In this review, we describe current Machine Learning approaches to hand gesture recognition with depth data from time-of-flight sensors. In particular, we summarise the achievements on a line of research at the Computational Neuroscience laboratory at the Ruhr West University of Applied Sciences. Relating our results to the work of others in this field, we confirm that Convolutional Neural Networks and Long Short-Term Memory yield most reliable results. We investigated several sensor data fusion techniques in a deep learning framework and performed user studies to evaluate our system in practice. During our course of research, we gathered and published our data in a novel benchmark dataset (REHAP), containing over a million unique three-dimensional hand posture samples.

Hand Gesture Recognition in Automotive Human–Machine Interaction Using Depth Cameras

As the images are examined using the latest machine learning process, the techniques for computing the images become highly essential. This computation applied over the images allows one to have an assessable information’s or values from the images. Since segmentation plays a vital role in processing of images by enhancing or hypothetically altering the images making the examination of valuable insights easier. Several procedures and the methods for segmenting the images have been developed. However to have an better process it is important to sort out an effective segmentation procedure, so the paper performs the analysis of the clustering based image segmentation techniques applied on the magnetic resonance image of the human brain to detect the white matter hyper intensities part. The evaluation process take place in the MATLAB to evince the accurate valuation procedure. The optimal procedure is sorted out to be used in observing and examining the medical images by implementing over a computer assisted tool.

https://www.irojournals.com/iroiip/V2/I1/02.pdf

Performance Analysis of Clustering Based Image Segmentation Techniques

/pdf/antennas-for-global-navigation-satellite-systems-chen-2tloagd7dl.pdf

Antennas for Global Navigation Satellite Systems: Chen/Antennas for Global Navigation Satellite Systems

A novel circularly polarized (CP) beam-steering four-arm curl antenna with four feed points is presented. The antenna provides steerable high-gain high-tilt right-handed CP (RHCP) beams for satellite communications. The antenna operates over a test frequency band of 1500–1670 MHz and covers the entire L1 band. The four arms are arranged symmetrically with respect to the center of the antenna, and each arm is fed by a coaxial line. When one of the four feed points is excited and the remaining feed points are either open-circuited or terminated to 50 Ω impedance, the antenna generates an RHCP tilted beam of 49° in the elevation plane. At a test frequency of 1575 MHz, the antenna provides a gain of 8.12 dBic. The antenna can switch the tilted beam in the four different space quadrants in the azimuth plane by exciting one feed point at a time. It is found that over the test band, the antenna provides a total efficiency of more than 89% and a gain of greater than 8 dBic.

/pdf/a-four-arm-circularly-polarized-high-gain-high-tilt-beam-1mmsa14et8.pdf

A Four-Arm Circularly Polarized High-Gain High-Tilt Beam Curl Antenna for Beam Steering Applications

Outdoor optical fiber cabinets are generally installed along roadsides where environmental conditions, such as sun exposure, rain, and dust, can cause damage to the cabinets. Furthermore, high temperatures and unexpected impacts that cause cabinet deformation may damage the network equipment inside the cabinets, affecting the quality of communications. This paper developed an optical fiber sensing system for real-time monitoring of the temperature variation and external forces exerted on outdoor cabinets using fiber Bragg gratings (FBGs). This FBG sensing system was established in the network management center, and was linked to the outdoor cabinets at the remote end through optical fibers in order to monitor the impacts and temperature changes of the cabinets. Experimental results revealed that exerting an external impact force of 297 N on an outdoor cabinet severely dented the impacted cabinet surface. When the monitoring system detects external impacts exceeding 297 N or cabinet temperatures greater than 65 °C, the network management center can then immediately send maintenance personnel to check for any network impairments.

Application of a Packaged Fiber Bragg Grating Sensor to Outdoor Optical Fiber Cabinets for Environmental Monitoring

This work highlights the design, simulation and analysis of an Archimedean spiral antenna (ASA) for GPS application The antenna was fed using coaxial feed and a prototype was fabricated on FR4 of dielectric constant, e r = 49 with thickness of 154 mm while the center frequency was 1575 GHz The design and simulation of the ASA were carried out b y using commercial electromagnetic simulator, CST The prototype was fabricated, measured and analyzed using Vector Network Analyzer (VNA), ZVA40 2D radiation pattern was obtained by using antenna training system, ED3200 It was observed that the measured and simulated values of the parameters of the ASA were close with each other The frequency independent of the ASA was achieved by having the same values of inner radius r, width of arm w and the spacing, s between each turn of the ASA The radiation pattern obtained illustrated an omni-directional pattern

Coaxial feed Archimedean spiral antenna for GPS application

Hand gesture recognition system has evolved tremendously in the recent few years because of its ability to interact with machine efficiently. Mankind tries to incorporate human gestures into modern technology by searching and finding a replacement of multi touch technology which does not require any touching movement on screen. This paper presents an overview on several methods to realize hand gesture recognition by using three main modules: camera and segmentation module, detection module and feature extraction module. There are many methods which can be used to get the respective results depending on its advantages. Summary of previous research and results of hand gesture methods as well as comparison between gesture recognition are also given in this paper.

https://iopscience.iop.org/article/10.1088/1757-899X/99/1/012012/pdf

An Overview of Hand Gestures Recognition System Techniques

This paper highlights the design, simulation, analysis and fabrication of a coaxial-fed rectangular spiral microstrip antenna (RSMA) for Wi-Fi application. The centre frequency is 2.45 GHz and the bandwidth is 22 MHz. The radiation pattern of this RSMA illustrated an omni-directional pattern with voltage standing wave ratio of less than two (2), return loss of less than −10 dB, the line impedance of 50 Ω and gain of 5 dBi. All the design and simulation of this RSMA were carried by using a commercial 3-D electromagnetic simulator. The prototype was fabricated on FR 4 substrate with 4.9 dielectric constant and 1.54 mm of thickness. Vector network analyzer ZVA40 was used to measure all the parameters of this RSMA. The 2D radiation pattern was obtained by using antenna training system ED3200. It was observed that the simulated and measured values of the parameters of the RSMA were quite close with each other.

http://icact.org/upload/2011/0403/20110403_finalpaper.pdf

Design of a rectangular spiral antenna for Wi-Fi application

A great deal of previous research into wheel alignment has focused on techniques of the alignment, which involve big, bulky and high cost to maintain. Even though several approaches are required, the works are tedious and only performed in spacious area and trained mechanics. IoT is the alternatives due to the evolution of smartphone with numerous sensors to support and assist the research and development for IoT applications in vehicles. In this work, smaller and portable wheel alignment monitoring system is introduced by using communication protocol between sensors, microcontroller and mobile phone application. Thus, graphical user interface (GUI) is utilized to the system via wireless communication technology using TCP/IP Communication Protocol. The system has been tested to suit the functioning architecture system for the wheel alignment to provide the user awareness on early detection of wheel misalignment. In addition, the application has been successfully integrated with Android mobile application via TCP/IP communication protocol and view the results in smart phone in real-time.

/pdf/iot-for-wheel-alignment-monitoring-system-22jwfogcue.pdf

IoT for wheel alignment monitoring system

In this work, Fiber Bragg Grating (FBG) is characterized as temperature sensor because of its sensitivity to temperature, thus making it a potential device to perform pipeline water leakage inspection. Bragg wavelength □B is measured by tunable laser source (TLS) as light source and optical spectrum analyzer (OSA) is used to observe the reflected Bragg Wavelength at temperature from 24 °C to 40 °C. Analysis is carried out to define the relationship of □B with temperature based on the collected data. The temperature sensitivity of 9.2 pm/°C and 9.8 pm/°C was obtained for FBG1 and FBG2 respectively.

S. Sulaiman

Papers

Coaxial feed Archimedean spiral antenna for GPS application

An Overview of Hand Gestures Recognition System Techniques

Design of a rectangular spiral antenna for Wi-Fi application

IoT for wheel alignment monitoring system

Characterization of Fiber Bragg Grating as optical temperature sensor for pipeline water leakage inspection