scholarly journals An Enhanced Inverse Filtering Methodology for Drive-By Frequency Identification of Bridges Using Smartphones in Real-Life Conditions

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 499-513
Author(s):  
Nima Shirzad-Ghaleroudkhani ◽  
Mustafa Gül
Keyword(s):  
Surface Roughness ◽  
Smart Cities ◽  
Real Life ◽  
Cost Effective ◽  
Vehicle Speed ◽  
Inverse Filtering ◽  
Novel Approach ◽  
Life Scale ◽  
Frequency Identification ◽  
Speed Effect

This paper develops an enhanced inverse filtering-based methodology for drive-by frequency identification of bridges using smartphones for real-life applications. As the vibration recorded on a vehicle is dominated by vehicle features including suspension system and speed as well as road roughness, inverse filtering aims at suppressing these effects through filtering out vehicle- and road-related features, thus mitigating a few of the significant challenges for the indirect identification of the bridge frequency. In the context of inverse filtering, a novel approach of constructing a database of vehicle vibrations for different speeds is presented to account for the vehicle speed effect on the performance of the method. In addition, an energy-based surface roughness criterion is proposed to consider surface roughness influence on the identification process. The successful performance of the methodology is investigated for different vehicle speeds and surface roughness levels. While most indirect bridge monitoring studies are investigated in numerical and laboratory conditions, this study proves the capability of the proposed methodology for two bridges in a real-life scale. Promising results collected using only a smartphone as the data acquisition device corroborate the fact that the proposed inverse filtering methodology could be employed in a crowdsourced framework for monitoring bridges at a global level in smart cities through a more cost-effective and efficient process.

scholarly journals A Chemistry-Oriented Cost-Effective Expert Team Formation in Social Networks

2021 ◽  
Author(s):  
◽  
Yashar Najaflou
Keyword(s):  
Social Networks ◽  
Real Life ◽  
Cost Effective ◽  
Communication Cost ◽  
Team Formation ◽  
Personnel Cost ◽  
Effective Teams ◽  
Novel Approach ◽  
Effective Manner ◽  
Expertise Level

<p>The growth of social networks in modern information systems has enabled the collaboration of experts at an unprecedented scale. Given a social network and a task consisting of a set of required skills, Team Formation (TF) aims at finding a team of experts who can cover the required skills and can communicate in an effective manner. However, this definition has been interpreted as the problem of finding teams with minimum communication cost which neglects two aspect of team formation in real life. The first is that in reality experts are multi-skilled, hence communication cost cannot be a fixed value and should vary according to the channels employed. The second ignored aspect is disregarding teams with high expertise level who can still satisfy the required communication level.  To tackle above mentioned issues, I introduce a dynamic formof communication for multi-facet relationships and use it to devise a novel approach called Chemistry Oriented Team Formation (ChemoTF) based on two new metrics; Chemistry Level and Expertise Level. Chemistry Level measures scale of communication required by the task andExpertise Level measures the overall expertise among potential teams filtered by Chemistry Level. Moreover, I adopt a personnel cost metric to filter costly teams. The experimental results on the corpus compiled for this purpose suggests that ChemoTF returns communicative and cost-effective teams with the highest expertise level compared to state-of-the-art algorithms. The corpus itself is a valuable output which contains comprehensive scholarly information in the field of computer science.</p>

scholarly journals A Chemistry-Oriented Cost-Effective Expert Team Formation in Social Networks

2021 ◽  
Author(s):  
◽  
Yashar Najaflou
Keyword(s):  
Social Networks ◽  
Real Life ◽  
Cost Effective ◽  
Communication Cost ◽  
Team Formation ◽  
Personnel Cost ◽  
Effective Teams ◽  
Novel Approach ◽  
Effective Manner ◽  
Expertise Level

<p>The growth of social networks in modern information systems has enabled the collaboration of experts at an unprecedented scale. Given a social network and a task consisting of a set of required skills, Team Formation (TF) aims at finding a team of experts who can cover the required skills and can communicate in an effective manner. However, this definition has been interpreted as the problem of finding teams with minimum communication cost which neglects two aspect of team formation in real life. The first is that in reality experts are multi-skilled, hence communication cost cannot be a fixed value and should vary according to the channels employed. The second ignored aspect is disregarding teams with high expertise level who can still satisfy the required communication level.  To tackle above mentioned issues, I introduce a dynamic formof communication for multi-facet relationships and use it to devise a novel approach called Chemistry Oriented Team Formation (ChemoTF) based on two new metrics; Chemistry Level and Expertise Level. Chemistry Level measures scale of communication required by the task andExpertise Level measures the overall expertise among potential teams filtered by Chemistry Level. Moreover, I adopt a personnel cost metric to filter costly teams. The experimental results on the corpus compiled for this purpose suggests that ChemoTF returns communicative and cost-effective teams with the highest expertise level compared to state-of-the-art algorithms. The corpus itself is a valuable output which contains comprehensive scholarly information in the field of computer science.</p>

A Novel Approach for the Treatment of Sialolithiasis that Preserves Salivary Duct Anatomy

2021 ◽  
pp. 000348942110189
Author(s):  
Gani Atilla Şengör ◽  
Ahmet Mert Bilgili
Keyword(s):  
Salivary Gland ◽  
Success Rate ◽  
Cost Effective ◽  
Complete Removal ◽  
Level Of Evidence ◽  
Invasive Approach ◽  
Pneumatic Lithotripsy ◽  
Novel Approach ◽  
Surgical Methods ◽  
Salivary Gland Stones

Objective: The sialendoscopy era in the treatment of salivary gland stones has reduced the use of classical surgical methods. However, the miniature ducts and tools may cause difficulties in removing large sialoliths. Therefore, invasive combined oral surgeries or gland resection may be considered. We searched for the most suitable method in order to stay in line with the minimally invasive approach that preserves the ductus anatomy, and that can reduce the surgical fears of patients. Materials and Methods: The study included 84 cases (23 parotid and 61 submandibular) in whom stones were fragmented by pneumatic lithotripsy and removed between January 2015 and January 2020. The parotid cases comprised 7 females and 16 males, and the submandibular cases comprised 25 females and 36 males. Intraductal lithotripsy was performed using pneumatic lithotripter. This study has fourth level of evidence. Results: Based on total number of cases (n = 84), success rate was 67/84 (79.7%) immediately after sialendoscopy, and overall success rate was 77/84 (91.6%). Based on number of stones treated (n = 111), our immediate success rate was 94/111 (84.6%), and overall success rate was 104/111 (93.7%). The success criteria were complete removal of the stone and fragments in a single sialendoscopy procedure and resolution of symptoms. Conclusions: We successfully treated salivary gland stones, including L3b stones, in our patient cohort with sialendoscopy combined with pneumatic lithotripsy. The lithotripsy method that we have adapted seems to be more useful and cost-effective compared to its alternatives. We were also able to preserve the ductus anatomy and relieve patients’ concerns. Level of Evidence: Level IV

scholarly journals New fractional approaches for n-polynomial P-convexity with applications in special function theory

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shu-Bo Chen ◽  
Saima Rashid ◽  
Muhammad Aslam Noor ◽  
Zakia Hammouch ◽  
Yu-Ming Chu
Keyword(s):  
Fractional Calculus ◽  
Convex Functions ◽  
Special Functions ◽  
Real Life ◽  
Fractional Integrals ◽  
Digamma Function ◽  
Novel Approach ◽  
Inequality Theory ◽  
New Strategy ◽  
Significant Mechanism

Abstract Inequality theory provides a significant mechanism for managing symmetrical aspects in real-life circumstances. The renowned distinguishing feature of integral inequalities and fractional calculus has a solid possibility to regulate continuous issues with high proficiency. This manuscript contributes to a captivating association of fractional calculus, special functions and convex functions. The authors develop a novel approach for investigating a new class of convex functions which is known as an n-polynomial $\mathcal{P}$ P -convex function. Meanwhile, considering two identities via generalized fractional integrals, provide several generalizations of the Hermite–Hadamard and Ostrowski type inequalities by employing the better approaches of Hölder and power-mean inequalities. By this new strategy, using the concept of n-polynomial $\mathcal{P}$ P -convexity we can evaluate several other classes of n-polynomial harmonically convex, n-polynomial convex, classical harmonically convex and classical convex functions as particular cases. In order to investigate the efficiency and supremacy of the suggested scheme regarding the fractional calculus, special functions and n-polynomial $\mathcal{P}$ P -convexity, we present two applications for the modified Bessel function and $\mathfrak{q}$ q -digamma function. Finally, these outcomes can evaluate the possible symmetric roles of the criterion that express the real phenomena of the problem.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

New Multi-View Classification Method with Uncertain Data

2021 ◽  
Vol 16 (1) ◽  
pp. 1-23
Author(s):  
Bo Liu ◽  
Haowen Zhong ◽  
Yanshan Xiao
Keyword(s):  
Learning Strategy ◽  
State Of The Art ◽  
Uncertain Data ◽  
Real Life ◽  
Support Vector ◽  
Classification Methods ◽  
Complementary Information ◽  
Novel Approach ◽  
Svm Model ◽  
Iterative Framework

Multi-view classification aims at designing a multi-view learning strategy to train a classifier from multi-view data, which are easily collected in practice. Most of the existing works focus on multi-view classification by assuming the multi-view data are collected with precise information. However, we always collect the uncertain multi-view data due to the collection process is corrupted with noise in real-life application. In this case, this article proposes a novel approach, called uncertain multi-view learning with support vector machine (UMV-SVM) to cope with the problem of multi-view learning with uncertain data. The method first enforces the agreement among all the views to seek complementary information of multi-view data and takes the uncertainty of the multi-view data into consideration by modeling reachability area of the noise. Then it proposes an iterative framework to solve the proposed UMV-SVM model such that we can obtain the multi-view classifier for prediction. Extensive experiments on real-life datasets have shown that the proposed UMV-SVM can achieve a better performance for uncertain multi-view classification in comparison to the state-of-the-art multi-view classification methods.

scholarly journals Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Network Architecture ◽  
Cost Effective ◽  
Sensor Data ◽  
Dense Layer ◽  
Gaseous Emissions ◽  
Multiple Sensors ◽  
Single Output ◽  
Novel Approach ◽  
Single Sensor

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.

scholarly journals A Framework for Assessing the Value of RFID Implementation by Tier-One Suppliers to Major Retailers

2008 ◽  
Vol 3 (1) ◽  
pp. 55-70
Author(s):  
Dharmaraj Veeramani ◽  
Jenny Tang ◽  
Alfonso Gutierrez
Keyword(s):  
Supply Chain ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Return On Investment ◽  
Real Life ◽  
Data Capture ◽  
Automatic Identification ◽  
Rfid Technology ◽  
Frequency Identification ◽  
The Impact

Radio frequency identification (RFID) is a rapidly evolving technology for automatic identification and data capture of products. One of the barriers to the adoption of RFID by organizations is difficulty in assessing the potential return on investment (ROI). Much of the research and analyses to date of ROI in implementing RFID technology have focused on the benefits to the retailer. There is a lack of a good understanding of the impact of RFID at upper echelons of the supply chain. In this paper, we present a framework and models for assessing the value of RFID implementation by tier-one suppliers to major retailers. We also discuss our real-life application of this framework to one of Wal-Mart’s top 100 suppliers

scholarly journals Implementation of Fused Filament Fabrication in Dentistry

2021 ◽  
Vol 11 (14) ◽  
pp. 6444
Author(s):  
Jörg Lüchtenborg ◽  
Felix Burkhardt ◽  
Julian Nold ◽  
Severin Rothlauf ◽  
Christian Wesemann ◽  
...  
Keyword(s):  
Fused Deposition Modeling ◽  
Present Report ◽  
Cost Effective ◽  
Great Promise ◽  
Temperature Sensitive ◽  
Fused Filament Fabrication ◽  
Digital Light Processing ◽  
Fused Deposition ◽  
Surgical Guides ◽  
Novel Approach

Additive manufacturing is becoming an increasingly important technique for the production of dental restorations and assistive devices. The most commonly used systems are based on vat polymerization, e.g., stereolithography (SLA) and digital light processing (DLP). In contrast, fused filament fabrication (FFF), also known under the brand name fused deposition modeling (FDM), is rarely applied in the dental field. This might be due to the reduced accuracy and resolution of FFF compared to vat polymerization. However, the use of FFF in the dental sector seems very promising for in-house production since it presents a cost-effective and straight forward method. The manufacturing of nearly ready-to-use parts with only minimal post-processing can be considered highly advantageous. Therefore, the objective was to implement FFF in a digital dental workflow. The present report demonstrates the production of surgical guides for implant insertion by FFF. Furthermore, a novel approach using a temperature-sensitive filament for bite registration plates holds great promise for a simplified workflow. In combination with a medical-grade filament, a multi-material impression tray was printed for optimized impression taking of edentulous patients. Compared to the conventional way, the printed thermoplastic material is pleasant to model and can allow clean and fast work on the patient.

In Situ: A Novel Approach for the Production of Micro Holes

2010 ◽  
Vol 126-128 ◽  
pp. 885-890
Author(s):  
K.P. Somashekhar ◽  
N. Ramachandran ◽  
Jose Mathew
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Feed Rate ◽  
Machining Parameters ◽  
Average Roughness ◽  
Arithmetic Average ◽  
Quantitative Correlation ◽  
Good Surface ◽  
Novel Approach ◽  
Micro Holes

This work is on the preparation of microelectrodes for μ-EDM operation using μ-WEDG process. Electrodes of Ø500 μm are fabricated with various discharge energy machining conditions. Effects of gap voltage, capacitance & feed rate on the surface finish of the electrodes and overcut of the thus produced micro holes are investigated. The profile of microelectrodes is measured using surface roughness tester with 2μm stylus interfaced with SURFPAK software. The study demonstrated that for brass electrodes an arithmetic average roughness value as low as 1.7μm and an overcut of 3 µm could be achieved. The significant machining parameters are found using ANOVA. Surface of the produced microelectrodes are examined using Scanning Electron Microscope. μ-WEDG process parameters could be adjusted to achieve good surface integrity on microelectrodes. Experimental results showed that the surface roughness of microelectrodes depended primarily on feed rate of the electrode. The observations showed the clear and quantitative correlation existing between the micrometer level surface quality and process parameters. The resulting microelectrodes are found to be of exceptionally high quality and could be used for μ- EDM operation on different types of work materials.

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