scholarly journals Layout Construction: A Case Study In Algorithm Engineering

1993 ◽  
Vol 22 (450) ◽  
Author(s):  
Gudmund Skovbjerg Frandsen ◽  
Jens Palsberg ◽  
Erik Meineche Schmidt ◽  
Steen Sjøgaard
Keyword(s):  
Neural Networks ◽  
Combinatorial Optimization ◽  
Heuristic Search ◽  
User Interaction ◽  
Algorithm Engineering ◽  
Aesthetic Appearance ◽  
Automatic Inference ◽  
The Aesthetic ◽  
High Level

<p>We design a system for generating newspaper layout proposals. The input to the system consists of editorial information (text, pictures, etc) and style information (non-editorial information that specifies the aesthetic appearance of a layout). We consider the automation of layout construction to pose two main problems. One problem consists in optimizing the layout with respect to the constraints and preferences specified in the style information. Another problem consists in finding a representation of the style information that both supports its use in the combinatorial optimization and supports its modification through high level user interaction and automatic inference from a database of examples.</p><p> </p><p>We propose a solution that combines <em> heuristic search, randomization </em> and <em> neural networks.</em> We have implemented a first version based on the <var> bisection </var> strategy -- a page is bisected recursively until the number of sub-divisions matches the number of articles to be placed.</p>

scholarly journals Ear Reconstruction Simulation: From Handcrafting to 3D Printing

2019 ◽  
Vol 6 (1) ◽  
pp. 14 ◽  
Author(s):  
Elisa Mussi ◽  
Rocco Furferi ◽  
Yary Volpe ◽  
Flavio Facchini ◽  
Kathleen S. McGreevy ◽  
...  
Keyword(s):  
Costal Cartilage ◽  
Surgical Reconstruction ◽  
Ear Reconstruction ◽  
Autologous Tissue ◽  
Aesthetic Appearance ◽  
History Of ◽  
Common Clinical Practice ◽  
The Aesthetic ◽  
Manufacturing Technologies ◽  
High Level

Microtia is a congenital malformation affecting one in 5000 individuals and is characterized by physical deformity or absence of the outer ear. Nowadays, surgical reconstruction with autologous tissue is the most common clinical practice. The procedure requires a high level of manual and artistic techniques of a surgeon in carving and sculpting of harvested costal cartilage of the patient to recreate an auricular framework to insert within a skin pocket obtained at the malformed ear region. The aesthetic outcomes of the surgery are highly dependent on the experience of the surgeon performing the surgery. For this reason, surgeons need simulators to acquire adequate technical skills out of the surgery room without compromising the aesthetic appearance of the patient. The current paper aims to describe and analyze the different materials and methods adopted during the history of autologous ear reconstruction (AER) simulation to train surgeons by practice on geometrically and mechanically accurate physical replicas. Recent advances in 3D modelling software and manufacturing technologies to increase the effectiveness of AER simulators are particularly described to provide more recent outcomes.

scholarly journals INTERACTIVE ONLINE VISUALIZATION OF COMPLEX 3D GEOMETRIES

2019 ◽  
Vol XLII-2/W9 ◽  
pp. 173-180 ◽  
Author(s):  
A.-M. Boutsi ◽  
C. Ioannidis ◽  
S. Soile
Keyword(s):  
3D Model ◽  
Complex Geometry ◽  
User Interaction ◽  
Archaeological Site ◽  
3D Models ◽  
Web Browser ◽  
Metadata Repository ◽  
3D Scene ◽  
High Level

<p><strong>Abstract.</strong> In the last decade 3D datasets of the Cultural Heritage field have become extremely rich and high detailed due to the evolution of the technologies they derive from. However, their online deployment, both for scientific and general public purposes is usually deficient in user interaction and multimedia integration. A single solution that efficiently addresses these issues is presented in this paper. The developed framework provides an interactive and lightweight visualization of high-resolution 3D models in a web browser. It is based on 3D Heritage Online Presenter (3DHOP) and Three.js library, implemented on top of WebGL API. 3DHOP capabilities are fully exploited and enhanced with new, high level functionalities. The approach is especially suited to complex geometry and it is adapted to archaeological and architectural environments. Thus, the multi-dimensional documentation of the archaeological site of Meteora, in central Greece is chosen as the case study. Various navigation paradigms are implemented and the data structure is enriched with the incorporation of multiple 3D model viewers. Furthermore, a metadata repository, comprises ortho-images, photographic documentation, video and text, is accessed straight forward through the inspection of the main 3D scene of Meteora by a system of interconnections.</p>

scholarly journals Impacts of woodland planting on nature-based recreational tourism in upland England – a case study

2021 ◽  
Author(s):  
Sara Vangerschov Iversen ◽  
Claire Holt ◽  
Naomi van der Velden ◽  
Lois Mansfield ◽  
Ian Convery ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Land Management ◽  
National Park ◽  
Negative Impact ◽  
Economic Value ◽  
Landscape Changes ◽  
Aesthetic Appearance ◽  
Return Visits ◽  
The Aesthetic

Upland landscapes provide important ecosystem services (ES) to society. One cultural ES - nature-based recreational tourism (NBR) - is a growing industry in upland regions that provides an important revenue to areas where other industries are often in decline. NBR tourism is a service that relies partly on the aesthetic appearance of the landscape. Changes in land management, such as increasing woodland cover, changes the appearance of the landscape and may therefore have a positive or negative impact on the economic value generated by NBR tourism. We carried out a survey of NBR tourists, using photo visualisation of different woodland scenarios, in a pastoral upland landscape in a UK National Park. This was conducted to estimate the economic value of NBR tourism under different woodland scenarios and participant’s preferences. The findings presented in this paper suggest that NBR tourism generates a substantial income to the area and that the economic value would increase, under certain woodland cover scenarios. The findings also make an important observation on how there is a difference between peoples’ preference for woodland levels and the probability of return visits.

scholarly journals A New Multi-Scale Sliding Window LSTM Framework (MSSW-LSTM): A Case Study for GNSS Time-Series Prediction

2021 ◽  
Vol 13 (16) ◽  
pp. 3328
Author(s):  
Jian Wang ◽  
Weiping Jiang ◽  
Zhao Li ◽  
Yang Lu
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Short Term Memory ◽  
Time Series Prediction ◽  
Sliding Window ◽  
Plate Movement ◽  
Multi Scale ◽  
High Level ◽  
Gnss Time Series

GNSS time-series prediction plays an important role in the monitoring of crustal plate movement, and dam or bridge deformation, and the maintenance of global or regional coordinate frames. Deep learning is a state-of-the-art approach for extracting high-level abstract features from big data without any prior knowledge. Moreover, long short-term memory (LSTM) networks are a form of recurrent neural networks that have significant potential for processing time series. In this study, a novel prediction framework was proposed by combining a multi-scale sliding window (MSSW) with LSTM. Specifically, MSSW was applied for data preprocessing to effectively extract the feature relationship at different scales and simultaneously mine the deep characteristics of the dataset. Then, multiple LSTM neural networks were used to predict and obtain the final result by weighting. To verify the performance of MSSW-LSTM, 1000 daily solutions of the XJSS station in the Up component were selected for prediction experiments. Compared with the traditional LSTM method, our results of three groups of controlled experiments showed that the RMSE value was reduced by 2.1%, 23.7%, and 20.1%, and MAE was decreased by 1.6%, 21.1%, and 22.2%, respectively. Our results showed that the MSSW-LSTM algorithm can achieve higher prediction accuracy and smaller error, and can be applied to GNSS time-series prediction.

Work Life Balance Of Female Crew In The Aviation Industry: A Case Study

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 206-212
Author(s):  
Dr. D. Shoba ◽  
Dr. G. Suganthi
Keyword(s):  
Family Life ◽  
Work Life ◽  
Work Life Balance ◽  
Aviation Industry ◽  
Life Balance ◽  
International Airport ◽  
Work Pressure ◽  
Women Employees ◽  
High Level

Employees and employers are facing issues in work life balance. It has become a difficult domain now, because the work needs have increased due to an increase in work pressure and complexities in handling the technology. As there are drastic changes in the rules and regulations in the work scenario of the aviation industry, it makes work life balance of employees difficult and set more hurdles. Hence there are many distractions and imbalances in the life of women employees in the aviation industry working across all levels. This work pressure is creating high level of hurdles in maintaining a harmonious job and family life, especially for female aviation employees. Data is collected from 50 female crew members working at Cochin International Airport. The objective of this study is to analyze the work life balance of working females of Cochin International Airport and its influence on their personal and specialized lives. The result of the study shows that the management should frame certain policies which will help employees to have the balance among their personal and expert lives.

Withdrawn: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC)

2019 ◽  
Vol 13 ◽  
Author(s):  
Abeer A. Amer ◽  
Soha M. Ismail
Keyword(s):  
Diabetes Mellitus ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Computer Science ◽  
Recent Advances ◽  
Vascular Center ◽  
Copyright Permission ◽  
Legal Right

The following article has been withdrawn on the request of the author of the journal Recent Advances in Computer Science and Communications (Recent Patents on Computer Science): Title: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC) Authors: Abeer A. Amer and Soha M. Ismail* Bentham Science apologizes to the readers of the journal for any inconvenience this may cause BENTHAM SCIENCE DISCLAIMER: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

Candy and Drugs for Dinner

2019 ◽  
pp. 572-588
Author(s):  
Sean Guynes
Keyword(s):  
Comic Book ◽  
Gender Politics ◽  
Media Production ◽  
Comics Studies ◽  
Contemporary Media ◽  
The Aesthetic

This chapter links the seemingly disparate but deeply interconnected discourses and practices of contemporary media production, genre, aesthetics, and comics. It offers these arguments through a case study of the popular fantasy comic book Rat Queens and in the process demonstrates the critical utility to comics studies of reading genre, aesthetics, and industry together. The chapter reads Rat Queens through Sianne Ngai’s conception of the zany, cute, and interesting, showing how each of these categories is part of the aesthetic logic of the series, while also showing how each performs or critiques the series’ (superficial) investment in gender politics and the fantasy genre.

scholarly journals Spatial Analysis of the Drivers, Characteristics, and Effects of Forest Fragmentation

2021 ◽  
Vol 13 (6) ◽  
pp. 3246
Author(s):  
Zoe Slattery ◽  
Richard Fenner
Keyword(s):  
Forest Fragmentation ◽  
Forest Fires ◽  
Geographical Information ◽  
Agricultural Expansion ◽  
Forest Patches ◽  
Mato Grosso ◽  
Remote Imaging ◽  
Landscape Characteristics ◽  
High Level

Building on the existing literature, this study examines whether specific drivers of forest fragmentation cause particular fragmentation characteristics, and how these characteristics can be linked to their effects on forest-dwelling species. This research uses Landsat remote imaging to examine the changing patterns of forests. It focuses on areas which have undergone a high level of a specific fragmentation driver, in particular either agricultural expansion or commodity-driven deforestation. Seven municipalities in the states of Rondônia and Mato Grosso in Brazil are selected as case study areas, as these states experienced a high level of commodity-driven deforestation and agricultural expansion respectively. Land cover maps of each municipality are created using the Geographical Information System software ArcGIS Spatial Analyst extension. The resulting categorical maps are input into Fragstats fragmentation software to calculate quantifiable fragmentation metrics for each municipality. To determine the effects that these characteristics are likely to cause, this study uses a literature review to determine how species traits affect their responses to forest fragmentation. Results indicate that, in areas that underwent agricultural expansion, the remaining forest patches became more complex in shape with longer edges and lost a large amount of core area. This negatively affects species which are either highly dispersive or specialist to core forest habitat. In areas that underwent commodity-driven deforestation, it was more likely that forest patches would become less aggregated and create disjunct core areas. This negatively affects smaller, sedentary animals which do not naturally travel long distances. This study is significant in that it links individual fragmentation drivers to their landscape characteristics, and in turn uses these to predict effects on species with particular traits. This information will prove useful for forest managers, particularly in the case study municipalities examined in this study, in deciding which species require further protection measures. The methodology could be applied to other drivers of forest fragmentation such as forest fires.

scholarly journals Interpretation of Swedish Sign Language Using Convolutional Neural Networks and Transfer Learning

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Gustaf Halvardsson ◽  
Johanna Peterson ◽  
César Soto-Valero ◽  
Benoit Baudry
Keyword(s):  
Neural Networks ◽  
Sign Language ◽  
Transfer Learning ◽  
Convolutional Neural Networks ◽  
Web Application ◽  
Training Dataset ◽  
Motion Processing ◽  
Image Perception ◽  
Sign Languages ◽  
High Level

AbstractThe automatic interpretation of sign languages is a challenging task, as it requires the usage of high-level vision and high-level motion processing systems for providing accurate image perception. In this paper, we use Convolutional Neural Networks (CNNs) and transfer learning to make computers able to interpret signs of the Swedish Sign Language (SSL) hand alphabet. Our model consists of the implementation of a pre-trained InceptionV3 network, and the usage of the mini-batch gradient descent optimization algorithm. We rely on transfer learning during the pre-training of the model and its data. The final accuracy of the model, based on 8 study subjects and 9400 images, is 85%. Our results indicate that the usage of CNNs is a promising approach to interpret sign languages, and transfer learning can be used to achieve high testing accuracy despite using a small training dataset. Furthermore, we describe the implementation details of our model to interpret signs as a user-friendly web application.

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