scholarly journals Expanding Boundaries - Towards Integrated Design Strategies For Implementing BIPV Systems into Urban Renewal Processes: First Case Study in Neuchâtel (Switzerland) – S. Aguacil, S. Lufkin, E. Rey

2016 ◽  
Author(s):  
Aguacil, S. ◽  
Lufkin, S. ◽  
Rey, E.
Keyword(s):  
Urban Renewal ◽  
Integrated Design ◽  
Renewal Processes ◽  
Design Strategies ◽  
First Case

Scales and Units

2018 ◽  
Author(s):  
Kathryn M. de Luna
Keyword(s):  
Language Change ◽  
Historical Linguistics ◽  
Bantu Languages ◽  
The North ◽  
First Case ◽  
Linguistic Evidence ◽  
River Region ◽  
History Of ◽  
Alternative Approaches

This chapter uses two case studies to explore how historians study language movement and change through comparative historical linguistics. The first case study stands as a short chapter in the larger history of the expansion of Bantu languages across eastern, central, and southern Africa. It focuses on the expansion of proto-Kafue, ca. 950–1250, from a linguistic homeland in the middle Kafue River region to lands beyond the Lukanga swamps to the north and the Zambezi River to the south. This expansion was made possible by a dramatic reconfiguration of ties of kinship. The second case study explores linguistic evidence for ridicule along the Lozi-Botatwe frontier in the mid- to late 19th century. Significantly, the units and scales of language movement and change in precolonial periods rendered visible through comparative historical linguistics bring to our attention alternative approaches to language change and movement in contemporary Africa.

Applications of random graphs

2017 ◽  
Author(s):  
A.C.C. Coolen ◽  
A. Annibale ◽  
E.S. Roberts
Keyword(s):  
Social Networks ◽  
Random Graphs ◽  
Interaction Network ◽  
Power Grids ◽  
Protein Protein Interaction ◽  
Topological Features ◽  
First Case ◽  
The Stability ◽  
Protein Protein Interaction Network

This chapter reviews graph generation techniques in the context of applications. The first case study is power grids, where proposed strategies to prevent blackouts have been tested on tailored random graphs. The second case study is in social networks. Applications of random graphs to social networks are extremely wide ranging – the particular aspect looked at here is modelling the spread of disease on a social network – and how a particular construction based on projecting from a bipartite graph successfully captures some of the clustering observed in real social networks. The third case study is on null models of food webs, discussing the specific constraints relevant to this application, and the topological features which may contribute to the stability of an ecosystem. The final case study is taken from molecular biology, discussing the importance of unbiased graph sampling when considering if motifs are over-represented in a protein–protein interaction network.

Investigating the potential of redundant manipulators in narrow channels

2020 ◽  
pp. 095440622096451
Author(s):  
Ashish Singla ◽  
Jyotindra Narayan ◽  
Himanshu Arora
Keyword(s):  
Case Studies ◽  
Fuzzy Inference ◽  
Redundant Manipulators ◽  
Redundancy Resolution ◽  
Inference System ◽  
Narrow Channels ◽  
First Case ◽  
Task Priority ◽  
Patient Side

In this paper, an attempt has been made to investigate the potential of redundant manipulators, while tracking trajectories in narrow channels. The behavior of redundant manipulators is important in many challenging applications like under-water welding in narrow tanks, checking the blockage in sewerage pipes, performing a laparoscopy operation etc. To demonstrate this snake-like behavior, redundancy resolution scheme is utilized using two different approaches. The first approach is based on the concept of task priority, where a given task is split and prioritize into several subtasks like singularity avoidance, obstacle avoidance, torque minimization, and position preference over orientation etc. The second approach is based on Adaptive Neuro Fuzzy Inference System (ANFIS), where the training is provided through given datasets and the results are back-propagated using augmentation of neural networks with fuzzy logics. Three case studies are considered in this work to demonstrate the redundancy resolution of serial manipulators. The first case study of 3-link manipulator is attempted with both the approaches, where the objective is to track the desired trajectory while avoiding multiple obstacles. The second case study of 7-link manipulator, tracking trajectory in a narrow channel, is investigated using the concept of task priority. The realistic application of minimum-invasive surgery (MIS) based trajectory tracking is considered as the third case study, which is attempted using ANFIS approach. The 5-link spatial redundant manipulator, also known as a patient-side manipulator being developed at CSIR-CSIO, Chandigarh is used to track the desired surgical cuts. Through the three case studies, it is well demonstrated that both the approaches are giving satisfactory results.

scholarly journals APPLICATION OF DOMAIN INTEGRATED DESIGN METHODOLOGY FOR BIO-INSPIRED DESIGN- A CASE STUDY OF SUTURE PIN DESIGN

2021 ◽  
Vol 1 ◽  
pp. 487-496
Author(s):  
Pavan Tejaswi Velivela ◽  
Nikita Letov ◽  
Yuan Liu ◽  
Yaoyao Fiona Zhao
Keyword(s):  
Cross Sections ◽  
Design Methodology ◽  
Reaction Force ◽  
Integrated Design ◽  
Total Deformation ◽  
Insertion Force ◽  
Force Reaction ◽  
The Moment ◽  
Work Done

AbstractThis paper investigates the design and development of bio-inspired suture pins that would reduce the insertion force and thereby reducing the pain in the patients. Inspired by kingfisher's beak and porcupine quills, the conceptual design of the suture pin is developed by using a unique ideation methodology that is proposed in this research. The methodology is named as Domain Integrated Design, which involves in classifying bio-inspired structures into various domains. There is little work done on such bio-inspired multifunctional aspect. In this research we have categorized the vast biological functionalities into domains namely, cellular structures, shapes, cross-sections, and surfaces. Multi-functional bio-inspired structures are designed by combining different domains. In this research, the hypothesis is verified by simulating the total deformation of tissue and the needle at the moment of puncture. The results show that the bio-inspired suture pin has a low deformation on the tissue at higher velocities at the puncture point and low deformation in its own structure when an axial force (reaction force) is applied to its tip. This makes the design stiff and thus require less force of insertion.

scholarly journals Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Markus J. Ankenbrand ◽  
Liliia Shainberg ◽  
Michael Hock ◽  
David Lohr ◽  
Laura M. Schreiber
Keyword(s):  
Neural Networks ◽  
Sensitivity Analysis ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cardiac Mri ◽  
Magnetic Resonance Images ◽  
Model Interpretation ◽  
First Case ◽  
Segmentation Models

Abstract Background Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance. Results We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model. Conclusions Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.

scholarly journals From Eco-Urbanism to Eco-Fusion: An Augmented Multi-Scalar Framework in Sustainable Urbanism

2021 ◽  
Vol 13 (4) ◽  
pp. 2373
Author(s):  
Ali Cheshmehzangi ◽  
Andrew Flynn ◽  
May Tan-Mullins ◽  
Linjun Xie ◽  
Wu Deng ◽  
...  
Keyword(s):  
Best Practice ◽  
Sustainable Urban Development ◽  
Design Strategies ◽  
Development Models ◽  
Exploratory Case Study ◽  
Sustainable Urbanism ◽  
Integrated Methods ◽  
Practical Factors ◽  
Key Terms

This paper introduces the new concept of “eco-fusion” through an exploratory case study project. It suggests the importance of multi-scalar practice in the broader field of eco-urbanism. This study introduces eco-fusion as a multiplexed paradigm, which is then discussed in two different development models. This paper first highlights the position of “eco” in urbanism by providing a brief account of key terms and how they relate to one another. It then points out the associations between eco-fusion and sustainable urban development. Through an exploratory case study example in China, the practical factors of eco-development are assessed. The study aims to provide a set of intermediate development stages while maintaining each spatial level’s interface in their own defined and distinguished contexts. The key objective is to consider integrating the natural and built environments, which is considered the best practice of eco-development in urbanism. This study’s findings highlight integrated methods in eco-urbanism and suggest new directions for eco-planning/eco-design strategies.

scholarly journals Landscape design approaches to enhance human–wildlife interactions in a compact tropical city

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yun Hye Hwang ◽  
Anuj Jain
Keyword(s):  
Wildlife Conservation ◽  
Relevant Literature ◽  
Urban Landscapes ◽  
Design Strategies ◽  
Compact City ◽  
Public Preference ◽  
Conservation Principles ◽  
Design Projects ◽  
Collaborative Efforts

Abstract Urban landscapes have the potential to conserve wildlife. Despite increasing recognition of this potential, there are few collaborative efforts to integrate ecology and conservation principles into context-dependent, spatial and actionable design strategies. To address this issue and to encourage multi-disciplinary research on urban human–wildlife interactions, we ask the following questions. To what extent should design and planning actions be aligned with urban ecology in the context of a compact city? How can wildlife conservation meet the seemingly conflictual demands of urban development and public preference? To answer these questions, we refer to the relevant literature and a number of design projects. Using the compact tropical city of Singapore as a case study, we propose 12 design strategies. We encourage designers and planners to strengthen the links between wildlife and urban dwellers and promote wildlife conservation within cities.

scholarly journals Novel filter bank-based cooperative spectrum sensing under practical challenges for beyond 5G cognitive radios

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Sener Dikmese ◽  
Kishor Lamichhane ◽  
Markku Renfors
Keyword(s):  
Spectrum Sensing ◽  
Filter Bank ◽  
Cooperative Spectrum Sensing ◽  
Minimum Energy ◽  
Cognitive Radios ◽  
Spectrum Management ◽  
Wireless Channel ◽  
First Case ◽  
Channel Effects

AbstractCognitive radio (CR) technology with dynamic spectrum management capabilities is widely advocated for utilizing effectively the unused spectrum resources. The main idea behind CR technology is to trigger secondary communications to utilize the unused spectral resources. However, CR technology heavily relies on spectrum sensing techniques which are applied to estimate the presence of primary user (PU) signals. This paper firstly focuses on novel analysis filter bank (AFB) and FFT-based cooperative spectrum sensing (CSS) techniques as conceptually and computationally simplified CSS methods based on subband energies to detect the spectral holes in the interesting part of the radio spectrum. To counteract the practical wireless channel effects, collaborative subband-based approaches of PU signal sensing are studied. CSS has the capability to relax the problems of both hidden nodes and fading multipath channels. FFT- and AFB-based receiver side sensing methods are applied for OFDM waveform and filter bank-based multicarrier (FBMC) waveform, respectively, the latter one as a candidate beyond-OFDM/beyond-5G scheme. Subband energies are then applied for enhanced energy detection (ED)-based CSS methods that are proposed in the context of wideband, multimode sensing. Our first case study focuses on sensing potential spectral gaps close to relatively strong primary users, considering also the effects of spectral regrowth due to power amplifier nonlinearities. The study shows that AFB-based CSS with FBMC waveform is able to improve the performance significantly. Our second case study considers a novel maximum–minimum energy detector (Max–Min ED)-based CSS. The proposed method is expected to effectively overcome the issue of noise uncertainty (NU) with remarkably lower implementation complexity compared to the existing methods. The developed algorithm with reduced complexity, enhanced detection performance, and improved reliability is presented as an attractive solution to counteract the practical wireless channel effects under low SNR. Closed-form analytic expressions are derived for the threshold and false alarm and detection probabilities considering frequency selective scenarios under NU. The validity of the novel expressions is justified through comparisons with respective results from computer simulations.

scholarly journals Bioclimatic and Regenerative Design Guidelines for a Circular University Campus in India

2021 ◽  
Vol 13 (15) ◽  
pp. 8238
Author(s):  
Noemi Bakos ◽  
Rosa Schiano-Phan
Keyword(s):  
Construction Industry ◽  
Assessment Tool ◽  
Economic Benefits ◽  
Design Guidelines ◽  
University Campus ◽  
Design Strategies ◽  
Regenerative Design ◽  
Governmental Institutions ◽  
Social Environmental

To transform the negative impacts of buildings on the environment into a positive footprint, a radical shift from the current, linear ‘make-use-dispose’ practice to a closed-loop ‘make-use-return’ system, associated with a circular economy, is necessary. This research aims to demonstrate the possible shift to a circular construction industry by developing the first practical framework with tangible benchmarks for a ‘Circular University Campus’ based on an exemplary case study project, which is a real project development in India. As a first step, a thorough literature review was undertaken to demonstrate the social, environmental and economic benefits of a circular construction industry. As next step, the guideline for a ‘Circular University Campus’ was developed, and its applicability tested on the case study. As final step, the evolved principles were used to establish ‘Project Specific Circular Building Indicators’ for a student residential block and enhance the proposed design through bioclimatic and regenerative design strategies. The building’s performance was evaluated through computational simulations, whole-life carbon analysis and a circular building assessment tool. The results demonstrated the benefits and feasibility of bioclimatic, regenerative building and neighbourhood design and provided practical prototypical case study and guidelines which can be adapted by architects, planners and governmental institutions to other projects, thereby enabling the shift to a restorative, circular construction industry.

scholarly journals Geospatial Serverless Computing: Architectures, Tools and Future Directions

2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey
Keyword(s):  
Big Data ◽  
Forest Cover ◽  
Mineral Resources ◽  
Hyperspectral Data ◽  
Real Time Analysis ◽  
First Case ◽  
Amazon Web Services ◽  
Aws Lambda ◽  
Physical Features

Several real-world applications involve the aggregation of physical features corresponding to different geographic and topographic phenomena. This information plays a crucial role in analyzing and predicting several events. The application areas, which often require a real-time analysis, include traffic flow, forest cover, disease monitoring and so on. Thus, most of the existing systems portray some limitations at various levels of processing and implementation. Some of the most commonly observed factors involve lack of reliability, scalability and exceeding computational costs. In this paper, we address different well-known scalable serverless frameworks i.e., Amazon Web Services (AWS) Lambda, Google Cloud Functions and Microsoft Azure Functions for the management of geospatial big data. We discuss some of the existing approaches that are popularly used in analyzing geospatial big data and indicate their limitations. We report the applicability of our proposed framework in context of Cloud Geographic Information System (GIS) platform. An account of some state-of-the-art technologies and tools relevant to our problem domain are discussed. We also visualize performance of the proposed framework in terms of reliability, scalability, speed and security parameters. Furthermore, we present the map overlay analysis, point-cluster analysis, the generated heatmap and clustering analysis. Some relevant statistical plots are also visualized. In this paper, we consider two application case-studies. The first case study was explored using the Mineral Resources Data System (MRDS) dataset, which refers to worldwide density of mineral resources in a country-wise fashion. The second case study was performed using the Fairfax Forecast Households dataset, which signifies the parcel-level household prediction for 30 consecutive years. The proposed model integrates a serverless framework to reduce timing constraints and it also improves the performance associated to geospatial data processing for high-dimensional hyperspectral data.

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