Hybrid Geo-Location Routing Protocol for Indoor and Outdoor Positioning Applications

Mushtaq, Sania; Alandjani, Gasim; Abbasi, Saba Farooq; Abosaq, Nasser H.; Akram, Adeel; Pervez, Shahbaz

doi:10.14569/ijacsa.2019.0100701

Cited by 8 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Blockchain technology can be used to extend the presented method. [25][26][27] Additionally, the proposed deep neural network can be used for other real-time applications such as vehicle classification. [28][29][30][31]…”

Section: Experiments and Resultsmentioning

confidence: 99%

Meme Generation Using Deep Neural Network to Engage Viewers on Social Media

Alandjani

Bouk

2021

Yanbu Journal of Engineering and Science

View full text Add to dashboard Cite

In today’s technological era, most new generations are using memes because the phenomenon of memes is rapidly gaining in popularity. In addition, various modifications and parodies use social and cultural phenomena to transform an original idea into another. Virus memes are sometimes called virus scripts and are the most widespread on the Internet. However, there is little scientific evidence for this assumption. This paper presents an innovative method to generate memes using machine learning algorithms that match the users’ humorous and relevant captions. The VGG16 network is used to return the embedded image. We have collected feedback from citizens of more than five countries and received 37 feedbacks to find humorous memes. The obtained results from feedback are very encouraging from the generated memes.

show abstract

Section: Experiments and Resultsmentioning

confidence: 99%

Meme Generation Using Deep Neural Network to Engage Viewers on Social Media

Alandjani

Bouk

2021

Yanbu Journal of Engineering and Science

View full text Add to dashboard Cite

show abstract

“…Typically, these methods extracted the malware features manually and then utilized their handcrafted features to feed shallow classifiers like support vector machine (SVM), naive Bayes classifier, decision trees, k-nearest algorithms, etc. [37][38][39][40][41]. However, the effectiveness of these methods relies heavily on feature engineering.…”

Section: Traditional Machine Learningmentioning

confidence: 99%

Securing Edge Devices: Malware Classification with Dual-Attention Deep Network

Alandjani

2024

Applied Sciences

View full text Add to dashboard Cite

Detecting malware is a crucial defense mechanism against potential cyber-attacks. However, current methods illustrate significant limitations in achieving high performance while maintaining faster inference on edge devices. This study proposes a novel deep network with dual-attention feature refinement on a two-branch deep network to learn real-time malware detection on edge platforms. The proposed method introduces lightweight spatial-asymmetric attention for refining the extracted features of its backbone and multi-head attention to correlate learned features from the network branches. The experimental results show that the proposed method can significantly outperform existing methods in quantitative evaluation. In addition, this study also illustrates the practicability of a lightweight deep network on edge devices by optimizing and deploying the model directly on the actual edge hardware. The proposed optimization strategy achieves a frame rate of over 545 per second on low-power edge devices.

show abstract

“…Asghari et al (2019) discussed the achievements and disadvantages of each research into IoT and put forward some suggestions on the solution of the disadvantages as well as future challenges and problems to be addressed in IoT application. Mushtaq et al (2019) researched the performance of a position-based routing protocol Geocast self-adaptive Mesh environment. The environment was used to collect the routing for context information from the global positioning system and internal navigation and discovery framework.…”

Section: Introductionmentioning

confidence: 99%

“…(2019) discussed the achievements and disadvantages of each research into IoT and put forward some suggestions on the solution of the disadvantages as well as future challenges and problems to be addressed in IoT application. Mushtaq et al . (2019) researched the performance of a position-based routing protocol Geocast self-adaptive Mesh environment.…”

Section: Introductionmentioning

confidence: 99%

Digital media recording and broadcasting classroom using Internet intelligent image positioning and opinion monitoring in communication

2022

LHT

View full text Add to dashboard Cite

PurposeThe digital media recording and broadcasting classroom using Internet real-time intelligent image positioning and opinion monitoring in communication teaching is researched and analyzed.Design/methodology/approachFirst, spatial grid positioning and monitoring and image intelligent recognition technologies were used to extract and analyze teaching images by mastering Internet of Things (IoT) technology and establishing an intelligent image positioning and opinion monitoring digital media recording and broadcasting system framework. Next, a positioning node algorithm was utilized to measure the image distance, and then a moving node location model under the IoT was established. In addition, a radial basis function (RBF) neural network was used to realize the signal transmission function. The experimental data of the adopted RBF based on the optimization of the adaptive cuckoo search (ACS-RBF) neural network, particle swarm algorithm neural network, and method of least squares optimization were compared and analyzed. In addition, a more efficient RBF neural network was adopted. Finally, the digital media recording and broadcasting classroom scheme of real-time intelligent image positioning and opinion monitoring was designed. In addition, the application environment of digital media actual teacher teaching was detected, and recording and broadcasting pictures were analyzed and researched.FindingsThe actual value, predicted value, and the number of predicted samples of the ACS-RBF model were all better than those of the two other neural networks. According to the analysis and comparison of the sampling optimization Monte Carlo localization (SOMCL), Monte Carlo, and genetic algorithm optimization-based Monte Carlo positioning algorithms, the SOMCL algorithm showed better robustness, and its positioning efficiency was superior to that of the two other algorithms. In addition, the SOMCL algorithm greatly reduced the positioning and monitoring energy consumption.Originality/valueThe application of real-time intelligent image positioning and monitoring technology in actual communication teaching was realized in the study.

show abstract

Hybrid Geo-Location Routing Protocol for Indoor and Outdoor Positioning Applications

Cited by 8 publications

References 15 publications

Meme Generation Using Deep Neural Network to Engage Viewers on Social Media

Meme Generation Using Deep Neural Network to Engage Viewers on Social Media

Securing Edge Devices: Malware Classification with Dual-Attention Deep Network

Digital media recording and broadcasting classroom using Internet intelligent image positioning and opinion monitoring in communication

Contact Info

Product

Resources

About