scholarly journals Metodología para diseño de infraestructura de telecomunicaciones para campus universitarios medianos, caso La Dolorosa-UNACH. // Methodology for design of telecommunications infrastructure for medium-sized university campuses, La Dolorosa-UNACH case.

Ciencia Unemi ◽  
2017 ◽  
Vol 10 (23) ◽  
pp. 133
Author(s):  
Juan Carlos Santillán Lima ◽  
Anibal Llanga Vargas ◽  
Gustavo Chafla Altamirano
Keyword(s):  
Fiber Optics ◽  
State Of The Art ◽  
University Campus ◽  
Ict In Education ◽  
Ip Telephony ◽  
High Quality ◽  
University Campuses ◽  
Telecommunications Infrastructure ◽  
Acceptable Quality ◽  
Campus Networks

RESUMEN Se plantea una metodología para el diseño de infraestructuras de telecomunicaciones para campus universitarios medianos, aplicada en el Campus La Dolorosa de la Universidad Nacional de Chimborazo, UNACH, que garantice el acceso a los servicios en línea. Se contó con los diferentes estándares de Fibra Óptica, UTP y WIFI, publicaciones realizadas por la ITU y la IEEE, y el estándar ETSI EG 202 057-4, sobre accesos de calidad en internet, codecs de telefonía IP, artículos sobre TICS en la Educación. Dentro de esta investigación se analizó el estado del arte respecto a infraestructuras de telecomunicaciones, estudió y determinó los servicios que requieren las redes de campus universitarios y el tráfico que genera cada uno de los servicios, y por último el diseño de la infraestructura de telecomunicaciones de acuerdo a los parámetros determinados. Entre los principales resultados se evidenció que existen 1592 dispositivos que en conjunto pueden generar 6537.60Mbps en calidad alta y 100% de usuarios, y 543.28Mbps en calidad aceptable con usuarios concurrentes, y utilizando una red GPON G.987.2 se puede transmitir todo el tráfico generado. Se presenta una metodología para el diseño de infraestructuras de telecomunicaciones óptima para los requerimientos encontrados en el lugar de estudio. ABSTRACT A methodology design of a Telecommunications Infrastructures for medium-sized campus university is proposed, it is applied at La Dolorosa Campus of the “Universidad Nacional de Chimborazo” to guaranteed access to online services. Different standards of Fiber Optics, UTP and WIFI publications made by the ITU and the IEEE, and the ETSI standard EG 202 057-4, on Internet quality accesses, IP telephony codecs, articles on ICT in Education were used. This research analyzed the state of the art regarding telecommunications infrastructures, studied and determined the services required by university campus networks and the traffic generated by each of the services, as well as the design of the telecommunications infrastructure according to the determined parameters. Among the main results it is evident that there are 1592 devices that can generate 6537.60Mbps in high quality and 100% of users, and 543.28Mbps in acceptable quality with concurrent users, and using a GPON network with the standard G.987.2 can transmit all the generated traffic. A methodology is presented for the design of optimal telecommunications infrastructures for the requirements found at the study site.

scholarly journals Carpooling as an Immediate Strategy to Post-Lockdown Mobility: A Case Study in University Campuses

2021 ◽  
Vol 13 (10) ◽  
pp. 5512
Author(s):  
Ricardo Tomás ◽  
Paulo Fernandes ◽  
Joaquim Macedo ◽  
Margarida Cabrita Coelho
Keyword(s):  
Public Transportation ◽  
Road Traffic ◽  
Pollutant Emissions ◽  
University Campus ◽  
Microscopic Traffic Simulation ◽  
University Campuses ◽  
The Road ◽  
Traffic Performance ◽  
Campus Networks ◽  
The University

Carpooling is a mobility concept that has been showing promising results in reducing single occupancy use of private cars, which prompted many institutions, namely universities, to implement carpooling platforms to improve their networks sustainability. Nowadays, currently under a pandemic crisis, public transportation must be used with limitations regarding the number of occupants to prevent the spread of the virus and commuters are turning even more to private cars to perform their daily trips. Carpooling under a set of precaution rules is a potential solution to help commuters perform their daily trips while respecting COVID-19 safety recommendations. This research aimed to develop an analysis of the road traffic and emission impacts of implementing carpooling, with social distancing measures, in three university campus networks through microscopic traffic simulation modeling and microscopic vehicular exhaust emissions estimation. Results indicate that employing carpooling for groups of up to three people to safely commute from their residence area to the university campus has the potential to significantly reduce pollutant emissions (reductions of 5% and 7% in carbon dioxide and nitrogen oxides can be obtained, respectively) within the network while significantly improving road traffic performance (average speed increased by 7% and travel time reduced by 8%).

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

scholarly journals Global optimization of an encapsulated Si/SiO$$_2$$ L3 cavity with a 43 million quality factor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. P. Vasco ◽  
V. Savona
Keyword(s):  
Global Optimization ◽  
Photonic Crystal ◽  
Quality Factor ◽  
State Of The Art ◽  
Optimization Strategy ◽  
High Quality ◽  
Optimal Value ◽  
Out Of Plane ◽  
Fabrication Tolerances ◽  
Structural Imperfections

AbstractWe optimize a silica-encapsulated silicon L3 photonic crystal cavity for ultra-high quality factor by means of a global optimization strategy, where the closest holes surrounding the cavity are varied to minimize out-of-plane losses. We find an optimal value of $$Q_c=4.33\times 10^7$$ Q c = 4.33 × 10 7 , which is predicted to be in the 2 million regime in presence of structural imperfections compatible with state-of-the-art silicon fabrication tolerances.

scholarly journals An All-Batch Loss for Constructing Prediction Intervals

2021 ◽  
Vol 11 (4) ◽  
pp. 1728
Author(s):  
Hua Zhong ◽  
Li Xu
Keyword(s):  
Gradient Descent ◽  
State Of The Art ◽  
Prediction Interval ◽  
Feedforward Neural Networks ◽  
Important Research ◽  
Likelihood Principle ◽  
High Quality ◽  
Construction Methods ◽  
Important Research Topic ◽  
Benchmark Datasets

The prediction interval (PI) is an important research topic in reliability analyses and decision support systems. Data size and computation costs are two of the issues which may hamper the construction of PIs. This paper proposes an all-batch (AB) loss function for constructing high quality PIs. Taking the full advantage of the likelihood principle, the proposed loss makes it possible to train PI generation models using the gradient descent (GD) method for both small and large batches of samples. With the structure of dual feedforward neural networks (FNNs), a high-quality PI generation framework is introduced, which can be adapted to a variety of problems including regression analysis. Numerical experiments were conducted on the benchmark datasets; the results show that higher-quality PIs were achieved using the proposed scheme. Its reliability and stability were also verified in comparison with various state-of-the-art PI construction methods.

Approximate Mining of Frequent -Subgraph Patterns in Evolving Graphs

2021 ◽  
Vol 15 (3) ◽  
pp. 1-35
Author(s):  
Muhammad Anis Uddin Nasir ◽  
Cigdem Aslay ◽  
Gianmarco De Francisci Morales ◽  
Matteo Riondato
Keyword(s):  
Sample Size ◽  
State Of The Art ◽  
Empirical Evaluation ◽  
Connected Subgraph ◽  
Dynamic Graphs ◽  
High Quality ◽  
Complexity Bounds ◽  
Approximation Quality ◽  
Uniform Sample ◽  
Waiting For Godot

“Perhaps he could dance first and think afterwards, if it isn’t too much to ask him.” S. Beckett, Waiting for Godot Given a labeled graph, the collection of -vertex induced connected subgraph patterns that appear in the graph more frequently than a user-specified minimum threshold provides a compact summary of the characteristics of the graph, and finds applications ranging from biology to network science. However, finding these patterns is challenging, even more so for dynamic graphs that evolve over time, due to the streaming nature of the input and the exponential time complexity of the problem. We study this task in both incremental and fully-dynamic streaming settings, where arbitrary edges can be added or removed from the graph. We present TipTap , a suite of algorithms to compute high-quality approximations of the frequent -vertex subgraphs w.r.t. a given threshold, at any time (i.e., point of the stream), with high probability. In contrast to existing state-of-the-art solutions that require iterating over the entire set of subgraphs in the vicinity of the updated edge, TipTap operates by efficiently maintaining a uniform sample of connected -vertex subgraphs, thanks to an optimized neighborhood-exploration procedure. We provide a theoretical analysis of the proposed algorithms in terms of their unbiasedness and of the sample size needed to obtain a desired approximation quality. Our analysis relies on sample-complexity bounds that use Vapnik–Chervonenkis dimension, a key concept from statistical learning theory, which allows us to derive a sufficient sample size that is independent from the size of the graph. The results of our empirical evaluation demonstrates that TipTap returns high-quality results more efficiently and accurately than existing baselines.

scholarly journals A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 853
Author(s):  
Jesús Sánchez-Oro ◽  
Ana D. López-Sánchez ◽  
Anna Martínez-Gavara ◽  
Alfredo G. Hernández-Díaz ◽  
Abraham Duarte
Keyword(s):  
Location Problem ◽  
State Of The Art ◽  
Path Relinking ◽  
Multiobjective Evolutionary Algorithms ◽  
Demand Point ◽  
High Quality ◽  
Nondominated Solutions ◽  
Center Location ◽  
Strategic Oscillation ◽  
N Demand

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.

scholarly journals Evolutionary Machine Learning for Multi-Objective Class Solutions in Medical Deformable Image Registration

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 99 ◽  
Author(s):  
Kleopatra Pirpinia ◽  
Peter A. N. Bosman ◽  
Jan-Jakob Sonke ◽  
Marcel van Herk ◽  
Tanja Alderliesten
Keyword(s):  
Machine Learning ◽  
Image Registration ◽  
State Of The Art ◽  
Deformable Image Registration ◽  
Optimization Approach ◽  
High Quality ◽  
Trade Off ◽  
Multi Objective ◽  
Current State ◽  
Image Artefacts

Current state-of-the-art medical deformable image registration (DIR) methods optimize a weighted sum of key objectives of interest. Having a pre-determined weight combination that leads to high-quality results for any instance of a specific DIR problem (i.e., a class solution) would facilitate clinical application of DIR. However, such a combination can vary widely for each instance and is currently often manually determined. A multi-objective optimization approach for DIR removes the need for manual tuning, providing a set of high-quality trade-off solutions. Here, we investigate machine learning for a multi-objective class solution, i.e., not a single weight combination, but a set thereof, that, when used on any instance of a specific DIR problem, approximates such a set of trade-off solutions. To this end, we employed a multi-objective evolutionary algorithm to learn sets of weight combinations for three breast DIR problems of increasing difficulty: 10 prone-prone cases, 4 prone-supine cases with limited deformations and 6 prone-supine cases with larger deformations and image artefacts. Clinically-acceptable results were obtained for the first two problems. Therefore, for DIR problems with limited deformations, a multi-objective class solution can be machine learned and used to compute straightforwardly multiple high-quality DIR outcomes, potentially leading to more efficient use of DIR in clinical practice.

scholarly journals Taxonomy, Diversity and Cultivation of the Oudemansielloid/Xeruloid Taxa Hymenopellis, Mucidula, Oudemansiella, and Xerula with Respect to Their Bioactivities: A Review

2021 ◽  
Vol 7 (1) ◽  
pp. 51
Author(s):  
Allen Grace Niego ◽  
Olivier Raspé ◽  
Naritsada Thongklang ◽  
Rawiwan Charoensup ◽  
Saisamorn Lumyong ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Bioactive Compounds ◽  
State Of The Art ◽  
Bioactive Metabolites ◽  
High Quality ◽  
Important Resource ◽  
Molecular Weights ◽  
Anti Cancer ◽  
Potential Applications ◽  
Commercial Applications

The oudemansielloid/xeruloid taxa Hymenopellis, Mucidula, Oudemansiella, and Xerula are genera of Basidiomycota that constitute an important resource of bioactive compounds. Numerous studies have shown antimicrobial, anti-oxidative, anti-cancer, anti-inflammatory and other bioactivities of their extracts. The bioactive principles can be divided into two major groups: (a) hydrophilic polysaccharides with relatively high molecular weights and (b) low molecular medium polar secondary metabolites, such as the antifungal strobilurins. In this review, we summarize the state of the art on biodiversity, cultivation of the fungi and bioactivities of their secondary metabolites and discuss future applications. Although the strobilurins are well-documented, with commercial applications as agrochemical fungicides, there are also other known compounds from this group that have not yet been well-studied. Polysaccharides, dihydro-citrinone phenol A acid, scalusamides, and acetylenic lactones such as xerulin, also have potential applications in the nutraceutical, pharmaceutical and medicinal market and should be further explored. Further studies are recommended to isolate high quality bioactive compounds and fully understand their modes of action. Given that only few species of oudemansielloid/xeruloid mushrooms have been explored for their production of secondary metabolites, these taxa represent unexplored sources of potentially useful and novel bioactive metabolites.

Thermal Laser Separation – A Novel Dicing Technology Fulfilling the Demands of Volume Manufacturing of 4H-SiC Devices

2015 ◽  
Vol 821-823 ◽  
pp. 528-532 ◽  
Author(s):  
Dirk Lewke ◽  
Karl Otto Dohnke ◽  
Hans Ulrich Zühlke ◽  
Mercedes Cerezuela Barret ◽  
Martin Schellenberger ◽  
...  
Keyword(s):  
Experimental Data ◽  
Process Control ◽  
Tool Wear ◽  
Large Scale ◽  
State Of The Art ◽  
Scale Production ◽  
High Quality ◽  
Large Scale Production ◽  
Laser Separation

One challenge for volume manufacturing of 4H-SiC devices is the state-of-the-art wafer dicing technology – the mechanical blade dicing which suffers from high tool wear and low feed rates. In this paper we discuss Thermal Laser Separation (TLS) as a novel dicing technology for large scale production of SiC devices. We compare the latest TLS experimental data resulting from fully processed 4H-SiC wafers with results obtained by mechanical dicing technology. Especially typical product relevant features like process control monitoring (PCM) structures and backside metallization, quality of diced SiC-devices as well as productivity are considered. It could be shown that with feed rates up to two orders of magnitude higher than state-of-the-art, no tool wear and high quality of diced chips, TLS has a very promising potential to fulfill the demands of volume manufacturing of 4H-SiC devices.

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