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1 |
Advanced digital signatures for preserving privacy and trust management in hierarchical heterogeneous IoT: Taxonomy, capabilities, and objectives
امضای دیجیتالی پیشرفته برای حفظ حریم خصوصی و مدیریت اعتماد در اینترنت اشیا ناهمگون سلسله مراتبی: طبقه بندی، قابلیت ها و اهداف-2022 Internet of Things (IoT) systems in different areas, such as manufacturing, transportation, and
healthcare, are the convergence of several technologies. There are many concerns about security
and privacy drawbacks in IoT systems. Apart from confidentiality supported by encryption
primitives, authenticity and non-repudiation are of utmost importance. IoT entities generally
use conventional digital signature schemes to achieve imperative goals. However, there are
some state-of-the-art digital signatures with more functionalities, IoT-friendly properties, and
privacy-preserving features.
This survey paper aims to accelerate the adoption of advanced digital signatures. We bridge the gap between the advanced theoretical digital signatures recently designed in cryptographic oriented papers and the applied IoT systems. It aids researchers in achieving more security, privacy as well as some unique functionality aspects. First, we illustrate the benefits of the hierarchical and heterogeneous IoT architecture supporting the end-edge-fog-cloud continuum accompanying blockchain technology. Second, our survey delves into five state-of-the-art digital signatures, including randomizable, keyless, double-authentication-prevention, sanitizable, and redactable schemes, that are aligned with entities in IoT systems. We provide an outline, taxonomy, comparison table, and diverse IoT-based use cases for each of them. Then, the integration of primitives and the relationship diagrams give guidelines to help select the appropriate advanced digital signatures and highlights how researchers can use them with different IoT entities for preserving privacy and management of trust. keywords: امضای دیجیتالی | حفظ حریم خصوصی اینترنت اشیا | بلاک چین | محاسبات ابری | Digital signature | IoT Privacy-preserving | Blockchain | Cloud computing |
مقاله انگلیسی |
2 |
In-home Health Monitoring using Floor-based Gait Tracking
نظارت بر سلامت در خانه با استفاده از ردیابی راه رفتن مبتنی بر کف-2022 Gait assessments are commonly used for clinical evaluations of neurocognitive disease progression and general wellness. However, gait measurements in clinical settings do not accurately
reflect gait in daily life. We present a non-wearable and unobtrusive method of detecting
gait parameters in the home through the vibrations in the floor created by footfalls. Gait
characteristics and gait asymmetry are estimated despite a low sensor density of 6.7 m2/sensor.
Features from each footfall vibration signal is extracted and used to estimate gait parameters
with gradient boosting regression and probabilistic models. Temporal gait asymmetry, locations
of the footfalls, and peak tibial acceleration asymmetry can be predicted with a root mean
square error of 0.013 s, 0.42 m, and 0.34 g respectively. This system allows for continuous
at-home monitoring of gait which aids in early detection of gait anomalies.
keywords: Gait monitoring | Smart home | Signal processing | Localization | Ground reaction force |
مقاله انگلیسی |
3 |
Facial micro-expressions as a soft biometric for person recognition
عبارات خرد مرتبط به عنوان یک بیومتریک نرم برای تشخیص افراد-2021 Soft biometrics, although not discriminant enough for person recognition provides additional information that aids traditional person recognition. Initially, attempts were made to integrate appearance-based
facial soft biometrics, such as facial marks, skin color, and hair color/style, but more recently behavior based facial soft biometrics, such as head dynamics, visual speech, and facial expressions have also been
studied. Facial expressions are further classified as macro and micro-expressions and most of the existing
studies using facial expressions as a soft biometric have focused on macro-expressions. Therefore, in this
study, we investigate the utility of micro-expressions as a soft biometric for person recognition. The proposed system is based on the fusion of traditional facial features that model the facial appearance with
soft biometric features that model the micro-expressions in an image sequence. We tested a texture based traditional feature extraction technique, two motion-based soft biometric techniques, and several
fusion methods at feature, rank, and decision level. The experiments were conducted on three commonly
used micro-expression databases and exhibit an improvement of around 5% identification rate when soft
biometric traits are fused with traditional face recognition at decision level. Keywords: Person recognition | Multi-modal biometrics | Soft biometrics | Micro-expressions |
مقاله انگلیسی |
4 |
Multi-view discriminant analysis with sample diversity for ECG biometric recognition
تجزیه و تحلیل تشخیص چند دیدگاهی با تنوع نمونه برای تشخیص بیومتریک ECG-2021 Soft biometrics, although not discriminant enough for person recognition provides additional information that aids traditional person recognition. Initially, attempts were made to integrate appearance-based
facial soft biometrics, such as facial marks, skin color, and hair color/style, but more recently behavior based facial soft biometrics, such as head dynamics, visual speech, and facial expressions have also been
studied. Facial expressions are further classified as macro and micro-expressions and most of the existing
studies using facial expressions as a soft biometric have focused on macro-expressions. Therefore, in this
study, we investigate the utility of micro-expressions as a soft biometric for person recognition. The proposed system is based on the fusion of traditional facial features that model the facial appearance with
soft biometric features that model the micro-expressions in an image sequence. We tested a texture based traditional feature extraction technique, two motion-based soft biometric techniques, and several
fusion methods at feature, rank, and decision level. The experiments were conducted on three commonly
used micro-expression databases and exhibit an improvement of around 5% identification rate when soft
biometric traits are fused with traditional face recognition at decision level. Keywords: Person recognition | Multi-modal biometrics | Soft biometrics | Micro-expressions |
مقاله انگلیسی |
5 |
ResTS: Residual Deep interpretable architecture for plant disease detection
ResTS: Residual Deep interpretable architecture for plant disease detection-2021 Recently many methods have been induced for plant disease detection by the influence of Deep Neural Networks in Computer Vision. However, the dearth of transparency in these types of research makes their acquisition in the real-world scenario less approving. We pro- pose an architecture named ResTS (Residual Teacher/Student) that can be used as visualization and a classification technique for diagnosis of the plant disease. ResTS is a tertiary adaptation of formerly suggested Teacher/Student architecture. ResTS is grounded on a Convolutional Neural Network (CNN) structure that comprises two classifiers (ResTeacher and ResStudent) and a decoder. This architecture trains both the classifiers in a reciprocal mode and the conveyed representation between ResTeacher and ResStudent is used as a proxy to envision the dominant areas in the image for categorization. The experiments have shown that the proposed structure ResTS (F1 score: 0.991) has surpassed the Tea- cher/Student architecture (F1 score: 0.972) and can yield finer visualizations of symptoms of the disease. Novel ResTS architecture incorporates the residual connections in all the constituents and it executes batch normalization after each convolution operation which is dissimilar to the formerly proposed Teacher/Student architecture for plant disease diag- nosis. Residual connections in ResTS help in preserving the gradients and circumvent the problem of vanishing or exploding gradients. In addition, batch normalization after each convolution operation aids in swift convergence and increased reliability. All test results are attained on the PlantVillage dataset comprising 54 306 images of 14 crop species.© 2021 China Agricultural University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Autoencoders | Xception | Deep Learning | Computer Vision | Agriculture |
مقاله انگلیسی |
6 |
Identification and differentiation of commercial and military explosives via high performance liquid chromatography – high resolution mass spectrometry (HPLC-HRMS), X-ray diffractometry (XRD) and X-ray fluorescence spectroscopy (XRF): Towards a forensic substance database on explosives
شناسایی و تمایز مواد منفجره تجاری و نظامی از طریق کروماتوگرافی مایع با کارایی بالا - طیف سنجی جرمی با وضوح بالا (HPLC-HRMS) ، پراش سنجی اشعه ایکس (XRD) و طیف سنجی فلورسانس اشعه ایکس (XRF): به سمت پایگاه داده مواد پزشکی قانونی در مورد مواد منفجره-2020 The identification of confiscated commercial and military explosives is a crucial step not only in the
uncovering of distribution pathways, but it also aids investigating officers in criminal casework. Even
though commercial and military explosives mainly rely on a small number of high-energy compounds, a
great variety of additives and synthesis by-products can be found that can differ depending on the brand,
manufacturer and application. This makes the identification of commercial and military explosives based
on their overall composition a promising approach that can be used to establish a pan-European Forensic
Substance Database on Explosives.
In this work, three analytical techniques were employed to analyze 36 samples of commercial and
military explosives from Germany and Switzerland. An HPLC-HRMS method was developed, using 27
analytes of interest that encompass high-energy compounds, synthesis by-products and additives. HPLCHRMS
and XRD were used to gather and confirm molecular information on each sample and XRF analyses
were carried out to gain insight on the elemental composition. Combining the results from all three
techniques, 41 different additives could be identified as being diagnostic analytes and all samples showed
a unique analytical fingerprint, which allows for a differentiation of the samples. Therefore, this work
presents a set of methods that can be used as a foundation for the creation and population of a database
on explosives that enables the assigning of specific formulations to certain brands, manufacturers and
countries of origin. Keywords: HPLC-HRMS | Powder XRD | XRF | Explosives | Commercial explosives | Military explosives |
مقاله انگلیسی |
7 |
Technology adoption and entrepreneurial orientation for rural women_ Evidence from India
پذیرش فناوری و جهت گیری کارآفرینی برای زنان روستایی: شواهدی از هند-2020 Information and communication technology (ICTs) have been proven to be an enabler for women empowerment, particularly for marginalized women. Policies have been formulated to link ICT with gender issues. The success of such policy initiatives largely depends on adoption intention because only ‘transplanting’ will not work. This evidence-based article with primary data established the covariance structure between the dimensions of access, ICT adoption intention and entrepreneurial orientation. This study highlights that different types of access like mental, material, skill and usage contribute significantly towards the adoption of ICT among rural women. Adoption of the ICT leads to innovation. Adoption intention is a booster for entrepreneurial orientation which aids micro-entrepreneurship. The findings of this study are significant because it connects technology adoption with the entrepreneurial intention of women micro-entrepreneurs. Keywords: ICT | Access | Adoption | Women | Entrepreneurship | India |
مقاله انگلیسی |
8 |
Opportunities and barriers for innovation and entrepreneurship in orphan drug development
فرصت ها و موانع نوآوری و کارآفرینی در توسعه داروهای یتیم-2020 Orphan diseases pose both a challenge to the global medical community and an opportunity for it to focus on global peace engineering and innovation. Where, any single orphan disease is rare, when taken as a whole they affect more than 250 million people throughout the world. This number by comparison is larger than the global number of cancer and AIDS patients. We add to the literature by mapping the available knowledge in the orphan drug development field and exploring the tensions at play for innovation and entrepreneurship in this field. We further add to the literature by providing a framework to review this field based on social systems theory. Our review highlights the gaps in research and proposes a path forward in understanding of and learning from the orphan drug development field. Keywords: Healthcare innovation | Orphan drugs | Rare diseases | Responsible innovation |
مقاله انگلیسی |
9 |
Evaluation of interventions focused on reducing propeller scarring by recreational boaters in Florida, USA
ارزیابی مداخلات متمرکز بر کاهش پروانه زخم توسط قایقران تفریحی در فلوریدا ، ایالات متحده -2020 Propeller scarring by recreational vessels is a known threat to seagrass meadows in Florida. Despite decades of
awareness about the problem, there has been little meaningful progress in addressing this largely preventable
stressor. We consider it preventable because it rests on human behaviors, which can be changed by education,
technology, social norms, and policy. However, past attempts to address seagrass scarring have rarely been
evaluated for effectiveness. Thus, very little guidance exists for natural resource managers, educators, and policy
makers responsible for allocating limited resources toward effective interventions. Using a social marketing
approach, we deployed two separate interventions, one education-based and the other cue-based (navigational
aids) in Florida, USA. We measured boater behavior and attitudes before and after the interventions to assess the
relative effectiveness of each. Navigational aids elicited a clear behavioral improvement across a broad crosssection
of boaters, while minimal effects were observed for the educational intervention. However, analyses
suggest the recreational boating audience can be segmented by factors such as experience level to better target
educational messages in future seagrass protection efforts. These results will assist seagrass managers, educators,
advocates, policy makers, and boating industry stakeholders in deploying an efficient combination of approaches
to better address propeller scarring in Florida’s seagrass meadows. Keywords: Community-based social marketing | Habitat protection | Environmental management | Coastal habitat | Coastal management | Boater education | Environmental awareness |
مقاله انگلیسی |
10 |
Six degree-of-freedom body-fixed hovering over unmapped asteroids via LIDAR altimetry and reinforcement meta-learning
حرکات ثابت شش درجه آزادی بدن بر روی سیارک های غیرقابل نقشه از طریق ارتفاع سنجی LIDAR و تقویت یادگیری متقابل-2020 We optimize a six degrees of freedom hovering policy using reinforcement meta-learning. The policy maps flash
LIDAR measurements directly to on/off spacecraft body-frame thrust commands, allowing hovering at a fixed
position and attitude in the asteroid body-fixed reference frame. Importantly, the policy does not require position
and velocity estimates, and can operate in environments with unknown dynamics, and without an asteroid
shape model or navigation aids. Indeed, during optimization the agent is confronted with a new randomly
generated asteroid for each episode, insuring that it does not learn an asteroids shape, texture, or environmental
dynamics. This allows the deployed policy to generalize well to novel asteroid characteristics, which we demonstrate
in our experiments. Moreover, our experiments show that the optimized policy adapts to actuator
failure and sensor noise. Although the policy is optimized using randomly generated synthetic asteroids, it is
tested on two shape models from actual asteroids: Bennu and Itokawa. We find that the policy generalizes well to
these shape models. The hovering controller has the potential to simplify mission planning by allowing asteroid
body-fixed hovering immediately upon the spacecrafts arrival to an asteroid. This in turn simplifies shape model
generation and allows resource mapping via remote sensing immediately upon arrival at the target asteroid. Keywords: Reinforcement learning | Asteroid missions | Hovering artificial intelligence | Autonomous maneuvers |
مقاله انگلیسی |