Gesture Recognition Robot Via Kinect Sensor

This project is designed to develop Gesture Recognition Robot via Kinect Sensor. The idea of this project is starting from research of Kinect on pc. This paper is to provide plenty useful feature of Kinect such as controlling robot by using our gesture and motion. It is a breakthrough in the market as many applications will be using gesture or motion to control it. This project is a startup for various applications of Kinect or any sensors with the same capability to improve daily life

SIEM Network Behaviour Monitoring Framework using Deep Learning Approach for Campus Network Infrastructure

One major problem faced by network users is an attack on the security of the network especially if the network is vulnerable due to poor security policies. Network security is largely an exercise to protect not only the network itself but most importantly, the data. This exercise involves hardware and software technology. Secure and effective access management falls under the purview of network security. It focuses on threats both internally and externally, intending to protect and stop the threats from entering or spreading into the network. A specialized collection of physical devices, such as routers, firewalls, and anti-malware tools, is required to address and ensure a secure network. Almost all agencies and businesses employ highly qualified information security analysts to execute security policies and validate the policies’ effectiveness on regular basis. This research paper presents a significant and flexible way of providing centralized log analysis between network devices. Moreover, this paper proposes a novel method for compiling and displaying all potential threats and alert information in a single dashboard using a deep learning approach for campus network infrastructure

Pixel Value Graphical Password Scheme: Analysis on Time Complexity performance of Clustering Algorithm for Passpix Segmentation

Passpix is a key element in pixel value access control, containing a pixel value extracted from a digital image that users input to authenticate their username. However, it is unclear whether cloud storage settings apply compression to prevent deficiencies that would alter the file's 8-bit attribution and pixel value, causing user authentication failure. This study aims to determine the fastest clustering algorithm for faulty Passpix similarity classification, using a dataset of 1,000 objects. The source code for the K-Means, ISODATA, and K-Harmonic Mean scripts was loaded into a clustering experiment prototype compiled as Clustering.exe. The results demonstrate that the number of clusters affects the time taken to complete the clustering process, with the 20-cluster setting taking longer than the 10-cluster setting. The K-Harmonic Mean algorithm was the fastest, while K-Means performed moderately and ISODATA was the slowest of the three clustering algorithms. The results also indicate that the number of iterations did not affect the time taken to complete the clustering process. These findings provide a basis for future studies to increase the number of clusters for better accuracy

Pixel Value Graphical Password Scheme: K-Means as Graphical Password Fault Tolerance

Pixel value access control (PVAC) was introduced to deliver a secure and simple graphical password method where it requires users to load their image as their password. PVAC extracts the image to obtain a three-octet 8-bits Red-Green-Blue (RGB) value as its password to authenticate a user. The pixel value must be matched with the record stored in the database or otherwise, the user is failed to authenticate. However, users which prefer to store images on cloud storage would unintentionally alter and as well as the pixel value due to media compression and caused faulty pixels. Thus, the K-Means clustering algorithm is adapted to fix the issue where the faulty pixel value would be recognized as having the same pixel value cluster as the original. However, most of K-Means algorithm works were mainly developed for content-based image retrieval (CBIR) which having opposite characteristics from PVAC. Thus, this study was aimed to investigate the crucial criteria of PVAC and its compatibility with the K-Means algorithm for the problem. The theoretical analysis is used for this study where the suitable characteristics of K-Means are analyze based on PVAC requirements. The compliance analysis might become a referencing work for digital image clustering techniques adaptation on security system such as image filtering, image recognition, and object detection since most of image clustering works was focused on less sensitive image retrieval

Pixel Value Graphical Password Scheme-Graphical Password Scheme Literature Review

Abstract: Pixel Value Graphical Password Scheme is designed to offer a new method for graphical password. This paper presents literature review of graphical password scheme including recall-base scheme and recognition-base scheme. Recall-base scheme are involving user to sketch or draw on password input. While recognition-base require user to click on specific area on an image. Each scheme base can be categorized into several methods where each method was developed with different user-case method. Findings from existing graphical password scheme were used to determine the competencies focus on Pixel Value Graphical Password scheme based on user-case comparison. Final goal of this study is to produce a solid proof that Pixel Value Graphical Password Scheme being a unique and competitive scheme in graphical password category

Monitoring of mangroves changes in Pulau Kukup using geographical information system (GIS)

Mangroves forests provide a support to the coastal livelihood, ecosystem, socioeconomic and also the environment. In Malaysia, the mangroves forest has been in declining rate causes by a few factor such as conversion to shrimps ponds, urban development and tourism. Such threats led to increasing demand for detailed mangrove maps for the purpose of measuring the extent of deterioration of the mangrove ecosystem. However, it is difficult to produce a detailed mangrove map mainly because mangrove forest is very difficult to access. Remote sensing technology provides a genuine alternative to the traditional field-based method of mangrove mapping and monitoring. This study analyses and map the mangrove forest changes at Pulau Kukup, Ramsar Site Johor from 2013 until 2021 using the Normalized Difference Vegetation Index (NDVI). The findings of this study are the mangrove forests in Pulau Kukup, Ramsar Site Johor, revealed an unfavourable shift leading to deforestation from 2013 to 2016. However, between 2019 and 2021, the mangrove forest improves as the forest's vegetation grows