scholarly journals Recent Advances and Future Challenges for Artificial Neural Systems in Geotechnical Engineering Applications

2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
Mohamed A. Shahin ◽  
Mark B. Jaksa ◽  
Holger R. Maier
Keyword(s):  
Geotechnical Engineering ◽  
Neural Systems ◽  
Ann Modeling ◽  
Computational Capability ◽  
Engineering Problems ◽  
Future Challenges ◽  
Classical Mathematics ◽  
Artificial Neural ◽  
High Level ◽  
Almost All

Artificial neural networks (ANNs) are a form of artificial intelligence that has proved to provide a high level of competency in solving many complex engineering problems that are beyond the computational capability of classical mathematics and traditional procedures. In particular, ANNs have been applied successfully to almost all aspects of geotechnical engineering problems. Despite the increasing number and diversity of ANN applications in geotechnical engineering, the contents of reported applications indicate that the progress in ANN development and procedures is marginal and not moving forward since the mid-1990s. This paper presents a brief overview of ANN applications in geotechnical engineering, briefly provides an overview of the operation of ANN modeling, investigates the current research directions of ANNs in geotechnical engineering, and discusses some ANN modeling issues that need further attention in the future, including model robustness; transparency and knowledge extraction; extrapolation; uncertainty.

DFT Benchmark Study of the O--O Bond Dissociation Energy in Peroxides Validated with High-Level Ab-Initio Calculations

2019 ◽  
Author(s):  
Danilo Carmona ◽  
Pablo Jaque ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Reference Value ◽  
Basis Set ◽  
Basis Sets ◽  
Mean Deviation ◽  
Bond Dissociation ◽  
Dissociation Energies ◽  
The Mean ◽  
Experimental Values ◽  
High Level ◽  
Almost All

<div><div><div><p>Peroxides play a central role in many chemical and biological pro- cesses such as the Fenton reaction. The relevance of these compounds lies in the low stability of the O–O bond which upon dissociation results in radical species able to initiate various chemical or biological processes. In this work, a set of 64 DFT functional-basis set combinations has been validated in terms of their capability to describe bond dissociation energies (BDE) for the O–O bond in a database of 14 ROOH peroxides for which experimental values ofBDE are available. Moreover, the electronic contributions to the BDE were obtained for four of the peroxides and the anion H2O2− at the CBS limit at CCSD(T) level with Dunning’s basis sets up to triple–ζ quality provid- ing a reference value for the hydrogen peroxide anion as a model. Almost all the functionals considered here yielded mean absolute deviations around 5.0 kcal mol−1. The smallest values were observed for the ωB97 family and the Minnesota M11 functional with a marked basis set dependence. Despite the mean deviation, order relations among BDE experimental values of peroxides were also considered. The ωB97 family was able to reproduce the relations correctly whereas other functionals presented a marked dependence on the chemical nature of the R group. Interestingly, M11 functional did not show a very good agreement with the established order despite its good performance in the mean error. The obtained results support the use of similar validation strategies for proper prediction of BDE or other molecular properties by DF Tmethods in subsequent related studies.</p></div></div></div>

Methyl mercury in the dutch rhine delta

1994 ◽  
Vol 30 (10) ◽  
pp. 213-219 ◽  
Author(s):  
Hendrik Pieters ◽  
Victor Geuke
Keyword(s):  
Suspended Matter ◽  
Methyl Mercury ◽  
Mercury Contamination ◽  
Benthic Organisms ◽  
Considerable Decrease ◽  
Continuous Sedimentation ◽  
Highly Correlated ◽  
High Level ◽  
Almost All

Samples of yellow eel from various locations in the Dutch Rhine area have been analyzed for trend monitoring of mercury since 1977. In the western Rhine delta mercury levels in eels have hardly changed since the seventies, whereas in the eastern part of the Dutch Rhine area a considerable decrease of mercury concentrations in eel has occurred. Because of continuous sedimentation of contaminated suspended matter transported from upstream regions, accumulation rates and concentrations of mercury in eel in the western Rhine delta remained at a relatively high level. Analyses of methyl mercury in biota have been performed to elucidate the role of methyl mercury in the mercury contamination of the Dutch Rhine ecosystem. Low percentages of methyl mercury were observed in zooplankton (3 to 35%). In benthic organisms (mussels) percentages of methyl mercury ranged from 30 to 57%, while in fish species and liver of aquatic top predator birds almost all the mercury was present in the form of methyl mercury (&gt; 80%). During the period 1970-1990 mercury concentrations of suspended matter in the eastern Rhine delta have drastically decreased. These concentrations seemed to be highly correlated with mercury concentrations of eel (R = 0.84). The consequences of this relation are discussed.

Language and Aging

2019 ◽  
pp. 294-316
Author(s):  
Jonathan E. Peelle
Keyword(s):  
Language Processing ◽  
Brain Function ◽  
Neural Systems ◽  
Language Abilities ◽  
Physiological Mechanisms ◽  
Cognitive Changes ◽  
Older Adulthood ◽  
Neural Organization ◽  
Age Related ◽  
High Level

Language processing in older adulthood is a model of balance between preservation and decline. Despite widespread changes to physiological mechanisms supporting perception and cognition, older adults’ language abilities are frequently well preserved. At the same time, the neural systems engaged to achieve this high level of success change, and individual differences in neural organization appear to differentiate between more and less successful performers. This chapter reviews anatomical and cognitive changes that occur in aging and popular frameworks for age-related changes in brain function, followed by an examination of how these principles play out in the context of language comprehension and production.

scholarly journals Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed
Keyword(s):  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Autonomous Driving ◽  
Use Cases ◽  
Cooperative Driving ◽  
Vehicle To Vehicle ◽  
Future Challenges ◽  
Vehicle To Infrastructure ◽  
High Level ◽  
Intersection Management

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

scholarly journals Application of an Artificial Neural Network to Automate the Measurement of Kinematic Characteristics of Punches in Boxing

2021 ◽  
Vol 11 (3) ◽  
pp. 1223
Author(s):  
Ilshat Khasanshin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Kinematic Parameters ◽  
Constant Control ◽  
Measurement Units ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Effective Development ◽  
High Level ◽  
Different Levels

This work aimed to study the automation of measuring the speed of punches of boxers during shadow boxing using inertial measurement units (IMUs) based on an artificial neural network (ANN). In boxing, for the effective development of an athlete, constant control of the punch speed is required. However, even when using modern means of measuring kinematic parameters, it is necessary to record the circumstances under which the punch was performed: The type of punch (jab, cross, hook, or uppercut) and the type of activity (shadow boxing, single punch, or series of punches). Therefore, to eliminate errors and accelerate the process, that is, automate measurements, the use of an ANN in the form of a multilayer perceptron (MLP) is proposed. During the experiments, IMUs were installed on the boxers’ wrists. The input parameters of the ANN were the absolute acceleration and angular velocity. The experiment was conducted for three groups of boxers with different levels of training. The developed model showed a high level of punch recognition for all groups, and it can be concluded that the use of the ANN significantly accelerates the collection of data on the kinetic characteristics of boxers’ punches and allows this process to be automated.

scholarly journals Liquid Biopsy and Other Non-Invasive Diagnostic Measures in PCNSL

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2665
Author(s):  
Alexander Baraniskin ◽  
Roland Schroers
Keyword(s):  
Central Nervous System Lymphoma ◽  
Circulating Tumor Dna ◽  
Mri Findings ◽  
Diagnostic Measures ◽  
Non Hodgkin Lymphoma ◽  
Specificity And Sensitivity ◽  
Demyelinating Lesions ◽  
Granulomatous Diseases ◽  
High Level ◽  
Almost All

Primary central nervous system lymphoma is a rare but highly aggressive form of non-Hodgkin lymphoma that remains confined to the CNS neuroaxis. The diagnosis of PCNSL requires a high level of suspicion as clinical presentation varies depending on the involved CNS areas. Neurological symptoms and MRI findings may mimic gliomas, demyelinating lesions, or infectious and granulomatous diseases. Almost all PCNSL patients undergo invasive surgical procedures for definite diagnosis. Stereotactic biopsy is still the gold standard in achieving a diagnostic accuracy of 73–97%. Both the potential procedural morbidity and mortality, as well as the time to definite histopathologic diagnosis resulting in delays of treatment initiation, have to be considered. On the contrary, minimally invasive procedures, such as MRI, CSF cytology, and flow cytometry, still have limited value due to inferior specificity and sensitivity. Hence, novel diagnostic approaches, including mutation analyses (MYD88) in circulating tumor DNA (ctDNA) and the determination of microRNAs (miR-21, miR-19b, and miR-92) as well as cytokine levels (IL10 and IL6) in blood, cerebrospinal fluid (CSF), and vitreous fluid (VRF), move into the focus of investigation to facilitate the diagnosis of PCNSL. In this review, we outline the most promising approaches that are currently under clinical consideration.

POVERTY REDUCTION, UNEMPLOYMENT AND RURAL DEVELOPMENT; AFTERMATH OF COVID-19 PANDEMIC IN NIGERIA

2021 ◽  
Vol 9 (1) ◽  
pp. 36-49
Author(s):  
Oderinu Hassana ◽  
◽  
Kadir Mumini ◽  
Tijani Adebayo ◽  
Keyword(s):  
Economic Development ◽  
Rural Development ◽  
Rural Areas ◽  
Poverty Reduction ◽  
Design Method ◽  
Gear Up ◽  
Global Pandemic ◽  
High Level ◽  
Almost All ◽  
Self Administered Questionnaire

Nigeria has one of the countries whose experience of poverty and unemployment is on the high side makes this study to look into the effect of the economic lockdown during the global pandemic in the country, with the aim of making effort on how this effect can be translated into economic development. Survey research design method was adopted with self-administered questionnaire used to collect data. Findings revealed that in Nigeria COVID -19 outbreak effects was felt in almost all sectors and the aftermath greatly affected the country’s GDP and this adversely affect rural development in the country, which translated to a worrisome rate of poverty and unemployment. Hence, both individual and government have now seen that campaigning for economic diversification is not sufficient for economic development but rather a prompt swing into action by all is needed for sustainable development of rural areas to respond to the worrisome rate of unemployment and in turn high level of poverty caused by the COVID-19 lockdown in the country. It was recommended that government at all level as well as individuals and stakeholders should put in place actions that would gear up rural development and set policies at their various helms of affairs that would encourage economic participation of all citizens in all sector of the economy.

FOOD SAFETY KNOWLEDGE, ATTITUDES AND PRACTICES AMONG FEDERAL UNIVERSITY OF AGRICULTURE STUDENTS IN ABEOKUTA

2017 ◽  
Vol 15 (1) ◽  
pp. 94-107
Author(s):  
M O ADEGUNWA ◽  
M I SANUSI ◽  
H A BAKARE ◽  
A M OMEMU
Keyword(s):  
Food Safety ◽  
Contributing Factors ◽  
Safety Attitudes ◽  
Attitudes And Practices ◽  
Handling Practices ◽  
High Level ◽  
Almost All ◽  
The University ◽  
Safety Knowledge ◽  
Safety Attitude

Improper practices, poor attitudes and lack of knowledge by food handlers are contributing factors for the spread of foodborne diseases. Food safety knowledge is an important factor in improving food safety practices and subsequently food safety attitude. This study is aimed at exploring the food safety knowledge, practice and attitude of FUNAAB students. A self completed questionnaire was answered by randomly selected 270 students from each of the nine (9) colleges in the university and analyzed using SPSS software. The study revealed that almost all of the students had a high level of food safety awareness but the knowledge was not to large extent translated into practice. Majority of the students also had good food safety attitudes as many of them are willing to change their food handling behav-iour when they know they are incorrect (94.8%). The study further revealed similar level of food safety knowledge between the male and female. Despite the level of students’ knowledge, their choice of eating place on campus was determined by the price of the food. This study therefore concluded that good knowledge of food safety does not determine students’ safe handling practices and choice of eating place.Keywords: Food safety

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