scholarly journals Automated Evaluation of Secure Route Discovery in MANET Protocols

2008 ◽  
pp. 26-41 ◽  
Author(s):  
Todd R. Andel ◽  
Alec Yasinsac
Keyword(s):  
Route Discovery ◽  
Automated Evaluation

DEVELOPMENT OF AUTOMATED EVALUATION OF POSITIONING ACCURACY FOR SPECIALIZED NETWORKS’ POINTS IN TRILATERATION NETWORKS

2020 ◽  
Author(s):  
Мурат Газизович Мустафин ◽  
Глеб Андреевич Фролов
Keyword(s):  
Coordinate System ◽  
Visual Basic ◽  
Microsoft Excel ◽  
Positioning Accuracy ◽  
Automated Evaluation ◽  
Visual Basic For Applications ◽  
Multiple Configurations

В данной работе рассмотрен принцип работы созданного алгоритма, позволяющего автоматически определять среднюю квадратическую погрешность планового положения пунктов сетей трилатерации и представлены результаты автоматизации данного процесса при различных конфигурациях сети, с использованием пакетов Microsoft Excel, Visual Basic for Applications. This paper presents automatic solution for evaluating accuracy of positioning for specialized networks’ points in a plane coordinate system. The paper presents results of automation of this process through analysis of multiple configurations of trilateral networks using Microsoft Excel, Visual Basic for Applications.

Language Features for Automated Evaluation of Cognitive Behavior Psychotherapy Sessions

2018 ◽  
Author(s):  
Nikolaos Flemotomos ◽  
Victor Martinez ◽  
James Gibson ◽  
David Atkins ◽  
Torrey Creed ◽  
...  
Keyword(s):  
Cognitive Behavior ◽  
Automated Evaluation

CALDUEL: Cost and Load overhead Reduction for Route Discovery in LOAD Protocol

2015 ◽  
Vol 2 (2) ◽  
pp. 33-42
Author(s):  
A. Dalvin Vinoth Kumar ◽  
◽  
P.D. Sheba Kezia Malarchelvi ◽  
L. Arockiam ◽  
◽  
...  
Keyword(s):  
Route Discovery

scholarly journals How Do Machines Learn? Artificial Intelligence as a New Era in Medicine

2021 ◽  
Vol 11 (1) ◽  
pp. 32
Author(s):  
Oliwia Koteluk ◽  
Adrian Wartecki ◽  
Sylwia Mazurek ◽  
Iga Kołodziejczak ◽  
Andrzej Mackiewicz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Medical Data ◽  
General Process ◽  
New Era ◽  
Automated Evaluation ◽  
Machine Learning Applications ◽  
And Training ◽  
Current Standards

With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to make faster and more correct decisions and improving current standards of treatment. Today, machines can analyze, learn, communicate, and understand processed data and are used in health care increasingly. This review explains different models and the general process of machine learning and training the algorithms. Furthermore, it summarizes the most useful machine learning applications and tools in different branches of medicine and health care (radiology, pathology, pharmacology, infectious diseases, personalized decision making, and many others). The review also addresses the futuristic prospects and threats of applying artificial intelligence as an advanced, automated medicine tool.

An enhanced architecture for route discovery and load balancing in WSN

2021 ◽  
Author(s):  
Mandeep Kaur ◽  
Amit Gupta ◽  
Balwinder Singh Sohi
Keyword(s):  
Load Balancing ◽  
Route Discovery

scholarly journals Collision Avoidance Geographic P2P-RPL in Multi-Hop Indoor Wireless Networks

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1484
Author(s):  
Yunyoung Choi ◽  
Jaehyung Park ◽  
Jiwon Jung ◽  
Younggoo Kwon
Keyword(s):  
Energy Consumption ◽  
Collision Avoidance ◽  
Energy Efficient ◽  
Convergence Time ◽  
Location Information ◽  
Route Discovery ◽  
Localization Algorithm ◽  
Control Packet ◽  
Network Convergence ◽  
Routing Control

In home and building automation applications, wireless sensor devices need to be connected via unreliable wireless links within a few hundred milliseconds. Routing protocols in Low-power and Lossy Networks (LLNs) need to support reliable data transmission with an energy-efficient manner and short routing convergence time. IETF standardized the Point-to-Point RPL (P2P-RPL) routing protocol, in which P2P-RPL propagates the route discovery messages over the whole network. This leads to significant routing control packet overhead and a large amount of energy consumption. P2P-RPL uses the trickle algorithm to control the transmission rate of routing control packets. The non-deterministic message suppression nature of the trickle algorithm may generate a sub-optimal routing path. The listen-only period of the trickle algorithm may lead to a long network convergence time. In this paper, we propose Collision Avoidance Geographic P2P-RPL, which achieves energy-efficient P2P data delivery with a fast routing request procedure. The proposed algorithm uses the location information to limit the network search space for the desired route discovery to a smaller location-constrained forwarding zone. The Collision Avoidance Geographic P2P-RPL also dynamically selects the listen-only period of the trickle timer algorithm based on the transmission priority related to geographic position information. The location information of each node is obtained from the Impulse-Response Ultra-WideBand (IR-UWB)-based cooperative multi-hop self localization algorithm. We implement Collision Avoidance Geographic P2P-RPL on Contiki OS, an open-source operating system for LLNs and the Internet of Things. The performance results show that the Collision Avoidance Geographic P2P-RPL reduced the routing control packet overheads, energy consumption, and network convergence time significantly. The cooperative multi-hop self localization algorithm improved the practical implementation characteristics of the P2P-RPL protocol in real world environments. The collision avoidance algorithm using the dynamic trickle timer increased the operation efficiency of the P2P-RPL under various wireless channel conditions with a location-constrained routing space.

scholarly journals Automated evaluation of the surface point quality in dimensional X-ray computed tomography

2020 ◽  
Vol 87 (2) ◽  
pp. 111-121 ◽  
Author(s):  
Andreas Michael Müller ◽  
Lorenz Butzhammer ◽  
Florian Wohlgemuth ◽  
Tino Hausotte
Keyword(s):  
Computed Tomography ◽  
Surface Point ◽  
Random Measurement Error ◽  
X Ray ◽  
Random Measurement ◽  
Automated Evaluation ◽  
Dimensional Measurements ◽  
X Ray Computed ◽  
Model Measurement

AbstractX-ray computed tomography (CT) enables dimensional measurements of numerous measurands with a single scan, including the measurement of inner structures. However, measurement artefacts complicate the applicability of the technology in some cases. This paper presents a methodology to assess the surface point quality of computed tomography measurements without the requirement of a CAD model. Measurement artefacts lowering the surface point quality can therefore automatically be detected. The correlation of quality values with the random measurement error is demonstrated. The presented method can in principle be used to weight single fit points to reduce the measurement uncertainty of CT measurements.

scholarly journals Sensors in the Autoclave-Modelling and Implementation of the IoT Steam Sterilization Procedure Counter

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 510
Author(s):  
Lukas Boehler ◽  
Mateusz Daniol ◽  
Ryszard Sroka ◽  
Dominik Osinski ◽  
Anton Keller
Keyword(s):  
The Body ◽  
Surgical Instruments ◽  
Sensor System ◽  
Temperature Profiles ◽  
Measured Temperature ◽  
Steam Sterilization ◽  
Automated Evaluation ◽  
Normative Requirements ◽  
Thermal Simulations ◽  
The Relationship

Surgical procedures involve major risks, as pathogens can enter the body unhindered. To prevent this, most surgical instruments and implants are sterilized. However, ensuring that this process is carried out safely and according to the normative requirements is not a trivial task. This study aims to develop a sensor system that can automatically detect successful steam sterilization on the basis of the measured temperature profiles. This can be achieved only when the relationship between the temperature on the surface of the tool and the temperature at the measurement point inside the tool is known. To find this relationship, the thermodynamic model of the system has been developed. Simulated results of thermal simulations were compared with the acquired temperature profiles to verify the correctness of the model. Simulated temperature profiles are in accordance with the measured temperature profiles, thus the developed model can be used in the process of further development of the system as well as for the development of algorithms for automated evaluation of the sterilization process. Although the developed sensor system proved that the detection of sterilization cycles can be automated, further studies that address the possibility of optimization of the system in terms of geometrical dimensions, used materials, and processing algorithms will be of significant importance for the potential commercialization of the presented solution.

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