P...N Pnicogen Bonding Interaction In Phosphoryl Chloride...Nitrogen Bases: Evidence From Matrix Isolation Infrared Spctroscopy And Quantum Chemical Calculations

\begin{wrapfigure}{|}{0pt} \includegraphics[scale=0.3]{Fig.eps} \end{wrapfigure} Pnicogen bonding emerged as an important interaction as ubiquitous hydrogen bonding, the study of interactions of simple molecular model systems involving pnicogen bonding can be a platform to understand the complex mechanisms controlled by these non-covalent interactions. In the present work matrix isolation spectroscopy in combination with quantum chemical computations were used to elucidate the structures of P...N pnicogen bonded dimers of phosphoryl chloride(\chem{POCl_3}) prototype with nitrogen-bases such as ammonia (\chem{NH_3}), aniline (\chem{C_6H_7N}), and pyridine (\chem{C_5H_5N}), where phosphorus is predominantly present in pentavalent state. The basicities of the interacting partner (\chem{NH_3},\chem{C_6H_7N},\chem{C_5H_5N}) completely influences the geometrical preference of all these dimers. The \chem{POCl_3}-\chem{NH_3} dimer is anticipated to have a hydrogen bonded geometry, however with hydrogen bonding, a P...N pnicogen bonding plays a definite and a non-trivial role in their overall stabilization. An interesting paradigm transformation was noticed in \chem{POCl_3}-\chem{C_6H_7N} and \chem{POCl_3}-\chem{C_5H_5N} heterodimers, where P...N pnicogen bonding was observed to completely dominate the hydrogen bonding. Furthermore, the characteristic interactions were investigated through electrostatic potential mapping, energy decomposition and non covalent interaction analyses

Hybrid Approach for Emotion Classification of Audio Conversation Based on Text and Speech Mining

AbstractOne of the greatest challenges in speech technology is estimating the speaker's emotion. Most of the existing approaches concentrate either on audio or text features. In this work, we propose a novel approach for emotion classification of audio conversation based on both speech and text. The novelty in this approach is in the choice of features and the generation of a single feature vector for classification. Our main intention is to increase the accuracy of emotion classification of speech by considering both audio and text features. In this work we use standard methods such as Natural Language Processing, Support Vector Machines, WordNet Affect and SentiWordNet. The dataset for this work have been taken from Semval -2007 and eNTERFACE’05 EMOTION Database

Medical Image Segmentation Using Modified K Means And Cellular Automata Algorithms

ABSTRACT Segmentation is widely used in medical industry to get abnormal growth data from the medical image like MRI and CT .In this paper, I present a fast and robust practical tool for segmentation of solid tumors with minimal user interaction .K Means based seeded tumor segmentation method on contrast enhanced T1 weighted magnetic resonance (MR) images, is proposed. And the result is compared against Cellular automata based tumor segmentation method. Seed points are selected as the intersection of maximum white points row wise and column wise . First the seed pixels of tumor and background are fed to the algorithm. Using this seeds, the algorithm finds the strength maps for both tumor and background image .This maps are then combined to get the tumor probability map. Comparison studies on both clinical and synthetic brain tumor datasets for both this methods demonstrate performance of the proposed algorithm( K Means)in terms of, its efficiency and accuracy

Visual categorization and the parietal cortex

The primate brain is adept at rapidly grouping items and events into functional classes, or categories, in order to recognize the significance of stimuli and guide behavior. Higher cognitive functions have traditionally been considered the domain of frontal areas. However, increasing evidence suggests that parietal cortex is also involved in categorical and associative processes. Previous work showed that the parietal cortex is highly involved in spatial processing, attention, and saccadic eye movement planning, and more recent studies have found decision-making signals in lateral intraparietal area (LIP). We recently found that a subdivision of parietal cortex, LIP, reflects learned categories for multiple types of visual stimuli. Additionally, a comparison of categorization signals in parietal and frontal areas found stronger and earlier categorization signals in parietal cortex arguing that, in trained animals, parietal abstract association or category signals are unlikely to arise via feedback from prefrontal cortex (PFC)

Regional Planning Framework for Addressing Flood Vulnerability of a Metropolitan Region: The Case of Malappuram, Kerala, India

Flood susceptibility is becoming increasingly important among the various natural disasters in terms of environmental, economic, and social consequences. The eco-regional planning approach, which incorporates the ecological boundary as a layer in the spatial planning process of settlements, is one of the most innovative concepts in recent research to address these problems. Hence, this research interrogated flood susceptibility mapping tools using an appropriate model for better settlement planning and management. A frequency ratio model was applied to a case region, Malappuram (in  the State of Kerala, India), one of the world’s fastest urbanizing metropolitan regions, using a three-tier assessment framework. A frequency ratio database for flood susceptibility mapping was created by combining historic flood locations with independent factors. The study region was divided into five flood-risk zones based on the computed flood susceptibility index, which varied from 0 to 18.38, i.e., very high, high, moderate, low, and very low. The results showed that the high and very high susceptibility classes accounted for 8.82% and 17.17% of the land, respectively. This paper highlights the requirement for a multi-level assessment of an ecologically oriented regional planning regime in India and estimates the success rate of flood prediction at 79.33%. The proposed regional planning framework is therefore essential for local government planners, researchers, and administrators when creating flood mitigation measures, and has the potential to become a substantial and essential instrument

Regional Planning Framework for Addressing Flood Vulnerability of a Metropolitan Region: The Case of Malappuram, Kerala, India

Flood susceptibility is becoming increasingly important among the various natural disasters in terms of environmental, economic, and social consequences. The eco-regional planning approach, which incorporates the ecological boundary as a layer in the spatial planning process of settlements, is one of the most innovative concepts in recent research to address these problems. Hence, this research interrogated flood susceptibility mapping tools using an appropriate model for better settlement planning and management. A frequency ratio model was applied to a case region, Malappuram (in  the State of Kerala, India), one of the world’s fastest urbanizing metropolitan regions, using a three-tier assessment framework. A frequency ratio database for flood susceptibility mapping was created by combining historic flood locations with independent factors. The study region was divided into five flood-risk zones based on the computed flood susceptibility index, which varied from 0 to 18.38, i.e., very high, high, moderate, low, and very low. The results showed that the high and very high susceptibility classes accounted for 8.82% and 17.17% of the land, respectively. This paper highlights the requirement for a multi-level assessment of an ecologically oriented regional planning regime in India and estimates the success rate of flood prediction at 79.33%. The proposed regional planning framework is therefore essential for local government planners, researchers, and administrators when creating flood mitigation measures, and has the potential to become a substantial and essential instrument

A Dual-Polarized Wideband Probe for Near- Field Antenna Measurement

ABSTRACT: Antennas are one of the most important parts of a communication chain. They are used for both communication and calibration purposes. Antenna measurement techniques involving near-field probes have been a recently developing area. New developments in probe technologies have enabled near-field probes with much larger bandwidth. The objective of this Master's Thesis is to design, simulate and fabricate a dual polarized wideband inverted quad ridged shape horn antenna which can be used as measurement probe for near field measurements. Typical probes like Open Ended Waveguides, dipole antenna probes etc are bulky in mobile communication frequency bands. In addition they are narrow band probes. The inverted quad-ridged horn antenna probe not only provides measurement in the much wider range but also provides dual-polarization measurement thus enabling antenna developers to measure UWB, UHF, VHF antennas more precisely and at lower cost. The antenna is designed to meet the characteristics such as high gain, light weight, linearly polarized with suppressed side lobes for near-field measurement applications. The proposed antenna is simulated with commercially available packages such as Ansoft HFSS. The antenna gives a moderate gain over operating range while delivering a wide bandwidth

Implications of Social Media and Socio-Economic Activities on Micro and Small Enterprises in India

Purpose: The purpose of this research is to examine the implications of social media and socio-economic activities on micro and small enterprises in India.   Theoretical framework: The study will be based on the theories of social capital, network effects, and digital divide.   Design/methodology/approach: The research will be conducted using a mixed-methods approach, including both qualitative and quantitative data collection methods. Surveys and interviews will be conducted with micro and small enterprise owners in India to gather data on their use of social media and their socio-economic activities.   Findings: The findings of the study will explore the ways in which social media and socio-economic activities impact the growth and success of micro and small enterprises in India. This includes the potential for increased connectivity and networking opportunities, as well as the potential for digital divide and limited access to resources.   Research, practical and social implications: The research will have implications for policymakers and small business owners in India, as it will provide insight into the potential benefits and challenges of using social media for small business growth and success. It will also contribute to the broader literature on the impact of digital technologies on small businesses in developing countries.   Originality/value: This study fills a gap in the literature by focusing on the specific context of micro and small enterprises in India, and by using a mixed-methods approach to explore the implications of social media and socio-economic activities on these businesses

Design of Low Power and Area Efficient Carry Select Adder (CSLA) using Verilog Language

Carry select method has deemed to be a good compromise between cost and performance in carry propagation adder design. However conventional carry select adder (CSLA) is still area consuming due to the dual ripple carry adder structure. The excessive area overhead makes conventional carry select adder (CSLA) relatively unattractive but this has been the circumvented by the use of add-one circuit. In this an area efficient modified CSLA scheme based on a new first zero detection logic is proposed. The gate count in 32-bit modified CSLA can be greatly reduced, design proposed in this paper has been developed using VERILOG language and synthesized in XILINX13.2 version