Modeling and signal processing of GPR system

Ground Penetrating Radar (GPR) is a geo-sensor, which is used for detecting, locating, identifying and 3D imaging of the buried target inside the shallow surface. It is very difficult to detect and locate the target when limited amount of information is delivered by geo-sensor. On the basis of scattering parameter we try to extract information (related to feature of surface and target) as many as possible. Geometrical modeling of ground and target, as well as mathematical modeling for transmitting and receiving signal are the key factor in the field of GPR research. Receiving signal is nothing but the scaled version of transmitting signal which is affected by noise. So for mathematical modeling of receiving signal, scaling parameter and noise plays a vital role. Whereas in signal processing domain time and frequency are the observation parameter. In signal processing cross correlation, windowing technique and time domain gating are the excellent features, which help in delay measurement, for suppression of an unwanted frequency and for extracting the time domain information of GPR signal at any specified duration. SFCW technique is a modern technique which is more applicable in GPR comparison to conventional FMCW technique. This technique can be operated at low power and license free band (ISM band)

ACO for continuous function optimization: a performance analysis

The performance of the meta-heuristic algorithms often depends on their parameter settings. Appropriate tuning of the underlying parameters can drastically improve the performance of a meta-heuristic. The Ant Colony Optimization (ACO), a population based meta-heuristic algorithm inspired by the foraging behavior of the ants, is no different. Fundamentally, the ACO depends on the construction of new solutions, variable by variable basis using Gaussian sampling of the selected variables from an archive of solutions. A comprehensive performance analysis of the underlying parameters such as: selection strategy, distance measure metric and pheromone evaporation rate of the ACO suggests that the Roulette Wheel Selection strategy enhances the performance of the ACO due to its ability to provide non-uniformity and adequate diversity in the selection of a solution. On the other hand, the Squared Euclidean distance-measure metric offers better performance than other distance-measure metrics. It is observed from the analysis that the ACO is sensitive towards the evaporation rate. Experimental analysis between classical ACO and other meta-heuristic suggested that the performance of the well-tuned ACO surpasses its counterparts

Understanding the Role and Importance of Design Problems in Creativity Research

The overall objective of this research is to address the need for using similar conceptual design problems in experiments in engineering design creativity. This is accomplished by addressing three sub-objectives i) to identify the pattern of design problem usage, ii) to enable comparison between two conceptual design problems based on their natural language representations and iii) to analyze the impact of design problems on effectiveness of example interventions used in user studies in engineering design creativity. Design problems are an essential component of experiments in creativity research.The requirements of experiment’s design sometimes limit problem sharing between researchers or studies conducted by them. For understanding and identifying the design problem usage pattern, two network representations of design problems, connected to each other by authors and papers using them has been used. Both networks indicate that several problems have been used for creativity experiments and suggest the need for using same or ‘similar’ design problems to reduce between-study differences in design problem usage.This addresses the first objective of identifying pattern of design problem usage in creativity research. Problem similarity is assessed using two methods. The first method is based on identification of five structural elements of a design problem namely goals of a problem, functional requirements, non – functional requirements, reference to an existing product and information about end user. The protocol for identifying these elements in problem statement and then comparing design problems is illustrated through two examples. The second method for similarity assessment is based on Latent Semantic Analysis (LSA) of problem statements. LSA provides an objective method to compare semantic similarity of problem statements. Both methods help address the research objective of comparing problems based on their representation but fail to evaluate problem solvability. For understanding whether design problems influence the effectiveness of examples used as interventions, a meta-regression model between effect size and problem size has been used. Regression models suggest that problem size might have a linear relationship with effectiveness of examples for quantity of ideas produced by treatment group participants but enough evidence did not exist to suggest similar relationship for metrics quality and novelty. This addresses the sub-objective of design problems affecting the effectiveness of methods tested in experiments and overall objective of the need for using similar problems in creativity research

Role of a digital clinical decision-support system in management of chronic obstructive pulmonary disease

Postponed access: the file will be accessible after 2022-05-18M.Phil. in Global Health - ThesisINTH395AMAMD-GLO

Topology Optimization of Lightweight Structural Composites Inspired by Cuttlefish Bone

Lightweight material structure is a crucial subject in product design. The lightweight material has high strength to weight proportion which turns into an immense fascination and a territory of investigation for the researchers as its application is wide and expanding consistently. Lightweight composite material design is accomplished by choice of the cellular structure and its optimization. Cellular structure is utilized as it has wide multifunctional properties with lightweight characteristics. Unless it has been topologically optimized, each part in a assembly most likely weighs more than it needs to. Additional weight implies abundance materials are being utilized, loads on moving parts are higher than would normally be appropriate, energy effectiveness is being reduced and increase in costs. Presently, with Topology Optimization innovation, products can be design durable, lightweight for any kind of applications. In this thesis, the design and forecast of cellular structure\u27s performance are presented for developing lightweight cellular composites strengthened by carbon fibers. A 3D cuttlefish bone structure inspired by bio material is presented. With help of topology optimization and finite element analysis, analysis was directed on different volume percentage to characterize the cellular structure for its strength and stiffness. In addition, non-linear analysis was conducted to examine the behavior of the cellular structure with an-isotropic properties

Multi-task near-field perception for autonomous driving using surround-view fisheye cameras

Die Bildung der Augen führte zum Urknall der Evolution. Die Dynamik änderte sich von einem primitiven Organismus, der auf den Kontakt mit der Nahrung wartete, zu einem Organismus, der durch visuelle Sensoren gesucht wurde. Das menschliche Auge ist eine der raffiniertesten Entwicklungen der Evolution, aber es hat immer noch Mängel. Der Mensch hat über Millionen von Jahren einen biologischen Wahrnehmungsalgorithmus entwickelt, der in der Lage ist, Autos zu fahren, Maschinen zu bedienen, Flugzeuge zu steuern und Schiffe zu navigieren. Die Automatisierung dieser Fähigkeiten für Computer ist entscheidend für verschiedene Anwendungen, darunter selbstfahrende Autos, Augmented Realität und architektonische Vermessung. Die visuelle Nahfeldwahrnehmung im Kontext von selbstfahrenden Autos kann die Umgebung in einem Bereich von 0 - 10 Metern und 360° Abdeckung um das Fahrzeug herum wahrnehmen. Sie ist eine entscheidende Entscheidungskomponente bei der Entwicklung eines sichereren automatisierten Fahrens. Jüngste Fortschritte im Bereich Computer Vision und Deep Learning in Verbindung mit hochwertigen Sensoren wie Kameras und LiDARs haben ausgereifte Lösungen für die visuelle Wahrnehmung hervorgebracht. Bisher stand die Fernfeldwahrnehmung im Vordergrund. Ein weiteres wichtiges Problem ist die begrenzte Rechenleistung, die für die Entwicklung von Echtzeit-Anwendungen zur Verfügung steht. Aufgrund dieses Engpasses kommt es häufig zu einem Kompromiss zwischen Leistung und Laufzeiteffizienz. Wir konzentrieren uns auf die folgenden Themen, um diese anzugehen: 1) Entwicklung von Nahfeld-Wahrnehmungsalgorithmen mit hoher Leistung und geringer Rechenkomplexität für verschiedene visuelle Wahrnehmungsaufgaben wie geometrische und semantische Aufgaben unter Verwendung von faltbaren neuronalen Netzen. 2) Verwendung von Multi-Task-Learning zur Überwindung von Rechenengpässen durch die gemeinsame Nutzung von initialen Faltungsschichten zwischen den Aufgaben und die Entwicklung von Optimierungsstrategien, die die Aufgaben ausbalancieren.The formation of eyes led to the big bang of evolution. The dynamics changed from a primitive organism waiting for the food to come into contact for eating food being sought after by visual sensors. The human eye is one of the most sophisticated developments of evolution, but it still has defects. Humans have evolved a biological perception algorithm capable of driving cars, operating machinery, piloting aircraft, and navigating ships over millions of years. Automating these capabilities for computers is critical for various applications, including self-driving cars, augmented reality, and architectural surveying. Near-field visual perception in the context of self-driving cars can perceive the environment in a range of 0 - 10 meters and 360° coverage around the vehicle. It is a critical decision-making component in the development of safer automated driving. Recent advances in computer vision and deep learning, in conjunction with high-quality sensors such as cameras and LiDARs, have fueled mature visual perception solutions. Until now, far-field perception has been the primary focus. Another significant issue is the limited processing power available for developing real-time applications. Because of this bottleneck, there is frequently a trade-off between performance and run-time efficiency. We concentrate on the following issues in order to address them: 1) Developing near-field perception algorithms with high performance and low computational complexity for various visual perception tasks such as geometric and semantic tasks using convolutional neural networks. 2) Using Multi-Task Learning to overcome computational bottlenecks by sharing initial convolutional layers between tasks and developing optimization strategies that balance tasks

Machine Learning Enabled Vital Sign Monitoring System

Internet of Things (IoT)- based remote health monitoring systems have an enormous potential of becoming an integral part of the future medical system. In particular, these systems can play life-saving roles for treating or monitoring patients with critical health issues. On the other hand, it can also reduce pressure on the health-care system by reducing unnecessary hospital visits of patients. Any health care monitoring system must be free from erroneous data, which may arise because of instrument failure or communication errors. In this thesis, machine-learning techniques are implemented to detect reliability and accuracy of data obtained by the IoT-based remote health monitoring. A system is a set-up where vital health signs, namely, blood pressure, respiratory rate, and pulse rate, are collected by using Spire Stone and iHealth Sense devices. This data is then sent to the intermediate device and then to the cloud. In this system, it is assumed that the channel for transmission of data (vital signs) from users to cloud server is error-free. Afterward, the information is extracted from the cloud, and two machine learning techniques, i.e., Support Vector Machines and K-Nearest Neighbor are applied to compare their accuracy in distinguishing correct and erroneous data. The thesis undertakes two different approaches of erroneous data detection. In the first approach, an unsupervised classifier called Auto Encoder (AE) is used for labeling data by using the latent features. Then the labeled data from AE is used as ground truth for comparing the accuracy of supervised learning models. In the second approach, the raw data is labeled based on the correlation between various features. The accuracy comparison is performed between strongly correlated features and weakly correlated features. Finally, the accuracy comparison between two approaches is performed to check which method is performing better for detecting erroneous data for the given dataset

Simplifying Ecommerce

This study is about InterShop. It will explain how InterShop has widely impacted an IT sector due to its amazing features .InterShop helps you manage , present and handle your ecommerce business effectively. InterShop helps you implementing strategies in such a way that helps in increasing sales of your business

Plagiarism Awareness Among Post-Graduate Students and Research Scholars of the Jawaharlal Nehru University and University of Delhi, Delhi: A Comparative Study

The paper overtly and comprehensively presents the awareness of Plagiarism among Post Graduate Students and Research Scholars of two prominent universities viz. Jawaharlal Nehru University and University of Delhi, Delhi. The study employed the survey research methodology and a structured questionnaire was designed keeping in view the stated objectives and was distributed questionnaires among the users in each library and got a total of 296 responses from both library users. The findings of the study revealed that the level of awareness about plagiarism and related aspects among users of Jawaharlal Nehru University is very high in comparison to the University of Delhi. The findings tangibly reflects that 99% users of JNU and 97% of DU are well aware about plagiarism, 157(53.10%) users\u27 of both universities admitted that less/no knowledge of using source properly is the main reason for plagiarism and lastly 109(24%) users\u27 of JNU and 103(68%) of DU are also well aware about plagiarism detection software

Results of open reduction and fixed angle locked volar plate fixation for fracture lower end of radius

Background: The fracture of lower end radius is the most common fracture of upper extremity encountered in practice. Intra-articular fractures of distal radius present a challenging task to the operating surgeon. Open reduction and internal fixation using volar fixed-angle plates has shown to be a valid treatment option for unstable, dorsally displaced distal radial fractures. The present study was undertaken to evaluate the functional outcome of unstable distal radius fractures treated with fixed angle volar locking plate.Methods: The current study aimed at using fixed angle volar locking plate to treat unstable distal radius fractures. A total of 25 patients records were studied comprising of 19 males and 6 females with a mean of 44.5 years and followed up for a maximum of 1.5 year. Fractures were classified using the AO classification. The interpretation of functional outcome was done according to Mayo Wrist Score.Results: At final functional assessment, according to the Mayo wrist score, the scores of 6 patients were excellent, 10 patients good, 8 patients satisfactory and 1 patient poor. No non-union was reported in any patients. 3 patients developed minor complications in the form of superficial infection, hypertrophic scar and reflex sympathetic dystrophy and 1 patient developed major complication in the form of deep infection.Conclusions: Primary volar plate fixation of unstable distal radius fracture provides a stable construct that helps in early mobilization, better functional outcome and minimizes chances of complications and thereby is the treatment of choice for fracture distal end of radius