Abstract

Formants (peaks in the spectrum) are typically found in vowel regions.However, resonances of vocal tract are present in both voiced and unvoiced regions.It is important to focus on extracting vocal tract resonances from speech signal toprovide compact and effective representation. This work applies multilayered neuralnetworks for the estimation of vocal tract resonances from linear prediction cepstralcoefficients. To train such a neural network, the voiced regions of speech signal are firstprobed forreliable spectral prominent regions. A sequence of spectral peaks detectedby imposing continuity constraints in voiced regions is referred to as reliable spectralprominent regions. A multilayer feedforward neural network is then trained to model amapping function from linear prediction cepstral coefficients to vocal tract resonancesestimated in these reliable spectral prominent regions. This modeled function is usedto estimate vocal tract resonances in all speech regions including unvoiced sections

Abstract

Intensity and duration are both pertinent aspects of an emotional experience, yet how they are related is unclear. Though stronger emotions usually last longer, sometimes they abate faster than the weaker ones. We present a quantitative model of affective adaptation, the process by which emotional responses to unchanging affective stimuli weaken with time, that addresses this intensity-duration problem. The model, described by three simple linear algebraic equations, assumes that the relationship between an affective stimulus and its experiencer can be broken down into three parameters. Self-relevance and explanation level combine multiplicatively to determine emotion intensity whereas the interaction of these with explanatory ease determines its duration. The model makes predictions, consistent with available empirical data, about emotion intensity, its duration, and adaptation speed for different scenarios. It predicts when the intensity-duration correlation is positive, negative or even absent, thus offering a solution to the intensity-duration problem. The model also addresses the shortcomings of past models of affective adaptation with its enhanced predictive power and by offering a more complete explanation to empirical observations that earlier models explain inadequately or fail to explain altogether. The model has potential applications in areas such as virtual reality training, games, human-computer interactions, and robotics.

Abstract

A building is a boundary between an outdoor climate and indoor conditions. The building energy consumption, notably the energy used for air-conditioning is closely related to outdoor climate. The Solar Radiation, Drybulb Temperature and Relative Humidity are the important climatic parameters which affect building’s thermal and visual conditions. The energy codes development analyses and evaluation of new technologies with respect to energy savings and financial viability have been carried out for selected cities that are supposed to represent any particular climate zone. There is a significant change in thermal loads in different cities of a climate zone. Selection of a representative city for a climatic zone is important because it needs to reflect average climatic conditions for a particular climate zone accurately. This study presents a new method that has been developed for the selection of a representative city in any climate zone, using the principle of Euclidean distance approach having a dry-bulb temperature, wet bulb temperature and solar radiation as three axes. The city having minimum Euclidean distance with respect to remaining cities of the same climatic zone is proposed to be taken as a representative city. The proposed method has been applied on each of the five existing climatic zones of India according to National Building Code (NBC) of India and eight climate zones according to ASHRAE Standard 169-2013.

Abstract

This study demonstrates an experimental example of application of time-lapse high dynamic range images for analyzing variations in correlated color temperature (CCT) and circadian lighting in an interior space daylit using a tubular daylight device (TDD). Previous studies have shown that the spectral composition of daylight affects human circadian rhythms, with emphasis on wavelengths towards the blue region of the visible spectrum. Spectrally based metrics such as CCT can therefore aid in evaluating the circadian impact of daylight. TDDs redirect daylight towards interior spaces with changing light levels and color temperatures during the daylight hours. This paper details the color temperature and circadian lighting metrics (circadian luminance and illuminance) in an interior space throughout a period of several days in a mid-latitude, temperate, sunny climate. An automated timelapse HDR photography apparatus was modified to allow for calculation of CCT and circadian lighting metrics using state-of-the art techniques available in the literature. Prior to the measurements in the space with the TDD, this device was calibrated against a spectrophotometer. Results indicate the level of daily variation in CCT and circadian lighting metrics that can be expected in interior spaces daylit by TDDs without any other sources of daylight. Besides showcasing the use of HDR techniques, these results could be used to support design decisions involving daylighting in interior spaces. These techniques can also be used outside the laboratory in the evaluation of the circadian impact of lighting throughout the built environment.

Abstract

Real-time Indoor theft detection from surveillancevideos is not only a challenging problem of object detection and human activity recognition in the field of computer vision, but also an urgent need for preventing theft crimes in real life. The system uses digital cameras to scan the faces of people approaching a security gate i.e. the entry gate, and then matches its faces with the faces in the database, and if found not to be a known one it automatically generates an alert. In this paper, we propose a framework for real-time indoor theft detection based on the combining result of face recognition and pattern matching by analyzing the activities with that of thieves. At last, if detected abnormal it automatically sends a message using Multimedia Message Service with the help of GPRS/GSM modem.

Abstract

In the present study an attempt has been made to study the 1D (One Dimensional), 2D (Two Dimensional) and 3D (Three Dimensional) ground response of pond ash collected from Odisha under different earthquake motions. 1D ground response analysis of pond ash deposit has been carried out by using equivalent linear and nonlinear analysis method using SHAKE2000 and Cyclic1D software respectively. 2D and 3D ground response analysis of pond ash deposit has been carried out by using finite element software Plaxis2D and Plaxis3D respectively. The response analyses of the pond ash deposit have been performed under the excitation of North East India earthquake (Mw-7.5) and Nepal earthquake (Mw-7.8). The results of the response analyses have been presented in terms of acceleration, displacement, excess pore pressure and excess pore pressure ratio. A comparative study between 1D, 2D and 3D ground response analysis has been performed to predict seismic risk of the pond ash site in Odisha.

Abstract

Abstract In the current study laboratory experiments were conducted to elucidate the allelopathic and autotoxic effects of Parthenium hysterophorus, Senna uniflora and Hyptis suaveolens. The seed germination experiments were conducted using the leachates obtained from different organs of the three species. Ten grams, each of the plant materials were homogenized in 100 mL of quartz-distilled water for 24 hours, filtered and used as a stock solution of 100% concentration. From the stock solution, 25, 50 and 75% concentrations were prepared by diluting with quartz-distilled water. Three replicates with 30 seeds each for each plant species were maintained. Observations were made at regular intervals of 24 hours. The emergence of radicle was taken as the indicator of germination. Germination, root and shoot elongation was monitored for eight days. The study revealed inhibition of germination …

Abstract

The Kondapalli reserve forest (KRF) of the Eastern Ghats, India is subjected to severe anthropogenic interference, despite its status as reserve forest. The present research focuses on assessing the land use and land cover changes in and around KRF using temporal satellite data. It is evident from the current study that there has been a considerable decrease in the forest cover from 1990 to 2015; as seen from 2017 data, huge urban expansions and development activities were observed around KRF. This increase is linked to the growth in population, thereby consuming land available for their basic needs. To assess the rate of urban expansion around the forest, Land consumption rate and Land absorption coefficient were computed. The result of this analysis showed a rapid growth in built-up land between 1990 and 2017 while the periods between 1990 and 2015 witnessed a reduction in the forest class. Further

Abstract

Forest inventory parameters, primarily tree diameter and height, are required for several management and planning activities. Currently, Terrestrial Laser Scanning (TLS) is a promising technology in automated measurements of tree parameters using dense 3D point clouds. In comparison with conventional manual field inventory methods, TLS systems would supplement field data with detailed and relatively higher degree of accurate measurements and increased measurement frequency. Although, multiple scans from TLS captures more area, they are resource and time consuming to ensure proper co-registration between the scans. On the other hand, Single scans provide a fast and recording of the data but are often affected by occlusions between the trees. The current study evaluates potential of single scan TLS data to (1) develop an automatic method for tree stem identification and diameter estimation …

Abstract

Forest inventories are critical for effective management of forest resources. Recently, the use of terrestrial laser scanning (TLS) to automatically extract forest inventory parameters at tree level (eg tree location, diameter at breast height (DBH) and height) has gained significant importance. TLS using both single-scan and multi-scan techniques, not only helps in detailed and accurate measurements of tree objects but also helps increase the measurement frequency. In the current study, we develop an automated solution to extract forest inventory parameters at individual tree level from TLS data by using random sample consensus (RANSAC)-based circle fitting algorithm. The method was evaluated on both single-and multiscan data by characterizing four circular plots of radius 20 m in dry deciduous forests of Betul, Madhya Pradesh (India). Over all the plots, tree detection rates of 75% and 97% were obtained using single-and multi-scan TLS data respectively. Tree detection rates were significantly affected by increase in distance from the scanner, in single-scan approach when compared to multi-scan approach. Field based DBH measurements correlated well using both single (R2= 0.96) and multiple scans (R2= 0.99). The DBH estimates from multi-scan TLS data resulted in low root-meansquare error (RMSE) of 2.2 cm compared to that of 4.1 cm using single-scan. Further, tree heights were extracted from TLS data and validated with selectively measured trees on field (R2= 0.98; N= 65). The RMSE of tree height was estimated to be 1.65 m. The current results show the potential use of TLS in automatically deriving forest inventory parameters with …