern Libya) by Surface Soil Sampling

The study area is the city of Zintan, in northwestern Libya, which has grown over the past 30 years. Its current population is roughly 30,000. Although the city is in part commercial, most of the population engages in agriculture and primarily grows cereal crops (wheat and barley). The demand of the growing city for agricultural products has increased, intensifying the use of fertilizers, pesticides, and insecticides. Consequently, concentrations of potentially toxic elements (PTE) in the soil have increased. To assess the soil quality (to provide a snapshot of the condition of the soil), systematic sampling was undertaken across a grid of about 2 km × 2 km. The main objective was to determine the chemical and mineral composition of the area of interest, keeping in mind the geological footprint of the terrain. The geologic framework itself is not conducive to elevated concentrations of elements like U, Th, Mo, As, Hg, Pb, and Cr. Therefore, metal concentrations greater than the amounts in the Earth’s crust are most likely of anthropogenic origin. A total of 143 samples were collected and chemical analyses were performed using a Thermo Fisher Scientific Niton XL3t GOLDD+ XRF analyzer for the following elements: Mo, Zr, Sr, U, Rb, Th, Pb, Au, Se, As, Hg, Zn, W, Cu, Ni, Co, Fe, Mn, Cr, V, Ti, Sc, Ca, K, S, Ba, Cs, Te, Sb, Sn, Cd, Pd, and Ag. This paper provides examples of elevated concentrations, potentially harmful to the environment, such as those of the following: sulfur of unknown origin (two to three times higher than the Earth’s crust average); arsenic, given that there are no related natural phenomena (all the samples measured displayed concentrations higher than those found in the Earth’s crust); mercury (concentrations much higher than permissible levels); cesium (additional investigations required to determine the origin); molybdenum; and uranium likely resulting from the use of superphosphates (concentrations nearly always significantly higher than those in the Earth’s crust).