scholarly journals Hybrid Approach for Detection of Objects from Images Using Fisher Vector and PSO Based CNN

2021 ◽  
Vol 26 (5) ◽  
pp. 483-489
Author(s):  
RatnaKumari Challa ◽  
Kanusu Srinivasa Rao
Keyword(s):  
Video Processing ◽  
Optimization Technique ◽  
Hybrid Approach ◽  
Picture Perception ◽  
Fisher Kernel ◽  
Picture Arrangement ◽  
Proposed Model ◽  
Detection Of Objects ◽  
Slow Moving ◽  
Performance Results

Owing to the near connection between object recognition and video processing and picture perception, a lot of research interest has been received in recent years. Standard methods of object detection are focused on manufactured technologies and slow-moving architectures. Fisher Vectors (FV) and Convolutional Neural Networks (CNN) are two picture arrangement pipelines with various qualities. While CNNs have indicated predominant exactness on various order assignments, FV classifiers are normally less exorbitant to prepare and assess. In this paper we propose a mechanism for detection of objects in image based on Fisher kernel and CNN with a PSO optimization technique. Here fisher kernel draws the global or statically features from the image object and CNN is used for local and more complex feature extraction from an image and here we use CNN with PSO to reduce the training complexity. Performance results shows that the proposed model is detect the object better than the existing models.

Speed as a Variable on Three Wisc Performance Subtests

1972 ◽  
Vol 34 (2) ◽  
pp. 451-455 ◽  
Author(s):  
James Woo-Sam ◽  
Irla Lee Zimmerman
Keyword(s):  
Power Function ◽  
Block Design ◽  
Handicapped Child ◽  
Normal Intelligence ◽  
Design Object ◽  
Picture Arrangement ◽  
Normal Limits ◽  
Test Materials ◽  
Performance Results

This study tested the hypothesis that for younger children of normal intellect, speed of performance plays a minimal if not negligible role in determining the obtained scores on the Block Design, Object Assembly, and Picture Arrangement subtests. It was further argued that if such were the case, then it was not necessary to exclude these subtests in the evaluation of the orthopedically handicapped child capable of manipulating the test materials. Under these circumstances, a poor showing could not be attributed to loss of bonus credits because of slow performance. Results based on five groups of children of normal intelligence ages 7 1/2 through 13 1/2 yr. ( N = 119) indicate that the Block Design and Object Assembly subtests essentially measure a power function through age 10 1/3. Speed is a determinant by age 13 1/2. On the Picture Arrangement subtest, the power function holds only at age 7 1/2. However, a score within normal limits is possible without speed bonuses through age 9 1/2.

scholarly journals KGPMH: A hybrid approach for solving a novel facility location problem

2021 ◽  
Author(s):  
Maryam DehghanChenary ◽  
Arman Ferdowsi ◽  
Fariborz Jolai ◽  
Reza Tavakkoli-Moghaddam
Keyword(s):  
Mathematical Model ◽  
Location Problem ◽  
Hybrid Approach ◽  
Facility Location Problem ◽  
Evaluation Function ◽  
Genetic Approach ◽  
Hub Location ◽  
Hub Location Problem ◽  
Proposed Model ◽  
The Impact

<pre>The focus of this paper is to propose a bi-objective mathematical model for a new extension of a multi-period p-mobile hub location problem and then to devise an algorithm for solving it. The developed model considers the impact of the time spent traveling at the hubs' network, the time spent at hubs for processing the flows, and the delay caused by congestion at hubs with specific capacities. Following the unveiled model, a hybrid meta-heuristic algorithm will be devised that simultaneously takes advantage of a novel evaluation function, a clustering technique, and a genetic approach for solving the proposed model.</pre>

Modelling, analysis and experimental verification of air disc brake used in heavy duty vehicles

2021 ◽  
pp. 095440622110520
Author(s):  
İbrahim Can Güleryüz ◽  
Barış Yılmaz
Keyword(s):  
Design Stage ◽  
Maximum Deviation ◽  
Disc Brake ◽  
Commercial Vehicles ◽  
Actual Performance ◽  
Test Fixture ◽  
Simulink Model ◽  
Proposed Model ◽  
Mathematical Equations ◽  
Performance Results

This paper proposes a reliable mathematical model that can be used for design stage of new air disc brake (ADB) development projects. All three phases of braking mechanism (brake apply, brake release and automatic adjustment) are modelled by Matlab Simulink in consideration of hysteresis and adjuster performance experiments. Firstly, mathematical relations of each friction interfaces of air disc brake components are derived and mathematical equations adapted to the Simulink model. To ensure the accuracy of ADB system model, hysteresis and adjuster performance experiments are conducted on a prototype disc brake mechanism supported by a test fixture. This prototype single piston disc brake mechanism is fitted to wheel size in 17.5″ used in heavy commercial vehicles. The predicted clamping force, mechanical ratio, brake efficiency and adjuster rate results are verified by using experimental data. The maximum deviation in hysteresis results is 3.08%. Besides, the maximum deviation in adjuster performance results is 7.15%. The numerically and experimentally obtained hysteresis and adjuster performance results show good agreement. The proposed model is modified in consideration of mechanism supported by a brake calliper for predicting actual performance of single piston brake mechanism on the brake level. The hysteresis and the adjuster performance analyses are conducted by using modified ADB model to calculate the hysteresis based brake efficiency and the adjuster rate. The brake efficiency of new single piston brake design provides similar efficiency as the twin piston disc brake used in heavy commercial vehicles.

scholarly journals Optimization technique combined with deep learning method for teeth recognition in dental panoramic radiographs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fahad Parvez Mahdi ◽  
Kota Motoki ◽  
Syoji Kobashi
Keyword(s):  
Dental Care ◽  
Cross Validation ◽  
Optimization Technique ◽  
Confidence Score ◽  
Computer Assisted ◽  
Proposed Model ◽  
Tenfold Cross Validation ◽  
Stress Fatigue ◽  
Assisted Analysis ◽  
High Degree

Abstract Computer-assisted analysis of dental radiograph in dentistry is getting increasing attention from the researchers in recent years. This is mainly because it can successfully reduce human-made error due to stress, fatigue or lack of experience. Furthermore, it reduces diagnosis time and thus, improves overall efficiency and accuracy of dental care system. An automatic teeth recognition model is proposed here using residual network-based faster R-CNN technique. The detection result obtained from faster R-CNN is further refined by using a candidate optimization technique that evaluates both positional relationship and confidence score of the candidates. It achieves 0.974 and 0.981 mAPs for ResNet-50 and ResNet-101, respectively with faster R-CNN technique. The optimization technique further improves the results i.e. F1 score improves from 0.978 to 0.982 for ResNet-101. These results verify the proposed method’s ability to recognize teeth with high degree of accuracy. To test the feasibility and robustness of the model, a tenfold cross validation (CV) is presented in this paper. The result of tenfold CV effectively verifies the robustness of the model as the average F1 score obtained is more than 0.970. Thus, the proposed model can be used as a useful and reliable tool to assist dental care professionals in dentistry.

scholarly journals A New Click-Through Rates Prediction Model Based on Deep&Cross Network

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 342
Author(s):  
Guojing Huang ◽  
Qingliang Chen ◽  
Congjian Deng
Keyword(s):  
Neural Networks ◽  
Prediction Model ◽  
Deep Neural Networks ◽  
Prediction Models ◽  
State Of The Art ◽  
Online Advertising ◽  
Optimization Technique ◽  
Proposed Model ◽  
Great Progress ◽  
Online Advertisement

With the development of E-commerce, online advertising began to thrive and has gradually developed into a new mode of business, of which Click-Through Rates (CTR) prediction is the essential driving technology. Given a user, commodities and scenarios, the CTR model can predict the user’s click probability of an online advertisement. Recently, great progress has been made with the introduction of Deep Neural Networks (DNN) into CTR. In order to further advance the DNN-based CTR prediction models, this paper introduces a new model of FO-FTRL-DCN, based on the prestigious model of Deep&Cross Network (DCN) augmented with the latest optimization technique of Follow The Regularized Leader (FTRL) for DNN. The extensive comparative experiments on the iPinYou datasets show that the proposed model has outperformed other state-of-the-art baselines, with better generalization across different datasets in the benchmark.

scholarly journals Hybrid Approach for Enhancing Performance of Genomic Data for Stream Matching

2021 ◽  
Vol 15 (4) ◽  
pp. 1-18
Author(s):  
Gururaj T. ◽  
Siddesh G. M.
Keyword(s):  
Processing Time ◽  
Gene Expression Analysis ◽  
Gene Sequence ◽  
Hybrid Approach ◽  
Basic Operation ◽  
Sequence Matching ◽  
Hadoop Mapreduce ◽  
Proposed Model ◽  
Performance Issues ◽  
Memory Utilization

In gene expression analysis, the expression levels of thousands of genes are analyzed, such as separate stages of treatments or diseases. Identifying particular gene sequence pattern is a challenging task with respect to performance issues. The proposed solution addresses the performance issues in genomic stream matching by involving assembly and sequencing. Counting the k-mer based on k-input value and while performing DNA sequencing tasks, the researches need to concentrate on sequence matching. The proposed solution addresses performance issue metrics such as processing time for k-mer counting, number of operations for matching similarity, memory utilization while performing similarity search, and processing time for stream matching. By suggesting an improved algorithm, Revised Rabin Karp(RRK) for basic operation and also to achieve more efficiency, the proposed solution suggests a novel framework based on Hadoop MapReduce blended with Pig & Apache Tez. The measure of memory utilization and processing time proposed model proves its efficiency when compared to existing approaches.

scholarly journals A Novel Adaptive Approach for Autonomous Vehicle Based on Optimization Technique for Enhancing the Communication between Autonomous Vehicle-to-Everything through Cooperative Communication

2021 ◽  
Vol 11 (19) ◽  
pp. 9089
Author(s):  
Radwa Ahmed Osman ◽  
Ahmed Kadry Abdelsalam
Keyword(s):  
Cooperative Communication ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicle ◽  
Optimization Technique ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Emergency Vehicle ◽  
System Quality ◽  
Vehicular Communication ◽  
Proposed Model

Recent autonomous intelligent transportation systems commonly adopt vehicular communication. Efficient communication between autonomous vehicles-to-everything (AV2X) is mandatory to ensure road safety by decreasing traffic jamming, approaching emergency vehicle warning, and assisting in low visibility traffic. In this paper, a new adaptive AV2X model, based on a novel optimization method to enhance the connectivity of the vehicular networks, is proposed. The presented model optimizes the inter-vehicle position to communicate with the autonomous vehicle (AV) or to relay information to everything. Based on the system quality-of-service (QoS) being achieved, a decision will be taken whether the transmitting AV communicates directly to the destination or through cooperative communication. To achieve the given objectives, the best position of the relay-vehicle issue was mathematically formulated as a constrained optimization problem to enhance the communication between AV2X under different environmental conditions. To illustrate the effectiveness of the proposed model, the following factors are considered: distribution of vehicles, vehicle density, vehicle mobility and speed. Simulation results show how the proposed model outperforms other previous models and enhances system performance in terms of four benchmark aspects: throughput (S), packet loss rate (PLR), packet delivery ratio (PDR) and average delivery latency (DL).

scholarly journals Density based Automatic Traffic Junction Synchronization

2019 ◽  
Vol 8 (2) ◽  
pp. 5781-5786
Keyword(s):  
Control System ◽  
Video Processing ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Noise Pollution ◽  
Moving Vehicle ◽  
Metropolitan Cities ◽  
Commuting Time ◽  
Traffic Control System ◽  
Slow Moving

Traffic congestion nowadays has become a chronic issue in the Metropolitan cities due to which it takes more time to travel than the same distance travelled during the off peak hours. This decreases the productivity of an individual by instances such as delayed delivery of services, unnecessary fuel consumption, air and noise pollution, delay in the case of emergency. The traffic congestion has become a predominant problem due to the rapid increase in the demand of vehicles. In places where junctions are closely spaced, encounter a typical issue of lingering in the same traffic signal for multiple times due to the slow moving vehicle caused by congestion. In order to control this issue, research works have been carried out in automating the traffic control system with the help of sensors, image or video processing and also by prioritizing emergency vehicles approaching the junctions. However, employing camera to monitor the traffic is an expensive task. Thus, we are proposing the Density based synchronous of junctions that are closely placed which helps us to save our commuting time significantly and thus enhancing one’s productivity

Mathematical Modeling of Cardiopulmonary Resuscitation

2015 ◽  
Author(s):  
Ali Jalali ◽  
Robert A. Berg ◽  
Vinay M. Nadkarni ◽  
C. Nataraj
Keyword(s):  
Mathematical Modeling ◽  
Mechanical Properties ◽  
Cardiac Arrest ◽  
Cardiopulmonary Resuscitation ◽  
Nonlinear Model ◽  
Optimization Technique ◽  
Nonlinear Damping ◽  
Complex Behavior ◽  
Proposed Model ◽  
Compression Data

The cardiopulmonary resuscitation procedure (CPR) is a widely used procedure for resuscitating cardiac arrest patients. Many physiological aspects of the procedure are not yet well understood. The first step for understanding and modeling such a complicated procedure is to develop an accurate model of mechanical properties of the chest during CPR. In this paper we propose a novel nonlinear model of the chest that captures the complex behavior of the chest during CPR. The proposed model consists of nonlinear elasticity and nonlinear damping along with frequency dependent hysteresis. We use an optimization technique to estimate the model coefficients for force-compression data collected from careful experiments conducted on swine. The results show excellent agreement.

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