scholarly journals A Hybrid Approach for Providing Improved Link Connectivity in SDN

2019 ◽  
Vol 17 (2) ◽  
pp. 250-256
Author(s):  
Muthumanikandan Vanamoorthy ◽  
Valliyammai Chinnaiah ◽  
Harish Sekar
Keyword(s):  
Response Time ◽  
Shortest Path ◽  
Hybrid Approach ◽  
Link Failure ◽  
Use Case ◽  
Hybrid Scheme ◽  
Backup Path ◽  
The Past ◽  
Unique Approach ◽  
Traditional Approaches

Software-Defined Networking (SDN) is a unique approach to design and build networks. The networks services can be better handled by administrators with the abstraction that SDN provides. The problem of re-routing the packets with minimum overhead in case of link failure is handled in this work. Protection and restoration schemes have been used in the past to handle such issues by giving more priority to minimal response time or controller overhead based on the use case. A hybrid scheme has been proposed with per-link Bidirectional forwarding mechanism to handle the failover. The proposed method makes sure that the controller overhead does not impact the flow of packets, thereby decreasing the overall response time, even with guaranteed network resiliency. The computation of the next shortest backup path also guarantees that the subsequent routing of packets always chooses the shortest path available. The proposed method is compared with the traditional approaches and proven by results to perform better with minimal response time.

Extended Lateral Transsylvian Approach for Basilar Bifurcation Aneurysms

Neurosurgery ◽  
2004 ◽  
Vol 55 (1) ◽  
pp. 174-178 ◽  
Author(s):  
Bernard R. Bendok ◽  
Christopher C. Getch ◽  
Richard Parkinson ◽  
Brian A. O'shaughnessy ◽  
H. Hunt Batjer
Keyword(s):  
Surgical Management ◽  
Successful Treatment ◽  
Hybrid Approach ◽  
Senior Author ◽  
The Past ◽  
Transsylvian Approach ◽  
Traditional Approaches

Abstract THE SURGICAL MANAGEMENT of aneurysms of the basilar apex is one of the most challenging areas in neurosurgery. Successful treatment of this subgroup of aneurysms is dependent on the mastery of technical nuances that have been pioneered and advanced over the past 4 decades. Although both the traditional transsylvian and subtemporal approaches have distinct advantages, each is associated with significant limitations. In this article, the senior author shares his insights into a hybrid approach: the extended lateral transsylvian approach. This approach combines the assets of the two traditional approaches while eliminating their liabilities.

E-Projects Challenges in India – Role of Human Resource Management and Technology

2018 ◽  
Vol 6 (8) ◽  
pp. 263
Author(s):  
Ramnik Kaur
Keyword(s):  
Developing Countries ◽  
Public Administration ◽  
Paradigm Shift ◽  
Successful Implementation ◽  
The Public ◽  
Government Services ◽  
The Past ◽  
The Government ◽  
Traditional Approaches

E-governance is a paradigm shift over the traditional approaches in Public Administration which means rendering of government services and information to the public by using electronic means. In the past decades, service quality and responsiveness of the government towards the citizens were least important but with the approach of E-Government the government activities are now well dealt. This paper withdraws experiences from various studies from different countries and projects facing similar challenges which need to be consigned for the successful implementation of e-governance projects. Developing countries like India face poverty and illiteracy as a major obstacle in any form of development which makes it difficult for its government to provide e-services to its people conveniently and fast. It also suggests few suggestions to cope up with the challenges faced while implementing e-projects in India.

Recent Progress in Machine Learning-based Prediction of Peptide Activity for Drug Discovery

2019 ◽  
Vol 19 (1) ◽  
pp. 4-16 ◽  
Author(s):  
Qihui Wu ◽  
Hanzhong Ke ◽  
Dongli Li ◽  
Qi Wang ◽  
Jiansong Fang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Drug Discovery ◽  
Large Scale ◽  
Recent Progress ◽  
High Specificity ◽  
Learning Approaches ◽  
Anticancer Peptides ◽  
The Past ◽  
Traditional Approaches ◽  
Large Scale Screening

Over the past decades, peptide as a therapeutic candidate has received increasing attention in drug discovery, especially for antimicrobial peptides (AMPs), anticancer peptides (ACPs) and antiinflammatory peptides (AIPs). It is considered that the peptides can regulate various complex diseases which are previously untouchable. In recent years, the critical problem of antimicrobial resistance drives the pharmaceutical industry to look for new therapeutic agents. Compared to organic small drugs, peptide- based therapy exhibits high specificity and minimal toxicity. Thus, peptides are widely recruited in the design and discovery of new potent drugs. Currently, large-scale screening of peptide activity with traditional approaches is costly, time-consuming and labor-intensive. Hence, in silico methods, mainly machine learning approaches, for their accuracy and effectiveness, have been introduced to predict the peptide activity. In this review, we document the recent progress in machine learning-based prediction of peptides which will be of great benefit to the discovery of potential active AMPs, ACPs and AIPs.

scholarly journals Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3046
Author(s):  
Shervin Minaee ◽  
Mehdi Minaei ◽  
Amirali Abdolrashidi
Keyword(s):  
Deep Learning ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Visualization Technique ◽  
Convolutional Network ◽  
The Past ◽  
Multiple Datasets ◽  
The Face ◽  
Traditional Approaches

Facial expression recognition has been an active area of research over the past few decades, and it is still challenging due to the high intra-class variation. Traditional approaches for this problem rely on hand-crafted features such as SIFT, HOG, and LBP, followed by a classifier trained on a database of images or videos. Most of these works perform reasonably well on datasets of images captured in a controlled condition but fail to perform as well on more challenging datasets with more image variation and partial faces. In recent years, several works proposed an end-to-end framework for facial expression recognition using deep learning models. Despite the better performance of these works, there are still much room for improvement. In this work, we propose a deep learning approach based on attentional convolutional network that is able to focus on important parts of the face and achieves significant improvement over previous models on multiple datasets, including FER-2013, CK+, FERG, and JAFFE. We also use a visualization technique that is able to find important facial regions to detect different emotions based on the classifier’s output. Through experimental results, we show that different emotions are sensitive to different parts of the face.

scholarly journals Escaping the past and living in the present: a qualitative exploration of substance use among Syrian male refugees in Germany

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Jutta Lindert ◽  
Ulrike Neuendorf ◽  
Marta Natan ◽  
Ingo Schäfer
Keyword(s):  
Substance Use ◽  
Hybrid Approach ◽  
Syrian Refugees ◽  
Group Discussions ◽  
The Past ◽  
Audio Recordings ◽  
Psychosocial Difficulties ◽  
Professional Treatment ◽  
And Coping ◽  
Qualitative Exploration

Abstract Background Syrians have been the largest group of refugees in Germany since 2014. Little is known about Syrian refugees` perspectives on substance use. The aim of this study is to investigate the perspective of male refugees from Syria and to foster specific knowledge and understanding of substance use. Methods We applied a qualitative study design. Five semi-structured focus group discussions with a total of 19 refugees were conducted in 2019 among the difficult to reach population of Syrian refugees. Audio recordings were translated and transcribed. We used a hybrid approach by integrating inductive and deductive thematic frameworks. Results We identified common themes. Firstly, refugees perceived that substances are widely available and accepted in Germany. Secondly, refugees perceived that rules and norms in Germany differ from rules and norms in the home country and favor availability of substances. Thirdly, substance use is related to the intention to escape the past. Fourthly, substance use is related to living in the present through connecting with others and being part of the community. Finally, mental health professional treatment for substance use is associated with shame. Conclusions Findings support Syrian refugees` perspectives of substance use as a way of both escaping the past and coping with psychosocial difficulties in the present in a socio-ecological understanding. Understanding the explanatory model of Syrian refugees can inform future interventions to prevent substance abuse and design tailored interventions. Further studies with Syrian refugees in more countries are needed to better understand resettled refugees` perspectives on substance use.

scholarly journals A Comparative Framework for Evaluating Consensus Algorithms for Blockchains

2021 ◽  
Author(s):  
Dipti Mahamuni
Keyword(s):  
Use Case ◽  
Consensus Algorithms ◽  
The Past ◽  
Comparative Framework

The past five years have seen a significant increase in the popularity of Decentralized Ledgers, commonly referred to as Blockchains. Many new protocols have been launched to cater to various applications serving individual consumers and enterprises. While research is conducted on individual consensus mechanisms and comparison against popular protocols, decisionmaking and selection between the protocols is still amorphous. This paper proposes a comprehensive comparative framework to evaluate various consensus algorithms. We hope that such a framework will help evaluate current as well as future consensus algorithms objectively for a given use case. The past five years have seen a significant increase in the popularity of Decentralized Ledgers, commonly referred to as Blockchains. Many new protocols have been launched to cater to various applications serving individual consumers and enterprises. While research is conducted on individual consensus mechanisms and comparison against popular protocols, decisionmaking and selection between the protocols is still amorphous. This paper proposes a comprehensive comparative framework to evaluate various consensus algorithms. We hope that such a framework will help evaluate current as well as future consensus algorithms objectively for a given use case.

scholarly journals Content analytics for curriculum review: A learning analytics use case for exploration of learner context

2020 ◽  
Author(s):  
Leah P. Macfadyen
Keyword(s):  
Text Analysis ◽  
Student Writing ◽  
Analysis Tool ◽  
Use Case ◽  
Curriculum Analysis ◽  
Curriculum Review ◽  
Curriculum Renewal ◽  
Text Content ◽  
User Friendly ◽  
Traditional Approaches

Curriculum analysis is a core component of curriculum renewal. Traditional approaches to curriculum analysis are manual, slow and subjective, but some studies have suggested that text analysis might usefully be employed for exploration of curriculum. This concise paper outlines a pilot use case of content analytics to support curriculum review and analysis. I have co-opted Quantext – a relatively user-friendly text analysis tool designed to help educators explore student writing – for analysis of the text content of the 17 courses in our online master’s program. Quantext computed descriptive metrics and readability indices for each course and identified top keywords and ngrams per course. Compilation and comparison of these revealed frequent curricular topics and networks of thematic relationships between courses, in ways that both individual educators and curriculum committees can interpret and use for decision-making. Future Quantext features will allow even more sophisticated identification of curricular gaps and redundancies.

Personality and Emotional Development

2013 ◽  
Author(s):  
Nathan A. Fox ◽  
Bethany C. Reeb-Sutherland ◽  
Kathryn A. Degnan
Keyword(s):  
Emotional Development ◽  
Neural Circuitry ◽  
Infants And Children ◽  
Emotion Development ◽  
The Past ◽  
Traditional Approaches ◽  
Gene X Environment Interactions ◽  
In Infants And Children

Over the past 20 years, research on the development of emotions and interest in the emotion–cognition interface has blossomed. Coinciding with this growth has been research on the neural circuitry and development of two basic motivational/emotion states: one brought on by threat and danger (i.e., fear) and one resulting from actively pursuing or receiving reward (i.e., reward/joy). The current chapter reviews traditional approaches to thinking about emotional development and temperament in infants and children. It then reviews the neuroscience work associated with fear and reward with a focus on the development of these systems. A particular emphasis will be placed on how this research and the examination of gene X environment interactions can influence research in personality and emotion development.

A Genetic Algorithms Approach for Inverse Shortest Path Length Problems

2014 ◽  
Vol 4 (4) ◽  
pp. 36-54 ◽  
Author(s):  
António Leitão ◽  
Adriano Vinhas ◽  
Penousal Machado ◽  
Francisco Câmara Pereira
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Path Length ◽  
Shortest Paths ◽  
Research Subject ◽  
Relevant Research ◽  
Real Cost ◽  
Shortest Path Problems ◽  
The Past ◽  
Specific Outcome

Inverse Combinatorial Optimization has become a relevant research subject over the past decades. In graph theory, the Inverse Shortest Path Length problem becomes relevant when people don't have access to the real cost of the arcs and want to infer their value so that the system has a specific outcome, such as one or more shortest paths between nodes. Several approaches have been proposed to tackle this problem, relying on different methods, and several applications have been suggested. This study explores an innovative evolutionary approach relying on a genetic algorithm. Two scenarios and corresponding representations are presented and experiments are conducted to test how they react to different graph characteristics and parameters. Their behaviour and differences are thoroughly discussed. The outcome supports that evolutionary algorithms may be a viable venue to tackle Inverse Shortest Path problems.

scholarly journals Analysis, identification and visualization of subgroups in genomics

2020 ◽  
Author(s):  
Gunnar Völkel ◽  
Simon Laban ◽  
Axel Fürstberger ◽  
Silke D Kühlwein ◽  
Nensi Ikonomi ◽  
...  
Keyword(s):  
Large Scale ◽  
Somatic Mutations ◽  
Target Selection ◽  
Gene Mutations ◽  
Use Case ◽  
The Past ◽  
Wide Availability ◽  
Approaches To Study ◽  
User Friendly ◽  
Personalized Intervention

Abstract Motivation Cancer is a complex and heterogeneous disease involving multiple somatic mutations that accumulate during its progression. In the past years, the wide availability of genomic data from patients’ samples opened new perspectives in the analysis of gene mutations and alterations. Hence, visualizing and further identifying genes mutated in massive sets of patients are nowadays a critical task that sheds light on more personalized intervention approaches. Results Here, we extensively review existing tools for visualization and analysis of alteration data. We compare different approaches to study mutual exclusivity and sample coverage in large-scale omics data. We complement our review with the standalone software AVAtar (‘analysis and visualization of alteration data’) that integrates diverse aspects known from different tools into a comprehensive platform. AVAtar supplements customizable alteration plots by a multi-objective evolutionary algorithm for subset identification and provides an innovative and user-friendly interface for the evaluation of concurrent solutions. A use case from personalized medicine demonstrates its unique features showing an application on vaccination target selection. Availability AVAtar is available at: https://github.com/sysbio-bioinf/avatar Contact [email protected], phone: +49 (0) 731 500 24 500, fax: +49 (0) 731 500 24 502

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