Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Digital processing of speech signals

Probability, Reliability and Statistical Methods in Engineering Design

In this paper, real measurements were conducted to investigate the impact of rain on the propagation of millimeter waves at 26 GHz. The measurements were accomplished using a microwave fifth generation radio link system with 1.3 km path length implemented at Universiti Teknologi Malaysia Johor Bahru, Malaysia. The implemented system consisted of Ericsson CN500 mini E-link, radio unit, rain gauge, and data logger. The measurements were attained and logged daily for a continuous year, with 1-min time intervals. Next, the MATLAB software was used to process and analyze the annual rain rate and rain attenuation, including for the worst month. From the analyzed results, it was found that at 0.01% percentage of time, the rain rate was 120 mm/hr; while the specific rain attenuation was 26.2 dB/km and the total rain attenuation over 1.3 km was 34 dB. In addition, the statistics acquired from the measurements for the worst month were lower than what was predicted by the international telecommunication union (ITU) model; around 51% and 34% for the rain rate and rain attenuation, respectively. The average percentage of error calculated between the measurements and predicted results for the rain rate and rain attenuation were 143% and 159%, respectively. Thus, it can be concluded that the statistics for the worst month in Malaysia is lower than what was predicted by the ITU model.

Real Measurement Study for Rain Rate and Rain Attenuation Conducted Over 26 GHz Microwave 5G Link System in Malaysia

The Internet of things (IOT) is remodeling the agriculture enabling the farmers with the wide range of techniques such as precision and sustainable agriculture to face challenges in the field. IOT technology helps in collecting information about conditions like weather, moisture, temperature and fertility of soil, Crop online monitoring enables detection of weed, level of water, pest detection, animal intrusion in to the field, crop growth, agriculture. IOT leverages farmers to get connected to his farm from anywhere and anytime. Wireless sensor networks are used for monitoring the farm conditions and micro controllers are used to control and automate the farm processes. To view remotely the conditions in the form of image and video, wireless cameras have been used. A smart phone empowers farmer to keep updated with the ongoing conditions of his agricultural land using IOT at any time and any part of the world. IOT technology can reduce the cost and enhance the productivity of traditional farming.

Agricultural crop monitoring using IOT - a study

A model that is less sensitive to errors in the extreme small and large drop diameters, the gamma model with central moments (3, 4 and 6), is proposed to model the rain drop size distribution of Singapore. This is because, the rain rate estimated using measured drop size distribution shows that the contributions of lower drop diameters are small as compared to the central drop diameters. This is expected since the sensitivity of the Joss distrometer degrades for small drop diameters. The lower drop diameters are therefore removed from the drop size data and the gamma model is redesigned for its moments. The effects of the removal of a particular rain drop size diameter on the specific rain attenuation (in dB) and the slant-path rain attenuation calculations with forward scattering coefficients for vertical polarization are analyzed at Ku-band, Ka-band and Q-band frequencies. It is concluded that the sensitivity of the Joss distrometer although affects the rain rate estimation at low rain rates, does not affect the slant path rain attenuation on microwave links. Therefore, the small drop diameters can be ignored completely for slant path rain attenuation calculations in the tropical region of Singapore.

/pdf/truncated-gamma-drop-size-distribution-models-for-rain-1d2qcr5jow.pdf

Truncated Gamma Drop Size Distribution Models for Rain Attenuation in Singapore

In the present world, there are many high tech appliances in our homes that make our lives easier. It is necessary to control these appliances remotely. To automate a machine, a secondary brain (another machine) is required to ‘Think’ and control machines to do tasks as per the convenience of the user from long distances. An automation system is proposed for the users to control home electronic appliances with high mobility and security. A set of switches will be controlled by internet with the use of a Raspberry pi micro-controller board. A Raspberry pi micro-controller board obtains user input from a website that is accessed through a user name and password. The customized user friendly website has several buttons to control the appliances. A Raspberry pi will be located in a room and will be connected to all electronic appliances in the home with the help of electromagnetic relays. The Raspberry pi can be controlled from any distant place with the help of weaved cloud service. Webiopi framework gives us a platform to interact with Raspberry pi's General Purpose Input Output pins. The Raspberry pi then either passes or stops current through an electromagnetic relay connected to the intended switch and this closes/opens the circuit allowing the appliance to run or get switched off. Thus globally accessible automation of electronic appliances can be made possible with the use of a Raspberry Pi micro-controller board, an internet connection and relay switches in a user friendly way.

Globally accessible machine automation using Raspberry pi based on Internet of Things

A Z-R relation is derived using a data set which consists of nine rain events selected from Singapore's drop size distribution. Rain events are separated into convective and stratiform types of rain using two methods: the Gamache-Houze method, a simple threshold technique, and the Atlas-Ulbrich method. In the Atlas-Ulbrich method, the variability of the rain integral parameters R; Z, Nw, D0 and gamma model parameter " are used for the classiflcation of rain into convective, stratiform and transition. Z-R relations are derived for each type of rain after classiflcation. The changes in the coe-cients of the Z-R relations for difierent rain events are plotted and analyzed. The Z-R relations of the difierent methods using the Singapore data are compared and analyzed. It is concluded that the coe-cient A of the Z-R relation is higher for the convective stage followed by the stratiform and transition stages. The coe-cient b values are higher for the transition stage followed by the stratiform and convective stages. Re∞ectivities are extracted from RADAR data above NTU site for rain events and compared with the re∞ectivities derived from the distrometer data. Rain rates retrieved from RADAR data using the proposed relations from Singapore's data set are compared with the distrometer rain rates. The RADAR extracted rain rates are found to be constantly lower than the distrometer derived rain rates but matches well.

/pdf/tropical-rain-classification-and-estimation-of-rain-from-z-r-4b9cvarfhc.pdf

Tropical rain classification and estimation of rain from z-r (reflectivity-rain rate) relationships

Gamma model is fitted using the second, fourth, and sixth moments to model the rain drop size distribution (DSD) of Singapore. As the Joss distrometer measures the number of rain drops between the drop diameters from 0.3 to 5 mm, the truncated moment fitting between these drop diameter ranges is also used for modeling the DSD. Gamma DSD requires three-parameter estimation:N0, the intercept parameter; μ, the shape parameter; and Λ, the slope parameter. The aim of this paper is to find a suitable fixed μ and derive an appropriate μ-Λ relation for the tropical region in order to form a two-parameter gamma model. To find an appropriate μ value, observed DSDs are fitted with different μ values to estimate the rain rates, which are assessed by rain rate observations of the distrometer. Shape-slope relationships are fitted for different categories according to the rain rate and the number of drops. The derived μ-Λ relationships for the Singapore region are compared to the published results from two other regions, and the analysis is presented. Two-parameter gamma models are compared by retrieving the rain rate using the polarimetric radar variables. The effect of truncation on rain rate retrieval is also studied, and the use of the μ-Λ relationship for rain retrieval is recommended for the tropical region. The μ-Λ relation using the truncated moment method for the rain category R ≥ 5 mm/hr and rain counts ≥ 1000 drops retrieves the rain rates well compared to other μ-Λ relations.

/pdf/two-parameter-gamma-drop-size-distribution-models-for-4bh3d1dnrh.pdf

L. S. Kumar

Papers

Truncated Gamma Drop Size Distribution Models for Rain Attenuation in Singapore

Globally accessible machine automation using Raspberry pi based on Internet of Things

Tropical rain classification and estimation of rain from z-r (reflectivity-rain rate) relationships

Two-Parameter Gamma Drop Size Distribution Models for Singapore

Speech emotion recognition using cepstral features extracted with novel triangular filter banks based on bark and ERB frequency scales