Search results for: communal practice network

Authors: Breanna Wright, Peter Bragge

Abstract:

Diagnostic error rates in healthcare are approximately 10% of cases. Diagnostic errors can cause patient harm due to inappropriate, inadequate or delayed treatment, and such errors contribute heavily to medical liability claims globally. Therefore, addressing diagnostic error is a high priority. In most cases, diagnostic errors are the result of faulty information synthesis rather than lack of knowledge. Specifically, the majority of diagnostic errors involve cognitive factors, and in particular, cognitive biases. Emergency Departments are an environment with heightened risk of diagnostic error due to time and resource pressures, a frequently chaotic environment, and patients arriving undifferentiated and with minimal context. This project aimed to develop a behavioural, evidence-informed intervention to reduce diagnostic error in Emergency Departments through co-design with emergency physicians, insurers, researchers, hospital managers, citizens and consumer representatives. The Forum Process was utilised to address this aim. This involves convening a small (4 – 6 member) expert panel to guide a focused literature and practice review; convening of a 10 – 12 person citizens panel to gather perspectives of laypeople, including those affected by misdiagnoses; and a 18 – 22 person structured stakeholder dialogue bringing together representatives of the aforementioned stakeholder groups. The process not only provides in-depth analysis of the problem and associated behaviours, but brings together expertise and insight to facilitate identification of a behaviour change intervention. Informed by the literature and practice review, the Citizens Panel focused on eliciting the values and concerns of those affected or potentially affected by diagnostic error. Citizens were comfortable with diagnostic uncertainty if doctors were honest with them. They also emphasised the importance of open communication between doctors and patients and their families. Citizens expect more consistent standards across the state and better access for both patients and their doctors to patient health information to avoid time-consuming re-taking of long patient histories and medication regimes when re-presenting at Emergency Departments and to reduce the risk of unintentional omissions. The structured Stakeholder Dialogue focused on identifying a feasible behavioural intervention to review diagnoses in Emergency Departments. This needed to consider the role of cognitive bias in medical decision-making; contextual factors (in Victoria, there is a legislated 4-hour maximum time between ED triage and discharge / hospital admission); resource availability; and the need to ensure the intervention could work in large metropolitan as well as small rural and regional ED settings across Victoria. The identified behavioural intervention will be piloted in approximately ten hospital EDs across Victoria, Australia. This presentation will detail the findings of all review and consultation activities, describe the behavioural intervention developed and present results of the pilot trial.

Keywords: behavioural intervention, cognitive bias, decision-making, diagnostic error

Procedia PDF Downloads 128

Authors: Seyedmahdi Mousavihashemi

Abstract:

One of the most important subjects of interest in researches is 'improving' which result in various algorithms. In so many geometrical problems we are faced with target functions which should be optimized. In group practices, all the functions’ cooperation lead to convergence. In the study, the optimization algorithm of dense particles is used. Usage of the algorithm improves the given performance norms. The results reveal that usage of swarm algorithm for reinforced particles in designing state feedback improves the given performance norm and in optimized designing of multi-target state feedback controlling, the network will maintain its bearing structure. The results also show that PSO is usable for optimization of state feedback controllers.

Keywords: multi-objective, enhanced, feedback, optimization, algorithm, particle, design

Procedia PDF Downloads 500

Authors: Amanda Rebman

Abstract:

This paper challenges the criminal justice system’s traditional stance regarding prostitution. Historically, the acceptance and morality of prostitution within the United States has fluctuated depending upon the social attitudes of the era. Today, prostitutes are allegedly viewed as victims; however, they are treated like criminals throughout the criminal justice system and society. Dominant patriarchal narratives within the United States has resulted in woman lacking autonomy over their bodies and diminished their ability to choose their own career. Even though prostitutes are deemed victims, many times, they are convicted of crimes, a practice that results in further victimization. Utilizing the socialist feminist theory to understand these juxtaposing positions on whether to legalize prostitution facilitates a greater understanding of how patriarchal capitalist arrangements ensure the oppression of women throughout the criminal justice system. The legalization of prostitution will alleviate some of this oppression and ensure a more equal treatment of women in the criminal justice system and society at large.

Keywords: equality, feminist theory, prostitution, sex work

Procedia PDF Downloads 136

Authors: Elizabeth M. Seabrook, Nikki S. Rickard

Abstract:

Examining time-dependent measures of emotion such as variability, instability, and inertia, provide critical and complementary insights into mental health status. Observing changes in the pattern of emotional expression over time could act as a tool to identify meaningful shifts between psychological well- and ill-being. From a practical standpoint, however, examining emotion dynamics day-to-day is likely to be burdensome and invasive. Utilizing social media data as a facet of lived experience can provide real-world, temporally specific access to emotional expression. Emotional language on social media may provide accurate and sensitive insights into individual and community mental health and well-being, particularly with focus placed on the within-person dynamics of online emotion expression. The objective of the current study was to examine the dynamics of emotional expression on the social network platform Facebook for active users and their relationship with psychological well- and ill-being. It was expected that greater positive and negative emotion variability, instability, and inertia would be associated with poorer psychological well-being and greater depression symptoms. Data were collected using a smartphone app, MoodPrism, which delivered demographic questionnaires, psychological inventories assessing depression symptoms and psychological well-being, and collected the Status Updates of consenting participants. MoodPrism also delivered an experience sampling methodology where participants completed items assessing positive affect, negative affect, and arousal, daily for a 30-day period. The number of positive and negative words in posts was extracted and automatically collated by MoodPrism. The relative proportion of positive and negative words from the total words written in posts was then calculated. Preliminary analyses have been conducted with the data of 9 participants. While these analyses are underpowered due to sample size, they have revealed trends that greater variability in the emotion valence expressed in posts is positively associated with greater depression symptoms (r(9) = .56, p = .12), as is greater instability in emotion valence (r(9) = .58, p = .099). Full data analysis utilizing time-series techniques to explore the Facebook data set will be presented at the conference. Identifying the features of emotion dynamics (variability, instability, inertia) that are relevant to mental health in social media emotional expression is a fundamental step in creating automated screening tools for mental health that are temporally sensitive, unobtrusive, and accurate. The current findings show how monitoring basic social network characteristics over time can provide greater depth in predicting risk and changes in depression and positive well-being.

Keywords: emotion, experience sampling methods, mental health, social media

Procedia PDF Downloads 250

Authors: April Mattix Foster, Kathleen A. Ramos, Sarah Rich, Rebecca Eisenberg, Lisa Dornan

Abstract:

As the number of children from immigrant and refugee backgrounds in our schools continues to grow, the need to cultivate antiracist educators is crucial. This e-poster outlines the design of online university course modules, funded by the Longview Foundation, designed to support pre- and in-service educators in developing great awareness of, empathy for, and advocacy with immigrant and refugee students in the classroom. These modules guide educators in using children’s and adolescent literature that highlights the lived experiences of immigrant and refugee families, utilizing scaffolded reading and thinking protocols as a model for encouraging empathy and global competence in young learners. Educators reported several benefits of using the modules and curated literature, including greater awareness of the significance of diverse literature, deeper self-reflection and empathy, and stronger connections to classroom practice—ultimately benefiting both educators and their students.

Keywords: antiracist, children’s literature, global competence, empathy, self-reflection

Procedia PDF Downloads 25

Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

Abstract:

Due to the rapid growth in modern communication systems, fault tolerance and data security are two important issues in a secure transaction. During the transmission of data between the sender and receiver, errors may occur frequently. Therefore, the sender must re-transmit the data to the receiver in order to correct these errors, which makes the system very feeble. To improve the scalability of the scheme, we present a secure proxy signature scheme with fault tolerance over an efficient and secure authenticated key agreement protocol based on RSA system. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties.

Keywords: proxy signature, fault tolerance, rsa, key agreement protocol

Procedia PDF Downloads 286

Authors: Godfrey Omulo, Regina Birner, Karlheinz Koller, Thomas Daum

Abstract:

Conservation agriculture (CA) as a climate-resilient and sustainable practice have been carried out for over three decades in Zambia. However, its continued promotion and adoption has been predominantly on a small-scale basis. Despite the plethora of scholarship pointing to the positive benefits of CA in regard to enhanced yield, profitability, carbon sequestration and minimal environmental degradation, these have not stimulated commensurate agricultural extensification desired for Zambia. The objective of this study was to investigate the potential differences between mechanized conventional and conservation tillage practices on operation time, fuel consumption, labor costs, soil moisture retention, soil temperature and crop yield. An on-farm mechanized conservation agriculture (MCA) experiment arranged in a randomized complete block design with four replications was used. The research was conducted on a 15 ha of sandy loam rainfed land: soybeans on 7ha with plot dimensions of 24 m by 210 m and maize on 8ha with plot dimensions of 24 m by 250 m. The three tillage treatments were: residue burning followed by disc harrowing, ripping tillage and no-till. The crops were rotated in two subsequent seasons. All operations were done using a 60hp 2-wheel tractor, a disc harrow, a two-tine ripper and a two-row planter. Soil measurements and the agro-economic factors were recorded for two farming seasons. The season results showed that the yield of maize and soybeans under no-till and ripping tillage practices were not significantly different from the conventional burning and discing. But, there was a significant difference in soil moisture content between no-till (25.31SFU±2.77) and disced (11.91SFU±0.59) plots at depths from 10-60 cm. Soil temperature in no-till plots (24.59°C±0.91) was significantly lower compared to the disced plots (26.20°C±1.75) at the depths 15 cm and 45 cm. For maize, there was a significant difference in operation time between disc-harrowed (3.68hr/ha±1.27) and no-till (1.85hr/ha±0.04) plots, and a significant difference in cost of labor between disc-harrowed (45.45$/ha±19.56) and no-till (21.76$/ha) plots. There was no significant difference in fuel consumption between ripping and disc-harrowing and direct seeding. For soybeans, there was a significant difference in operation time between no-tillage (1.96hr/ha±0.31) and ripping (3.34hr/ha±0.53) and disc harrowing (3.30hr/ha±0.16). Further, fuel consumption and labor on no-till plots were significantly different from both the ripped and disc-harrowed plots. The high seed emergence percentage on maize disc-harrowed plot (93.75%±5.87) was not significantly different from ripping and no-till plots. Again, the high seed emergence percentage for the soybean ripped plot (93.75%±13.03) had no significant difference with discing and ripping. The results show that it is economically sound and timesaving to practice MCA and get viable yields compared to conventional farming. This research fills the gap on the potential of MCA in the context of Zambia and its profitability in incentivizing policymakers to invest in appropriate and sustainable machinery and implements for extensive agricultural production.

Keywords: climate-smart agriculture, labor cost, mechanized conservation agriculture, soil moisture, Zambia

Procedia PDF Downloads 148

Authors: Fred Mageto

Abstract:

A great number of children in mainstream schools across Kenya are currently living with emotional, behavioural difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioural difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Kenya find classroom behaviour problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with emotional and behavioural difficulties (EBD). The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: teachers, children, learning, emotional and behaviour difficulties

Procedia PDF Downloads 163

Authors: Mahmoud Samkan

Abstract:

Dispersed Generation (DG) is a promising solution to many power system problems such as voltage regulation and power loss. This paper proposes a heuristic two-step method to optimize the location and size of DG for reducing active power losses and, therefore, improve the voltage profile in radial distribution networks. In addition to a DG placed at the system load gravity center, this method consists in assigning a DG to each lateral of the network. After having determined the central DG placement, the location and size of each lateral DG are predetermined in the first step. The results are then refined in the second step. This method is tested for 33-bus system for 100% DG penetration. The results obtained are compared with those of other methods found in the literature.

Keywords: optimal location, optimal size, dispersed generation (DG), radial distribution networks, reducing losses

Procedia PDF Downloads 443

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

Abstract:

This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 141

Authors: Claudia Popescu, Adriana Mihaela Soaita

Abstract:

Within the EU accession process, Romania, as well as other CEE countries, have embarked on the post-1990 urbanization wave aiming to reduce the gaps between ‘older’ and ‘new’ EU member states. While post-socialist urban transitions have been extensively scrutinized, little is known about the developing trajectories of these new towns across the CEE region. To start addressing this knowledge gap, we wish to bring to the fore one of the most humble expressions of urbanism, that of the small, new towns of Romania. Despite rural-to-urban reclassification, urbanization levels have remained persistently low over the last three decades. In this context, it is timely and legitimate to ask about the prospects of new towns for a ‘successful’ socioeconomic performance within the urban network and avoidance of precarity and marginalization and adequate measure of place performance within the urban/settlement network and understanding the drivers that trigger towns’ socioeconomic performances. To answer these, we create a socioeconomic index of the place in order to compare the profile of the 60 new towns with large cities, old small towns and rural. We conceive ‘successful’ and ‘precarious’ performance in terms of a locality’s index value being above or below all small towns’ index average. Second, we performed logistic regression to interrogate the relevance of some key structural factors to the new towns’ socioeconomic performance (i.e. population size, urban history, regional location, connectivity and political determination of their local governments). Related to the first research question, our findings highlight the precarity of place as a long-standing condition of living and working in the new towns of Romania, particularly evident through our cross-comparative analysis across key category along the rural-urban continuum. We have substantiated the socioeconomic condition of precarity in rural places, with the new towns still maintaining features of ‘rurality’ rather than ‘urbanity’ - except a few successful satellites of economically striving large cities, particularly the country capital of Bucharest, which benefited from spillover effects. Related to our second research question, we found that the new towns of Romania have significantly higher odds of being characterized by precarity as a socioeconomic condition than all other small towns and urban places, but less so compared to the even more marginalized rural areas. Many new towns contain resource-dependent rural communities with a poor response to the context of change. Therefore, issues pertaining to local capacity building to adapt to the new urban environment should be addressed by the spatial planning policy. Our approach allowed us to bring to the fore the idea of precarity as a condition of whole localities. Thinking of precarity of place is important as it brings the whole institutional and political apparatus of spatial planning, urban and regional, into conversation with other causative or substantive axes of precarity developed in the literature. We recommend future research on the new towns in Romania and elsewhere.

Keywords: politics of fantasy, precarity of place, urbanization, Romania

Procedia PDF Downloads 15

Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

Abstract:

Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

Procedia PDF Downloads 158

Authors: Salima Tabti, Amel Djedouani., Djouhra Aggoun, Ismail Warad

Abstract:

The reaction of copper (II) with 4-hydroxy-3-[(2E)-3-(1H-indol-3-yl)prop-2-enoyl]-6-methyl-2H-pyran-2-one (HL) lead to a new complexe: Cu(L)₂(DMF)₂. The crystal structure of the Cu(L)₂(DMF)₂ complex have been determined by X-ray diffraction methods. The Cu(II) lying on an inversion centre is coordinated to six oxygen atoms forming an octahedral elongated. Additionally, the electrochemical behavior of the metal complexe was investigated by cyclic voltammetry at a glassy carbon electrode (GC) in CH₃CN solution, showing the quasi-reversible redox process ascribed to the reduction of the MII/MI couple. The X-ray single crystal structure data of the complex was matched excellently with the optimized monomer structure of the desired compound; Hirschfeld surface analysis supported the packed crystal lattice 3D network intermolecular forces.

Keywords: chalcones, cyclic voltametry, X-ray, Hirschfeld surface

Procedia PDF Downloads 65

Authors: Ndivhuho Tshikovhi

Abstract:

The debate about indigenous people throughout the world has been necessitated by different circumstances that indigenous communities continue to suffer. Indigenous people of the world suffer chronic diseases, poor education, high unemployment and slow economic developments. This paper contributes to the continuous debate by studying the common elements of indigenous entrepreneur of the world and that of the South African indigenous entrepreneur. The research objective of this paper is to understand what constitute an indigenous status in the South African context as opposed to the indigenous people of the world. Furthermore, the study will explore the indigenous status through their entrepreneurial engagements. The paper will adopt a secondary data research method, by utilising the literature on indigenous entrepreneurship practice and theory of indigenous entrepreneurship. The implications of this paper is to bring about an African indigenous entrepreneurship debate rooted from the correct circumstances rather than generalised definitions. Recommendations for future research will be outlined, together with further readings on circumstantial evidence that necessitate indigenous entrepreneurs status in South Africa.

Keywords: indigenous entrepreneur, indigenous, entrepreneurship, indigenous people, entrepreneurship development

Procedia PDF Downloads 477

Authors: Valentina Adduci

Abstract:

The developing research aims to define in general the criteria of environmental sustainability of rural buildings in Puglia and particularly in the manor farm. The main part of the study analyzes the relationship / dependence between the rural building and the landscape which, after many stratifications, results clearly identified and sometimes also characterized in a positive way. The location of the manor farm, in fact, is often conditioned by the infrastructural network and by the structure of the agricultural landscape. The manor farm, without the constraints due to the urban pattern’s density, was developed in accordance with a logical settlement that gives priority to the environmental aspects. These vernacular architectures are the most valuable example of how our ancestors have planned their dwellings according to nature. The 237 farms, analysis’ object, have been reported in cartography through the GIS system; a symbol has been assigned to each of them to identify the architectural typology and a different color for the historical period of construction. A datasheet template has been drawn up, and it has made possible a deeper understanding of each manor farm. This method provides a faster comparison of the most recurring characters in all the considered buildings, except for those farms which benefited from special geographical conditions, such as proximity to the road network or waterways. Below there are some of the most frequently constants derived from the statistical study of the examined buildings: southeast orientation of the main facade; placement of the sheep pen on the ground tilted and exposed to the south side; larger windowed surface on the south elevation; smaller windowed surface on the north elevation; presence of shielding vegetation near the more exposed elevations to the solar radiation; food storage’s rooms located on the ground floor or in the basement; animal shelter located in north side of the farm; presence of tanks and wells, sometimes combined with a very accurate channeling storm water system; thick layers of masonry walls, inside of which were often obtained hollow spaces to house stairwells or depots for the food storage; exclusive use of local building materials. The research aims to trace the ancient use of bioclimatic constructive techniques in the Apulian rural architecture and to define those that derive from an empirical knowledge and those that respond to an already encoded design. These constructive expedients are especially useful to obtain an effective passive cooling, to promote the natural ventilation and to built ingenious systems for the recovery and the preservation of rainwater and are still found in some of the manor farms analyzed, most of them are, today, in a serious state of neglect.

Keywords: bioclimatic devices, farmstead, rural landscape, sustainability

Procedia PDF Downloads 383

Authors: M. Azugama, P. Okoro Ugo Chigozie, A. O. Nnamocha

Abstract:

Emotional Intelligence constitutes powerful psychological forces that can strongly influence performance in behaviour, interaction and relationship management. Surprisingly how emotions are interpreted and employed in marketing of hospitality experience have had limited comprehension. Marketing of hospitality experiences have important emotional dimensions which the traditional marketing techniques tend to underplay. Guest and host relationship are challenged by mutual hospitableness obligations; suggesting that the commercial practice of delivering satisfactory guest experience has much to gain from traditional understanding of hospitality. By understanding the emotion-based hospitality transaction between guests and hosts, customers’ experiences can be delivered over and against competitor pressure. In this paper, marketing strategies and tactics in hospitality and tourism are principally concerned with adjusting each of the 6P & T elements (i.e. product, place, price and promotion; and adding people, processes and Time in service contexts), to provide a competitive offer (experience) to customers.

Keywords: Emotional intelligence, hospitality and tourism, relationship management, marketing

Procedia PDF Downloads 472

Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

Abstract:

Vast changes and developments achieved in information technology field in recent decades have made the review of different issues such as organizational structures unavoidable. Applying informative technologies such as internet and also vast use of computer and related networks have led to new organizational formations with a nature completely different from the traditional, great and bureaucratic ones; some common specifications of such organizations are transfer of the affairs out of the organization, benefiting from informative and communicative networks and centered-science workers. Such communicative necessities have led to network sciences development including grid computing. First, the grid computing was only to relate some sites for short – time and use their sources simultaneously, but now it has gone beyond such idea. In this article, the grid computing technology was examined, and at the same time, virtual organization concept was discussed.

Keywords: grid computing, virtual organizations, software engineering, organization

Procedia PDF Downloads 332

Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

Abstract:

Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

Procedia PDF Downloads 80

Authors: Xu LiYun, Briand Florent, Fan GuoLiang

Abstract:

The loop-layout design problem (LLDP) aims at optimizing the sequence of positioning of the machines around the cyclic production line. Traffic congestion is the usual criteria to minimize in this type of problem, i.e. the number of additional cycles spent by each part in the network until the completion of its required routing sequence of machines. This paper aims at applying several improvements mechanisms such as a positioned-based crossover operator for the Genetic Algorithm (GA) called a Two Points Crossover (TPC) and an offspring selection process. The performance of the improved GA is measured using well-known examples from literature and compared to other evolutionary algorithms. Good results show that GA can still be competitive for this type of problem against more recent evolutionary algorithms.

Keywords: crossover, genetic algorithm, layout design problem, loop-layout, manufacturing optimization

Procedia PDF Downloads 279

Authors: Jafaru Ibrahim, Tonga Agadi Danladi, Haruna Sani

Abstract:

Many telecommunications industry are looking for new ways to maximize their investment in communication networks while ensuring reliable and secure information transmission. There is a variety of communications medium solutions, the two must popularly in used are wireless technology and wired options, such as copper and fiber-optic cable. Wired network has proven its potential in the olden days but nowadays wireless communication has emerged as a robust and most intellect and preferred communication technique. Each of these types of communication medium has their advantages and disadvantages according to its technological characteristics. Wired and wireless networking has different hardware requirements, ranges, mobility, reliability and benefits. The aim of the paper is to compare both the Wired and Wireless medium on the basis of various parameters such as usability, cost, efficiency, flexibility, coverage, reliability, mobility, speed, security etc.

Keywords: cost, mobility, reliability, speed, security, wired, wireless

Procedia PDF Downloads 470

Authors: Ioannis Manikas

Abstract:

The increased consumer demand for environmentally friendly production and distribution practices and the stricter environmental regulations turned environmental aspects into important criteria in business decision-making. On the other hand, Food and Nutrition Security (FNS) has evolved dramatically during the last decades in theory and practice serving as a reference point for exchanging experiences among all agents involved in programs and projects to fostering policy and strategy development. Global pressures make it more important than ever to gain a better understanding of the contribution that agrifood businesses make to FNS and to examine ways to make them more resilient in an increasingly globalized and uncertain world. This study extends the standard three-dimensional model of sustainability to include two more dimensions: A technological dimension and a policy/political dimension. Apart from the economic, environmental and social dimensions regularly used in sustainability literature, the extended model will accurately represent the measures and policies addressing food and nutrition security.

Keywords: food and nutrition security, sustainability, food safety, resilience

Procedia PDF Downloads 339

Authors: Shripad Kulkarni

Abstract:

Plant disease is an impairment of the normal state of a plant that interrupts or modifies its vital functions. Disease occurs on different parts of plants and cause heavy losses. Diagnosis of Problem is very important before planning any management practice and this can be done based on appearance of the crop, examination of the root and examination of the soil. There are various types of diseases such as biotic (transmissible) which accounts for ~30% whereas , abiotic (not transmissible) diseases are the major one with ~70% incidence. Plant diseases caused by different groups of organism’s belonging fungi, bacteria, viruses, nematodes and few others have remained important in causing significant losses in different crops indicating the urgent need of their integrated management. Various factors favor disease development and different steps and methods are involved in management of diseases under protected condition. Management of diseases through botanicals and bioagents by modifying root and aerial environment, vector management along with care to be taken while managing the disease are analysed.

Keywords: organic production system, diseases, bioagents and polyhouse, agriculture

Procedia PDF Downloads 406

Authors: Erika Ruíz, Luis Amaya, Diego Carreño

Abstract:

The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Keywords: location routing problem, logistic, mining collection, model

Procedia PDF Downloads 217

Authors: Melaku Takele Abate, Abbi Lemma Wodajo, Adula Bekele Hunde

Abstract:

This study aimed at exploring mathematics teachers' reactions, learning, school leaders’ support, and use of the Lesson Study for Transformative Assessment (LSforTA) program ideas in practice. The LSforTA program was new, and therefore, a local and grounded approach was needed to examine teachers’ knowledge and skills acquired using LSforTA. So, a design-based research approach was selected to evaluate and refine the LSforTA approach. The results showed that LSforTA increased teachers' knowledge and use of different levels of mathematics assessment tasks. The program positively affected teachers' practices of transformative assessment and enhanced their knowledge and skills in assessing students in a transformative way. The paper concludes how the LSforTA procedures were adapted in response to this evaluation and provides suggestions for future development and research.

Keywords: classroom assessment, feedback practices, lesson study, mathematics, design-based research

Procedia PDF Downloads 55

Authors: Seunghee Park, Junkyeong Kim, Eun-Seok Shin, Sang-Hun Han

Abstract:

In this study, two kinds of nondestructive evaluation (NDE) techniques (rebound hardness and ultrasonic pulse velocity methods) are investigated for the effective maintenance of underwater concrete structures. A new methodology to estimate the underwater concrete strengths more effectively, named “artificial neural network (ANN) – based concrete strength estimation with the combination of rebound hardness and ultrasonic pulse velocity methods” is proposed and verified throughout a series of experimental works.

Keywords: underwater concrete, rebound hardness, Schmidt hammer, ultrasonic pulse velocity, ultrasonic sensor, artificial neural networks, ANN

Procedia PDF Downloads 532

Authors: Ali H. Daraji, Ye Jianqiao

Abstract:

The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.

Keywords: energy harvesting, optimisation, sensor, wing

Procedia PDF Downloads 301

Authors: Marcos Silva Tavares, Jamile Raquel Regazzo, Edson José de Souza Sardinha, Murilo Mesquita Baesso

Abstract:

Common beans are a widely cultivated and consumed legume globally, serving as a staple food for humans, especially in developing countries, due to their nutritional characteristics. Nitrogen (N) is the most limiting nutrient for productivity, and foliar analysis is crucial to ensure balanced nitrogen fertilization. Excessive N applications can cause, either isolated or cumulatively, soil and water contamination, plant toxicity, and increase their susceptibility to diseases and pests. However, the quantification of N using conventional methods is time-consuming and costly, demanding new technologies to optimize the adequate supply of N to plants. Thus, it becomes necessary to establish constant monitoring of the foliar content of this macronutrient in plants, mainly at the V4 stage, aiming at precision management of nitrogen fertilization. In this work, the objective was to evaluate the performance of a deep learning model, Resnet-50, in the classification of foliar nitrogen in common beans using RGB images. The BRS Estilo cultivar was sown in a greenhouse in a completely randomized design with four nitrogen doses (T1 = 0 kg N ha-1, T2 = 25 kg N ha-1, T3 = 75 kg N ha-1, and T4 = 100 kg N ha-1) and 12 replications. Pots with 5L capacity were used with a substrate composed of 43% soil (Neossolo Quartzarênico), 28.5% crushed sugarcane bagasse, and 28.5% cured bovine manure. The water supply of the plants was done with 5mm of water per day. The application of urea (45% N) and the acquisition of images occurred 14 and 32 days after sowing, respectively. A code developed in Matlab© R2022b was used to cut the original images into smaller blocks, originating an image bank composed of 4 folders representing the four classes and labeled as T1, T2, T3, and T4, each containing 500 images of 224x224 pixels obtained from plants cultivated under different N doses. The Matlab© R2022b software was used for the implementation and performance analysis of the model. The evaluation of the efficiency was done by a set of metrics, including accuracy (AC), F1-score (F1), specificity (SP), area under the curve (AUC), and precision (P). The ResNet-50 showed high performance in the classification of foliar N levels in common beans, with AC values of 85.6%. The F1 for classes T1, T2, T3, and T4 was 76, 72, 74, and 77%, respectively. This study revealed that the use of RGB images combined with deep learning can be a promising alternative to slow laboratory analyses, capable of optimizing the estimation of foliar N. This can allow rapid intervention by the producer to achieve higher productivity and less fertilizer waste. Future approaches are encouraged to develop mobile devices capable of handling images using deep learning for the classification of the nutritional status of plants in situ.

Keywords: convolutional neural network, residual network 50, nutritional status, artificial intelligence

Procedia PDF Downloads 19

Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

Abstract:

The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

Procedia PDF Downloads 369

Authors: Farhan Ali

Abstract:

Use of wastewater for growing vegetables has become a common practice around big cities. Wastewater contains organic material and inorganic elements essential for plant growth but also contain heavy metals, which may be lethal for animals and humans if their concentration increases than permissible limit. To monitor this situation, a survey was conducted to ascertain the addition of heavy metals into agricultural fields through wastewater irrigation and their translocation in to the edible parts of the vegetables. The study highlighted that there is a large accumulation of heavy metals in the soil, which is irrigated with industrial wastewater Laden and people consume vegetables grown in soil irrigated with sewage water to absorb a large amount of these metals. This accumulation of heavy metals in food cause possible health risks for the consumer. Regular monitoring of the levels of pathogens and heavy metals from the waste water drain which effluent are used for growing vegetables and other foodstuffs is essential to monitor excessive accumulation of these metals in the food chain.

Keywords: pathogens, wastewater, concentration, effluent

Procedia PDF Downloads 297

Authors: Raghad A. Altowairgi

Abstract:

With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

Procedia PDF Downloads 130