scholarly journals Design of an Intelligent Approach on Capsule Networks to Detect Forged Images

2021 ◽  
Vol 3 (3) ◽  
pp. 205-221
Author(s):  
J. Samuel Manoharan
Keyword(s):  
Performance Metrics ◽  
Total Error ◽  
Research Work ◽  
Modern Technology ◽  
Forgery Detection ◽  
Efficient Manner ◽  
Total Error Rate ◽  
Reference Images ◽  
Image Separation ◽  
Intelligent Approach

Forgeries have recently become more prevalent in the society as a result of recent improvements in media generation technologies. In real-time, modern technology allows for the creation of a forged version of a single image obtained from a social network. Forgery detection algorithms have been created for a variety of areas; however they quickly become obsolete as new attack types exist. This paper presents a unique image forgery detection strategy based on deep learning algorithms. The proposed approach employs a convolutional neural network (CNN) to produce histogram representations from input RGB color images, which are then utilized to detect image forgeries. With the image separation method and copy-move detection applications in mind, the proposed CNN is combined with an intelligent approach and histogram mapping. It is used to detect fake or true images at the initial stage of our proposed work. Besides, it is specially designed for performing feature extraction in image layer separation with the help of CNN model. To capture both geographical and histogram information and the likelihood of presence at the same time, we use vectors in our dynamic capsule networks to detect the forgery kernels from reference images. The proposed research work integrates the intelligence with a feature engineering approach in an efficient manner. They are well-known and efficient in the identification of forged images. The performance metrics such as accuracy, recall, precision, and half total error rate (HTER) are computed and tabulated with the graph plot.

scholarly journals Dynamic Link Failure Detection using Robust Virus Swarm Routing Protocol in Wireless Sensor Network

2019 ◽  
Vol 8 (2) ◽  
pp. 1574-1578
Keyword(s):  
Routing Protocol ◽  
Performance Metrics ◽  
Research Work ◽  
Failure Detection ◽  
Wireless Sensor ◽  
Link Failure ◽  
Efficient Manner ◽  
Link Failures ◽  
Network Failure ◽  
Available Energy

Wireless Sensor Networks (WSN) gets weak due to node failures because of different reasons like intervention and faults that arise in communication. These kind of failures makes the entire network failure or disconnect part of the network leading to link failure. Routing protocols are responsible to find the best route to destination, because link failure minimizes the entire quality of service. Hence, there exist a need to find the preeminent route between source and destination which makes the communication in a efficient manner. Optimization started playing a major role in research, specifically in mining and networking issues. This paper aims to propose a optimization based routing protocol namely robust virus swarm routing protocol in order to effectively detect the link failures to find the alternative path and efficiently utilize the available energy to extend the network lifetime. The proposed protocol works by utilizing the dissemination and infection method followed by virus which defends the host-cell for the survival and progression. This research work uses the benchmark performance metrics to evaluate the proposed protocol against the existing protocols in the simulator NS2. The result shows that the proposed protocol outperforms the existing protocols in terms of all the metrics.

Modeling and analysis of impact energy absorber by using ls dyna

2015 ◽  
Vol 12 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Adik Yadao ◽  
R. S. Hingole
Keyword(s):  
Impact Energy ◽  
Material Properties ◽  
Research Work ◽  
Cad Model ◽  
Post Processing ◽  
Passenger Compartment ◽  
Efficient Manner ◽  
Energy Absorber ◽  
Modeling And Analysis ◽  
Energy Absorbing

Today’s car is one of the most important things in everyone’s life .Every person wants to have his or her own car but the question that arises in each buyer’s mind is whether the vehicle is safe enough to spend so much of money so it is the responsibility of an mechanical engineer to make the vehical comfortable and at the Same time safer. Now a days automakers are coming with various energy absorbing devices such as crush box, door beams etc. this energy absorbing device s prove to be very useful in reducing the amount force that is being transmitted to the occupant. In this we are using impact energy absorber in efficient manner as compare to earlier. The various steps involved in this project starting from developing the cad model of this inner impact energy absorber using the CAD software CATIA V5 R19. Then pre-processing is carried out in HYPERMESH 11.0 which includes assigning material, properties, boundary conditions such as contacts, constraints etc. LS-DYNA971 is used as a solver and LS-POST is used for the post processing and results obtained are compared to the standards. By carrying out this idea it has been observed that there is a considerable amount of energy that is being absorbed by this energy-absorbing device. Along with this energy absorption, the intrusion in passenger compartment is also reduced by considerable amount. So for safer and comfortable car with inner impact energy absorber is one of the best options available. This will get implement by this research work.

scholarly journals Performance evaluation and comparison study of adaptive MANET service location and discovery protocols for highly dynamic environments

2022 ◽  
Vol 2022 (1) ◽  
Author(s):  
Ghassen Ben Brahim ◽  
Nazeeruddin Mohammad ◽  
Wassim El-Hajj ◽  
Gerard Parr ◽  
Bryan Scotney
Keyword(s):  
Service Discovery ◽  
Ad Hoc ◽  
Performance Metrics ◽  
Research Work ◽  
Communication Overhead ◽  
Multimedia Networks ◽  
Service Availability ◽  
Critical Requirement ◽  
Hoc Networks ◽  
Service Location

AbstractA critical requirement in Mobile Ad Hoc Networks (MANETs) is its ability to automatically discover existing services as well as their locations. Several solutions have been proposed in various communication domains which could be classified into two categories: (1) directory based, and (2) directory-less. The former is efficient but suffers from the amount of control messages being exchanged to maintain all directories in an agile environment. However, the latter approach attempts to reduce the amount of control messages to update directories, by simply sending broadcast messages to discover services; which is also a non-desirable approach in MANETs. This research work builds on top of our prior work (Nazeeruddin et al. in IFIP/IEEE international conference on management of multimedia networks and services, Springer, Berlin, 2006)) where we introduced a new efficient protocol for service discovery in MANETs (MSLD); a lightweight, robust, scalable, and flexible protocol which supports node heterogeneity and dynamically adapts to network changes while not flooding the network with extra protocol messages—a major challenge in today’s network environments, such as Internet of Things (IoT). Extensive simulations study was conducted on MSLD to: (1) initially evaluate its performance in terms of latency, service availability, and overhead messages, then (2) compare its performance to Dir-Based, Dir-less, and PDP protocols under various network conditions. For most performance metrics, simulation results show that MSLD outperforms Dir-Based, Dir-less, and PDP by either matching or achieving high service availability, low service discovery latency, and considerably less communication overhead.

scholarly journals Segmentation of thyroid nodules using Improvised U-Net Architecture

2020 ◽  
Vol 9 (8) ◽  
pp. 56-60
Keyword(s):  
Thyroid Nodules ◽  
Performance Metrics ◽  
Automatic Segmentation ◽  
Research Work ◽  
Ultrasound Image ◽  
True Positive Rate ◽  
Medical Image Segmentation ◽  
Common Disease ◽  
Low Resolution ◽  
Feature Map

Thyroid nodules are considered as most common disease found in adults and thyroid cancer has increased over the years rapidly. Further automatic segmentation for ultrasound image is quite difficult due to the image poor quality, hence several researcher have focused and observed that U-Net achieves significant performance in medical image segmentation. However U-net faces the problem of low resolution which causes smoothness in image, hence in this research work we have proposed improvised U-Net which helps in achieving the better performance. The main aim of this research work is to achieve the probable Region of Interest through segmentation with better efficiency. In order to achieve that Improvised U-Net develops two distinctive feature map i.e. High level feature Map and low level feature map to avoid the problem of low resolution. Further proposed model is evaluated considering the standard dataset based on performance metrics such as Dice Coefficient and True positive Rate. Moreover our model achieves better performance than the existing model.

scholarly journals Financial Control Systems and Financial Systems Theory: Free Cash Flow and Profitability Nexus: a Comparative Study of Manufacturing Firms in Nigeria and Ghana

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Cash Flow ◽  
Net Present Value ◽  
Performance Metrics ◽  
Positive Impact ◽  
Research Work ◽  
Manufacturing Firms ◽  
Free Cash Flow ◽  
Estimation Model ◽  
Financial Systems ◽  
The Impact

In Financial Systems, the impact of Free Cash Flow (FCF) on the performance of a company has been in the center of academic discourse in recent years. Several studies have tried to ascertain the nature and magnitude of the relationship between free cash flow and firm profitability with conflicting results coming from different scholars. The main objective of this research work was to examine the impact of FCF on the profitability of quoted manufacturing firms in the Nigerian and Ghana stock exchanges. Data were pooled from twenty (20) different companies (ten each from Nigeria and Ghana) for a period of six years (2012 – 2017). A panel data estimation model was used to measure the impact of FCF and other performance metrics on the Return on Assets (ROA), which is our chosen profitability measure. The results show a positive but insignificant relationship between FCF and ROA both for Ghana and Nigerian manufacturing firms. Also, sales growth showed a positive impact on profitability of both countries while leverage negatively impacted on profitability. with Ghana being significant at 5%. The implication of the findings of the study is that it makes no business sense for companies to keep piling up excess funds beyond that which is needed for transactional purposes. The similarity between the results from Ghana and Nigeria in most of the variables shows that the findings of this study can be generalized to other countries. Based on the findings of the study, we recommend that the management of companies should strive to keep only the minimum needed free cash flow while the rest should be invested in other projects with positive net present value

scholarly journals Dragos Gheorghiu, Livia Stefan, Immersing into the Past: an Augmented Reality Method to Link Tangible and Intangible Heritage

2020 ◽  
Vol 8 (2) ◽  
pp. 91-102
Author(s):  
Dragos Gheorghiu ◽  
Livia Stefan
Keyword(s):  
Augmented Reality ◽  
Research Work ◽  
Modern Method ◽  
Sufficient Information ◽  
Efficient Manner ◽  
The Past ◽  
Intangible Heritage ◽  
Points Of Interest ◽  
Local Material ◽  
World Information

The current IT and digital technologies such as Mobile Augmented Reality (MAR) enable the overlap of digital and real world information in relation with a topic, in an engaging and efficient manner, and therefore can be used to store intangible heritage and to study it in the context as well. The current paper refers to such an augmentation of cultural information, performed at the Kallatis site, whose ruins, at present mostly covered by the modern town, do not offer sufficient information on the complexity of the Greek civilization. The implementation of a MAR application consisted in defining several points of interest of the important local archaeologic discoveries, which can trigger, for the visitors using our application, an augmentation of the historical site with images and videos. With the current research work, the authors propose and demonstrate that a mobile MAR application can constitute a modern method for providing visitors with an immersive and holistic experience for understanding the local material and intangible heritage.

scholarly journals Structure, Function and Historical Importance of Watermills in the Swat Valley

2020 ◽  
Vol V (III) ◽  
pp. 237-245
Author(s):  
Faisal Khan ◽  
Junaid Babar ◽  
Zahir Hussain
Keyword(s):  
Cultural Context ◽  
Qualitative Method ◽  
Research Work ◽  
Modern Technology ◽  
Ancient Technology ◽  
History Of ◽  
Swat Valley ◽  
And Function ◽  
Mode Of Production

The paper deals with the architecture and function of watermills in Swat valley. Watermill is a seldom-used term; however, it has played a significant role in the socio-cultural and economic lives of people in the past. This research work explores the case study of water mills in the Swat region. It examined in detail its processing and operation. The watermill was not only an instrument used for grinding purposes but also determined the mode of production, class system and social values of people. Modern technology has though changed people's behaviors and social formations up to a large extent, but it couldn't erase people's memories and history. A qualitative method has been used for conducting this research work. An ethnic-archaeological method was focused on recording the history of this tremendous ancient technology which contributed widely to the socio-cultural context of people.

scholarly journals Text Input in Virtual Reality: A Preliminary Evaluation of the Drum-Like VR Keyboard

Technologies ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 31 ◽  
Author(s):  
Costas Boletsis ◽  
Stian Kongsvik
Keyword(s):  
Virtual Reality ◽  
User Experience ◽  
Total Error ◽  
Preliminary Evaluation ◽  
Text Entry ◽  
Entry Rate ◽  
Drum Set ◽  
Text Input ◽  
Total Error Rate ◽  
Experience Questionnaire

The drum-like virtual reality (VR) keyboard is a contemporary, controller-based interface for text input in VR that uses a drum set metaphor. The controllers are used as sticks which, through downward movements, “press” the keys of the virtual keyboard. In this work, a preliminary feasibility study of the drum-like VR keyboard is described, focusing on the text entry rate and accuracy as well as its usability and the user experience it offers. Seventeen participants evaluated the drum-like VR keyboard by having a typing session and completing a usability and a user experience questionnaire. The interface achieved a good usability score, positive experiential feedback around its entertaining and immersive qualities, a satisfying text entry rate (24.61 words-per-minute), as well as moderate-to-high total error rate (7.2%) that can probably be further improved in future studies. The work provides strong indications that the drum-like VR keyboard can be an effective and entertaining way to type in VR.

scholarly journals Real-Time Predictive Analytics for Sepsis Level and Therapeutic Plans in Intensive Care Medicine

2014 ◽  
Vol 9 (3) ◽  
pp. 36-54 ◽  
Author(s):  
João M. C. Gonçalves ◽  
Filipe Portela ◽  
Manuel F. Santos ◽  
Álvaro Silva ◽  
José Machado ◽  
...  
Keyword(s):  
Intensive Care ◽  
Predictive Analytics ◽  
Total Error ◽  
Confusion Matrix ◽  
Rate Sensitivity ◽  
Great Accuracy ◽  
Support Vector ◽  
Classification Models ◽  
Learning Context ◽  
Total Error Rate

Optimal treatments for patients with microbiological problems depend significantly on the ability of the attending physicians to predict sepsis level. A set of Data Mining (DM) models has been developed using forecasting techniques and classification models to aid decision making by physicians about the appropriate, and most effective, therapeutic plan to adopt in specific situations. A combination of Decision Trees, Support Vector Machines and Naïve Bayes classifier were being used to generate the DM models. Confusion Matrix, including associated metrics, and Cross-validation were used to evaluate the models. Associated metrics used to identify the most relevant measures to predict sepsis level and treatment procedures include the analysis of the total error rate, sensitivity, specificity, and accuracy measures. The data used in DM models were collected at the Intensive Care Unit of the Centro Hospitalar do Porto, in Oporto, Portugal. Encapsulated within a supervised learning context, classification models were applied to predict sepsis level and direct the therapeutic plan for patients with sepsis. This work concludes that it was possible to predict sepsis level (2nd and 3rd) with great accuracy (accuracy: 100%), but not for the therapeutic plan (best accuracy level: 62.8%).

scholarly journals Evaluation of CMIP5 Global Climate Models for Simulating Climatological Temperature and Precipitation for Southeast Asia

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Suchada Kamworapan ◽  
Chinnawat Surussavadee
Keyword(s):  
Southeast Asia ◽  
Climate Models ◽  
Performance Metrics ◽  
Global Climate ◽  
Total Error ◽  
Coupled Model ◽  
Global Climate Models ◽  
Ensemble Average ◽  
Temperature And Precipitation ◽  
Intercomparison Project

This study evaluates the performances of all forty different global climate models (GCMs) that participate in the Coupled Model Intercomparison Project Phase 5 (CMIP5) for simulating climatological temperature and precipitation for Southeast Asia. Historical simulations of climatological temperature and precipitation of the 40 GCMs for the 40-year period of 1960–1999 for both land and sea and those for the century of 1901–1999 for land are evaluated using observation and reanalysis datasets. Nineteen different performance metrics are employed. The results show that the performances of different GCMs vary greatly. CNRM-CM5-2 performs best among the 40 GCMs, where its total error is 3.25 times less than that of GCM performing worst. The performance of CNRM-CM5-2 is compared with those of the ensemble average of all 40 GCMs (40-GCM-Ensemble) and the ensemble average of the 6 best GCMs (6-GCM-Ensemble) for four categories, i.e., temperature only, precipitation only, land only, and sea only. While 40-GCM-Ensemble performs best for temperature, 6-GCM-Ensemble performs best for precipitation. 6-GCM-Ensemble performs best for temperature and precipitation simulations over sea, whereas CNRM-CM5-2 performs best over land. Overall results show that 6-GCM-Ensemble performs best and is followed by CNRM-CM5-2 and 40-GCM-Ensemble, respectively. The total errors of 6-GCM-Ensemble, CNRM-CM5-2, and 40-GCM-Ensemble are 11.84, 13.69, and 14.09, respectively. 6-GCM-Ensemble and CNRM-CM5-2 agree well with observations and can provide useful climate simulations for Southeast Asia. This suggests the use of 6-GCM-Ensemble and CNRM-CM5-2 for climate studies and projections for Southeast Asia.

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