Miracle-dz/UniFAR-FTUs huggingface dataset:
Far Proximity Identification in Wireless Systems

As wireless mobile devices are more and more pervasive and adopted in critical applications, it is becoming increasingly important to measure the physical proximity of these devices in a secure way. Although various techniques have been developed to identify whether a device is close, the problem of identifying the far proximity (i.e., a target is at least a certain distance away) has been neglected by the research community. Meanwhile, verifying the far proximity is desirable and critical to enhance the security of emerging wireless applications. In this article, we propose a secure far proximity identification approach that determines whether or not a remote device is far away. The key idea of the proposed approach is to estimate the far proximity from the unforgeable “fingerprint” of the proximity. We have validated and evaluated the effectiveness of the proposed far proximity identification method through experiments on real measured channel data. The experiment results show that the proposed approach can detect the far proximity with a successful rate of 0.85 for the non-Line-of-sight (NLoS) scenario, and the successful rate can be further increased to 0.99 for the Line-of-sight (LoS) scenario.
Improving the quality of production of gears in terms of errors in the profile of teeth in gear milling operations

The article describes the scheme for continual improvement of manufacturing quality spur gears in terms of error profiles of the side surfaces of gear teeth. The technique is universal and applicable to any operations of gear processing. The practical application of the technique is considered by the example of gear milling with a worm gear cutter. The errors of profile include metrological indicators of total error profile, the error direction and error of form profile. The scheme of analysis of the data consists of several steps – evaluation of indicators relative to the limit values, identification of the technological structure of the profile errors and expert analysis of the profile profilograms. The final expert analysis of profilograms allows to reveal the most probable operating negative technological factors leading to deviations of a profile from nominal position. The advantage of the quality improvement scheme is its high efficiency and effectiveness in comparison with traditional methods of statistical quality management, since it does not require the collection of significant amounts of statistical information.
Model-Free Gene Selection Method by Considering Unbalanced Samples

In gene expression data analysis, discriminator genes are importantly informative genes for further research. Recently, a great deal of research has focused on the challenging task of identifying these informative genes from microarray data. However, the sizes of sample classes in microarray data are often unbalanced. The unbalance of samples has not been explicitly and correctly considered by the existing gene selection methods, especially nonparametric methods. Considering the unbalance of samples and the stability of the approach for identifying informative genes, a novel and model-free gene selection method is proposed in this paper. With considering within-class difference and between-class variation, as well as the homogeneities of the within-class difference and between-class variations, scoring functions of genes are constructed to select discriminator genes. This method is not only applicable in two-category case but also applicable in multi-category case. The experimental results on two publicly available microarray datasets, leukemia data and small round blue cell tumor data, show that the proposed method is very efficient and robust to select discriminator genes.
Design and Evaluation of a Leisure Education Program for Caregivers of Institutionalized Care Recipients

Family caregivers are confronted with stressors such as depression and guilt resulting from institutional placement decisions. Leisure education programs can enhance caregivers' sense of caring for themselves too. The purpose of this study was to evaluate the effectiveness of a leisure education program for caregivers of persons with dementia residing in an institution serving veterans as therapeutic recreation service provision. The program was designed to assist caregivers to develop personal knowledge and understanding of oneself in leisure and to develop the knowledge and ability to plan for leisure. Results indicated a positive impact on the leisure knowledge and self-care practices of the caregivers and a need for ongoing modifications of the leisure education program content and process.
Specifics of Semantics of a Statically Typed Language of Functional and Dataflow Parallel Programming

It is proposed to add a static system of types to the dataflow functional model of parallel computing and the dataflow functional parallel programming language developed on its basis. The use of static typing increases the possibility of transforming dataflow functional parallel programs into programs running on modern parallel computing systems. Language constructions are proposed. Their syntax and semantics are described. It is noted that the need to use the single assignment principle in the formation of data storages of a particular type. The features of instrumental support of the proposed approach are considered.
A Novel Multiscale Modelling Approach for Evaluation of the ASR in Concrete Structures

This paper presents a new multiscale approach for evaluation of the volume change in concrete structures due to the alkali-silica reaction (ASR). A practical step by step approach that can be applied to the real structures is developed based on combined experimental and numerical assessment by considering the most influential ASR parameters at different scales. In the first step, the ASR expansion is measured using accelerated concrete cylinder test (ACCT) for different concrete mixtures covering different variables of important factors such as mix design (e.g., w/cm, fly ash type and replacement percentages), aggregate reactivity, alkali loadings, temperature, and relative humidity etc. All measured expansion data are then modelled using artificial neural network (ANN) modeling approach in the second step. In the third step, finite element (FE) model is utilized at different scales to analyze the real structures and representative volume element (RVE) taking into account the ASR gel expansion and structural boundary conditions. Finally, the effects of the structural constraints are taken into account by introducing correction factors to the predicted free expansion (i.e. no constraints) of the RVE by ANN model. It was found that a combined effect of both internal gel pressure and structural constraints determines the net volume expansion in a concrete structure. In order to show the applicability of the proposed approach, the model is employed for evaluation of the ASR-induced net volume expansion at different locations of a dam structure under realistic in-service conditions. The microstructural study was also done by using X-ray CT that can be used to estimate the ASR progress in concrete structure and validate / support the FEM based predictions.
Amniotic fluid embolism: incidence, risk factors, and impact on perinatal outcome

Please cite this paper as: Kramer M, Rouleau J, Liu S, Bartholomew S, Joseph K for the Maternal Health Study Group of the Canadian Perinatal Surveillance System. Amniotic fluid embolism: incidence, risk factors, and impact on perinatal outcome. BJOG 2012;119:874–879.
Emotional AI and EdTech: serving the public good?

ABSTRACT Education Technology (EdTech) companies are deploying emotional AI to quantify social and emotional learning. Focusing on facial coding emotional AI that uses computer vision and algorithms to see, recognise, categorise and learn about facial expressions of emotion, this paper evaluates nascent usage of these technologies in education. To do this, it assesses the nature of child rights, the history and modern usage of face-based emotional AI, methodology and efficacy, and what this paper sees as a clash of private and public interests. Concern is shown to be two-fold: first is on method, especially given scope for material effects on students; second are ethical and legal concerns. While proposing a list of considerations for any implementation for these technologies in the classroom, the paper concludes that significant risks exist in deployment of these technologies in the classroom.
Evaluating the accuracy of the VitalWellness device

Background and Objective: Portable and readily accessible wellness devices can aid vital sign measuring for those interested in tracking their health. In this diagnostic accuracy study, we evaluated the performance of the VitalWellness device (VW), a wireless, compact, noninvasive device that measures four vital signs (VS) – blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature (BT) – using the index finger and forehead. Methods: Adult volunteers with VS that fell both within and outside of the normal physiological range were enrolled to provide BP, HR, RR, and BT measurements using both the VW and Food and Drug Administration-approved reference devices. A subgroup of participants underwent an additional test to analyze the VW's performance on HR and RR outside of normal physiological ranges. Statistical measurements were plotted on scatter and Bland–Altman plots. Sensitivity analyses to evaluate the VW's performance by gender, skin color, finger size, and auxiliary activities were performed. Results: A total of 263 participants completed the study. On an average, systolic BP measured using the VW was 10 mmHg lower than that of the reference device (correlation coefficient r = 0.7), whereas diastolic BP was 3 mmHg lower (r = 0.6), and RR was 2 bpm lower (r = 0.7). VW HR and BT measurements were, on average, 1 bpm and 0.3°F higher than the corresponding reference measurements (r = 0.9 and r = 0.3), respectively. Conclusion: The VW device is well-suited for home-based, nonmedical monitoring of HR, RR, and BP. Further improvement in measurement accuracy is required to enable applications for medical use.
Goal-oriented dialog systems and Memory : an overview

After recalling generally accepted models for representing human dialogues and the different types of human memory, we review goal oriented dialog systems and chatbots, detailing both dialog models and memory-based systems. From some recent investigations about core human language working hinting at reﬂective aspects, we explain how we think that the recent advances in adversarial learning could provide an interesting research avenue for improving goal oriented chatbots architecture, by injecting in the usual representation triple: dialog turn, dialogue history and knowledge base, more cognitive oriented aspects inspired by the human memory model.
Assessment of RNA stability for age determination of body fluid stains in forensic biology

Recent studies in forensic science have shown a possible correlation between the degradation rate of some RNA transcripts and the age of bloodstains. The time of deposition of a stain can be of major importance to determine the relevance of a sample in a forensic investigation. We assessed the possibility of using the stability differences of RNA transcripts to determine the age of the most common body fluid stains encountered in forensic biology.
Advantages of Heterogeneous Logic Block Architectures for

Most FPGAs use an array of identical logic blocks, largely because such devices are easy to design. Previous studies on logic block architecture, however, have concluded that while 4-input lookup tables (4-LUTs) make efficient use of area [Rose901 [Kou192], significantly more coarse-grain blocks such as 5-LUTs, 6-LUTs and 7-LUTs are superior in terms of system speed [KoulSl] [Sing911 [Sing92]. These results suggest that a mixture of different size LUTs (for example 4-LUTs and 6-LUTs) may provide a better tradeoff between speed and density. This paper presents an architectural investigation into such heterogeneous FPGAs. We consider FPGAs that use two different sizes of lookup table logic blocks, and investigate the areaefficiency of different mixtures of different sizes of LUTs. Experimental results on a set of benchmark circuits indicate that several heterogeneous architectures achieve significant reduction in the number of programming bits and logic block pins compared to the industry standard 4-input lookup tables [HsieSO] [Hi1192]. Furthermore, a 6-LUT/4-LUT combination will likely exhibit better performance with nearly equivalent area than a homogeneous 4-LUT FPGA.
Context-Aware Adaptive Remote Access for IoT Applications

The rapid growth of communication networking, ubiquitous sensing, and signal processing has spurred the emergence of the Internet of Things (IoT) era. As a novel cutting-edge technology, the IoT enables a plethora of smart-devices equipped with diverse computing, sensing, and actuation capabilities to be connected to the Internet. Thus, it promises to provide a revolutionary and fully connected “smart” world while greatly developing economies and enhancing the quality of life. IoT is indeed an emergent global phenomenon, where real-time remote access to data and applications opens new unprecedented opportunities for ubiquitous monitoring and managing. In such dynamic, interconnected, and heterogeneous environment where the context conditions (location, time, situation sensitivity, etc.) are continuously and frequently changing, context-aware and adaptive solutions for data access are required to respond to the applications’ needs. Nevertheless, until now, no schemes provide concrete context-aware access control mechanisms in IoT. In this article, we design a novel context-aware attribute-based access control (CAABAC) that considers the dynamic context changes. The proposed approach incorporates the contextual information with the ciphertext-policy attribute-based encryption (CP-ABE) to guarantee adaptive contextual access to data. The extensive analysis and simulations prove both the effectiveness and efficiency of the proposed scheme. Specifically, context-aware and adaptive remote access is enabled while outperforming other benchmarked schemes in terms of storage, communication, and computational cost.
Interrater and intrarater reliability of the alpha angle of the hip: is the alpha angle reliable?

Background:The purpose of the study was to determine the inter- and intra-rater reliability of the alpha angle measured on hip axial and axial oblique MRI, which has not been well defined in the existing orthopaedic literature. Methods:Fifty MRIs were reviewed by one musculoskeletal radiologist and two orthopaedic hip surgeons. The examiners evaluated the alpha angle measurements in two rounds. In each round, the three examiners independently reviewed all MRIs in random order to establish intrarater and interrater reliability. Correlation coefficients were calculated between pairs of alpha angle readings. Results:The pooled intrarater reliability when testing all 50 MRIs was 0.78 indicating strong agreement. The pooled intrarater reliability for only axial oblique images was 0.85, indicating almost perfect agreement. The interclass correlation coefficients for all 50 MRIs was 0.63–0.75, indicating strong agreement. The pooled interrater reliability using only the axial oblique images was 0.84, demonstrating near perfect agreement. Conclusions:The alpha angle is a reliable measure when calculated on axial oblique MRI. Our study indicates that almost perfect agreement exists when measuring the alpha angle on axial oblique MRI.
Sel-INT: A Runtime-Programmable Selective In-Band Network Telemetry System

It is known that by leveraging programmable data plane, in-band network telemetry (INT) can be realized to provide a powerful and promising method to collect realtime network statistics for monitoring and troubleshooting. However, existing INT implementations still exhibit a few drawbacks such as lack of runtime-programmability and relatively high overheads due to per-packet operation. In this work, we propose and design a runtime-programmable selective INT system, namely, Sel-INT, to resolve these issues. Specifically, we first design a runtime-programmable selective INT scheme based on protocol oblivious forwarding (POF), and then prototype our design by extending the famous OpenvSwitch (OVS) platform to obtain a software switch that supports Sel-INT and implementing a Data Analyzer to parse, extract and analyze the INT data. Our implementation of Sel-INT is verified and evaluated in a real network testbed that consists of a few stand-alone software switches. The experimental results demonstrate that Sel-INT can not only adjust the sampling rate of INT in runtime but also program the corresponding data types dynamically, and they also confirm that our proposal can ensure proper accuracy and timeliness for network monitoring while greatly reducing the overheads of INT.
A NEW DENSITY BASED SAMPLING TO ENHANCE DBSCAN CLUSTERING ALGORITHM

DBSCAN is one of the efficient density-based clustering algorithms. It is characterized by its ability to discover clusters with different shapes and sizes, and to separate noise and outliers. However, when the dataset contain different densities, DBSCAN clustering will be inefficient. In this paper, we propose an approach to enable DBSCAN to cluster dataset having different densities by preprocess the dataset to make it with one density level. This system composed of four stages: firstly, a new approach to separate dataset based on density is presented. Secondly, a new density biased sampling technique is proposed. Thirdly, the resulted sparse data from the last two stages is clustered with DBSCAN. Finally, the remaining data from sampling will be clustered with KNN. The experimental results on synthetic and real datasets on average show that the clustering of the proposed algorithm is better than that of DBSCAN by more than 7% and retains time complexity of DBSCAN.
Advantages of Having Users' Trust and Reputation Values on Data Sharing Process in Online Social Networks*

Online Social Networks (OSNs) are quite popular platforms that have an environment where a person can contact to another person without restricting their locations. Users get in contact with each other via sharing contents of data such as videos, photos, messages, and events. Shared contents do not include always only the user's information, who uploads the content to OSNs, but also include other users' information. This type of data sharing might cause serious problems on other people's lives, the type of content is called co-owned data. Current OSNs do not have systems in which there is an enforcement system to make a balance between co-owned data sharing and protection of users' privacy. One way to make the balance is to use reputation systems on co-owned data sharing process in which OSNs' users could be punished or awarded based on their own actions on the co-owned data sharing process. In this work, we propose a reputation system where trust values, which exist between OSNs' users, are used as feedback values. The beta reputation system is used as a groundwork to develop the proposed work's models.
Self-adaptive Stable Grasp of Two-finger End-effector: A Review

There have been growth demands for two-finger end-effector in agricultural and industrial because of the simple structure and control strategy. This paper reviews the human grasp behaviour, design of two-finger end-effectors, and research on self-adaptive stable grasp control. Human grasp behaviors such as grasp pattern and self-adaptive grasp provide useful information for humanoid two-finger end-effector. Most of the two-finger gripper and intelligent grasp strategy are focused on the stable grasp for regular object at present time. The self-adaptive stable grasp strategies of two-finger end-effector are presented by force-closure grasps strategy, contact stability grasp strategy and grasp synthesis strategy. Self-adaptive stable grasp synthesis strategy should consider the influence factor include geometric of contact surface and interaction of center of mass. In addition, the future work on two-finger self-adaptive stable grasp for 3D irregular object and 3D soft object is also reviewed.
High Dynamic Range Point Clouds for Real‐Time Relighting

Acquired 3D point clouds make possible quick modeling of virtual scenes from the real world. With modern 3D capture pipelines, each point sample often comes with additional attributes such as normal vector and color response. Although rendering and processing such data has been extensively studied, little attention has been devoted using the light transport hidden in the recorded per‐sample color response to relight virtual objects in visual effects (VFX) look‐dev or augmented reality (AR) scenarios. Typically, standard relighting environment exploits global environment maps together with a collection of local light probes to reflect the light mood of the real scene on the virtual object. We propose instead a unified spatial approximation of the radiance and visibility relationships present in the scene, in the form of a colored point cloud. To do so, our method relies on two core components: High Dynamic Range (HDR) expansion and real‐time Point‐Based Global Illumination (PBGI). First, since an acquired color point cloud typically comes in Low Dynamic Range (LDR) format, we boost it using a single HDR photo exemplar of the captured scene that can cover part of it. We perform this expansion efficiently by first expanding the dynamic range of a set of renderings of the point cloud and then projecting these renderings on the original cloud. At this stage, we propagate the expansion to the regions not covered by the renderings or with low‐quality dynamic range by solving a Poisson system. Then, at rendering time, we use the resulting HDR point cloud to relight virtual objects, providing a diffuse model of the indirect illumination propagated by the environment. To do so, we design a PBGI algorithm that exploits the GPU's geometry shader stage as well as a new mipmapping operator, tailored for G‐buffers, to achieve real‐time performances. As a result, our method can effectively relight virtual objects exhibiting diffuse and glossy physically‐based materials in real time. Furthermore, it accounts for the spatial embedding of the object within the 3D environment. We evaluate our approach on manufactured scenes to assess the error introduced at every step from the perfect ground truth. We also report experiments with real captured data, covering a range of capture technologies, from active scanning to multiview stereo reconstruction.