scholarly journals Similarity and automatic imitation

2021 ◽  
Author(s):  
Oliver Genschow ◽  
Emiel Cracco ◽  
Pieter Verbeke ◽  
Mareike Westfal ◽  
Jan Crusius
Keyword(s):  
Social Process ◽  
Material Constant ◽  
Stimulus Material ◽  
The Other ◽  
Perceived Similarity ◽  
Future Directions ◽  
Automatic Imitation ◽  
Wide Range ◽  
Interaction Partners

Individuals automatically imitate a wide range of different behaviors. Previous research suggests that imitation as a social process depends on the similarity between interaction partners. However, some of the experiments supporting this notion could not be replicated and all of the supporting experiments manipulated not only similarity between actor and observer, but also other features. Thus, the existing evidence leaves open whether similarity as such moderates automatic imitation. To directly test the similarity account, in four experiments, we manipulated participants’ focus on similarities or differences while holding the stimulus material constant. In Experiment 1, we presented participants with a hand and let them either focus on similarities, differences, or neutral aspects between their own hand and the other person’s hand. The results indicate that focusing on similarities increased perceived similarity between the own and the other person’s hand. In Experiments 2 to 4, we tested the hypothesis that focusing on similarities, as compared with differences, increases automatic imitation. Experiment 2 tested the basic effect and found support for our prediction. Experiment 3 and 4 replicated this finding with higher-powered samples. Exploratory investigations further suggest that it is a focus on differences that decreases automatic imitation, and not a focus on similarities that increases automatic imitation. Theoretical implications and future directions are discussed.

scholarly journals Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey

2020 ◽  
Author(s):  
Dinh C. Nguyen ◽  
Ming Dinh ◽  
Pubudu N. Pathirana ◽  
Aruna Seneviratne
Keyword(s):  
Public Health ◽  
Healthcare Systems ◽  
The Other ◽  
User Privacy ◽  
Future Directions ◽  
Public Health Emergencies ◽  
Wide Range ◽  
Drug Manufacturing ◽  
Novel Virus ◽  
The One

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

scholarly journals Blockchain and AI-based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey

2020 ◽  
Author(s):  
Dinh Nguyen ◽  
Ming Ding ◽  
Pubudu N. Pathirana ◽  
Aruna Seneviratne
Keyword(s):  
Public Health ◽  
Healthcare Systems ◽  
The Other ◽  
User Privacy ◽  
Future Directions ◽  
Public Health Emergencies ◽  
Wide Range ◽  
Drug Manufacturing ◽  
Novel Virus ◽  
The One

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

scholarly journals Blockchain and AI-based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey

2020 ◽  
Author(s):  
Dinh Nguyen ◽  
Ming Ding ◽  
Pubudu N. Pathirana ◽  
Aruna Seneviratne
Keyword(s):  
Public Health ◽  
Healthcare Systems ◽  
The Other ◽  
User Privacy ◽  
Future Directions ◽  
Public Health Emergencies ◽  
Wide Range ◽  
Drug Manufacturing ◽  
Novel Virus ◽  
The One

The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.

2D Color-Intensity Representation of Ultrasonic Thickness Gauge Measurements

2020 ◽  
pp. 1192-1198
Author(s):  
M.S. Mohammad ◽  
Tibebe Tesfaye ◽  
Kim Ki-Seong
Keyword(s):  
Cost Effective ◽  
The Other ◽  
Thickness Gauge ◽  
Color Intensity ◽  
Digital Readout ◽  
Flat Surfaces ◽  
Video Cameras ◽  
Wide Range ◽  
Cost Effective Alternative ◽  
Ultrasonic Thickness

Ultrasonic thickness gauges are easy to operate and reliable, and can be used to measure a wide range of thicknesses and inspect all engineering materials. Supplementing the simple ultrasonic thickness gauges that present results in either a digital readout or as an A-scan with systems that enable correlating the measured values to their positions on the inspected surface to produce a two-dimensional (2D) thickness representation can extend their benefits and provide a cost-effective alternative to expensive advanced C-scan machines. In previous work, the authors introduced a system for the positioning and mapping of the values measured by the ultrasonic thickness gauges and flaw detectors (Tesfaye et al. 2019). The system is an alternative to the systems that use mechanical scanners, encoders, and sophisticated UT machines. It used a camera to record the probe’s movement and a projected laser grid obtained by a laser pattern generator to locate the probe on the inspected surface. In this paper, a novel system is proposed to be applied to flat surfaces, in addition to overcoming the other limitations posed due to the use of the laser projection. The proposed system uses two video cameras, one to monitor the probe’s movement on the inspected surface and the other to capture the corresponding digital readout of the thickness gauge. The acquired images of the probe’s position and thickness gauge readout are processed to plot the measured data in a 2D color-coded map. The system is meant to be simpler and more effective than the previous development.

History of the Study of Apocrypha in Early Medieval England

2020 ◽  
Vol 48 (3-4) ◽  
pp. 13-26
Author(s):  
Brandon W. Hawk
Keyword(s):  
Old Testament ◽  
Medieval England ◽  
Medieval Period ◽  
Early Medieval ◽  
Future Directions ◽  
Early Judaism ◽  
Wide Range ◽  
History Of ◽  
The Subject ◽  
Early English

Literature written in England between about 500 and 1100 CE attests to a wide range of traditions, although it is clear that Christian sources were the most influential. Biblical apocrypha feature prominently across this corpus of literature, as early English authors clearly relied on a range of extra-biblical texts and traditions related to works under the umbrella of what have been called “Old Testament Pseudepigrapha” and “New Testament/Christian Apocrypha." While scholars of pseudepigrapha and apocrypha have long trained their eyes upon literature from the first few centuries of early Judaism and early Christianity, the medieval period has much to offer. This article presents a survey of significant developments and key threads in the history of scholarship on apocrypha in early medieval England. My purpose is not to offer a comprehensive bibliography, but to highlight major studies that have focused on the transmission of specific apocrypha, contributed to knowledge about medieval uses of apocrypha, and shaped the field from the nineteenth century up to the present. Bringing together major publications on the subject presents a striking picture of the state of the field as well as future directions.

A review on aversive Pavlovian-to-Instrumental transfer in humans

2020 ◽  
Author(s):  
Anna Gerlicher ◽  
Merel Kindt
Keyword(s):  
Avoidance Behavior ◽  
Neural Circuits ◽  
Transfer Effects ◽  
Future Directions ◽  
Transfer Paradigm ◽  
Wide Range ◽  
Threat Cues ◽  
Imminent Threat ◽  
Fear And Anxiety ◽  
Pathological Anxiety

A cue that indicates imminent threat elicits a wide range of physiological, hormonal, autonomic, cognitive, and emotional fear responses in humans and facilitates threat-specific avoidance behavior. The occurrence of a threat cue can, however, also have general motivational effects and affect behavior. That is, the encounter with a threat cue can increase our tendency to engage in general avoidance behavior that does neither terminate nor prevent the threat-cue or the threat itself. Furthermore, the encounter with a threat-cue can substantially reduce our likelihood to engage in behavior that leads to rewarding outcomes. Such general motivational effects of threat-cues on behavior can be informative about the transition from normal to pathological anxiety and could also explain the development of comorbid disorders, such as depression and substance abuse. Despite the unmistakable relevance of the motivational effects of threat for our understanding of anxiety disorders, their investigation is still in its infancy. Pavlovian-to-Instrumental transfer is one paradigm that allows us to investigate such motivational effects of threat cues. Here, we review studies investigating aversive transfer in humans and discuss recent results on the neural circuits mediating Pavlovian-to-Instrumental transfer effects. Finally, we discuss potential limitations of the transfer paradigm and future directions for employing Pavlovian-to-Instrumental transfer for the investigation of motivational effects of fear and anxiety.

p-Sulfonic acid calix[n]arene catalyzed synthesis of bioactive heterocycles: A review

2020 ◽  
Vol 24 ◽  
Author(s):  
Bubun Banerjee ◽  
Gurpreet Kaur ◽  
Navdeep Kaur
Keyword(s):  
Supramolecular Chemistry ◽  
Sulfonic Acid ◽  
Catalytic Efficiency ◽  
The Other ◽  
Reaction Conditions ◽  
Metal Free ◽  
Bioactive Scaffolds ◽  
Wide Range ◽  
Efficient Alternative ◽  
Bioactive Heterocycles

: Metal-free organocatalysts are becoming an important tool for the sustainable developments of various bioactive heterocycles. On the other hand, during last two decades, calix[n]arenes have been gaining considerable attention due to their wide range of applicability in the field of supramolecular chemistry. Recently, sulfonic acid functionalized calix[n] arenes are being employed as an efficient alternative catalyst for the synthesis of various bioactive scaffolds. In this review we have summarized the catalytic efficiency of p-sulfonic acid calix[n]arenes for the synthesis of diverse biologically promising scaffolds under various reaction conditions. There is no such review available in the literature showing the catalytic applicability of p-sulfonic acid calix[n]arenes. Therefore, we strongly believe that this review will surely attract those researchers who are interested about this fascinating organocatalyst.

Automatic Vulnerability Detection in Embedded Devices and Firmware

2021 ◽  
Vol 54 (2) ◽  
pp. 1-42
Author(s):  
Abdullah Qasem ◽  
Paria Shirani ◽  
Mourad Debbabi ◽  
Lingyu Wang ◽  
Bernard Lebel ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Symbolic Execution ◽  
Vital Role ◽  
Security And Privacy ◽  
Embedded Devices ◽  
Security Vulnerabilities ◽  
Future Directions ◽  
Hybrid Approaches ◽  
Wide Range ◽  
The Internet Of Things

In the era of the internet of things (IoT), software-enabled inter-connected devices are of paramount importance. The embedded systems are very frequently used in both security and privacy-sensitive applications. However, the underlying software (a.k.a. firmware) very often suffers from a wide range of security vulnerabilities, mainly due to their outdated systems or reusing existing vulnerable libraries; which is evident by the surprising rise in the number of attacks against embedded systems. Therefore, to protect those embedded systems, detecting the presence of vulnerabilities in the large pool of embedded devices and their firmware plays a vital role. To this end, there exist several approaches to identify and trigger potential vulnerabilities within deployed embedded systems firmware. In this survey, we provide a comprehensive review of the state-of-the-art proposals, which detect vulnerabilities in embedded systems and firmware images by employing various analysis techniques, including static analysis, dynamic analysis, symbolic execution, and hybrid approaches. Furthermore, we perform both quantitative and qualitative comparisons among the surveyed approaches. Moreover, we devise taxonomies based on the applications of those approaches, the features used in the literature, and the type of the analysis. Finally, we identify the unresolved challenges and discuss possible future directions in this field of research.

scholarly journals Density Guarantee on Finding Multiple Subgraphs and Subtensors

2021 ◽  
Vol 15 (5) ◽  
pp. 1-32
Author(s):  
Quang-huy Duong ◽  
Heri Ramampiaro ◽  
Kjetil Nørvåg ◽  
Thu-lan Dam
Keyword(s):  
Lower Bound ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Exact Methods ◽  
Practical Solution ◽  
Novel Approach ◽  
Wide Range ◽  
Real World Datasets ◽  
Tensor Data

Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used for detecting dense subregions due to the complexity of the exact methods. Existing algorithms are generally efficient for dense subtensor and subgraph detection, and can perform well in many applications. However, most of the existing works utilize the state-or-the-art greedy 2-approximation algorithm to capably provide solutions with a loose theoretical density guarantee. The main drawback of most of these algorithms is that they can estimate only one subtensor, or subgraph, at a time, with a low guarantee on its density. While some methods can, on the other hand, estimate multiple subtensors, they can give a guarantee on the density with respect to the input tensor for the first estimated subsensor only. We address these drawbacks by providing both theoretical and practical solution for estimating multiple dense subtensors in tensor data and giving a higher lower bound of the density. In particular, we guarantee and prove a higher bound of the lower-bound density of the estimated subgraph and subtensors. We also propose a novel approach to show that there are multiple dense subtensors with a guarantee on its density that is greater than the lower bound used in the state-of-the-art algorithms. We evaluate our approach with extensive experiments on several real-world datasets, which demonstrates its efficiency and feasibility.

scholarly journals Grasp to See—Object Classification Using Flexion Glove with Support Vector Machine

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1461
Author(s):  
Shun-Hsin Yu ◽  
Jen-Shuo Chang ◽  
Chia-Hung Dylan Tsai
Keyword(s):  
Support Vector Machine ◽  
Daily Life ◽  
Object Classification ◽  
Target Object ◽  
The Other ◽  
Support Vector ◽  
Wide Range ◽  
Dark Space ◽  
Flex Sensors ◽  
Shape And Size

This paper proposes an object classification method using a flexion glove and machine learning. The classification is performed based on the information obtained from a single grasp on a target object. The flexion glove is developed with five flex sensors mounted on five finger sleeves, and is used for measuring the flexion of individual fingers while grasping an object. Flexion signals are divided into three phases, and they are the phases of picking, holding and releasing, respectively. Grasping features are extracted from the phase of holding for training the support vector machine. Two sets of objects are prepared for the classification test. One is printed-object set and the other is daily-life object set. The printed-object set is for investigating the patterns of grasping with specified shape and size, while the daily-life object set includes nine objects randomly chosen from daily life for demonstrating that the proposed method can be used to identify a wide range of objects. According to the results, the accuracy of the classifications are achieved 95.56% and 88.89% for the sets of printed objects and daily-life objects, respectively. A flexion glove which can perform object classification is successfully developed in this work and is aimed at potential grasp-to-see applications, such as visual impairment aid and recognition in dark space.

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