Real Life Design: A Case Study in Universal Design

2017 ◽  
Vol 109 (4) ◽  
pp. 14-20
Author(s):  
Julia O. Beamish ◽  
Eunju Hwang ◽  
Kathleen Parrott ◽  
Margaret Carneal
Keyword(s):  
Universal Design ◽  
Real Life ◽  
Life Design

Contamination Lab of Turin (CLabTo)

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Eleonora FIORE ◽  
Giuliano SANSONE ◽  
Chiara Lorenza REMONDINO ◽  
Paolo Marco TAMBORRINI
Keyword(s):  
University Students ◽  
Single Case ◽  
Real Life ◽  
Learning By Doing ◽  
Assessment Data ◽  
Entrepreneurial Skills ◽  
Fields Of Study ◽  
Education Levels ◽  
Positive Effect

Interest in offering Entrepreneurship Education (EE) to all kinds of university students is increasing. Therefore, universities are increasing the number of entrepreneurship courses intended for students from different fields of study and with different education levels. Through a single case study of the Contamination Lab of Turin (CLabTo), we suggest how EE may be taught to all kinds of university students. We have combined design methods with EE to create a practical-oriented entrepreneurship course which allows students to work in transdisciplinary teams through a learning-by-doing approach on real-life projects. Professors from different departments have been included to create a multidisciplinary environment. We have drawn on programme assessment data, including pre- and post-surveys. Overall, we have found a positive effect of the programme on the students’ entrepreneurial skills. However, when the data was broken down according to the students’ fields of study and education levels, mixed results emerged.

Participation and spatial transformation in large housing estates in Poland. Case study of Ursynów Północny

2018 ◽  
Vol 60 (1) ◽  
pp. 55-65
Author(s):  
Krystyna Ilmurzyńska
Keyword(s):  
Basic Assumption ◽  
Real Life ◽  
Business Environment ◽  
Spatial Transformation ◽  
Reciprocal Relationships ◽  
Spatial Transformations ◽  
Large Housing Estates ◽  
Existing Housing ◽  
Housing Estates

Abstract This article investigates the suitability of traditional and participatory planning approaches in managing the process of spatial development of existing housing estates, based on the case study of Warsaw’s Ursynów Północny district. The basic assumption of the article is that due to lack of government schemes targeted at the restructuring of large housing estates, it is the business environment that drives spatial transformations and through that shapes the development of participation. Consequently the article focuses on the reciprocal relationships between spatial transformations and participatory practices. Analysis of Ursynów Północny against the background of other estates indicates that it presents more endangered qualities than issues to be tackled. Therefore the article focuses on the potential of the housing estate and good practices which can be tracked throughout its lifetime. The paper focuses furthermore on real-life processes, addressing the issue of privatisation, development pressure, formal planning procedures and participatory budgeting. In the conclusion it attempts to interpret the existing spatial structure of the estate as a potential framework for a participatory approach.

Bleak Weather for Sun-Shine AG: A Case Study of Impairment of Assets

2014 ◽  
Vol 30 (2) ◽  
pp. 113-126 ◽  
Author(s):  
Dominic Detzen ◽  
Tobias Stork genannt Wersborg ◽  
Henning Zülch
Keyword(s):  
Real Life ◽  
Accounting Standards ◽  
Point Of View ◽  
Professional Judgment ◽  
Economic Point ◽  
Instructional Resource

ABSTRACT This case originates from a real-life business situation and illustrates the application of impairment tests in accordance with IFRS and U.S. GAAP. In the first part of the case study, students examine conceptual questions of impairment tests under IFRS and U.S. GAAP with respect to applicable accounting standards, definitions, value concepts, and frequency of application. In addition, the case encourages students to discuss the impairment regime from an economic point of view. The second part of the instructional resource continues to provide instructors with the flexibility of applying U.S. GAAP and/or IFRS when students are asked to test a long-lived asset for impairment and, if necessary, allocate any potential impairment. This latter part demonstrates that impairment tests require professional judgment that students are to exercise in the case.

Design and Real-life Deployment of a Smart Nanogrid: A Greek Case Study

2020 ◽  
Author(s):  
Apostolos C. Tsolakis ◽  
Angelina D. Bintoudi ◽  
Lampros Zyglakis ◽  
Stylianos Zikos ◽  
Christos Timplalexis ◽  
...  
Keyword(s):  
Real Life

scholarly journals Investigating the Potential of Network Optimization for a Constrained Object Detection Problem

2021 ◽  
Vol 7 (4) ◽  
pp. 64
Author(s):  
Tanguy Ophoff ◽  
Cédric Gullentops ◽  
Kristof Van Beeck ◽  
Toon Goedemé
Keyword(s):  
Computational Complexity ◽  
Object Detection ◽  
Network Optimization ◽  
Real Life ◽  
Optimization Techniques ◽  
Training Data ◽  
Single Shot ◽  
Standard Object ◽  
Number Of Classes

Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situations: they have a limited number of classes to be detected, less intra-class variance, less lighting and background variance, constrained or even fixed camera viewpoints, etc. In these cases, we hypothesize that smaller networks could be used without deteriorating the accuracy. However, there are multiple reasons why this does not happen in practice. Firstly, overparameterized networks tend to learn better, and secondly, transfer learning is usually used to reduce the necessary amount of training data. In this paper, we investigate how much we can reduce the computational complexity of a standard object detection network in such constrained object detection problems. As a case study, we focus on a well-known single-shot object detector, YoloV2, and combine three different techniques to reduce the computational complexity of the model without reducing its accuracy on our target dataset. To investigate the influence of the problem complexity, we compare two datasets: a prototypical academic (Pascal VOC) and a real-life operational (LWIR person detection) dataset. The three optimization steps we exploited are: swapping all the convolutions for depth-wise separable convolutions, perform pruning and use weight quantization. The results of our case study indeed substantiate our hypothesis that the more constrained a problem is, the more the network can be optimized. On the constrained operational dataset, combining these optimization techniques allowed us to reduce the computational complexity with a factor of 349, as compared to only a factor 9.8 on the academic dataset. When running a benchmark on an Nvidia Jetson AGX Xavier, our fastest model runs more than 15 times faster than the original YoloV2 model, whilst increasing the accuracy by 5% Average Precision (AP).

scholarly journals DOLARS, a Distributed On-Line Activity Recognition System by Means of Heterogeneous Sensors in Real-Life Deployments—A Case Study in the Smart Lab of The University of Almería

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 405
Author(s):  
Marcos Lupión ◽  
Javier Medina-Quero ◽  
Juan F. Sanjuan ◽  
Pilar M. Ortigosa
Keyword(s):  
Real Time ◽  
Activity Recognition ◽  
Real Life ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Heterogeneous Sensors ◽  
On Line ◽  
The University

Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real time, including binary, wearable and location sensors. Different descriptors and metrics from the heterogeneous sensor data are integrated in a common feature vector whose extraction is developed by a sliding window approach under real-time conditions. DOLARS provides a distributed architecture where: (i) stages for processing data in AR are deployed in distributed nodes, (ii) temporal cache modules compute metrics which aggregate sensor data for computing feature vectors in an efficient way; (iii) publish-subscribe models are integrated both to spread data from sensors and orchestrate the nodes (communication and replication) for computing AR and (iv) machine learning algorithms are used to classify and recognize the activities. A successful case study of daily activities recognition developed in the Smart Lab of The University of Almería (UAL) is presented in this paper. Results present an encouraging performance in recognition of sequences of activities and show the need for distributed architectures to achieve real time recognition.

scholarly journals Research on feeder network design: a case study of feeder service for the port of Kotka

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Yisong Lin ◽  
Xuefeng Wang ◽  
Hao Hu ◽  
Hui Zhao
Keyword(s):  
Control System ◽  
Numerical Experiment ◽  
Network Design ◽  
Evaluation System ◽  
Real Life ◽  
Objective Evaluation ◽  
Multi Objective Optimization ◽  
Real Life Data ◽  
The Mathematical Model

Abstract By exemplifying the feeder service for the port of Kotka, this study proposed a multi-objective optimization model for feeder network design. Innovative for difference from the single-objective evaluation system, the objective of feeder network design was proposed to include single allocation cost, intra-Europe cargo revenue, equipment balance, sailing cycle, allocation utilization, service route competitiveness, and stability. A three-stage control system was presented, and numerical experiment based on container liner’s real life data was conducted to verify the mathematical model and the control system. The numerical experiment revealed that the three-stage control system is effective and practical, and the research ideas had been applicable with satisfactory effect.

scholarly journals Extending Multilevel Statistical Entropy Analysis towards Plastic Recyclability Prediction

2021 ◽  
Vol 13 (6) ◽  
pp. 3553
Author(s):  
Philippe Nimmegeers ◽  
Alexej Parchomenko ◽  
Paul De Meulenaere ◽  
Dagmar R. D’hooge ◽  
Paul H. M. Van Steenberge ◽  
...  
Keyword(s):  
Circular Economy ◽  
Real Life ◽  
Plastic Waste ◽  
Entropy Analysis ◽  
Waste Collection ◽  
Statistical Entropy ◽  
Waste Streams ◽  
Material Component ◽  
Future Work

Multilevel statistical entropy analysis (SEA) is a method that has been recently proposed to evaluate circular economy strategies on the material, component and product levels to identify critical stages of resource and functionality losses. However, the comparison of technological alternatives may be difficult, and equal entropies do not necessarily correspond with equal recyclability. A coupling with energy consumption aspects is strongly recommended but largely lacking. The aim of this paper is to improve the multilevel SEA method to reliably assess the recyclability of plastics. Therefore, the multilevel SEA method is first applied to a conceptual case study of a fictitious bag filled with plastics, and the possibilities and limitations of the method are highlighted. Subsequently, it is proposed to extend the method with the computation of the relative decomposition energies of components and products. Finally, two recyclability metrics are proposed. A plastic waste collection bag filled with plastic bottles is used as a case study to illustrate the potential of the developed extended multilevel SEA method. The proposed extension allows us to estimate the recyclability of plastics. In future work, this method will be refined and other potential extensions will be studied together with applications to real-life plastic products and plastic waste streams.

scholarly journals Improvements in Energy Saving and Thermal Environment after Retrofitting with Interior Insulation in Intermittently Cooled Residences in Hot-Summer/Cold-Winter Zone of China: A Case Study in Chengdu

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2776
Author(s):  
Xin Ye ◽  
Jun Lu ◽  
Tao Zhang ◽  
Yupeng Wang ◽  
Hiroatsu Fukuda
Keyword(s):  
Energy Saving ◽  
Thermal Environment ◽  
Real Life ◽  
Average Energy ◽  
Experimental Result ◽  
Cold Winter ◽  
The South ◽  
Indoor Thermal Environment ◽  
Space Cooling

Space cooling is currently the fastest-growing end-user in buildings. The global warming trend combined with increased population and economic development will lead to accelerated growth in space cooling in the future, especially in China. The hot summer and cold winter (HSCW) zone is the most densely populated and economically developed region in China, but with the worst indoor thermal environment. Relatively few studies have been conducted on the actual measurements in the optimization of insulation design under typical intermittent cooling modes in this region. This case study was conducted in Chengdu—the two residences selected were identical in design, but the south bedroom of the case study residence had interior insulation (inside insulation on all opaque interior surfaces of a space) retrofitted in the bedroom area in 2017. In August 2019, a comparative on-site measurement was done to investigate the effect of the retrofit work under three typical intermittent cooling patterns in the real-life scenario. The experimental result shows that interior insulation provides a significant improvement in energy-saving and the indoor thermal environment. The average energy savings in daily cooling energy consumption of the south bedroom is 42.09%, with the maximum reaching 48.91%. In the bedroom with interior insulation retrofit, the indoor temperature is closer to the set temperature and the vertical temperature difference is smaller during the cooling period; when the air conditioner is off, the room remains a comfortable temperature for a slightly longer time.

Multi-objective robust-stochastic optimisation of relief goods distribution under uncertainty: a real-life case study

2021 ◽  
pp. 1-22
Author(s):  
Zuhayer Mahtab ◽  
Abdullahil Azeem ◽  
Syed Mithun Ali ◽  
Sanjoy Kumar Paul ◽  
Amir Mohammad Fathollahi-Fard
Keyword(s):  
Real Life ◽  
Multi Objective ◽  
Stochastic Optimisation
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